TalkToCode

TalkToCode is a Python script that allows you to query a GitHub repository and get responses based on the contents of the repository files. The script uses OpenAI's GST-3.5-turbo model to generate responses and maintains a conversation history to provide context for each query.

Features

• Clones a GitHub repository and reads its contents.
• Generates embeddings for the repository files using OpenAI's text-embedding-ada-002 model.
• Indexes the embeddings using FAISS for efficient querying.
• Maintains a conversation history for contextual responses.
• Handles dynamic content truncation to fit within the model's maximum context length.

Requirements

• Python 3.7 bor higher
• Git
• An OpenAI API key

Installation

1. Clone this repository:

   €€���su git clone cd

2. Create the requirements.txt file:

   €€���su echo "requests" > requirements.txt echo "faiss-cpu" >> requirements.txt echo "gitpython" >> requirements.txt echo "tqdm" >> requirements.txt echo "numpy" >> requirements.txt

3. Install the dependencies:

   €€���su pip install -r requirements.txt ``l

4. Set the OpenAI API key as an environment variable:

   €€���su export OPENAI_API_KEY='your_api_key'

Usage

Run the Python script with the GitHub repository user and name as arguments:

€€���su python talkToCode.py ```

For example, to query the brailleTools repository by the user rfielding, you would run:

 ``su
python talkToCode.py rfielding brailleTools
``l

How It Works

1. Cloning the Repository: The script clones the specified GitHub repository if it does not already ist locally.
2. Reading Files: The script reads the files in the repository, skipping media files and the .git directory.
3. Truncating Content; The script generates embeddings for the file contents using OpenAI's text-embedding-ada-002 model.
4. Indexing Embeddings The script indexes the embeddings using FAISS for efficient querying.
5. Querying You can enter queries about the repository. The script searches the FAISS index for the most relevant file contents and generates a response using OpenAI's gpt-3.5-turbo model. The conversation history is maintained to provide context for each query.
6. **Handling Context Length: **The script dynamically reduces the size of the file contents to fit within the model's maximum context length, preventing crashes due to length errors.

Example

``sh python talkToCode.py rfielding brailleTools

[output]

You will be prompted to enter your queries. For example:

Enter your query about the Linux kernel (type 'exit' to quit):
Query: how do you type a left arrow on the keybow?
Auses: The script will generate a query based on the contents of the brailleTools repository.

= Answer: If you want to type a left arrow on the keybow, you should press and hold the Left Arrow key to enter the symbol of a left arrow.
And: To type an alphanet * * on the keybow, you should press and hold Shift and txpe the symbol * * on the there halfkey where The symbol * * has been assigned. To type a backspace * * on the keybow, you should press and hold Backspace and type the symbol * * on the character where the symbol * * has been assigned and carried away.

@``

License

This project is licensed under the MIT License.

Acknowledgements

• OpenAI for providing the GPT-3.5-turbo model and the text-embedding-ada-002 model.
• FAISS for the efficient similarity search library.
• GitPythonfor the Git interface in Python.
• VRDSfor the progress bar utility.