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| """ | |
| Configuration file for LLM provider | |
| Change LLM_PROVIDER to switch between different models | |
| """ | |
| import os | |
| # Swappable LLM provider (environment configurable) | |
| LLM_PROVIDER = os.getenv("LLM_PROVIDER", "local") # Options: "huggingface", "local" | |
| # API Keys (set these as environment variables in HuggingFace Space secrets) | |
| HUGGINGFACE_API_KEY = os.getenv("HUGGINGFACE_API_KEY", "") | |
| # Model configurations | |
| HUGGINGFACE_MODEL = "google/gemma-2-2b-it" | |
| # Local model configuration (for quantized models hosted within the Space) | |
| LOCAL_MODEL_REPO = os.getenv("LOCAL_MODEL_REPO", "tensorblock/gemma-2-2b-it-GGUF") | |
| LOCAL_MODEL_FILENAME = os.getenv("LOCAL_MODEL_FILENAME", "gemma-2-2b-it-Q4_K_M.gguf") | |
| LOCAL_MODEL_CONTEXT_LENGTH = int(os.getenv("LOCAL_MODEL_CONTEXT_LENGTH", "4096")) | |
| LOCAL_MODEL_THREADS = int(os.getenv("LOCAL_MODEL_THREADS", str(os.cpu_count() or 4))) | |
| LOCAL_MODEL_BATCH_SIZE = int(os.getenv("LOCAL_MODEL_BATCH_SIZE", "256")) | |
| LOCAL_MODEL_MAX_OUTPUT_TOKENS = int(os.getenv("LOCAL_MODEL_MAX_OUTPUT_TOKENS", "512")) | |
| LOCAL_MODEL_HF_TOKEN = os.getenv("LOCAL_MODEL_HF_TOKEN", HUGGINGFACE_API_KEY or "") | |
| # Access control configuration | |
| CLIENT_APP_ORIGINS = [ | |
| origin.strip() | |
| for origin in os.getenv("CLIENT_APP_ORIGINS", "").split(",") | |
| if origin.strip() | |
| ] | |
| API_ACCESS_TOKEN = os.getenv("API_ACCESS_TOKEN", "") | |
| # Session token configuration | |
| SESSION_TOKEN_SECRET = os.getenv("SESSION_TOKEN_SECRET", "") | |
| SESSION_TOKEN_TTL_SECONDS = int(os.getenv("SESSION_TOKEN_TTL_SECONDS", "600")) | |
| # RAG Configuration | |
| EMBEDDING_MODEL = "sentence-transformers/all-MiniLM-L6-v2" # Fast, lightweight | |
| CHUNK_SIZE = 500 # Characters per chunk | |
| CHUNK_OVERLAP = 50 # Overlap between chunks | |
| TOP_K_RESULTS = 3 # Number of relevant chunks to retrieve | |
| # System prompt for the chatbot | |
| SYSTEM_PROMPT = """You are Bi's professional assistant, helping visitors learn about his background, skills, and experience. | |
| Instructions: | |
| - Refer to Bi directly by name (e.g., "Bi has experience in...", "Bi worked on...") | |
| - Answer questions based ONLY on the provided context about Bi | |
| - Be conversational, friendly, and professional - like a knowledgeable secretary | |
| - If information is not in the context, politely say you don't have that information about Bi | |
| - Keep responses concise but informative | |
| - Speak on Bi's behalf in a supportive, professional manner | |
| """ | |