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Parent(s):
092270e
Initial commit
Browse files- Dockerfile +57 -0
- README.md +46 -3
- app.py +116 -0
- requirements.txt +25 -0
Dockerfile
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FROM python:3.10-slim
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WORKDIR /code
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# Install system dependencies
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RUN apt-get update && apt-get install -y \
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build-essential \
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curl \
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software-properties-common \
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git \
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&& rm -rf /var/lib/apt/lists/*
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# Install Chrome dependencies for playwright
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RUN apt-get update && apt-get install -y \
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libnss3 \
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libnspr4 \
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libatk1.0-0 \
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libatk-bridge2.0-0 \
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libcups2 \
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libdrm2 \
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libxkbcommon0 \
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libxcomposite1 \
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libxdamage1 \
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libxfixes3 \
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libxrandr2 \
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libgbm1 \
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libasound2 \
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&& rm -rf /var/lib/apt/lists/*
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# Copy requirements first for better caching
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COPY requirements.txt .
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# Install Python dependencies
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RUN pip install --no-cache-dir -r requirements.txt
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# Install playwright browsers
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RUN playwright install chromium
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RUN playwright install-deps chromium
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# Copy the rest of the application
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COPY . .
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# Create necessary directories with proper permissions
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RUN mkdir -p db logs projects screenshots pdfs && \
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chmod 777 db logs projects screenshots pdfs
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# Set environment variables
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ENV PYTHONUNBUFFERED=1
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ENV PYTHONDONTWRITEBYTECODE=1
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ENV GRADIO_SERVER_PORT=7860
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ENV GRADIO_SERVER_NAME=0.0.0.0
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# Expose port for Gradio
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EXPOSE 7860
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# Command to run the application
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CMD ["python", "app.py"]
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README.md
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---
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title: Devika Assistant
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-
emoji:
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colorFrom: indigo
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colorTo: yellow
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sdk: docker
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pinned: false
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license: apache-2.0
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short_description:
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---
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-
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---
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title: Devika Assistant
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emoji: π€
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colorFrom: indigo
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colorTo: yellow
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sdk: docker
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pinned: false
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license: apache-2.0
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short_description: An advanced AI coding assistant powered by GPT and Claude models.
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---
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# π€ Devika AI Assistant
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Devika is an advanced AI coding assistant that helps developers with various programming tasks. This Hugging Face Space provides a simplified interface to interact with Devika's core functionality.
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## π Features
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- **Code Generation**: Get help writing code in various programming languages
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- **Project Creation**: Start new coding projects with best practices
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- **Code Debugging**: Get assistance in finding and fixing bugs
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- **Programming Q&A**: Ask questions about programming concepts and get detailed answers
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## π How to Use
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1. Type your coding request or question in the text input
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2. Select your preferred language model:
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- GPT-3.5 Turbo (default)
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- GPT-4
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- Claude-3-Opus
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3. Choose your search engine:
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- DuckDuckGo (default, no API key needed)
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- Bing (requires API key)
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- Google (requires API key)
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4. Click "Send Message" and wait for Devika's response
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## π API Keys
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To use certain features, you'll need to set up API keys in the Space settings:
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- For GPT models: Set up your OpenAI API key
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- For Claude: Set up your Anthropic API key
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- For search engines: Follow the setup guide in the [documentation](https://github.com/stitionai/devika/blob/main/docs/Installation/search_engine.md)
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## π Example Queries
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- "Create a React component for a todo list"
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- "Help me debug this Python function..."
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- "How do I implement authentication in Express.js?"
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- "Create a new Django project with user authentication"
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## π Links
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- [GitHub Repository](https://github.com/stitionai/devika)
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- [Documentation](https://github.com/stitionai/devika/tree/main/docs)
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- [Report Issues](https://github.com/stitionai/devika/issues)
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app.py
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import os
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from dotenv import load_dotenv
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load_dotenv() # Load environment variables from .env file
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import gradio as gr
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from threading import Thread
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import tiktoken
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import logging
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from src.config import Config
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from src.logger import Logger
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from src.project import ProjectManager
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from src.state import AgentState
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from src.agents import Agent
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# Initialize core components
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manager = ProjectManager()
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AgentState = AgentState()
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config = Config()
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logger = Logger()
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TIKTOKEN_ENC = tiktoken.get_encoding("cl100k_base")
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# Configure logging
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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def process_message(message, base_model="gpt-3.5-turbo", project_name="default", search_engine="duckduckgo"):
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try:
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agent = Agent(base_model=base_model, search_engine=search_engine.lower())
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state = AgentState.get_latest_state(project_name)
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if not state:
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agent.execute(message, project_name)
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else:
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if AgentState.is_agent_completed(project_name):
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agent.subsequent_execute(message, project_name)
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else:
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agent.execute(message, project_name)
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# Get the latest messages
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messages = manager.get_messages(project_name)
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return messages[-1]["message"] if messages else "No response generated"
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except Exception as e:
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logger.error(f"Error processing message: {str(e)}")
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return f"An error occurred: {str(e)}"
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def create_gradio_interface():
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with gr.Blocks(title="Devika AI Assistant", theme=gr.themes.Soft()) as interface:
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gr.Markdown("""
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# π€ Devika AI Assistant
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Devika is an advanced AI coding assistant that helps you with:
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- Writing and debugging code
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- Creating new projects
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- Answering programming questions
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- And much more!
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Simply type your request below and Devika will help you out.
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""")
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with gr.Row():
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with gr.Column(scale=2):
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message_input = gr.Textbox(
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label="Your Message",
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placeholder="Type your coding request here...",
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lines=3
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)
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with gr.Row():
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model_dropdown = gr.Dropdown(
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choices=["gpt-3.5-turbo", "gpt-4", "claude-3-opus"],
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value="gpt-3.5-turbo",
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label="Model"
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)
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search_engine_dropdown = gr.Dropdown(
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choices=["DuckDuckGo", "Bing", "Google"],
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value="DuckDuckGo",
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label="Search Engine"
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)
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submit_btn = gr.Button("Send Message", variant="primary")
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with gr.Column(scale=3):
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output_box = gr.Markdown(label="Devika's Response")
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# Add examples
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gr.Examples(
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examples=[
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["Create a React component for a todo list", "gpt-3.5-turbo", "DuckDuckGo"],
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["Help me understand how to use Python decorators", "gpt-3.5-turbo", "DuckDuckGo"],
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["Write a Node.js API endpoint for user authentication", "gpt-3.5-turbo", "DuckDuckGo"]
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],
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inputs=[message_input, model_dropdown, search_engine_dropdown],
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outputs=output_box,
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fn=lambda x, y, z: process_message(x, y, "default", z),
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cache_examples=True
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)
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submit_btn.click(
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fn=process_message,
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inputs=[message_input, model_dropdown, gr.Textbox(value="default", visible=False), search_engine_dropdown],
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outputs=output_box
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)
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return interface
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# Create and launch the Gradio interface
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interface = create_gradio_interface()
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if __name__ == "__main__":
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interface.launch(
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server_name="0.0.0.0",
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server_port=7860,
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share=False,
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debug=False
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)
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requirements.txt
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flask>=2.0.0
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flask-cors>=4.0.0
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flask-socketio>=5.3.0
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gevent>=22.10.2
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gradio>=4.19.2
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tiktoken>=0.5.2
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python-socketio>=5.11.0
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fastlogging>=1.0.0
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toml>=0.10.2
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sqlmodel>=0.0.14
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sqlalchemy>=2.0.0
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playwright>=1.41.2
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sentence-transformers>=2.5.1
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urllib3>=2.0.0
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requests>=2.31.0
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colorama>=0.4.6
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Jinja2>=3.1.2
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mistletoe>=1.2.1
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markdownify>=0.11.6
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pytest-playwright>=0.4.3
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openai>=1.12.0
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anthropic>=0.18.1
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duckduckgo-search>=4.4.3
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orjson>=3.9.15
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python-dotenv>=1.0.0
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