🛩️ Fleet Context

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

Website      |      Data Visualizer      |      PyPI      |      @fleet_ai‎

fleet-context.mp4

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 the keyword context, you can also activate Fleet Context by running:

fleet-context

API

You can download any library's embeddings and load it up into a dataframe by running:

from context import download_embeddings

df = download_embeddings("langchain")

100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 901k/901k [00:00<00:00, 2.64MiB/s]
                                     id                                   dense_embeddings                                           metadata                                      sparse_values
0  91cd9f22-b3b6-49e1-8672-e1e42a1cf766  [-0.014795871, -0.013938751, 0.02374646, -0.02...  {'id': '91cd9f22-b3b6-49e1-8672-e1e42a1cf766',...  {'indices': [4279915734, 3106554626, 771291085...
1  80cd620e-7408-4649-aaa7-3fe3c719b4ed  [-0.0027519625, 0.013772411, 0.0019546314, -0....  {'id': '80cd620e-7408-4649-aaa7-3fe3c719b4ed',...  {'indices': [1497795724, 573857107, 2203090375...
2  87a406ad-e413-42fc-8813-6fa042f80f6a  [-0.022883521, -0.0036436971, 0.0026068306, 0....  {'id': '87a406ad-e413-42fc-8813-6fa042f80f6a',...  {'indices': [1558403699, 640376310, 358389376,...
3  8bdd8dae-8384-414d-87d2-4390ca29d857  [-0.024882555, -0.0041470923, -0.011419726, -0...  {'id': '8bdd8dae-8384-414d-87d2-4390ca29d857',...  {'indices': [1558403699, 3778951566, 274301652...
4  8cc5eb61-317a-4196-8099-51c47ef70406  [-0.036361936, 0.0027855083, -0.013214805, -0....  {'id': '8cc5eb61-317a-4196-8099-51c47ef70406',...  {'indices': [3586802366, 1110127215, 161253108...

You can see a full list of supported libraries & search through them on our website at the bottom of the page.

CLI Tool

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

Using local models

Local model support is powered by LM Studio. To use local models, you can use --local or -n:

context --local

You need to download your local model through LM Studio. To do that:

1. Download LM Studio. You can find the download link here: https://lmstudio.ai
2. Open LM Studio and download your model of choice.
3. Click the ↔ icon on the very left sidebar
4. Select your model and click "Start Server"

The context window is defaulted to 3000. You can change this by using --context_window or -w:

context --local --context_window 4096

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.