refac: clearer code, fix output

src/core/config.py

@@ -2,17 +2,6 @@ from pydantic_settings import BaseSettings
 import os
 from pathlib import Path
 
-
-def read_secret_from_file(secret_name: str) -> str:
-    """Read a secret from HuggingFace Spaces secrets directory."""
-    secrets_dir = Path("/run/secrets")
-    secret_file = secrets_dir / secret_name
-    
-    if secret_file.exists():
-        return secret_file.read_text().strip()
-    return ""
-
-
 class Settings(BaseSettings):
     MODEL_NAME: str = "mistralai/Mistral-7B-Instruct-v0.2"
 
@@ -30,10 +19,4 @@ class Settings(BaseSettings):
     class Config:
         env_file = ".env"
 
-
-# Try to read HF_TOKEN from HuggingFace Spaces secrets first, then fall back to env
-hf_token_from_file = read_secret_from_file("HF_TOKEN")
-if hf_token_from_file:
-    os.environ["HF_TOKEN"] = hf_token_from_file
-
 settings = Settings()

src/rag/llm.py

@@ -1,22 +1,3 @@
-import os
-import logging
-
-# Check what the OS actually sees
-raw_token = os.getenv("HF_TOKEN")
-
-print("--- DEBUG START ---")
-if raw_token:
-    print(f"OS found HF_TOKEN! Length: {len(raw_token)}")
-    print(f"First 3 chars: {raw_token[:3]}...") # Safety check
-else:
-    print("OS did NOT find HF_TOKEN. It is None/Empty.")
-    # Print all keys available (masked) to see if there is a typo
-    print("Available Env Vars:", [k for k in os.environ.keys() if 'TOKEN' in k])
-print("--- DEBUG END ---")
-
-from langchain_huggingface import ChatHuggingFace, HuggingFaceEndpoint
-from langchain_core.prompts import ChatPromptTemplate
-
 from src.prompts import SYSTEM_PROMPT
 from src.core.config import settings
 

src/rag/pipeline.py

@@ -54,7 +54,9 @@ def answer_question(question: str) -> tuple[str, list[dict]]:
         chain = get_chain()
 
         response = chain.invoke({"context": context, "question": question})
-        return response, citations
+        # Extract just the content from the response message
+        answer_text = response.content if hasattr(response, 'content') else str(response)
+        return answer_text, citations
     except Exception as e:
         logging.error(f"Error occurred while answering question: {e}")
         error_msg = f"Sorry, an error occurred while processing your request: {str(e)}"