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chatWeb

SkywalkerDarren/chatWeb

ChatWeb can crawl web pages and various document types for content extraction and summarization.

GraphCanon updated 1mo · GitHub synced 1mo

916 stars137 forksLast push 2mo Python MIT

Decision brief

ChatWeb is a Python-based content crawler and summarization chatbot designed for extracting main contents from web pages, PDFs, DOCX, and TXT files. It leverages OpenAI's GPT technology to summarize key points or answer질

Good fit when

  • You need to rapidly extract actionable insights or summaries from multiple sources of data including websites and documents.
  • Your goal is to integrate a conversational interface with content retrieval capabilities leveraging AI for natural language processing tasks.

Avoid when

  • If your use case exclusively involves handling multimedia files like videos or images since ChatWeb is specifically designed for text-based content from web pages and documents.
  • Consider other tools if you are working in an environment where OpenAI services are not accessible or if APIs requiring personal API keys are a concern as this tool relies on the OpenAI API for its N-

Observed Jul 11, 2026 · Source: enrich:decision_facts

Verify the decision

Maintenance and security

Full trust report
Maintenance
Steady (57d since push)
As of 1mo
Provenance
Not a fork · Personal account
As of 1mo
Security (OSV)
No lockfile
As of 1mo

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install chatWeb
PyPI

How it fits your stack(13)

Typed graph edges - alternatives, integrations, successors, and dependencies. Ranked by relationship type, not raw GitHub stars.

Alternative

Integrates

Relationship graph

Optional deeper exploration of typed edges and category neighbours.

Similar tools

Same-category neighbours not already linked as typed edges.

Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

A tool that crawls the web and processes documents to extract main content and summarize key points in response to queries.

Capability facts

Deploy
Self-host

Source: dockerfile:Dockerfile · Jul 22, 2026

Docker
Dockerfile present

Source: dockerfile:Dockerfile · Jul 22, 2026

Languages
python

Source: github.language · Jul 22, 2026

Categories

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

OpenAI APIOpenAI API

Source: README excerpt (regex_v1, Jul 22, 2026)

- Edit `config.json` and set `open_ai_key` to your OpenAI API key
Source link
Python runtimePython

Source: README excerpt (regex_v1, Jul 22, 2026)

- Install Python3
Source link

Tags

README

Manual installation:

  • Install Python3
  • Download this repository by running git clone https://github.com/SkywalkerDarren/chatWeb.git
  • Navigate to the directory by running cd chatWeb
  • Copy config.example.json to config.json
  • Edit config.json and set open_ai_key to your OpenAI API key
  • Install dependencies by running pip3 install -r requirements.txt
  • Start the application by running python3 main.py

Docker:

if you prefer, you can also run this project using docker:

  • build the container using docker-compose build (only needed once when you are not planning to contibute to this repo)
  • copy config.example.json to config.json and set all the needed stuff. The example config is already fine for running with docker, no need to change anything there, if you don't have the OPEN_AI_KEY in your env variables you can set it here too, or later if you run this app.
  • run the container: `docker-compose up"
  • open the application in browser: http://localhost:7860

Install PostgreSQL (Optional)

  • Edit config.json and set use_postgres to true.
  • Install PostgreSQL.
    • The default SQL address is postgresql://localhost:5432/mydb, or you can set it in config.json.
  • Install the pgvector plugin.

Compile and install the extension (support Postgres 11+).

git clone --branch v0.4.0 https://github.com/pgvector/pgvector.git
cd pgvector
make
make install # may need sudo

Then load it in the database you want to use it in

CREATE EXTENSION vector;
  • Install dependency with pip: pip3 install psycopg2

For agents

This page has a .md twin and JSON over the API.

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