Language Model Configuration
LLM Configuration File
To edit your LLM configuration, open this file with your preferred text editor:
{{ llm_file_path }}
Default Configuration Example
""" LLM configuration for Local Deep Research. This file is loaded as a Python module, allowing for complex customization of LLM behavior. """ # Default model settings DEFAULT_MODEL = "mistral" DEFAULT_MODEL_TYPE = "ollama" # Options: ollama, openai, anthropic DEFAULT_TEMPERATURE = 0.7 MAX_TOKENS = 30000 # API keys and endpoints (consider using environment variables instead) USE_OPENAI_ENDPOINT = False OPENAI_ENDPOINT_URL = "https://openrouter.ai/api/v1" OPENAI_ENDPOINT_REQUIRES_MODEL = True # Custom model loading function def get_llm(model_name=None, model_type=None, temperature=None, **kwargs): """ Get a language model instance. Args: model_name: Name of the model to use model_type: Type of model provider temperature: Model temperature **kwargs: Additional parameters Returns: A LangChain language model instance """ # Use defaults if not provided model_name = model_name or DEFAULT_MODEL model_type = model_type or DEFAULT_MODEL_TYPE temperature = temperature or DEFAULT_TEMPERATURE # If using Ollama if model_type == "ollama": from langchain_ollama import ChatOllama return ChatOllama( model=model_name, temperature=temperature, **kwargs ) # Default fallback from langchain_ollama import ChatOllama return ChatOllama( model="mistral", temperature=0.7, **kwargs )