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what is autonomous_web_agent_ fr?

gmanu0077/autonomous_web_agent_ — explained in plain English

Analysis updated 2026-05-18

8PythonAudience · developerLicense

tl;dr

A three-phase autonomous browser agent that maps out a web page's structure first, then either clicks through it or answers questions about it.

vibe map

mindmap
  root((repo))
    What it does
      Controls real browser
      Executes page actions
      Answers page questions
    Tech stack
      Python
      LangGraph
      Pydoll
      Gemini
      Ollama
    Use cases
      Automate web tasks
      Chat with a live page
      Build generic scrapers
    Audience
      Developers
      AI agent builders
    Approach
      Builds DOM graph
      Vector search selectors
      Verifies each step

Code map

Detail Auto

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filefunction / class

what do people make with this?

VIBE 1

Automate multi-step web tasks like filling forms or navigating a site without hard-coded selectors.

VIBE 2

Ask plain-language questions about a web page's content using semantic search.

VIBE 3

Build a general-purpose browser agent that adapts to new sites without site-specific code.

what's the stack?

PythonLangGraphPydollSeleniumChromaDBGeminiOllama

how it stacks up fr

gmanu0077/autonomous_web_agent_adam-s/car-diagnosisbobholamovic/dudulearnstocode-template
Stars888
LanguagePythonPythonPython
Last pushed2022-01-16
MaintenanceDormant
Setup difficultymoderatemoderate
Complexity3/53/5
Audiencedeveloperresearcherdeveloper

Figures from each repo's GitHub metadata at analysis time.

in plain english

Web Agent Framework, or WAF, is a three phase autonomous agent that controls a real Chrome browser. Given a URL, it can either execute actions on the page, such as clicking buttons, filling forms, and navigating, or answer questions about the page's content. The distinguishing approach is that it does not simply dump raw HTML into an AI model. Instead, it builds a structured graph of every element on the page and queries that graph to find precise selectors before generating any automation code. Phase 1, page preparation, handles the grunt work: dismissing cookie banners and popups, scrolling to reveal hidden content, and building a graph of every DOM node on the page, which is then indexed into a vector store. Phase 2 detects whether the user's request is an action or a question. Phase 3a, action mode, uses the DOM graph to find relevant selectors, asks an LLM to generate targeted Python code using Pydoll or Selenium, runs it against the live browser, then verifies the result and retries if it failed. Phase 3b, chat mode, answers plain language questions about the page using semantic search over the indexed DOM nodes. The AI backbone supports Google Gemini or a locally running Ollama model. The pipeline is built on LangGraph. The project is written in Python. The full README is longer than what was shown.

prompts (copy fr)

prompt 1
Set up gmanu0077/autonomous_Web_agent_ to run an action against a given URL and explain the phase it goes through.
prompt 2
Explain how the DOM graph and node RAG work together to find selectors in this repo's Phase 1 and Phase 3a.
prompt 3
Configure this framework to use Ollama locally instead of Gemini for the LLM backbone.

Frequently asked questions

what is autonomous_web_agent_ fr?

A three-phase autonomous browser agent that maps out a web page's structure first, then either clicks through it or answers questions about it.

What language is autonomous_web_agent_ written in?

Mainly Python. The stack also includes Python, LangGraph, Pydoll.

Who is autonomous_web_agent_ for?

Mainly developer.

peek the repo → explain another one

This repo across BitVibe Labs

double-check against the repo, no cap.