semvec/pypi-packages huggingface dataset:
llm-council 0.1.3
Use LLM to generate and execute commands in your shell
License: MIT

# llm-council

Get a council of LLMs to advise consult for you!

## Installation

This plugin should be installed in the same environment as [LLM](https://llm.datasette.io/).
```bash
llm install llm-council
```

![council](https://raw.githubusercontent.com/nuwandavek/llm-council/refs/heads/master/assets/council2.png)

### Supported models/providers
The models themselves are fixed as of now with:
- `openai`: `gpt-4o`
- `anthropic`: `clause-3.5-sonnet`
- `google`: `gemini-1.5-flash-latest`

The necessary `llm plugins` are already installed. But you still need to set the keys
```bash
llm keys set openai
llm keys set claude
llm keys set gemini
```

## Usage

I usually run every query on all LLMs just to see what they have to say. And I love the llm library. You can now assemble your own council of advisors by simply running `llm council` like this:

```bash
llm council 'whats the california traffic law around double white lines?'
```

By default, it uses `openai` and `anthropic`. But you can specify the providers by:

```bash
llm council -p openai -p anthropic 'tell me a joke'
```
Press Q or Ctrl + C to exit.

## The system prompt

This is the prompt used by this tool:

> Keep your answers brief and to the point.

Feel free to modify it by passing the `--system` arg.

## Development

To set up this plugin locally, first checkout the code. Then create a new virtual environment:
```bash
cd llm-council
uv venv
source .venv/bin/activate

uv pip install -r pyproject.toml
```
Now install the plugin with:
```bash
llm install -e .
```
foxglove-schemas-protobuf 0.3.0
Precompiled protocol buffer schemas for Foxglove
License: MIT
Requires Python: >=3.9

# Foxglove Schemas (Protobuf)

This package provides [Protobuf](https://developers.google.com/protocol-buffers/) classes for [Foxglove Schemas](https://docs.foxglove.dev/docs/visualization/message-schemas/introduction).

## Installation

Install via [Poetry](https://python-poetry.org/):

```sh
poetry add foxglove-schemas-protobuf
```

## Usage

Import types from the `foxglove_schemas_protobuf` module as follows:

```py
from foxglove_schemas_protobuf.CompressedImage_pb2 import CompressedImage
```

## Stay in touch

Join our [Slack channel](https://foxglove.dev/slack) to ask questions, share feedback, and stay up to date on what our team is working on.
foxglove-schemas-flatbuffer 0.3.0
Precompiled flatbuffer schemas for Foxglove
License: MIT
Requires Python: >=3.9

# Foxglove Schemas (Flatbuffer)

This package provides [Flatbuffer](https://google.github.io/flatbuffers/) classes for [Foxglove Schemas](https://docs.foxglove.dev/docs/visualization/message-schemas/introduction).

## Installation

Install via [Poetry](https://python-poetry.org/):

```sh
poetry add foxglove-schemas-flatbuffer
```

## Usage

Import types from the `foxglove_schemas_flatbuffer` module as follows:

```py
import flatbuffers
import foxglove_schemas_flatbuffer.CompressedImage as CompressedImage
from foxglove_schemas_flatbuffer import get_schema

builder = flatbuffers.Builder(1024)
png = builder.CreateString("png")
CompressedImage.Start(builder)
CompressedImage.AddFormat(builder, png)
img = CompressedImage.End(builder)
builder.Finish(img)

# Serialized flatbuffer schema
schema_data = get_schema("CompressedImage")

# Serialized CompressedImage message
msg_data = builder.Output()
```

## Stay in touch

Join our [Slack channel](https://foxglove.dev/slack) to ask questions, share feedback, and stay up to date on what our team is working on.