Spaces:
Sleeping
Sleeping
chore: update project dependencies and add README and TODO files for better documentation and feature tracking
Browse files- README.md +152 -0
- TODO.md +11 -0
- app/main.py +4 -5
- pyproject.toml +0 -2
- requirements.txt +169 -0
- uv.lock +0 -0
README.md
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---
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title: LinkedIn Career Advisor
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emoji: 🚀
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colorFrom: blue
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colorTo: green
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sdk: gradio
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sdk_version: 3.50.2
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app_file: app/main.py
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pinned: false
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---
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# LinkedIn Career Advisor 🚀
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+

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+

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+

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+

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+
A professional career pathway analysis tool that leverages AI to provide tailored career path recommendations based on your professional background, education, and goals. No telemetry.
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+

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## ✨ Features
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- **Comprehensive Career Analysis**: Get detailed insights on potential career paths tailored to your unique professional background
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- **Multi-dimensional Evaluation**: Each path is scored on financial potential, human impact, and opportunity creation
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- **Customizable Preferences**: Adjust weights for different factors based on your personal priorities
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+
- **Time Horizon Options**: Choose between short-term (3 years), mid-term (10 years), or long-term (10+ years) career planning
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- **Easy Sharing**: Export your analysis to LinkedIn or copy to clipboard with a single click
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- **Intuitive Interface**: User-friendly Gradio UI for seamless interaction
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## 🔧 Installation
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### Prerequisites
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- Python 3.12 or higher
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- OpenAI API key
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### Setup
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1. Clone the repository:
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```bash
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git clone https://github.com/danivpv/linkedinadvice.git
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cd linkedinadvice
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```
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2. Install dependencies using uv (recommended):
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```bash
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uv sync --all-extras
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```
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3. Create a `.env` file in the root directory with your OpenAI API key:
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```
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OPENAI_API_KEY=your-api-key-here
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```
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## 🚀 Running Locally
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Start the application with:
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```bash
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uv run poe start # alternatively, uv run gradio app/main.py
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```
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The Gradio interface will be available at `http://localhost:7860` in your browser.
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## 📦 Project Structure
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```
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linkedin-career-advisor/
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├── app/
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│ ├── main.py # Application entry point and Gradio UI
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│ ├── constants.py # Application constants and example data
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│ └── utils.py # Utility functions for clipboard and sharing
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│
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├── linkedinadvice/
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│ ├── __init__.py
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│ ├── career_analysis.py # Career analysis using LangChain and LLM
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│ └── monitoring.py # API usage monitoring and logging
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│
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├── requirements.txt # Project dependencies
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├── .env # Environment variables (not tracked by git)
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└── README.md # Project documentation
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```
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## 🌐 Deploying to Hugging Face Spaces
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1. Create a new Space on [Hugging Face Spaces](https://huggingface.co/spaces)
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2. Choose Gradio as the SDK
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3. Push this repository to the created Space
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4. Add your `OPENAI_API_KEY` as a secret in the Space settings
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## 💻 Development
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### Dependencies
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- `gradio`: For the web interface
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- `langchain`: For LLM integration and career analysis pipeline
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- `openai`: For accessing GPT models
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- `python-dotenv`: For environment variable management
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### Adding New Features
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To extend the application:
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1. Modify the analysis logic in `linkedinadvice/career_analysis.py`
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2. Update UI components in `app/main.py`
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3. Add new constants in `app/constants.py` if needed
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## 📊 Usage Example
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1. **Input your professional experience**:
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- Add current and previous roles
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- Specify years of experience
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- List notable achievements
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2. **Add educational background**:
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- Enter degrees, institutions, and dates
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- Highlight academic achievements
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3. **Define your goals and preferences**:
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- Set career goals
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- Add additional insights
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- Adjust time horizon and factor weights
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4. **Analyze and review results**:
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- Get personalized career path recommendations
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- See detailed scoring across dimensions
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- Export or share your results
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## 🤝 Contributing
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Contributions are welcome! Please feel free to submit a Pull Request.
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1. Fork the repository
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2. Create your feature branch (`git checkout -b feature/amazing-feature`)
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3. Commit your changes (`git commit -m 'Add some amazing feature'`)
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4. Push to the branch (`git push origin feature/amazing-feature`)
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5. Open a Pull Request
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## 📄 License
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This project is licensed under the MIT License - see the LICENSE file for details.
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## 🙏 Acknowledgements
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- [OpenAI](https://openai.com/) for providing the underlying language models
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- [Gradio](https://gradio.app/) for the easy-to-use UI framework
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framework
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---
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Built with ❤️ for career professionals worldwide
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TODO.md
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# LinkedIn Career Advice - TODO
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## Features
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- [ ] Data extraction from PDF
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- [ ] Sharing button to LinkedIn
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- [ ] Optimizing prompts to multiple prompts
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## Dev
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- [ ] Improve monitoring and logging
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- [ ] Add tests
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- [ ] Add CI/CD
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app/main.py
CHANGED
@@ -3,7 +3,7 @@ import os
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import gradio as gr
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from dotenv import load_dotenv
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from app.constants import ROLE_PLACEHOLDER
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from app.utils import copy_to_clipboard, export_state
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from linkedinadvice.career_analysis import CareerAnalyzer
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from linkedinadvice.monitoring import monitor_api
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with gr.Column(scale=2):
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output_box = gr.Markdown(
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output.value,
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label="Career Analysis Report",
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container=True,
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height=614,
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show_copy_button=
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)
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with gr.Row():
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fn=lambda: None, inputs=[], outputs=[], js="() => location.reload()"
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)
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-
"""
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example_btn.click(
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fn=lambda _: SAMPLE_RESULT,
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inputs=[output_box],
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outputs=[output_box],
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)
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-
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# Launch the app
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if __name__ == "__main__":
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import gradio as gr
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from dotenv import load_dotenv
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from app.constants import ROLE_PLACEHOLDER, SAMPLE_RESULT
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from app.utils import copy_to_clipboard, export_state
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from linkedinadvice.career_analysis import CareerAnalyzer
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from linkedinadvice.monitoring import monitor_api
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with gr.Column(scale=2):
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output_box = gr.Markdown(
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output.value,
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container=True,
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height=614,
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show_copy_button=True,
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key="output_box",
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)
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with gr.Row():
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fn=lambda: None, inputs=[], outputs=[], js="() => location.reload()"
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)
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example_btn.click(
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fn=lambda _: SAMPLE_RESULT,
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inputs=[output_box],
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outputs=[output_box],
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)
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+
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# Launch the app
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if __name__ == "__main__":
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pyproject.toml
CHANGED
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requires-python = ">=3.12"
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dependencies = [
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"gradio>=5.22.0",
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-
"langchain>=0.3.21",
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-
"langchain-community>=0.3.20",
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"openai>=1.68.0",
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"pyperclip>=1.9.0",
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"python-dotenv>=1.0.1",
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requires-python = ">=3.12"
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dependencies = [
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"gradio>=5.22.0",
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"openai>=1.68.0",
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"pyperclip>=1.9.0",
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"python-dotenv>=1.0.1",
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requirements.txt
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# This file was autogenerated by uv via the following command:
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2 |
+
# uv pip compile pyproject.toml -o requirements.txt
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3 |
+
aiofiles==23.2.1
|
4 |
+
# via gradio
|
5 |
+
annotated-types==0.7.0
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6 |
+
# via pydantic
|
7 |
+
anyio==4.9.0
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8 |
+
# via
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9 |
+
# gradio
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10 |
+
# httpx
|
11 |
+
# openai
|
12 |
+
# starlette
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13 |
+
certifi==2025.1.31
|
14 |
+
# via
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15 |
+
# httpcore
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16 |
+
# httpx
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17 |
+
# requests
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18 |
+
charset-normalizer==3.4.1
|
19 |
+
# via requests
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20 |
+
click==8.1.8
|
21 |
+
# via
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22 |
+
# typer
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23 |
+
# uvicorn
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24 |
+
colorama==0.4.6
|
25 |
+
# via
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26 |
+
# click
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27 |
+
# tqdm
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28 |
+
distro==1.9.0
|
29 |
+
# via openai
|
30 |
+
fastapi==0.115.11
|
31 |
+
# via gradio
|
32 |
+
ffmpy==0.5.0
|
33 |
+
# via gradio
|
34 |
+
filelock==3.18.0
|
35 |
+
# via huggingface-hub
|
36 |
+
fsspec==2025.3.0
|
37 |
+
# via
|
38 |
+
# gradio-client
|
39 |
+
# huggingface-hub
|
40 |
+
gradio==5.22.0
|
41 |
+
# via linkedinadvice (pyproject.toml)
|
42 |
+
gradio-client==1.8.0
|
43 |
+
# via gradio
|
44 |
+
groovy==0.1.2
|
45 |
+
# via gradio
|
46 |
+
h11==0.14.0
|
47 |
+
# via
|
48 |
+
# httpcore
|
49 |
+
# uvicorn
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50 |
+
httpcore==1.0.7
|
51 |
+
# via httpx
|
52 |
+
httpx==0.28.1
|
53 |
+
# via
|
54 |
+
# gradio
|
55 |
+
# gradio-client
|
56 |
+
# openai
|
57 |
+
# safehttpx
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58 |
+
huggingface-hub==0.29.3
|
59 |
+
# via
|
60 |
+
# gradio
|
61 |
+
# gradio-client
|
62 |
+
idna==3.10
|
63 |
+
# via
|
64 |
+
# anyio
|
65 |
+
# httpx
|
66 |
+
# requests
|
67 |
+
jinja2==3.1.6
|
68 |
+
# via gradio
|
69 |
+
jiter==0.9.0
|
70 |
+
# via openai
|
71 |
+
markdown-it-py==3.0.0
|
72 |
+
# via rich
|
73 |
+
markupsafe==3.0.2
|
74 |
+
# via
|
75 |
+
# gradio
|
76 |
+
# jinja2
|
77 |
+
mdurl==0.1.2
|
78 |
+
# via markdown-it-py
|
79 |
+
numpy==2.2.4
|
80 |
+
# via
|
81 |
+
# gradio
|
82 |
+
# pandas
|
83 |
+
openai==1.68.2
|
84 |
+
# via linkedinadvice (pyproject.toml)
|
85 |
+
orjson==3.10.15
|
86 |
+
# via gradio
|
87 |
+
packaging==24.2
|
88 |
+
# via
|
89 |
+
# gradio
|
90 |
+
# gradio-client
|
91 |
+
# huggingface-hub
|
92 |
+
pandas==2.2.3
|
93 |
+
# via gradio
|
94 |
+
pillow==11.1.0
|
95 |
+
# via gradio
|
96 |
+
pydantic==2.10.6
|
97 |
+
# via
|
98 |
+
# fastapi
|
99 |
+
# gradio
|
100 |
+
# openai
|
101 |
+
pydantic-core==2.27.2
|
102 |
+
# via pydantic
|
103 |
+
pydub==0.25.1
|
104 |
+
# via gradio
|
105 |
+
pygments==2.19.1
|
106 |
+
# via rich
|
107 |
+
pyperclip==1.9.0
|
108 |
+
# via linkedinadvice (pyproject.toml)
|
109 |
+
python-dateutil==2.9.0.post0
|
110 |
+
# via pandas
|
111 |
+
python-dotenv==1.0.1
|
112 |
+
# via linkedinadvice (pyproject.toml)
|
113 |
+
python-multipart==0.0.20
|
114 |
+
# via gradio
|
115 |
+
pytz==2025.1
|
116 |
+
# via pandas
|
117 |
+
pyyaml==6.0.2
|
118 |
+
# via
|
119 |
+
# gradio
|
120 |
+
# huggingface-hub
|
121 |
+
requests==2.32.3
|
122 |
+
# via huggingface-hub
|
123 |
+
rich==13.9.4
|
124 |
+
# via typer
|
125 |
+
ruff==0.11.2
|
126 |
+
# via gradio
|
127 |
+
safehttpx==0.1.6
|
128 |
+
# via gradio
|
129 |
+
semantic-version==2.10.0
|
130 |
+
# via gradio
|
131 |
+
shellingham==1.5.4
|
132 |
+
# via typer
|
133 |
+
six==1.17.0
|
134 |
+
# via python-dateutil
|
135 |
+
sniffio==1.3.1
|
136 |
+
# via
|
137 |
+
# anyio
|
138 |
+
# openai
|
139 |
+
starlette==0.46.1
|
140 |
+
# via
|
141 |
+
# fastapi
|
142 |
+
# gradio
|
143 |
+
tomlkit==0.13.2
|
144 |
+
# via gradio
|
145 |
+
tqdm==4.67.1
|
146 |
+
# via
|
147 |
+
# huggingface-hub
|
148 |
+
# openai
|
149 |
+
typer==0.15.2
|
150 |
+
# via gradio
|
151 |
+
typing-extensions==4.12.2
|
152 |
+
# via
|
153 |
+
# anyio
|
154 |
+
# fastapi
|
155 |
+
# gradio
|
156 |
+
# gradio-client
|
157 |
+
# huggingface-hub
|
158 |
+
# openai
|
159 |
+
# pydantic
|
160 |
+
# pydantic-core
|
161 |
+
# typer
|
162 |
+
tzdata==2025.1
|
163 |
+
# via pandas
|
164 |
+
urllib3==2.3.0
|
165 |
+
# via requests
|
166 |
+
uvicorn==0.34.0
|
167 |
+
# via gradio
|
168 |
+
websockets==15.0.1
|
169 |
+
# via gradio-client
|
uv.lock
CHANGED
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