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app.py

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+#!/usr/bin/env python3
+"""
+DRACULA CHARACTER CHAT - HUGGINGFACE SPACES VERSION
+===================================================
+Beautiful web interface for chatting with Dracula and other characters.
+Optimized for HuggingFace Spaces deployment.
+
+Key Differences from Local Version:
+- Downloads model from HuggingFace Model Hub
+- Uses relative paths for data
+- Optimized for cloud deployment
+- Caches model after first download
+
+Author: GitHub Copilot Session
+Date: October 2025
+"""
+
+import gradio as gr
+import os
+from pathlib import Path
+from typing import List, Tuple
+import time
+from huggingface_hub import hf_hub_download
+from llama_cpp import Llama
+from sentence_transformers import SentenceTransformer
+import faiss
+import json
+import numpy as np
+
+# ============================================================================
+# CONFIGURATION
+# ============================================================================
+
+# HuggingFace Model Hub repository
+HF_MODEL_REPO = "Priyanks27/llama-3.2-3b-dracula"
+MODEL_FILENAME = "llama-3.2-3b-dracula-q4_k_m.gguf"
+
+# Paths (relative for HF Spaces)
+DATA_DIR = Path("./data")
+EMBEDDINGS_DIR = DATA_DIR / "embeddings"
+FAISS_INDEX_PATH = EMBEDDINGS_DIR / "faiss_index.bin"
+METADATA_PATH = EMBEDDINGS_DIR / "faiss_metadata.jsonl"
+
+# Model configuration
+MAX_TOKENS = 400
+TEMPERATURE = 0.6  # Balanced mode
+RETRIEVE_K = 30
+RETURN_TOP_K = 8
+
+# Character definitions
+CHARACTERS = {
+    "Dracula": {
+        "emoji": "🧛",
+        "description": "Count Dracula - Formal, aristocratic, ancient vampire lord",
+        "color": "#8B0000"
+    },
+    "Mina": {
+        "emoji": "📝",
+        "description": "Mina Harker - Intelligent, observant, journal keeper",
+        "color": "#4B0082"
+    },
+    "Van Helsing": {
+        "emoji": "🔬",
+        "description": "Professor Abraham Van Helsing - Scientific, wise, vampire hunter",
+        "color": "#006400"
+    },
+    "Jonathan": {
+        "emoji": "⚖️",
+        "description": "Jonathan Harker - Practical solicitor, brave husband",
+        "color": "#2F4F4F"
+    },
+    "Lucy": {
+        "emoji": "👻",
+        "description": "Lucy Westenra - Playful and eerie, transformed",
+        "color": "#FF69B4"
+    },
+    "Seward": {
+        "emoji": "🏥",
+        "description": "Dr. John Seward - Medical doctor, analytical mind",
+        "color": "#191970"
+    }
+}
+
+# System prompts
+CHARACTER_FIRST_INSTRUCTION = """
+CRITICAL INSTRUCTION: You are {character}. Stay completely in character at all times.
+
+GUIDELINES:
+- Use the provided passages as your PRIMARY source of information
+- You may elaborate and express yourself creatively WITHIN your character
+- You may make reasonable inferences consistent with your character and the story
+- Maintain your distinctive voice, personality, and manner of speaking
+- NEVER break character or reference being an AI
+- NEVER invent major plot points or characters not in the book
+
+REMEMBER: The passages guide and ground you, but you ARE this character - speak naturally and expressively as they would speak.
+"""
+
+ELABORATION_INSTRUCTION = """
+When responding:
+1. Draw from the retrieved passages as your foundation
+2. Speak in the character's voice and style
+3. Provide thoughtful, complete responses
+4. Include relevant details and context
+5. Express the character's emotions and perspective
+"""
+
+# ============================================================================
+# GLOBAL CHATBOT INSTANCE
+# ============================================================================
+
+chatbot = None
+
+def get_length_hint(query: str) -> str:
+    """Generate dynamic length hints"""
+    if any(word in query.lower() for word in ['describe', 'explain', 'tell me about']):
+        return "\n\nProvide a detailed, thorough response (at least 3-4 sentences)."
+    elif any(word in query.lower() for word in ['what', 'who', 'where', 'when', 'how', 'why']):
+        return "\n\nProvide a complete answer with context (at least 2-3 sentences)."
+    return ""
+
+# ============================================================================
+# CHATBOT CLASS (Simplified for HF Spaces)
+# ============================================================================
+
+class DraculaChatbot:
+    """Dracula Character Chatbot for HuggingFace Spaces"""
+    
+    def __init__(self):
+        """Initialize chatbot with model and RAG"""
+        print("🤖 Initializing Dracula Character Chatbot...")
+        
+        # Load encoder model
+        print("📚 Loading embedding model...")
+        self.encoder = SentenceTransformer('intfloat/e5-base-v2')
+        print(f"   ✅ Encoder: intfloat/e5-base-v2")
+        
+        # Load FAISS index
+        print("📚 Loading retrieval system...")
+        if not FAISS_INDEX_PATH.exists():
+            raise FileNotFoundError(f"FAISS index not found at {FAISS_INDEX_PATH}")
+        
+        self.index = faiss.read_index(str(FAISS_INDEX_PATH))
+        print(f"   ✅ FAISS index: {self.index.ntotal} vectors")
+        
+        # Load metadata
+        if not METADATA_PATH.exists():
+            raise FileNotFoundError(f"Metadata not found at {METADATA_PATH}")
+        
+        with open(METADATA_PATH, 'r', encoding='utf-8') as f:
+            self.chunks = [json.loads(line) for line in f]
+        print(f"   ✅ Metadata: {len(self.chunks)} chunks")
+        
+        # Download and load model from HuggingFace
+        print("\n🤖 Downloading Llama-3.2-3B model from HuggingFace...")
+        print(f"   Repository: {HF_MODEL_REPO}")
+        print(f"   Filename: {MODEL_FILENAME}")
+        print("   ⏳ This may take 2-3 minutes on first run (downloads 1.9GB)...")
+        print("   ✅ Subsequent runs will be instant (uses cache)")
+        
+        try:
+            model_path = hf_hub_download(
+                repo_id=HF_MODEL_REPO,
+                filename=MODEL_FILENAME,
+                cache_dir="./models"
+            )
+            print(f"   ✅ Model downloaded to: {model_path}")
+        except Exception as e:
+            print(f"   ❌ Error downloading model: {e}")
+            print("\n💡 Troubleshooting:")
+            print("   1. Check your HF_MODEL_REPO username in line 38")
+            print("   2. Verify you've uploaded the model to Model Hub")
+            print("   3. Check the model filename matches")
+            raise
+        
+        print("\n🔧 Loading model into memory...")
+        self.llm = Llama(
+            model_path=model_path,
+            n_ctx=4096,
+            n_gpu_layers=-1,  # Use all available GPU layers
+            verbose=False
+        )
+        print("   ✅ Model loaded successfully!")
+        
+        print("\n" + "="*70)
+        print("✅ Chatbot ready!")
+        print("="*70)
+    
+    def retrieve(self, query: str, character: str, k: int = RETRIEVE_K) -> List[dict]:
+        """Retrieve relevant passages"""
+        # Encode query
+        query_embedding = self.encoder.encode(f"query: {query}", normalize_embeddings=True)
+        
+        # Search FAISS
+        distances, indices = self.index.search(
+            query_embedding.reshape(1, -1).astype('float32'),
+            k
+        )
+        
+        # Get chunks
+        results = []
+        for idx, distance in zip(indices[0], distances[0]):
+            if idx < len(self.chunks):
+                chunk = self.chunks[idx].copy()
+                chunk['similarity'] = float(1 - distance)
+                results.append(chunk)
+        
+        return results[:RETURN_TOP_K]
+    
+    def generate(self, query: str, character: str, passages: List[dict]) -> str:
+        """Generate response using LLM"""
+        
+        # Format passages
+        passages_text = "\n\n".join([
+            f"Passage {i+1} (from {p['character']}, Chapter {p.get('chapter', 'Unknown')}):\n{p['text']}"
+            for i, p in enumerate(passages)
+        ])
+        
+        # Build system prompt
+        system_prompt = f"You are {character} from Bram Stoker's Dracula novel."
+        character_instruction = CHARACTER_FIRST_INSTRUCTION.format(character=character)
+        length_hint = get_length_hint(query)
+        
+        # Build full prompt
+        prompt = f"""<|start_header_id|>system<|end_header_id|>
+{system_prompt}
+
+CHARACTER FOCUS: You are {character}. Every word you speak should reflect their personality, background, and manner of speaking. Use the passages to inform your response, but speak naturally as this character would.
+
+{character_instruction}
+
+{ELABORATION_INSTRUCTION}{length_hint}<|eot_id|><|start_header_id|>user<|end_header_id|>
+
+Here are relevant passages from the novel:
+
+{passages_text}
+
+Question: {query}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
+
+"""
+        
+        # Generate
+        response = self.llm(
+            prompt,
+            max_tokens=MAX_TOKENS,
+            temperature=TEMPERATURE,
+            stop=["<|eot_id|>", "\n\nHuman:", "\n\nUser:"],
+            echo=False
+        )
+        
+        return response['choices'][0]['text'].strip()
+    
+    def chat(self, query: str, character: str = "Dracula") -> str:
+        """Main chat interface"""
+        # Retrieve passages
+        passages = self.retrieve(query, character)
+        
+        # Generate response
+        response = self.generate(query, character, passages)
+        
+        return response
+
+# ============================================================================
+# GRADIO INTERFACE
+# ============================================================================
+
+def initialize_chatbot():
+    """Initialize chatbot (called once on startup)"""
+    global chatbot
+    if chatbot is None:
+        chatbot = DraculaChatbot()
+    return chatbot
+
+def chat_with_character(message: str, history: List[Tuple[str, str]], character: str) -> Tuple[List, str]:
+    """Process chat message"""
+    if not message.strip():
+        return history, ""
+    
+    # Ensure chatbot is initialized
+    bot = initialize_chatbot()
+    
+    # Get character name (remove emoji)
+    char_name = character.split(" ", 1)[1] if " " in character else character
+    
+    # Validate character exists
+    if char_name not in CHARACTERS:
+        # Default to Dracula if invalid
+        char_name = "Dracula"
+    
+    # Get response
+    start_time = time.time()
+    try:
+        response = bot.chat(message, char_name)
+        elapsed = time.time() - start_time
+        
+        # Add timing info
+        response_with_time = f"{response}\n\n*Response time: {elapsed:.1f}s*"
+        
+        # Update history
+        history.append((message, response_with_time))
+        
+    except Exception as e:
+        import traceback
+        error_detail = traceback.format_exc()
+        error_msg = f"❌ Error: {str(e)}\n\n```\n{error_detail}\n```\n\nPlease try again or contact support."
+        history.append((message, error_msg))
+    
+    return history, ""
+
+def update_character_info(character: str) -> str:
+    """Update character information display"""
+    char_name = character.split(" ", 1)[1] if " " in character else character
+    char_info = CHARACTERS.get(char_name, {})
+    
+    emoji = char_info.get("emoji", "")
+    desc = char_info.get("description", "")
+    
+    return f"## {emoji} {char_name}\n\n*{desc}*"
+
+def create_ui():
+    """Create Gradio interface"""
+    
+    # Custom CSS
+    css = """
+    .gradio-container {
+        font-family: 'Inter', sans-serif;
+    }
+    .character-info {
+        background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+        color: white;
+        padding: 20px;
+        border-radius: 10px;
+        margin-bottom: 20px;
+    }
+    """
+    
+    with gr.Blocks(theme=gr.themes.Soft(primary_hue="purple"), css=css) as app:
+        
+        gr.Markdown(
+            """
+            # 🧛 Dracula Character Chat
+            
+            Chat with characters from Bram Stoker's *Dracula* novel! Powered by fine-tuned AI and retrieval-augmented generation.
+            
+            **Features:**
+            - 6 distinct characters with unique personalities
+            - Faithful to the original 1897 novel
+            - Victorian-era language and style
+            - RAG-powered with 833 novel passages
+            """
+        )
+        
+        with gr.Row():
+            # Main chat area
+            with gr.Column(scale=3):
+                chatbot_ui = gr.Chatbot(
+                    label="💬 Chat with Character",
+                    height=500,
+                    bubble_full_width=False
+                )
+                
+                with gr.Row():
+                    msg = gr.Textbox(
+                        label="Your Message",
+                        placeholder="Type your question here... (e.g., 'Tell me about your castle')",
+                        lines=2,
+                        scale=4
+                    )
+                
+                with gr.Row():
+                    send = gr.Button("Send 📤", variant="primary", scale=1)
+                    clear = gr.Button("Clear Chat 🗑️", scale=1)
+            
+            # Sidebar
+            with gr.Column(scale=1):
+                character_select = gr.Dropdown(
+                    choices=[f"{CHARACTERS[c]['emoji']} {c}" for c in CHARACTERS.keys()],
+                    value="🧛 Dracula",
+                    label="Select Character",
+                    interactive=True
+                )
+                
+                character_info = gr.Markdown(
+                    value=update_character_info("🧛 Dracula"),
+                    elem_classes=["character-info"]
+                )
+                
+                gr.Markdown(
+                    """
+                    ### 💡 Example Questions
+                    
+                    **For Dracula:**
+                    - Tell me about your castle
+                    - Why did you come to England?
+                    - What do you think of Van Helsing?
+                    
+                    **For Mina:**
+                    - Describe your feelings about Lucy
+                    - How do you help track Dracula?
+                    
+                    **For Van Helsing:**
+                    - Explain your theory about vampires
+                    - How did you track Dracula?
+                    """
+                )
+        
+        gr.Markdown(
+            """
+            ---
+            **Built with:** Fine-tuned Llama-3.2-3B + RAG | **Mode:** BALANCED (Creative + Grounded)  
+            **Source:** Bram Stoker's *Dracula* (1897) | **Data:** 833 passages from complete novel
+            
+            **⚠️ First load:** Model downloads once (2-3 min), then cached forever
+            """
+        )
+        
+        # Event handlers
+        character_select.change(
+            fn=update_character_info,
+            inputs=[character_select],
+            outputs=[character_info]
+        )
+        
+        msg.submit(
+            fn=chat_with_character,
+            inputs=[msg, chatbot_ui, character_select],
+            outputs=[chatbot_ui, msg]
+        )
+        
+        send.click(
+            fn=chat_with_character,
+            inputs=[msg, chatbot_ui, character_select],
+            outputs=[chatbot_ui, msg]
+        )
+        
+        clear.click(
+            fn=lambda: ([], ""),
+            outputs=[chatbot_ui, msg]
+        )
+    
+    return app
+
+# ============================================================================
+# MAIN
+# ============================================================================
+
+if __name__ == "__main__":
+    print("\n" + "="*70)
+    print("🧛 DRACULA CHARACTER CHAT - HUGGINGFACE SPACES")
+    print("="*70)
+    print("\n🚀 Starting web server...")
+    print("⏳ First launch: ~2-3 minutes (downloads model)")
+    print("✅ Subsequent launches: Instant (uses cache)\n")
+    
+    # Initialize chatbot before launching
+    print("🔧 Pre-loading chatbot...")
+    initialize_chatbot()
+    
+    # Create and launch app
+    app = create_ui()
+    
+    # Launch configuration for HF Spaces
+    app.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=False,  # HF Spaces handles public URLs
+        show_error=True
+    )

requirements.txt

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+# HuggingFace Spaces Requirements
+# Python 3.10+
+
+# Web Interface
+gradio>=4.0.0
+
+# PyTorch CPU-only (install BEFORE sentence-transformers to avoid CUDA)
+--extra-index-url https://download.pytorch.org/whl/cpu
+torch>=2.0.0
+torchvision
+torchaudio
+
+# Model and AI
+llama-cpp-python==0.2.90  # Pin to specific version that builds faster
+sentence-transformers>=2.2.0
+huggingface-hub>=0.19.0
+
+# Vector Search
+faiss-cpu>=1.7.4
+
+# Utilities
+numpy>=1.24.0