Compare commits

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8 Commits

Author SHA1 Message Date
Marco Beretta
c27e8566fb Merge branch 'main' into re-add-download-audio 2024-07-30 05:36:43 -04:00
Marco Beretta
511f1336da Merge branch 'main' into re-add-download-audio 2024-07-17 18:38:28 +02:00
Marco Beretta
25ea3b8e98 revert lint 2 2024-07-16 17:18:15 +02:00
Marco Beretta
b1ec67ea42 revert lint 2024-07-16 17:17:43 +02:00
Marco Beretta
f1bb5fa4c5 revert back translation changes 2024-07-15 18:54:44 +02:00
Marco Beretta
44d8596872 fix: removed title button 2024-07-15 18:48:21 +02:00
Marco Beretta
32d84c85ea Merge branch 'main' into re-add-download-audio 2024-07-15 18:37:04 +02:00
Marco Beretta
d839e4661c feat: download audio file support 2024-06-18 16:24:37 +02:00
804 changed files with 47728 additions and 56637 deletions

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@@ -1,3 +1,5 @@
version: "3.8"
services:
app:
build:

View File

@@ -65,7 +65,6 @@ PROXY=
# ANYSCALE_API_KEY=
# APIPIE_API_KEY=
# COHERE_API_KEY=
# DEEPSEEK_API_KEY=
# DATABRICKS_API_KEY=
# FIREWORKS_API_KEY=
# GROQ_API_KEY=
@@ -75,20 +74,20 @@ PROXY=
# PERPLEXITY_API_KEY=
# SHUTTLEAI_API_KEY=
# TOGETHERAI_API_KEY=
# UNIFY_API_KEY=
#============#
# Anthropic #
#============#
ANTHROPIC_API_KEY=user_provided
# ANTHROPIC_MODELS=claude-3-5-sonnet-20241022,claude-3-5-sonnet-latest,claude-3-5-sonnet-20240620,claude-3-opus-20240229,claude-3-sonnet-20240229,claude-3-haiku-20240307,claude-2.1,claude-2,claude-1.2,claude-1,claude-1-100k,claude-instant-1,claude-instant-1-100k
# ANTHROPIC_MODELS=claude-3-5-sonnet-20240620,claude-3-opus-20240229,claude-3-sonnet-20240229,claude-3-haiku-20240307,claude-2.1,claude-2,claude-1.2,claude-1,claude-1-100k,claude-instant-1,claude-instant-1-100k
# ANTHROPIC_REVERSE_PROXY=
#============#
# Azure #
#============#
# Note: these variables are DEPRECATED
# Use the `librechat.yaml` configuration for `azureOpenAI` instead
# You may also continue to use them if you opt out of using the `librechat.yaml` configuration
@@ -111,26 +110,6 @@ ANTHROPIC_API_KEY=user_provided
BINGAI_TOKEN=user_provided
# BINGAI_HOST=https://cn.bing.com
#=================#
# AWS Bedrock #
#=================#
# BEDROCK_AWS_DEFAULT_REGION=us-east-1 # A default region must be provided
# BEDROCK_AWS_ACCESS_KEY_ID=someAccessKey
# BEDROCK_AWS_SECRET_ACCESS_KEY=someSecretAccessKey
# Note: This example list is not meant to be exhaustive. If omitted, all known, supported model IDs will be included for you.
# BEDROCK_AWS_MODELS=anthropic.claude-3-5-sonnet-20240620-v1:0,meta.llama3-1-8b-instruct-v1:0
# See all Bedrock model IDs here: https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html#model-ids-arns
# Notes on specific models:
# The following models are not support due to not supporting streaming:
# ai21.j2-mid-v1
# The following models are not support due to not supporting conversation history:
# ai21.j2-ultra-v1, cohere.command-text-v14, cohere.command-light-text-v14
#============#
# Google #
#============#
@@ -138,7 +117,7 @@ BINGAI_TOKEN=user_provided
GOOGLE_KEY=user_provided
# GOOGLE_REVERSE_PROXY=
# Gemini API (AI Studio)
# Gemini API
# GOOGLE_MODELS=gemini-1.5-flash-latest,gemini-1.0-pro,gemini-1.0-pro-001,gemini-1.0-pro-latest,gemini-1.0-pro-vision-latest,gemini-1.5-pro-latest,gemini-pro,gemini-pro-vision
# Vertex AI
@@ -146,32 +125,26 @@ GOOGLE_KEY=user_provided
# GOOGLE_TITLE_MODEL=gemini-pro
# GOOGLE_LOC=us-central1
# Google Safety Settings
# NOTE: These settings apply to both Vertex AI and Gemini API (AI Studio)
# Google Gemini Safety Settings
# NOTE (Vertex AI): You do not have access to the BLOCK_NONE setting by default.
# To use this restricted HarmBlockThreshold setting, you will need to either:
#
# For Vertex AI:
# To use the BLOCK_NONE setting, you need either:
# (a) Access through an allowlist via your Google account team, or
# (b) Switch to monthly invoiced billing: https://cloud.google.com/billing/docs/how-to/invoiced-billing
#
# For Gemini API (AI Studio):
# BLOCK_NONE is available by default, no special account requirements.
#
# Available options: BLOCK_NONE, BLOCK_ONLY_HIGH, BLOCK_MEDIUM_AND_ABOVE, BLOCK_LOW_AND_ABOVE
# (a) Get access through an allowlist via your Google account team
# (b) Switch your account type to monthly invoiced billing following this instruction:
# https://cloud.google.com/billing/docs/how-to/invoiced-billing
#
# GOOGLE_SAFETY_SEXUALLY_EXPLICIT=BLOCK_ONLY_HIGH
# GOOGLE_SAFETY_HATE_SPEECH=BLOCK_ONLY_HIGH
# GOOGLE_SAFETY_HARASSMENT=BLOCK_ONLY_HIGH
# GOOGLE_SAFETY_DANGEROUS_CONTENT=BLOCK_ONLY_HIGH
#============#
# OpenAI #
#============#
OPENAI_API_KEY=user_provided
# OPENAI_MODELS=gpt-4o,chatgpt-4o-latest,gpt-4o-mini,gpt-3.5-turbo-0125,gpt-3.5-turbo-0301,gpt-3.5-turbo,gpt-4,gpt-4-0613,gpt-4-vision-preview,gpt-3.5-turbo-0613,gpt-3.5-turbo-16k-0613,gpt-4-0125-preview,gpt-4-turbo-preview,gpt-4-1106-preview,gpt-3.5-turbo-1106,gpt-3.5-turbo-instruct,gpt-3.5-turbo-instruct-0914,gpt-3.5-turbo-16k
# OPENAI_MODELS=gpt-4o,gpt-4o-mini,gpt-3.5-turbo-0125,gpt-3.5-turbo-0301,gpt-3.5-turbo,gpt-4,gpt-4-0613,gpt-4-vision-preview,gpt-3.5-turbo-0613,gpt-3.5-turbo-16k-0613,gpt-4-0125-preview,gpt-4-turbo-preview,gpt-4-1106-preview,gpt-3.5-turbo-1106,gpt-3.5-turbo-instruct,gpt-3.5-turbo-instruct-0914,gpt-3.5-turbo-16k
DEBUG_OPENAI=false
@@ -288,6 +261,7 @@ MEILI_NO_ANALYTICS=true
MEILI_HOST=http://0.0.0.0:7700
MEILI_MASTER_KEY=DrhYf7zENyR6AlUCKmnz0eYASOQdl6zxH7s7MKFSfFCt
#==================================================#
# Speech to Text & Text to Speech #
#==================================================#
@@ -295,16 +269,6 @@ MEILI_MASTER_KEY=DrhYf7zENyR6AlUCKmnz0eYASOQdl6zxH7s7MKFSfFCt
STT_API_KEY=
TTS_API_KEY=
#==================================================#
# RAG #
#==================================================#
# More info: https://www.librechat.ai/docs/configuration/rag_api
# RAG_OPENAI_BASEURL=
# RAG_OPENAI_API_KEY=
# EMBEDDINGS_PROVIDER=openai
# EMBEDDINGS_MODEL=text-embedding-3-small
#===================================================#
# User System #
#===================================================#
@@ -414,7 +378,6 @@ LDAP_CA_CERT_PATH=
# LDAP_LOGIN_USES_USERNAME=true
# LDAP_ID=
# LDAP_USERNAME=
# LDAP_EMAIL=
# LDAP_FULL_NAME=
#========================#
@@ -450,18 +413,6 @@ FIREBASE_APP_ID=
ALLOW_SHARED_LINKS=true
ALLOW_SHARED_LINKS_PUBLIC=true
#==============================#
# Static File Cache Control #
#==============================#
# Leave commented out to use defaults: 1 day (86400 seconds) for s-maxage and 2 days (172800 seconds) for max-age
# NODE_ENV must be set to production for these to take effect
# STATIC_CACHE_MAX_AGE=172800
# STATIC_CACHE_S_MAX_AGE=86400
# If you have another service in front of your LibreChat doing compression, disable express based compression here
# DISABLE_COMPRESSION=true
#===================================================#
# UI #
#===================================================#

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@@ -12,7 +12,6 @@ module.exports = {
'plugin:react-hooks/recommended',
'plugin:jest/recommended',
'prettier',
'plugin:jsx-a11y/recommended',
],
ignorePatterns: [
'client/dist/**/*',
@@ -33,7 +32,7 @@ module.exports = {
jsx: true,
},
},
plugins: ['react', 'react-hooks', '@typescript-eslint', 'import', 'jsx-a11y'],
plugins: ['react', 'react-hooks', '@typescript-eslint', 'import'],
rules: {
'react/react-in-jsx-scope': 'off',
'@typescript-eslint/ban-ts-comment': ['error', { 'ts-ignore': 'allow' }],
@@ -66,7 +65,6 @@ module.exports = {
'no-restricted-syntax': 'off',
'react/prop-types': ['off'],
'react/display-name': ['off'],
'no-nested-ternary': 'error',
'no-unused-vars': ['error', { varsIgnorePattern: '^_' }],
quotes: ['error', 'single'],
},
@@ -120,8 +118,6 @@ module.exports = {
],
rules: {
'@typescript-eslint/no-explicit-any': 'error',
'@typescript-eslint/no-unnecessary-condition': 'warn',
'@typescript-eslint/strict-boolean-expressions': 'warn',
},
},
{

47
.github/dependabot.yml vendored Normal file
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@@ -0,0 +1,47 @@
# To get started with Dependabot version updates, you'll need to specify which
# package ecosystems to update and where the package manifests are located.
# Please see the documentation for all configuration options:
# https://docs.github.com/github/administering-a-repository/configuration-options-for-dependency-updates
version: 2
updates:
- package-ecosystem: "npm" # See documentation for possible values
directory: "/api" # Location of package manifests
target-branch: "dev"
versioning-strategy: increase-if-necessary
schedule:
interval: "weekly"
allow:
# Allow both direct and indirect updates for all packages
- dependency-type: "all"
commit-message:
prefix: "npm api prod"
prefix-development: "npm api dev"
include: "scope"
- package-ecosystem: "npm" # See documentation for possible values
directory: "/client" # Location of package manifests
target-branch: "dev"
versioning-strategy: increase-if-necessary
schedule:
interval: "weekly"
allow:
# Allow both direct and indirect updates for all packages
- dependency-type: "all"
commit-message:
prefix: "npm client prod"
prefix-development: "npm client dev"
include: "scope"
- package-ecosystem: "npm" # See documentation for possible values
directory: "/" # Location of package manifests
target-branch: "dev"
versioning-strategy: increase-if-necessary
schedule:
interval: "weekly"
allow:
# Allow both direct and indirect updates for all packages
- dependency-type: "all"
commit-message:
prefix: "npm all prod"
prefix-development: "npm all dev"
include: "scope"

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@@ -1,26 +0,0 @@
name: Lint for accessibility issues
on:
pull_request:
paths:
- 'client/src/**'
workflow_dispatch:
inputs:
run_workflow:
description: 'Set to true to run this workflow'
required: true
default: 'false'
jobs:
axe-linter:
runs-on: ubuntu-latest
if: >
(github.event_name == 'pull_request' && github.event.pull_request.head.repo.full_name == 'danny-avila/LibreChat') ||
(github.event_name == 'workflow_dispatch' && github.event.inputs.run_workflow == 'true')
steps:
- uses: actions/checkout@v4
- uses: dequelabs/axe-linter-action@v1
with:
api_key: ${{ secrets.AXE_LINTER_API_KEY }}
github_token: ${{ secrets.GITHUB_TOKEN }}

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@@ -1,41 +0,0 @@
name: Update Test Server
on:
workflow_run:
workflows: ["Docker Dev Images Build"]
types:
- completed
workflow_dispatch:
jobs:
deploy:
runs-on: ubuntu-latest
if: |
github.repository == 'danny-avila/LibreChat' &&
(github.event_name == 'workflow_dispatch' || github.event.workflow_run.conclusion == 'success')
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Install SSH Key
uses: shimataro/ssh-key-action@v2
with:
key: ${{ secrets.DO_SSH_PRIVATE_KEY }}
known_hosts: ${{ secrets.DO_KNOWN_HOSTS }}
- name: Run update script on DigitalOcean Droplet
env:
DO_HOST: ${{ secrets.DO_HOST }}
DO_USER: ${{ secrets.DO_USER }}
run: |
ssh -o StrictHostKeyChecking=no ${DO_USER}@${DO_HOST} << EOF
sudo -i -u danny bash << EEOF
cd ~/LibreChat && \
git fetch origin main && \
npm run update:deployed && \
git checkout do-deploy && \
git rebase main && \
npm run start:deployed && \
echo "Update completed. Application should be running now."
EEOF
EOF

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@@ -53,4 +53,4 @@ jobs:
- name: Run unit tests
run: npm run test:ci --verbose
working-directory: client
working-directory: client

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@@ -1,33 +0,0 @@
name: Build Helm Charts on Tag
# The workflow is triggered when a tag is pushed
on:
push:
tags:
- "*"
jobs:
release:
permissions:
contents: write
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Configure Git
run: |
git config user.name "$GITHUB_ACTOR"
git config user.email "$GITHUB_ACTOR@users.noreply.github.com"
- name: Install Helm
uses: azure/setup-helm@v4
env:
GITHUB_TOKEN: "${{ secrets.GITHUB_TOKEN }}"
- name: Run chart-releaser
uses: helm/chart-releaser-action@v1.6.0
env:
CR_TOKEN: "${{ secrets.GITHUB_TOKEN }}"

16
.vscode/launch.json vendored
View File

@@ -1,16 +0,0 @@
{
"version": "0.2.0",
"configurations": [
{
"type": "node",
"request": "launch",
"name": "Launch LibreChat (debug)",
"skipFiles": ["<node_internals>/**"],
"program": "${workspaceFolder}/api/server/index.js",
"env": {
"NODE_ENV": "production"
},
"console": "integratedTerminal"
}
]
}

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@@ -1,4 +1,4 @@
# v0.7.5
# v0.7.3
# Base node image
FROM node:20-alpine AS node

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@@ -1,44 +1,43 @@
# Dockerfile.multi
# v0.7.5
# v0.7.3
# Base for all builds
# Build API, Client and Data Provider
FROM node:20-alpine AS base
WORKDIR /app
RUN apk --no-cache add curl
RUN npm config set fetch-retry-maxtimeout 600000 && \
npm config set fetch-retries 5 && \
npm config set fetch-retry-mintimeout 15000
COPY package*.json ./
COPY packages/data-provider/package*.json ./packages/data-provider/
COPY client/package*.json ./client/
COPY api/package*.json ./api/
RUN npm ci
# Build data-provider
FROM base AS data-provider-build
WORKDIR /app/packages/data-provider
COPY packages/data-provider ./
COPY ./packages/data-provider ./
RUN npm install; npm cache clean --force
RUN npm run build
RUN npm prune --production
# Client build
# React client build
FROM base AS client-build
WORKDIR /app/client
COPY client ./
COPY --from=data-provider-build /app/packages/data-provider/dist /app/packages/data-provider/dist
COPY ./client/package*.json ./
# Copy data-provider to client's node_modules
COPY --from=data-provider-build /app/packages/data-provider/ /app/client/node_modules/librechat-data-provider/
RUN npm install; npm cache clean --force
COPY ./client/ ./
ENV NODE_OPTIONS="--max-old-space-size=2048"
RUN npm run build
RUN npm prune --production
# API setup (including client dist)
# Node API setup
FROM base AS api-build
WORKDIR /app
COPY api ./api
COPY config ./config
COPY --from=data-provider-build /app/packages/data-provider/dist ./packages/data-provider/dist
COPY --from=client-build /app/client/dist ./client/dist
WORKDIR /app/api
RUN npm prune --production
COPY api/package*.json ./
COPY api/ ./
# Copy helper scripts
COPY config/ ./
# Copy data-provider to API's node_modules
COPY --from=data-provider-build /app/packages/data-provider/ /app/api/node_modules/librechat-data-provider/
RUN npm install --include prod; npm cache clean --force
COPY --from=client-build /app/client/dist /app/client/dist
EXPOSE 3080
ENV HOST=0.0.0.0
CMD ["node", "server/index.js"]
# Nginx setup
FROM nginx:1.21.1-alpine AS prod-stage
COPY ./client/nginx.conf /etc/nginx/conf.d/default.conf
CMD ["nginx", "-g", "daemon off;"]

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@@ -42,11 +42,9 @@
- 🖥️ UI matching ChatGPT, including Dark mode, Streaming, and latest updates
- 🤖 AI model selection:
- Anthropic (Claude), AWS Bedrock, OpenAI, Azure OpenAI, BingAI, ChatGPT, Google Vertex AI, Plugins, Assistants API (including Azure Assistants)
- OpenAI, Azure OpenAI, BingAI, ChatGPT, Google Vertex AI, Anthropic (Claude), Plugins, Assistants API (including Azure Assistants)
- ✅ Compatible across both **[Remote & Local AI services](https://www.librechat.ai/docs/configuration/librechat_yaml/ai_endpoints):**
- groq, Ollama, Cohere, Mistral AI, Apple MLX, koboldcpp, OpenRouter, together.ai, Perplexity, ShuttleAI, and more
- 🪄 Generative UI with **[Code Artifacts](https://youtu.be/GfTj7O4gmd0?si=WJbdnemZpJzBrJo3)**
- Create React, HTML code, and Mermaid diagrams right in chat
- 💾 Create, Save, & Share Custom Presets
- 🔀 Switch between AI Endpoints and Presets, mid-chat
- 🔄 Edit, Resubmit, and Continue Messages with Conversation branching
@@ -83,7 +81,7 @@ LibreChat brings together the future of assistant AIs with the revolutionary tec
With LibreChat, you no longer need to opt for ChatGPT Plus and can instead use free or pay-per-call APIs. We welcome contributions, cloning, and forking to enhance the capabilities of this advanced chatbot platform.
[![Watch the video](https://raw.githubusercontent.com/LibreChat-AI/librechat.ai/main/public/images/changelog/v0.7.4.png)](https://www.youtube.com/watch?v=cvosUxogdpI)
[![Watch the video](https://img.youtube.com/vi/bSVHEbVPNl4/maxresdefault.jpg)](https://www.youtube.com/watch?v=bSVHEbVPNl4)
Click on the thumbnail to open the video☝
---

View File

@@ -12,13 +12,12 @@ const { encodeAndFormat } = require('~/server/services/Files/images/encode');
const {
truncateText,
formatMessage,
addCacheControl,
titleFunctionPrompt,
parseParamFromPrompt,
createContextHandlers,
} = require('./prompts');
const { getModelMaxTokens, getModelMaxOutputTokens, matchModelName } = require('~/utils');
const { spendTokens, spendStructuredTokens } = require('~/models/spendTokens');
const spendTokens = require('~/models/spendTokens');
const { getModelMaxTokens } = require('~/utils');
const { sleep } = require('~/server/utils');
const BaseClient = require('./BaseClient');
const { logger } = require('~/config');
@@ -33,7 +32,6 @@ function delayBeforeRetry(attempts, baseDelay = 1000) {
return new Promise((resolve) => setTimeout(resolve, baseDelay * attempts));
}
const tokenEventTypes = new Set(['message_start', 'message_delta']);
const { legacy } = anthropicSettings;
class AnthropicClient extends BaseClient {
@@ -46,30 +44,6 @@ class AnthropicClient extends BaseClient {
? options.contextStrategy.toLowerCase()
: 'discard';
this.setOptions(options);
/** @type {string | undefined} */
this.systemMessage;
/** @type {AnthropicMessageStartEvent| undefined} */
this.message_start;
/** @type {AnthropicMessageDeltaEvent| undefined} */
this.message_delta;
/** Whether the model is part of the Claude 3 Family
* @type {boolean} */
this.isClaude3;
/** Whether to use Messages API or Completions API
* @type {boolean} */
this.useMessages;
/** Whether or not the model is limited to the legacy amount of output tokens
* @type {boolean} */
this.isLegacyOutput;
/** Whether or not the model supports Prompt Caching
* @type {boolean} */
this.supportsCacheControl;
/** The key for the usage object's input tokens
* @type {string} */
this.inputTokensKey = 'input_tokens';
/** The key for the usage object's output tokens
* @type {string} */
this.outputTokensKey = 'output_tokens';
}
setOptions(options) {
@@ -89,19 +63,14 @@ class AnthropicClient extends BaseClient {
this.options = options;
}
this.modelOptions = Object.assign(
{
model: anthropicSettings.model.default,
},
this.modelOptions,
this.options.modelOptions,
);
const modelOptions = this.options.modelOptions || {};
this.modelOptions = {
...modelOptions,
model: modelOptions.model || anthropicSettings.model.default,
};
const modelMatch = matchModelName(this.modelOptions.model, EModelEndpoint.anthropic);
this.isClaude3 = modelMatch.startsWith('claude-3');
this.isLegacyOutput = !modelMatch.startsWith('claude-3-5-sonnet');
this.supportsCacheControl =
this.options.promptCache && this.checkPromptCacheSupport(modelMatch);
this.isClaude3 = this.modelOptions.model.includes('claude-3');
this.isLegacyOutput = !this.modelOptions.model.includes('claude-3-5-sonnet');
if (
this.isLegacyOutput &&
@@ -120,14 +89,7 @@ class AnthropicClient extends BaseClient {
this.options.maxContextTokens ??
getModelMaxTokens(this.modelOptions.model, EModelEndpoint.anthropic) ??
100000;
this.maxResponseTokens =
this.modelOptions.maxOutputTokens ??
getModelMaxOutputTokens(
this.modelOptions.model,
this.options.endpointType ?? this.options.endpoint,
this.options.endpointTokenConfig,
) ??
1500;
this.maxResponseTokens = this.modelOptions.maxOutputTokens || 1500;
this.maxPromptTokens =
this.options.maxPromptTokens || this.maxContextTokens - this.maxResponseTokens;
@@ -151,6 +113,17 @@ class AnthropicClient extends BaseClient {
this.endToken = '';
this.gptEncoder = this.constructor.getTokenizer('cl100k_base');
if (!this.modelOptions.stop) {
const stopTokens = [this.startToken];
if (this.endToken && this.endToken !== this.startToken) {
stopTokens.push(this.endToken);
}
stopTokens.push(`${this.userLabel}`);
stopTokens.push('<|diff_marker|>');
this.modelOptions.stop = stopTokens;
}
return this;
}
@@ -174,74 +147,19 @@ class AnthropicClient extends BaseClient {
options.baseURL = this.options.reverseProxyUrl;
}
if (
this.supportsCacheControl &&
requestOptions?.model &&
requestOptions.model.includes('claude-3-5-sonnet')
) {
if (requestOptions?.model && requestOptions.model.includes('claude-3-5-sonnet')) {
options.defaultHeaders = {
'anthropic-beta': 'max-tokens-3-5-sonnet-2024-07-15,prompt-caching-2024-07-31',
};
} else if (this.supportsCacheControl) {
options.defaultHeaders = {
'anthropic-beta': 'prompt-caching-2024-07-31',
'anthropic-beta': 'max-tokens-3-5-sonnet-2024-07-15',
};
}
return new Anthropic(options);
}
/**
* Get stream usage as returned by this client's API response.
* @returns {AnthropicStreamUsage} The stream usage object.
*/
getStreamUsage() {
const inputUsage = this.message_start?.message?.usage ?? {};
const outputUsage = this.message_delta?.usage ?? {};
return Object.assign({}, inputUsage, outputUsage);
}
/**
* Calculates the correct token count for the current user message based on the token count map and API usage.
* Edge case: If the calculation results in a negative value, it returns the original estimate.
* If revisiting a conversation with a chat history entirely composed of token estimates,
* the cumulative token count going forward should become more accurate as the conversation progresses.
* @param {Object} params - The parameters for the calculation.
* @param {Record<string, number>} params.tokenCountMap - A map of message IDs to their token counts.
* @param {string} params.currentMessageId - The ID of the current message to calculate.
* @param {AnthropicStreamUsage} params.usage - The usage object returned by the API.
* @returns {number} The correct token count for the current user message.
*/
calculateCurrentTokenCount({ tokenCountMap, currentMessageId, usage }) {
const originalEstimate = tokenCountMap[currentMessageId] || 0;
if (!usage || typeof usage.input_tokens !== 'number') {
return originalEstimate;
}
tokenCountMap[currentMessageId] = 0;
const totalTokensFromMap = Object.values(tokenCountMap).reduce((sum, count) => {
const numCount = Number(count);
return sum + (isNaN(numCount) ? 0 : numCount);
}, 0);
const totalInputTokens =
(usage.input_tokens ?? 0) +
(usage.cache_creation_input_tokens ?? 0) +
(usage.cache_read_input_tokens ?? 0);
const currentMessageTokens = totalInputTokens - totalTokensFromMap;
return currentMessageTokens > 0 ? currentMessageTokens : originalEstimate;
}
/**
* Get Token Count for LibreChat Message
* @param {TMessage} responseMessage
* @returns {number}
*/
getTokenCountForResponse(responseMessage) {
getTokenCountForResponse(response) {
return this.getTokenCountForMessage({
role: 'assistant',
content: responseMessage.text,
content: response.text,
});
}
@@ -294,38 +212,7 @@ class AnthropicClient extends BaseClient {
return files;
}
/**
* @param {object} params
* @param {number} params.promptTokens
* @param {number} params.completionTokens
* @param {AnthropicStreamUsage} [params.usage]
* @param {string} [params.model]
* @param {string} [params.context='message']
* @returns {Promise<void>}
*/
async recordTokenUsage({ promptTokens, completionTokens, usage, model, context = 'message' }) {
if (usage != null && usage?.input_tokens != null) {
const input = usage.input_tokens ?? 0;
const write = usage.cache_creation_input_tokens ?? 0;
const read = usage.cache_read_input_tokens ?? 0;
await spendStructuredTokens(
{
context,
user: this.user,
conversationId: this.conversationId,
model: model ?? this.modelOptions.model,
endpointTokenConfig: this.options.endpointTokenConfig,
},
{
promptTokens: { input, write, read },
completionTokens,
},
);
return;
}
async recordTokenUsage({ promptTokens, completionTokens, model, context = 'message' }) {
await spendTokens(
{
context,
@@ -494,10 +381,7 @@ class AnthropicClient extends BaseClient {
identityPrefix = `${identityPrefix}\nYou are ${this.options.modelLabel}`;
}
let promptPrefix = (this.options.promptPrefix ?? '').trim();
if (typeof this.options.artifactsPrompt === 'string' && this.options.artifactsPrompt) {
promptPrefix = `${promptPrefix ?? ''}\n${this.options.artifactsPrompt}`.trim();
}
let promptPrefix = (this.options.promptPrefix || '').trim();
if (promptPrefix) {
// If the prompt prefix doesn't end with the end token, add it.
if (!promptPrefix.endsWith(`${this.endToken}`)) {
@@ -676,25 +560,6 @@ class AnthropicClient extends BaseClient {
: await client.completions.create(options);
}
/**
* @param {string} modelName
* @returns {boolean}
*/
checkPromptCacheSupport(modelName) {
const modelMatch = matchModelName(modelName, EModelEndpoint.anthropic);
if (modelMatch.includes('claude-3-5-sonnet-latest')) {
return false;
}
if (
modelMatch === 'claude-3-5-sonnet' ||
modelMatch === 'claude-3-haiku' ||
modelMatch === 'claude-3-opus'
) {
return true;
}
return false;
}
async sendCompletion(payload, { onProgress, abortController }) {
if (!abortController) {
abortController = new AbortController();
@@ -741,22 +606,10 @@ class AnthropicClient extends BaseClient {
requestOptions.max_tokens_to_sample = maxOutputTokens || 1500;
}
if (this.systemMessage && this.supportsCacheControl === true) {
requestOptions.system = [
{
type: 'text',
text: this.systemMessage,
cache_control: { type: 'ephemeral' },
},
];
} else if (this.systemMessage) {
if (this.systemMessage) {
requestOptions.system = this.systemMessage;
}
if (this.supportsCacheControl === true && this.useMessages) {
requestOptions.messages = addCacheControl(requestOptions.messages);
}
logger.debug('[AnthropicClient]', { ...requestOptions });
const handleChunk = (currentChunk) => {
@@ -786,11 +639,6 @@ class AnthropicClient extends BaseClient {
for await (const completion of response) {
// Handle each completion as before
const type = completion?.type ?? '';
if (tokenEventTypes.has(type)) {
logger.debug(`[AnthropicClient] ${type}`, completion);
this[type] = completion;
}
if (completion?.delta?.text) {
handleChunk(completion.delta.text);
} else if (completion.completion) {
@@ -832,10 +680,8 @@ class AnthropicClient extends BaseClient {
getSaveOptions() {
return {
maxContextTokens: this.options.maxContextTokens,
artifacts: this.options.artifacts,
promptPrefix: this.options.promptPrefix,
modelLabel: this.options.modelLabel,
promptCache: this.options.promptCache,
resendFiles: this.options.resendFiles,
iconURL: this.options.iconURL,
greeting: this.options.greeting,
@@ -881,8 +727,6 @@ class AnthropicClient extends BaseClient {
*/
async titleConvo({ text, responseText = '' }) {
let title = 'New Chat';
this.message_delta = undefined;
this.message_start = undefined;
const convo = `<initial_message>
${truncateText(text)}
</initial_message>

View File

@@ -1,14 +1,6 @@
const crypto = require('crypto');
const fetch = require('node-fetch');
const {
supportsBalanceCheck,
isAgentsEndpoint,
isParamEndpoint,
ErrorTypes,
Constants,
CacheKeys,
Time,
} = require('librechat-data-provider');
const { supportsBalanceCheck, Constants, CacheKeys, Time } = require('librechat-data-provider');
const { getMessages, saveMessage, updateMessage, saveConvo } = require('~/models');
const { addSpaceIfNeeded, isEnabled } = require('~/server/utils');
const checkBalance = require('~/models/checkBalance');
@@ -36,20 +28,6 @@ class BaseClient {
this.userMessagePromise;
/** @type {ClientDatabaseSavePromise} */
this.responsePromise;
/** @type {string} */
this.user;
/** @type {string} */
this.conversationId;
/** @type {string} */
this.responseMessageId;
/** @type {TAttachment[]} */
this.attachments;
/** The key for the usage object's input tokens
* @type {string} */
this.inputTokensKey = 'prompt_tokens';
/** The key for the usage object's output tokens
* @type {string} */
this.outputTokensKey = 'completion_tokens';
}
setOptions() {
@@ -76,33 +54,10 @@ class BaseClient {
throw new Error('Subclasses attempted to call summarizeMessages without implementing it');
}
/**
* @returns {string}
*/
getResponseModel() {
if (isAgentsEndpoint(this.options.endpoint) && this.options.agent && this.options.agent.id) {
return this.options.agent.id;
}
return this.modelOptions.model;
async getTokenCountForResponse(response) {
logger.debug('`[BaseClient] recordTokenUsage` not implemented.', response);
}
/**
* Abstract method to get the token count for a message. Subclasses must implement this method.
* @param {TMessage} responseMessage
* @returns {number}
*/
getTokenCountForResponse(responseMessage) {
logger.debug('`[BaseClient] recordTokenUsage` not implemented.', responseMessage);
}
/**
* Abstract method to record token usage. Subclasses must implement this method.
* If a correction to the token usage is needed, the method should return an object with the corrected token counts.
* @param {number} promptTokens
* @param {number} completionTokens
* @returns {Promise<void>}
*/
async recordTokenUsage({ promptTokens, completionTokens }) {
logger.debug('`[BaseClient] recordTokenUsage` not implemented.', {
promptTokens,
@@ -188,8 +143,6 @@ class BaseClient {
this.currentMessages[this.currentMessages.length - 1].messageId = head;
}
this.responseMessageId = responseMessageId;
return {
...opts,
user,
@@ -238,7 +191,6 @@ class BaseClient {
userMessage,
conversationId,
responseMessageId,
sender: this.sender,
});
}
@@ -377,12 +329,7 @@ class BaseClient {
};
}
async handleContextStrategy({
instructions,
orderedMessages,
formattedMessages,
buildTokenMap = true,
}) {
async handleContextStrategy({ instructions, orderedMessages, formattedMessages }) {
let _instructions;
let tokenCount;
@@ -424,10 +371,9 @@ class BaseClient {
const latestMessage = orderedWithInstructions[orderedWithInstructions.length - 1];
if (payload.length === 0 && !shouldSummarize && latestMessage) {
const info = `${latestMessage.tokenCount} / ${this.maxContextTokens}`;
const errorMessage = `{ "type": "${ErrorTypes.INPUT_LENGTH}", "info": "${info}" }`;
logger.warn(`Prompt token count exceeds max token count (${info}).`);
throw new Error(errorMessage);
throw new Error(
`Prompt token count of ${latestMessage.tokenCount} exceeds max token count of ${this.maxContextTokens}.`,
);
}
if (usePrevSummary) {
@@ -452,23 +398,19 @@ class BaseClient {
maxContextTokens: this.maxContextTokens,
});
/** @type {Record<string, number> | undefined} */
let tokenCountMap;
if (buildTokenMap) {
tokenCountMap = orderedWithInstructions.reduce((map, message, index) => {
const { messageId } = message;
if (!messageId) {
return map;
}
if (shouldSummarize && index === summaryIndex && !usePrevSummary) {
map.summaryMessage = { ...summaryMessage, messageId, tokenCount: summaryTokenCount };
}
map[messageId] = orderedWithInstructions[index].tokenCount;
let tokenCountMap = orderedWithInstructions.reduce((map, message, index) => {
const { messageId } = message;
if (!messageId) {
return map;
}, {});
}
}
if (shouldSummarize && index === summaryIndex && !usePrevSummary) {
map.summaryMessage = { ...summaryMessage, messageId, tokenCount: summaryTokenCount };
}
map[messageId] = orderedWithInstructions[index].tokenCount;
return map;
}, {});
const promptTokens = this.maxContextTokens - remainingContextTokens;
@@ -570,7 +512,6 @@ class BaseClient {
});
}
/** @type {string|string[]|undefined} */
const completion = await this.sendCompletion(payload, opts);
this.abortController.requestCompleted = true;
@@ -580,61 +521,28 @@ class BaseClient {
parentMessageId: userMessage.messageId,
isCreatedByUser: false,
isEdited,
model: this.getResponseModel(),
model: this.modelOptions.model,
sender: this.sender,
text: addSpaceIfNeeded(generation) + completion,
promptTokens,
iconURL: this.options.iconURL,
endpoint: this.options.endpoint,
...(this.metadata ?? {}),
};
if (typeof completion === 'string') {
responseMessage.text = addSpaceIfNeeded(generation) + completion;
} else if (
Array.isArray(completion) &&
isParamEndpoint(this.options.endpoint, this.options.endpointType)
) {
responseMessage.text = '';
responseMessage.content = completion;
} else if (Array.isArray(completion)) {
responseMessage.text = addSpaceIfNeeded(generation) + completion.join('');
}
if (
tokenCountMap &&
this.recordTokenUsage &&
this.getTokenCountForResponse &&
this.getTokenCount
) {
let completionTokens;
/**
* Metadata about input/output costs for the current message. The client
* should provide a function to get the current stream usage metadata; if not,
* use the legacy token estimations.
* @type {StreamUsage | null} */
const usage = this.getStreamUsage != null ? this.getStreamUsage() : null;
if (usage != null && Number(usage[this.outputTokensKey]) > 0) {
responseMessage.tokenCount = usage[this.outputTokensKey];
completionTokens = responseMessage.tokenCount;
await this.updateUserMessageTokenCount({ usage, tokenCountMap, userMessage, opts });
} else {
responseMessage.tokenCount = this.getTokenCountForResponse(responseMessage);
completionTokens = this.getTokenCount(completion);
}
await this.recordTokenUsage({ promptTokens, completionTokens, usage });
responseMessage.tokenCount = this.getTokenCountForResponse(responseMessage);
const completionTokens = this.getTokenCount(completion);
await this.recordTokenUsage({ promptTokens, completionTokens });
}
if (this.userMessagePromise) {
await this.userMessagePromise;
}
if (this.artifactPromises) {
responseMessage.attachments = (await Promise.all(this.artifactPromises)).filter((a) => a);
}
this.responsePromise = this.saveMessageToDatabase(responseMessage, saveOptions, user);
const messageCache = getLogStores(CacheKeys.MESSAGES);
messageCache.set(
@@ -649,66 +557,6 @@ class BaseClient {
return responseMessage;
}
/**
* Stream usage should only be used for user message token count re-calculation if:
* - The stream usage is available, with input tokens greater than 0,
* - the client provides a function to calculate the current token count,
* - files are being resent with every message (default behavior; or if `false`, with no attachments),
* - the `promptPrefix` (custom instructions) is not set.
*
* In these cases, the legacy token estimations would be more accurate.
*
* TODO: included system messages in the `orderedMessages` accounting, potentially as a
* separate message in the UI. ChatGPT does this through "hidden" system messages.
* @param {object} params
* @param {StreamUsage} params.usage
* @param {Record<string, number>} params.tokenCountMap
* @param {TMessage} params.userMessage
* @param {object} params.opts
*/
async updateUserMessageTokenCount({ usage, tokenCountMap, userMessage, opts }) {
/** @type {boolean} */
const shouldUpdateCount =
this.calculateCurrentTokenCount != null &&
Number(usage[this.inputTokensKey]) > 0 &&
(this.options.resendFiles ||
(!this.options.resendFiles && !this.options.attachments?.length)) &&
!this.options.promptPrefix;
if (!shouldUpdateCount) {
return;
}
const userMessageTokenCount = this.calculateCurrentTokenCount({
currentMessageId: userMessage.messageId,
tokenCountMap,
usage,
});
if (userMessageTokenCount === userMessage.tokenCount) {
return;
}
userMessage.tokenCount = userMessageTokenCount;
/*
Note: `AskController` saves the user message, so we update the count of its `userMessage` reference
*/
if (typeof opts?.getReqData === 'function') {
opts.getReqData({
userMessage,
});
}
/*
Note: we update the user message to be sure it gets the calculated token count;
though `AskController` saves the user message, EditController does not
*/
await this.userMessagePromise;
await this.updateMessageInDatabase({
messageId: userMessage.messageId,
tokenCount: userMessageTokenCount,
});
}
async loadHistory(conversationId, parentMessageId = null) {
logger.debug('[BaseClient] Loading history:', { conversationId, parentMessageId });
@@ -796,10 +644,6 @@ class BaseClient {
return { message: savedMessage, conversation };
}
/**
* Update a message in the database.
* @param {Partial<TMessage>} message
*/
async updateMessageInDatabase(message) {
await updateMessage(this.options.req, message);
}
@@ -923,12 +767,8 @@ class BaseClient {
processValue(nestedValue);
}
} else if (typeof value === 'string') {
} else {
numTokens += this.getTokenCount(value);
} else if (typeof value === 'number') {
numTokens += this.getTokenCount(value.toString());
} else if (typeof value === 'boolean') {
numTokens += this.getTokenCount(value.toString());
}
};

View File

@@ -1,21 +1,19 @@
const Keyv = require('keyv');
const crypto = require('crypto');
const { CohereClient } = require('cohere-ai');
const { fetchEventSource } = require('@waylaidwanderer/fetch-event-source');
const { encoding_for_model: encodingForModel, get_encoding: getEncoding } = require('tiktoken');
const {
ImageDetail,
EModelEndpoint,
resolveHeaders,
CohereConstants,
mapModelToAzureConfig,
} = require('librechat-data-provider');
const { extractBaseURL, constructAzureURL, genAzureChatCompletion } = require('~/utils');
const { createContextHandlers } = require('./prompts');
const { CohereClient } = require('cohere-ai');
const { encoding_for_model: encodingForModel, get_encoding: getEncoding } = require('tiktoken');
const { fetchEventSource } = require('@waylaidwanderer/fetch-event-source');
const { createCoherePayload } = require('./llm');
const { Agent, ProxyAgent } = require('undici');
const BaseClient = require('./BaseClient');
const { logger } = require('~/config');
const { extractBaseURL, constructAzureURL, genAzureChatCompletion } = require('~/utils');
const CHATGPT_MODEL = 'gpt-3.5-turbo';
const tokenizersCache = {};
@@ -614,66 +612,21 @@ ${botMessage.message}
async buildPrompt(messages, { isChatGptModel = false, promptPrefix = null }) {
promptPrefix = (promptPrefix || this.options.promptPrefix || '').trim();
// Handle attachments and create augmentedPrompt
if (this.options.attachments) {
const attachments = await this.options.attachments;
const lastMessage = messages[messages.length - 1];
if (this.message_file_map) {
this.message_file_map[lastMessage.messageId] = attachments;
} else {
this.message_file_map = {
[lastMessage.messageId]: attachments,
};
}
const files = await this.addImageURLs(lastMessage, attachments);
this.options.attachments = files;
this.contextHandlers = createContextHandlers(this.options.req, lastMessage.text);
}
if (this.message_file_map) {
this.contextHandlers = createContextHandlers(
this.options.req,
messages[messages.length - 1].text,
);
}
// Calculate image token cost and process embedded files
messages.forEach((message, i) => {
if (this.message_file_map && this.message_file_map[message.messageId]) {
const attachments = this.message_file_map[message.messageId];
for (const file of attachments) {
if (file.embedded) {
this.contextHandlers?.processFile(file);
continue;
}
messages[i].tokenCount =
(messages[i].tokenCount || 0) +
this.calculateImageTokenCost({
width: file.width,
height: file.height,
detail: this.options.imageDetail ?? ImageDetail.auto,
});
}
}
});
if (this.contextHandlers) {
this.augmentedPrompt = await this.contextHandlers.createContext();
promptPrefix = this.augmentedPrompt + promptPrefix;
}
if (promptPrefix) {
// If the prompt prefix doesn't end with the end token, add it.
if (!promptPrefix.endsWith(`${this.endToken}`)) {
promptPrefix = `${promptPrefix.trim()}${this.endToken}\n\n`;
}
promptPrefix = `${this.startToken}Instructions:\n${promptPrefix}`;
} else {
const currentDateString = new Date().toLocaleDateString('en-us', {
year: 'numeric',
month: 'long',
day: 'numeric',
});
promptPrefix = `${this.startToken}Instructions:\nYou are ChatGPT, a large language model trained by OpenAI. Respond conversationally.\nCurrent date: ${currentDateString}${this.endToken}\n\n`;
}
const promptSuffix = `${this.startToken}${this.chatGptLabel}:\n`; // Prompt ChatGPT to respond.
const instructionsPayload = {
@@ -761,6 +714,10 @@ ${botMessage.message}
this.maxResponseTokens,
);
if (this.options.debug) {
console.debug(`Prompt : ${prompt}`);
}
if (isChatGptModel) {
return { prompt: [instructionsPayload, messagePayload], context };
}

View File

@@ -28,7 +28,7 @@ const {
} = require('./prompts');
const BaseClient = require('./BaseClient');
const loc = process.env.GOOGLE_LOC || 'us-central1';
const loc = 'us-central1';
const publisher = 'google';
const endpointPrefix = `https://${loc}-aiplatform.googleapis.com`;
// const apiEndpoint = loc + '-aiplatform.googleapis.com';
@@ -120,7 +120,19 @@ class GoogleClient extends BaseClient {
.filter((ex) => ex)
.filter((obj) => obj.input.content !== '' && obj.output.content !== '');
this.modelOptions = this.options.modelOptions || {};
const modelOptions = this.options.modelOptions || {};
this.modelOptions = {
...modelOptions,
// set some good defaults (check for undefined in some cases because they may be 0)
model: modelOptions.model || settings.model.default,
temperature:
typeof modelOptions.temperature === 'undefined'
? settings.temperature.default
: modelOptions.temperature,
topP: typeof modelOptions.topP === 'undefined' ? settings.topP.default : modelOptions.topP,
topK: typeof modelOptions.topK === 'undefined' ? settings.topK.default : modelOptions.topK,
// stop: modelOptions.stop // no stop method for now
};
this.options.attachments?.then((attachments) => this.checkVisionRequest(attachments));
@@ -390,13 +402,8 @@ class GoogleClient extends BaseClient {
parameters: this.modelOptions,
};
let promptPrefix = (this.options.promptPrefix ?? '').trim();
if (typeof this.options.artifactsPrompt === 'string' && this.options.artifactsPrompt) {
promptPrefix = `${promptPrefix ?? ''}\n${this.options.artifactsPrompt}`.trim();
}
if (promptPrefix) {
payload.instances[0].context = promptPrefix;
if (this.options.promptPrefix) {
payload.instances[0].context = this.options.promptPrefix;
}
if (this.options.examples.length > 0) {
@@ -450,10 +457,7 @@ class GoogleClient extends BaseClient {
identityPrefix = `${identityPrefix}\nYou are ${this.options.modelLabel}`;
}
let promptPrefix = (this.options.promptPrefix ?? '').trim();
if (typeof this.options.artifactsPrompt === 'string' && this.options.artifactsPrompt) {
promptPrefix = `${promptPrefix ?? ''}\n${this.options.artifactsPrompt}`.trim();
}
let promptPrefix = (this.options.promptPrefix || '').trim();
if (promptPrefix) {
// If the prompt prefix doesn't end with the end token, add it.
if (!promptPrefix.endsWith(`${this.endToken}`)) {
@@ -593,8 +597,6 @@ class GoogleClient extends BaseClient {
createLLM(clientOptions) {
const model = clientOptions.modelName ?? clientOptions.model;
clientOptions.location = loc;
clientOptions.endpoint = `${loc}-aiplatform.googleapis.com`;
if (this.project_id && this.isTextModel) {
logger.debug('Creating Google VertexAI client');
return new GoogleVertexAI(clientOptions);
@@ -675,27 +677,24 @@ class GoogleClient extends BaseClient {
const modelName = clientOptions.modelName ?? clientOptions.model ?? '';
if (modelName?.includes('1.5') && !this.project_id) {
/** @type {GenerativeModel} */
const client = model;
const requestOptions = {
contents: _payload,
};
let promptPrefix = (this.options.promptPrefix ?? '').trim();
if (typeof this.options.artifactsPrompt === 'string' && this.options.artifactsPrompt) {
promptPrefix = `${promptPrefix ?? ''}\n${this.options.artifactsPrompt}`.trim();
}
if (this.options?.promptPrefix?.length) {
requestOptions.systemInstruction = {
parts: [
{
text: promptPrefix,
text: this.options.promptPrefix,
},
],
};
}
requestOptions.safetySettings = _payload.safetySettings;
const safetySettings = _payload.safetySettings;
requestOptions.safetySettings = safetySettings;
const delay = modelName.includes('flash') ? 8 : 14;
const result = await client.generateContentStream(requestOptions);
@@ -710,10 +709,11 @@ class GoogleClient extends BaseClient {
return reply;
}
const safetySettings = _payload.safetySettings;
const stream = await model.stream(messages, {
signal: abortController.signal,
timeout: 7000,
safetySettings: _payload.safetySettings,
safetySettings: safetySettings,
});
let delay = this.options.streamRate || 8;
@@ -782,16 +782,11 @@ class GoogleClient extends BaseClient {
contents: _payload,
};
let promptPrefix = (this.options.promptPrefix ?? '').trim();
if (typeof this.options.artifactsPrompt === 'string' && this.options.artifactsPrompt) {
promptPrefix = `${promptPrefix ?? ''}\n${this.options.artifactsPrompt}`.trim();
}
if (this.options?.promptPrefix?.length) {
requestOptions.systemInstruction = {
parts: [
{
text: promptPrefix,
text: this.options.promptPrefix,
},
],
};
@@ -816,7 +811,7 @@ class GoogleClient extends BaseClient {
});
reply = titleResponse.content;
// TODO: RECORD TOKEN USAGE
return reply;
}
}
@@ -862,7 +857,6 @@ class GoogleClient extends BaseClient {
getSaveOptions() {
return {
artifacts: this.options.artifacts,
promptPrefix: this.options.promptPrefix,
modelLabel: this.options.modelLabel,
iconURL: this.options.iconURL,
@@ -877,36 +871,38 @@ class GoogleClient extends BaseClient {
}
async sendCompletion(payload, opts = {}) {
payload.safetySettings = this.getSafetySettings();
const modelName = payload.parameters?.model;
if (modelName && modelName.toLowerCase().includes('gemini')) {
const safetySettings = [
{
category: 'HARM_CATEGORY_SEXUALLY_EXPLICIT',
threshold:
process.env.GOOGLE_SAFETY_SEXUALLY_EXPLICIT || 'HARM_BLOCK_THRESHOLD_UNSPECIFIED',
},
{
category: 'HARM_CATEGORY_HATE_SPEECH',
threshold: process.env.GOOGLE_SAFETY_HATE_SPEECH || 'HARM_BLOCK_THRESHOLD_UNSPECIFIED',
},
{
category: 'HARM_CATEGORY_HARASSMENT',
threshold: process.env.GOOGLE_SAFETY_HARASSMENT || 'HARM_BLOCK_THRESHOLD_UNSPECIFIED',
},
{
category: 'HARM_CATEGORY_DANGEROUS_CONTENT',
threshold:
process.env.GOOGLE_SAFETY_DANGEROUS_CONTENT || 'HARM_BLOCK_THRESHOLD_UNSPECIFIED',
},
];
payload.safetySettings = safetySettings;
}
let reply = '';
reply = await this.getCompletion(payload, opts);
return reply.trim();
}
getSafetySettings() {
return [
{
category: 'HARM_CATEGORY_SEXUALLY_EXPLICIT',
threshold:
process.env.GOOGLE_SAFETY_SEXUALLY_EXPLICIT || 'HARM_BLOCK_THRESHOLD_UNSPECIFIED',
},
{
category: 'HARM_CATEGORY_HATE_SPEECH',
threshold: process.env.GOOGLE_SAFETY_HATE_SPEECH || 'HARM_BLOCK_THRESHOLD_UNSPECIFIED',
},
{
category: 'HARM_CATEGORY_HARASSMENT',
threshold: process.env.GOOGLE_SAFETY_HARASSMENT || 'HARM_BLOCK_THRESHOLD_UNSPECIFIED',
},
{
category: 'HARM_CATEGORY_DANGEROUS_CONTENT',
threshold:
process.env.GOOGLE_SAFETY_DANGEROUS_CONTENT || 'HARM_BLOCK_THRESHOLD_UNSPECIFIED',
},
];
}
/* TO-DO: Handle tokens with Google tokenization NOTE: these are required */
static getTokenizer(encoding, isModelName = false, extendSpecialTokens = {}) {
if (tokenizersCache[encoding]) {

View File

@@ -60,9 +60,7 @@ class OllamaClient {
try {
const ollamaEndpoint = deriveBaseURL(baseURL);
/** @type {Promise<AxiosResponse<OllamaListResponse>>} */
const response = await axios.get(`${ollamaEndpoint}/api/tags`, {
timeout: 5000,
});
const response = await axios.get(`${ollamaEndpoint}/api/tags`);
models = response.data.models.map((tag) => tag.name);
return models;
} catch (error) {

View File

@@ -6,7 +6,6 @@ const {
ImageDetail,
EModelEndpoint,
resolveHeaders,
openAISettings,
ImageDetailCost,
CohereConstants,
getResponseSender,
@@ -19,7 +18,6 @@ const {
constructAzureURL,
getModelMaxTokens,
genAzureChatCompletion,
getModelMaxOutputTokens,
} = require('~/utils');
const {
truncateText,
@@ -29,9 +27,9 @@ const {
createContextHandlers,
} = require('./prompts');
const { encodeAndFormat } = require('~/server/services/Files/images/encode');
const { spendTokens } = require('~/models/spendTokens');
const { isEnabled, sleep } = require('~/server/utils');
const { handleOpenAIErrors } = require('./tools/util');
const spendTokens = require('~/models/spendTokens');
const { createLLM, RunManager } = require('./llm');
const ChatGPTClient = require('./ChatGPTClient');
const { summaryBuffer } = require('./memory');
@@ -65,11 +63,6 @@ class OpenAIClient extends BaseClient {
/** @type {string | undefined} - The API Completions URL */
this.completionsUrl;
/** @type {OpenAIUsageMetadata | undefined} */
this.usage;
/** @type {boolean|undefined} */
this.isO1Model;
}
// TODO: PluginsClient calls this 3x, unneeded
@@ -92,15 +85,26 @@ class OpenAIClient extends BaseClient {
this.apiKey = this.options.openaiApiKey;
}
this.modelOptions = Object.assign(
{
model: openAISettings.model.default,
},
this.modelOptions,
this.options.modelOptions,
);
const modelOptions = this.options.modelOptions || {};
this.isO1Model = /\bo1\b/i.test(this.modelOptions.model);
if (!this.modelOptions) {
this.modelOptions = {
...modelOptions,
model: modelOptions.model || 'gpt-3.5-turbo',
temperature:
typeof modelOptions.temperature === 'undefined' ? 0.8 : modelOptions.temperature,
top_p: typeof modelOptions.top_p === 'undefined' ? 1 : modelOptions.top_p,
presence_penalty:
typeof modelOptions.presence_penalty === 'undefined' ? 1 : modelOptions.presence_penalty,
stop: modelOptions.stop,
};
} else {
// Update the modelOptions if it already exists
this.modelOptions = {
...this.modelOptions,
...modelOptions,
};
}
this.defaultVisionModel = this.options.visionModel ?? 'gpt-4-vision-preview';
if (typeof this.options.attachments?.then === 'function') {
@@ -146,8 +150,7 @@ class OpenAIClient extends BaseClient {
const { model } = this.modelOptions;
this.isChatCompletion =
/\bo1\b/i.test(model) || model.includes('gpt') || this.useOpenRouter || !!reverseProxy;
this.isChatCompletion = this.useOpenRouter || !!reverseProxy || model.includes('gpt');
this.isChatGptModel = this.isChatCompletion;
if (
model.includes('text-davinci') ||
@@ -178,14 +181,7 @@ class OpenAIClient extends BaseClient {
logger.debug('[OpenAIClient] maxContextTokens', this.maxContextTokens);
}
this.maxResponseTokens =
this.modelOptions.max_tokens ??
getModelMaxOutputTokens(
model,
this.options.endpointType ?? this.options.endpoint,
this.options.endpointTokenConfig,
) ??
1024;
this.maxResponseTokens = this.modelOptions.max_tokens || 1024;
this.maxPromptTokens =
this.options.maxPromptTokens || this.maxContextTokens - this.maxResponseTokens;
@@ -203,8 +199,8 @@ class OpenAIClient extends BaseClient {
model: this.modelOptions.model,
endpoint: this.options.endpoint,
endpointType: this.options.endpointType,
chatGptLabel: this.options.chatGptLabel,
modelDisplayLabel: this.options.modelDisplayLabel,
chatGptLabel: this.options.chatGptLabel || this.options.modelLabel,
});
this.userLabel = this.options.userLabel || 'User';
@@ -417,7 +413,6 @@ class OpenAIClient extends BaseClient {
getSaveOptions() {
return {
artifacts: this.options.artifacts,
maxContextTokens: this.options.maxContextTokens,
chatGptLabel: this.options.chatGptLabel,
promptPrefix: this.options.promptPrefix,
@@ -480,9 +475,6 @@ class OpenAIClient extends BaseClient {
let promptTokens;
promptPrefix = (promptPrefix || this.options.promptPrefix || '').trim();
if (typeof this.options.artifactsPrompt === 'string' && this.options.artifactsPrompt) {
promptPrefix = `${promptPrefix ?? ''}\n${this.options.artifactsPrompt}`.trim();
}
if (this.options.attachments) {
const attachments = await this.options.attachments;
@@ -549,7 +541,7 @@ class OpenAIClient extends BaseClient {
promptPrefix = this.augmentedPrompt + promptPrefix;
}
if (promptPrefix && this.isO1Model !== true) {
if (promptPrefix) {
promptPrefix = `Instructions:\n${promptPrefix.trim()}`;
instructions = {
role: 'system',
@@ -577,16 +569,6 @@ class OpenAIClient extends BaseClient {
messages,
};
/** EXPERIMENTAL */
if (promptPrefix && this.isO1Model === true) {
const lastUserMessageIndex = payload.findLastIndex((message) => message.role === 'user');
if (lastUserMessageIndex !== -1) {
payload[
lastUserMessageIndex
].content = `${promptPrefix}\n${payload[lastUserMessageIndex].content}`;
}
}
if (tokenCountMap) {
tokenCountMap.instructions = instructions?.tokenCount;
result.tokenCountMap = tokenCountMap;
@@ -647,12 +629,6 @@ class OpenAIClient extends BaseClient {
if (completionResult && typeof completionResult === 'string') {
reply = completionResult;
} else if (
completionResult &&
typeof completionResult === 'object' &&
Array.isArray(completionResult.choices)
) {
reply = completionResult.choices[0]?.text?.replace(this.endToken, '');
}
} else if (typeof opts.onProgress === 'function' || this.options.useChatCompletion) {
reply = await this.chatCompletion({
@@ -842,27 +818,27 @@ class OpenAIClient extends BaseClient {
}
const titleChatCompletion = async () => {
try {
modelOptions.model = model;
modelOptions.model = model;
if (this.azure) {
modelOptions.model = process.env.AZURE_OPENAI_DEFAULT_MODEL ?? modelOptions.model;
this.azureEndpoint = genAzureChatCompletion(this.azure, modelOptions.model, this);
}
if (this.azure) {
modelOptions.model = process.env.AZURE_OPENAI_DEFAULT_MODEL ?? modelOptions.model;
this.azureEndpoint = genAzureChatCompletion(this.azure, modelOptions.model, this);
}
const instructionsPayload = [
{
role: this.options.titleMessageRole ?? (this.isOllama ? 'user' : 'system'),
content: `Please generate ${titleInstruction}
const instructionsPayload = [
{
role: this.options.titleMessageRole ?? 'system',
content: `Please generate ${titleInstruction}
${convo}
||>Title:`,
},
];
},
];
const promptTokens = this.getTokenCountForMessage(instructionsPayload[0]);
const promptTokens = this.getTokenCountForMessage(instructionsPayload[0]);
try {
let useChatCompletion = true;
if (this.options.reverseProxyUrl === CohereConstants.API_URL) {
@@ -917,60 +893,6 @@ ${convo}
return title;
}
/**
* Get stream usage as returned by this client's API response.
* @returns {OpenAIUsageMetadata} The stream usage object.
*/
getStreamUsage() {
if (
this.usage &&
typeof this.usage === 'object' &&
'completion_tokens_details' in this.usage &&
this.usage.completion_tokens_details &&
typeof this.usage.completion_tokens_details === 'object' &&
'reasoning_tokens' in this.usage.completion_tokens_details
) {
const outputTokens = Math.abs(
this.usage.completion_tokens_details.reasoning_tokens - this.usage[this.outputTokensKey],
);
return {
...this.usage.completion_tokens_details,
[this.inputTokensKey]: this.usage[this.inputTokensKey],
[this.outputTokensKey]: outputTokens,
};
}
return this.usage;
}
/**
* Calculates the correct token count for the current user message based on the token count map and API usage.
* Edge case: If the calculation results in a negative value, it returns the original estimate.
* If revisiting a conversation with a chat history entirely composed of token estimates,
* the cumulative token count going forward should become more accurate as the conversation progresses.
* @param {Object} params - The parameters for the calculation.
* @param {Record<string, number>} params.tokenCountMap - A map of message IDs to their token counts.
* @param {string} params.currentMessageId - The ID of the current message to calculate.
* @param {OpenAIUsageMetadata} params.usage - The usage object returned by the API.
* @returns {number} The correct token count for the current user message.
*/
calculateCurrentTokenCount({ tokenCountMap, currentMessageId, usage }) {
const originalEstimate = tokenCountMap[currentMessageId] || 0;
if (!usage || typeof usage[this.inputTokensKey] !== 'number') {
return originalEstimate;
}
tokenCountMap[currentMessageId] = 0;
const totalTokensFromMap = Object.values(tokenCountMap).reduce((sum, count) => {
const numCount = Number(count);
return sum + (isNaN(numCount) ? 0 : numCount);
}, 0);
const totalInputTokens = usage[this.inputTokensKey] ?? 0;
const currentMessageTokens = totalInputTokens - totalTokensFromMap;
return currentMessageTokens > 0 ? currentMessageTokens : originalEstimate;
}
async summarizeMessages({ messagesToRefine, remainingContextTokens }) {
logger.debug('[OpenAIClient] Summarizing messages...');
let context = messagesToRefine;
@@ -1086,16 +1008,7 @@ ${convo}
}
}
/**
* @param {object} params
* @param {number} params.promptTokens
* @param {number} params.completionTokens
* @param {OpenAIUsageMetadata} [params.usage]
* @param {string} [params.model]
* @param {string} [params.context='message']
* @returns {Promise<void>}
*/
async recordTokenUsage({ promptTokens, completionTokens, usage, context = 'message' }) {
async recordTokenUsage({ promptTokens, completionTokens, context = 'message' }) {
await spendTokens(
{
context,
@@ -1106,24 +1019,6 @@ ${convo}
},
{ promptTokens, completionTokens },
);
if (
usage &&
typeof usage === 'object' &&
'reasoning_tokens' in usage &&
typeof usage.reasoning_tokens === 'number'
) {
await spendTokens(
{
context: 'reasoning',
model: this.modelOptions.model,
conversationId: this.conversationId,
user: this.user ?? this.options.req.user?.id,
endpointTokenConfig: this.options.endpointTokenConfig,
},
{ completionTokens: usage.reasoning_tokens },
);
}
}
getTokenCountForResponse(response) {
@@ -1136,7 +1031,7 @@ ${convo}
async chatCompletion({ payload, onProgress, abortController = null }) {
let error = null;
const errorCallback = (err) => (error = err);
const intermediateReply = [];
let intermediateReply = '';
try {
if (!abortController) {
abortController = new AbortController();
@@ -1230,11 +1125,6 @@ ${convo}
opts.defaultHeaders = { ...opts.defaultHeaders, 'api-key': this.apiKey };
}
if (this.isO1Model === true && modelOptions.max_tokens != null) {
modelOptions.max_completion_tokens = modelOptions.max_tokens;
delete modelOptions.max_tokens;
}
if (process.env.OPENAI_ORGANIZATION) {
opts.organization = process.env.OPENAI_ORGANIZATION;
}
@@ -1304,20 +1194,7 @@ ${convo}
}
let UnexpectedRoleError = false;
/** @type {Promise<void>} */
let streamPromise;
/** @type {(value: void | PromiseLike<void>) => void} */
let streamResolve;
if (modelOptions.stream && this.isO1Model) {
delete modelOptions.stream;
delete modelOptions.stop;
}
if (modelOptions.stream) {
streamPromise = new Promise((resolve) => {
streamResolve = resolve;
});
const stream = await openai.beta.chat.completions
.stream({
...modelOptions,
@@ -1329,30 +1206,26 @@ ${convo}
.on('error', (err) => {
handleOpenAIErrors(err, errorCallback, 'stream');
})
.on('finalChatCompletion', async (finalChatCompletion) => {
.on('finalChatCompletion', (finalChatCompletion) => {
const finalMessage = finalChatCompletion?.choices?.[0]?.message;
if (!finalMessage) {
return;
}
await streamPromise;
if (finalMessage?.role !== 'assistant') {
if (finalMessage && finalMessage?.role !== 'assistant') {
finalChatCompletion.choices[0].message.role = 'assistant';
}
if (typeof finalMessage.content !== 'string' || finalMessage.content.trim() === '') {
finalChatCompletion.choices[0].message.content = intermediateReply.join('');
if (finalMessage && !finalMessage?.content?.trim()) {
finalChatCompletion.choices[0].message.content = intermediateReply;
}
})
.on('finalMessage', (message) => {
if (message?.role !== 'assistant') {
stream.messages.push({ role: 'assistant', content: intermediateReply.join('') });
stream.messages.push({ role: 'assistant', content: intermediateReply });
UnexpectedRoleError = true;
}
});
for await (const chunk of stream) {
const token = chunk.choices[0]?.delta?.content || '';
intermediateReply.push(token);
intermediateReply += token;
onProgress(token);
if (abortController.signal.aborted) {
stream.controller.abort();
@@ -1362,8 +1235,6 @@ ${convo}
await sleep(streamRate);
}
streamResolve();
if (!UnexpectedRoleError) {
chatCompletion = await stream.finalChatCompletion().catch((err) => {
handleOpenAIErrors(err, errorCallback, 'finalChatCompletion');
@@ -1391,31 +1262,19 @@ ${convo}
throw new Error('Chat completion failed');
}
const { choices } = chatCompletion;
this.usage = chatCompletion.usage;
if (!Array.isArray(choices) || choices.length === 0) {
logger.warn('[OpenAIClient] Chat completion response has no choices');
return intermediateReply.join('');
const { message, finish_reason } = chatCompletion.choices[0];
if (chatCompletion) {
this.metadata = { finish_reason };
}
const { message, finish_reason } = choices[0] ?? {};
this.metadata = { finish_reason };
logger.debug('[OpenAIClient] chatCompletion response', chatCompletion);
if (!message) {
logger.warn('[OpenAIClient] Message is undefined in chatCompletion response');
return intermediateReply.join('');
}
if (typeof message.content !== 'string' || message.content.trim() === '') {
const reply = intermediateReply.join('');
if (!message?.content?.trim() && intermediateReply.length) {
logger.debug(
'[OpenAIClient] chatCompletion: using intermediateReply due to empty message.content',
{ intermediateReply: reply },
{ intermediateReply },
);
return reply;
return intermediateReply;
}
return message.content;
@@ -1424,7 +1283,7 @@ ${convo}
err?.message?.includes('abort') ||
(err instanceof OpenAI.APIError && err?.message?.includes('abort'))
) {
return intermediateReply.join('');
return intermediateReply;
}
if (
err?.message?.includes(
@@ -1439,10 +1298,10 @@ ${convo}
(err instanceof OpenAI.OpenAIError && err?.message?.includes('missing finish_reason'))
) {
logger.error('[OpenAIClient] Known OpenAI error:', err);
return intermediateReply.join('');
return intermediateReply;
} else if (err instanceof OpenAI.APIError) {
if (intermediateReply.length > 0) {
return intermediateReply.join('');
if (intermediateReply) {
return intermediateReply;
} else {
throw err;
}

View File

@@ -42,7 +42,6 @@ class PluginsClient extends OpenAIClient {
getSaveOptions() {
return {
artifacts: this.options.artifacts,
chatGptLabel: this.options.chatGptLabel,
promptPrefix: this.options.promptPrefix,
tools: this.options.tools,
@@ -146,22 +145,16 @@ class PluginsClient extends OpenAIClient {
// initialize agent
const initializer = this.functionsAgent ? initializeFunctionsAgent : initializeCustomAgent;
let customInstructions = (this.options.promptPrefix ?? '').trim();
if (typeof this.options.artifactsPrompt === 'string' && this.options.artifactsPrompt) {
customInstructions = `${customInstructions ?? ''}\n${this.options.artifactsPrompt}`.trim();
}
this.executor = await initializer({
model,
signal,
pastMessages,
tools: this.tools,
customInstructions,
verbose: this.options.debug,
returnIntermediateSteps: true,
customName: this.options.chatGptLabel,
currentDateString: this.currentDateString,
customInstructions: this.options.promptPrefix,
callbackManager: CallbackManager.fromHandlers({
async handleAgentAction(action, runId) {
handleAction(action, runId, onAgentAction);

View File

@@ -1,5 +1,5 @@
const { createStartHandler } = require('~/app/clients/callbacks');
const { spendTokens } = require('~/models/spendTokens');
const spendTokens = require('~/models/spendTokens');
const { logger } = require('~/config');
class RunManager {

View File

@@ -8,7 +8,7 @@ const { isEnabled } = require('~/server/utils');
* @param {Object} options - The options for creating the LLM.
* @param {ModelOptions} options.modelOptions - The options specific to the model, including modelName, temperature, presence_penalty, frequency_penalty, and other model-related settings.
* @param {ConfigOptions} options.configOptions - Configuration options for the API requests, including proxy settings and custom headers.
* @param {Callbacks} [options.callbacks] - Callback functions for managing the lifecycle of the LLM, including token buffers, context, and initial message count.
* @param {Callbacks} options.callbacks - Callback functions for managing the lifecycle of the LLM, including token buffers, context, and initial message count.
* @param {boolean} [options.streaming=false] - Determines if the LLM should operate in streaming mode.
* @param {string} options.openAIApiKey - The API key for OpenAI, used for authentication.
* @param {AzureOptions} [options.azure={}] - Optional Azure-specific configurations. If provided, Azure configurations take precedence over OpenAI configurations.

View File

@@ -60,10 +60,10 @@ function addImages(intermediateSteps, responseMessage) {
if (!observation || !observation.includes('![')) {
return;
}
const observedImagePath = observation.match(/!\[[^(]*\]\([^)]*\)/g);
const observedImagePath = observation.match(/!\[.*\]\([^)]*\)/g);
if (observedImagePath && !responseMessage.text.includes(observedImagePath[0])) {
responseMessage.text += '\n' + observedImagePath[0];
logger.debug('[addImages] added image from intermediateSteps:', observedImagePath[0]);
responseMessage.text += '\n' + observation;
logger.debug('[addImages] added image from intermediateSteps:', observation);
}
});
}

View File

@@ -81,62 +81,4 @@ describe('addImages', () => {
addImages(intermediateSteps, responseMessage);
expect(responseMessage.text).toBe(`${originalText}\n${imageMarkdown}`);
});
it('should extract only image markdowns when there is text between them', () => {
const markdownWithTextBetweenImages = `
![image1](/images/image1.png)
Some text between images that should not be included.
![image2](/images/image2.png)
More text that should be ignored.
![image3](/images/image3.png)
`;
intermediateSteps.push({ observation: markdownWithTextBetweenImages });
addImages(intermediateSteps, responseMessage);
expect(responseMessage.text).toBe('\n![image1](/images/image1.png)');
});
it('should only return the first image when multiple images are present', () => {
const markdownWithMultipleImages = `
![image1](/images/image1.png)
![image2](/images/image2.png)
![image3](/images/image3.png)
`;
intermediateSteps.push({ observation: markdownWithMultipleImages });
addImages(intermediateSteps, responseMessage);
expect(responseMessage.text).toBe('\n![image1](/images/image1.png)');
});
it('should not include any text or metadata surrounding the image markdown', () => {
const markdownWithMetadata = `
Title: Test Document
Author: John Doe
![image1](/images/image1.png)
Some content after the image.
Vector values: [0.1, 0.2, 0.3]
`;
intermediateSteps.push({ observation: markdownWithMetadata });
addImages(intermediateSteps, responseMessage);
expect(responseMessage.text).toBe('\n![image1](/images/image1.png)');
});
it('should handle complex markdown with multiple images and only return the first one', () => {
const complexMarkdown = `
# Document Title
## Section 1
Here's some text with an embedded image:
![image1](/images/image1.png)
## Section 2
More text here...
![image2](/images/image2.png)
### Subsection
Even more content
![image3](/images/image3.png)
`;
intermediateSteps.push({ observation: complexMarkdown });
addImages(intermediateSteps, responseMessage);
expect(responseMessage.text).toBe('\n![image1](/images/image1.png)');
});
});

View File

@@ -1,43 +0,0 @@
/**
* Anthropic API: Adds cache control to the appropriate user messages in the payload.
* @param {Array<AnthropicMessage>} messages - The array of message objects.
* @returns {Array<AnthropicMessage>} - The updated array of message objects with cache control added.
*/
function addCacheControl(messages) {
if (!Array.isArray(messages) || messages.length < 2) {
return messages;
}
const updatedMessages = [...messages];
let userMessagesModified = 0;
for (let i = updatedMessages.length - 1; i >= 0 && userMessagesModified < 2; i--) {
const message = updatedMessages[i];
if (message.role !== 'user') {
continue;
}
if (typeof message.content === 'string') {
message.content = [
{
type: 'text',
text: message.content,
cache_control: { type: 'ephemeral' },
},
];
userMessagesModified++;
} else if (Array.isArray(message.content)) {
for (let j = message.content.length - 1; j >= 0; j--) {
if (message.content[j].type === 'text') {
message.content[j].cache_control = { type: 'ephemeral' };
userMessagesModified++;
break;
}
}
}
}
return updatedMessages;
}
module.exports = addCacheControl;

View File

@@ -1,227 +0,0 @@
const addCacheControl = require('./addCacheControl');
describe('addCacheControl', () => {
test('should add cache control to the last two user messages with array content', () => {
const messages = [
{ role: 'user', content: [{ type: 'text', text: 'Hello' }] },
{ role: 'assistant', content: [{ type: 'text', text: 'Hi there' }] },
{ role: 'user', content: [{ type: 'text', text: 'How are you?' }] },
{ role: 'assistant', content: [{ type: 'text', text: 'I\'m doing well, thanks!' }] },
{ role: 'user', content: [{ type: 'text', text: 'Great!' }] },
];
const result = addCacheControl(messages);
expect(result[0].content[0]).not.toHaveProperty('cache_control');
expect(result[2].content[0].cache_control).toEqual({ type: 'ephemeral' });
expect(result[4].content[0].cache_control).toEqual({ type: 'ephemeral' });
});
test('should add cache control to the last two user messages with string content', () => {
const messages = [
{ role: 'user', content: 'Hello' },
{ role: 'assistant', content: 'Hi there' },
{ role: 'user', content: 'How are you?' },
{ role: 'assistant', content: 'I\'m doing well, thanks!' },
{ role: 'user', content: 'Great!' },
];
const result = addCacheControl(messages);
expect(result[0].content).toBe('Hello');
expect(result[2].content[0]).toEqual({
type: 'text',
text: 'How are you?',
cache_control: { type: 'ephemeral' },
});
expect(result[4].content[0]).toEqual({
type: 'text',
text: 'Great!',
cache_control: { type: 'ephemeral' },
});
});
test('should handle mixed string and array content', () => {
const messages = [
{ role: 'user', content: 'Hello' },
{ role: 'assistant', content: 'Hi there' },
{ role: 'user', content: [{ type: 'text', text: 'How are you?' }] },
];
const result = addCacheControl(messages);
expect(result[0].content[0]).toEqual({
type: 'text',
text: 'Hello',
cache_control: { type: 'ephemeral' },
});
expect(result[2].content[0].cache_control).toEqual({ type: 'ephemeral' });
});
test('should handle less than two user messages', () => {
const messages = [
{ role: 'user', content: 'Hello' },
{ role: 'assistant', content: 'Hi there' },
];
const result = addCacheControl(messages);
expect(result[0].content[0]).toEqual({
type: 'text',
text: 'Hello',
cache_control: { type: 'ephemeral' },
});
expect(result[1].content).toBe('Hi there');
});
test('should return original array if no user messages', () => {
const messages = [
{ role: 'assistant', content: 'Hi there' },
{ role: 'assistant', content: 'How can I help?' },
];
const result = addCacheControl(messages);
expect(result).toEqual(messages);
});
test('should handle empty array', () => {
const messages = [];
const result = addCacheControl(messages);
expect(result).toEqual([]);
});
test('should handle non-array input', () => {
const messages = 'not an array';
const result = addCacheControl(messages);
expect(result).toBe('not an array');
});
test('should not modify assistant messages', () => {
const messages = [
{ role: 'user', content: 'Hello' },
{ role: 'assistant', content: 'Hi there' },
{ role: 'user', content: 'How are you?' },
];
const result = addCacheControl(messages);
expect(result[1].content).toBe('Hi there');
});
test('should handle multiple content items in user messages', () => {
const messages = [
{
role: 'user',
content: [
{ type: 'text', text: 'Hello' },
{ type: 'image', url: 'http://example.com/image.jpg' },
{ type: 'text', text: 'This is an image' },
],
},
{ role: 'assistant', content: 'Hi there' },
{ role: 'user', content: 'How are you?' },
];
const result = addCacheControl(messages);
expect(result[0].content[0]).not.toHaveProperty('cache_control');
expect(result[0].content[1]).not.toHaveProperty('cache_control');
expect(result[0].content[2].cache_control).toEqual({ type: 'ephemeral' });
expect(result[2].content[0]).toEqual({
type: 'text',
text: 'How are you?',
cache_control: { type: 'ephemeral' },
});
});
test('should handle an array with mixed content types', () => {
const messages = [
{ role: 'user', content: 'Hello' },
{ role: 'assistant', content: 'Hi there' },
{ role: 'user', content: [{ type: 'text', text: 'How are you?' }] },
{ role: 'assistant', content: 'I\'m doing well, thanks!' },
{ role: 'user', content: 'Great!' },
];
const result = addCacheControl(messages);
expect(result[0].content).toEqual('Hello');
expect(result[2].content[0]).toEqual({
type: 'text',
text: 'How are you?',
cache_control: { type: 'ephemeral' },
});
expect(result[4].content).toEqual([
{
type: 'text',
text: 'Great!',
cache_control: { type: 'ephemeral' },
},
]);
expect(result[1].content).toBe('Hi there');
expect(result[3].content).toBe('I\'m doing well, thanks!');
});
test('should handle edge case with multiple content types', () => {
const messages = [
{
role: 'user',
content: [
{
type: 'image',
source: { type: 'base64', media_type: 'image/png', data: 'some_base64_string' },
},
{
type: 'image',
source: { type: 'base64', media_type: 'image/png', data: 'another_base64_string' },
},
{ type: 'text', text: 'what do all these images have in common' },
],
},
{ role: 'assistant', content: 'I see multiple images.' },
{ role: 'user', content: 'Correct!' },
];
const result = addCacheControl(messages);
expect(result[0].content[0]).not.toHaveProperty('cache_control');
expect(result[0].content[1]).not.toHaveProperty('cache_control');
expect(result[0].content[2].cache_control).toEqual({ type: 'ephemeral' });
expect(result[2].content[0]).toEqual({
type: 'text',
text: 'Correct!',
cache_control: { type: 'ephemeral' },
});
});
test('should handle user message with no text block', () => {
const messages = [
{
role: 'user',
content: [
{
type: 'image',
source: { type: 'base64', media_type: 'image/png', data: 'some_base64_string' },
},
{
type: 'image',
source: { type: 'base64', media_type: 'image/png', data: 'another_base64_string' },
},
],
},
{ role: 'assistant', content: 'I see two images.' },
{ role: 'user', content: 'Correct!' },
];
const result = addCacheControl(messages);
expect(result[0].content[0]).not.toHaveProperty('cache_control');
expect(result[0].content[1]).not.toHaveProperty('cache_control');
expect(result[2].content[0]).toEqual({
type: 'text',
text: 'Correct!',
cache_control: { type: 'ephemeral' },
});
});
});

View File

@@ -1,527 +0,0 @@
const dedent = require('dedent');
const { EModelEndpoint, ArtifactModes } = require('librechat-data-provider');
const { generateShadcnPrompt } = require('~/app/clients/prompts/shadcn-docs/generate');
const { components } = require('~/app/clients/prompts/shadcn-docs/components');
// eslint-disable-next-line no-unused-vars
const artifactsPromptV1 = dedent`The assistant can create and reference artifacts during conversations.
Artifacts are for substantial, self-contained content that users might modify or reuse, displayed in a separate UI window for clarity.
# Good artifacts are...
- Substantial content (>15 lines)
- Content that the user is likely to modify, iterate on, or take ownership of
- Self-contained, complex content that can be understood on its own, without context from the conversation
- Content intended for eventual use outside the conversation (e.g., reports, emails, presentations)
- Content likely to be referenced or reused multiple times
# Don't use artifacts for...
- Simple, informational, or short content, such as brief code snippets, mathematical equations, or small examples
- Primarily explanatory, instructional, or illustrative content, such as examples provided to clarify a concept
- Suggestions, commentary, or feedback on existing artifacts
- Conversational or explanatory content that doesn't represent a standalone piece of work
- Content that is dependent on the current conversational context to be useful
- Content that is unlikely to be modified or iterated upon by the user
- Request from users that appears to be a one-off question
# Usage notes
- One artifact per message unless specifically requested
- Prefer in-line content (don't use artifacts) when possible. Unnecessary use of artifacts can be jarring for users.
- If a user asks the assistant to "draw an SVG" or "make a website," the assistant does not need to explain that it doesn't have these capabilities. Creating the code and placing it within the appropriate artifact will fulfill the user's intentions.
- If asked to generate an image, the assistant can offer an SVG instead. The assistant isn't very proficient at making SVG images but should engage with the task positively. Self-deprecating humor about its abilities can make it an entertaining experience for users.
- The assistant errs on the side of simplicity and avoids overusing artifacts for content that can be effectively presented within the conversation.
- Always provide complete, specific, and fully functional content without any placeholders, ellipses, or 'remains the same' comments.
<artifact_instructions>
When collaborating with the user on creating content that falls into compatible categories, the assistant should follow these steps:
1. Create the artifact using the following format:
:::artifact{identifier="unique-identifier" type="mime-type" title="Artifact Title"}
\`\`\`
Your artifact content here
\`\`\`
:::
2. Assign an identifier to the \`identifier\` attribute. For updates, reuse the prior identifier. For new artifacts, the identifier should be descriptive and relevant to the content, using kebab-case (e.g., "example-code-snippet"). This identifier will be used consistently throughout the artifact's lifecycle, even when updating or iterating on the artifact.
3. Include a \`title\` attribute to provide a brief title or description of the content.
4. Add a \`type\` attribute to specify the type of content the artifact represents. Assign one of the following values to the \`type\` attribute:
- HTML: "text/html"
- The user interface can render single file HTML pages placed within the artifact tags. HTML, JS, and CSS should be in a single file when using the \`text/html\` type.
- Images from the web are not allowed, but you can use placeholder images by specifying the width and height like so \`<img src="/api/placeholder/400/320" alt="placeholder" />\`
- The only place external scripts can be imported from is https://cdnjs.cloudflare.com
- Mermaid Diagrams: "application/vnd.mermaid"
- The user interface will render Mermaid diagrams placed within the artifact tags.
- React Components: "application/vnd.react"
- Use this for displaying either: React elements, e.g. \`<strong>Hello World!</strong>\`, React pure functional components, e.g. \`() => <strong>Hello World!</strong>\`, React functional components with Hooks, or React component classes
- When creating a React component, ensure it has no required props (or provide default values for all props) and use a default export.
- Use Tailwind classes for styling. DO NOT USE ARBITRARY VALUES (e.g. \`h-[600px]\`).
- Base React is available to be imported. To use hooks, first import it at the top of the artifact, e.g. \`import { useState } from "react"\`
- The lucide-react@0.263.1 library is available to be imported. e.g. \`import { Camera } from "lucide-react"\` & \`<Camera color="red" size={48} />\`
- The recharts charting library is available to be imported, e.g. \`import { LineChart, XAxis, ... } from "recharts"\` & \`<LineChart ...><XAxis dataKey="name"> ...\`
- The assistant can use prebuilt components from the \`shadcn/ui\` library after it is imported: \`import { Alert, AlertDescription, AlertTitle, AlertDialog, AlertDialogAction } from '/components/ui/alert';\`. If using components from the shadcn/ui library, the assistant mentions this to the user and offers to help them install the components if necessary.
- Components MUST be imported from \`/components/ui/name\` and NOT from \`/components/name\` or \`@/components/ui/name\`.
- NO OTHER LIBRARIES (e.g. zod, hookform) ARE INSTALLED OR ABLE TO BE IMPORTED.
- Images from the web are not allowed, but you can use placeholder images by specifying the width and height like so \`<img src="/api/placeholder/400/320" alt="placeholder" />\`
- If you are unable to follow the above requirements for any reason, don't use artifacts and use regular code blocks instead, which will not attempt to render the component.
5. Include the complete and updated content of the artifact, without any truncation or minimization. Don't use "// rest of the code remains the same...".
6. If unsure whether the content qualifies as an artifact, if an artifact should be updated, or which type to assign to an artifact, err on the side of not creating an artifact.
7. Always use triple backticks (\`\`\`) to enclose the content within the artifact, regardless of the content type.
</artifact_instructions>
Here are some examples of correct usage of artifacts:
<examples>
<example_docstring>
This example demonstrates how to create a Mermaid artifact for a simple flow chart.
</example_docstring>
<example>
<user_query>Can you create a simple flow chart showing the process of making tea using Mermaid?</user_query>
<assistant_response>
Sure! Here's a simple flow chart depicting the process of making tea using Mermaid syntax:
:::artifact{identifier="tea-making-flowchart" type="application/vnd.mermaid" title="Flow chart: Making Tea"}
\`\`\`mermaid
graph TD
A[Start] --> B{Water boiled?}
B -->|Yes| C[Add tea leaves to cup]
B -->|No| D[Boil water]
D --> B
C --> E[Pour boiling water into cup]
E --> F[Steep tea for desired time]
F --> G[Remove tea leaves]
G --> H[Add milk or sugar, if desired]
H --> I[Enjoy your tea!]
I --> J[End]
\`\`\`
:::
This flow chart uses Mermaid syntax to visualize the steps involved in making a cup of tea. Here's a brief explanation of the process:
1. Start
2. Check if water is boiled
3. If not boiled, boil the water
4. Once water is boiled, add tea leaves to the cup
5. Pour boiling water into the cup
6. Steep the tea for the desired time
7. Remove the tea leaves
8. Optionally add milk or sugar
9. Enjoy your tea!
10. End
This chart provides a clear visual representation of the tea-making process. You can easily modify or expand this chart if you want to add more details or steps to the process. Let me know if you'd like any changes or have any questions!
</assistant_response>
</example>
</examples>`;
const artifactsPrompt = dedent`The assistant can create and reference artifacts during conversations.
Artifacts are for substantial, self-contained content that users might modify or reuse, displayed in a separate UI window for clarity.
# Good artifacts are...
- Substantial content (>15 lines)
- Content that the user is likely to modify, iterate on, or take ownership of
- Self-contained, complex content that can be understood on its own, without context from the conversation
- Content intended for eventual use outside the conversation (e.g., reports, emails, presentations)
- Content likely to be referenced or reused multiple times
# Don't use artifacts for...
- Simple, informational, or short content, such as brief code snippets, mathematical equations, or small examples
- Primarily explanatory, instructional, or illustrative content, such as examples provided to clarify a concept
- Suggestions, commentary, or feedback on existing artifacts
- Conversational or explanatory content that doesn't represent a standalone piece of work
- Content that is dependent on the current conversational context to be useful
- Content that is unlikely to be modified or iterated upon by the user
- Request from users that appears to be a one-off question
# Usage notes
- One artifact per message unless specifically requested
- Prefer in-line content (don't use artifacts) when possible. Unnecessary use of artifacts can be jarring for users.
- If a user asks the assistant to "draw an SVG" or "make a website," the assistant does not need to explain that it doesn't have these capabilities. Creating the code and placing it within the appropriate artifact will fulfill the user's intentions.
- If asked to generate an image, the assistant can offer an SVG instead. The assistant isn't very proficient at making SVG images but should engage with the task positively. Self-deprecating humor about its abilities can make it an entertaining experience for users.
- The assistant errs on the side of simplicity and avoids overusing artifacts for content that can be effectively presented within the conversation.
- Always provide complete, specific, and fully functional content for artifacts without any snippets, placeholders, ellipses, or 'remains the same' comments.
- If an artifact is not necessary or requested, the assistant should not mention artifacts at all, and respond to the user accordingly.
<artifact_instructions>
When collaborating with the user on creating content that falls into compatible categories, the assistant should follow these steps:
1. Create the artifact using the following format:
:::artifact{identifier="unique-identifier" type="mime-type" title="Artifact Title"}
\`\`\`
Your artifact content here
\`\`\`
:::
2. Assign an identifier to the \`identifier\` attribute. For updates, reuse the prior identifier. For new artifacts, the identifier should be descriptive and relevant to the content, using kebab-case (e.g., "example-code-snippet"). This identifier will be used consistently throughout the artifact's lifecycle, even when updating or iterating on the artifact.
3. Include a \`title\` attribute to provide a brief title or description of the content.
4. Add a \`type\` attribute to specify the type of content the artifact represents. Assign one of the following values to the \`type\` attribute:
- HTML: "text/html"
- The user interface can render single file HTML pages placed within the artifact tags. HTML, JS, and CSS should be in a single file when using the \`text/html\` type.
- Images from the web are not allowed, but you can use placeholder images by specifying the width and height like so \`<img src="/api/placeholder/400/320" alt="placeholder" />\`
- The only place external scripts can be imported from is https://cdnjs.cloudflare.com
- SVG: "image/svg+xml"
- The user interface will render the Scalable Vector Graphics (SVG) image within the artifact tags.
- The assistant should specify the viewbox of the SVG rather than defining a width/height
- Mermaid Diagrams: "application/vnd.mermaid"
- The user interface will render Mermaid diagrams placed within the artifact tags.
- React Components: "application/vnd.react"
- Use this for displaying either: React elements, e.g. \`<strong>Hello World!</strong>\`, React pure functional components, e.g. \`() => <strong>Hello World!</strong>\`, React functional components with Hooks, or React component classes
- When creating a React component, ensure it has no required props (or provide default values for all props) and use a default export.
- Use Tailwind classes for styling. DO NOT USE ARBITRARY VALUES (e.g. \`h-[600px]\`).
- Base React is available to be imported. To use hooks, first import it at the top of the artifact, e.g. \`import { useState } from "react"\`
- The lucide-react@0.394.0 library is available to be imported. e.g. \`import { Camera } from "lucide-react"\` & \`<Camera color="red" size={48} />\`
- The recharts charting library is available to be imported, e.g. \`import { LineChart, XAxis, ... } from "recharts"\` & \`<LineChart ...><XAxis dataKey="name"> ...\`
- The three.js library is available to be imported, e.g. \`import * as THREE from "three";\`
- The date-fns library is available to be imported, e.g. \`import { compareAsc, format } from "date-fns";\`
- The react-day-picker library is available to be imported, e.g. \`import { DayPicker } from "react-day-picker";\`
- The assistant can use prebuilt components from the \`shadcn/ui\` library after it is imported: \`import { Alert, AlertDescription, AlertTitle, AlertDialog, AlertDialogAction } from '/components/ui/alert';\`. If using components from the shadcn/ui library, the assistant mentions this to the user and offers to help them install the components if necessary.
- Components MUST be imported from \`/components/ui/name\` and NOT from \`/components/name\` or \`@/components/ui/name\`.
- NO OTHER LIBRARIES (e.g. zod, hookform) ARE INSTALLED OR ABLE TO BE IMPORTED.
- Images from the web are not allowed, but you can use placeholder images by specifying the width and height like so \`<img src="/api/placeholder/400/320" alt="placeholder" />\`
- When iterating on code, ensure that the code is complete and functional without any snippets, placeholders, or ellipses.
- If you are unable to follow the above requirements for any reason, don't use artifacts and use regular code blocks instead, which will not attempt to render the component.
5. Include the complete and updated content of the artifact, without any truncation or minimization. Don't use "// rest of the code remains the same...".
6. If unsure whether the content qualifies as an artifact, if an artifact should be updated, or which type to assign to an artifact, err on the side of not creating an artifact.
7. Always use triple backticks (\`\`\`) to enclose the content within the artifact, regardless of the content type.
</artifact_instructions>
Here are some examples of correct usage of artifacts:
<examples>
<example_docstring>
This example demonstrates how to create a Mermaid artifact for a simple flow chart.
</example_docstring>
<example>
<user_query>Can you create a simple flow chart showing the process of making tea using Mermaid?</user_query>
<assistant_response>
Sure! Here's a simple flow chart depicting the process of making tea using Mermaid syntax:
:::artifact{identifier="tea-making-flowchart" type="application/vnd.mermaid" title="Flow chart: Making Tea"}
\`\`\`mermaid
graph TD
A[Start] --> B{Water boiled?}
B -->|Yes| C[Add tea leaves to cup]
B -->|No| D[Boil water]
D --> B
C --> E[Pour boiling water into cup]
E --> F[Steep tea for desired time]
F --> G[Remove tea leaves]
G --> H[Add milk or sugar, if desired]
H --> I[Enjoy your tea!]
I --> J[End]
\`\`\`
:::
This flow chart uses Mermaid syntax to visualize the steps involved in making a cup of tea. Here's a brief explanation of the process:
1. Start
2. Check if water is boiled
3. If not boiled, boil the water
4. Once water is boiled, add tea leaves to the cup
5. Pour boiling water into the cup
6. Steep the tea for the desired time
7. Remove the tea leaves
8. Optionally add milk or sugar
9. Enjoy your tea!
10. End
This chart provides a clear visual representation of the tea-making process. You can easily modify or expand this chart if you want to add more details or steps to the process. Let me know if you'd like any changes or have any questions!
</assistant_response>
</example>
<example>
<user_query>Create a simple React counter component</user_query>
<assistant_response>
Here's a simple React counter component:
:::artifact{identifier="react-counter" type="application/vnd.react" title="React Counter"}
\`\`\`
import { useState } from 'react';
export default function Counter() {
const [count, setCount] = useState(0);
return (
<div className="p-4">
<p className="mb-2">Count: {count}</p>
<button className="bg-blue-500 text-white px-4 py-2 rounded" onClick={() => setCount(count + 1)}>
Increment
</button>
</div>
);
}
\`\`\`
:::
This component creates a simple counter with an increment button.
</assistant_response>
</example>
<example>
<user_query>Create a basic HTML structure for a blog post</user_query>
<assistant_response>
Here's a basic HTML structure for a blog post:
:::artifact{identifier="blog-post-html" type="text/html" title="Blog Post HTML"}
\`\`\`
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>My Blog Post</title>
<style>
body { font-family: Arial, sans-serif; line-height: 1.6; max-width: 800px; margin: 0 auto; padding: 20px; }
h1 { color: #333; }
p { margin-bottom: 15px; }
</style>
</head>
<body>
<header>
<h1>My First Blog Post</h1>
</header>
<main>
<article>
<p>This is the content of my blog post. It's short and sweet!</p>
</article>
</main>
<footer>
<p>&copy; 2023 My Blog</p>
</footer>
</body>
</html>
\`\`\`
:::
This HTML structure provides a simple layout for a blog post.
</assistant_response>
</example>
</examples>`;
const artifactsOpenAIPrompt = dedent`The assistant can create and reference artifacts during conversations.
Artifacts are for substantial, self-contained content that users might modify or reuse, displayed in a separate UI window for clarity.
# Good artifacts are...
- Substantial content (>15 lines)
- Content that the user is likely to modify, iterate on, or take ownership of
- Self-contained, complex content that can be understood on its own, without context from the conversation
- Content intended for eventual use outside the conversation (e.g., reports, emails, presentations)
- Content likely to be referenced or reused multiple times
# Don't use artifacts for...
- Simple, informational, or short content, such as brief code snippets, mathematical equations, or small examples
- Primarily explanatory, instructional, or illustrative content, such as examples provided to clarify a concept
- Suggestions, commentary, or feedback on existing artifacts
- Conversational or explanatory content that doesn't represent a standalone piece of work
- Content that is dependent on the current conversational context to be useful
- Content that is unlikely to be modified or iterated upon by the user
- Request from users that appears to be a one-off question
# Usage notes
- One artifact per message unless specifically requested
- Prefer in-line content (don't use artifacts) when possible. Unnecessary use of artifacts can be jarring for users.
- If a user asks the assistant to "draw an SVG" or "make a website," the assistant does not need to explain that it doesn't have these capabilities. Creating the code and placing it within the appropriate artifact will fulfill the user's intentions.
- If asked to generate an image, the assistant can offer an SVG instead. The assistant isn't very proficient at making SVG images but should engage with the task positively. Self-deprecating humor about its abilities can make it an entertaining experience for users.
- The assistant errs on the side of simplicity and avoids overusing artifacts for content that can be effectively presented within the conversation.
- Always provide complete, specific, and fully functional content for artifacts without any snippets, placeholders, ellipses, or 'remains the same' comments.
- If an artifact is not necessary or requested, the assistant should not mention artifacts at all, and respond to the user accordingly.
## Artifact Instructions
When collaborating with the user on creating content that falls into compatible categories, the assistant should follow these steps:
1. Create the artifact using the following remark-directive markdown format:
:::artifact{identifier="unique-identifier" type="mime-type" title="Artifact Title"}
\`\`\`
Your artifact content here
\`\`\`
:::
a. Example of correct format:
:::artifact{identifier="example-artifact" type="text/plain" title="Example Artifact"}
\`\`\`
This is the content of the artifact.
It can span multiple lines.
\`\`\`
:::
b. Common mistakes to avoid:
- Don't split the opening ::: line
- Don't add extra backticks outside the artifact structure
- Don't omit the closing :::
2. Assign an identifier to the \`identifier\` attribute. For updates, reuse the prior identifier. For new artifacts, the identifier should be descriptive and relevant to the content, using kebab-case (e.g., "example-code-snippet"). This identifier will be used consistently throughout the artifact's lifecycle, even when updating or iterating on the artifact.
3. Include a \`title\` attribute to provide a brief title or description of the content.
4. Add a \`type\` attribute to specify the type of content the artifact represents. Assign one of the following values to the \`type\` attribute:
- HTML: "text/html"
- The user interface can render single file HTML pages placed within the artifact tags. HTML, JS, and CSS should be in a single file when using the \`text/html\` type.
- Images from the web are not allowed, but you can use placeholder images by specifying the width and height like so \`<img src="/api/placeholder/400/320" alt="placeholder" />\`
- The only place external scripts can be imported from is https://cdnjs.cloudflare.com
- SVG: "image/svg+xml"
- The user interface will render the Scalable Vector Graphics (SVG) image within the artifact tags.
- The assistant should specify the viewbox of the SVG rather than defining a width/height
- Mermaid Diagrams: "application/vnd.mermaid"
- The user interface will render Mermaid diagrams placed within the artifact tags.
- React Components: "application/vnd.react"
- Use this for displaying either: React elements, e.g. \`<strong>Hello World!</strong>\`, React pure functional components, e.g. \`() => <strong>Hello World!</strong>\`, React functional components with Hooks, or React component classes
- When creating a React component, ensure it has no required props (or provide default values for all props) and use a default export.
- Use Tailwind classes for styling. DO NOT USE ARBITRARY VALUES (e.g. \`h-[600px]\`).
- Base React is available to be imported. To use hooks, first import it at the top of the artifact, e.g. \`import { useState } from "react"\`
- The lucide-react@0.394.0 library is available to be imported. e.g. \`import { Camera } from "lucide-react"\` & \`<Camera color="red" size={48} />\`
- The recharts charting library is available to be imported, e.g. \`import { LineChart, XAxis, ... } from "recharts"\` & \`<LineChart ...><XAxis dataKey="name"> ...\`
- The three.js library is available to be imported, e.g. \`import * as THREE from "three";\`
- The date-fns library is available to be imported, e.g. \`import { compareAsc, format } from "date-fns";\`
- The react-day-picker library is available to be imported, e.g. \`import { DayPicker } from "react-day-picker";\`
- The assistant can use prebuilt components from the \`shadcn/ui\` library after it is imported: \`import { Alert, AlertDescription, AlertTitle, AlertDialog, AlertDialogAction } from '/components/ui/alert';\`. If using components from the shadcn/ui library, the assistant mentions this to the user and offers to help them install the components if necessary.
- Components MUST be imported from \`/components/ui/name\` and NOT from \`/components/name\` or \`@/components/ui/name\`.
- NO OTHER LIBRARIES (e.g. zod, hookform) ARE INSTALLED OR ABLE TO BE IMPORTED.
- Images from the web are not allowed, but you can use placeholder images by specifying the width and height like so \`<img src="/api/placeholder/400/320" alt="placeholder" />\`
- When iterating on code, ensure that the code is complete and functional without any snippets, placeholders, or ellipses.
- If you are unable to follow the above requirements for any reason, don't use artifacts and use regular code blocks instead, which will not attempt to render the component.
5. Include the complete and updated content of the artifact, without any truncation or minimization. Don't use "// rest of the code remains the same...".
6. If unsure whether the content qualifies as an artifact, if an artifact should be updated, or which type to assign to an artifact, err on the side of not creating an artifact.
7. NEVER use triple backticks to enclose the artifact, ONLY the content within the artifact.
Here are some examples of correct usage of artifacts:
## Examples
### Example 1
This example demonstrates how to create a Mermaid artifact for a simple flow chart.
User: Can you create a simple flow chart showing the process of making tea using Mermaid?
Assistant: Sure! Here's a simple flow chart depicting the process of making tea using Mermaid syntax:
:::artifact{identifier="tea-making-flowchart" type="application/vnd.mermaid" title="Flow chart: Making Tea"}
\`\`\`mermaid
graph TD
A[Start] --> B{Water boiled?}
B -->|Yes| C[Add tea leaves to cup]
B -->|No| D[Boil water]
D --> B
C --> E[Pour boiling water into cup]
E --> F[Steep tea for desired time]
F --> G[Remove tea leaves]
G --> H[Add milk or sugar, if desired]
H --> I[Enjoy your tea!]
I --> J[End]
\`\`\`
:::
This flow chart uses Mermaid syntax to visualize the steps involved in making a cup of tea. Here's a brief explanation of the process:
1. Start
2. Check if water is boiled
3. If not boiled, boil the water
4. Once water is boiled, add tea leaves to the cup
5. Pour boiling water into the cup
6. Steep the tea for the desired time
7. Remove the tea leaves
8. Optionally add milk or sugar
9. Enjoy your tea!
10. End
This chart provides a clear visual representation of the tea-making process. You can easily modify or expand this chart if you want to add more details or steps to the process. Let me know if you'd like any changes or have any questions!
---
### Example 2
User: Create a simple React counter component
Assistant: Here's a simple React counter component:
:::artifact{identifier="react-counter" type="application/vnd.react" title="React Counter"}
\`\`\`
import { useState } from 'react';
export default function Counter() {
const [count, setCount] = useState(0);
return (
<div className="p-4">
<p className="mb-2">Count: {count}</p>
<button className="bg-blue-500 text-white px-4 py-2 rounded" onClick={() => setCount(count + 1)}>
Increment
</button>
</div>
);
}
\`\`\`
:::
This component creates a simple counter with an increment button.
---
### Example 3
User: Create a basic HTML structure for a blog post
Assistant: Here's a basic HTML structure for a blog post:
:::artifact{identifier="blog-post-html" type="text/html" title="Blog Post HTML"}
\`\`\`
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>My Blog Post</title>
<style>
body { font-family: Arial, sans-serif; line-height: 1.6; max-width: 800px; margin: 0 auto; padding: 20px; }
h1 { color: #333; }
p { margin-bottom: 15px; }
</style>
</head>
<body>
<header>
<h1>My First Blog Post</h1>
</header>
<main>
<article>
<p>This is the content of my blog post. It's short and sweet!</p>
</article>
</main>
<footer>
<p>&copy; 2023 My Blog</p>
</footer>
</body>
</html>
\`\`\`
:::
This HTML structure provides a simple layout for a blog post.
---`;
/**
*
* @param {Object} params
* @param {EModelEndpoint | string} params.endpoint - The current endpoint
* @param {ArtifactModes} params.artifacts - The current artifact mode
* @returns
*/
const generateArtifactsPrompt = ({ endpoint, artifacts }) => {
if (artifacts === ArtifactModes.CUSTOM) {
return null;
}
let prompt = artifactsPrompt;
if (endpoint !== EModelEndpoint.anthropic) {
prompt = artifactsOpenAIPrompt;
}
if (artifacts === ArtifactModes.SHADCNUI) {
prompt += generateShadcnPrompt({ components, useXML: endpoint === EModelEndpoint.anthropic });
}
return prompt;
};
module.exports = generateArtifactsPrompt;

View File

@@ -1,285 +0,0 @@
const { ToolMessage } = require('@langchain/core/messages');
const { ContentTypes } = require('librechat-data-provider');
const { HumanMessage, AIMessage, SystemMessage } = require('langchain/schema');
const { formatAgentMessages } = require('./formatMessages');
describe('formatAgentMessages', () => {
it('should format simple user and AI messages', () => {
const payload = [
{ role: 'user', content: 'Hello' },
{ role: 'assistant', content: 'Hi there!' },
];
const result = formatAgentMessages(payload);
expect(result).toHaveLength(2);
expect(result[0]).toBeInstanceOf(HumanMessage);
expect(result[1]).toBeInstanceOf(AIMessage);
});
it('should handle system messages', () => {
const payload = [{ role: 'system', content: 'You are a helpful assistant.' }];
const result = formatAgentMessages(payload);
expect(result).toHaveLength(1);
expect(result[0]).toBeInstanceOf(SystemMessage);
});
it('should format messages with content arrays', () => {
const payload = [
{
role: 'user',
content: [{ type: ContentTypes.TEXT, [ContentTypes.TEXT]: 'Hello' }],
},
];
const result = formatAgentMessages(payload);
expect(result).toHaveLength(1);
expect(result[0]).toBeInstanceOf(HumanMessage);
});
it('should handle tool calls and create ToolMessages', () => {
const payload = [
{
role: 'assistant',
content: [
{
type: ContentTypes.TEXT,
[ContentTypes.TEXT]: 'Let me check that for you.',
tool_call_ids: ['123'],
},
{
type: ContentTypes.TOOL_CALL,
tool_call: {
id: '123',
name: 'search',
args: '{"query":"weather"}',
output: 'The weather is sunny.',
},
},
],
},
];
const result = formatAgentMessages(payload);
expect(result).toHaveLength(2);
expect(result[0]).toBeInstanceOf(AIMessage);
expect(result[1]).toBeInstanceOf(ToolMessage);
expect(result[0].tool_calls).toHaveLength(1);
expect(result[1].tool_call_id).toBe('123');
});
it('should handle multiple content parts in assistant messages', () => {
const payload = [
{
role: 'assistant',
content: [
{ type: ContentTypes.TEXT, [ContentTypes.TEXT]: 'Part 1' },
{ type: ContentTypes.TEXT, [ContentTypes.TEXT]: 'Part 2' },
],
},
];
const result = formatAgentMessages(payload);
expect(result).toHaveLength(1);
expect(result[0]).toBeInstanceOf(AIMessage);
expect(result[0].content).toHaveLength(2);
});
it('should throw an error for invalid tool call structure', () => {
const payload = [
{
role: 'assistant',
content: [
{
type: ContentTypes.TOOL_CALL,
tool_call: {
id: '123',
name: 'search',
args: '{"query":"weather"}',
output: 'The weather is sunny.',
},
},
],
},
];
expect(() => formatAgentMessages(payload)).toThrow('Invalid tool call structure');
});
it('should handle tool calls with non-JSON args', () => {
const payload = [
{
role: 'assistant',
content: [
{ type: ContentTypes.TEXT, [ContentTypes.TEXT]: 'Checking...', tool_call_ids: ['123'] },
{
type: ContentTypes.TOOL_CALL,
tool_call: {
id: '123',
name: 'search',
args: 'non-json-string',
output: 'Result',
},
},
],
},
];
const result = formatAgentMessages(payload);
expect(result).toHaveLength(2);
expect(result[0].tool_calls[0].args).toBe('non-json-string');
});
it('should handle complex tool calls with multiple steps', () => {
const payload = [
{
role: 'assistant',
content: [
{
type: ContentTypes.TEXT,
[ContentTypes.TEXT]: 'I\'ll search for that information.',
tool_call_ids: ['search_1'],
},
{
type: ContentTypes.TOOL_CALL,
tool_call: {
id: 'search_1',
name: 'search',
args: '{"query":"weather in New York"}',
output: 'The weather in New York is currently sunny with a temperature of 75°F.',
},
},
{
type: ContentTypes.TEXT,
[ContentTypes.TEXT]: 'Now, I\'ll convert the temperature.',
tool_call_ids: ['convert_1'],
},
{
type: ContentTypes.TOOL_CALL,
tool_call: {
id: 'convert_1',
name: 'convert_temperature',
args: '{"temperature": 75, "from": "F", "to": "C"}',
output: '23.89°C',
},
},
{ type: ContentTypes.TEXT, [ContentTypes.TEXT]: 'Here\'s your answer.' },
],
},
];
const result = formatAgentMessages(payload);
expect(result).toHaveLength(5);
expect(result[0]).toBeInstanceOf(AIMessage);
expect(result[1]).toBeInstanceOf(ToolMessage);
expect(result[2]).toBeInstanceOf(AIMessage);
expect(result[3]).toBeInstanceOf(ToolMessage);
expect(result[4]).toBeInstanceOf(AIMessage);
// Check first AIMessage
expect(result[0].content).toBe('I\'ll search for that information.');
expect(result[0].tool_calls).toHaveLength(1);
expect(result[0].tool_calls[0]).toEqual({
id: 'search_1',
name: 'search',
args: { query: 'weather in New York' },
});
// Check first ToolMessage
expect(result[1].tool_call_id).toBe('search_1');
expect(result[1].name).toBe('search');
expect(result[1].content).toBe(
'The weather in New York is currently sunny with a temperature of 75°F.',
);
// Check second AIMessage
expect(result[2].content).toBe('Now, I\'ll convert the temperature.');
expect(result[2].tool_calls).toHaveLength(1);
expect(result[2].tool_calls[0]).toEqual({
id: 'convert_1',
name: 'convert_temperature',
args: { temperature: 75, from: 'F', to: 'C' },
});
// Check second ToolMessage
expect(result[3].tool_call_id).toBe('convert_1');
expect(result[3].name).toBe('convert_temperature');
expect(result[3].content).toBe('23.89°C');
// Check final AIMessage
expect(result[4].content).toStrictEqual([
{ [ContentTypes.TEXT]: 'Here\'s your answer.', type: ContentTypes.TEXT },
]);
});
it.skip('should not produce two consecutive assistant messages and format content correctly', () => {
const payload = [
{ role: 'user', content: 'Hello' },
{
role: 'assistant',
content: [{ type: ContentTypes.TEXT, [ContentTypes.TEXT]: 'Hi there!' }],
},
{
role: 'assistant',
content: [{ type: ContentTypes.TEXT, [ContentTypes.TEXT]: 'How can I help you?' }],
},
{ role: 'user', content: 'What\'s the weather?' },
{
role: 'assistant',
content: [
{
type: ContentTypes.TEXT,
[ContentTypes.TEXT]: 'Let me check that for you.',
tool_call_ids: ['weather_1'],
},
{
type: ContentTypes.TOOL_CALL,
tool_call: {
id: 'weather_1',
name: 'check_weather',
args: '{"location":"New York"}',
output: 'Sunny, 75°F',
},
},
],
},
{
role: 'assistant',
content: [
{ type: ContentTypes.TEXT, [ContentTypes.TEXT]: 'Here\'s the weather information.' },
],
},
];
const result = formatAgentMessages(payload);
// Check correct message count and types
expect(result).toHaveLength(6);
expect(result[0]).toBeInstanceOf(HumanMessage);
expect(result[1]).toBeInstanceOf(AIMessage);
expect(result[2]).toBeInstanceOf(HumanMessage);
expect(result[3]).toBeInstanceOf(AIMessage);
expect(result[4]).toBeInstanceOf(ToolMessage);
expect(result[5]).toBeInstanceOf(AIMessage);
// Check content of messages
expect(result[0].content).toStrictEqual([
{ [ContentTypes.TEXT]: 'Hello', type: ContentTypes.TEXT },
]);
expect(result[1].content).toStrictEqual([
{ [ContentTypes.TEXT]: 'Hi there!', type: ContentTypes.TEXT },
{ [ContentTypes.TEXT]: 'How can I help you?', type: ContentTypes.TEXT },
]);
expect(result[2].content).toStrictEqual([
{ [ContentTypes.TEXT]: 'What\'s the weather?', type: ContentTypes.TEXT },
]);
expect(result[3].content).toBe('Let me check that for you.');
expect(result[4].content).toBe('Sunny, 75°F');
expect(result[5].content).toStrictEqual([
{ [ContentTypes.TEXT]: 'Here\'s the weather information.', type: ContentTypes.TEXT },
]);
// Check that there are no consecutive AIMessages
const messageTypes = result.map((message) => message.constructor);
for (let i = 0; i < messageTypes.length - 1; i++) {
expect(messageTypes[i] === AIMessage && messageTypes[i + 1] === AIMessage).toBe(false);
}
// Additional check to ensure the consecutive assistant messages were combined
expect(result[1].content).toHaveLength(2);
});
});

View File

@@ -1,5 +1,4 @@
const { ToolMessage } = require('@langchain/core/messages');
const { EModelEndpoint, ContentTypes } = require('librechat-data-provider');
const { EModelEndpoint } = require('librechat-data-provider');
const { HumanMessage, AIMessage, SystemMessage } = require('langchain/schema');
/**
@@ -15,11 +14,11 @@ const { HumanMessage, AIMessage, SystemMessage } = require('langchain/schema');
*/
const formatVisionMessage = ({ message, image_urls, endpoint }) => {
if (endpoint === EModelEndpoint.anthropic) {
message.content = [...image_urls, { type: ContentTypes.TEXT, text: message.content }];
message.content = [...image_urls, { type: 'text', text: message.content }];
return message;
}
message.content = [{ type: ContentTypes.TEXT, text: message.content }, ...image_urls];
message.content = [{ type: 'text', text: message.content }, ...image_urls];
return message;
};
@@ -52,7 +51,7 @@ const formatMessage = ({ message, userName, assistantName, endpoint, langChain =
_role = roleMapping[lc_id[2]];
}
const role = _role ?? (sender && sender?.toLowerCase() === 'user' ? 'user' : 'assistant');
const content = _content ?? text ?? '';
const content = text ?? _content ?? '';
const formattedMessage = {
role,
content,
@@ -132,94 +131,4 @@ const formatFromLangChain = (message) => {
};
};
/**
* Formats an array of messages for LangChain, handling tool calls and creating ToolMessage instances.
*
* @param {Array<Partial<TMessage>>} payload - The array of messages to format.
* @returns {Array<(HumanMessage|AIMessage|SystemMessage|ToolMessage)>} - The array of formatted LangChain messages, including ToolMessages for tool calls.
*/
const formatAgentMessages = (payload) => {
const messages = [];
for (const message of payload) {
if (typeof message.content === 'string') {
message.content = [{ type: ContentTypes.TEXT, [ContentTypes.TEXT]: message.content }];
}
if (message.role !== 'assistant') {
messages.push(formatMessage({ message, langChain: true }));
continue;
}
let currentContent = [];
let lastAIMessage = null;
for (const part of message.content) {
if (part.type === ContentTypes.TEXT && part.tool_call_ids) {
/*
If there's pending content, it needs to be aggregated as a single string to prepare for tool calls.
For Anthropic models, the "tool_calls" field on a message is only respected if content is a string.
*/
if (currentContent.length > 0) {
let content = currentContent.reduce((acc, curr) => {
if (curr.type === ContentTypes.TEXT) {
return `${acc}${curr[ContentTypes.TEXT]}\n`;
}
return acc;
}, '');
content = `${content}\n${part[ContentTypes.TEXT] ?? ''}`.trim();
lastAIMessage = new AIMessage({ content });
messages.push(lastAIMessage);
currentContent = [];
continue;
}
// Create a new AIMessage with this text and prepare for tool calls
lastAIMessage = new AIMessage({
content: part.text || '',
});
messages.push(lastAIMessage);
} else if (part.type === ContentTypes.TOOL_CALL) {
if (!lastAIMessage) {
throw new Error('Invalid tool call structure: No preceding AIMessage with tool_call_ids');
}
// Note: `tool_calls` list is defined when constructed by `AIMessage` class, and outputs should be excluded from it
const { output, args: _args, ...tool_call } = part.tool_call;
// TODO: investigate; args as dictionary may need to be provider-or-tool-specific
let args = _args;
try {
args = JSON.parse(args);
} catch (e) {
// failed to parse, leave as is
}
tool_call.args = args;
lastAIMessage.tool_calls.push(tool_call);
// Add the corresponding ToolMessage
messages.push(
new ToolMessage({
tool_call_id: tool_call.id,
name: tool_call.name,
content: output,
}),
);
} else {
currentContent.push(part);
}
}
if (currentContent.length > 0) {
messages.push(new AIMessage({ content: currentContent }));
}
}
return messages;
};
module.exports = {
formatMessage,
formatFromLangChain,
formatAgentMessages,
formatLangChainMessages,
};
module.exports = { formatMessage, formatLangChainMessages, formatFromLangChain };

View File

@@ -1,4 +1,3 @@
const addCacheControl = require('./addCacheControl');
const formatMessages = require('./formatMessages');
const summaryPrompts = require('./summaryPrompts');
const handleInputs = require('./handleInputs');
@@ -9,7 +8,6 @@ const createVisionPrompt = require('./createVisionPrompt');
const createContextHandlers = require('./createContextHandlers');
module.exports = {
addCacheControl,
...formatMessages,
...summaryPrompts,
...handleInputs,

View File

@@ -1,495 +0,0 @@
// Essential Components
const essentialComponents = {
avatar: {
componentName: 'Avatar',
importDocs: 'import { Avatar, AvatarFallback, AvatarImage } from "/components/ui/avatar"',
usageDocs: `
<Avatar>
<AvatarImage src="https://github.com/shadcn.png" />
<AvatarFallback>CN</AvatarFallback>
</Avatar>`,
},
button: {
componentName: 'Button',
importDocs: 'import { Button } from "/components/ui/button"',
usageDocs: `
<Button variant="outline">Button</Button>`,
},
card: {
componentName: 'Card',
importDocs: `
import {
Card,
CardContent,
CardDescription,
CardFooter,
CardHeader,
CardTitle,
} from "/components/ui/card"`,
usageDocs: `
<Card>
<CardHeader>
<CardTitle>Card Title</CardTitle>
<CardDescription>Card Description</CardDescription>
</CardHeader>
<CardContent>
<p>Card Content</p>
</CardContent>
<CardFooter>
<p>Card Footer</p>
</CardFooter>
</Card>`,
},
checkbox: {
componentName: 'Checkbox',
importDocs: 'import { Checkbox } from "/components/ui/checkbox"',
usageDocs: '<Checkbox />',
},
input: {
componentName: 'Input',
importDocs: 'import { Input } from "/components/ui/input"',
usageDocs: '<Input />',
},
label: {
componentName: 'Label',
importDocs: 'import { Label } from "/components/ui/label"',
usageDocs: '<Label htmlFor="email">Your email address</Label>',
},
radioGroup: {
componentName: 'RadioGroup',
importDocs: `
import { Label } from "/components/ui/label"
import { RadioGroup, RadioGroupItem } from "/components/ui/radio-group"`,
usageDocs: `
<RadioGroup defaultValue="option-one">
<div className="flex items-center space-x-2">
<RadioGroupItem value="option-one" id="option-one" />
<Label htmlFor="option-one">Option One</Label>
</div>
<div className="flex items-center space-x-2">
<RadioGroupItem value="option-two" id="option-two" />
<Label htmlFor="option-two">Option Two</Label>
</div>
</RadioGroup>`,
},
select: {
componentName: 'Select',
importDocs: `
import {
Select,
SelectContent,
SelectItem,
SelectTrigger,
SelectValue,
} from "/components/ui/select"`,
usageDocs: `
<Select>
<SelectTrigger className="w-[180px]">
<SelectValue placeholder="Theme" />
</SelectTrigger>
<SelectContent>
<SelectItem value="light">Light</SelectItem>
<SelectItem value="dark">Dark</SelectItem>
<SelectItem value="system">System</SelectItem>
</SelectContent>
</Select>`,
},
textarea: {
componentName: 'Textarea',
importDocs: 'import { Textarea } from "/components/ui/textarea"',
usageDocs: '<Textarea />',
},
};
// Extra Components
const extraComponents = {
accordion: {
componentName: 'Accordion',
importDocs: `
import {
Accordion,
AccordionContent,
AccordionItem,
AccordionTrigger,
} from "/components/ui/accordion"`,
usageDocs: `
<Accordion type="single" collapsible>
<AccordionItem value="item-1">
<AccordionTrigger>Is it accessible?</AccordionTrigger>
<AccordionContent>
Yes. It adheres to the WAI-ARIA design pattern.
</AccordionContent>
</AccordionItem>
</Accordion>`,
},
alertDialog: {
componentName: 'AlertDialog',
importDocs: `
import {
AlertDialog,
AlertDialogAction,
AlertDialogCancel,
AlertDialogContent,
AlertDialogDescription,
AlertDialogFooter,
AlertDialogHeader,
AlertDialogTitle,
AlertDialogTrigger,
} from "/components/ui/alert-dialog"`,
usageDocs: `
<AlertDialog>
<AlertDialogTrigger>Open</AlertDialogTrigger>
<AlertDialogContent>
<AlertDialogHeader>
<AlertDialogTitle>Are you absolutely sure?</AlertDialogTitle>
<AlertDialogDescription>
This action cannot be undone.
</AlertDialogDescription>
</AlertDialogHeader>
<AlertDialogFooter>
<AlertDialogCancel>Cancel</AlertDialogCancel>
<AlertDialogAction>Continue</AlertDialogAction>
</AlertDialogFooter>
</AlertDialogContent>
</AlertDialog>`,
},
alert: {
componentName: 'Alert',
importDocs: `
import {
Alert,
AlertDescription,
AlertTitle,
} from "/components/ui/alert"`,
usageDocs: `
<Alert>
<AlertTitle>Heads up!</AlertTitle>
<AlertDescription>
You can add components to your app using the cli.
</AlertDescription>
</Alert>`,
},
aspectRatio: {
componentName: 'AspectRatio',
importDocs: 'import { AspectRatio } from "/components/ui/aspect-ratio"',
usageDocs: `
<AspectRatio ratio={16 / 9}>
<Image src="..." alt="Image" className="rounded-md object-cover" />
</AspectRatio>`,
},
badge: {
componentName: 'Badge',
importDocs: 'import { Badge } from "/components/ui/badge"',
usageDocs: '<Badge>Badge</Badge>',
},
calendar: {
componentName: 'Calendar',
importDocs: 'import { Calendar } from "/components/ui/calendar"',
usageDocs: '<Calendar />',
},
carousel: {
componentName: 'Carousel',
importDocs: `
import {
Carousel,
CarouselContent,
CarouselItem,
CarouselNext,
CarouselPrevious,
} from "/components/ui/carousel"`,
usageDocs: `
<Carousel>
<CarouselContent>
<CarouselItem>...</CarouselItem>
<CarouselItem>...</CarouselItem>
<CarouselItem>...</CarouselItem>
</CarouselContent>
<CarouselPrevious />
<CarouselNext />
</Carousel>`,
},
collapsible: {
componentName: 'Collapsible',
importDocs: `
import {
Collapsible,
CollapsibleContent,
CollapsibleTrigger,
} from "/components/ui/collapsible"`,
usageDocs: `
<Collapsible>
<CollapsibleTrigger>Can I use this in my project?</CollapsibleTrigger>
<CollapsibleContent>
Yes. Free to use for personal and commercial projects. No attribution required.
</CollapsibleContent>
</Collapsible>`,
},
dialog: {
componentName: 'Dialog',
importDocs: `
import {
Dialog,
DialogContent,
DialogDescription,
DialogHeader,
DialogTitle,
DialogTrigger,
} from "/components/ui/dialog"`,
usageDocs: `
<Dialog>
<DialogTrigger>Open</DialogTrigger>
<DialogContent>
<DialogHeader>
<DialogTitle>Are you sure absolutely sure?</DialogTitle>
<DialogDescription>
This action cannot be undone.
</DialogDescription>
</DialogHeader>
</DialogContent>
</Dialog>`,
},
dropdownMenu: {
componentName: 'DropdownMenu',
importDocs: `
import {
DropdownMenu,
DropdownMenuContent,
DropdownMenuItem,
DropdownMenuLabel,
DropdownMenuSeparator,
DropdownMenuTrigger,
} from "/components/ui/dropdown-menu"`,
usageDocs: `
<DropdownMenu>
<DropdownMenuTrigger>Open</DropdownMenuTrigger>
<DropdownMenuContent>
<DropdownMenuLabel>My Account</DropdownMenuLabel>
<DropdownMenuSeparator />
<DropdownMenuItem>Profile</DropdownMenuItem>
<DropdownMenuItem>Billing</DropdownMenuItem>
<DropdownMenuItem>Team</DropdownMenuItem>
<DropdownMenuItem>Subscription</DropdownMenuItem>
</DropdownMenuContent>
</DropdownMenu>`,
},
menubar: {
componentName: 'Menubar',
importDocs: `
import {
Menubar,
MenubarContent,
MenubarItem,
MenubarMenu,
MenubarSeparator,
MenubarShortcut,
MenubarTrigger,
} from "/components/ui/menubar"`,
usageDocs: `
<Menubar>
<MenubarMenu>
<MenubarTrigger>File</MenubarTrigger>
<MenubarContent>
<MenubarItem>
New Tab <MenubarShortcut>⌘T</MenubarShortcut>
</MenubarItem>
<MenubarItem>New Window</MenubarItem>
<MenubarSeparator />
<MenubarItem>Share</MenubarItem>
<MenubarSeparator />
<MenubarItem>Print</MenubarItem>
</MenubarContent>
</MenubarMenu>
</Menubar>`,
},
navigationMenu: {
componentName: 'NavigationMenu',
importDocs: `
import {
NavigationMenu,
NavigationMenuContent,
NavigationMenuItem,
NavigationMenuLink,
NavigationMenuList,
NavigationMenuTrigger,
navigationMenuTriggerStyle,
} from "/components/ui/navigation-menu"`,
usageDocs: `
<NavigationMenu>
<NavigationMenuList>
<NavigationMenuItem>
<NavigationMenuTrigger>Item One</NavigationMenuTrigger>
<NavigationMenuContent>
<NavigationMenuLink>Link</NavigationMenuLink>
</NavigationMenuContent>
</NavigationMenuItem>
</NavigationMenuList>
</NavigationMenu>`,
},
popover: {
componentName: 'Popover',
importDocs: `
import {
Popover,
PopoverContent,
PopoverTrigger,
} from "/components/ui/popover"`,
usageDocs: `
<Popover>
<PopoverTrigger>Open</PopoverTrigger>
<PopoverContent>Place content for the popover here.</PopoverContent>
</Popover>`,
},
progress: {
componentName: 'Progress',
importDocs: 'import { Progress } from "/components/ui/progress"',
usageDocs: '<Progress value={33} />',
},
separator: {
componentName: 'Separator',
importDocs: 'import { Separator } from "/components/ui/separator"',
usageDocs: '<Separator />',
},
sheet: {
componentName: 'Sheet',
importDocs: `
import {
Sheet,
SheetContent,
SheetDescription,
SheetHeader,
SheetTitle,
SheetTrigger,
} from "/components/ui/sheet"`,
usageDocs: `
<Sheet>
<SheetTrigger>Open</SheetTrigger>
<SheetContent>
<SheetHeader>
<SheetTitle>Are you sure absolutely sure?</SheetTitle>
<SheetDescription>
This action cannot be undone.
</SheetDescription>
</SheetHeader>
</SheetContent>
</Sheet>`,
},
skeleton: {
componentName: 'Skeleton',
importDocs: 'import { Skeleton } from "/components/ui/skeleton"',
usageDocs: '<Skeleton className="w-[100px] h-[20px] rounded-full" />',
},
slider: {
componentName: 'Slider',
importDocs: 'import { Slider } from "/components/ui/slider"',
usageDocs: '<Slider defaultValue={[33]} max={100} step={1} />',
},
switch: {
componentName: 'Switch',
importDocs: 'import { Switch } from "/components/ui/switch"',
usageDocs: '<Switch />',
},
table: {
componentName: 'Table',
importDocs: `
import {
Table,
TableBody,
TableCaption,
TableCell,
TableHead,
TableHeader,
TableRow,
} from "/components/ui/table"`,
usageDocs: `
<Table>
<TableCaption>A list of your recent invoices.</TableCaption>
<TableHeader>
<TableRow>
<TableHead className="w-[100px]">Invoice</TableHead>
<TableHead>Status</TableHead>
<TableHead>Method</TableHead>
<TableHead className="text-right">Amount</TableHead>
</TableRow>
</TableHeader>
<TableBody>
<TableRow>
<TableCell className="font-medium">INV001</TableCell>
<TableCell>Paid</TableCell>
<TableCell>Credit Card</TableCell>
<TableCell className="text-right">$250.00</TableCell>
</TableRow>
</TableBody>
</Table>`,
},
tabs: {
componentName: 'Tabs',
importDocs: `
import {
Tabs,
TabsContent,
TabsList,
TabsTrigger,
} from "/components/ui/tabs"`,
usageDocs: `
<Tabs defaultValue="account" className="w-[400px]">
<TabsList>
<TabsTrigger value="account">Account</TabsTrigger>
<TabsTrigger value="password">Password</TabsTrigger>
</TabsList>
<TabsContent value="account">Make changes to your account here.</TabsContent>
<TabsContent value="password">Change your password here.</TabsContent>
</Tabs>`,
},
toast: {
componentName: 'Toast',
importDocs: `
import { useToast } from "/components/ui/use-toast"
import { Button } from "/components/ui/button"`,
usageDocs: `
export function ToastDemo() {
const { toast } = useToast()
return (
<Button
onClick={() => {
toast({
title: "Scheduled: Catch up",
description: "Friday, February 10, 2023 at 5:57 PM",
})
}}
>
Show Toast
</Button>
)
}`,
},
toggle: {
componentName: 'Toggle',
importDocs: 'import { Toggle } from "/components/ui/toggle"',
usageDocs: '<Toggle>Toggle</Toggle>',
},
tooltip: {
componentName: 'Tooltip',
importDocs: `
import {
Tooltip,
TooltipContent,
TooltipProvider,
TooltipTrigger,
} from "/components/ui/tooltip"`,
usageDocs: `
<TooltipProvider>
<Tooltip>
<TooltipTrigger>Hover</TooltipTrigger>
<TooltipContent>
<p>Add to library</p>
</TooltipContent>
</Tooltip>
</TooltipProvider>`,
},
};
const components = Object.assign({}, essentialComponents, extraComponents);
module.exports = {
components,
};

View File

@@ -1,50 +0,0 @@
const dedent = require('dedent');
/**
* Generate system prompt for AI-assisted React component creation
* @param {Object} options - Configuration options
* @param {Object} options.components - Documentation for shadcn components
* @param {boolean} [options.useXML=false] - Whether to use XML-style formatting for component instructions
* @returns {string} The generated system prompt
*/
function generateShadcnPrompt(options) {
const { components, useXML = false } = options;
let systemPrompt = dedent`
## Additional Artifact Instructions for React Components: "application/vnd.react"
There are some prestyled components (primitives) available for use. Please use your best judgement to use any of these components if the app calls for one.
Here are the components that are available, along with how to import them, and how to use them:
${Object.values(components)
.map((component) => {
if (useXML) {
return dedent`
<component>
<name>${component.componentName}</name>
<import-instructions>${component.importDocs}</import-instructions>
<usage-instructions>${component.usageDocs}</usage-instructions>
</component>
`;
} else {
return dedent`
# ${component.componentName}
## Import Instructions
${component.importDocs}
## Usage Instructions
${component.usageDocs}
`;
}
})
.join('\n\n')}
`;
return systemPrompt;
}
module.exports = {
generateShadcnPrompt,
};

View File

@@ -201,58 +201,20 @@ describe('AnthropicClient', () => {
);
});
it('should add "max-tokens" & "prompt-caching" beta header for claude-3-5-sonnet model', () => {
it('should add beta header for claude-3-5-sonnet model', () => {
const client = new AnthropicClient('test-api-key');
const modelOptions = {
model: 'claude-3-5-sonnet-20241022',
model: 'claude-3-5-sonnet-20240307',
};
client.setOptions({ modelOptions, promptCache: true });
client.setOptions({ modelOptions });
const anthropicClient = client.getClient(modelOptions);
expect(anthropicClient._options.defaultHeaders).toBeDefined();
expect(anthropicClient._options.defaultHeaders).toHaveProperty('anthropic-beta');
expect(anthropicClient._options.defaultHeaders['anthropic-beta']).toBe(
'max-tokens-3-5-sonnet-2024-07-15,prompt-caching-2024-07-31',
'max-tokens-3-5-sonnet-2024-07-15',
);
});
it('should add "prompt-caching" beta header for claude-3-haiku model', () => {
const client = new AnthropicClient('test-api-key');
const modelOptions = {
model: 'claude-3-haiku-2028',
};
client.setOptions({ modelOptions, promptCache: true });
const anthropicClient = client.getClient(modelOptions);
expect(anthropicClient._options.defaultHeaders).toBeDefined();
expect(anthropicClient._options.defaultHeaders).toHaveProperty('anthropic-beta');
expect(anthropicClient._options.defaultHeaders['anthropic-beta']).toBe(
'prompt-caching-2024-07-31',
);
});
it('should add "prompt-caching" beta header for claude-3-opus model', () => {
const client = new AnthropicClient('test-api-key');
const modelOptions = {
model: 'claude-3-opus-2028',
};
client.setOptions({ modelOptions, promptCache: true });
const anthropicClient = client.getClient(modelOptions);
expect(anthropicClient._options.defaultHeaders).toBeDefined();
expect(anthropicClient._options.defaultHeaders).toHaveProperty('anthropic-beta');
expect(anthropicClient._options.defaultHeaders['anthropic-beta']).toBe(
'prompt-caching-2024-07-31',
);
});
it('should not add beta header for claude-3-5-sonnet-latest model', () => {
const client = new AnthropicClient('test-api-key');
const modelOptions = {
model: 'anthropic/claude-3-5-sonnet-latest',
};
client.setOptions({ modelOptions, promptCache: true });
const anthropicClient = client.getClient(modelOptions);
expect(anthropicClient.defaultHeaders).not.toHaveProperty('anthropic-beta');
});
it('should not add beta header for other models', () => {
const client = new AnthropicClient('test-api-key');
client.setOptions({
@@ -264,145 +226,4 @@ describe('AnthropicClient', () => {
expect(anthropicClient.defaultHeaders).not.toHaveProperty('anthropic-beta');
});
});
describe('calculateCurrentTokenCount', () => {
let client;
beforeEach(() => {
client = new AnthropicClient('test-api-key');
});
it('should calculate correct token count when usage is provided', () => {
const tokenCountMap = {
msg1: 10,
msg2: 20,
currentMsg: 30,
};
const currentMessageId = 'currentMsg';
const usage = {
input_tokens: 70,
output_tokens: 50,
};
const result = client.calculateCurrentTokenCount({ tokenCountMap, currentMessageId, usage });
expect(result).toBe(40); // 70 - (10 + 20) = 40
});
it('should return original estimate if calculation results in negative value', () => {
const tokenCountMap = {
msg1: 40,
msg2: 50,
currentMsg: 30,
};
const currentMessageId = 'currentMsg';
const usage = {
input_tokens: 80,
output_tokens: 50,
};
const result = client.calculateCurrentTokenCount({ tokenCountMap, currentMessageId, usage });
expect(result).toBe(30); // Original estimate
});
it('should handle cache creation and read input tokens', () => {
const tokenCountMap = {
msg1: 10,
msg2: 20,
currentMsg: 30,
};
const currentMessageId = 'currentMsg';
const usage = {
input_tokens: 50,
cache_creation_input_tokens: 10,
cache_read_input_tokens: 20,
output_tokens: 40,
};
const result = client.calculateCurrentTokenCount({ tokenCountMap, currentMessageId, usage });
expect(result).toBe(50); // (50 + 10 + 20) - (10 + 20) = 50
});
it('should handle missing usage properties', () => {
const tokenCountMap = {
msg1: 10,
msg2: 20,
currentMsg: 30,
};
const currentMessageId = 'currentMsg';
const usage = {
output_tokens: 40,
};
const result = client.calculateCurrentTokenCount({ tokenCountMap, currentMessageId, usage });
expect(result).toBe(30); // Original estimate
});
it('should handle empty tokenCountMap', () => {
const tokenCountMap = {};
const currentMessageId = 'currentMsg';
const usage = {
input_tokens: 50,
output_tokens: 40,
};
const result = client.calculateCurrentTokenCount({ tokenCountMap, currentMessageId, usage });
expect(result).toBe(50);
expect(Number.isNaN(result)).toBe(false);
});
it('should handle zero values in usage', () => {
const tokenCountMap = {
msg1: 10,
currentMsg: 20,
};
const currentMessageId = 'currentMsg';
const usage = {
input_tokens: 0,
cache_creation_input_tokens: 0,
cache_read_input_tokens: 0,
output_tokens: 0,
};
const result = client.calculateCurrentTokenCount({ tokenCountMap, currentMessageId, usage });
expect(result).toBe(20); // Should return original estimate
expect(Number.isNaN(result)).toBe(false);
});
it('should handle undefined usage', () => {
const tokenCountMap = {
msg1: 10,
currentMsg: 20,
};
const currentMessageId = 'currentMsg';
const usage = undefined;
const result = client.calculateCurrentTokenCount({ tokenCountMap, currentMessageId, usage });
expect(result).toBe(20); // Should return original estimate
expect(Number.isNaN(result)).toBe(false);
});
it('should handle non-numeric values in tokenCountMap', () => {
const tokenCountMap = {
msg1: 'ten',
currentMsg: 20,
};
const currentMessageId = 'currentMsg';
const usage = {
input_tokens: 30,
output_tokens: 10,
};
const result = client.calculateCurrentTokenCount({ tokenCountMap, currentMessageId, usage });
expect(result).toBe(30); // Should return 30 (input_tokens) - 0 (ignored 'ten') = 30
expect(Number.isNaN(result)).toBe(false);
});
});
});

View File

@@ -565,13 +565,11 @@ describe('BaseClient', () => {
const getReqData = jest.fn();
const opts = { getReqData };
const response = await TestClient.sendMessage('Hello, world!', opts);
expect(getReqData).toHaveBeenCalledWith(
expect.objectContaining({
userMessage: expect.objectContaining({ text: 'Hello, world!' }),
conversationId: response.conversationId,
responseMessageId: response.messageId,
}),
);
expect(getReqData).toHaveBeenCalledWith({
userMessage: expect.objectContaining({ text: 'Hello, world!' }),
conversationId: response.conversationId,
responseMessageId: response.messageId,
});
});
test('onStart is called with the correct arguments', async () => {

View File

@@ -611,7 +611,15 @@ describe('OpenAIClient', () => {
expect(getCompletion).toHaveBeenCalled();
expect(getCompletion.mock.calls.length).toBe(1);
expect(getCompletion.mock.calls[0][0]).toBe('||>User:\nHi mom!\n||>Assistant:\n');
const currentDateString = new Date().toLocaleDateString('en-us', {
year: 'numeric',
month: 'long',
day: 'numeric',
});
expect(getCompletion.mock.calls[0][0]).toBe(
`||>Instructions:\nYou are ChatGPT, a large language model trained by OpenAI. Respond conversationally.\nCurrent date: ${currentDateString}\n\n||>User:\nHi mom!\n||>Assistant:\n`,
);
expect(fetchEventSource).toHaveBeenCalled();
expect(fetchEventSource.mock.calls.length).toBe(1);
@@ -693,70 +701,4 @@ describe('OpenAIClient', () => {
expect(client.modelOptions.stop).toBeUndefined();
});
});
describe('getStreamUsage', () => {
it('should return this.usage when completion_tokens_details is null', () => {
const client = new OpenAIClient('test-api-key', defaultOptions);
client.usage = {
completion_tokens_details: null,
prompt_tokens: 10,
completion_tokens: 20,
};
client.inputTokensKey = 'prompt_tokens';
client.outputTokensKey = 'completion_tokens';
const result = client.getStreamUsage();
expect(result).toEqual(client.usage);
});
it('should return this.usage when completion_tokens_details is missing reasoning_tokens', () => {
const client = new OpenAIClient('test-api-key', defaultOptions);
client.usage = {
completion_tokens_details: {
other_tokens: 5,
},
prompt_tokens: 10,
completion_tokens: 20,
};
client.inputTokensKey = 'prompt_tokens';
client.outputTokensKey = 'completion_tokens';
const result = client.getStreamUsage();
expect(result).toEqual(client.usage);
});
it('should calculate output tokens correctly when completion_tokens_details is present with reasoning_tokens', () => {
const client = new OpenAIClient('test-api-key', defaultOptions);
client.usage = {
completion_tokens_details: {
reasoning_tokens: 30,
other_tokens: 5,
},
prompt_tokens: 10,
completion_tokens: 20,
};
client.inputTokensKey = 'prompt_tokens';
client.outputTokensKey = 'completion_tokens';
const result = client.getStreamUsage();
expect(result).toEqual({
reasoning_tokens: 30,
other_tokens: 5,
prompt_tokens: 10,
completion_tokens: 10, // |30 - 20| = 10
});
});
it('should return this.usage when it is undefined', () => {
const client = new OpenAIClient('test-api-key', defaultOptions);
client.usage = undefined;
const result = client.getStreamUsage();
expect(result).toBeUndefined();
});
});
});

View File

@@ -38,12 +38,7 @@ const run = async () => {
"On the other hand, we denounce with righteous indignation and dislike men who are so beguiled and demoralized by the charms of pleasure of the moment, so blinded by desire, that they cannot foresee the pain and trouble that are bound to ensue; and equal blame belongs to those who fail in their duty through weakness of will, which is the same as saying through shrinking from toil and pain. These cases are perfectly simple and easy to distinguish. In a free hour, when our power of choice is untrammelled and when nothing prevents our being able to do what we like best, every pleasure is to be welcomed and every pain avoided. But in certain circumstances and owing to the claims of duty or the obligations of business it will frequently occur that pleasures have to be repudiated and annoyances accepted. The wise man therefore always holds in these matters to this principle of selection: he rejects pleasures to secure other greater pleasures, or else he endures pains to avoid worse pains."
`;
const model = 'gpt-3.5-turbo';
let maxContextTokens = 4095;
if (model === 'gpt-4') {
maxContextTokens = 8191;
} else if (model === 'gpt-4-32k') {
maxContextTokens = 32767;
}
const maxContextTokens = model === 'gpt-4' ? 8191 : model === 'gpt-4-32k' ? 32767 : 4095; // 1 less than maximum
const clientOptions = {
reverseProxyUrl: process.env.OPENAI_REVERSE_PROXY || null,
maxContextTokens,

View File

@@ -77,7 +77,7 @@ class AzureAISearch extends StructuredTool {
try {
const searchOption = {
queryType: this.queryType,
top: typeof this.top === 'string' ? Number(this.top) : this.top,
top: this.top,
};
if (this.select) {
searchOption.select = this.select.split(',');

View File

@@ -25,6 +25,7 @@ module.exports = {
// Basic Tools
CodeBrew,
AzureAiSearch,
GoogleSearchAPI,
WolframAlphaAPI,
OpenAICreateImage,
StableDiffusionAPI,
@@ -36,9 +37,8 @@ module.exports = {
CodeSherpa,
StructuredSD,
StructuredACS,
GoogleSearchAPI,
CodeSherpaTools,
TraversaalSearch,
StructuredWolfram,
TavilySearchResults,
TraversaalSearch,
};

View File

@@ -1,9 +1,9 @@
const { z } = require('zod');
const { Tool } = require('@langchain/core/tools');
const { StructuredTool } = require('langchain/tools');
const { SearchClient, AzureKeyCredential } = require('@azure/search-documents');
const { logger } = require('~/config');
class AzureAISearch extends Tool {
class AzureAISearch extends StructuredTool {
// Constants for default values
static DEFAULT_API_VERSION = '2023-11-01';
static DEFAULT_QUERY_TYPE = 'simple';
@@ -83,7 +83,7 @@ class AzureAISearch extends Tool {
try {
const searchOption = {
queryType: this.queryType,
top: typeof this.top === 'string' ? Number(this.top) : this.top,
top: this.top,
};
if (this.select) {
searchOption.select = this.select.split(',');

View File

@@ -2,7 +2,7 @@ const { z } = require('zod');
const path = require('path');
const OpenAI = require('openai');
const { v4: uuidv4 } = require('uuid');
const { Tool } = require('@langchain/core/tools');
const { Tool } = require('langchain/tools');
const { HttpsProxyAgent } = require('https-proxy-agent');
const { FileContext } = require('librechat-data-provider');
const { getImageBasename } = require('~/server/services/Files/images');

View File

@@ -4,24 +4,17 @@ const { getEnvironmentVariable } = require('@langchain/core/utils/env');
class GoogleSearchResults extends Tool {
static lc_name() {
return 'google';
return 'GoogleSearchResults';
}
constructor(fields = {}) {
super(fields);
this.name = 'google';
this.envVarApiKey = 'GOOGLE_SEARCH_API_KEY';
this.envVarSearchEngineId = 'GOOGLE_CSE_ID';
this.override = fields.override ?? false;
this.apiKey = fields[this.envVarApiKey] ?? getEnvironmentVariable(this.envVarApiKey);
this.apiKey = fields.apiKey ?? getEnvironmentVariable(this.envVarApiKey);
this.searchEngineId =
fields[this.envVarSearchEngineId] ?? getEnvironmentVariable(this.envVarSearchEngineId);
if (!this.override && (!this.apiKey || !this.searchEngineId)) {
throw new Error(
`Missing ${this.envVarApiKey} or ${this.envVarSearchEngineId} environment variable.`,
);
}
fields.searchEngineId ?? getEnvironmentVariable(this.envVarSearchEngineId);
this.kwargs = fields?.kwargs ?? {};
this.name = 'google';

View File

@@ -5,12 +5,12 @@ const path = require('path');
const axios = require('axios');
const sharp = require('sharp');
const { v4: uuidv4 } = require('uuid');
const { Tool } = require('@langchain/core/tools');
const { StructuredTool } = require('langchain/tools');
const { FileContext } = require('librechat-data-provider');
const paths = require('~/config/paths');
const { logger } = require('~/config');
class StableDiffusionAPI extends Tool {
class StableDiffusionAPI extends StructuredTool {
constructor(fields) {
super();
/** @type {string} User ID */

View File

@@ -1,78 +0,0 @@
const { z } = require('zod');
const { tool } = require('@langchain/core/tools');
const { getEnvironmentVariable } = require('@langchain/core/utils/env');
function createTavilySearchTool(fields = {}) {
const envVar = 'TAVILY_API_KEY';
const override = fields.override ?? false;
const apiKey = fields.apiKey ?? getApiKey(envVar, override);
const kwargs = fields?.kwargs ?? {};
function getApiKey(envVar, override) {
const key = getEnvironmentVariable(envVar);
if (!key && !override) {
throw new Error(`Missing ${envVar} environment variable.`);
}
return key;
}
return tool(
async (input) => {
const { query, ...rest } = input;
const requestBody = {
api_key: apiKey,
query,
...rest,
...kwargs,
};
const response = await fetch('https://api.tavily.com/search', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify(requestBody),
});
const json = await response.json();
if (!response.ok) {
throw new Error(`Request failed with status ${response.status}: ${json.error}`);
}
return JSON.stringify(json);
},
{
name: 'tavily_search_results_json',
description:
'A search engine optimized for comprehensive, accurate, and trusted results. Useful for when you need to answer questions about current events.',
schema: z.object({
query: z.string().min(1).describe('The search query string.'),
max_results: z
.number()
.min(1)
.max(10)
.optional()
.describe('The maximum number of search results to return. Defaults to 5.'),
search_depth: z
.enum(['basic', 'advanced'])
.optional()
.describe(
'The depth of the search, affecting result quality and response time (`basic` or `advanced`). Default is basic for quick results and advanced for indepth high quality results but longer response time. Advanced calls equals 2 requests.',
),
include_images: z
.boolean()
.optional()
.describe(
'Whether to include a list of query-related images in the response. Default is False.',
),
include_answer: z
.boolean()
.optional()
.describe('Whether to include answers in the search results. Default is False.'),
}),
},
);
}
module.exports = createTavilySearchTool;

View File

@@ -12,7 +12,7 @@ class TavilySearchResults extends Tool {
this.envVar = 'TAVILY_API_KEY';
/* Used to initialize the Tool without necessary variables. */
this.override = fields.override ?? false;
this.apiKey = fields[this.envVar] ?? this.getApiKey();
this.apiKey = fields.apiKey ?? this.getApiKey();
this.kwargs = fields?.kwargs ?? {};
this.name = 'tavily_search_results_json';
@@ -82,9 +82,7 @@ class TavilySearchResults extends Tool {
const json = await response.json();
if (!response.ok) {
throw new Error(
`Request failed with status ${response.status}: ${json?.detail?.error || json?.error}`,
);
throw new Error(`Request failed with status ${response.status}: ${json.error}`);
}
return JSON.stringify(json);

View File

@@ -1,10 +1,10 @@
/* eslint-disable no-useless-escape */
const axios = require('axios');
const { z } = require('zod');
const { Tool } = require('@langchain/core/tools');
const { StructuredTool } = require('langchain/tools');
const { logger } = require('~/config');
class WolframAlphaAPI extends Tool {
class WolframAlphaAPI extends StructuredTool {
constructor(fields) {
super();
/* Used to initialize the Tool without necessary variables. */

View File

@@ -1,50 +0,0 @@
const GoogleSearch = require('../GoogleSearch');
jest.mock('node-fetch');
jest.mock('@langchain/core/utils/env');
describe('GoogleSearch', () => {
let originalEnv;
const mockApiKey = 'mock_api';
const mockSearchEngineId = 'mock_search_engine_id';
beforeAll(() => {
originalEnv = { ...process.env };
});
beforeEach(() => {
jest.resetModules();
process.env = {
...originalEnv,
GOOGLE_SEARCH_API_KEY: mockApiKey,
GOOGLE_CSE_ID: mockSearchEngineId,
};
});
afterEach(() => {
jest.clearAllMocks();
process.env = originalEnv;
});
it('should use mockApiKey and mockSearchEngineId when environment variables are not set', () => {
const instance = new GoogleSearch({
GOOGLE_SEARCH_API_KEY: mockApiKey,
GOOGLE_CSE_ID: mockSearchEngineId,
});
expect(instance.apiKey).toBe(mockApiKey);
expect(instance.searchEngineId).toBe(mockSearchEngineId);
});
it('should throw an error if GOOGLE_SEARCH_API_KEY or GOOGLE_CSE_ID is missing', () => {
delete process.env.GOOGLE_SEARCH_API_KEY;
expect(() => new GoogleSearch()).toThrow(
'Missing GOOGLE_SEARCH_API_KEY or GOOGLE_CSE_ID environment variable.',
);
process.env.GOOGLE_SEARCH_API_KEY = mockApiKey;
delete process.env.GOOGLE_CSE_ID;
expect(() => new GoogleSearch()).toThrow(
'Missing GOOGLE_SEARCH_API_KEY or GOOGLE_CSE_ID environment variable.',
);
});
});

View File

@@ -1,38 +0,0 @@
const TavilySearchResults = require('../TavilySearchResults');
jest.mock('node-fetch');
jest.mock('@langchain/core/utils/env');
describe('TavilySearchResults', () => {
let originalEnv;
const mockApiKey = 'mock_api_key';
beforeAll(() => {
originalEnv = { ...process.env };
});
beforeEach(() => {
jest.resetModules();
process.env = {
...originalEnv,
TAVILY_API_KEY: mockApiKey,
};
});
afterEach(() => {
jest.clearAllMocks();
process.env = originalEnv;
});
it('should throw an error if TAVILY_API_KEY is missing', () => {
delete process.env.TAVILY_API_KEY;
expect(() => new TavilySearchResults()).toThrow('Missing TAVILY_API_KEY environment variable.');
});
it('should use mockApiKey when TAVILY_API_KEY is not set in the environment', () => {
const instance = new TavilySearchResults({
TAVILY_API_KEY: mockApiKey,
});
expect(instance.apiKey).toBe(mockApiKey);
});
});

View File

@@ -1,104 +0,0 @@
const { z } = require('zod');
const axios = require('axios');
const { tool } = require('@langchain/core/tools');
const { Tools, EToolResources } = require('librechat-data-provider');
const { getFiles } = require('~/models/File');
const { logger } = require('~/config');
/**
*
* @param {Object} options
* @param {ServerRequest} options.req
* @param {Agent['tool_resources']} options.tool_resources
* @returns
*/
const createFileSearchTool = async (options) => {
const { req, tool_resources } = options;
const file_ids = tool_resources?.[EToolResources.file_search]?.file_ids ?? [];
const files = (await getFiles({ file_id: { $in: file_ids } })).map((file) => ({
file_id: file.file_id,
filename: file.filename,
}));
const fileList = files.map((file) => `- ${file.filename}`).join('\n');
const toolDescription = `Performs a semantic search based on a natural language query across the following files:\n${fileList}`;
const FileSearch = tool(
async ({ query }) => {
if (files.length === 0) {
return 'No files to search. Instruct the user to add files for the search.';
}
const jwtToken = req.headers.authorization.split(' ')[1];
if (!jwtToken) {
return 'There was an error authenticating the file search request.';
}
const queryPromises = files.map((file) =>
axios
.post(
`${process.env.RAG_API_URL}/query`,
{
file_id: file.file_id,
query,
k: 5,
},
{
headers: {
Authorization: `Bearer ${jwtToken}`,
'Content-Type': 'application/json',
},
},
)
.catch((error) => {
logger.error(
`Error encountered in \`file_search\` while querying file_id ${file._id}:`,
error,
);
return null;
}),
);
const results = await Promise.all(queryPromises);
const validResults = results.filter((result) => result !== null);
if (validResults.length === 0) {
return 'No results found or errors occurred while searching the files.';
}
const formattedResults = validResults
.flatMap((result) =>
result.data.map(([docInfo, relevanceScore]) => ({
filename: docInfo.metadata.source.split('/').pop(),
content: docInfo.page_content,
relevanceScore,
})),
)
.sort((a, b) => b.relevanceScore - a.relevanceScore);
const formattedString = formattedResults
.map(
(result) =>
`File: ${result.filename}\nRelevance: ${result.relevanceScore.toFixed(4)}\nContent: ${
result.content
}\n`,
)
.join('\n---\n');
return formattedString;
},
{
name: Tools.file_search,
description: toolDescription,
schema: z.object({
query: z
.string()
.describe(
'A natural language query to search for relevant information in the files. Be specific and use keywords related to the information you\'re looking for. The query will be used for semantic similarity matching against the file contents.',
),
}),
},
);
return FileSearch;
};
module.exports = createFileSearchTool;

View File

@@ -1,8 +1,8 @@
const { Tools } = require('librechat-data-provider');
const { ZapierToolKit } = require('langchain/agents');
const { Calculator } = require('langchain/tools/calculator');
const { WebBrowser } = require('langchain/tools/webbrowser');
const { SerpAPI, ZapierNLAWrapper } = require('langchain/tools');
const { createCodeExecutionTool, EnvVar } = require('@librechat/agents');
const { OpenAIEmbeddings } = require('langchain/embeddings/openai');
const { getUserPluginAuthValue } = require('~/server/services/PluginService');
const {
availableTools,
@@ -24,11 +24,16 @@ const {
StructuredWolfram,
TavilySearchResults,
} = require('../');
const createFileSearchTool = require('./createFileSearchTool');
const { loadToolSuite } = require('./loadToolSuite');
const { loadSpecs } = require('./loadSpecs');
const { logger } = require('~/config');
const getOpenAIKey = async (options, user) => {
let openAIApiKey = options.openAIApiKey ?? process.env.OPENAI_API_KEY;
openAIApiKey = openAIApiKey === 'user_provided' ? null : openAIApiKey;
return openAIApiKey || (await getUserPluginAuthValue(user, 'OPENAI_API_KEY'));
};
/**
* Validates the availability and authentication of tools for a user based on environment variables or user-specific plugin authentication values.
* Tools without required authentication or with valid authentication are considered valid.
@@ -92,45 +97,6 @@ const validateTools = async (user, tools = []) => {
}
};
const loadAuthValues = async ({ userId, authFields }) => {
let authValues = {};
/**
* Finds the first non-empty value for the given authentication field, supporting alternate fields.
* @param {string[]} fields Array of strings representing the authentication fields. Supports alternate fields delimited by "||".
* @returns {Promise<{ authField: string, authValue: string} | null>} An object containing the authentication field and value, or null if not found.
*/
const findAuthValue = async (fields) => {
for (const field of fields) {
let value = process.env[field];
if (value) {
return { authField: field, authValue: value };
}
try {
value = await getUserPluginAuthValue(userId, field);
} catch (err) {
if (field === fields[fields.length - 1] && !value) {
throw err;
}
}
if (value) {
return { authField: field, authValue: value };
}
}
return null;
};
for (let authField of authFields) {
const fields = authField.split('||');
const result = await findAuthValue(fields);
if (result) {
authValues[result.authField] = result.authValue;
}
}
return authValues;
};
/**
* Initializes a tool with authentication values for the given user, supporting alternate authentication fields.
* Authentication fields can have alternates separated by "||", and the first defined variable will be used.
@@ -143,7 +109,41 @@ const loadAuthValues = async ({ userId, authFields }) => {
*/
const loadToolWithAuth = (userId, authFields, ToolConstructor, options = {}) => {
return async function () {
const authValues = await loadAuthValues({ userId, authFields });
let authValues = {};
/**
* Finds the first non-empty value for the given authentication field, supporting alternate fields.
* @param {string[]} fields Array of strings representing the authentication fields. Supports alternate fields delimited by "||".
* @returns {Promise<{ authField: string, authValue: string} | null>} An object containing the authentication field and value, or null if not found.
*/
const findAuthValue = async (fields) => {
for (const field of fields) {
let value = process.env[field];
if (value) {
return { authField: field, authValue: value };
}
try {
value = await getUserPluginAuthValue(userId, field);
} catch (err) {
if (field === fields[fields.length - 1] && !value) {
throw err;
}
}
if (value) {
return { authField: field, authValue: value };
}
}
return null;
};
for (let authField of authFields) {
const fields = authField.split('||');
const result = await findAuthValue(fields);
if (result) {
authValues[result.authField] = result.authValue;
}
}
return new ToolConstructor({ ...options, ...authValues, userId });
};
};
@@ -169,6 +169,8 @@ const loadTools = async ({
traversaal_search: TraversaalSearch,
};
const openAIApiKey = await getOpenAIKey(options, user);
const customConstructors = {
e2b_code_interpreter: async () => {
if (!functions) {
@@ -181,6 +183,7 @@ const loadTools = async ({
user,
options: {
model,
openAIApiKey,
...options,
},
});
@@ -197,6 +200,14 @@ const loadTools = async ({
options,
});
},
'web-browser': async () => {
// let openAIApiKey = options.openAIApiKey ?? process.env.OPENAI_API_KEY;
// openAIApiKey = openAIApiKey === 'user_provided' ? null : openAIApiKey;
// openAIApiKey = openAIApiKey || (await getUserPluginAuthValue(user, 'OPENAI_API_KEY'));
const browser = new WebBrowser({ model, embeddings: new OpenAIEmbeddings({ openAIApiKey }) });
browser.description_for_model = browser.description;
return browser;
},
serpapi: async () => {
let apiKey = process.env.SERPAPI_API_KEY;
if (!apiKey) {
@@ -253,22 +264,6 @@ const loadTools = async ({
const remainingTools = [];
for (const tool of tools) {
if (tool === Tools.execute_code) {
const authValues = await loadAuthValues({
userId: user.id,
authFields: [EnvVar.CODE_API_KEY],
});
requestedTools[tool] = () =>
createCodeExecutionTool({
user_id: user.id,
...authValues,
});
continue;
} else if (tool === Tools.file_search) {
requestedTools[tool] = () => createFileSearchTool(options);
continue;
}
if (customConstructors[tool]) {
requestedTools[tool] = customConstructors[tool];
continue;
@@ -336,7 +331,6 @@ const loadTools = async ({
module.exports = {
loadToolWithAuth,
loadAuthValues,
validateTools,
loadTools,
};

View File

@@ -1,9 +1,8 @@
const { validateTools, loadTools, loadAuthValues } = require('./handleTools');
const { validateTools, loadTools } = require('./handleTools');
const handleOpenAIErrors = require('./handleOpenAIErrors');
module.exports = {
handleOpenAIErrors,
loadAuthValues,
validateTools,
loadTools,
};

View File

@@ -35,7 +35,7 @@ const clearPendingReq = async ({ userId, cache: _cache }) => {
return;
}
const key = `${isEnabled(USE_REDIS) ? namespace : ''}:${userId ?? ''}`;
const key = `${USE_REDIS ? namespace : ''}:${userId ?? ''}`;
const currentReq = +((await cache.get(key)) ?? 0);
if (currentReq && currentReq >= 1) {

View File

@@ -35,11 +35,11 @@ const messages = isEnabled(USE_REDIS)
? new Keyv({ store: keyvRedis, ttl: Time.FIVE_MINUTES })
: new Keyv({ namespace: CacheKeys.MESSAGES, ttl: Time.FIVE_MINUTES });
const tokenConfig = isEnabled(USE_REDIS)
const tokenConfig = isEnabled(USE_REDIS) // ttl: 30 minutes
? new Keyv({ store: keyvRedis, ttl: Time.THIRTY_MINUTES })
: new Keyv({ namespace: CacheKeys.TOKEN_CONFIG, ttl: Time.THIRTY_MINUTES });
const genTitle = isEnabled(USE_REDIS)
const genTitle = isEnabled(USE_REDIS) // ttl: 2 minutes
? new Keyv({ store: keyvRedis, ttl: Time.TWO_MINUTES })
: new Keyv({ namespace: CacheKeys.GEN_TITLE, ttl: Time.TWO_MINUTES });
@@ -69,7 +69,6 @@ const namespaces = {
registrations: createViolationInstance('registrations'),
[ViolationTypes.TTS_LIMIT]: createViolationInstance(ViolationTypes.TTS_LIMIT),
[ViolationTypes.STT_LIMIT]: createViolationInstance(ViolationTypes.STT_LIMIT),
[ViolationTypes.CONVO_ACCESS]: createViolationInstance(ViolationTypes.CONVO_ACCESS),
[ViolationTypes.FILE_UPLOAD_LIMIT]: createViolationInstance(ViolationTypes.FILE_UPLOAD_LIMIT),
[ViolationTypes.VERIFY_EMAIL_LIMIT]: createViolationInstance(ViolationTypes.VERIFY_EMAIL_LIMIT),
[ViolationTypes.RESET_PASSWORD_LIMIT]: createViolationInstance(

View File

@@ -5,16 +5,17 @@ const Action = mongoose.model('action', actionSchema);
/**
* Update an action with new data without overwriting existing properties,
* or create a new action if it doesn't exist.
* or create a new action if it doesn't exist, within a transaction session if provided.
*
* @param {Object} searchParams - The search parameters to find the action to update.
* @param {string} searchParams.action_id - The ID of the action to update.
* @param {string} searchParams.user - The user ID of the action's author.
* @param {Object} updateData - An object containing the properties to update.
* @returns {Promise<Action>} The updated or newly created action document as a plain object.
* @param {mongoose.ClientSession} [session] - The transaction session to use.
* @returns {Promise<Object>} The updated or newly created action document as a plain object.
*/
const updateAction = async (searchParams, updateData) => {
const options = { new: true, upsert: true };
const updateAction = async (searchParams, updateData, session = null) => {
const options = { new: true, upsert: true, session };
return await Action.findOneAndUpdate(searchParams, updateData, options).lean();
};
@@ -23,7 +24,7 @@ const updateAction = async (searchParams, updateData) => {
*
* @param {Object} searchParams - The search parameters to find matching actions.
* @param {boolean} includeSensitive - Flag to include sensitive data in the metadata.
* @returns {Promise<Array<Action>>} A promise that resolves to an array of action documents as plain objects.
* @returns {Promise<Array<Object>>} A promise that resolves to an array of action documents as plain objects.
*/
const getActions = async (searchParams, includeSensitive = false) => {
const actions = await Action.find(searchParams).lean();
@@ -48,27 +49,31 @@ const getActions = async (searchParams, includeSensitive = false) => {
};
/**
* Deletes an action by params.
* Deletes an action by params, within a transaction session if provided.
*
* @param {Object} searchParams - The search parameters to find the action to delete.
* @param {string} searchParams.action_id - The ID of the action to delete.
* @param {string} searchParams.user - The user ID of the action's author.
* @returns {Promise<Action>} A promise that resolves to the deleted action document as a plain object, or null if no document was found.
* @param {mongoose.ClientSession} [session] - The transaction session to use (optional).
* @returns {Promise<Object>} A promise that resolves to the deleted action document as a plain object, or null if no document was found.
*/
const deleteAction = async (searchParams) => {
return await Action.findOneAndDelete(searchParams).lean();
const deleteAction = async (searchParams, session = null) => {
const options = session ? { session } : {};
return await Action.findOneAndDelete(searchParams, options).lean();
};
/**
* Deletes actions by params.
* Deletes actions by params, within a transaction session if provided.
*
* @param {Object} searchParams - The search parameters to find the actions to delete.
* @param {string} searchParams.action_id - The ID of the action(s) to delete.
* @param {string} searchParams.user - The user ID of the action's author.
* @param {mongoose.ClientSession} [session] - The transaction session to use (optional).
* @returns {Promise<Number>} A promise that resolves to the number of deleted action documents.
*/
const deleteActions = async (searchParams) => {
const result = await Action.deleteMany(searchParams);
const deleteActions = async (searchParams, session = null) => {
const options = session ? { session } : {};
const result = await Action.deleteMany(searchParams, options);
return result.deletedCount;
};

View File

@@ -1,285 +0,0 @@
const mongoose = require('mongoose');
const { SystemRoles } = require('librechat-data-provider');
const { GLOBAL_PROJECT_NAME } = require('librechat-data-provider').Constants;
const { CONFIG_STORE, STARTUP_CONFIG } = require('librechat-data-provider').CacheKeys;
const {
getProjectByName,
addAgentIdsToProject,
removeAgentIdsFromProject,
removeAgentFromAllProjects,
} = require('./Project');
const getLogStores = require('~/cache/getLogStores');
const agentSchema = require('./schema/agent');
const Agent = mongoose.model('agent', agentSchema);
/**
* Create an agent with the provided data.
* @param {Object} agentData - The agent data to create.
* @returns {Promise<Agent>} The created agent document as a plain object.
* @throws {Error} If the agent creation fails.
*/
const createAgent = async (agentData) => {
return await Agent.create(agentData);
};
/**
* Get an agent document based on the provided ID.
*
* @param {Object} searchParameter - The search parameters to find the agent to update.
* @param {string} searchParameter.id - The ID of the agent to update.
* @param {string} searchParameter.author - The user ID of the agent's author.
* @returns {Promise<Agent|null>} The agent document as a plain object, or null if not found.
*/
const getAgent = async (searchParameter) => await Agent.findOne(searchParameter).lean();
/**
* Load an agent based on the provided ID
*
* @param {Object} params
* @param {ServerRequest} params.req
* @param {string} params.agent_id
* @returns {Promise<Agent|null>} The agent document as a plain object, or null if not found.
*/
const loadAgent = async ({ req, agent_id }) => {
const agent = await getAgent({
id: agent_id,
});
if (agent.author.toString() === req.user.id) {
return agent;
}
if (!agent.projectIds) {
return null;
}
const cache = getLogStores(CONFIG_STORE);
/** @type {TStartupConfig} */
const cachedStartupConfig = await cache.get(STARTUP_CONFIG);
let { instanceProjectId } = cachedStartupConfig ?? {};
if (!instanceProjectId) {
instanceProjectId = (await getProjectByName(GLOBAL_PROJECT_NAME, '_id'))._id.toString();
}
for (const projectObjectId of agent.projectIds) {
const projectId = projectObjectId.toString();
if (projectId === instanceProjectId) {
return agent;
}
}
};
/**
* Update an agent with new data without overwriting existing
* properties, or create a new agent if it doesn't exist.
*
* @param {Object} searchParameter - The search parameters to find the agent to update.
* @param {string} searchParameter.id - The ID of the agent to update.
* @param {string} [searchParameter.author] - The user ID of the agent's author.
* @param {Object} updateData - An object containing the properties to update.
* @returns {Promise<Agent>} The updated or newly created agent document as a plain object.
*/
const updateAgent = async (searchParameter, updateData) => {
const options = { new: true, upsert: false };
return await Agent.findOneAndUpdate(searchParameter, updateData, options).lean();
};
/**
* Modifies an agent with the resource file id.
* @param {object} params
* @param {ServerRequest} params.req
* @param {string} params.agent_id
* @param {string} params.tool_resource
* @param {string} params.file_id
* @returns {Promise<Agent>} The updated agent.
*/
const addAgentResourceFile = async ({ agent_id, tool_resource, file_id }) => {
const searchParameter = { id: agent_id };
const agent = await getAgent(searchParameter);
if (!agent) {
throw new Error('Agent not found for adding resource file');
}
const tool_resources = agent.tool_resources || {};
if (!tool_resources[tool_resource]) {
tool_resources[tool_resource] = { file_ids: [] };
}
if (!tool_resources[tool_resource].file_ids.includes(file_id)) {
tool_resources[tool_resource].file_ids.push(file_id);
}
const updateData = { tool_resources };
return await updateAgent(searchParameter, updateData);
};
/**
* Removes a resource file id from an agent.
* @param {object} params
* @param {ServerRequest} params.req
* @param {string} params.agent_id
* @param {string} params.tool_resource
* @param {string} params.file_id
* @returns {Promise<Agent>} The updated agent.
*/
const removeAgentResourceFile = async ({ agent_id, tool_resource, file_id }) => {
const searchParameter = { id: agent_id };
const agent = await getAgent(searchParameter);
if (!agent) {
throw new Error('Agent not found for removing resource file');
}
const tool_resources = agent.tool_resources || {};
if (tool_resources[tool_resource] && tool_resources[tool_resource].file_ids) {
tool_resources[tool_resource].file_ids = tool_resources[tool_resource].file_ids.filter(
(id) => id !== file_id,
);
if (tool_resources[tool_resource].file_ids.length === 0) {
delete tool_resources[tool_resource];
}
}
const updateData = { tool_resources };
return await updateAgent(searchParameter, updateData);
};
/**
* Deletes an agent based on the provided ID.
*
* @param {Object} searchParameter - The search parameters to find the agent to delete.
* @param {string} searchParameter.id - The ID of the agent to delete.
* @param {string} [searchParameter.author] - The user ID of the agent's author.
* @returns {Promise<void>} Resolves when the agent has been successfully deleted.
*/
const deleteAgent = async (searchParameter) => {
const agent = await Agent.findOneAndDelete(searchParameter);
if (agent) {
await removeAgentFromAllProjects(agent.id);
}
return agent;
};
/**
* Get all agents.
* @param {Object} searchParameter - The search parameters to find matching agents.
* @param {string} searchParameter.author - The user ID of the agent's author.
* @returns {Promise<Object>} A promise that resolves to an object containing the agents data and pagination info.
*/
const getListAgents = async (searchParameter) => {
const { author, ...otherParams } = searchParameter;
let query = Object.assign({ author }, otherParams);
const globalProject = await getProjectByName(GLOBAL_PROJECT_NAME, ['agentIds']);
if (globalProject && (globalProject.agentIds?.length ?? 0) > 0) {
const globalQuery = { id: { $in: globalProject.agentIds }, ...otherParams };
delete globalQuery.author;
query = { $or: [globalQuery, query] };
}
const agents = (
await Agent.find(query, {
id: 1,
_id: 0,
name: 1,
avatar: 1,
author: 1,
projectIds: 1,
isCollaborative: 1,
}).lean()
).map((agent) => {
if (agent.author?.toString() !== author) {
delete agent.author;
}
if (agent.author) {
agent.author = agent.author.toString();
}
return agent;
});
const hasMore = agents.length > 0;
const firstId = agents.length > 0 ? agents[0].id : null;
const lastId = agents.length > 0 ? agents[agents.length - 1].id : null;
return {
data: agents,
has_more: hasMore,
first_id: firstId,
last_id: lastId,
};
};
/**
* Updates the projects associated with an agent, adding and removing project IDs as specified.
* This function also updates the corresponding projects to include or exclude the agent ID.
*
* @param {Object} params - Parameters for updating the agent's projects.
* @param {import('librechat-data-provider').TUser} params.user - Parameters for updating the agent's projects.
* @param {string} params.agentId - The ID of the agent to update.
* @param {string[]} [params.projectIds] - Array of project IDs to add to the agent.
* @param {string[]} [params.removeProjectIds] - Array of project IDs to remove from the agent.
* @returns {Promise<MongoAgent>} The updated agent document.
* @throws {Error} If there's an error updating the agent or projects.
*/
const updateAgentProjects = async ({ user, agentId, projectIds, removeProjectIds }) => {
const updateOps = {};
if (removeProjectIds && removeProjectIds.length > 0) {
for (const projectId of removeProjectIds) {
await removeAgentIdsFromProject(projectId, [agentId]);
}
updateOps.$pull = { projectIds: { $in: removeProjectIds } };
}
if (projectIds && projectIds.length > 0) {
for (const projectId of projectIds) {
await addAgentIdsToProject(projectId, [agentId]);
}
updateOps.$addToSet = { projectIds: { $each: projectIds } };
}
if (Object.keys(updateOps).length === 0) {
return await getAgent({ id: agentId });
}
const updateQuery = { id: agentId, author: user.id };
if (user.role === SystemRoles.ADMIN) {
delete updateQuery.author;
}
const updatedAgent = await updateAgent(updateQuery, updateOps);
if (updatedAgent) {
return updatedAgent;
}
if (updateOps.$addToSet) {
for (const projectId of projectIds) {
await removeAgentIdsFromProject(projectId, [agentId]);
}
} else if (updateOps.$pull) {
for (const projectId of removeProjectIds) {
await addAgentIdsToProject(projectId, [agentId]);
}
}
return await getAgent({ id: agentId });
};
module.exports = {
getAgent,
loadAgent,
createAgent,
updateAgent,
deleteAgent,
getListAgents,
updateAgentProjects,
addAgentResourceFile,
removeAgentResourceFile,
};

View File

@@ -5,16 +5,17 @@ const Assistant = mongoose.model('assistant', assistantSchema);
/**
* Update an assistant with new data without overwriting existing properties,
* or create a new assistant if it doesn't exist.
* or create a new assistant if it doesn't exist, within a transaction session if provided.
*
* @param {Object} searchParams - The search parameters to find the assistant to update.
* @param {string} searchParams.assistant_id - The ID of the assistant to update.
* @param {string} searchParams.user - The user ID of the assistant's author.
* @param {Object} updateData - An object containing the properties to update.
* @returns {Promise<AssistantDocument>} The updated or newly created assistant document as a plain object.
* @param {mongoose.ClientSession} [session] - The transaction session to use (optional).
* @returns {Promise<Object>} The updated or newly created assistant document as a plain object.
*/
const updateAssistantDoc = async (searchParams, updateData) => {
const options = { new: true, upsert: true };
const updateAssistantDoc = async (searchParams, updateData, session = null) => {
const options = { new: true, upsert: true, session };
return await Assistant.findOneAndUpdate(searchParams, updateData, options).lean();
};
@@ -24,7 +25,7 @@ const updateAssistantDoc = async (searchParams, updateData) => {
* @param {Object} searchParams - The search parameters to find the assistant to update.
* @param {string} searchParams.assistant_id - The ID of the assistant to update.
* @param {string} searchParams.user - The user ID of the assistant's author.
* @returns {Promise<AssistantDocument|null>} The assistant document as a plain object, or null if not found.
* @returns {Promise<Object|null>} The assistant document as a plain object, or null if not found.
*/
const getAssistant = async (searchParams) => await Assistant.findOne(searchParams).lean();
@@ -32,17 +33,10 @@ const getAssistant = async (searchParams) => await Assistant.findOne(searchParam
* Retrieves all assistants that match the given search parameters.
*
* @param {Object} searchParams - The search parameters to find matching assistants.
* @param {Object} [select] - Optional. Specifies which document fields to include or exclude.
* @returns {Promise<Array<AssistantDocument>>} A promise that resolves to an array of assistant documents as plain objects.
* @returns {Promise<Array<Object>>} A promise that resolves to an array of action documents as plain objects.
*/
const getAssistants = async (searchParams, select = null) => {
let query = Assistant.find(searchParams);
if (select) {
query = query.select(select);
}
return await query.lean();
const getAssistants = async (searchParams) => {
return await Assistant.find(searchParams).lean();
};
/**

View File

@@ -1,27 +0,0 @@
const Banner = require('./schema/banner');
const logger = require('~/config/winston');
/**
* Retrieves the current active banner.
* @returns {Promise<Object|null>} The active banner object or null if no active banner is found.
*/
const getBanner = async (user) => {
try {
const now = new Date();
const banner = await Banner.findOne({
displayFrom: { $lte: now },
$or: [{ displayTo: { $gte: now } }, { displayTo: null }],
type: 'banner',
}).lean();
if (!banner || banner.isPublic || user) {
return banner;
}
return null;
} catch (error) {
logger.error('[getBanners] Error getting banners', error);
throw new Error('Error getting banners');
}
};
module.exports = { getBanner };

View File

@@ -2,20 +2,6 @@ const Conversation = require('./schema/convoSchema');
const { getMessages, deleteMessages } = require('./Message');
const logger = require('~/config/winston');
/**
* Searches for a conversation by conversationId and returns a lean document with only conversationId and user.
* @param {string} conversationId - The conversation's ID.
* @returns {Promise<{conversationId: string, user: string} | null>} The conversation object with selected fields or null if not found.
*/
const searchConversation = async (conversationId) => {
try {
return await Conversation.findOne({ conversationId }, 'conversationId user').lean();
} catch (error) {
logger.error('[searchConversation] Error searching conversation', error);
throw new Error('Error searching conversation');
}
};
/**
* Retrieves a single conversation for a given user and conversation ID.
* @param {string} user - The user's ID.
@@ -31,39 +17,8 @@ const getConvo = async (user, conversationId) => {
}
};
const deleteNullOrEmptyConversations = async () => {
try {
const filter = {
$or: [
{ conversationId: null },
{ conversationId: '' },
{ conversationId: { $exists: false } },
],
};
const result = await Conversation.deleteMany(filter);
// Delete associated messages
const messageDeleteResult = await deleteMessages(filter);
logger.info(
`[deleteNullOrEmptyConversations] Deleted ${result.deletedCount} conversations and ${messageDeleteResult.deletedCount} messages`,
);
return {
conversations: result,
messages: messageDeleteResult,
};
} catch (error) {
logger.error('[deleteNullOrEmptyConversations] Error deleting conversations', error);
throw new Error('Error deleting conversations with null or empty conversationId');
}
};
module.exports = {
Conversation,
searchConversation,
deleteNullOrEmptyConversations,
/**
* Saves a conversation to the database.
* @param {Object} req - The request object.

View File

@@ -1,249 +1,268 @@
const ConversationTag = require('./schema/conversationTagSchema');
const Conversation = require('./schema/convoSchema');
//const crypto = require('crypto');
const logger = require('~/config/winston');
const Conversation = require('./schema/convoSchema');
const ConversationTag = require('./schema/conversationTagSchema');
/**
* Retrieves all conversation tags for a user.
* @param {string} user - The user ID.
* @returns {Promise<Array>} An array of conversation tags.
*/
const getConversationTags = async (user) => {
try {
return await ConversationTag.find({ user }).sort({ position: 1 }).lean();
} catch (error) {
logger.error('[getConversationTags] Error getting conversation tags', error);
throw new Error('Error getting conversation tags');
}
};
const SAVED_TAG = 'Saved';
/**
* Creates a new conversation tag.
* @param {string} user - The user ID.
* @param {Object} data - The tag data.
* @param {string} data.tag - The tag name.
* @param {string} [data.description] - The tag description.
* @param {boolean} [data.addToConversation] - Whether to add the tag to a conversation.
* @param {string} [data.conversationId] - The conversation ID to add the tag to.
* @returns {Promise<Object>} The created tag.
*/
const createConversationTag = async (user, data) => {
try {
const { tag, description, addToConversation, conversationId } = data;
const existingTag = await ConversationTag.findOne({ user, tag }).lean();
if (existingTag) {
return existingTag;
}
const maxPosition = await ConversationTag.findOne({ user }).sort('-position').lean();
const position = (maxPosition?.position || 0) + 1;
const newTag = await ConversationTag.findOneAndUpdate(
{ tag, user },
{
tag,
user,
count: addToConversation ? 1 : 0,
position,
description,
$setOnInsert: { createdAt: new Date() },
},
{
new: true,
upsert: true,
lean: true,
},
);
if (addToConversation && conversationId) {
await Conversation.findOneAndUpdate(
{ user, conversationId },
{ $addToSet: { tags: tag } },
{ new: true },
);
}
return newTag;
} catch (error) {
logger.error('[createConversationTag] Error creating conversation tag', error);
throw new Error('Error creating conversation tag');
}
};
/**
* Updates an existing conversation tag.
* @param {string} user - The user ID.
* @param {string} oldTag - The current tag name.
* @param {Object} data - The updated tag data.
* @param {string} [data.tag] - The new tag name.
* @param {string} [data.description] - The updated description.
* @param {number} [data.position] - The new position.
* @returns {Promise<Object>} The updated tag.
*/
const updateConversationTag = async (user, oldTag, data) => {
try {
const { tag: newTag, description, position } = data;
const existingTag = await ConversationTag.findOne({ user, tag: oldTag }).lean();
if (!existingTag) {
return null;
}
if (newTag && newTag !== oldTag) {
const tagAlreadyExists = await ConversationTag.findOne({ user, tag: newTag }).lean();
if (tagAlreadyExists) {
throw new Error('Tag already exists');
}
await Conversation.updateMany({ user, tags: oldTag }, { $set: { 'tags.$': newTag } });
}
const updateData = {};
if (newTag) {
updateData.tag = newTag;
}
if (description !== undefined) {
updateData.description = description;
}
if (position !== undefined) {
await adjustPositions(user, existingTag.position, position);
updateData.position = position;
}
return await ConversationTag.findOneAndUpdate({ user, tag: oldTag }, updateData, {
new: true,
lean: true,
});
} catch (error) {
logger.error('[updateConversationTag] Error updating conversation tag', error);
throw new Error('Error updating conversation tag');
}
};
/**
* Adjusts positions of tags when a tag's position is changed.
* @param {string} user - The user ID.
* @param {number} oldPosition - The old position of the tag.
* @param {number} newPosition - The new position of the tag.
* @returns {Promise<void>}
*/
const adjustPositions = async (user, oldPosition, newPosition) => {
if (oldPosition === newPosition) {
return;
}
const update = oldPosition < newPosition ? { $inc: { position: -1 } } : { $inc: { position: 1 } };
const position =
oldPosition < newPosition
? {
$gt: Math.min(oldPosition, newPosition),
$lte: Math.max(oldPosition, newPosition),
}
: {
$gte: Math.min(oldPosition, newPosition),
$lt: Math.max(oldPosition, newPosition),
};
await ConversationTag.updateMany(
{
user,
position,
},
update,
);
};
/**
* Deletes a conversation tag.
* @param {string} user - The user ID.
* @param {string} tag - The tag to delete.
* @returns {Promise<Object>} The deleted tag.
*/
const deleteConversationTag = async (user, tag) => {
try {
const deletedTag = await ConversationTag.findOneAndDelete({ user, tag }).lean();
if (!deletedTag) {
return null;
}
await Conversation.updateMany({ user, tags: tag }, { $pull: { tags: tag } });
await ConversationTag.updateMany(
{ user, position: { $gt: deletedTag.position } },
{ $inc: { position: -1 } },
);
return deletedTag;
} catch (error) {
logger.error('[deleteConversationTag] Error deleting conversation tag', error);
throw new Error('Error deleting conversation tag');
}
};
/**
* Updates tags for a specific conversation.
* @param {string} user - The user ID.
* @param {string} conversationId - The conversation ID.
* @param {string[]} tags - The new set of tags for the conversation.
* @returns {Promise<string[]>} The updated list of tags for the conversation.
*/
const updateTagsForConversation = async (user, conversationId, tags) => {
try {
const conversation = await Conversation.findOne({ user, conversationId }).lean();
const conversation = await Conversation.findOne({ user, conversationId });
if (!conversation) {
throw new Error('Conversation not found');
return { message: 'Conversation not found' };
}
const oldTags = new Set(conversation.tags);
const newTags = new Set(tags);
const addedTags = [...newTags].filter((tag) => !oldTags.has(tag));
const removedTags = [...oldTags].filter((tag) => !newTags.has(tag));
const bulkOps = [];
const addedTags = tags.tags.filter((tag) => !conversation.tags.includes(tag));
const removedTags = conversation.tags.filter((tag) => !tags.tags.includes(tag));
for (const tag of addedTags) {
bulkOps.push({
updateOne: {
filter: { user, tag },
update: { $inc: { count: 1 } },
upsert: true,
},
});
await ConversationTag.updateOne({ tag, user }, { $inc: { count: 1 } }, { upsert: true });
}
for (const tag of removedTags) {
bulkOps.push({
updateOne: {
filter: { user, tag },
update: { $inc: { count: -1 } },
},
});
await ConversationTag.updateOne({ tag, user }, { $inc: { count: -1 } });
}
if (bulkOps.length > 0) {
await ConversationTag.bulkWrite(bulkOps);
}
const updatedConversation = (
await Conversation.findOneAndUpdate(
{ user, conversationId },
{ $set: { tags: [...newTags] } },
{ new: true },
)
).toObject();
return updatedConversation.tags;
conversation.tags = tags.tags;
await conversation.save({ timestamps: { updatedAt: false } });
return conversation.tags;
} catch (error) {
logger.error('[updateTagsForConversation] Error updating tags', error);
throw new Error('Error updating tags for conversation');
logger.error('[updateTagsToConversation] Error updating tags', error);
return { message: 'Error updating tags' };
}
};
module.exports = {
getConversationTags,
createConversationTag,
updateConversationTag,
deleteConversationTag,
updateTagsForConversation,
const createConversationTag = async (user, data) => {
try {
const cTag = await ConversationTag.findOne({ user, tag: data.tag });
if (cTag) {
return cTag;
}
const addToConversation = data.addToConversation && data.conversationId;
const newTag = await ConversationTag.create({
user,
tag: data.tag,
count: 0,
description: data.description,
position: 1,
});
await ConversationTag.updateMany(
{ user, position: { $gte: 1 }, _id: { $ne: newTag._id } },
{ $inc: { position: 1 } },
);
if (addToConversation) {
const conversation = await Conversation.findOne({
user,
conversationId: data.conversationId,
});
if (conversation) {
const tags = [...(conversation.tags || []), data.tag];
await updateTagsForConversation(user, data.conversationId, { tags });
} else {
logger.warn('[updateTagsForConversation] Conversation not found', data.conversationId);
}
}
return await ConversationTag.findOne({ user, tag: data.tag });
} catch (error) {
logger.error('[createConversationTag] Error updating conversation tag', error);
return { message: 'Error updating conversation tag' };
}
};
const replaceOrRemoveTagInConversations = async (user, oldtag, newtag) => {
try {
const conversations = await Conversation.find({ user, tags: { $in: [oldtag] } });
for (const conversation of conversations) {
if (newtag && newtag !== '') {
conversation.tags = conversation.tags.map((tag) => (tag === oldtag ? newtag : tag));
} else {
conversation.tags = conversation.tags.filter((tag) => tag !== oldtag);
}
await conversation.save({ timestamps: { updatedAt: false } });
}
} catch (error) {
logger.error('[replaceOrRemoveTagInConversations] Error updating conversation tags', error);
return { message: 'Error updating conversation tags' };
}
};
const updateTagPosition = async (user, tag, newPosition) => {
try {
const cTag = await ConversationTag.findOne({ user, tag });
if (!cTag) {
return { message: 'Tag not found' };
}
const oldPosition = cTag.position;
if (newPosition === oldPosition) {
return cTag;
}
const updateOperations = [];
if (newPosition > oldPosition) {
// Move other tags up
updateOperations.push({
updateMany: {
filter: {
user,
position: { $gt: oldPosition, $lte: newPosition },
tag: { $ne: SAVED_TAG },
},
update: { $inc: { position: -1 } },
},
});
} else {
// Move other tags down
updateOperations.push({
updateMany: {
filter: {
user,
position: { $gte: newPosition, $lt: oldPosition },
tag: { $ne: SAVED_TAG },
},
update: { $inc: { position: 1 } },
},
});
}
// Update the target tag's position
updateOperations.push({
updateOne: {
filter: { _id: cTag._id },
update: { $set: { position: newPosition } },
},
});
await ConversationTag.bulkWrite(updateOperations);
return await ConversationTag.findById(cTag._id);
} catch (error) {
logger.error('[updateTagPosition] Error updating tag position', error);
return { message: 'Error updating tag position' };
}
};
module.exports = {
SAVED_TAG,
ConversationTag,
getConversationTags: async (user) => {
try {
const cTags = await ConversationTag.find({ user }).sort({ position: 1 }).lean();
cTags.sort((a, b) => (a.tag === SAVED_TAG ? -1 : b.tag === SAVED_TAG ? 1 : 0));
return cTags;
} catch (error) {
logger.error('[getShare] Error getting share link', error);
return { message: 'Error getting share link' };
}
},
createConversationTag,
updateConversationTag: async (user, tag, data) => {
try {
const cTag = await ConversationTag.findOne({ user, tag });
if (!cTag) {
return createConversationTag(user, data);
}
if (cTag.tag !== data.tag || cTag.description !== data.description) {
cTag.tag = data.tag;
cTag.description = data.description === undefined ? cTag.description : data.description;
await cTag.save();
}
if (data.position !== undefined && cTag.position !== data.position) {
await updateTagPosition(user, tag, data.position);
}
// update conversation tags properties
replaceOrRemoveTagInConversations(user, tag, data.tag);
return await ConversationTag.findOne({ user, tag: data.tag });
} catch (error) {
logger.error('[updateConversationTag] Error updating conversation tag', error);
return { message: 'Error updating conversation tag' };
}
},
deleteConversationTag: async (user, tag) => {
try {
const currentTag = await ConversationTag.findOne({ user, tag });
if (!currentTag) {
return;
}
await currentTag.deleteOne({ user, tag });
await replaceOrRemoveTagInConversations(user, tag, null);
return currentTag;
} catch (error) {
logger.error('[deleteConversationTag] Error deleting conversation tag', error);
return { message: 'Error deleting conversation tag' };
}
},
updateTagsForConversation,
rebuildConversationTags: async (user) => {
try {
const conversations = await Conversation.find({ user }).select('tags');
const tagCountMap = {};
// Count the occurrences of each tag
conversations.forEach((conversation) => {
conversation.tags.forEach((tag) => {
if (tagCountMap[tag]) {
tagCountMap[tag]++;
} else {
tagCountMap[tag] = 1;
}
});
});
const tags = await ConversationTag.find({ user }).sort({ position: -1 });
// Update existing tags and add new tags
for (const [tag, count] of Object.entries(tagCountMap)) {
const existingTag = tags.find((t) => t.tag === tag);
if (existingTag) {
existingTag.count = count;
await existingTag.save();
} else {
const newTag = new ConversationTag({ user, tag, count });
tags.push(newTag);
await newTag.save();
}
}
// Set count to 0 for tags that are not in the grouped tags
for (const tag of tags) {
if (!tagCountMap[tag.tag]) {
tag.count = 0;
await tag.save();
}
}
// Sort tags by position in descending order
tags.sort((a, b) => a.position - b.position);
// Move the tag with name "saved" to the first position
const savedTagIndex = tags.findIndex((tag) => tag.tag === SAVED_TAG);
if (savedTagIndex !== -1) {
const [savedTag] = tags.splice(savedTagIndex, 1);
tags.unshift(savedTag);
}
// Reassign positions starting from 0
tags.forEach((tag, index) => {
tag.position = index;
tag.save();
});
return tags;
} catch (error) {
logger.error('[rearrangeTags] Error rearranging tags', error);
return { message: 'Error rearranging tags' };
}
},
};

View File

@@ -35,34 +35,82 @@ const idSchema = z.string().uuid();
* @throws {Error} If there is an error in saving the message.
*/
async function saveMessage(req, params, metadata) {
if (!req?.user?.id) {
throw new Error('User not authenticated');
}
const validConvoId = idSchema.safeParse(params.conversationId);
if (!validConvoId.success) {
logger.warn(`Invalid conversation ID: ${params.conversationId}`);
logger.info(`---\`saveMessage\` context: ${metadata?.context}`);
logger.info(`---Invalid conversation ID Params: ${JSON.stringify(params, null, 2)}`);
return;
}
try {
if (!req || !req.user || !req.user.id) {
throw new Error('User not authenticated');
}
const {
text,
error,
model,
files,
plugin,
sender,
plugins,
iconURL,
endpoint,
isEdited,
messageId,
unfinished,
tokenCount,
newMessageId,
finish_reason,
conversationId,
parentMessageId,
isCreatedByUser,
} = params;
const validConvoId = idSchema.safeParse(conversationId);
if (!validConvoId.success) {
logger.warn(`Invalid conversation ID: ${conversationId}`);
if (metadata && metadata?.context) {
logger.info(`---\`saveMessage\` context: ${metadata.context}`);
}
logger.info(`---Invalid conversation ID Params:
${JSON.stringify(params, null, 2)}
`);
return;
}
const update = {
...params,
user: req.user.id,
messageId: params.newMessageId || params.messageId,
iconURL,
endpoint,
messageId: newMessageId || messageId,
conversationId,
parentMessageId,
sender,
text,
isCreatedByUser,
isEdited,
finish_reason,
error,
unfinished,
tokenCount,
plugin,
plugins,
model,
};
const message = await Message.findOneAndUpdate(
{ messageId: params.messageId, user: req.user.id },
update,
{ upsert: true, new: true },
);
if (files) {
update.files = files;
}
const message = await Message.findOneAndUpdate({ messageId, user: req.user.id }, update, {
upsert: true,
new: true,
});
return message.toObject();
} catch (err) {
logger.error('Error saving message:', err);
logger.info(`---\`saveMessage\` context: ${metadata?.context}`);
if (metadata && metadata?.context) {
logger.info(`---\`saveMessage\` context: ${metadata.context}`);
}
throw err;
}
}
@@ -164,8 +212,8 @@ async function updateMessageText(req, { messageId, text }) {
*
* @async
* @function updateMessage
* @param {Object} req - The request object.
* @param {Object} message - The message object containing update data.
* @param {Object} req - The request object.
* @param {string} message.messageId - The unique identifier for the message.
* @param {string} [message.text] - The new text content of the message.
* @param {Object[]} [message.files] - The files associated with the message.
@@ -269,7 +317,7 @@ async function getMessages(filter, select) {
* @async
* @function deleteMessages
* @param {Object} filter - The filter criteria to find messages to delete.
* @returns {Promise<Object>} The metadata with count of deleted messages.
* @returns {Promise<Number>} The number of deleted messages.
* @throws {Error} If there is an error in deleting messages.
*/
async function deleteMessages(filter) {

View File

@@ -38,8 +38,7 @@ module.exports = {
savePreset: async (user, { presetId, newPresetId, defaultPreset, ...preset }) => {
try {
const setter = { $set: {} };
const { user: _, ...cleanPreset } = preset;
const update = { presetId, ...cleanPreset };
const update = { presetId, ...preset };
if (preset.tools && Array.isArray(preset.tools)) {
update.tools =
preset.tools

View File

@@ -1,5 +1,4 @@
const { model } = require('mongoose');
const { GLOBAL_PROJECT_NAME } = require('librechat-data-provider').Constants;
const projectSchema = require('~/models/schema/projectSchema');
const Project = model('Project', projectSchema);
@@ -34,7 +33,7 @@ const getProjectByName = async function (projectName, fieldsToSelect = null) {
const update = { $setOnInsert: { name: projectName } };
const options = {
new: true,
upsert: projectName === GLOBAL_PROJECT_NAME,
upsert: projectName === 'instance',
lean: true,
select: fieldsToSelect,
};
@@ -82,55 +81,10 @@ const removeGroupFromAllProjects = async (promptGroupId) => {
await Project.updateMany({}, { $pull: { promptGroupIds: promptGroupId } });
};
/**
* Add an array of agent IDs to a project's agentIds array, ensuring uniqueness.
*
* @param {string} projectId - The ID of the project to update.
* @param {string[]} agentIds - The array of agent IDs to add to the project.
* @returns {Promise<MongoProject>} The updated project document.
*/
const addAgentIdsToProject = async function (projectId, agentIds) {
return await Project.findByIdAndUpdate(
projectId,
{ $addToSet: { agentIds: { $each: agentIds } } },
{ new: true },
);
};
/**
* Remove an array of agent IDs from a project's agentIds array.
*
* @param {string} projectId - The ID of the project to update.
* @param {string[]} agentIds - The array of agent IDs to remove from the project.
* @returns {Promise<MongoProject>} The updated project document.
*/
const removeAgentIdsFromProject = async function (projectId, agentIds) {
return await Project.findByIdAndUpdate(
projectId,
{ $pull: { agentIds: { $in: agentIds } } },
{ new: true },
);
};
/**
* Remove an agent ID from all projects.
*
* @param {string} agentId - The ID of the agent to remove from projects.
* @returns {Promise<void>}
*/
const removeAgentFromAllProjects = async (agentId) => {
await Project.updateMany({}, { $pull: { agentIds: agentId } });
};
module.exports = {
getProjectById,
getProjectByName,
/* prompts */
addGroupIdsToProject,
removeGroupIdsFromProject,
removeGroupFromAllProjects,
/* agents */
addAgentIdsToProject,
removeAgentIdsFromProject,
removeAgentFromAllProjects,
};

View File

@@ -1,5 +1,5 @@
const { ObjectId } = require('mongodb');
const { SystemRoles, SystemCategories, Constants } = require('librechat-data-provider');
const { SystemRoles, SystemCategories } = require('librechat-data-provider');
const {
getProjectByName,
addGroupIdsToProject,
@@ -7,7 +7,6 @@ const {
removeGroupFromAllProjects,
} = require('./Project');
const { Prompt, PromptGroup } = require('./schema/promptSchema');
const { escapeRegExp } = require('~/server/utils');
const { logger } = require('~/config');
/**
@@ -107,7 +106,7 @@ const getAllPromptGroups = async (req, filter) => {
let searchShared = true;
let searchSharedOnly = false;
if (name) {
query.name = new RegExp(escapeRegExp(name), 'i');
query.name = new RegExp(name, 'i');
}
if (!query.category) {
delete query.category;
@@ -124,7 +123,7 @@ const getAllPromptGroups = async (req, filter) => {
let combinedQuery = query;
if (searchShared) {
const project = await getProjectByName(Constants.GLOBAL_PROJECT_NAME, 'promptGroupIds');
const project = await getProjectByName('instance', 'promptGroupIds');
if (project && project.promptGroupIds.length > 0) {
const projectQuery = { _id: { $in: project.promptGroupIds }, ...query };
delete projectQuery.author;
@@ -160,7 +159,7 @@ const getPromptGroups = async (req, filter) => {
let searchShared = true;
let searchSharedOnly = false;
if (name) {
query.name = new RegExp(escapeRegExp(name), 'i');
query.name = new RegExp(name, 'i');
}
if (!query.category) {
delete query.category;
@@ -178,7 +177,7 @@ const getPromptGroups = async (req, filter) => {
if (searchShared) {
// const projects = req.user.projects || []; // TODO: handle multiple projects
const project = await getProjectByName(Constants.GLOBAL_PROJECT_NAME, 'promptGroupIds');
const project = await getProjectByName('instance', 'promptGroupIds');
if (project && project.promptGroupIds.length > 0) {
const projectQuery = { _id: { $in: project.promptGroupIds }, ...query };
delete projectQuery.author;

View File

@@ -1,17 +1,6 @@
const {
CacheKeys,
SystemRoles,
roleDefaults,
PermissionTypes,
removeNullishValues,
agentPermissionsSchema,
promptPermissionsSchema,
bookmarkPermissionsSchema,
multiConvoPermissionsSchema,
} = require('librechat-data-provider');
const { SystemRoles, CacheKeys, roleDefaults } = require('librechat-data-provider');
const getLogStores = require('~/cache/getLogStores');
const Role = require('~/models/schema/roleSchema');
const { logger } = require('~/config');
/**
* Retrieve a role by name and convert the found role document to a plain object.
@@ -72,69 +61,9 @@ const updateRoleByName = async function (roleName, updates) {
}
};
const permissionSchemas = {
[PermissionTypes.AGENTS]: agentPermissionsSchema,
[PermissionTypes.PROMPTS]: promptPermissionsSchema,
[PermissionTypes.BOOKMARKS]: bookmarkPermissionsSchema,
[PermissionTypes.MULTI_CONVO]: multiConvoPermissionsSchema,
};
/**
* Updates access permissions for a specific role and multiple permission types.
* @param {SystemRoles} roleName - The role to update.
* @param {Object.<PermissionTypes, Object.<Permissions, boolean>>} permissionsUpdate - Permissions to update and their values.
*/
async function updateAccessPermissions(roleName, permissionsUpdate) {
const updates = {};
for (const [permissionType, permissions] of Object.entries(permissionsUpdate)) {
if (permissionSchemas[permissionType]) {
updates[permissionType] = removeNullishValues(permissions);
}
}
if (Object.keys(updates).length === 0) {
return;
}
try {
const role = await getRoleByName(roleName);
if (!role) {
return;
}
const updatedPermissions = {};
let hasChanges = false;
for (const [permissionType, permissions] of Object.entries(updates)) {
const currentPermissions = role[permissionType] || {};
updatedPermissions[permissionType] = { ...currentPermissions };
for (const [permission, value] of Object.entries(permissions)) {
if (currentPermissions[permission] !== value) {
updatedPermissions[permissionType][permission] = value;
hasChanges = true;
logger.info(
`Updating '${roleName}' role ${permissionType} '${permission}' permission from ${currentPermissions[permission]} to: ${value}`,
);
}
}
}
if (hasChanges) {
await updateRoleByName(roleName, updatedPermissions);
logger.info(`Updated '${roleName}' role permissions`);
} else {
logger.info(`No changes needed for '${roleName}' role permissions`);
}
} catch (error) {
logger.error(`Failed to update ${roleName} role permissions:`, error);
}
}
/**
* Initialize default roles in the system.
* Creates the default roles (ADMIN, USER) if they don't exist in the database.
* Updates existing roles with new permission types if they're missing.
*
* @returns {Promise<void>}
*/
@@ -142,30 +71,16 @@ const initializeRoles = async function () {
const defaultRoles = [SystemRoles.ADMIN, SystemRoles.USER];
for (const roleName of defaultRoles) {
let role = await Role.findOne({ name: roleName });
let role = await Role.findOne({ name: roleName }).select('name').lean();
if (!role) {
// Create new role if it doesn't exist
role = new Role(roleDefaults[roleName]);
} else {
// Add missing permission types
let isUpdated = false;
for (const permType of Object.values(PermissionTypes)) {
if (!role[permType]) {
role[permType] = roleDefaults[roleName][permType];
isUpdated = true;
}
}
if (isUpdated) {
await role.save();
}
await role.save();
}
await role.save();
}
};
module.exports = {
getRoleByName,
initializeRoles,
updateRoleByName,
updateAccessPermissions,
};

View File

@@ -1,420 +0,0 @@
const mongoose = require('mongoose');
const { MongoMemoryServer } = require('mongodb-memory-server');
const {
SystemRoles,
PermissionTypes,
roleDefaults,
Permissions,
} = require('librechat-data-provider');
const { updateAccessPermissions, initializeRoles } = require('~/models/Role');
const getLogStores = require('~/cache/getLogStores');
const Role = require('~/models/schema/roleSchema');
// Mock the cache
jest.mock('~/cache/getLogStores', () => {
return jest.fn().mockReturnValue({
get: jest.fn(),
set: jest.fn(),
del: jest.fn(),
});
});
let mongoServer;
beforeAll(async () => {
mongoServer = await MongoMemoryServer.create();
const mongoUri = mongoServer.getUri();
await mongoose.connect(mongoUri);
});
afterAll(async () => {
await mongoose.disconnect();
await mongoServer.stop();
});
beforeEach(async () => {
await Role.deleteMany({});
getLogStores.mockClear();
});
describe('updateAccessPermissions', () => {
it('should update permissions when changes are needed', async () => {
await new Role({
name: SystemRoles.USER,
[PermissionTypes.PROMPTS]: {
CREATE: true,
USE: true,
SHARED_GLOBAL: false,
},
}).save();
await updateAccessPermissions(SystemRoles.USER, {
[PermissionTypes.PROMPTS]: {
CREATE: true,
USE: true,
SHARED_GLOBAL: true,
},
});
const updatedRole = await Role.findOne({ name: SystemRoles.USER }).lean();
expect(updatedRole[PermissionTypes.PROMPTS]).toEqual({
CREATE: true,
USE: true,
SHARED_GLOBAL: true,
});
});
it('should not update permissions when no changes are needed', async () => {
await new Role({
name: SystemRoles.USER,
[PermissionTypes.PROMPTS]: {
CREATE: true,
USE: true,
SHARED_GLOBAL: false,
},
}).save();
await updateAccessPermissions(SystemRoles.USER, {
[PermissionTypes.PROMPTS]: {
CREATE: true,
USE: true,
SHARED_GLOBAL: false,
},
});
const updatedRole = await Role.findOne({ name: SystemRoles.USER }).lean();
expect(updatedRole[PermissionTypes.PROMPTS]).toEqual({
CREATE: true,
USE: true,
SHARED_GLOBAL: false,
});
});
it('should handle non-existent roles', async () => {
await updateAccessPermissions('NON_EXISTENT_ROLE', {
[PermissionTypes.PROMPTS]: {
CREATE: true,
},
});
const role = await Role.findOne({ name: 'NON_EXISTENT_ROLE' });
expect(role).toBeNull();
});
it('should update only specified permissions', async () => {
await new Role({
name: SystemRoles.USER,
[PermissionTypes.PROMPTS]: {
CREATE: true,
USE: true,
SHARED_GLOBAL: false,
},
}).save();
await updateAccessPermissions(SystemRoles.USER, {
[PermissionTypes.PROMPTS]: {
SHARED_GLOBAL: true,
},
});
const updatedRole = await Role.findOne({ name: SystemRoles.USER }).lean();
expect(updatedRole[PermissionTypes.PROMPTS]).toEqual({
CREATE: true,
USE: true,
SHARED_GLOBAL: true,
});
});
it('should handle partial updates', async () => {
await new Role({
name: SystemRoles.USER,
[PermissionTypes.PROMPTS]: {
CREATE: true,
USE: true,
SHARED_GLOBAL: false,
},
}).save();
await updateAccessPermissions(SystemRoles.USER, {
[PermissionTypes.PROMPTS]: {
USE: false,
},
});
const updatedRole = await Role.findOne({ name: SystemRoles.USER }).lean();
expect(updatedRole[PermissionTypes.PROMPTS]).toEqual({
CREATE: true,
USE: false,
SHARED_GLOBAL: false,
});
});
it('should update multiple permission types at once', async () => {
await new Role({
name: SystemRoles.USER,
[PermissionTypes.PROMPTS]: {
CREATE: true,
USE: true,
SHARED_GLOBAL: false,
},
[PermissionTypes.BOOKMARKS]: {
USE: true,
},
}).save();
await updateAccessPermissions(SystemRoles.USER, {
[PermissionTypes.PROMPTS]: { USE: false, SHARED_GLOBAL: true },
[PermissionTypes.BOOKMARKS]: { USE: false },
});
const updatedRole = await Role.findOne({ name: SystemRoles.USER }).lean();
expect(updatedRole[PermissionTypes.PROMPTS]).toEqual({
CREATE: true,
USE: false,
SHARED_GLOBAL: true,
});
expect(updatedRole[PermissionTypes.BOOKMARKS]).toEqual({
USE: false,
});
});
it('should handle updates for a single permission type', async () => {
await new Role({
name: SystemRoles.USER,
[PermissionTypes.PROMPTS]: {
CREATE: true,
USE: true,
SHARED_GLOBAL: false,
},
}).save();
await updateAccessPermissions(SystemRoles.USER, {
[PermissionTypes.PROMPTS]: { USE: false, SHARED_GLOBAL: true },
});
const updatedRole = await Role.findOne({ name: SystemRoles.USER }).lean();
expect(updatedRole[PermissionTypes.PROMPTS]).toEqual({
CREATE: true,
USE: false,
SHARED_GLOBAL: true,
});
});
it('should update MULTI_CONVO permissions', async () => {
await new Role({
name: SystemRoles.USER,
[PermissionTypes.MULTI_CONVO]: {
USE: false,
},
}).save();
await updateAccessPermissions(SystemRoles.USER, {
[PermissionTypes.MULTI_CONVO]: {
USE: true,
},
});
const updatedRole = await Role.findOne({ name: SystemRoles.USER }).lean();
expect(updatedRole[PermissionTypes.MULTI_CONVO]).toEqual({
USE: true,
});
});
it('should update MULTI_CONVO permissions along with other permission types', async () => {
await new Role({
name: SystemRoles.USER,
[PermissionTypes.PROMPTS]: {
CREATE: true,
USE: true,
SHARED_GLOBAL: false,
},
[PermissionTypes.MULTI_CONVO]: {
USE: false,
},
}).save();
await updateAccessPermissions(SystemRoles.USER, {
[PermissionTypes.PROMPTS]: { SHARED_GLOBAL: true },
[PermissionTypes.MULTI_CONVO]: { USE: true },
});
const updatedRole = await Role.findOne({ name: SystemRoles.USER }).lean();
expect(updatedRole[PermissionTypes.PROMPTS]).toEqual({
CREATE: true,
USE: true,
SHARED_GLOBAL: true,
});
expect(updatedRole[PermissionTypes.MULTI_CONVO]).toEqual({
USE: true,
});
});
it('should not update MULTI_CONVO permissions when no changes are needed', async () => {
await new Role({
name: SystemRoles.USER,
[PermissionTypes.MULTI_CONVO]: {
USE: true,
},
}).save();
await updateAccessPermissions(SystemRoles.USER, {
[PermissionTypes.MULTI_CONVO]: {
USE: true,
},
});
const updatedRole = await Role.findOne({ name: SystemRoles.USER }).lean();
expect(updatedRole[PermissionTypes.MULTI_CONVO]).toEqual({
USE: true,
});
});
});
describe('initializeRoles', () => {
beforeEach(async () => {
await Role.deleteMany({});
});
it('should create default roles if they do not exist', async () => {
await initializeRoles();
const adminRole = await Role.findOne({ name: SystemRoles.ADMIN }).lean();
const userRole = await Role.findOne({ name: SystemRoles.USER }).lean();
expect(adminRole).toBeTruthy();
expect(userRole).toBeTruthy();
// Check if all permission types exist
Object.values(PermissionTypes).forEach((permType) => {
expect(adminRole[permType]).toBeDefined();
expect(userRole[permType]).toBeDefined();
});
// Check if permissions match defaults (example for ADMIN role)
expect(adminRole[PermissionTypes.PROMPTS].SHARED_GLOBAL).toBe(true);
expect(adminRole[PermissionTypes.BOOKMARKS].USE).toBe(true);
expect(adminRole[PermissionTypes.AGENTS].CREATE).toBe(true);
});
it('should not modify existing permissions for existing roles', async () => {
const customUserRole = {
name: SystemRoles.USER,
[PermissionTypes.PROMPTS]: {
[Permissions.USE]: false,
[Permissions.CREATE]: true,
[Permissions.SHARED_GLOBAL]: true,
},
[PermissionTypes.BOOKMARKS]: {
[Permissions.USE]: false,
},
};
await new Role(customUserRole).save();
await initializeRoles();
const userRole = await Role.findOne({ name: SystemRoles.USER }).lean();
expect(userRole[PermissionTypes.PROMPTS]).toEqual(customUserRole[PermissionTypes.PROMPTS]);
expect(userRole[PermissionTypes.BOOKMARKS]).toEqual(customUserRole[PermissionTypes.BOOKMARKS]);
expect(userRole[PermissionTypes.AGENTS]).toBeDefined();
});
it('should add new permission types to existing roles', async () => {
const partialUserRole = {
name: SystemRoles.USER,
[PermissionTypes.PROMPTS]: roleDefaults[SystemRoles.USER][PermissionTypes.PROMPTS],
[PermissionTypes.BOOKMARKS]: roleDefaults[SystemRoles.USER][PermissionTypes.BOOKMARKS],
};
await new Role(partialUserRole).save();
await initializeRoles();
const userRole = await Role.findOne({ name: SystemRoles.USER }).lean();
expect(userRole[PermissionTypes.AGENTS]).toBeDefined();
expect(userRole[PermissionTypes.AGENTS].CREATE).toBeDefined();
expect(userRole[PermissionTypes.AGENTS].USE).toBeDefined();
expect(userRole[PermissionTypes.AGENTS].SHARED_GLOBAL).toBeDefined();
});
it('should handle multiple runs without duplicating or modifying data', async () => {
await initializeRoles();
await initializeRoles();
const adminRoles = await Role.find({ name: SystemRoles.ADMIN });
const userRoles = await Role.find({ name: SystemRoles.USER });
expect(adminRoles).toHaveLength(1);
expect(userRoles).toHaveLength(1);
const adminRole = adminRoles[0].toObject();
const userRole = userRoles[0].toObject();
// Check if all permission types exist
Object.values(PermissionTypes).forEach((permType) => {
expect(adminRole[permType]).toBeDefined();
expect(userRole[permType]).toBeDefined();
});
});
it('should update roles with missing permission types from roleDefaults', async () => {
const partialAdminRole = {
name: SystemRoles.ADMIN,
[PermissionTypes.PROMPTS]: {
[Permissions.USE]: false,
[Permissions.CREATE]: false,
[Permissions.SHARED_GLOBAL]: false,
},
[PermissionTypes.BOOKMARKS]: roleDefaults[SystemRoles.ADMIN][PermissionTypes.BOOKMARKS],
};
await new Role(partialAdminRole).save();
await initializeRoles();
const adminRole = await Role.findOne({ name: SystemRoles.ADMIN }).lean();
expect(adminRole[PermissionTypes.PROMPTS]).toEqual(partialAdminRole[PermissionTypes.PROMPTS]);
expect(adminRole[PermissionTypes.AGENTS]).toBeDefined();
expect(adminRole[PermissionTypes.AGENTS].CREATE).toBeDefined();
expect(adminRole[PermissionTypes.AGENTS].USE).toBeDefined();
expect(adminRole[PermissionTypes.AGENTS].SHARED_GLOBAL).toBeDefined();
});
it('should include MULTI_CONVO permissions when creating default roles', async () => {
await initializeRoles();
const adminRole = await Role.findOne({ name: SystemRoles.ADMIN }).lean();
const userRole = await Role.findOne({ name: SystemRoles.USER }).lean();
expect(adminRole[PermissionTypes.MULTI_CONVO]).toBeDefined();
expect(userRole[PermissionTypes.MULTI_CONVO]).toBeDefined();
// Check if MULTI_CONVO permissions match defaults
expect(adminRole[PermissionTypes.MULTI_CONVO].USE).toBe(
roleDefaults[SystemRoles.ADMIN][PermissionTypes.MULTI_CONVO].USE,
);
expect(userRole[PermissionTypes.MULTI_CONVO].USE).toBe(
roleDefaults[SystemRoles.USER][PermissionTypes.MULTI_CONVO].USE,
);
});
it('should add MULTI_CONVO permissions to existing roles without them', async () => {
const partialUserRole = {
name: SystemRoles.USER,
[PermissionTypes.PROMPTS]: roleDefaults[SystemRoles.USER][PermissionTypes.PROMPTS],
[PermissionTypes.BOOKMARKS]: roleDefaults[SystemRoles.USER][PermissionTypes.BOOKMARKS],
};
await new Role(partialUserRole).save();
await initializeRoles();
const userRole = await Role.findOne({ name: SystemRoles.USER }).lean();
expect(userRole[PermissionTypes.MULTI_CONVO]).toBeDefined();
expect(userRole[PermissionTypes.MULTI_CONVO].USE).toBeDefined();
});
});

View File

@@ -1,6 +1,6 @@
const crypto = require('crypto');
const mongoose = require('mongoose');
const signPayload = require('~/server/services/signPayload');
const { hashToken } = require('~/server/utils/crypto');
const { logger } = require('~/config');
const { REFRESH_TOKEN_EXPIRY } = process.env ?? {};
@@ -39,7 +39,8 @@ sessionSchema.methods.generateRefreshToken = async function () {
expirationTime: Math.floor((expiresIn - Date.now()) / 1000),
});
this.refreshTokenHash = await hashToken(refreshToken);
const hash = crypto.createHash('sha256');
this.refreshTokenHash = hash.update(refreshToken).digest('hex');
await this.save();

View File

@@ -1,252 +1,117 @@
const { nanoid } = require('nanoid');
const { Constants } = require('librechat-data-provider');
const SharedLink = require('./schema/shareSchema');
const crypto = require('crypto');
const { getMessages } = require('./Message');
const SharedLink = require('./schema/shareSchema');
const logger = require('~/config/winston');
/**
* Anonymizes a conversation ID
* @returns {string} The anonymized conversation ID
*/
function anonymizeConvoId() {
return `convo_${nanoid()}`;
}
module.exports = {
SharedLink,
getSharedMessages: async (shareId) => {
try {
const share = await SharedLink.findOne({ shareId })
.populate({
path: 'messages',
select: '-_id -__v -user',
})
.select('-_id -__v -user')
.lean();
/**
* Anonymizes an assistant ID
* @returns {string} The anonymized assistant ID
*/
function anonymizeAssistantId() {
return `a_${nanoid()}`;
}
if (!share || !share.conversationId || !share.isPublic) {
return null;
}
/**
* Anonymizes a message ID
* @param {string} id - The original message ID
* @returns {string} The anonymized message ID
*/
function anonymizeMessageId(id) {
return id === Constants.NO_PARENT ? id : `msg_${nanoid()}`;
}
/**
* Anonymizes a conversation object
* @param {object} conversation - The conversation object
* @returns {object} The anonymized conversation object
*/
function anonymizeConvo(conversation) {
const newConvo = { ...conversation };
if (newConvo.assistant_id) {
newConvo.assistant_id = anonymizeAssistantId();
}
return newConvo;
}
/**
* Anonymizes messages in a conversation
* @param {TMessage[]} messages - The original messages
* @param {string} newConvoId - The new conversation ID
* @returns {TMessage[]} The anonymized messages
*/
function anonymizeMessages(messages, newConvoId) {
const idMap = new Map();
return messages.map((message) => {
const newMessageId = anonymizeMessageId(message.messageId);
idMap.set(message.messageId, newMessageId);
const anonymizedMessage = Object.assign(message, {
messageId: newMessageId,
parentMessageId:
idMap.get(message.parentMessageId) || anonymizeMessageId(message.parentMessageId),
conversationId: newConvoId,
});
if (anonymizedMessage.model && anonymizedMessage.model.startsWith('asst_')) {
anonymizedMessage.model = anonymizeAssistantId();
return share;
} catch (error) {
logger.error('[getShare] Error getting share link', error);
throw new Error('Error getting share link');
}
},
return anonymizedMessage;
});
}
/**
* Retrieves shared messages for a given share ID
* @param {string} shareId - The share ID
* @returns {Promise<object|null>} The shared conversation data or null if not found
*/
async function getSharedMessages(shareId) {
try {
const share = await SharedLink.findOne({ shareId })
.populate({
path: 'messages',
select: '-_id -__v -user',
})
.select('-_id -__v -user')
.lean();
if (!share || !share.conversationId || !share.isPublic) {
return null;
}
const newConvoId = anonymizeConvoId();
return Object.assign(share, {
conversationId: newConvoId,
messages: anonymizeMessages(share.messages, newConvoId),
});
} catch (error) {
logger.error('[getShare] Error getting share link', error);
throw new Error('Error getting share link');
}
}
/**
* Retrieves shared links for a user
* @param {string} user - The user ID
* @param {number} [pageNumber=1] - The page number
* @param {number} [pageSize=25] - The page size
* @param {boolean} [isPublic=true] - Whether to retrieve public links only
* @returns {Promise<object>} The shared links and pagination data
*/
async function getSharedLinks(user, pageNumber = 1, pageSize = 25, isPublic = true) {
const query = { user, isPublic };
try {
const [totalConvos, sharedLinks] = await Promise.all([
SharedLink.countDocuments(query),
SharedLink.find(query)
getSharedLinks: async (user, pageNumber = 1, pageSize = 25, isPublic = true) => {
const query = { user, isPublic };
try {
const totalConvos = (await SharedLink.countDocuments(query)) || 1;
const totalPages = Math.ceil(totalConvos / pageSize);
const shares = await SharedLink.find(query)
.sort({ updatedAt: -1 })
.skip((pageNumber - 1) * pageSize)
.limit(pageSize)
.select('-_id -__v -user')
.lean(),
]);
.lean();
const totalPages = Math.ceil((totalConvos || 1) / pageSize);
return { sharedLinks: shares, pages: totalPages, pageNumber, pageSize };
} catch (error) {
logger.error('[getShareByPage] Error getting shares', error);
throw new Error('Error getting shares');
}
},
return {
sharedLinks,
pages: totalPages,
pageNumber,
pageSize,
};
} catch (error) {
logger.error('[getShareByPage] Error getting shares', error);
throw new Error('Error getting shares');
}
}
createSharedLink: async (user, { conversationId, ...shareData }) => {
try {
const share = await SharedLink.findOne({ conversationId }).select('-_id -__v -user').lean();
if (share) {
return share;
}
/**
* Creates a new shared link
* @param {string} user - The user ID
* @param {object} shareData - The share data
* @param {string} shareData.conversationId - The conversation ID
* @returns {Promise<object>} The created shared link
*/
async function createSharedLink(user, { conversationId, ...shareData }) {
try {
const share = await SharedLink.findOne({ conversationId }).select('-_id -__v -user').lean();
if (share) {
const newConvoId = anonymizeConvoId();
const sharedConvo = anonymizeConvo(share);
return Object.assign(sharedConvo, {
conversationId: newConvoId,
messages: anonymizeMessages(share.messages, newConvoId),
const shareId = crypto.randomUUID();
const messages = await getMessages({ conversationId });
const update = { ...shareData, shareId, messages, user };
return await SharedLink.findOneAndUpdate({ conversationId: conversationId, user }, update, {
new: true,
upsert: true,
});
} catch (error) {
logger.error('[createSharedLink] Error creating shared link', error);
throw new Error('Error creating shared link');
}
},
const shareId = nanoid();
const messages = await getMessages({ conversationId });
const update = { ...shareData, shareId, messages, user };
const newShare = await SharedLink.findOneAndUpdate({ conversationId, user }, update, {
new: true,
upsert: true,
}).lean();
updateSharedLink: async (user, { conversationId, ...shareData }) => {
try {
const share = await SharedLink.findOne({ conversationId }).select('-_id -__v -user').lean();
if (!share) {
return { message: 'Share not found' };
}
const newConvoId = anonymizeConvoId();
const sharedConvo = anonymizeConvo(newShare);
return Object.assign(sharedConvo, {
conversationId: newConvoId,
messages: anonymizeMessages(newShare.messages, newConvoId),
});
} catch (error) {
logger.error('[createSharedLink] Error creating shared link', error);
throw new Error('Error creating shared link');
}
}
/**
* Updates an existing shared link
* @param {string} user - The user ID
* @param {object} shareData - The share data to update
* @param {string} shareData.conversationId - The conversation ID
* @returns {Promise<object>} The updated shared link
*/
async function updateSharedLink(user, { conversationId, ...shareData }) {
try {
const share = await SharedLink.findOne({ conversationId }).select('-_id -__v -user').lean();
if (!share) {
return { message: 'Share not found' };
// update messages to the latest
const messages = await getMessages({ conversationId });
const update = { ...shareData, messages, user };
return await SharedLink.findOneAndUpdate({ conversationId: conversationId, user }, update, {
new: true,
upsert: false,
});
} catch (error) {
logger.error('[updateSharedLink] Error updating shared link', error);
throw new Error('Error updating shared link');
}
},
const messages = await getMessages({ conversationId });
const update = { ...shareData, messages, user };
const updatedShare = await SharedLink.findOneAndUpdate({ conversationId, user }, update, {
new: true,
upsert: false,
}).lean();
const newConvoId = anonymizeConvoId();
const sharedConvo = anonymizeConvo(updatedShare);
return Object.assign(sharedConvo, {
conversationId: newConvoId,
messages: anonymizeMessages(updatedShare.messages, newConvoId),
});
} catch (error) {
logger.error('[updateSharedLink] Error updating shared link', error);
throw new Error('Error updating shared link');
}
}
/**
* Deletes a shared link
* @param {string} user - The user ID
* @param {object} params - The deletion parameters
* @param {string} params.shareId - The share ID to delete
* @returns {Promise<object>} The result of the deletion
*/
async function deleteSharedLink(user, { shareId }) {
try {
const result = await SharedLink.findOneAndDelete({ shareId, user });
return result ? { message: 'Share deleted successfully' } : { message: 'Share not found' };
} catch (error) {
logger.error('[deleteSharedLink] Error deleting shared link', error);
throw new Error('Error deleting shared link');
}
}
/**
* Deletes all shared links for a specific user
* @param {string} user - The user ID
* @returns {Promise<object>} The result of the deletion
*/
async function deleteAllSharedLinks(user) {
try {
const result = await SharedLink.deleteMany({ user });
return {
message: 'All shared links have been deleted successfully',
deletedCount: result.deletedCount,
};
} catch (error) {
logger.error('[deleteAllSharedLinks] Error deleting shared links', error);
throw new Error('Error deleting shared links');
}
}
module.exports = {
SharedLink,
getSharedLinks,
createSharedLink,
updateSharedLink,
deleteSharedLink,
getSharedMessages,
deleteAllSharedLinks,
deleteSharedLink: async (user, { shareId }) => {
try {
const share = await SharedLink.findOne({ shareId, user });
if (!share) {
return { message: 'Share not found' };
}
return await SharedLink.findOneAndDelete({ shareId, user });
} catch (error) {
logger.error('[deleteSharedLink] Error deleting shared link', error);
throw new Error('Error deleting shared link');
}
},
/**
* Deletes all shared links for a specific user.
* @param {string} user - The user ID.
* @returns {Promise<{ message: string, deletedCount?: number }>} A result object indicating success or error message.
*/
deleteAllSharedLinks: async (user) => {
try {
const result = await SharedLink.deleteMany({ user });
return {
message: 'All shared links have been deleted successfully',
deletedCount: result.deletedCount,
};
} catch (error) {
logger.error('[deleteAllSharedLinks] Error deleting shared links', error);
throw new Error('Error deleting shared links');
}
},
};

View File

@@ -1,117 +0,0 @@
const tokenSchema = require('./schema/tokenSchema');
const mongoose = require('mongoose');
const { logger } = require('~/config');
/**
* Token model.
* @type {mongoose.Model}
*/
const Token = mongoose.model('Token', tokenSchema);
/**
* Creates a new Token instance.
* @param {Object} tokenData - The data for the new Token.
* @param {mongoose.Types.ObjectId} tokenData.userId - The user's ID. It is required.
* @param {String} tokenData.email - The user's email.
* @param {String} tokenData.token - The token. It is required.
* @param {Number} tokenData.expiresIn - The number of seconds until the token expires.
* @returns {Promise<mongoose.Document>} The new Token instance.
* @throws Will throw an error if token creation fails.
*/
async function createToken(tokenData) {
try {
const currentTime = new Date();
const expiresAt = new Date(currentTime.getTime() + tokenData.expiresIn * 1000);
const newTokenData = {
...tokenData,
createdAt: currentTime,
expiresAt,
};
const newToken = new Token(newTokenData);
return await newToken.save();
} catch (error) {
logger.debug('An error occurred while creating token:', error);
throw error;
}
}
/**
* Finds a Token document that matches the provided query.
* @param {Object} query - The query to match against.
* @param {mongoose.Types.ObjectId|String} query.userId - The ID of the user.
* @param {String} query.token - The token value.
* @param {String} query.email - The email of the user.
* @returns {Promise<Object|null>} The matched Token document, or null if not found.
* @throws Will throw an error if the find operation fails.
*/
async function findToken(query) {
try {
const conditions = [];
if (query.userId) {
conditions.push({ userId: query.userId });
}
if (query.token) {
conditions.push({ token: query.token });
}
if (query.email) {
conditions.push({ email: query.email });
}
const token = await Token.findOne({
$and: conditions,
}).lean();
return token;
} catch (error) {
logger.debug('An error occurred while finding token:', error);
throw error;
}
}
/**
* Updates a Token document that matches the provided query.
* @param {Object} query - The query to match against.
* @param {mongoose.Types.ObjectId|String} query.userId - The ID of the user.
* @param {String} query.token - The token value.
* @param {Object} updateData - The data to update the Token with.
* @returns {Promise<mongoose.Document|null>} The updated Token document, or null if not found.
* @throws Will throw an error if the update operation fails.
*/
async function updateToken(query, updateData) {
try {
return await Token.findOneAndUpdate(query, updateData, { new: true });
} catch (error) {
logger.debug('An error occurred while updating token:', error);
throw error;
}
}
/**
* Deletes all Token documents that match the provided token, user ID, or email.
* @param {Object} query - The query to match against.
* @param {mongoose.Types.ObjectId|String} query.userId - The ID of the user.
* @param {String} query.token - The token value.
* @param {String} query.email - The email of the user.
* @returns {Promise<Object>} The result of the delete operation.
* @throws Will throw an error if the delete operation fails.
*/
async function deleteTokens(query) {
try {
return await Token.deleteMany({
$or: [{ userId: query.userId }, { token: query.token }, { email: query.email }],
});
} catch (error) {
logger.debug('An error occurred while deleting tokens:', error);
throw error;
}
}
module.exports = {
createToken,
findToken,
updateToken,
deleteTokens,
};

View File

@@ -1,12 +1,12 @@
const mongoose = require('mongoose');
const { isEnabled } = require('~/server/utils/handleText');
const { isEnabled } = require('../server/utils/handleText');
const transactionSchema = require('./schema/transaction');
const { getMultiplier, getCacheMultiplier } = require('./tx');
const { getMultiplier } = require('./tx');
const { logger } = require('~/config');
const Balance = require('./Balance');
const cancelRate = 1.15;
/** Method to calculate and set the tokenValue for a transaction */
// Method to calculate and set the tokenValue for a transaction
transactionSchema.methods.calculateTokenValue = function () {
if (!this.valueKey || !this.tokenType) {
this.tokenValue = this.rawAmount;
@@ -21,17 +21,15 @@ transactionSchema.methods.calculateTokenValue = function () {
}
};
/**
* Static method to create a transaction and update the balance
* @param {txData} txData - Transaction data.
*/
transactionSchema.statics.create = async function (txData) {
// Static method to create a transaction and update the balance
transactionSchema.statics.create = async function (transactionData) {
const Transaction = this;
const transaction = new Transaction(txData);
transaction.endpointTokenConfig = txData.endpointTokenConfig;
const transaction = new Transaction(transactionData);
transaction.endpointTokenConfig = transactionData.endpointTokenConfig;
transaction.calculateTokenValue();
// Save the transaction
await transaction.save();
if (!isEnabled(process.env.CHECK_BALANCE)) {
@@ -59,109 +57,6 @@ transactionSchema.statics.create = async function (txData) {
};
};
/**
* Static method to create a structured transaction and update the balance
* @param {txData} txData - Transaction data.
*/
transactionSchema.statics.createStructured = async function (txData) {
const Transaction = this;
const transaction = new Transaction({
...txData,
endpointTokenConfig: txData.endpointTokenConfig,
});
transaction.calculateStructuredTokenValue();
await transaction.save();
if (!isEnabled(process.env.CHECK_BALANCE)) {
return;
}
let balance = await Balance.findOne({ user: transaction.user }).lean();
let incrementValue = transaction.tokenValue;
if (balance && balance?.tokenCredits + incrementValue < 0) {
incrementValue = -balance.tokenCredits;
}
balance = await Balance.findOneAndUpdate(
{ user: transaction.user },
{ $inc: { tokenCredits: incrementValue } },
{ upsert: true, new: true },
).lean();
return {
rate: transaction.rate,
user: transaction.user.toString(),
balance: balance.tokenCredits,
[transaction.tokenType]: incrementValue,
};
};
/** Method to calculate token value for structured tokens */
transactionSchema.methods.calculateStructuredTokenValue = function () {
if (!this.tokenType) {
this.tokenValue = this.rawAmount;
return;
}
const { model, endpointTokenConfig } = this;
if (this.tokenType === 'prompt') {
const inputMultiplier = getMultiplier({ tokenType: 'prompt', model, endpointTokenConfig });
const writeMultiplier =
getCacheMultiplier({ cacheType: 'write', model, endpointTokenConfig }) ?? inputMultiplier;
const readMultiplier =
getCacheMultiplier({ cacheType: 'read', model, endpointTokenConfig }) ?? inputMultiplier;
this.rateDetail = {
input: inputMultiplier,
write: writeMultiplier,
read: readMultiplier,
};
const totalPromptTokens =
Math.abs(this.inputTokens || 0) +
Math.abs(this.writeTokens || 0) +
Math.abs(this.readTokens || 0);
if (totalPromptTokens > 0) {
this.rate =
(Math.abs(inputMultiplier * (this.inputTokens || 0)) +
Math.abs(writeMultiplier * (this.writeTokens || 0)) +
Math.abs(readMultiplier * (this.readTokens || 0))) /
totalPromptTokens;
} else {
this.rate = Math.abs(inputMultiplier); // Default to input rate if no tokens
}
this.tokenValue = -(
Math.abs(this.inputTokens || 0) * inputMultiplier +
Math.abs(this.writeTokens || 0) * writeMultiplier +
Math.abs(this.readTokens || 0) * readMultiplier
);
this.rawAmount = -totalPromptTokens;
} else if (this.tokenType === 'completion') {
const multiplier = getMultiplier({ tokenType: this.tokenType, model, endpointTokenConfig });
this.rate = Math.abs(multiplier);
this.tokenValue = -Math.abs(this.rawAmount) * multiplier;
this.rawAmount = -Math.abs(this.rawAmount);
}
if (this.context && this.tokenType === 'completion' && this.context === 'incomplete') {
this.tokenValue = Math.ceil(this.tokenValue * cancelRate);
this.rate *= cancelRate;
if (this.rateDetail) {
this.rateDetail = Object.fromEntries(
Object.entries(this.rateDetail).map(([k, v]) => [k, v * cancelRate]),
);
}
}
};
const Transaction = mongoose.model('Transaction', transactionSchema);
/**

View File

@@ -1,348 +0,0 @@
const mongoose = require('mongoose');
const { MongoMemoryServer } = require('mongodb-memory-server');
const Balance = require('./Balance');
const { spendTokens, spendStructuredTokens } = require('./spendTokens');
const { getMultiplier, getCacheMultiplier } = require('./tx');
let mongoServer;
beforeAll(async () => {
mongoServer = await MongoMemoryServer.create();
const mongoUri = mongoServer.getUri();
await mongoose.connect(mongoUri);
});
afterAll(async () => {
await mongoose.disconnect();
await mongoServer.stop();
});
beforeEach(async () => {
await mongoose.connection.dropDatabase();
});
describe('Regular Token Spending Tests', () => {
test('Balance should decrease when spending tokens with spendTokens', async () => {
// Arrange
const userId = new mongoose.Types.ObjectId();
const initialBalance = 10000000; // $10.00
await Balance.create({ user: userId, tokenCredits: initialBalance });
const model = 'gpt-3.5-turbo';
const txData = {
user: userId,
conversationId: 'test-conversation-id',
model,
context: 'test',
endpointTokenConfig: null,
};
const tokenUsage = {
promptTokens: 100,
completionTokens: 50,
};
// Act
process.env.CHECK_BALANCE = 'true';
await spendTokens(txData, tokenUsage);
// Assert
console.log('Initial Balance:', initialBalance);
const updatedBalance = await Balance.findOne({ user: userId });
console.log('Updated Balance:', updatedBalance.tokenCredits);
const promptMultiplier = getMultiplier({ model, tokenType: 'prompt' });
const completionMultiplier = getMultiplier({ model, tokenType: 'completion' });
const expectedPromptCost = tokenUsage.promptTokens * promptMultiplier;
const expectedCompletionCost = tokenUsage.completionTokens * completionMultiplier;
const expectedTotalCost = expectedPromptCost + expectedCompletionCost;
const expectedBalance = initialBalance - expectedTotalCost;
expect(updatedBalance.tokenCredits).toBeLessThan(initialBalance);
expect(updatedBalance.tokenCredits).toBeCloseTo(expectedBalance, 0);
console.log('Expected Total Cost:', expectedTotalCost);
console.log('Actual Balance Decrease:', initialBalance - updatedBalance.tokenCredits);
});
test('spendTokens should handle zero completion tokens', async () => {
// Arrange
const userId = new mongoose.Types.ObjectId();
const initialBalance = 10000000; // $10.00
await Balance.create({ user: userId, tokenCredits: initialBalance });
const model = 'gpt-3.5-turbo';
const txData = {
user: userId,
conversationId: 'test-conversation-id',
model,
context: 'test',
endpointTokenConfig: null,
};
const tokenUsage = {
promptTokens: 100,
completionTokens: 0,
};
// Act
process.env.CHECK_BALANCE = 'true';
await spendTokens(txData, tokenUsage);
// Assert
const updatedBalance = await Balance.findOne({ user: userId });
const promptMultiplier = getMultiplier({ model, tokenType: 'prompt' });
const expectedCost = tokenUsage.promptTokens * promptMultiplier;
expect(updatedBalance.tokenCredits).toBeCloseTo(initialBalance - expectedCost, 0);
console.log('Initial Balance:', initialBalance);
console.log('Updated Balance:', updatedBalance.tokenCredits);
console.log('Expected Cost:', expectedCost);
});
test('spendTokens should handle undefined token counts', async () => {
const userId = new mongoose.Types.ObjectId();
const initialBalance = 10000000; // $10.00
await Balance.create({ user: userId, tokenCredits: initialBalance });
const model = 'gpt-3.5-turbo';
const txData = {
user: userId,
conversationId: 'test-conversation-id',
model,
context: 'test',
endpointTokenConfig: null,
};
const tokenUsage = {};
const result = await spendTokens(txData, tokenUsage);
expect(result).toBeUndefined();
});
test('spendTokens should handle only prompt tokens', async () => {
const userId = new mongoose.Types.ObjectId();
const initialBalance = 10000000; // $10.00
await Balance.create({ user: userId, tokenCredits: initialBalance });
const model = 'gpt-3.5-turbo';
const txData = {
user: userId,
conversationId: 'test-conversation-id',
model,
context: 'test',
endpointTokenConfig: null,
};
const tokenUsage = { promptTokens: 100 };
await spendTokens(txData, tokenUsage);
const updatedBalance = await Balance.findOne({ user: userId });
const promptMultiplier = getMultiplier({ model, tokenType: 'prompt' });
const expectedCost = 100 * promptMultiplier;
expect(updatedBalance.tokenCredits).toBeCloseTo(initialBalance - expectedCost, 0);
});
});
describe('Structured Token Spending Tests', () => {
test('Balance should decrease and rawAmount should be set when spending a large number of structured tokens', async () => {
// Arrange
const userId = new mongoose.Types.ObjectId();
const initialBalance = 17613154.55; // $17.61
await Balance.create({ user: userId, tokenCredits: initialBalance });
const model = 'claude-3-5-sonnet';
const txData = {
user: userId,
conversationId: 'c23a18da-706c-470a-ac28-ec87ed065199',
model,
context: 'message',
endpointTokenConfig: null, // We'll use the default rates
};
const tokenUsage = {
promptTokens: {
input: 11,
write: 140522,
read: 0,
},
completionTokens: 5,
};
// Get the actual multipliers
const promptMultiplier = getMultiplier({ model, tokenType: 'prompt' });
const completionMultiplier = getMultiplier({ model, tokenType: 'completion' });
const writeMultiplier = getCacheMultiplier({ model, cacheType: 'write' });
const readMultiplier = getCacheMultiplier({ model, cacheType: 'read' });
console.log('Multipliers:', {
promptMultiplier,
completionMultiplier,
writeMultiplier,
readMultiplier,
});
// Act
process.env.CHECK_BALANCE = 'true';
const result = await spendStructuredTokens(txData, tokenUsage);
// Assert
console.log('Initial Balance:', initialBalance);
console.log('Updated Balance:', result.completion.balance);
console.log('Transaction Result:', result);
const expectedPromptCost =
tokenUsage.promptTokens.input * promptMultiplier +
tokenUsage.promptTokens.write * writeMultiplier +
tokenUsage.promptTokens.read * readMultiplier;
const expectedCompletionCost = tokenUsage.completionTokens * completionMultiplier;
const expectedTotalCost = expectedPromptCost + expectedCompletionCost;
const expectedBalance = initialBalance - expectedTotalCost;
console.log('Expected Cost:', expectedTotalCost);
console.log('Expected Balance:', expectedBalance);
expect(result.completion.balance).toBeLessThan(initialBalance);
// Allow for a small difference (e.g., 100 token credits, which is $0.0001)
const allowedDifference = 100;
expect(Math.abs(result.completion.balance - expectedBalance)).toBeLessThan(allowedDifference);
// Check if the decrease is approximately as expected
const balanceDecrease = initialBalance - result.completion.balance;
expect(balanceDecrease).toBeCloseTo(expectedTotalCost, 0);
// Check token values
const expectedPromptTokenValue = -(
tokenUsage.promptTokens.input * promptMultiplier +
tokenUsage.promptTokens.write * writeMultiplier +
tokenUsage.promptTokens.read * readMultiplier
);
const expectedCompletionTokenValue = -tokenUsage.completionTokens * completionMultiplier;
expect(result.prompt.prompt).toBeCloseTo(expectedPromptTokenValue, 1);
expect(result.completion.completion).toBe(expectedCompletionTokenValue);
console.log('Expected prompt tokenValue:', expectedPromptTokenValue);
console.log('Actual prompt tokenValue:', result.prompt.prompt);
console.log('Expected completion tokenValue:', expectedCompletionTokenValue);
console.log('Actual completion tokenValue:', result.completion.completion);
});
test('should handle zero completion tokens in structured spending', async () => {
const userId = new mongoose.Types.ObjectId();
const initialBalance = 17613154.55;
await Balance.create({ user: userId, tokenCredits: initialBalance });
const model = 'claude-3-5-sonnet';
const txData = {
user: userId,
conversationId: 'test-convo',
model,
context: 'message',
};
const tokenUsage = {
promptTokens: {
input: 10,
write: 100,
read: 5,
},
completionTokens: 0,
};
process.env.CHECK_BALANCE = 'true';
const result = await spendStructuredTokens(txData, tokenUsage);
expect(result.prompt).toBeDefined();
expect(result.completion).toBeUndefined();
expect(result.prompt.prompt).toBeLessThan(0);
});
test('should handle only prompt tokens in structured spending', async () => {
const userId = new mongoose.Types.ObjectId();
const initialBalance = 17613154.55;
await Balance.create({ user: userId, tokenCredits: initialBalance });
const model = 'claude-3-5-sonnet';
const txData = {
user: userId,
conversationId: 'test-convo',
model,
context: 'message',
};
const tokenUsage = {
promptTokens: {
input: 10,
write: 100,
read: 5,
},
};
process.env.CHECK_BALANCE = 'true';
const result = await spendStructuredTokens(txData, tokenUsage);
expect(result.prompt).toBeDefined();
expect(result.completion).toBeUndefined();
expect(result.prompt.prompt).toBeLessThan(0);
});
test('should handle undefined token counts in structured spending', async () => {
const userId = new mongoose.Types.ObjectId();
const initialBalance = 17613154.55;
await Balance.create({ user: userId, tokenCredits: initialBalance });
const model = 'claude-3-5-sonnet';
const txData = {
user: userId,
conversationId: 'test-convo',
model,
context: 'message',
};
const tokenUsage = {};
process.env.CHECK_BALANCE = 'true';
const result = await spendStructuredTokens(txData, tokenUsage);
expect(result).toEqual({
prompt: undefined,
completion: undefined,
});
});
test('should handle incomplete context for completion tokens', async () => {
const userId = new mongoose.Types.ObjectId();
const initialBalance = 17613154.55;
await Balance.create({ user: userId, tokenCredits: initialBalance });
const model = 'claude-3-5-sonnet';
const txData = {
user: userId,
conversationId: 'test-convo',
model,
context: 'incomplete',
};
const tokenUsage = {
promptTokens: {
input: 10,
write: 100,
read: 5,
},
completionTokens: 50,
};
process.env.CHECK_BALANCE = 'true';
const result = await spendStructuredTokens(txData, tokenUsage);
expect(result.completion.completion).toBeCloseTo(-50 * 15 * 1.15, 0); // Assuming multiplier is 15 and cancelRate is 1.15
});
});

View File

@@ -1,3 +1,11 @@
const {
getMessages,
saveMessage,
recordMessage,
updateMessage,
deleteMessagesSince,
deleteMessages,
} = require('./Message');
const {
comparePassword,
deleteUserById,
@@ -8,6 +16,8 @@ const {
countUsers,
findUser,
} = require('./userMethods');
const { getConvoTitle, getConvo, saveConvo, deleteConvos } = require('./Conversation');
const { getPreset, getPresets, savePreset, deletePresets } = require('./Preset');
const {
findFileById,
createFile,
@@ -17,40 +27,26 @@ const {
getFiles,
updateFileUsage,
} = require('./File');
const {
getMessages,
saveMessage,
recordMessage,
updateMessage,
deleteMessagesSince,
deleteMessages,
} = require('./Message');
const { getConvoTitle, getConvo, saveConvo, deleteConvos } = require('./Conversation');
const { getPreset, getPresets, savePreset, deletePresets } = require('./Preset');
const { createToken, findToken, updateToken, deleteTokens } = require('./Token');
const Key = require('./Key');
const User = require('./User');
const Session = require('./Session');
const Balance = require('./Balance');
const User = require('./User');
const Key = require('./Key');
module.exports = {
User,
Key,
Session,
Balance,
comparePassword,
deleteUserById,
generateToken,
getUserById,
updateUser,
createUser,
countUsers,
createUser,
updateUser,
findUser,
findFileById,
createFile,
updateFile,
deleteFile,
deleteFiles,
getFiles,
updateFileUsage,
getMessages,
saveMessage,
recordMessage,
@@ -68,13 +64,11 @@ module.exports = {
savePreset,
deletePresets,
createToken,
findToken,
updateToken,
deleteTokens,
User,
Key,
Session,
Balance,
findFileById,
createFile,
updateFile,
deleteFile,
deleteFiles,
getFiles,
updateFileUsage,
};

View File

@@ -1,69 +0,0 @@
const mongoose = require('mongoose');
const { getRandomValues, hashToken } = require('~/server/utils/crypto');
const { createToken, findToken } = require('./Token');
const logger = require('~/config/winston');
/**
* @module inviteUser
* @description This module provides functions to create and get user invites
*/
/**
* @function createInvite
* @description This function creates a new user invite
* @param {string} email - The email of the user to invite
* @returns {Promise<Object>} A promise that resolves to the saved invite document
* @throws {Error} If there is an error creating the invite
*/
const createInvite = async (email) => {
try {
const token = await getRandomValues(32);
const hash = await hashToken(token);
const encodedToken = encodeURIComponent(token);
const fakeUserId = new mongoose.Types.ObjectId();
await createToken({
userId: fakeUserId,
email,
token: hash,
createdAt: Date.now(),
expiresIn: 604800,
});
return encodedToken;
} catch (error) {
logger.error('[createInvite] Error creating invite', error);
return { message: 'Error creating invite' };
}
};
/**
* @function getInvite
* @description This function retrieves a user invite
* @param {string} encodedToken - The token of the invite to retrieve
* @param {string} email - The email of the user to validate
* @returns {Promise<Object>} A promise that resolves to the retrieved invite document
* @throws {Error} If there is an error retrieving the invite, if the invite does not exist, or if the email does not match
*/
const getInvite = async (encodedToken, email) => {
try {
const token = decodeURIComponent(encodedToken);
const hash = await hashToken(token);
const invite = await findToken({ token: hash, email });
if (!invite) {
throw new Error('Invite not found or email does not match');
}
return invite;
} catch (error) {
logger.error('[getInvite] Error getting invite:', error);
return { error: true, message: error.message };
}
};
module.exports = {
createInvite,
getInvite,
};

View File

@@ -39,7 +39,6 @@ const actionSchema = new Schema({
default: 'action_prototype',
},
settings: Schema.Types.Mixed,
agent_id: String,
assistant_id: String,
metadata: {
api_key: String, // private, encrypted

View File

@@ -1,84 +0,0 @@
const mongoose = require('mongoose');
const agentSchema = mongoose.Schema(
{
id: {
type: String,
index: true,
unique: true,
required: true,
},
name: {
type: String,
},
description: {
type: String,
},
instructions: {
type: String,
},
avatar: {
type: {
filepath: String,
source: String,
},
default: undefined,
},
provider: {
type: String,
required: true,
},
model: {
type: String,
required: true,
},
model_parameters: {
type: Object,
},
access_level: {
type: Number,
},
tools: {
type: [String],
default: undefined,
},
tool_kwargs: {
type: [{ type: mongoose.Schema.Types.Mixed }],
},
actions: {
type: [String],
default: undefined,
},
author: {
type: mongoose.Schema.Types.ObjectId,
ref: 'User',
required: true,
},
authorName: {
type: String,
default: undefined,
},
isCollaborative: {
type: Boolean,
default: undefined,
},
conversation_starters: {
type: [String],
default: [],
},
tool_resources: {
type: mongoose.Schema.Types.Mixed,
default: {},
},
projectIds: {
type: [mongoose.Schema.Types.ObjectId],
ref: 'Project',
index: true,
},
},
{
timestamps: true,
},
);
module.exports = agentSchema;

View File

@@ -19,10 +19,6 @@ const assistantSchema = mongoose.Schema(
},
default: undefined,
},
conversation_starters: {
type: [String],
default: [],
},
access_level: {
type: Number,
},

View File

@@ -1,36 +0,0 @@
const mongoose = require('mongoose');
const bannerSchema = mongoose.Schema(
{
bannerId: {
type: String,
required: true,
},
message: {
type: String,
required: true,
},
displayFrom: {
type: Date,
required: true,
default: Date.now,
},
displayTo: {
type: Date,
},
type: {
type: String,
enum: ['banner', 'popup'],
default: 'banner',
},
isPublic: {
type: Boolean,
default: false,
},
},
{ timestamps: true },
);
const Banner = mongoose.model('Banner', bannerSchema);
module.exports = Banner;

View File

@@ -21,7 +21,6 @@ const conversationTagSchema = mongoose.Schema(
position: {
type: Number,
default: 0,
index: true,
},
},
{ timestamps: true },

View File

@@ -61,7 +61,6 @@ if (process.env.MEILI_HOST && process.env.MEILI_MASTER_KEY) {
}
convoSchema.index({ createdAt: 1, updatedAt: 1 });
convoSchema.index({ conversationId: 1, user: 1 }, { unique: true });
const Conversation = mongoose.models.Conversation || mongoose.model('Conversation', convoSchema);

View File

@@ -13,11 +13,6 @@ const conversationPreset = {
type: String,
required: false,
},
// for bedrock only
region: {
type: String,
required: false,
},
// for azureOpenAI, openAI only
chatGptLabel: {
type: String,
@@ -79,13 +74,6 @@ const conversationPreset = {
resendImages: {
type: Boolean,
},
/* Anthropic only */
promptCache: {
type: Boolean,
},
system: {
type: String,
},
// files
resendFiles: {
type: Boolean,

View File

@@ -115,29 +115,6 @@ const messageSchema = mongoose.Schema(
iconURL: {
type: String,
},
attachments: { type: [{ type: mongoose.Schema.Types.Mixed }], default: undefined },
/*
attachments: {
type: [
{
file_id: String,
filename: String,
filepath: String,
expiresAt: Date,
width: Number,
height: Number,
type: String,
conversationId: String,
messageId: {
type: String,
required: true,
},
toolCallId: String,
},
],
default: undefined,
},
*/
},
{ timestamps: true },
);
@@ -154,7 +131,6 @@ if (process.env.MEILI_HOST && process.env.MEILI_MASTER_KEY) {
messageSchema.index({ createdAt: 1 });
messageSchema.index({ messageId: 1, user: 1 }, { unique: true });
/** @type {mongoose.Model<TMessage>} */
const Message = mongoose.models.Message || mongoose.model('Message', messageSchema);
module.exports = Message;

View File

@@ -21,11 +21,6 @@ const projectSchema = new Schema(
ref: 'PromptGroup',
default: [],
},
agentIds: {
type: [String],
ref: 'Agent',
default: [],
},
},
{
timestamps: true,

View File

@@ -8,12 +8,6 @@ const roleSchema = new mongoose.Schema({
unique: true,
index: true,
},
[PermissionTypes.BOOKMARKS]: {
[Permissions.USE]: {
type: Boolean,
default: true,
},
},
[PermissionTypes.PROMPTS]: {
[Permissions.SHARED_GLOBAL]: {
type: Boolean,
@@ -28,26 +22,6 @@ const roleSchema = new mongoose.Schema({
default: true,
},
},
[PermissionTypes.AGENTS]: {
[Permissions.SHARED_GLOBAL]: {
type: Boolean,
default: false,
},
[Permissions.USE]: {
type: Boolean,
default: true,
},
[Permissions.CREATE]: {
type: Boolean,
default: true,
},
},
[PermissionTypes.MULTI_CONVO]: {
[Permissions.USE]: {
type: Boolean,
default: true,
},
},
});
const Role = mongoose.model('Role', roleSchema);

View File

@@ -18,13 +18,8 @@ const tokenSchema = new Schema({
type: Date,
required: true,
default: Date.now,
},
expiresAt: {
type: Date,
required: true,
expires: 900,
},
});
tokenSchema.index({ expiresAt: 1 }, { expireAfterSeconds: 0 });
module.exports = tokenSchema;
module.exports = mongoose.model('Token', tokenSchema);

View File

@@ -30,9 +30,6 @@ const transactionSchema = mongoose.Schema(
rate: Number,
rawAmount: Number,
tokenValue: Number,
inputTokens: { type: Number },
writeTokens: { type: Number },
readTokens: { type: Number },
},
{
timestamps: true,

View File

@@ -1,5 +1,4 @@
const mongoose = require('mongoose');
const { SystemRoles } = require('librechat-data-provider');
/**
* @typedef {Object} MongoSession
@@ -79,7 +78,7 @@ const userSchema = mongoose.Schema(
},
role: {
type: String,
default: SystemRoles.USER,
default: 'USER',
},
googleId: {
type: String,
@@ -122,12 +121,7 @@ const userSchema = mongoose.Schema(
type: Date,
expires: 604800, // 7 days in seconds
},
termsAccepted: {
type: Boolean,
default: false,
},
},
{ timestamps: true },
);

View File

@@ -11,7 +11,7 @@ const { logger } = require('~/config');
* @param {String} txData.conversationId - The ID of the conversation.
* @param {String} txData.model - The model name.
* @param {String} txData.context - The context in which the transaction is made.
* @param {EndpointTokenConfig} [txData.endpointTokenConfig] - The current endpoint token config.
* @param {String} [txData.endpointTokenConfig] - The current endpoint token config.
* @param {String} [txData.valueKey] - The value key (optional).
* @param {Object} tokenUsage - The number of tokens used.
* @param {Number} tokenUsage.promptTokens - The number of prompt tokens used.
@@ -32,109 +32,38 @@ const spendTokens = async (txData, tokenUsage) => {
);
let prompt, completion;
try {
if (promptTokens !== undefined) {
if (promptTokens >= 0) {
prompt = await Transaction.create({
...txData,
tokenType: 'prompt',
rawAmount: -Math.max(promptTokens, 0),
rawAmount: -promptTokens,
});
}
if (completionTokens !== undefined) {
completion = await Transaction.create({
...txData,
tokenType: 'completion',
rawAmount: -Math.max(completionTokens, 0),
});
if (!completionTokens && isNaN(completionTokens)) {
logger.debug('[spendTokens] !completionTokens', { prompt, completion });
return;
}
if (prompt || completion) {
completion = await Transaction.create({
...txData,
tokenType: 'completion',
rawAmount: -completionTokens,
});
prompt &&
completion &&
logger.debug('[spendTokens] Transaction data record against balance:', {
user: txData.user,
prompt: prompt?.prompt,
promptRate: prompt?.rate,
completion: completion?.completion,
completionRate: completion?.rate,
balance: completion?.balance ?? prompt?.balance,
prompt: prompt.prompt,
promptRate: prompt.rate,
completion: completion.completion,
completionRate: completion.rate,
balance: completion.balance,
});
} else {
logger.debug('[spendTokens] No transactions incurred against balance');
}
} catch (err) {
logger.error('[spendTokens]', err);
}
};
/**
* Creates transactions to record the spending of structured tokens.
*
* @function
* @async
* @param {Object} txData - Transaction data.
* @param {mongoose.Schema.Types.ObjectId} txData.user - The user ID.
* @param {String} txData.conversationId - The ID of the conversation.
* @param {String} txData.model - The model name.
* @param {String} txData.context - The context in which the transaction is made.
* @param {EndpointTokenConfig} [txData.endpointTokenConfig] - The current endpoint token config.
* @param {String} [txData.valueKey] - The value key (optional).
* @param {Object} tokenUsage - The number of tokens used.
* @param {Object} tokenUsage.promptTokens - The number of prompt tokens used.
* @param {Number} tokenUsage.promptTokens.input - The number of input tokens.
* @param {Number} tokenUsage.promptTokens.write - The number of write tokens.
* @param {Number} tokenUsage.promptTokens.read - The number of read tokens.
* @param {Number} tokenUsage.completionTokens - The number of completion tokens used.
* @returns {Promise<void>} - Returns nothing.
* @throws {Error} - Throws an error if there's an issue creating the transactions.
*/
const spendStructuredTokens = async (txData, tokenUsage) => {
const { promptTokens, completionTokens } = tokenUsage;
logger.debug(
`[spendStructuredTokens] conversationId: ${txData.conversationId}${
txData?.context ? ` | Context: ${txData?.context}` : ''
} | Token usage: `,
{
promptTokens,
completionTokens,
},
);
let prompt, completion;
try {
if (promptTokens) {
const { input = 0, write = 0, read = 0 } = promptTokens;
prompt = await Transaction.createStructured({
...txData,
tokenType: 'prompt',
inputTokens: -input,
writeTokens: -write,
readTokens: -read,
});
}
if (completionTokens) {
completion = await Transaction.create({
...txData,
tokenType: 'completion',
rawAmount: -completionTokens,
});
}
if (prompt || completion) {
logger.debug('[spendStructuredTokens] Transaction data record against balance:', {
user: txData.user,
prompt: prompt?.prompt,
promptRate: prompt?.rate,
completion: completion?.completion,
completionRate: completion?.rate,
balance: completion?.balance ?? prompt?.balance,
});
} else {
logger.debug('[spendStructuredTokens] No transactions incurred against balance');
}
} catch (err) {
logger.error('[spendStructuredTokens]', err);
}
return { prompt, completion };
};
module.exports = { spendTokens, spendStructuredTokens };
module.exports = spendTokens;

View File

@@ -1,197 +0,0 @@
const mongoose = require('mongoose');
jest.mock('./Transaction', () => ({
Transaction: {
create: jest.fn(),
createStructured: jest.fn(),
},
}));
jest.mock('./Balance', () => ({
findOne: jest.fn(),
findOneAndUpdate: jest.fn(),
}));
jest.mock('~/config', () => ({
logger: {
debug: jest.fn(),
error: jest.fn(),
},
}));
// Import after mocking
const { spendTokens, spendStructuredTokens } = require('./spendTokens');
const { Transaction } = require('./Transaction');
const Balance = require('./Balance');
describe('spendTokens', () => {
beforeEach(() => {
jest.clearAllMocks();
process.env.CHECK_BALANCE = 'true';
});
it('should create transactions for both prompt and completion tokens', async () => {
const txData = {
user: new mongoose.Types.ObjectId(),
conversationId: 'test-convo',
model: 'gpt-3.5-turbo',
context: 'test',
};
const tokenUsage = {
promptTokens: 100,
completionTokens: 50,
};
Transaction.create.mockResolvedValueOnce({ tokenType: 'prompt', rawAmount: -100 });
Transaction.create.mockResolvedValueOnce({ tokenType: 'completion', rawAmount: -50 });
Balance.findOne.mockResolvedValue({ tokenCredits: 10000 });
Balance.findOneAndUpdate.mockResolvedValue({ tokenCredits: 9850 });
await spendTokens(txData, tokenUsage);
expect(Transaction.create).toHaveBeenCalledTimes(2);
expect(Transaction.create).toHaveBeenCalledWith(
expect.objectContaining({
tokenType: 'prompt',
rawAmount: -100,
}),
);
expect(Transaction.create).toHaveBeenCalledWith(
expect.objectContaining({
tokenType: 'completion',
rawAmount: -50,
}),
);
});
it('should handle zero completion tokens', async () => {
const txData = {
user: new mongoose.Types.ObjectId(),
conversationId: 'test-convo',
model: 'gpt-3.5-turbo',
context: 'test',
};
const tokenUsage = {
promptTokens: 100,
completionTokens: 0,
};
Transaction.create.mockResolvedValueOnce({ tokenType: 'prompt', rawAmount: -100 });
Transaction.create.mockResolvedValueOnce({ tokenType: 'completion', rawAmount: -0 });
Balance.findOne.mockResolvedValue({ tokenCredits: 10000 });
Balance.findOneAndUpdate.mockResolvedValue({ tokenCredits: 9850 });
await spendTokens(txData, tokenUsage);
expect(Transaction.create).toHaveBeenCalledTimes(2);
expect(Transaction.create).toHaveBeenCalledWith(
expect.objectContaining({
tokenType: 'prompt',
rawAmount: -100,
}),
);
expect(Transaction.create).toHaveBeenCalledWith(
expect.objectContaining({
tokenType: 'completion',
rawAmount: -0, // Changed from 0 to -0
}),
);
});
it('should handle undefined token counts', async () => {
const txData = {
user: new mongoose.Types.ObjectId(),
conversationId: 'test-convo',
model: 'gpt-3.5-turbo',
context: 'test',
};
const tokenUsage = {};
await spendTokens(txData, tokenUsage);
expect(Transaction.create).not.toHaveBeenCalled();
});
it('should not update balance when CHECK_BALANCE is false', async () => {
process.env.CHECK_BALANCE = 'false';
const txData = {
user: new mongoose.Types.ObjectId(),
conversationId: 'test-convo',
model: 'gpt-3.5-turbo',
context: 'test',
};
const tokenUsage = {
promptTokens: 100,
completionTokens: 50,
};
Transaction.create.mockResolvedValueOnce({ tokenType: 'prompt', rawAmount: -100 });
Transaction.create.mockResolvedValueOnce({ tokenType: 'completion', rawAmount: -50 });
await spendTokens(txData, tokenUsage);
expect(Transaction.create).toHaveBeenCalledTimes(2);
expect(Balance.findOne).not.toHaveBeenCalled();
expect(Balance.findOneAndUpdate).not.toHaveBeenCalled();
});
it('should create structured transactions for both prompt and completion tokens', async () => {
const txData = {
user: new mongoose.Types.ObjectId(),
conversationId: 'test-convo',
model: 'claude-3-5-sonnet',
context: 'test',
};
const tokenUsage = {
promptTokens: {
input: 10,
write: 100,
read: 5,
},
completionTokens: 50,
};
Transaction.createStructured.mockResolvedValueOnce({
rate: 3.75,
user: txData.user.toString(),
balance: 9570,
prompt: -430,
});
Transaction.create.mockResolvedValueOnce({
rate: 15,
user: txData.user.toString(),
balance: 8820,
completion: -750,
});
const result = await spendStructuredTokens(txData, tokenUsage);
expect(Transaction.createStructured).toHaveBeenCalledWith(
expect.objectContaining({
tokenType: 'prompt',
inputTokens: -10,
writeTokens: -100,
readTokens: -5,
}),
);
expect(Transaction.create).toHaveBeenCalledWith(
expect.objectContaining({
tokenType: 'completion',
rawAmount: -50,
}),
);
expect(result).toEqual({
prompt: expect.objectContaining({
rate: 3.75,
user: txData.user.toString(),
balance: 9570,
prompt: -430,
}),
completion: expect.objectContaining({
rate: 15,
user: txData.user.toString(),
balance: 8820,
completion: -750,
}),
});
});
});

View File

@@ -1,80 +1,37 @@
const { matchModelName } = require('../utils');
const defaultRate = 6;
/** AWS Bedrock pricing */
const bedrockValues = {
'llama2-13b': { prompt: 0.75, completion: 1.0 },
'llama2-70b': { prompt: 1.95, completion: 2.56 },
'llama3-8b': { prompt: 0.3, completion: 0.6 },
'llama3-70b': { prompt: 2.65, completion: 3.5 },
'llama3-1-8b': { prompt: 0.3, completion: 0.6 },
'llama3-1-70b': { prompt: 2.65, completion: 3.5 },
'llama3-1-405b': { prompt: 5.32, completion: 16.0 },
'mistral-7b': { prompt: 0.15, completion: 0.2 },
'mistral-small': { prompt: 0.15, completion: 0.2 },
'mixtral-8x7b': { prompt: 0.45, completion: 0.7 },
'mistral-large-2402': { prompt: 4.0, completion: 12.0 },
'mistral-large-2407': { prompt: 3.0, completion: 9.0 },
'command-text': { prompt: 1.5, completion: 2.0 },
'command-light': { prompt: 0.3, completion: 0.6 },
'ai21.j2-mid-v1': { prompt: 12.5, completion: 12.5 },
'ai21.j2-ultra-v1': { prompt: 18.8, completion: 18.8 },
'ai21.jamba-instruct-v1:0': { prompt: 0.5, completion: 0.7 },
'amazon.titan-text-lite-v1': { prompt: 0.15, completion: 0.2 },
'amazon.titan-text-express-v1': { prompt: 0.2, completion: 0.6 },
'amazon.titan-text-premier-v1:0': { prompt: 0.5, completion: 1.5 },
};
/**
* Mapping of model token sizes to their respective multipliers for prompt and completion.
* The rates are 1 USD per 1M tokens.
* @type {Object.<string, {prompt: number, completion: number}>}
*/
const tokenValues = Object.assign(
{
'8k': { prompt: 30, completion: 60 },
'32k': { prompt: 60, completion: 120 },
'4k': { prompt: 1.5, completion: 2 },
'16k': { prompt: 3, completion: 4 },
'gpt-3.5-turbo-1106': { prompt: 1, completion: 2 },
'o1-preview': { prompt: 15, completion: 60 },
'o1-mini': { prompt: 3, completion: 12 },
o1: { prompt: 15, completion: 60 },
'gpt-4o-mini': { prompt: 0.15, completion: 0.6 },
'gpt-4o': { prompt: 2.5, completion: 10 },
'gpt-4o-2024-05-13': { prompt: 5, completion: 15 },
'gpt-4-1106': { prompt: 10, completion: 30 },
'gpt-3.5-turbo-0125': { prompt: 0.5, completion: 1.5 },
'claude-3-opus': { prompt: 15, completion: 75 },
'claude-3-sonnet': { prompt: 3, completion: 15 },
'claude-3-5-sonnet': { prompt: 3, completion: 15 },
'claude-3.5-sonnet': { prompt: 3, completion: 15 },
'claude-3-haiku': { prompt: 0.25, completion: 1.25 },
'claude-2.1': { prompt: 8, completion: 24 },
'claude-2': { prompt: 8, completion: 24 },
'claude-instant': { prompt: 0.8, completion: 2.4 },
'claude-': { prompt: 0.8, completion: 2.4 },
'command-r-plus': { prompt: 3, completion: 15 },
'command-r': { prompt: 0.5, completion: 1.5 },
/* cohere doesn't have rates for the older command models,
const tokenValues = {
'8k': { prompt: 30, completion: 60 },
'32k': { prompt: 60, completion: 120 },
'4k': { prompt: 1.5, completion: 2 },
'16k': { prompt: 3, completion: 4 },
'gpt-3.5-turbo-1106': { prompt: 1, completion: 2 },
'gpt-4o-mini': { prompt: 0.15, completion: 0.6 },
'gpt-4o': { prompt: 5, completion: 15 },
'gpt-4-1106': { prompt: 10, completion: 30 },
'gpt-3.5-turbo-0125': { prompt: 0.5, completion: 1.5 },
'claude-3-opus': { prompt: 15, completion: 75 },
'claude-3-sonnet': { prompt: 3, completion: 15 },
'claude-3-5-sonnet': { prompt: 3, completion: 15 },
'claude-3-haiku': { prompt: 0.25, completion: 1.25 },
'claude-2.1': { prompt: 8, completion: 24 },
'claude-2': { prompt: 8, completion: 24 },
'claude-': { prompt: 0.8, completion: 2.4 },
'command-r-plus': { prompt: 3, completion: 15 },
'command-r': { prompt: 0.5, completion: 1.5 },
/* cohere doesn't have rates for the older command models,
so this was from https://artificialanalysis.ai/models/command-light/providers */
command: { prompt: 0.38, completion: 0.38 },
'gemini-1.5': { prompt: 7, completion: 21 }, // May 2nd, 2024 pricing
gemini: { prompt: 0.5, completion: 1.5 }, // May 2nd, 2024 pricing
},
bedrockValues,
);
/**
* Mapping of model token sizes to their respective multipliers for cached input, read and write.
* See Anthropic's documentation on this: https://docs.anthropic.com/en/docs/build-with-claude/prompt-caching#pricing
* The rates are 1 USD per 1M tokens.
* @type {Object.<string, {write: number, read: number }>}
*/
const cacheTokenValues = {
'claude-3.5-sonnet': { write: 3.75, read: 0.3 },
'claude-3-5-sonnet': { write: 3.75, read: 0.3 },
'claude-3-haiku': { write: 0.3, read: 0.03 },
command: { prompt: 0.38, completion: 0.38 },
// 'gemini-1.5': { prompt: 7, completion: 21 }, // May 2nd, 2024 pricing
// 'gemini': { prompt: 0.5, completion: 1.5 }, // May 2nd, 2024 pricing
'gemini-1.5': { prompt: 0, completion: 0 }, // currently free
gemini: { prompt: 0, completion: 0 }, // currently free
};
/**
@@ -98,14 +55,6 @@ const getValueKey = (model, endpoint) => {
return 'gpt-3.5-turbo-1106';
} else if (modelName.includes('gpt-3.5')) {
return '4k';
} else if (modelName.includes('o1-preview')) {
return 'o1-preview';
} else if (modelName.includes('o1-mini')) {
return 'o1-mini';
} else if (modelName.includes('o1')) {
return 'o1';
} else if (modelName.includes('gpt-4o-2024-05-13')) {
return 'gpt-4o-2024-05-13';
} else if (modelName.includes('gpt-4o-mini')) {
return 'gpt-4o-mini';
} else if (modelName.includes('gpt-4o')) {
@@ -135,7 +84,7 @@ const getValueKey = (model, endpoint) => {
*
* @param {Object} params - The parameters for the function.
* @param {string} [params.valueKey] - The key corresponding to the model name.
* @param {'prompt' | 'completion'} [params.tokenType] - The type of token (e.g., 'prompt' or 'completion').
* @param {string} [params.tokenType] - The type of token (e.g., 'prompt' or 'completion').
* @param {string} [params.model] - The model name to derive the value key from if not provided.
* @param {string} [params.endpoint] - The endpoint name to derive the value key from if not provided.
* @param {EndpointTokenConfig} [params.endpointTokenConfig] - The token configuration for the endpoint.
@@ -160,41 +109,7 @@ const getMultiplier = ({ valueKey, tokenType, model, endpoint, endpointTokenConf
}
// If we got this far, and values[tokenType] is undefined somehow, return a rough average of default multipliers
return tokenValues[valueKey]?.[tokenType] ?? defaultRate;
return tokenValues[valueKey][tokenType] ?? defaultRate;
};
/**
* Retrieves the cache multiplier for a given value key and token type. If no value key is provided,
* it attempts to derive it from the model name.
*
* @param {Object} params - The parameters for the function.
* @param {string} [params.valueKey] - The key corresponding to the model name.
* @param {'write' | 'read'} [params.cacheType] - The type of token (e.g., 'write' or 'read').
* @param {string} [params.model] - The model name to derive the value key from if not provided.
* @param {string} [params.endpoint] - The endpoint name to derive the value key from if not provided.
* @param {EndpointTokenConfig} [params.endpointTokenConfig] - The token configuration for the endpoint.
* @returns {number | null} The multiplier for the given parameters, or `null` if not found.
*/
const getCacheMultiplier = ({ valueKey, cacheType, model, endpoint, endpointTokenConfig }) => {
if (endpointTokenConfig) {
return endpointTokenConfig?.[model]?.[cacheType] ?? null;
}
if (valueKey && cacheType) {
return cacheTokenValues[valueKey]?.[cacheType] ?? null;
}
if (!cacheType || !model) {
return null;
}
valueKey = getValueKey(model, endpoint);
if (!valueKey) {
return null;
}
// If we got this far, and values[cacheType] is undefined somehow, return a rough average of default multipliers
return cacheTokenValues[valueKey]?.[cacheType] ?? null;
};
module.exports = { tokenValues, getValueKey, getMultiplier, getCacheMultiplier, defaultRate };
module.exports = { tokenValues, getValueKey, getMultiplier, defaultRate };

View File

@@ -1,11 +1,4 @@
const { EModelEndpoint } = require('librechat-data-provider');
const {
defaultRate,
tokenValues,
getValueKey,
getMultiplier,
getCacheMultiplier,
} = require('./tx');
const { getValueKey, getMultiplier, defaultRate, tokenValues } = require('./tx');
describe('getValueKey', () => {
it('should return "16k" for model name containing "gpt-3.5-turbo-16k"', () => {
@@ -50,10 +43,8 @@ describe('getValueKey', () => {
});
it('should return "gpt-4o" for model type of "gpt-4o"', () => {
expect(getValueKey('gpt-4o-2024-08-06')).toBe('gpt-4o');
expect(getValueKey('gpt-4o-2024-08-06-0718')).toBe('gpt-4o');
expect(getValueKey('gpt-4o-2024-05-13')).toBe('gpt-4o');
expect(getValueKey('openai/gpt-4o')).toBe('gpt-4o');
expect(getValueKey('openai/gpt-4o-2024-08-06')).toBe('gpt-4o');
expect(getValueKey('gpt-4o-turbo')).toBe('gpt-4o');
expect(getValueKey('gpt-4o-0125')).toBe('gpt-4o');
});
@@ -62,21 +53,6 @@ describe('getValueKey', () => {
expect(getValueKey('gpt-4o-mini-2024-07-18')).toBe('gpt-4o-mini');
expect(getValueKey('openai/gpt-4o-mini')).toBe('gpt-4o-mini');
expect(getValueKey('gpt-4o-mini-0718')).toBe('gpt-4o-mini');
expect(getValueKey('gpt-4o-2024-08-06-0718')).not.toBe('gpt-4o-mini');
});
it('should return "gpt-4o-2024-05-13" for model type of "gpt-4o-2024-05-13"', () => {
expect(getValueKey('gpt-4o-2024-05-13')).toBe('gpt-4o-2024-05-13');
expect(getValueKey('openai/gpt-4o-2024-05-13')).toBe('gpt-4o-2024-05-13');
expect(getValueKey('gpt-4o-2024-05-13-0718')).toBe('gpt-4o-2024-05-13');
expect(getValueKey('gpt-4o-2024-05-13-0718')).not.toBe('gpt-4o');
});
it('should return "gpt-4o" for model type of "chatgpt-4o"', () => {
expect(getValueKey('chatgpt-4o-latest')).toBe('gpt-4o');
expect(getValueKey('openai/chatgpt-4o-latest')).toBe('gpt-4o');
expect(getValueKey('chatgpt-4o-latest-0916')).toBe('gpt-4o');
expect(getValueKey('chatgpt-4o-latest-0718')).toBe('gpt-4o');
});
it('should return "claude-3-5-sonnet" for model type of "claude-3-5-sonnet-"', () => {
@@ -85,13 +61,6 @@ describe('getValueKey', () => {
expect(getValueKey('claude-3-5-sonnet-turbo')).toBe('claude-3-5-sonnet');
expect(getValueKey('claude-3-5-sonnet-0125')).toBe('claude-3-5-sonnet');
});
it('should return "claude-3.5-sonnet" for model type of "claude-3.5-sonnet-"', () => {
expect(getValueKey('claude-3.5-sonnet-20240620')).toBe('claude-3.5-sonnet');
expect(getValueKey('anthropic/claude-3.5-sonnet')).toBe('claude-3.5-sonnet');
expect(getValueKey('claude-3.5-sonnet-turbo')).toBe('claude-3.5-sonnet');
expect(getValueKey('claude-3.5-sonnet-0125')).toBe('claude-3.5-sonnet');
});
});
describe('getMultiplier', () => {
@@ -136,7 +105,7 @@ describe('getMultiplier', () => {
});
it('should return the correct multiplier for gpt-4o', () => {
const valueKey = getValueKey('gpt-4o-2024-08-06');
const valueKey = getValueKey('gpt-4o-2024-05-13');
expect(getMultiplier({ valueKey, tokenType: 'prompt' })).toBe(tokenValues['gpt-4o'].prompt);
expect(getMultiplier({ valueKey, tokenType: 'completion' })).toBe(
tokenValues['gpt-4o'].completion,
@@ -159,17 +128,6 @@ describe('getMultiplier', () => {
);
});
it('should return the correct multiplier for chatgpt-4o-latest', () => {
const valueKey = getValueKey('chatgpt-4o-latest');
expect(getMultiplier({ valueKey, tokenType: 'prompt' })).toBe(tokenValues['gpt-4o'].prompt);
expect(getMultiplier({ valueKey, tokenType: 'completion' })).toBe(
tokenValues['gpt-4o'].completion,
);
expect(getMultiplier({ valueKey, tokenType: 'completion' })).not.toBe(
tokenValues['gpt-4o-mini'].completion,
);
});
it('should derive the valueKey from the model if not provided for new models', () => {
expect(
getMultiplier({ tokenType: 'prompt', model: 'gpt-3.5-turbo-1106-some-other-info' }),
@@ -194,125 +152,3 @@ describe('getMultiplier', () => {
);
});
});
describe('AWS Bedrock Model Tests', () => {
const awsModels = [
'anthropic.claude-3-haiku-20240307-v1:0',
'anthropic.claude-3-sonnet-20240229-v1:0',
'anthropic.claude-3-opus-20240229-v1:0',
'anthropic.claude-3-5-sonnet-20240620-v1:0',
'anthropic.claude-v2:1',
'anthropic.claude-instant-v1',
'meta.llama2-13b-chat-v1',
'meta.llama2-70b-chat-v1',
'meta.llama3-8b-instruct-v1:0',
'meta.llama3-70b-instruct-v1:0',
'meta.llama3-1-8b-instruct-v1:0',
'meta.llama3-1-70b-instruct-v1:0',
'meta.llama3-1-405b-instruct-v1:0',
'mistral.mistral-7b-instruct-v0:2',
'mistral.mistral-small-2402-v1:0',
'mistral.mixtral-8x7b-instruct-v0:1',
'mistral.mistral-large-2402-v1:0',
'mistral.mistral-large-2407-v1:0',
'cohere.command-text-v14',
'cohere.command-light-text-v14',
'cohere.command-r-v1:0',
'cohere.command-r-plus-v1:0',
'ai21.j2-mid-v1',
'ai21.j2-ultra-v1',
'amazon.titan-text-lite-v1',
'amazon.titan-text-express-v1',
];
it('should return the correct prompt multipliers for all models', () => {
const results = awsModels.map((model) => {
const valueKey = getValueKey(model, EModelEndpoint.bedrock);
const multiplier = getMultiplier({ valueKey, tokenType: 'prompt' });
return tokenValues[valueKey].prompt && multiplier === tokenValues[valueKey].prompt;
});
expect(results.every(Boolean)).toBe(true);
});
it('should return the correct completion multipliers for all models', () => {
const results = awsModels.map((model) => {
const valueKey = getValueKey(model, EModelEndpoint.bedrock);
const multiplier = getMultiplier({ valueKey, tokenType: 'completion' });
return tokenValues[valueKey].completion && multiplier === tokenValues[valueKey].completion;
});
expect(results.every(Boolean)).toBe(true);
});
});
describe('getCacheMultiplier', () => {
it('should return the correct cache multiplier for a given valueKey and cacheType', () => {
expect(getCacheMultiplier({ valueKey: 'claude-3-5-sonnet', cacheType: 'write' })).toBe(3.75);
expect(getCacheMultiplier({ valueKey: 'claude-3-5-sonnet', cacheType: 'read' })).toBe(0.3);
expect(getCacheMultiplier({ valueKey: 'claude-3-haiku', cacheType: 'write' })).toBe(0.3);
expect(getCacheMultiplier({ valueKey: 'claude-3-haiku', cacheType: 'read' })).toBe(0.03);
});
it('should return null if cacheType is provided but not found in cacheTokenValues', () => {
expect(
getCacheMultiplier({ valueKey: 'claude-3-5-sonnet', cacheType: 'unknownType' }),
).toBeNull();
});
it('should derive the valueKey from the model if not provided', () => {
expect(getCacheMultiplier({ cacheType: 'write', model: 'claude-3-5-sonnet-20240620' })).toBe(
3.75,
);
expect(getCacheMultiplier({ cacheType: 'read', model: 'claude-3-haiku-20240307' })).toBe(0.03);
});
it('should return null if only model or cacheType is missing', () => {
expect(getCacheMultiplier({ cacheType: 'write' })).toBeNull();
expect(getCacheMultiplier({ model: 'claude-3-5-sonnet' })).toBeNull();
});
it('should return null if derived valueKey does not match any known patterns', () => {
expect(getCacheMultiplier({ cacheType: 'write', model: 'gpt-4-some-other-info' })).toBeNull();
});
it('should handle endpointTokenConfig if provided', () => {
const endpointTokenConfig = {
'custom-model': {
write: 5,
read: 1,
},
};
expect(
getCacheMultiplier({ model: 'custom-model', cacheType: 'write', endpointTokenConfig }),
).toBe(5);
expect(
getCacheMultiplier({ model: 'custom-model', cacheType: 'read', endpointTokenConfig }),
).toBe(1);
});
it('should return null if model is not found in endpointTokenConfig', () => {
const endpointTokenConfig = {
'custom-model': {
write: 5,
read: 1,
},
};
expect(
getCacheMultiplier({ model: 'unknown-model', cacheType: 'write', endpointTokenConfig }),
).toBeNull();
});
it('should handle models with "bedrock/" prefix', () => {
expect(
getCacheMultiplier({
model: 'bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0',
cacheType: 'write',
}),
).toBe(3.75);
expect(
getCacheMultiplier({
model: 'bedrock/anthropic.claude-3-haiku-20240307-v1:0',
cacheType: 'read',
}),
).toBe(0.03);
});
});

View File

@@ -1,6 +1,6 @@
{
"name": "@librechat/backend",
"version": "v0.7.5",
"version": "0.7.4-rc1",
"description": "",
"scripts": {
"start": "echo 'please run this from the root directory'",
@@ -12,7 +12,6 @@
"list-balances": "node ./list-balances.js",
"user-stats": "node ./user-stats.js",
"create-user": "node ./create-user.js",
"invite-user": "node ./invite-user.js",
"ban-user": "node ./ban-user.js",
"delete-user": "node ./delete-user.js"
},
@@ -40,25 +39,20 @@
"@keyv/mongo": "^2.1.8",
"@keyv/redis": "^2.8.1",
"@langchain/community": "^0.0.46",
"@langchain/core": "^0.2.18",
"@langchain/google-genai": "^0.0.11",
"@langchain/google-vertexai": "^0.0.17",
"@librechat/agents": "^1.6.9",
"axios": "^1.7.7",
"axios": "^1.3.4",
"bcryptjs": "^2.4.3",
"cheerio": "^1.0.0-rc.12",
"cohere-ai": "^7.9.1",
"compression": "^1.7.4",
"connect-redis": "^7.1.0",
"cookie": "^0.7.2",
"cookie-parser": "^1.4.7",
"cookie": "^0.5.0",
"cors": "^2.8.5",
"dedent": "^1.5.3",
"dotenv": "^16.0.3",
"express": "^4.21.1",
"express": "^4.18.2",
"express-mongo-sanitize": "^2.2.0",
"express-rate-limit": "^7.4.1",
"express-session": "^1.18.1",
"express-rate-limit": "^6.9.0",
"express-session": "^1.17.3",
"file-type": "^18.7.0",
"firebase": "^10.6.0",
"googleapis": "^126.0.1",
@@ -76,11 +70,10 @@
"meilisearch": "^0.38.0",
"mime": "^3.0.0",
"module-alias": "^2.2.3",
"mongoose": "^7.3.3",
"mongoose": "^7.1.1",
"multer": "^1.4.5-lts.1",
"nanoid": "^3.3.7",
"nodejs-gpt": "^1.37.4",
"nodemailer": "^6.9.15",
"nodemailer": "^6.9.4",
"ollama": "^0.5.0",
"openai": "^4.47.1",
"openai-chat-tokens": "^0.2.8",
@@ -101,11 +94,11 @@
"ua-parser-js": "^1.0.36",
"winston": "^3.11.0",
"winston-daily-rotate-file": "^4.7.1",
"ws": "^8.17.0",
"zod": "^3.22.4"
},
"devDependencies": {
"jest": "^29.7.0",
"mongodb-memory-server": "^10.0.0",
"jest": "^29.5.0",
"nodemon": "^3.0.1",
"supertest": "^6.3.3"
}

View File

@@ -16,12 +16,7 @@ const AskController = async (req, res, next, initializeClient, addTitle) => {
overrideParentMessageId = null,
} = req.body;
logger.debug('[AskController]', {
text,
conversationId,
...endpointOption,
modelsConfig: endpointOption.modelsConfig ? 'exists' : '',
});
logger.debug('[AskController]', { text, conversationId, ...endpointOption });
let userMessage;
let userMessagePromise;
@@ -128,6 +123,11 @@ const AskController = async (req, res, next, initializeClient, addTitle) => {
};
let response = await client.sendMessage(text, messageOptions);
if (overrideParentMessageId) {
response.parentMessageId = overrideParentMessageId;
}
response.endpoint = endpointOption.endpoint;
const { conversation = {} } = await client.responsePromise;

View File

@@ -1,3 +1,4 @@
const crypto = require('crypto');
const cookies = require('cookie');
const jwt = require('jsonwebtoken');
const {
@@ -6,7 +7,6 @@ const {
setAuthTokens,
requestPasswordReset,
} = require('~/server/services/AuthService');
const { hashToken } = require('~/server/utils/crypto');
const { Session, getUserById } = require('~/models');
const { logger } = require('~/config');
@@ -74,7 +74,8 @@ const refreshController = async (req, res) => {
}
// Hash the refresh token
const hashedToken = await hashToken(refreshToken);
const hash = crypto.createHash('sha256');
const hashedToken = hash.update(refreshToken).digest('hex');
// Find the session with the hashed refresh token
const session = await Session.findOne({ user: userId, refreshTokenHash: hashedToken });

View File

@@ -1,4 +1,4 @@
const Balance = require('~/models/Balance');
const Balance = require('../../models/Balance');
async function balanceController(req, res) {
const { tokenCredits: balance = '' } =

View File

@@ -25,7 +25,6 @@ const EditController = async (req, res, next, initializeClient) => {
isContinued,
conversationId,
...endpointOption,
modelsConfig: endpointOption.modelsConfig ? 'exists' : '',
});
let userMessage;

View File

@@ -44,14 +44,6 @@ async function endpointController(req, res) {
};
}
if (mergedConfig[EModelEndpoint.bedrock] && req.app.locals?.[EModelEndpoint.bedrock]) {
const { availableRegions } = req.app.locals[EModelEndpoint.bedrock];
mergedConfig[EModelEndpoint.bedrock] = {
...mergedConfig[EModelEndpoint.bedrock],
availableRegions,
};
}
const endpointsConfig = orderEndpointsConfig(mergedConfig);
await cache.set(CacheKeys.ENDPOINT_CONFIG, endpointsConfig);

View File

@@ -2,9 +2,6 @@ const { CacheKeys } = require('librechat-data-provider');
const { loadDefaultModels, loadConfigModels } = require('~/server/services/Config');
const { getLogStores } = require('~/cache');
/**
* @param {ServerRequest} req
*/
const getModelsConfig = async (req) => {
const cache = getLogStores(CacheKeys.CONFIG_STORE);
let modelsConfig = await cache.get(CacheKeys.MODELS_CONFIG);
@@ -17,7 +14,7 @@ const getModelsConfig = async (req) => {
/**
* Loads the models from the config.
* @param {ServerRequest} req - The Express request object.
* @param {Express.Request} req - The Express request object.
* @returns {Promise<TModelsConfig>} The models config.
*/
async function loadModels(req) {

View File

@@ -8,7 +8,6 @@ const {
deleteMessages,
deleteUserById,
} = require('~/models');
const User = require('~/models/User');
const { updateUserPluginAuth, deleteUserPluginAuth } = require('~/server/services/PluginService');
const { updateUserPluginsService, deleteUserKey } = require('~/server/services/UserService');
const { verifyEmail, resendVerificationEmail } = require('~/server/services/AuthService');
@@ -21,32 +20,6 @@ const getUserController = async (req, res) => {
res.status(200).send(req.user);
};
const getTermsStatusController = async (req, res) => {
try {
const user = await User.findById(req.user.id);
if (!user) {
return res.status(404).json({ message: 'User not found' });
}
res.status(200).json({ termsAccepted: !!user.termsAccepted });
} catch (error) {
logger.error('Error fetching terms acceptance status:', error);
res.status(500).json({ message: 'Error fetching terms acceptance status' });
}
};
const acceptTermsController = async (req, res) => {
try {
const user = await User.findByIdAndUpdate(req.user.id, { termsAccepted: true }, { new: true });
if (!user) {
return res.status(404).json({ message: 'User not found' });
}
res.status(200).json({ message: 'Terms accepted successfully' });
} catch (error) {
logger.error('Error accepting terms:', error);
res.status(500).json({ message: 'Error accepting terms' });
}
};
const deleteUserFiles = async (req) => {
try {
const userFiles = await getFiles({ user: req.user.id });
@@ -162,8 +135,6 @@ const resendVerificationController = async (req, res) => {
module.exports = {
getUserController,
getTermsStatusController,
acceptTermsController,
deleteUserController,
verifyEmailController,
updateUserPluginsController,

View File

@@ -1,193 +0,0 @@
const { Tools } = require('librechat-data-provider');
const { GraphEvents, ToolEndHandler, ChatModelStreamHandler } = require('@librechat/agents');
const { processCodeOutput } = require('~/server/services/Files/Code/process');
const { logger } = require('~/config');
/** @typedef {import('@librechat/agents').Graph} Graph */
/** @typedef {import('@librechat/agents').EventHandler} EventHandler */
/** @typedef {import('@librechat/agents').ModelEndData} ModelEndData */
/** @typedef {import('@librechat/agents').ToolEndData} ToolEndData */
/** @typedef {import('@librechat/agents').ToolEndCallback} ToolEndCallback */
/** @typedef {import('@librechat/agents').ChatModelStreamHandler} ChatModelStreamHandler */
/** @typedef {import('@librechat/agents').ContentAggregatorResult['aggregateContent']} ContentAggregator */
/** @typedef {import('@librechat/agents').GraphEvents} GraphEvents */
/**
* Sends message data in Server Sent Events format.
* @param {ServerResponse} res - The server response.
* @param {{ data: string | Record<string, unknown>, event?: string }} event - The message event.
* @param {string} event.event - The type of event.
* @param {string} event.data - The message to be sent.
*/
const sendEvent = (res, event) => {
if (typeof event.data === 'string' && event.data.length === 0) {
return;
}
res.write(`event: message\ndata: ${JSON.stringify(event)}\n\n`);
};
class ModelEndHandler {
/**
* @param {Array<UsageMetadata>} collectedUsage
*/
constructor(collectedUsage) {
if (!Array.isArray(collectedUsage)) {
throw new Error('collectedUsage must be an array');
}
this.collectedUsage = collectedUsage;
}
/**
* @param {string} event
* @param {ModelEndData | undefined} data
* @param {Record<string, unknown> | undefined} metadata
* @param {Graph} graph
* @returns
*/
handle(event, data, metadata, graph) {
if (!graph || !metadata) {
console.warn(`Graph or metadata not found in ${event} event`);
return;
}
const usage = data?.output?.usage_metadata;
if (usage) {
this.collectedUsage.push(usage);
}
}
}
/**
* Get default handlers for stream events.
* @param {Object} options - The options object.
* @param {ServerResponse} options.res - The options object.
* @param {ContentAggregator} options.aggregateContent - The options object.
* @param {ToolEndCallback} options.toolEndCallback - Callback to use when tool ends.
* @param {Array<UsageMetadata>} options.collectedUsage - The list of collected usage metadata.
* @returns {Record<string, t.EventHandler>} The default handlers.
* @throws {Error} If the request is not found.
*/
function getDefaultHandlers({ res, aggregateContent, toolEndCallback, collectedUsage }) {
if (!res || !aggregateContent) {
throw new Error(
`[getDefaultHandlers] Missing required options: res: ${!res}, aggregateContent: ${!aggregateContent}`,
);
}
const handlers = {
[GraphEvents.CHAT_MODEL_END]: new ModelEndHandler(collectedUsage),
[GraphEvents.TOOL_END]: new ToolEndHandler(toolEndCallback),
[GraphEvents.CHAT_MODEL_STREAM]: new ChatModelStreamHandler(),
[GraphEvents.ON_RUN_STEP]: {
/**
* Handle ON_RUN_STEP event.
* @param {string} event - The event name.
* @param {StreamEventData} data - The event data.
*/
handle: (event, data) => {
sendEvent(res, { event, data });
aggregateContent({ event, data });
},
},
[GraphEvents.ON_RUN_STEP_DELTA]: {
/**
* Handle ON_RUN_STEP_DELTA event.
* @param {string} event - The event name.
* @param {StreamEventData} data - The event data.
*/
handle: (event, data) => {
sendEvent(res, { event, data });
aggregateContent({ event, data });
},
},
[GraphEvents.ON_RUN_STEP_COMPLETED]: {
/**
* Handle ON_RUN_STEP_COMPLETED event.
* @param {string} event - The event name.
* @param {StreamEventData & { result: ToolEndData }} data - The event data.
*/
handle: (event, data) => {
sendEvent(res, { event, data });
aggregateContent({ event, data });
},
},
[GraphEvents.ON_MESSAGE_DELTA]: {
/**
* Handle ON_MESSAGE_DELTA event.
* @param {string} event - The event name.
* @param {StreamEventData} data - The event data.
*/
handle: (event, data) => {
sendEvent(res, { event, data });
aggregateContent({ event, data });
},
},
};
return handlers;
}
/**
*
* @param {Object} params
* @param {ServerRequest} params.req
* @param {ServerResponse} params.res
* @param {Promise<MongoFile | { filename: string; filepath: string; expires: number;} | null>[]} params.artifactPromises
* @returns {ToolEndCallback} The tool end callback.
*/
function createToolEndCallback({ req, res, artifactPromises }) {
/**
* @type {ToolEndCallback}
*/
return async (data, metadata) => {
const output = data?.output;
if (!output) {
return;
}
if (output.name !== Tools.execute_code) {
return;
}
const { tool_call_id, artifact } = output;
if (!artifact.files) {
return;
}
for (const file of artifact.files) {
const { id, name } = file;
artifactPromises.push(
(async () => {
const fileMetadata = await processCodeOutput({
req,
id,
name,
toolCallId: tool_call_id,
messageId: metadata.run_id,
sessionId: artifact.session_id,
conversationId: metadata.thread_id,
});
if (!res.headersSent) {
return fileMetadata;
}
if (!fileMetadata) {
return null;
}
res.write(`event: attachment\ndata: ${JSON.stringify(fileMetadata)}\n\n`);
return fileMetadata;
})().catch((error) => {
logger.error('Error processing code output:', error);
return null;
}),
);
}
};
}
module.exports = {
sendEvent,
getDefaultHandlers,
createToolEndCallback,
};

View File

@@ -1,598 +0,0 @@
// const { HttpsProxyAgent } = require('https-proxy-agent');
// const {
// Constants,
// ImageDetail,
// EModelEndpoint,
// resolveHeaders,
// validateVisionModel,
// mapModelToAzureConfig,
// } = require('librechat-data-provider');
const { Callback, createMetadataAggregator } = require('@librechat/agents');
const {
Constants,
VisionModes,
openAISchema,
EModelEndpoint,
anthropicSchema,
bedrockOutputParser,
providerEndpointMap,
removeNullishValues,
} = require('librechat-data-provider');
const {
extractBaseURL,
// constructAzureURL,
// genAzureChatCompletion,
} = require('~/utils');
const {
formatMessage,
formatAgentMessages,
createContextHandlers,
} = require('~/app/clients/prompts');
const { encodeAndFormat } = require('~/server/services/Files/images/encode');
const Tokenizer = require('~/server/services/Tokenizer');
const { spendTokens } = require('~/models/spendTokens');
const BaseClient = require('~/app/clients/BaseClient');
// const { sleep } = require('~/server/utils');
const { createRun } = require('./run');
const { logger } = require('~/config');
/** @typedef {import('@librechat/agents').MessageContentComplex} MessageContentComplex */
const providerParsers = {
[EModelEndpoint.openAI]: openAISchema,
[EModelEndpoint.azureOpenAI]: openAISchema,
[EModelEndpoint.anthropic]: anthropicSchema,
[EModelEndpoint.bedrock]: bedrockOutputParser,
};
class AgentClient extends BaseClient {
constructor(options = {}) {
super(null, options);
/** @type {'discard' | 'summarize'} */
this.contextStrategy = 'discard';
/** @deprecated @type {true} - Is a Chat Completion Request */
this.isChatCompletion = true;
/** @type {AgentRun} */
this.run;
const {
contentParts,
collectedUsage,
artifactPromises,
maxContextTokens,
modelOptions = {},
...clientOptions
} = options;
this.modelOptions = modelOptions;
this.maxContextTokens = maxContextTokens;
/** @type {MessageContentComplex[]} */
this.contentParts = contentParts;
/** @type {Array<UsageMetadata>} */
this.collectedUsage = collectedUsage;
/** @type {ArtifactPromises} */
this.artifactPromises = artifactPromises;
this.options = Object.assign({ endpoint: options.endpoint }, clientOptions);
}
/**
* Returns the aggregated content parts for the current run.
* @returns {MessageContentComplex[]} */
getContentParts() {
return this.contentParts;
}
setOptions(options) {
logger.info('[api/server/controllers/agents/client.js] setOptions', options);
}
/**
*
* Checks if the model is a vision model based on request attachments and sets the appropriate options:
* - Sets `this.modelOptions.model` to `gpt-4-vision-preview` if the request is a vision request.
* - Sets `this.isVisionModel` to `true` if vision request.
* - Deletes `this.modelOptions.stop` if vision request.
* @param {MongoFile[]} attachments
*/
checkVisionRequest(attachments) {
logger.info(
'[api/server/controllers/agents/client.js #checkVisionRequest] not implemented',
attachments,
);
// if (!attachments) {
// return;
// }
// const availableModels = this.options.modelsConfig?.[this.options.endpoint];
// if (!availableModels) {
// return;
// }
// let visionRequestDetected = false;
// for (const file of attachments) {
// if (file?.type?.includes('image')) {
// visionRequestDetected = true;
// break;
// }
// }
// if (!visionRequestDetected) {
// return;
// }
// this.isVisionModel = validateVisionModel({ model: this.modelOptions.model, availableModels });
// if (this.isVisionModel) {
// delete this.modelOptions.stop;
// return;
// }
// for (const model of availableModels) {
// if (!validateVisionModel({ model, availableModels })) {
// continue;
// }
// this.modelOptions.model = model;
// this.isVisionModel = true;
// delete this.modelOptions.stop;
// return;
// }
// if (!availableModels.includes(this.defaultVisionModel)) {
// return;
// }
// if (!validateVisionModel({ model: this.defaultVisionModel, availableModels })) {
// return;
// }
// this.modelOptions.model = this.defaultVisionModel;
// this.isVisionModel = true;
// delete this.modelOptions.stop;
}
getSaveOptions() {
const parseOptions = providerParsers[this.options.endpoint];
let runOptions =
this.options.endpoint === EModelEndpoint.agents
? {
model: undefined,
// TODO:
// would need to be override settings; otherwise, model needs to be undefined
// model: this.override.model,
// instructions: this.override.instructions,
// additional_instructions: this.override.additional_instructions,
}
: {};
if (parseOptions) {
runOptions = parseOptions(this.modelOptions);
}
return removeNullishValues(
Object.assign(
{
endpoint: this.options.endpoint,
agent_id: this.options.agent.id,
modelLabel: this.options.modelLabel,
maxContextTokens: this.options.maxContextTokens,
resendFiles: this.options.resendFiles,
imageDetail: this.options.imageDetail,
spec: this.options.spec,
},
// TODO: PARSE OPTIONS BY PROVIDER, MAY CONTAIN SENSITIVE DATA
runOptions,
),
);
}
getBuildMessagesOptions() {
return {
instructions: this.options.agent.instructions,
additional_instructions: this.options.agent.additional_instructions,
};
}
async addImageURLs(message, attachments) {
const { files, image_urls } = await encodeAndFormat(
this.options.req,
attachments,
this.options.agent.provider,
VisionModes.agents,
);
message.image_urls = image_urls.length ? image_urls : undefined;
return files;
}
async buildMessages(
messages,
parentMessageId,
{ instructions = null, additional_instructions = null },
opts,
) {
let orderedMessages = this.constructor.getMessagesForConversation({
messages,
parentMessageId,
summary: this.shouldSummarize,
});
let payload;
/** @type {number | undefined} */
let promptTokens;
/** @type {string} */
let systemContent = `${instructions ?? ''}${additional_instructions ?? ''}`;
if (this.options.attachments) {
const attachments = await this.options.attachments;
if (this.message_file_map) {
this.message_file_map[orderedMessages[orderedMessages.length - 1].messageId] = attachments;
} else {
this.message_file_map = {
[orderedMessages[orderedMessages.length - 1].messageId]: attachments,
};
}
const files = await this.addImageURLs(
orderedMessages[orderedMessages.length - 1],
attachments,
);
this.options.attachments = files;
}
if (this.message_file_map) {
this.contextHandlers = createContextHandlers(
this.options.req,
orderedMessages[orderedMessages.length - 1].text,
);
}
const formattedMessages = orderedMessages.map((message, i) => {
const formattedMessage = formatMessage({
message,
userName: this.options?.name,
assistantName: this.options?.modelLabel,
});
const needsTokenCount = this.contextStrategy && !orderedMessages[i].tokenCount;
/* If tokens were never counted, or, is a Vision request and the message has files, count again */
if (needsTokenCount || (this.isVisionModel && (message.image_urls || message.files))) {
orderedMessages[i].tokenCount = this.getTokenCountForMessage(formattedMessage);
}
/* If message has files, calculate image token cost */
if (this.message_file_map && this.message_file_map[message.messageId]) {
const attachments = this.message_file_map[message.messageId];
for (const file of attachments) {
if (file.embedded) {
this.contextHandlers?.processFile(file);
continue;
}
// orderedMessages[i].tokenCount += this.calculateImageTokenCost({
// width: file.width,
// height: file.height,
// detail: this.options.imageDetail ?? ImageDetail.auto,
// });
}
}
return formattedMessage;
});
if (this.contextHandlers) {
this.augmentedPrompt = await this.contextHandlers.createContext();
systemContent = this.augmentedPrompt + systemContent;
}
if (systemContent) {
this.options.agent.instructions = systemContent;
}
if (this.contextStrategy) {
({ payload, promptTokens, messages } = await this.handleContextStrategy({
orderedMessages,
formattedMessages,
/* prefer usage_metadata from final message */
buildTokenMap: false,
}));
}
const result = {
prompt: payload,
promptTokens,
messages,
};
if (promptTokens >= 0 && typeof opts?.getReqData === 'function') {
opts.getReqData({ promptTokens });
}
return result;
}
/** @type {sendCompletion} */
async sendCompletion(payload, opts = {}) {
this.modelOptions.user = this.user;
await this.chatCompletion({
payload,
onProgress: opts.onProgress,
abortController: opts.abortController,
});
return this.contentParts;
}
/**
* @param {Object} params
* @param {string} [params.model]
* @param {string} [params.context='message']
* @param {UsageMetadata[]} [params.collectedUsage=this.collectedUsage]
*/
async recordCollectedUsage({ model, context = 'message', collectedUsage = this.collectedUsage }) {
for (const usage of collectedUsage) {
await spendTokens(
{
context,
model: model ?? this.modelOptions.model,
conversationId: this.conversationId,
user: this.user ?? this.options.req.user?.id,
endpointTokenConfig: this.options.endpointTokenConfig,
},
{ promptTokens: usage.input_tokens, completionTokens: usage.output_tokens },
);
}
}
async chatCompletion({ payload, abortController = null }) {
try {
if (!abortController) {
abortController = new AbortController();
}
const baseURL = extractBaseURL(this.completionsUrl);
logger.debug('[api/server/controllers/agents/client.js] chatCompletion', {
baseURL,
payload,
});
// if (this.useOpenRouter) {
// opts.defaultHeaders = {
// 'HTTP-Referer': 'https://librechat.ai',
// 'X-Title': 'LibreChat',
// };
// }
// if (this.options.headers) {
// opts.defaultHeaders = { ...opts.defaultHeaders, ...this.options.headers };
// }
// if (this.options.proxy) {
// opts.httpAgent = new HttpsProxyAgent(this.options.proxy);
// }
// if (this.isVisionModel) {
// modelOptions.max_tokens = 4000;
// }
// /** @type {TAzureConfig | undefined} */
// const azureConfig = this.options?.req?.app?.locals?.[EModelEndpoint.azureOpenAI];
// if (
// (this.azure && this.isVisionModel && azureConfig) ||
// (azureConfig && this.isVisionModel && this.options.endpoint === EModelEndpoint.azureOpenAI)
// ) {
// const { modelGroupMap, groupMap } = azureConfig;
// const {
// azureOptions,
// baseURL,
// headers = {},
// serverless,
// } = mapModelToAzureConfig({
// modelName: modelOptions.model,
// modelGroupMap,
// groupMap,
// });
// opts.defaultHeaders = resolveHeaders(headers);
// this.langchainProxy = extractBaseURL(baseURL);
// this.apiKey = azureOptions.azureOpenAIApiKey;
// const groupName = modelGroupMap[modelOptions.model].group;
// this.options.addParams = azureConfig.groupMap[groupName].addParams;
// this.options.dropParams = azureConfig.groupMap[groupName].dropParams;
// // Note: `forcePrompt` not re-assigned as only chat models are vision models
// this.azure = !serverless && azureOptions;
// this.azureEndpoint =
// !serverless && genAzureChatCompletion(this.azure, modelOptions.model, this);
// }
// if (this.azure || this.options.azure) {
// /* Azure Bug, extremely short default `max_tokens` response */
// if (!modelOptions.max_tokens && modelOptions.model === 'gpt-4-vision-preview') {
// modelOptions.max_tokens = 4000;
// }
// /* Azure does not accept `model` in the body, so we need to remove it. */
// delete modelOptions.model;
// opts.baseURL = this.langchainProxy
// ? constructAzureURL({
// baseURL: this.langchainProxy,
// azureOptions: this.azure,
// })
// : this.azureEndpoint.split(/(?<!\/)\/(chat|completion)\//)[0];
// opts.defaultQuery = { 'api-version': this.azure.azureOpenAIApiVersion };
// opts.defaultHeaders = { ...opts.defaultHeaders, 'api-key': this.apiKey };
// }
// if (process.env.OPENAI_ORGANIZATION) {
// opts.organization = process.env.OPENAI_ORGANIZATION;
// }
// if (this.options.addParams && typeof this.options.addParams === 'object') {
// modelOptions = {
// ...modelOptions,
// ...this.options.addParams,
// };
// logger.debug('[api/server/controllers/agents/client.js #chatCompletion] added params', {
// addParams: this.options.addParams,
// modelOptions,
// });
// }
// if (this.options.dropParams && Array.isArray(this.options.dropParams)) {
// this.options.dropParams.forEach((param) => {
// delete modelOptions[param];
// });
// logger.debug('[api/server/controllers/agents/client.js #chatCompletion] dropped params', {
// dropParams: this.options.dropParams,
// modelOptions,
// });
// }
const run = await createRun({
req: this.options.req,
agent: this.options.agent,
tools: this.options.tools,
toolMap: this.options.toolMap,
runId: this.responseMessageId,
modelOptions: this.modelOptions,
customHandlers: this.options.eventHandlers,
});
const config = {
configurable: {
provider: providerEndpointMap[this.options.agent.provider],
thread_id: this.conversationId,
},
signal: abortController.signal,
streamMode: 'values',
version: 'v2',
};
if (!run) {
throw new Error('Failed to create run');
}
this.run = run;
const messages = formatAgentMessages(payload);
await run.processStream({ messages }, config, {
[Callback.TOOL_ERROR]: (graph, error, toolId) => {
logger.error(
'[api/server/controllers/agents/client.js #chatCompletion] Tool Error',
error,
toolId,
);
},
});
this.recordCollectedUsage({ context: 'message' }).catch((err) => {
logger.error(
'[api/server/controllers/agents/client.js #chatCompletion] Error recording collected usage',
err,
);
});
} catch (err) {
if (!abortController.signal.aborted) {
logger.error(
'[api/server/controllers/agents/client.js #sendCompletion] Unhandled error type',
err,
);
throw err;
}
logger.warn(
'[api/server/controllers/agents/client.js #sendCompletion] Operation aborted',
err,
);
}
}
/**
*
* @param {Object} params
* @param {string} params.text
* @param {string} params.conversationId
*/
async titleConvo({ text }) {
if (!this.run) {
throw new Error('Run not initialized');
}
const { handleLLMEnd, collected: collectedMetadata } = createMetadataAggregator();
const clientOptions = {};
const providerConfig = this.options.req.app.locals[this.options.agent.provider];
if (
providerConfig &&
providerConfig.titleModel &&
providerConfig.titleModel !== Constants.CURRENT_MODEL
) {
clientOptions.model = providerConfig.titleModel;
}
try {
const titleResult = await this.run.generateTitle({
inputText: text,
contentParts: this.contentParts,
clientOptions,
chainOptions: {
callbacks: [
{
handleLLMEnd,
},
],
},
});
const collectedUsage = collectedMetadata.map((item) => {
let input_tokens, output_tokens;
if (item.usage) {
input_tokens = item.usage.input_tokens || item.usage.inputTokens;
output_tokens = item.usage.output_tokens || item.usage.outputTokens;
} else if (item.tokenUsage) {
input_tokens = item.tokenUsage.promptTokens;
output_tokens = item.tokenUsage.completionTokens;
}
return {
input_tokens: input_tokens,
output_tokens: output_tokens,
};
});
this.recordCollectedUsage({
model: clientOptions.model,
context: 'title',
collectedUsage,
}).catch((err) => {
logger.error(
'[api/server/controllers/agents/client.js #titleConvo] Error recording collected usage',
err,
);
});
return titleResult.title;
} catch (err) {
logger.error('[api/server/controllers/agents/client.js #titleConvo] Error', err);
return;
}
}
getEncoding() {
return this.modelOptions.model?.includes('gpt-4o') ? 'o200k_base' : 'cl100k_base';
}
/**
* Returns the token count of a given text. It also checks and resets the tokenizers if necessary.
* @param {string} text - The text to get the token count for.
* @returns {number} The token count of the given text.
*/
getTokenCount(text) {
const encoding = this.getEncoding();
return Tokenizer.getTokenCount(text, encoding);
}
}
module.exports = AgentClient;

View File

@@ -1,153 +0,0 @@
// errorHandler.js
const { logger } = require('~/config');
const getLogStores = require('~/cache/getLogStores');
const { CacheKeys, ViolationTypes } = require('librechat-data-provider');
const { recordUsage } = require('~/server/services/Threads');
const { getConvo } = require('~/models/Conversation');
const { sendResponse } = require('~/server/utils');
/**
* @typedef {Object} ErrorHandlerContext
* @property {OpenAIClient} openai - The OpenAI client
* @property {string} run_id - The run ID
* @property {boolean} completedRun - Whether the run has completed
* @property {string} assistant_id - The assistant ID
* @property {string} conversationId - The conversation ID
* @property {string} parentMessageId - The parent message ID
* @property {string} responseMessageId - The response message ID
* @property {string} endpoint - The endpoint being used
* @property {string} cacheKey - The cache key for the current request
*/
/**
* @typedef {Object} ErrorHandlerDependencies
* @property {Express.Request} req - The Express request object
* @property {Express.Response} res - The Express response object
* @property {() => ErrorHandlerContext} getContext - Function to get the current context
* @property {string} [originPath] - The origin path for the error handler
*/
/**
* Creates an error handler function with the given dependencies
* @param {ErrorHandlerDependencies} dependencies - The dependencies for the error handler
* @returns {(error: Error) => Promise<void>} The error handler function
*/
const createErrorHandler = ({ req, res, getContext, originPath = '/assistants/chat/' }) => {
const cache = getLogStores(CacheKeys.ABORT_KEYS);
/**
* Handles errors that occur during the chat process
* @param {Error} error - The error that occurred
* @returns {Promise<void>}
*/
return async (error) => {
const {
openai,
run_id,
endpoint,
cacheKey,
completedRun,
assistant_id,
conversationId,
parentMessageId,
responseMessageId,
} = getContext();
const defaultErrorMessage =
'The Assistant run failed to initialize. Try sending a message in a new conversation.';
const messageData = {
assistant_id,
conversationId,
parentMessageId,
sender: 'System',
user: req.user.id,
shouldSaveMessage: false,
messageId: responseMessageId,
endpoint,
};
if (error.message === 'Run cancelled') {
return res.end();
} else if (error.message === 'Request closed' && completedRun) {
return;
} else if (error.message === 'Request closed') {
logger.debug(`[${originPath}] Request aborted on close`);
} else if (/Files.*are invalid/.test(error.message)) {
const errorMessage = `Files are invalid, or may not have uploaded yet.${
endpoint === 'azureAssistants'
? ' If using Azure OpenAI, files are only available in the region of the assistant\'s model at the time of upload.'
: ''
}`;
return sendResponse(req, res, messageData, errorMessage);
} else if (error?.message?.includes('string too long')) {
return sendResponse(
req,
res,
messageData,
'Message too long. The Assistants API has a limit of 32,768 characters per message. Please shorten it and try again.',
);
} else if (error?.message?.includes(ViolationTypes.TOKEN_BALANCE)) {
return sendResponse(req, res, messageData, error.message);
} else {
logger.error(`[${originPath}]`, error);
}
if (!openai || !run_id) {
return sendResponse(req, res, messageData, defaultErrorMessage);
}
await new Promise((resolve) => setTimeout(resolve, 2000));
try {
const status = await cache.get(cacheKey);
if (status === 'cancelled') {
logger.debug(`[${originPath}] Run already cancelled`);
return res.end();
}
await cache.delete(cacheKey);
// const cancelledRun = await openai.beta.threads.runs.cancel(thread_id, run_id);
// logger.debug(`[${originPath}] Cancelled run:`, cancelledRun);
} catch (error) {
logger.error(`[${originPath}] Error cancelling run`, error);
}
await new Promise((resolve) => setTimeout(resolve, 2000));
let run;
try {
// run = await openai.beta.threads.runs.retrieve(thread_id, run_id);
await recordUsage({
...run.usage,
model: run.model,
user: req.user.id,
conversationId,
});
} catch (error) {
logger.error(`[${originPath}] Error fetching or processing run`, error);
}
let finalEvent;
try {
// const errorContentPart = {
// text: {
// value:
// error?.message ?? 'There was an error processing your request. Please try again later.',
// },
// type: ContentTypes.ERROR,
// };
finalEvent = {
final: true,
conversation: await getConvo(req.user.id, conversationId),
// runMessages,
};
} catch (error) {
logger.error(`[${originPath}] Error finalizing error process`, error);
return sendResponse(req, res, messageData, 'The Assistant run failed');
}
return sendResponse(req, res, finalEvent);
};
};
module.exports = { createErrorHandler };

View File

@@ -1,106 +0,0 @@
const { HttpsProxyAgent } = require('https-proxy-agent');
const { resolveHeaders } = require('librechat-data-provider');
const { createLLM } = require('~/app/clients/llm');
/**
* Initializes and returns a Language Learning Model (LLM) instance.
*
* @param {Object} options - Configuration options for the LLM.
* @param {string} options.model - The model identifier.
* @param {string} options.modelName - The specific name of the model.
* @param {number} options.temperature - The temperature setting for the model.
* @param {number} options.presence_penalty - The presence penalty for the model.
* @param {number} options.frequency_penalty - The frequency penalty for the model.
* @param {number} options.max_tokens - The maximum number of tokens for the model output.
* @param {boolean} options.streaming - Whether to use streaming for the model output.
* @param {Object} options.context - The context for the conversation.
* @param {number} options.tokenBuffer - The token buffer size.
* @param {number} options.initialMessageCount - The initial message count.
* @param {string} options.conversationId - The ID of the conversation.
* @param {string} options.user - The user identifier.
* @param {string} options.langchainProxy - The langchain proxy URL.
* @param {boolean} options.useOpenRouter - Whether to use OpenRouter.
* @param {Object} options.options - Additional options.
* @param {Object} options.options.headers - Custom headers for the request.
* @param {string} options.options.proxy - Proxy URL.
* @param {Object} options.options.req - The request object.
* @param {Object} options.options.res - The response object.
* @param {boolean} options.options.debug - Whether to enable debug mode.
* @param {string} options.apiKey - The API key for authentication.
* @param {Object} options.azure - Azure-specific configuration.
* @param {Object} options.abortController - The AbortController instance.
* @returns {Object} The initialized LLM instance.
*/
function initializeLLM(options) {
const {
model,
modelName,
temperature,
presence_penalty,
frequency_penalty,
max_tokens,
streaming,
user,
langchainProxy,
useOpenRouter,
options: { headers, proxy },
apiKey,
azure,
} = options;
const modelOptions = {
modelName: modelName || model,
temperature,
presence_penalty,
frequency_penalty,
user,
};
if (max_tokens) {
modelOptions.max_tokens = max_tokens;
}
const configOptions = {};
if (langchainProxy) {
configOptions.basePath = langchainProxy;
}
if (useOpenRouter) {
configOptions.basePath = 'https://openrouter.ai/api/v1';
configOptions.baseOptions = {
headers: {
'HTTP-Referer': 'https://librechat.ai',
'X-Title': 'LibreChat',
},
};
}
if (headers && typeof headers === 'object' && !Array.isArray(headers)) {
configOptions.baseOptions = {
headers: resolveHeaders({
...headers,
...configOptions?.baseOptions?.headers,
}),
};
}
if (proxy) {
configOptions.httpAgent = new HttpsProxyAgent(proxy);
configOptions.httpsAgent = new HttpsProxyAgent(proxy);
}
const llm = createLLM({
modelOptions,
configOptions,
openAIApiKey: apiKey,
azure,
streaming,
});
return llm;
}
module.exports = {
initializeLLM,
};

View File

@@ -1,142 +0,0 @@
const { Constants } = require('librechat-data-provider');
const { createAbortController, handleAbortError } = require('~/server/middleware');
const { sendMessage } = require('~/server/utils');
const { saveMessage } = require('~/models');
const { logger } = require('~/config');
const AgentController = async (req, res, next, initializeClient, addTitle) => {
let {
text,
endpointOption,
conversationId,
parentMessageId = null,
overrideParentMessageId = null,
} = req.body;
let sender;
let userMessage;
let promptTokens;
let userMessageId;
let responseMessageId;
let userMessagePromise;
const newConvo = !conversationId;
const user = req.user.id;
const getReqData = (data = {}) => {
for (let key in data) {
if (key === 'userMessage') {
userMessage = data[key];
userMessageId = data[key].messageId;
} else if (key === 'userMessagePromise') {
userMessagePromise = data[key];
} else if (key === 'responseMessageId') {
responseMessageId = data[key];
} else if (key === 'promptTokens') {
promptTokens = data[key];
} else if (key === 'sender') {
sender = data[key];
} else if (!conversationId && key === 'conversationId') {
conversationId = data[key];
}
}
};
try {
/** @type {{ client: TAgentClient }} */
const { client } = await initializeClient({ req, res, endpointOption });
const getAbortData = () => ({
sender,
userMessage,
promptTokens,
conversationId,
userMessagePromise,
messageId: responseMessageId,
content: client.getContentParts(),
parentMessageId: overrideParentMessageId ?? userMessageId,
});
const { abortController, onStart } = createAbortController(req, res, getAbortData, getReqData);
res.on('close', () => {
logger.debug('[AgentController] Request closed');
if (!abortController) {
return;
} else if (abortController.signal.aborted) {
return;
} else if (abortController.requestCompleted) {
return;
}
abortController.abort();
logger.debug('[AgentController] Request aborted on close');
});
const messageOptions = {
user,
onStart,
getReqData,
conversationId,
parentMessageId,
abortController,
overrideParentMessageId,
progressOptions: {
res,
// parentMessageId: overrideParentMessageId || userMessageId,
},
};
let response = await client.sendMessage(text, messageOptions);
response.endpoint = endpointOption.endpoint;
const { conversation = {} } = await client.responsePromise;
conversation.title =
conversation && !conversation.title ? null : conversation?.title || 'New Chat';
if (client.options.attachments) {
userMessage.files = client.options.attachments;
delete userMessage.image_urls;
}
if (!abortController.signal.aborted) {
sendMessage(res, {
final: true,
conversation,
title: conversation.title,
requestMessage: userMessage,
responseMessage: response,
});
res.end();
await saveMessage(
req,
{ ...response, user },
{ context: 'api/server/controllers/agents/request.js - response end' },
);
}
if (!client.skipSaveUserMessage) {
await saveMessage(req, userMessage, {
context: 'api/server/controllers/agents/request.js - don\'t skip saving user message',
});
}
if (addTitle && parentMessageId === Constants.NO_PARENT && newConvo) {
addTitle(req, {
text,
response,
client,
});
}
} catch (error) {
handleAbortError(res, req, error, {
conversationId,
sender,
messageId: responseMessageId,
parentMessageId: userMessageId ?? parentMessageId,
});
}
};
module.exports = AgentController;

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