feat(docker): add flexible LLM provider configuration
- Support LLM_PROVIDER env var to override default provider (openai/gpt-4o-mini) - Add optional 'provider' parameter to API endpoints for per-request overrides - Implement provider validation to ensure API keys exist - Update documentation and examples with new configuration options Closes the need to hardcode providers in config.yml
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@@ -40,7 +40,9 @@ from utils import (
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get_base_url,
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is_task_id,
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should_cleanup_task,
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decode_redis_hash
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decode_redis_hash,
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get_llm_api_key,
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validate_llm_provider
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)
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import psutil, time
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@@ -89,10 +91,12 @@ async def handle_llm_qa(
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Answer:"""
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# api_token=os.environ.get(config["llm"].get("api_key_env", ""))
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response = perform_completion_with_backoff(
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provider=config["llm"]["provider"],
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prompt_with_variables=prompt,
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api_token=os.environ.get(config["llm"].get("api_key_env", ""))
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api_token=get_llm_api_key(config)
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)
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return response.choices[0].message.content
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@@ -110,19 +114,23 @@ async def process_llm_extraction(
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url: str,
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instruction: str,
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schema: Optional[str] = None,
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cache: str = "0"
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cache: str = "0",
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provider: Optional[str] = None
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) -> None:
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"""Process LLM extraction in background."""
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try:
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# If config['llm'] has api_key then ignore the api_key_env
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api_key = ""
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if "api_key" in config["llm"]:
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api_key = config["llm"]["api_key"]
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else:
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api_key = os.environ.get(config["llm"].get("api_key_env", None), "")
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# Validate provider
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is_valid, error_msg = validate_llm_provider(config, provider)
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if not is_valid:
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await redis.hset(f"task:{task_id}", mapping={
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"status": TaskStatus.FAILED,
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"error": error_msg
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})
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return
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api_key = get_llm_api_key(config, provider)
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llm_strategy = LLMExtractionStrategy(
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llm_config=LLMConfig(
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provider=config["llm"]["provider"],
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provider=provider or config["llm"]["provider"],
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api_token=api_key
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),
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instruction=instruction,
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@@ -169,10 +177,19 @@ async def handle_markdown_request(
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filter_type: FilterType,
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query: Optional[str] = None,
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cache: str = "0",
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config: Optional[dict] = None
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config: Optional[dict] = None,
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provider: Optional[str] = None
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) -> str:
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"""Handle markdown generation requests."""
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try:
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# Validate provider if using LLM filter
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if filter_type == FilterType.LLM:
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is_valid, error_msg = validate_llm_provider(config, provider)
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if not is_valid:
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raise HTTPException(
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status_code=status.HTTP_400_BAD_REQUEST,
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detail=error_msg
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)
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decoded_url = unquote(url)
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if not decoded_url.startswith(('http://', 'https://')):
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decoded_url = 'https://' + decoded_url
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@@ -185,8 +202,8 @@ async def handle_markdown_request(
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FilterType.BM25: BM25ContentFilter(user_query=query or ""),
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FilterType.LLM: LLMContentFilter(
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llm_config=LLMConfig(
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provider=config["llm"]["provider"],
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api_token=os.environ.get(config["llm"].get("api_key_env", None), ""),
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provider=provider or config["llm"]["provider"],
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api_token=get_llm_api_key(config, provider),
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),
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instruction=query or "Extract main content"
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)
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@@ -230,7 +247,8 @@ async def handle_llm_request(
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query: Optional[str] = None,
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schema: Optional[str] = None,
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cache: str = "0",
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config: Optional[dict] = None
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config: Optional[dict] = None,
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provider: Optional[str] = None
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) -> JSONResponse:
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"""Handle LLM extraction requests."""
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base_url = get_base_url(request)
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@@ -260,7 +278,8 @@ async def handle_llm_request(
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schema,
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cache,
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base_url,
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config
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config,
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provider
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)
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except Exception as e:
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@@ -304,7 +323,8 @@ async def create_new_task(
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schema: Optional[str],
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cache: str,
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base_url: str,
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config: dict
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config: dict,
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provider: Optional[str] = None
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) -> JSONResponse:
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"""Create and initialize a new task."""
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decoded_url = unquote(input_path)
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@@ -328,7 +348,8 @@ async def create_new_task(
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decoded_url,
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query,
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schema,
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cache
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cache,
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provider
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)
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return JSONResponse({
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