A web application that allows users to interact with a chatbot representing a professional profile. The chatbot is designed to answer questions about the profile's career, background, skills, and experience in a professional and engaging manner.
- Interactive Chat Interface: Built with Gradio, providing a user-friendly chat experience.
- Professional Profile Representation: The chatbot acts as a representative of a professional profile, answering questions based on the provided profile information.
- Quality Control: An evaluator agent ensures that the responses are acceptable and professional, with feedback for improvement if needed.
- Docker Support: Containerized deployment for easy setup and scalability.
-
Clone the repository:
git clone https://github.com/kaushik2901/talk-to-my-cv.git cd talk-to-my-cv -
Install the required dependencies:
pip install -r requirements.txt
-
Set up environment variables:
- Create a
.envfile in the root directory. - Add the following variables:
OPENAI_API_KEY=your_openai_api_key GEMINI_API_KEY=your_gemini_api_key
- Create a
-
Ensure your profile information is set up:
- Update
data/name.txtwith the name of the profile. - Update
data/profile.mdwith the professional background details.
- Update
-
Run the application:
python src/main.py
-
Open your web browser and navigate to the provided URL (usually
http://localhost:7860). -
Start chatting with the bot!
-
Build the Docker image:
docker build -t talk-to-my-cv . -
Run the container:
docker run -p 7860:7860 talk-to-my-cv
-
Access the application at
http://localhost:7860.
src/: Contains the main application code.main.py: Entry point for the application.agents/: Contains the chat and evaluator agents.models/: Contains the data models.utils/: Contains utility functions.
data/: Contains the profile information.Dockerfile: Configuration for Docker deployment.requirements.txt: List of Python dependencies.
This project is licensed under the MIT License - see the LICENSE file for details.