Updated

main.py

@@ -1,15 +1,17 @@
-# ===============================================
-# Tech Disciples AI Backend — LangChain ≥1.0
-# ===============================================
+# =====================================================
+# Tech Disciples AI Backend — Llama 3.1 (8B) Version
+# =====================================================
 
 from fastapi import FastAPI, HTTPException, Header
 from pydantic import BaseModel
 import torch
 import logging
 import os
+
+# Hugging Face Hub
 from huggingface_hub import login
 
-# LangChain imports (modern ≥1.0)
+# LangChain
 from langchain.llms.huggingface_pipeline import HuggingFacePipeline
 from langchain.chains import LLMChain
 from langchain.prompts.prompt import PromptTemplate
@@ -18,80 +20,75 @@ from langchain.memory import ConversationBufferMemory
 # Transformers pipeline
 from transformers import pipeline
 
-# ===============================================
+# =====================================================
 # CONFIGURATION
-# ===============================================
+# =====================================================
 API_SECRET = "techdisciplesai404"
 MODEL_NAME = "meta-llama/Llama-3.1-8B"
 DEVICE = 0 if torch.cuda.is_available() else -1
 
-# ===============================================
-# LOGGING SETUP
-# ===============================================
+# =====================================================
+# LOGGING
+# =====================================================
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger("TechDisciplesAI")
 
-# ===============================================
+# =====================================================
 # FASTAPI APP
-# ===============================================
-app = FastAPI(title="Tech Disciples AI", version="3.0")
-
-# ===============================================
-# LOGIN TO HUGGINGFACE HUB
-# ===============================================
-hf_token = os.getenv("HUGGINGFACEHUB_API_TOKEN")
-if hf_token:
-    try:
-        login(token=hf_token)
-        logger.info("✅ Logged into Hugging Face Hub successfully.")
-    except Exception as e:
-        logger.error(f"⚠️ Hugging Face login failed: {e}")
-else:
-    logger.warning("⚠️ No HUGGINGFACEHUB_API_TOKEN found in environment.")
+# =====================================================
+app = FastAPI(title="Tech Disciples AI", version="3.1")
+
+# =====================================================
+# MODEL LOAD
+# =====================================================
+llm = None
 
-# ===============================================
-# LOAD MODEL USING PIPELINE + LANGCHAIN
-# ===============================================
 try:
     logger.info(f"🚀 Loading model: {MODEL_NAME}")
 
+    hf_token = os.getenv("HUGGINGFACEHUB_API_TOKEN")
+    if hf_token:
+        login(token=hf_token)
+        logger.info("🔐 Hugging Face authentication successful.")
+    else:
+        logger.warning("⚠️ HUGGINGFACEHUB_API_TOKEN not found — gated models may fail.")
+
+    # Load text generation pipeline
     hf_pipeline = pipeline(
         "text-generation",
         model=MODEL_NAME,
         device=DEVICE,
         max_new_tokens=1024,
         temperature=0.4,
-        do_sample=True,
         top_p=0.9,
-        repetition_penalty=1.2,
+        repetition_penalty=1.15,
+        do_sample=True,
+        use_auth_token=True
     )
 
     llm = HuggingFacePipeline(pipeline=hf_pipeline)
-    logger.info("✅ Model loaded successfully.")
+    logger.info("✅ Model loaded successfully (Llama 3.1 - 8B).")
 
 except Exception as e:
-    logger.error(f"❌ Failed to load model: {e}")
+    logger.error(f"❌ Model load failed: {e}")
     llm = None
 
-# ===============================================
-# MEMORY SYSTEM
-# ===============================================
+# =====================================================
+# MEMORY + PROMPT
+# =====================================================
 memory = ConversationBufferMemory(memory_key="conversation_history")
 
-# ===============================================
-# PROMPT TEMPLATE
-# ===============================================
 prompt_template = """
-You are Tech Disciples AI — a spiritually aware, friendly, pastor-like talk buddy.
-You respond warmly, naturally, and thoughtfully like a caring church member.
-Always provide a clear, detailed answer with biblical insights or Bible verses.
-Do not give vague responses. If a question is not related to Christianity or the Bible, politely inform the user.
+You are Tech Disciples AI — a warm, spiritual, and knowledgeable conversational AI built
+to give Biblical guidance and Christian-based reflections. You speak with empathy, wisdom,
+and natural tone — never robotic. Always connect your points to scripture or Christian principles
+when relevant.
 
 Conversation so far:
 {conversation_history}
 
 User: {query}
-Tech Disciples AI (respond fully with examples, guidance, or Bible references):
+Tech Disciples AI (respond with warmth, depth, and Biblical understanding):
 """
 
 prompt = PromptTemplate(
@@ -99,41 +96,36 @@ prompt = PromptTemplate(
     input_variables=["conversation_history", "query"]
 )
 
-# ===============================================
-# LLM CHAIN (with memory)
-# ===============================================
-chain = LLMChain(
-    prompt=prompt,
-    llm=llm,
-    memory=memory
-)
+if llm:
+    chain = LLMChain(prompt=prompt, llm=llm, memory=memory)
+else:
+    chain = None
 
-# ===============================================
+# =====================================================
 # REQUEST MODEL
-# ===============================================
+# =====================================================
 class QueryInput(BaseModel):
     query: str
     session_id: str | None = "default"
 
-# ===============================================
+# =====================================================
 # ROUTES
-# ===============================================
+# =====================================================
 @app.get("/")
 async def root():
-    return {"message": "✅ Tech Disciples AI is running."}
+    return {"message": "✅ Tech Disciples AI (Llama 3.1) is running."}
 
 @app.post("/ai-chat")
 async def ai_chat(data: QueryInput, x_api_key: str = Header(None)):
     if x_api_key != API_SECRET:
         raise HTTPException(status_code=403, detail="Forbidden: Invalid API key")
 
-    if not llm:
-        raise HTTPException(status_code=500, detail="Model not initialized")
+    if not chain:
+        raise HTTPException(status_code=500, detail="Model not initialized or failed to load")
 
     try:
         response = chain.run(query=data.query.strip())
         return {"reply": response.strip()}
     except Exception as e:
-        logger.error(f"⚠️ Model error: {e}")
+        logger.error(f"⚠️ Error generating response: {e}")
         raise HTTPException(status_code=500, detail="Model failed to respond")
-