First

.dockerignore

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+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# Virtual Environment
+venv/
+env/
+ENV/
+.venv
+
+# IDE
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+
+# Environment files
+.env
+.env.*
+!.env.example
+
+# Logs
+*.log
+logs/
+server.log
+
+# Testing
+.pytest_cache/
+.coverage
+htmlcov/
+.tox/
+.hypothesis/
+
+# Database
+*.db
+*.sqlite
+*.sqlite3
+
+# Documentation
+docs/_build/
+*.md.backup
+
+# Git
+.git/
+.gitignore
+.gitattributes
+
+# Docker
+Dockerfile.*
+docker-compose*.yml
+
+# OS
+.DS_Store
+Thumbs.db
+
+# Temporary files
+*.tmp
+*.temp
+tmp/
+temp/
+
+# Migration files (if needed)
+test_migration.py
+test_mcp_tools.py
+test_endpoints.sh
+run_migration.sh
+create_sample_users.py
+*.pid
+

.gitignore

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+# =============================================================================
+# PIXERSE LP CHATBOT - GIT IGNORE CONFIGURATION
+# =============================================================================
+
+# Environment files - NEVER commit these!
+.env
+.env.local
+.env.development
+.env.staging
+.env.production
+
+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
+# Virtual environments
+.env/
+.venv/
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# pyenv
+.python-version
+
+# pipenv
+Pipfile.lock
+
+# PEP 582
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# IDEs
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+
+# macOS
+.DS_Store
+.AppleDouble
+.LSOverride
+
+# Windows
+Thumbs.db
+ehthumbs.db
+Desktop.ini
+
+# Logs
+*.log
+logs/
+
+# Database
+*.db
+*.sqlite3
+
+# Temporary files
+*.tmp
+*.temp
+tmp/
+temp/
+
+# OS generated files
+.DS_Store
+.DS_Store?
+._*
+.Spotlight-V100
+.Trashes
+ehthumbs.db
+Thumbs.db
+
+# Application specific
+uploads/
+downloads/
+static/collected/
+
+# Docker
+.docker/
+
+# Node.js (if any frontend components)
+node_modules/
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*

DEPLOYMENT.md

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+# Hướng dẫn Deploy lên Hugging Face Spaces
+
+## Bước 1: Chuẩn bị Repository
+
+1. Tạo một Space mới trên Hugging Face: https://huggingface.co/new-space
+2. Chọn SDK: **Streamlit**
+3. Clone repository về máy hoặc upload files
+
+## Bước 2: Upload Files
+
+Upload các files sau lên repository:
+
+```
+├── main.py                     # File chính của ứng dụng
+├── requirements.txt            # Dependencies Python
+├── README.md                   # Metadata cho HF Spaces
+├── Dockerfile                  # Tùy chọn: để custom container
+├── .streamlit/
+│   ├── config.toml            # Cấu hình Streamlit
+│   └── secrets.example.toml   # Mẫu file secrets
+├── .env                       # Environment variables
+└── .dockerignore              # Ignore files cho Docker
+```
+
+## Bước 3: Cấu hình Environment Variables
+
+Trong Hugging Face Spaces Settings, thêm:
+
+- `API_BASE_URL`: URL của API backend (ví dụ: https://your-api.com)
+
+## Bước 4: Deploy
+
+1. Push code lên repository
+2. Hugging Face sẽ tự động build và deploy
+3. Kiểm tra logs nếu có lỗi
+
+## Lưu ý:
+
+- Port mặc định cho HF Spaces: 7860
+- App sẽ tự động restart khi có thay đổi code
+- Có thể monitor logs trong tab "Logs" của Space
+
+## Troubleshooting:
+
+1. **API connection issues**: Kiểm tra `API_BASE_URL` trong settings
+2. **Import errors**: Kiểm tra `requirements.txt`
+3. **Port issues**: Đảm bảo app chạy trên port 7860

Dockerfile

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+FROM python:3.9-slim
+
+WORKDIR /app
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    curl \
+    software-properties-common \
+    git \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy requirements and install Python dependencies
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy application files
+COPY . .
+
+# Expose port for Streamlit
+EXPOSE 7860
+
+# Health check
+HEALTHCHECK CMD curl --fail http://localhost:7860/_stcore/health
+
+# Run Streamlit app
+ENTRYPOINT ["streamlit", "run", "main.py", "--server.port=7860", "--server.address=0.0.0.0"]

main.py

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+import streamlit as st
+import requests
+import json
+import uuid
+from typing import Dict, Any
+import os
+from dotenv import load_dotenv
+
+# Load environment variables
+load_dotenv()
+
+# Configuration
+API_BASE_URL = os.getenv("API_BASE_URL", "https://pixerse-pixerse.hf.space")  # Default to the env value
+CHAT_ENDPOINT = f"{API_BASE_URL}/api/mcp/chat"
+
+def call_chat_api(query: str, user_id: str) -> Dict[str, Any]:
+    """Call the FastAPI chat endpoint"""
+    payload = {
+        "query": query,
+        "user_id": user_id
+    }
+    
+    try:
+        response = requests.post(
+            CHAT_ENDPOINT,
+            json=payload,
+            headers={"Content-Type": "application/json"},
+            timeout=30
+        )
+        
+        if response.status_code == 200:
+            return {
+                "success": True,
+                "data": response.json()
+            }
+        else:
+            return {
+                "success": False,
+                "error": f"API Error: {response.status_code} - {response.text}"
+            }
+    except requests.exceptions.RequestException as e:
+        return {
+            "success": False,
+            "error": f"Connection Error: {str(e)}"
+        }
+
+def main():
+    st.set_page_config(
+        page_title="PiXerse Chatbot",
+        page_icon="🤖",
+        layout="wide"
+    )
+    
+    st.title("🤖 PiXerse AI Chatbot")
+    st.markdown("---")
+    
+    # Initialize session state
+    if "messages" not in st.session_state:
+        st.session_state.messages = []
+    
+    if "user_id" not in st.session_state:
+        st.session_state.user_id = str(uuid.uuid4())
+    
+    # Sidebar for configuration
+    with st.sidebar:
+        st.header("⚙️ Configuration")
+        
+        # Display user ID
+        st.text_input(
+            "User ID", 
+            value=st.session_state.user_id, 
+            disabled=True,
+            help="Your unique session identifier"
+        )
+        
+        # API Status check
+        st.subheader("🔍 API Status")
+        if st.button("Check API Status"):
+            try:
+                health_response = requests.get(f"{API_BASE_URL}/docs", timeout=5)
+                if health_response.status_code == 200:
+                    st.success("✅ API is running")
+                else:
+                    st.error("❌ API is not responding properly")
+            except:
+                st.error("❌ Cannot connect to API")
+        
+        # Clear chat button
+        if st.button("🗑️ Clear Chat History"):
+            st.session_state.messages = []
+            st.rerun()
+    
+    # Main chat interface
+    st.subheader("💬 Chat Interface")
+    
+    # Display chat messages
+    chat_container = st.container()
+    with chat_container:
+        for message in st.session_state.messages:
+            with st.chat_message(message["role"]):
+                st.markdown(message["content"])
+                
+                # Show additional info for assistant messages
+                if message["role"] == "assistant" and "metadata" in message:
+                    with st.expander("📊 Response Details"):
+                        metadata = message["metadata"]
+                        col_meta1, col_meta2 = st.columns(2)
+                        
+                        with col_meta1:
+                            st.metric("Token Usage", metadata.get("token_usage", "N/A"))
+                            
+                        with col_meta2:
+                            st.metric("Tools Used", len(metadata.get("tools_used", [])))
+                        
+                        if metadata.get("tools_used"):
+                            st.write("**Tools Used:**")
+                            for tool in metadata["tools_used"]:
+                                st.code(tool, language="text")
+                        
+                        if metadata.get("tools_response"):
+                            st.write("**Tool Responses:**")
+                            for i, response in enumerate(metadata["tools_response"]):
+                                st.json(response)
+
+    # Chat input (outside columns to avoid Streamlit API error)
+    if prompt := st.chat_input("Type your message here..."):
+        # Add user message to chat
+        st.session_state.messages.append({
+            "role": "user", 
+            "content": prompt
+        })
+        
+        # Rerun to display new message immediately
+        st.rerun()
+
+    # Process last message if it's from user and no assistant response yet
+    if (st.session_state.messages and 
+        st.session_state.messages[-1]["role"] == "user" and
+        (len(st.session_state.messages) == 1 or 
+         st.session_state.messages[-2]["role"] == "assistant")):
+        
+        user_message = st.session_state.messages[-1]["content"]
+        
+        # Show processing message
+        with st.chat_message("assistant"):
+            with st.spinner("🤔 Thinking..."):
+                response = call_chat_api(user_message, st.session_state.user_id)
+            
+            if response["success"]:
+                data = response["data"]
+                assistant_message = data["response"]
+                
+                # Display response
+                st.markdown(assistant_message)
+                
+                # Add assistant message to chat with metadata
+                st.session_state.messages.append({
+                    "role": "assistant",
+                    "content": assistant_message,
+                    "metadata": {
+                        "token_usage": data.get("token_usage", 0),
+                        "tools_used": data.get("tools_used", []),
+                        "tools_response": data.get("tools_response", [])
+                    }
+                })
+                
+            else:
+                error_message = f"❌ Error: {response['error']}"
+                st.error(error_message)
+                
+                # Add error message to chat
+                st.session_state.messages.append({
+                    "role": "assistant",
+                    "content": error_message
+                })
+            
+            # Rerun to update the display
+            st.rerun()
+
+if __name__ == "__main__":
+    # Run Streamlit UI
+    main()

requirements.txt

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+streamlit>=1.28.0
+requests>=2.31.0
+python-dotenv>=1.0.0