GraphCanon
Home/LLM Frameworks/langchain-chat-websockets
langchain-chat-websockets logo

langchain-chat-websockets

Enrichment pending
pors/langchain-chat-websockets

LangChain LLM chat with streaming response over websockets

GitHub

GraphCanon updated today · GitHub synced today

97
Stars
8
Forks
3
Open issues
2
Watchers
2y
Last push
HTML Apache-2.0Created May 2, 2023

Trust & integrity

Full report
Maintenance
Dormant (954d since push)
As of today · Source: github_public_v1
Provenance
Not a fork · Personal account
As of today · Source: github_public_v1
Security (OSV)
50 low (50 low)
As of today · Source: osv@v1

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

Overview

LangChain LLM chat with streaming response over websockets

Capability facts

Deploy
Self-host

Source: dockerfile:Dockerfile · Jul 11, 2026

Docker
Dockerfile present

Source: dockerfile:Dockerfile · Jul 11, 2026

Languages
html

Source: github.language · Jul 11, 2026

Categories

LLM FrameworksComputer Vision

Compatibility

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

LangChain integrationLangChain

Source: README excerpt (regex_v1, Jul 11, 2026)

To run the LangChain chat application using Docker Compose, follow these steps:
Source link
OpenAI APIOpenAI API

Source: README excerpt (regex_v1, Jul 11, 2026)

3. Open the newly created `.env` file in a text editor and add your OpenAI API key:
Source link

Tags

llmfastapiopenaiopenai-apiopenai-chatgptasynclangchainlangchain-python

README

Run with Docker Compose

To run the LangChain chat application using Docker Compose, follow these steps:

  1. Make sure you have Docker installed on your machine.

  2. Create a file named .env file

  3. Open the newly created .env file in a text editor and add your OpenAI API key:

    OPENAI_API_KEY=your_openai_api_key_here

    Replace your_openai_api_key_here with your actual OpenAI API key.

  4. Run the following command to build the Docker image and start the FastAPI application inside a Docker container:

    docker-compose up --build

  5. Access the application at http://localhost:8000.

Thanks to @hwchase17 for showing the way in chat-langchain