fleet-context 1.0.14

A chat interface over up-to-date Python library documentation.

🛩️ Fleet Context

A CLI tool over the top 1218 Python libraries.
Used for library q/a & code generation with all avaliable OpenAI models

Website      |      Data Visualizer      |      PyPI      |      @fleet_ai‎

https://github.com/fleet-ai/context/assets/44193474/80381b25-551e-4602-8987-071e92354f6f

Quick Start

Install the package and run context to ask questions about the most up-to-date Python libraries. You will have to provide your OpenAI key to start a session.

pip install fleet-context
context

If you'd like to run the CLI tool locally, you can clone this repository, cd into it, then run:

pip install -e .
context

If you have an existing package that already uses they keyword context, you can also activate Fleet Context by running:

fleet-context

Limit libraries

You can use the -l or --libraries followed by a list of libraries to limit your session to a certain number of libraries. Defaults to all. View a list of all supported libraries on our website.

context -l langchain pydantic openai

Use a different OpenAI model

You can select a different OpenAI model by using -m or --model. Defaults to gpt-4. You can set your model to gpt-4-1106-preview (gpt-4-turbo), gpt-3.5-turbo, or gpt-3.5-turbo-16k.

context -m gpt-4-1106-preview

Advanced settings

You can control the number of retrieved chunks by using -k or --k_value (defaulted to 15), and you can toggle whether the model cites its source by using -c or --cite_sources (defaults to true).

context -k 25 -c false

Evaluations

Results

Sampled libraries

We saw a 37-point improvement for gpt-4 generation scores and a 34-point improvement for gpt-4-turbo generation scores amongst a randomly sampled set of 50 libraries.

We attribute this to a lack of knowledge for the most up-to-date versions of libraries for gpt-4, and a combination of relevant up-to-date information to generate with and relevance of information for gpt-4-turbo.

Embeddings

Check out our visualized data here.

You can download all embeddings here.