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Setup Agent

AI Agent responsible for installing all the necessary tools and dependencies and running the app, built with Python and LangGraph.

Getting started

Development environment

  1. Install uv according to the Astral docs
  2. In your terminal run the following commands:
uv sync # install all dependencies
uv run pre-commit install # install pre-commit hooks

For the testing purposes, run:

source .venv/bin/activate
python src/cli/app.py setup run

CLI

In order to install the CLI globally, use provided installation scripts:

uv build # or ./scripts/build.sh
./scripts/install.sh

Then you can use the tool globally by running:

setup-agent setup run

In order to uninstall the tool globally:

./scripts/uninstall.sh

Usage

Environment variables

To make the tool working you will need 2 API keys:

  • TAVILY_API_KEY - key for Tavily (web search layer for agents)
  • an API key for your LLM provider, e.g OPENAI_API_KEY for OpenAI models (i.e. gpt-4o) or ANTHROPIC_API_KEY for Anthropic models (i.e. claude-sonnet-4-5). For full list of possible integrations, please check out these Langchain docs (and make sure to install langchain package for given provider using uv if you're using provider other than OpenAI or Anthropic).

The easiest way to use the tool is to add these 2 API keys to the .env file located where the cli is used:

# .env
TAVILY_API_KEY=...
OPENAI_API_KEY=...
ANTHROPIC_API_KEY=...

For extended debugging and tool usage metrics, please consider adding these Langsmith related variables:

# .env
LANGSMITH_TRACING=...
LANGSMITH_ENDPOINT=...
LANGSMITH_API_KEY=...
LANGSMITH_PROJECT=...

Configuration options

The CLI runs an interactive script that allows user to configure everything and define the problem:

Option Type Description Default Required
Project root str Path to the root of the project (needs to be a valid directory) Current directory Yes
Guideline files List[str] Optional list of guideline files. If no guidelines files are specified at this point, agent will suggest all relevant files to the user. - No
Task str Predefined goal to achieve by the agent. If task is not defined, agent will suggest some tasks to the user. - No
Model str LLM model to be used as a core reasoning model. For a full list of available models check out these Langchain docs anthropic:claude-sonnet-4-5 No

The script allows for optional, extended model configuration as well:

Option Type Description Default Required
Temperature float Controls randomness of the model. Must be a number between 0.0 and 1.0 Model's default value No
Max output tokens int Max output tokens of the model. Model's default value No
Timeout int Timeout for LLM calls in seconds. Model's default value No
Max retries int Max number of retries for LLM calls. Model's default value No

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