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Virgo

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Virgo is a command-line assistant that helps you generate, review, and improve articles. It blends retrieval (Tavily), reasoning (LangChain + LangGraph), and drafting (OpenAI) into a guided flow so you can go from idea to polished copy quickly.

Quickstart

  1. Install (from PyPI):
pip install virgo-agent

# Optional: add Ollama provider support
pip install "virgo-agent[ollama]"
  1. Configure your environment (see next section), then run:
virgo --help

Environment

Set these variables before running Virgo:

Variable Required Purpose
OPENAI_API_KEY Yes Drafting, rewrites, and reviews via OpenAI models
TAVILY_API_KEY Yes Web research to gather facts and sources
LANGSMITH_API_KEY Optional Observability and tracing via LangSmith
LANGSMITH_TRACING Optional Enable LangSmith tracing (true/false)
LANGSMITH_ENDPOINT Optional Override LangSmith endpoint
LANGSMITH_PROJECT Optional LangSmith project name
VIRGO_GENAI_PROVIDER Optional openai (default) or ollama
VIRGO_MODEL_NAME Optional Model name for the chosen provider (default gpt-4-turbo)
VIRGO_MAX_ITERATIONS Optional Max tool iterations the agent will run (default 5)
OLLAMA_MODEL Optional Model name for local integration tests (e.g., llama3.2:1b)
OLLAMA_BASE_URL Optional Ollama base URL (e.g., http://localhost:11434)

Tips:

  • Put secrets in a local .env (not committed) or manage them via mise.
  • Python requirement: 3.14 (pre-release builds are fine).

How It Works (High-Level)

  • LangChain orchestrates LLM calls and tool usage for drafting and review steps.
  • LangGraph wires these steps into a controllable graph: gather context → draft → critique → refine.
  • Tavily performs targeted web searches to pull fresh facts and references.
  • OpenAI provides the language model for generation and editing.
  • Ollama can be used as an alternative model provider when installed (virgo-agent[ollama]) and selected via VIRGO_GENAI_PROVIDER=ollama.
  • Rich and Typer power the CLI experience (progress, prompts, commands).

Workflow overview:

  1. You provide a topic and intent via the CLI.
  2. Virgo runs Tavily searches to collect supporting context.
  3. LangGraph coordinates drafting with OpenAI, then runs critique/refinement passes.
  4. The final article is returned with suggested improvements and sources.

Common Commands

  • Show help: virgo --help
  • Generate/review (example): virgo generate "AI safety"

For Contributors

Developer tooling uses uv for fast installs:

  • Install deps: uv sync --group dev

  • Lint: uv run task lint:ci

  • Format check: uv run task format:ci

  • Type check: uv run task type-check

  • Tests with coverage: uv run pytest tests --cov=virgo --cov-report=term-missing

  • Integration tests (needs Docker + Ollama):

    docker compose -f docker-compose.development.yaml up -d --build
    uv run task integration
    docker compose -f docker-compose.development.yaml down
    

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