AbanteAI/rawdog
Fork: 137 Star: 1779 (更新于 2024-11-03 06:52:08)
license: Apache-2.0
Language: Python .
Generate and auto-execute Python scripts in the cli
最后发布版本: v0.1.6 ( 2024-02-18 20:45:53)
Rawdog
An CLI assistant that responds by generating and auto-executing a Python script.
https://github.com/AbanteAI/rawdog/assets/50287275/1417a927-58c1-424f-90a8-e8e63875dcda
You'll be surprised how useful this can be:
- "How many folders in my home directory are git repos?" ... "Plot them by disk size."
- "Give me the pd.describe() for all the csv's in this directory"
- "What ports are currently active?" ... "What are the Google ones?" ... "Cancel those please."
Rawdog (Recursive Augmentation With Deterministic Output Generations) is a novel alternative to RAG (Retrieval Augmented Generation). Rawdog can self-select context by running scripts to print things, adding the output to the conversation, and then calling itself again.
This works for tasks like:
- "Setup the repo per the instructions in the README"
- "Look at all these csv's and tell me if they can be merged or not, and why."
- "Try that again."
Please proceed with caution. This obviously has the potential to cause harm if so instructed.
Quickstart
-
Install rawdog with pip:
pip install rawdog-ai
-
Export your api key. See Model selection for how to use other providers
export OPENAI_API_KEY=your-api-key
-
Choose a mode of interaction.
Direct: Execute a single prompt and close
rawdog Plot the size of all the files and directories in cwd
Conversation: Initiate back-and-forth until you close. Rawdog can see its scripts and output.
rawdog >>> What can I do for you? (Ctrl-C to exit) >>> > |
Optional Arguments
-
--leash
: (default False) Print and manually approve each script before executing. -
--retries
: (default 2) If rawdog's script throws an error, review the error and try again.
Model selection
Rawdog uses litellm
for completions with 'gpt-4-turbo-preview' as the default. You can adjust the model or
point it to other providers by modifying ~/.rawdog/config.yaml
. Some examples:
To use gpt-3.5 turbo a minimal config is:
llm_model: gpt-3.5-turbo
To run mixtral locally with ollama a minimal config is (assuming you have ollama installed and a sufficient gpu):
llm_custom_provider: ollama
llm_model: mixtral
To run claude-2.1 set your API key:
export ANTHROPIC_API_KEY=your-api-key
and then set your config:
llm_model: claude-2.1
If you have a model running at a local endpoint (or want to change the baseurl for some other reason)
you can set the llm_base_url
. For instance if you have an openai compatible endpoint running at
http://localhost:8000 you can set your config to:
llm_base_url: http://localhost:8000
llm_model: openai/model # So litellm knows it's an openai compatible endpoint
Litellm supports a huge number of providers including Azure, VertexAi and Huggingface. See their docs for details on what environment variables, model names and llm_custom_providers you need to use for other providers.
最近版本更新:(数据更新于 2024-09-26 05:40:07)
2024-02-18 20:45:53 v0.1.6
2024-02-16 23:18:26 v0.1.5-fix
2024-02-16 13:09:47 v0.1.4
2024-02-16 09:12:31 v0.1.3
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