yoheinakajima / instagraph

Converts text input or URL into knowledge graph and displays
MIT License
3.27k stars 281 forks source link

Note for non-coders: you can sign up for the waitlist at instagraph.ai.

InstaGraph 🌐

Hello there, adventurous coder! Welcome to InstaGraph, your go-to application for converting text or URLs into insightful knowledge graphs. Curious about the relationships between entities in a complex topic? Feed the text to InstaGraph and voila! A beautiful knowledge graph is at your fingertips.

See example flowcharts generated by InstaGraph here.

Powered by OpenAI's GPT-3.5, this Flask application turns your text into a vividly colored graph, making it easier to visualize relationships between various entities. Enough talking—let's get started!

Author's TL;DR: If you're just looking for how the knowledge graph is generated, check out the function call parameters taking up half of main.py.

Table of Contents 📚

Features 🌟

Installation 🛠️

To get started, you'll need Python and pip installed.

1. Clone the repository

git clone https://github.com/yoheinakajima/instagraph.git

2. Navigate to the project directory

cd instagraph

3. Install the required Python packages

pip install -r requirements.txt

4. Set up your OpenAI API Key

Change .env.example to .env

mv .env.example .env

Add your OpenAI API key to .env file:

OPENAI_API_KEY=your-api-key-here
Optional - Set a Graph Database

Use: [--graph neo4j|falkordb] to select the Graph Database driver

Add Neo4J username, password and URL in the *.env file as well by creating an instance of neo4j.

NEO4J_USERNAME=
NEO4J_PASSWORD=
NEO4J_URI=

Add FalkorDB URL in the *.env file as well by creating an instance of FlakorDB.

FALKORDB_URL=

5. Run the Flask app

python main.py [--graph neo4j|falkordb] [--port port] [--debug]

Navigate to http://localhost:8080 to see your app running.

Run as Container

1. Clone the repository

git clone https://github.com/yoheinakajima/instagraph.git

2. Navigate to the project docker directory

cd instagraph/docker

3.1 Run in Dev mode

docker-compose -f docker-compose-dev.yml up # Add -d flag at the end to run in background/daemon mode.

3.2 Run in Prod - Create the docker image

docker-compose -f docker-compose.yml up --build -d

Usage 🎉

Web Interface

API Endpoints

  1. GET Response Data: /get_response_data

    • Method: POST
    • Data Params: {"user_input": "Your text here"}
    • Response: GPT-3.5 processed data
  2. GET Graph Data: /get_graph_data

    • Method: POST
    • Response: Graph Data
  3. GET History Data: /get_graph_history

    • Method: GET
    • Response: Graph Data

Contributing 🤝

Best way to chat with me is on Twitter at @yoheinakajima. I usually only code on the weekends or at night, and in pretty small chunks. I have lots ideas on what I want to add here, but obviously this would move faster with everyone. Not sure I can manage Github well given my time constraints, so please reach out if you want to help me run the Github. Now, here are a few ideas on what I think we should add based on comments...

There are a lot of "build a chart" tools out there, so instead of doing user account and custom charts, it sounds more fun for me to work on building the largest knowledge graph ever...

Before creating an Issue please refer the ISSUE_TEMPLATE provided.

License 📝

MIT License. See LICENSE for more information.


Enjoy using InstaGraph! 🎉