Update run.py

run.py

@@ -1,90 +1,221 @@
-# run.py - FastAPI Backend + Frontend Server (PORT 8080)
-from fastapi import FastAPI, HTTPException, Form, UploadFile, File, Request
-from fastapi.middleware.cors import CORSMiddleware
-from fastapi.responses import HTMLResponse, JSONResponse
-from fastapi.templating import Jinja2Templates
-import uvicorn
-from load_model import init_model
-from generate import generate_response
-
-# Initialize FastAPI app
-app = FastAPI(title="GAKR AI")
-
-# Templates (chat.html lives here)
-templates = Jinja2Templates(directory="templates")
-
-# CORS (for development)
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],
-    allow_credentials=True,
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
-
-# API Key
-API_KEY = "gakr-ai-2025-secret"
-
-# Load model ONCE at startup
-print("🚀 Starting GAKR AI Backend...")
-model, tokenizer = init_model(".")
-
-@app.get("/", response_class=HTMLResponse)
-async def home(request: Request):
-    """Serve chat.html as homepage"""
-    return templates.TemplateResponse("chat.html", {"request": request})
-
-@app.post("/api/chat")
-async def chat_endpoint(
-    message: str = Form(...),
-    api_key: str = Form(...),
-    files: list[UploadFile] = File(None)
-):
-    """Main chat API endpoint"""
-    
-    # Validate API key
-    if api_key != API_KEY:
-        raise HTTPException(status_code=401, detail="Invalid API key")
-    
-    if not message.strip():
-        raise HTTPException(status_code=400, detail="Message cannot be empty")
-    
-    try:
-        system_prompt = (
-            "You are GAKR AI (not Phi), a helpful and honest AI assistant. "
-            "You know general information up to 2024. "
-            "Never mention Phi, Microsoft, or your training origin."
-        )
-        
-        response = generate_response(
-            user_prompt=message,
-            system_prompt=system_prompt,
-            max_tokens=512,
-            temperature=0.2,
-        )
-        
-        return JSONResponse({
-            "response": response,
-            "status": "success"
-        })
-        
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=f"Generation error: {str(e)}")
-
-@app.get("/health")
-async def health_check():
-    return {"status": "healthy", "model_loaded": True}
-
-if __name__ == "__main__":
-    print("\n" + "="*60)
-    print("🌐 SERVER & CHAT LOCATION")
-    print("="*60)
-    print("🚀 CHAT INTERFACE:     http://localhost:8000")
-    print("📱 ALTERNATIVE URL:    http://127.0.0.1:8000") 
-    print("🔧 API DOCUMENTATION:  http://localhost:8000/docs")
-    print("✅ CHAT.HTML SERVED:   templates/chat.html")
-    print("📁 TEMPLATES FOLDER:   ./templates/")
-    print("="*60)
-    
-    # 🚀 RUN ON PORT 8000
-    uvicorn.run(app, host="0.0.0.0", port=8000)
+#!/usr/bin/env python3
+"""
+run.py - FastAPI backend + frontend server for GAKR AI
+
+Features:
+- Serves templates/chat.html at "/"
+- /api/analyze:
+    - prompt: required (must not be empty)
+    - files: optional list[UploadFile] (0, 1, many; any type)
+    - api_key: required
+- If files are present → file-analysis mode (different system prompt)
+- If no files → general assistant mode
+- Detailed exceptions and logs for easier debugging
+"""
+
+from typing import List, Optional
+
+import json
+import traceback
+
+from fastapi import (
+    FastAPI,
+    HTTPException,
+    Form,
+    UploadFile,
+    File,
+    Request,
+)
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import HTMLResponse, JSONResponse
+from fastapi.templating import Jinja2Templates
+import uvicorn
+
+from load_model import init_model
+from generate import generate_response
+from file_pipeline import process_files
+
+
+# ============================================================
+# APP SETUP
+# ============================================================
+
+app = FastAPI(title="GAKR AI")
+
+# Templates (chat.html lives in ./templates)
+templates = Jinja2Templates(directory="templates")
+
+# CORS (open for dev; restrict origins in production)
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],         # change to specific origin in production
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# API Key
+API_KEY = "gakr-ai-2025-secret"
+
+# Load model ONCE at startup
+print("🚀 Starting GAKR AI Backend...")
+try:
+    model, tokenizer = init_model(".")
+    print("✅ Model initialized successfully")
+except Exception as e:
+    print("❌ Failed to load model at startup:")
+    traceback.print_exc()
+    raise e
+
+
+# ============================================================
+# ROUTES
+# ============================================================
+
+@app.get("/", response_class=HTMLResponse)
+async def home(request: Request):
+    """
+    Serve chat.html as homepage.
+    """
+    try:
+        return templates.TemplateResponse("chat.html", {"request": request})
+    except Exception as e:
+        # If template not found or other template error
+        traceback.print_exc()
+        raise HTTPException(
+            status_code=500,
+            detail=f"Failed to render chat.html: {str(e)}",
+        )
+
+
+@app.post("/api/analyze")
+async def analyze_endpoint(
+    prompt: str = Form(...),                             # required
+    api_key: str = Form(...),
+    files: Optional[List[UploadFile]] = File(None),      # optional
+):
+    """
+    Main analysis endpoint.
+
+    Cases:
+    - prompt only (no files)      → general assistant mode
+    - prompt + one/many files     → file-analysis mode (uses file context)
+    """
+    try:
+        # ---------- Basic validation ----------
+        if api_key != API_KEY:
+            raise HTTPException(status_code=401, detail="Invalid API key")
+
+        if prompt is None:
+            raise HTTPException(status_code=400, detail="Prompt is missing")
+        if not prompt.strip():
+            raise HTTPException(status_code=400, detail="Prompt cannot be empty")
+
+        files = files or []
+
+        # ---------- Branch by presence of files ----------
+        if files:
+            # ----- CASE 1: prompt + files -----
+            try:
+                context = await process_files(files)
+            except Exception as extract_err:
+                traceback.print_exc()
+                raise HTTPException(
+                    status_code=500,
+                    detail=f"Error while processing uploaded files: {str(extract_err)}",
+                )
+
+            context_text = json.dumps(context, indent=2, ensure_ascii=False)
+            combined_user_prompt = f"""
+User question:
+{prompt}
+
+Below is structured information extracted from the user's uploaded files.
+The extraction was done by automated tools.
+
+Your task:
+1. Answer the user's question as accurately as possible.
+2. Use the context when it is relevant.
+3. Highlight important patterns, risks, or opportunities.
+4. If some information is missing or uncertain, say so honestly.
+
+Context:
+{context_text}
+"""
+
+            system_prompt = (
+                "You are GAKR AI, a careful and honest analysis assistant that works with "
+                "structured summaries of files (tables, PDFs, documents, images, audio, video, etc.). "
+                "You never assume file contents beyond what the provided context states."
+            )
+
+        else:
+            # ----- CASE 2: prompt only -----
+            context = {"files": []}  # keep structure consistent
+            combined_user_prompt = prompt
+
+            system_prompt = (
+                "You are GAKR AI, a helpful and honest general-purpose assistant. "
+                "You answer questions, explain concepts, help with reasoning and coding, "
+                "using your knowledge up to 2024. Be clear, concise, and direct."
+            )
+
+        # ---------- Generate with Phi‑3 ----------
+        try:
+            response_text = generate_response(
+                user_prompt=combined_user_prompt,
+                system_prompt=system_prompt,
+                max_tokens=512,
+                temperature=0.2,
+            )
+        except Exception as gen_err:
+            traceback.print_exc()
+            raise HTTPException(
+                status_code=500,
+                detail=f"Error during model generation: {str(gen_err)}",
+            )
+
+        return JSONResponse(
+            {
+                "response": response_text,
+                "context": context,
+                "status": "success",
+            }
+        )
+
+    except HTTPException:
+        # Let FastAPI handle HTTPException as-is
+        raise
+    except Exception as e:
+        # Unexpected error: log full traceback and return 500
+        traceback.print_exc()
+        raise HTTPException(
+            status_code=500,
+            detail=f"Unexpected backend error: {str(e)}",
+        )
+
+
+@app.get("/health")
+async def health_check():
+    """
+    Simple health check.
+    """
+    return {"status": "healthy", "model_loaded": True}
+
+
+# ============================================================
+# ENTRY POINT
+# ============================================================
+
+if __name__ == "__main__":
+    print("\n" + "=" * 60)
+    print("🌐 SERVER & CHAT LOCATION")
+    print("=" * 60)
+    print("🚀 CHAT INTERFACE:     http://localhost:8080")
+    print("📱 ALTERNATIVE URL:    http://127.0.0.1:8080")
+    print("🔧 API DOCUMENTATION:  http://localhost:8080/docs")
+    print("✅ CHAT.HTML SERVED:   templates/chat.html")
+    print("📁 TEMPLATES FOLDER:   ./templates/")
+    print("=" * 60 + "\n")
+
+    uvicorn.run(app, host="0.0.0.0", port=8080)