Updated

main.py

@@ -1,135 +1,81 @@
-# ==============================================================
-# Tech Disciples AI Backend — Free-Response Edition (Flan-T5 Fixed)
-# ==============================================================
-
-import os
-import logging
-import torch
-from fastapi import FastAPI, Header, HTTPException
-from fastapi.responses import JSONResponse
+from fastapi import FastAPI, HTTPException, Header
 from pydantic import BaseModel
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
-
-# --------------------------------------------------------------
-# Logging Setup
-# --------------------------------------------------------------
-logging.basicConfig(
-    level=logging.INFO,
-    format="%(asctime)s [%(levelname)s] %(message)s"
-)
-logger = logging.getLogger("Tech Disciples AI")
-
-# --------------------------------------------------------------
-# FastAPI App
-# --------------------------------------------------------------
-app = FastAPI(title="Tech Disciples AI")
-
-@app.get("/")
-async def root():
-    return {"status": "✅ Tech Disciples AI Backend is active and ready."}
-
-# --------------------------------------------------------------
-# Authentication
-# --------------------------------------------------------------
-PROJECT_API_KEY = os.getenv("PROJECT_API_KEY", "techdisciplesai404")
-
-def check_auth(authorization: str | None):
-    if not PROJECT_API_KEY:
-        return
-    if not authorization or not authorization.startswith("Bearer "):
-        raise HTTPException(status_code=401, detail="Missing bearer token")
-    token = authorization.split(" ", 1)[1]
-    if token != PROJECT_API_KEY:
-        raise HTTPException(status_code=403, detail="Invalid token")
-
-# --------------------------------------------------------------
-# Error Handler
-# --------------------------------------------------------------
-@app.exception_handler(Exception)
-async def global_exception_handler(request, exc):
-    logger.exception("Unhandled error:")
-    return JSONResponse(status_code=500, content={"error": str(exc)})
-
-# --------------------------------------------------------------
-# Request Model
-# --------------------------------------------------------------
-class ChatRequest(BaseModel):
-    query: str
-
-# --------------------------------------------------------------
-# System Prompt
-# --------------------------------------------------------------
-SYSTEM_TEMPLATE = """You are Tech Disciples AI — a spiritually aware, intelligent, and kind conversational assistant.
-You respond clearly and truthfully, offering thoughtful, biblically grounded, and intelligent answers.
-Avoid debates or judgmental tones, and always reply in full sentences with understanding and grace.
-"""
+from transformers import pipeline
+from langchain.llms import HuggingFacePipeline
+from langchain.chains import LLMChain
+from langchain.prompts import PromptTemplate
+import torch
+import logging
 
-# --------------------------------------------------------------
-# Model Load
-# --------------------------------------------------------------
+# ===== CONFIG =====
+API_SECRET = "techdisciplesai404"
 MODEL_NAME = "google/flan-t5-large"
-HF_TOKEN = os.getenv("HUGGINGFACEHUB_API_TOKEN")
+DEVICE = 0 if torch.cuda.is_available() else -1
 
-device = 0 if torch.cuda.is_available() else -1
-logger.info(f"🧠 Using device: {'GPU' if device == 0 else 'CPU'}")
+# ===== LOGGING =====
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger("TechDisciplesAI")
 
-chat_pipe = None
+# ===== INITIALIZE APP =====
+app = FastAPI(title="TechDisciples AI", version="2.0")
+
+# ===== MODEL SETUP =====
 try:
     logger.info(f"🚀 Loading model: {MODEL_NAME}")
-    tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, token=HF_TOKEN if HF_TOKEN else None)
-    model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_NAME, token=HF_TOKEN if HF_TOKEN else None)
-
-    chat_pipe = pipeline(
+    pipe = pipeline(
         "text2text-generation",
-        model=model,
-        tokenizer=tokenizer,
-        device=device
+        model=MODEL_NAME,
+        device=DEVICE,
+        max_new_tokens=256,
+        temperature=0.3,
+        do_sample=True
     )
-    logger.info("✅ Model pipeline initialized successfully.")
+
+    llm = HuggingFacePipeline(pipeline=pipe)
+    logger.info("✅ Model loaded successfully.")
 except Exception as e:
-    chat_pipe = None
-    logger.error(f"❌ Failed to initialize model pipeline: {e}")
+    logger.error(f"❌ Failed to load model: {e}")
+    llm = None
 
-# --------------------------------------------------------------
-# Helper: Generate Reply
-# --------------------------------------------------------------
-def generate_reply(pipe, user_input: str) -> str:
-    if not pipe:
-        return "⚠️ Model pipeline not initialized."
+# ===== PROMPT TEMPLATE =====
+prompt_template = """
+You are a Christian conversational AI named TechDisciples AI. 
+Answer the question naturally and clearly, providing biblical or inspirational insight where possible.
 
-    prompt = f"{SYSTEM_TEMPLATE}\nUser: {user_input}\nTech Disciples AI:"
+Question: {query}
+
+Response:
+"""
+
+prompt = PromptTemplate(template=prompt_template, input_variables=["query"])
+chain = LLMChain(prompt=prompt, llm=llm)
+
+# ===== REQUEST MODEL =====
+class QueryInput(BaseModel):
+    query: str
+
+
+# ===== ROUTES =====
+@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 llm is None:
+        raise HTTPException(status_code=500, detail="Model not initialized")
+
+    user_query = data.query.strip()
+    if not user_query:
+        raise HTTPException(status_code=400, detail="Query cannot be empty")
 
     try:
-        result = pipe(
-            prompt,
-            do_sample=True,
-            temperature=0.3,
-            top_p=0.9,
-            repetition_penalty=1.05
-        )
-
-        if not result or "generated_text" not in result[0]:
-            return "⚠️ Model returned no content."
-
-        text = result[0]["generated_text"]
-        if text.startswith(prompt):
-            text = text[len(prompt):]
-        text = text.replace("User:", "").replace("Tech Disciples AI:", "").strip()
-
-        return text if text else "⚠️ No valid reply generated."
+        response = chain.run(query=user_query)
+        return {"reply": response.strip(), "tone_used": "neutral"}
     except Exception as e:
-        logger.exception("Error generating reply:")
-        return f"⚠️ Model error: {e}"
+        logger.error(f"⚠️ Generation error: {e}")
+        raise HTTPException(status_code=500, detail="Model failed to respond")
 
-# --------------------------------------------------------------
-# Endpoint
-# --------------------------------------------------------------
-@app.post("/ai-chat")
-async def ai_chat(req: ChatRequest, authorization: str | None = Header(None)):
-    check_auth(authorization)
-    reply = generate_reply(chat_pipe, req.query)
-    return {"reply": reply}
-
-# ==============================================================
-# END OF FILE
-# ==============================================================
+
+@app.get("/")
+async def root():
+    return {"message": "✅ TechDisciples AI (LangChain) is running."}