Update app.py

app.py

@@ -3,147 +3,50 @@ from pydantic import BaseModel
 import uvicorn
 import torch
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-from huggingface_hub import login
-import os
 import time
 from fastapi.middleware.cors import CORSMiddleware
 
-# Get Hugging Face token from environment variables
-HUGGINGFACE_TOKEN = os.environ.get("HUGGINGFACE_TOKEN", "")
-
-if HUGGINGFACE_TOKEN:
-    try:
-        login(token=HUGGINGFACE_TOKEN)
-        print("✅ Successfully connected to Hugging Face")
-    except Exception as e:
-        print(f"❌ Hugging Face login failed: {e}")
-
-# Personal and Company Information
-PERSONAL_INFO = {
-    "name": "Adedoyin Ifeoluwa James",
-    "role": "Entrepreneur, Founder & CEO of YAH Tech",
-    "goals": [
-        "Build profitable systems that matter",
-        "Reshaping the economical world",
-        "Use software development to create flexibility and contribute to economic growth"
-    ]
-}
-
-COMPANY_INFO = {
-    "name": "YAH Tech",
-    "type": "venture studio / app development company focused on solving problems with futuristic solutions",
-    "purpose": "Build and launch technology-driven ventures that generate profit and societal value",
-    "primary_activity": "App development and creation of scalable business systems",
-    "philosophy": "Learn, understand, create, and evaluate",
-    "stage": "Growth and development, focused on building sustainable processes and systems"
-}
+# Initialize FastAPI app
+app = FastAPI(
+    title="YAH Tech AI API",
+    description="AI Assistant API for testing",
+    version="1.0.0"
+)
 
-# Knowledge base for the AI
-KNOWLEDGE_BASE = {
-    "personal": {
-        "who are you": f"I am YAH Bot, the personal AI assistant for {PERSONAL_INFO['name']}. I help answer questions about him and his company YAH Tech.",
-        "what are your goals": f"My purpose is to assist with information about {PERSONAL_INFO['name']} and YAH Tech. His goals include: {', '.join(PERSONAL_INFO['goals'])}",
-        "what do you do": f"I provide information about {PERSONAL_INFO['name']} and his work at YAH Tech.",
-        "tell me about yourself": f"I'm YAH Bot, an AI assistant created to help people learn about {PERSONAL_INFO['name']} and his technology ventures.",
-        "background": f"{PERSONAL_INFO['name']} is {PERSONAL_INFO['role']} focused on building impactful technology systems.",
-        "experience": f"As {PERSONAL_INFO['role']}, {PERSONAL_INFO['name']} has focused on building YAH Tech into a successful venture studio.",
-    },
-    "company": {
-        "what is yah tech": f"{COMPANY_INFO['name']} is a {COMPANY_INFO['type']} that {COMPANY_INFO['purpose'].lower()}.",
-        "what does yah tech do": f"We specialize in {COMPANY_INFO['primary_activity'].lower()}. {COMPANY_INFO['purpose']}.",
-        "company philosophy": f"Our philosophy is: '{COMPANY_INFO['philosophy']}'",
-        "company stage": f"We're currently in the {COMPANY_INFO['stage']} phase.",
-        "venture studio": "As a venture studio, we build complete businesses with scalable systems and futuristic solutions.",
-        "services": f"{COMPANY_INFO['name']} offers app development, venture building, business system design, technology solutions, and scalable platform development.",
-        "mission": f"Our mission at {COMPANY_INFO['name']} is to {COMPANY_INFO['purpose'].lower()}.",
-    }
-}
+# Add CORS middleware
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
 
 class YAHBot:
     def __init__(self):
-        # Changed: Now loading from YOUR private repo
-        self.model_name = "Adedoyinjames/YAH-Tech-Chat-Bot"
+        # ✅ Changed to load from your HF repo instead of direct model name
+        self.repo_id = "Adedoyinjames/brain-ai"  # Your HF repo
         self.tokenizer = None
         self.model = None
         self._load_model()
     
     def _load_model(self):
-        """Load the Hugging Face model from YOUR repo"""
+        """Load the model from your Hugging Face repo"""
         try:
-            print(f"🔄 Loading YAH Tech AI model from {self.model_name}...")
-            
-            # Use token from environment for private repo access
-            token = os.environ.get("HUGGINGFACE_TOKEN", "")
-            
-            if token:
-                # Load with authentication for private repo
-                self.tokenizer = AutoTokenizer.from_pretrained(
-                    self.model_name,
-                    use_auth_token=token
-                )
-                self.model = AutoModelForSeq2SeqLM.from_pretrained(
-                    self.model_name,
-                    use_auth_token=token
-                )
-            else:
-                # Fallback: try without auth (will work if repo becomes public)
-                self.tokenizer = AutoTokenizer.from_pretrained(self.model_name)
-                self.model = AutoModelForSeq2SeqLM.from_pretrained(self.model_name)
-            
-            print("✅ YAH Tech AI model loaded successfully from your repo!")
-            
+            print(f"🔄 Loading AI model from {self.repo_id}...")
+            self.tokenizer = AutoTokenizer.from_pretrained(self.repo_id)
+            self.model = AutoModelForSeq2SeqLM.from_pretrained(self.repo_id)
+            print("✅ AI model loaded successfully from HF repo!")
         except Exception as e:
-            print(f"❌ Failed to load AI model from your repo: {e}")
-            print("🔄 Falling back to default model...")
-            # Fallback to public model if your repo fails
-            try:
-                self.model_name = "google/flan-t5-base"
-                self.tokenizer = AutoTokenizer.from_pretrained(self.model_name)
-                self.model = AutoModelForSeq2SeqLM.from_pretrained(self.model_name)
-                print("✅ Fallback model loaded successfully!")
-            except Exception as fallback_error:
-                print(f"❌ Fallback model also failed: {fallback_error}")
-                self.model = None
-                self.tokenizer = None
-    
-    def _get_knowledge_response(self, user_input):
-        """Check if the input matches any knowledge base entries"""
-        user_input_lower = user_input.lower()
-        
-        # Check for specific brand-related queries
-        if any(word in user_input_lower for word in ["adedoyin", "ifeoluwa", "james"]):
-            return KNOWLEDGE_BASE["personal"]["who are you"]
-        
-        if any(word in user_input_lower for word in ["yah tech", "your company", "venture studio"]):
-            return KNOWLEDGE_BASE["company"]["what is yah tech"]
-        
-        # Check knowledge base
-        for category in KNOWLEDGE_BASE.values():
-            for key, response in category.items():
-                if key in user_input_lower:
-                    return response
-        
-        return None
-    
-    def _create_smart_prompt(self, user_input):
-        """Create a much better prompt that separates brand info from general knowledge"""
-        prompt = f"""You are a helpful AI assistant. Answer the following question accurately and helpfully.
-Question: {user_input}
-Answer: """
-        return prompt
+            print(f"❌ Failed to load AI model from repo: {e}")
+            self.model = None
+            self.tokenizer = None
     
     def generate_response(self, user_input):
-        """Generate response using knowledge base or AI model"""
-        # First check knowledge base for brand-specific queries
-        knowledge_response = self._get_knowledge_response(user_input)
-        if knowledge_response:
-            return knowledge_response
-        
-        # Use AI model for general knowledge questions
+        """Generate response using AI model"""
         if self.model and self.tokenizer:
             try:
-                # Create clean prompt without brand bias for general questions
-                prompt = self._create_smart_prompt(user_input)
+                prompt = f"Question: {user_input}\nAnswer: "
                 
                 # Tokenize
                 inputs = self.tokenizer(
@@ -163,7 +66,6 @@ Answer: """
                         temperature=0.7,
                         do_sample=True,
                         pad_token_id=self.tokenizer.pad_token_id,
-                        repetition_penalty=1.2
                     )
                 
                 response = self.tokenizer.decode(outputs[0], skip_special_tokens=True)
@@ -171,25 +73,9 @@ Answer: """
                 
             except Exception as e:
                 print(f"Model error: {str(e)}")
-                return "I apologize, but I'm having trouble processing your question right now. Please try again."
+                return "I apologize, but I'm having trouble processing your question right now."
         
-        return "I'm currently unavailable. Please check back later."
-
-# Initialize FastAPI app
-app = FastAPI(
-    title="YAH Tech AI API",
-    description=f"AI Assistant API for {PERSONAL_INFO['name']} - Personal assistant and company information",
-    version="1.0.0"
-)
-
-# Add CORS middleware
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],
-    allow_credentials=True,
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
+        return "AI model is not available."
 
 # Initialize the bot globally
 yah_bot = YAHBot()
@@ -197,7 +83,6 @@ yah_bot = YAHBot()
 # Request/Response models
 class ChatRequest(BaseModel):
     message: str
-    user_id: str = None
 
 class ChatResponse(BaseModel):
     response: str
@@ -209,22 +94,16 @@ class HealthResponse(BaseModel):
     service: str
     timestamp: float
 
-class InfoResponse(BaseModel):
-    personal_info: dict
-    company_info: dict
-    model: str
-    status: str
-
 # API Endpoints
 @app.get("/")
 async def root():
     return {
-        "message": f"YAH Tech AI API is running - Assistant for {PERSONAL_INFO['name']}",
+        "message": "YAH Tech AI API is running",
         "status": "active",
+        "model_repo": yah_bot.repo_id,  # Show which repo is being used
         "endpoints": {
             "chat": "POST /api/chat",
-            "health": "GET /api/health",
-            "info": "GET /api/info"
+            "health": "GET /api/health"
         }
     }
 
@@ -252,18 +131,6 @@ async def health_check():
         timestamp=time.time()
     )
 
-@app.get("/api/info", response_model=InfoResponse)
-async def get_info():
-    """
-    Get information about the AI assistant and company
-    """
-    return InfoResponse(
-        personal_info=PERSONAL_INFO,
-        company_info=COMPANY_INFO,
-        model=yah_bot.model_name,
-        status="active"
-    )
-
 # For Hugging Face Spaces
 def get_app():
     return app