This Django Note-Taking application provides a simple yet effective way to create, manage, and summarize notes. Built using Django and Django REST Framework, and integrated with ChatGPT using LangChain, it offers a range of functionalities accessible via a RESTful API.
- CRUD Operations: Create, Read, Update, and Delete notes.
- Note Summarization: Utilize LangChain and OpenAI's GPT-3 model to generate summaries of notes.
- API Documentation: Swagger UI for easy visualization and interaction with the API's resources.
To set up the project locally, follow these steps:
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Clone the repository: git clone https://github.com/TimNuga/note-taking-app.git cd note-taking-app
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Set up a virtual environment: python -m venv venv source venv/bin/activate (On Windows use
venv\Scripts\activate) -
Install the requirements: pip install -r requirements.txt
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Run migrations to create the database schema: python manage.py migrate
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Start the development server: python manage.py runserver
Once the server is running, you can access the API endpoints. For detailed endpoint documentation, visit http://localhost:8000/swagger/.
- List/Create Notes: GET and POST requests to /notes/
- Retrieve/Update/Delete Note: GET, PUT, PATCH, and DELETE requests to /notes/{note_id}/
- Summarize Note: GET request to /notes/{note_id}/summarize/
- Framework: Django, Django REST Framework
- Database: SQLite (default Django database)
- Summarization: LangChain, OpenAI GPT-3
- API Documentation: Swagger (drf-yasg)
To run tests, execute: python manage.py test
Langchain was used to leverage the chatGPT-3.5 model and it was ultimately integrated into the application providing a feature that summarizes notes passed into the model at a given endpoint in the REST structure. The current implementation uses the langchain large language model (llm) and the infrastructure provided by langchain when it is properly installed in a project. This infrastructure provided includes the ChatOpenAI model (which takes in the OpenAI API key required for gaining access to the OpenAI API), the PromptTemplate from the langchain prompts, the langchain chain class, and the StuffDocumentsChain provides us with the heavy lifting required to summarize the note contents passed in as documents to the model.
- Passing in the string values obtained in the notes as documents for the StuffDocumentsChain to utilize.
- Choosing the right kind of llm model for this feature.
- Utilizing the right kind of prompt template.
- OPENAI_API_KEY: API key for OpenAI GPT-3. Set this in a .env file in the root directory, you can copy it in the .env.example file and paste your genrated API key in the .env file.
Contributions to the project are welcome. Please follow the standard fork and pull request workflow.