GraphCanon
Home/LLM Frameworks/langchain-chatbot
langchain-chatbot logo

langchain-chatbot

Enrichment pending
minhbtrc/langchain-chatbot

This code is an implementation of a chatbot using LLM chat model API and Langchain.

GitHub

GraphCanon updated today · GitHub synced today

63
Stars
11
Forks
0
Open issues
6
Watchers
1y
Last push
Python MITCreated Oct 2, 2023

Trust & integrity

Full report
Maintenance
Dormant (472d since push)
As of today · Source: github_public_v1
Provenance
Not a fork · Personal account
As of today · Source: github_public_v1
Security (OSV)
No lockfile
As of today · Source: none

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

Overview

This code is an implementation of a chatbot using LLM chat model API and Langchain.

Capability facts

Deploy
Self-host

Source: dockerfile:Dockerfile · Jul 11, 2026

Docker
Dockerfile present

Source: dockerfile:Dockerfile · Jul 11, 2026

Languages
python

Source: github.language · Jul 11, 2026

Categories

LLM FrameworksInference & Serving

Compatibility

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

LangChain integrationLangChain

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

1. Clone repo: `git clone https://github.com/btrcm00/chatbot-with-langchain.git`
Source link
Node.js runtimeNode.js

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

2. Install packages: `npm install`
Source link
OpenAI APIOpenAI API

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

# Edit the .env file to add your OpenAI API key
Source link
Python runtimePython

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

1. `python -m spacy download en_core_web_md`
Source link

Tags

lcelllmlangsmithgpt-4langservelangchainchatbotgradio

README

Quick Start with Setup Script

The easiest way to run the entire application is using our setup script:

  1. Make the script executable:

    chmod +x setup.sh

  2. Run the setup script:

    ./setup.sh

  3. Follow the prompts:

    • The script will create necessary .env files if they don't exist
    • Choose between Docker Compose deployment or local development
    • The script will guide you through the rest of the setup process

For Windows users, use setup.bat instead.

Quick Start with Docker Compose Manually

If you prefer to run the commands manually:

  1. Set up environment variables:

    # For backend
cp backend/.env.example backend/.env
# Edit the .env file to add your OpenAI API key

# For frontend
cp frontend/.env.example frontend/.env

  2. Start the application:

    docker-compose up -d

  3. Access the application:

  4. Stop the application:

    docker-compose down

Running Locally (without Docker)

  1. Download the models for the languages to use in anonymizer. PII support.
    1. python -m spacy download en_core_web_md
  2. RUN backend
    1. Clone repo: git clone https://github.com/btrcm00/chatbot-with-langchain.git
    2. Add google-cloud-platform credential file to secure/vertexai.json or set up OpenAI API key
    3. cd backend
    4. Install required packages: pip install -r requirements.txt
    5. Create MongoDB database and config environment variables to connect Mongo
    6. Run: python -m uvicorn backend.main:app --reload --host 0.0.0.0 --port 8080
  3. RUN frontend
    1. cd frontend
    2. Install packages: npm install
    3. Start frontend: npm run dev