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Improve embedding config priority and add debug logging

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• Fix embedding_dim priority logic
• Add final config logging
This commit is contained in:
yangdx
2025-11-14 23:22:44 +08:00
parent 2fb57e767d
commit e5addf4d94
1 changed files with 21 additions and 9 deletions
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30
lightrag/api/lightrag_server.py
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@@ -655,8 +655,8 @@ def create_app(args):
# Step 1: Import provider function and extract default attributes
provider_func = None
default_max_token_size = None
default_embedding_dim = args.embedding_dim # Use config as default
provider_max_token_size = None
provider_embedding_dim = None
try:
if binding == "openai":
@@ -690,18 +690,24 @@ def create_app(args):
# Extract attributes if provider is an EmbeddingFunc
if provider_func and isinstance(provider_func, EmbeddingFunc):
default_max_token_size = provider_func.max_token_size
default_embedding_dim = provider_func.embedding_dim
provider_max_token_size = provider_func.max_token_size
provider_embedding_dim = provider_func.embedding_dim
logger.debug(
f"Extracted from {binding} provider: "
f"max_token_size={default_max_token_size}, "
f"embedding_dim={default_embedding_dim}"
f"max_token_size={provider_max_token_size}, "
f"embedding_dim={provider_embedding_dim}"
)
except ImportError as e:
logger.warning(f"Could not import provider function for {binding}: {e}")
# Step 2: Apply priority (environment variable > provider default)
final_max_token_size = args.embedding_token_limit or default_max_token_size
# Step 2: Apply priority (user config > provider default)
# For max_token_size: explicit env var > provider default > None
final_max_token_size = args.embedding_token_limit or provider_max_token_size
# For embedding_dim: user config (always has value) takes priority
# Only use provider default if user config is explicitly None (which shouldn't happen)
final_embedding_dim = (
args.embedding_dim if args.embedding_dim else provider_embedding_dim
)
# Step 3: Create optimized embedding function (calls underlying function directly)
async def optimized_embedding_function(texts, embedding_dim=None):
@@ -820,12 +826,18 @@ def create_app(args):
# Step 4: Wrap in EmbeddingFunc and return
embedding_func_instance = EmbeddingFunc(
embedding_dim=default_embedding_dim,
embedding_dim=final_embedding_dim,
func=optimized_embedding_function,
max_token_size=final_max_token_size,
send_dimensions=False, # Will be set later based on binding requirements
)
# Log final embedding configuration
logger.info(
f"Embedding config: binding={binding} model={model} "
f"embedding_dim={final_embedding_dim} max_token_size={final_max_token_size}"
)
return embedding_func_instance
llm_timeout = get_env_value("LLM_TIMEOUT", DEFAULT_LLM_TIMEOUT, int)