McGill-NLP/webllama

Health v2 · maintenance only

Adoption not part of the score

1402 stars · 102 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

WebLlama is a framework for building Llama-3-powered agents that browse the web by following natural language instructions and dialogue. It includes training scripts, evaluation benchmarks (WebLINX), datasets, and deployment integrations with Playwright, Selenium, and BrowserGym.

Use cases

• build an agent that browses the web for me
• train an LLM on web navigation tasks
• evaluate a model on real-world website navigation
• fine-tune Llama 3 on browser interaction data
• automate web browsing via dialogue instructions
• integrate LLM agents with Playwright or Selenium

When to choose

• you want to build or fine-tune LLM agents for web navigation
• you need the WebLINX benchmark or curated web interaction datasets
• you want a research-grade starting point for dialogue-driven browsing agents

When to avoid

• you need a production-ready, turnkey browser automation tool
• you only need simple scraping without an LLM agent
• you cannot run or fine-tune 8B-scale models

Facets

framework · maturity active

agent-framework llm-training machine-learning web-scraping chatbot large-language-models web-development machine-learning python cross-platform llama-3 web-navigation weblinx browser-automation dialogue-agents playwright selenium ai-agents natural-language-processing

Member repositories

For agents

markdown · JSON · MCP: product_card(name="McGill-NLP/webllama")