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fix: apply automatic ruff formatting

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This commit is contained in:
al1kss
2025-07-14 00:28:45 +06:00
parent 0d69e40995
commit e44e7296b2
1 changed files with 35 additions and 40 deletions
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75
examples/unofficial-sample/lightrag_cloudflare_demo.py
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@@ -4,13 +4,10 @@ import inspect
import logging
import logging.config
from lightrag import LightRAG, QueryParam
from lightrag.llm.ollama import ollama_model_complete, ollama_embed
from lightrag.utils import EmbeddingFunc, logger, set_verbose_debug
from lightrag.kg.shared_storage import initialize_pipeline_status
import requests
import json
from functools import partial
import numpy as np
from dotenv import load_dotenv
@@ -21,29 +18,32 @@ load_dotenv(dotenv_path=".env", override=False)
""" ----========= IMPORTANT CHANGE THIS! =========---- """
cloudflare_api_key = 'YOUR_API_KEY'
account_id = 'YOUR_ACCOUNT ID' #This is unique to your Cloudflare account
cloudflare_api_key = "YOUR_API_KEY"
account_id = "YOUR_ACCOUNT ID" # This is unique to your Cloudflare account
# Authomatically changes
api_base_url = f"https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/run/"
# choose an embedding model
EMBEDDING_MODEL = '@cf/baai/bge-m3'
EMBEDDING_MODEL = "@cf/baai/bge-m3"
# choose a generative model
LLM_MODEL = "@cf/meta/llama-3.2-3b-instruct"
WORKING_DIR = "../dickens" #you can change output as desired
WORKING_DIR = "../dickens" # you can change output as desired
# Cloudflare init
class CloudflareWorker:
def __init__(self,
cloudflare_api_key: str,
api_base_url: str,
llm_model_name: str,
embedding_model_name: str,
max_tokens: int = 4080,
max_response_tokens: int = 4080):
def __init__(
self,
cloudflare_api_key: str,
api_base_url: str,
llm_model_name: str,
embedding_model_name: str,
max_tokens: int = 4080,
max_response_tokens: int = 4080,
):
self.cloudflare_api_key = cloudflare_api_key
self.api_base_url = api_base_url
self.llm_model_name = llm_model_name
@@ -54,23 +54,21 @@ class CloudflareWorker:
async def _send_request(self, model_name: str, input_: dict, debug_log: str):
headers = {"Authorization": f"Bearer {self.cloudflare_api_key}"}
print(f'''
print(f"""
data sent to Cloudflare
~~~~~~~~~~~
{debug_log}
''')
""")
try:
response_raw = requests.post(
f"{self.api_base_url}{model_name}",
headers=headers,
json=input_
f"{self.api_base_url}{model_name}", headers=headers, json=input_
).json()
print(f'''
print(f"""
Cloudflare worker responded with:
~~~~~~~~~~~
{str(response_raw)}
''')
""")
result = response_raw.get("result", {})
if "data" in result: # Embedding case
@@ -82,22 +80,21 @@ class CloudflareWorker:
raise ValueError("Unexpected Cloudflare response format")
except Exception as e:
print(f'''
print(f"""
Cloudflare API returned:
~~~~~~~~~
Error: {e}
''')
""")
input("Press Enter to continue...")
return None
async def query(self, prompt, system_prompt: str = '', **kwargs) -> str:
async def query(self, prompt, system_prompt: str = "", **kwargs) -> str:
# since no caching is used and we don't want to mess with everything lightrag, pop the kwarg it is
kwargs.pop("hashing_kv", None)
message = [
{"role": "system", "content": system_prompt},
{"role": "user", "content": prompt}
{"role": "user", "content": prompt},
]
input_ = {
@@ -109,15 +106,15 @@ class CloudflareWorker:
return await self._send_request(
self.llm_model_name,
input_,
debug_log=f"\n- model used {self.llm_model_name}\n- system prompt: {system_prompt}\n- query: {prompt}"
debug_log=f"\n- model used {self.llm_model_name}\n- system prompt: {system_prompt}\n- query: {prompt}",
)
async def embedding_chunk(self, texts: list[str]) -> np.ndarray:
print(f'''
print(f"""
TEXT inputted
~~~~~
{texts}
''')
""")
input_ = {
"text": texts,
@@ -128,12 +125,10 @@ class CloudflareWorker:
return await self._send_request(
self.embedding_model_name,
input_,
debug_log=f"\n-llm model name {self.embedding_model_name}\n- texts: {texts}"
debug_log=f"\n-llm model name {self.embedding_model_name}\n- texts: {texts}",
)
def configure_logging():
"""Configure logging for the application"""
@@ -145,7 +140,9 @@ def configure_logging():
# Get log directory path from environment variable or use current directory
log_dir = os.getenv("LOG_DIR", os.getcwd())
log_file_path = os.path.abspath(os.path.join(log_dir, "lightrag_cloudflare_worker_demo.log"))
log_file_path = os.path.abspath(
os.path.join(log_dir, "lightrag_cloudflare_worker_demo.log")
)
print(f"\nLightRAG compatible demo log file: {log_file_path}\n")
os.makedirs(os.path.dirname(log_file_path), exist_ok=True)
@@ -203,10 +200,10 @@ if not os.path.exists(WORKING_DIR):
async def initialize_rag():
cloudflare_worker = CloudflareWorker(
cloudflare_api_key = cloudflare_api_key,
api_base_url = api_base_url,
embedding_model_name = EMBEDDING_MODEL,
llm_model_name = LLM_MODEL,
cloudflare_api_key=cloudflare_api_key,
api_base_url=api_base_url,
embedding_model_name=EMBEDDING_MODEL,
llm_model_name=LLM_MODEL,
)
rag = LightRAG(
@@ -269,7 +266,7 @@ async def main():
# Locate the location of what is needed to be added to the knowledge
# Can add several simultaneously by modifying code
with open("./book.txt", "r", encoding="utf-8") as f:
with open("./book.txt", "r", encoding="utf-8") as f:
await rag.ainsert(f.read())
# Perform naive search
@@ -324,8 +321,6 @@ async def main():
else:
print(resp)
""" FOR TESTING (if you want to test straight away, after building. Uncomment this part"""
"""