workflowstacks
ai-agent

SlashGPT

275 stars38 forksJupyter NotebookUpdated 5/12/2026100% free · open source
What it does

SlashGPT is an AI-powered chatbot that allows users to interact with a language model using a Jupyter Notebook interface, enabling them to build, train, and deploy conversational interfaces

When to use it
  • •Building a conversational interface for a startup's customer support
  • •Creating a chatbot for a specific domain or industry
  • •Prototyping and testing language models for various applications
Ready-to-paste prompt
slash_gpt.generate_response('Explain the concept of natural language processing and its applications')
Heads up: Make sure you have the necessary dependencies installed, including `transformers` and `torch`, and that you have a compatible Python version (Python 3.8 or higher) to avoid compatibility issues
Saves to your device
Use with Claude
New

Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.

🔑 Needs an API key

Works after you add credentials — the setup agent will ask you for them.

Try it instantly — no install
Claude Code
mkdir -p ~/.claude/skills/slashgpt && curl -fsSL https://workflowstacks.com/api/skills/slashgpt/claude-skill -o ~/.claude/skills/slashgpt/SKILL.md
Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)
claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

Adds a WorkflowStacks connector to Claude Code: search and load any skill here by chatting.

How SlashGPT works
Codeflow
Free to inspect

SlashGPT is a medium Jupyter Notebook project (~6.6k lines across 74 code files, plus 10 test files). Setup is light: runs with Docker — add your API keys to .env. Last commit 4 months ago, MIT license, has a test suite.

Size
Medium codebase
~6.6k lines · 74 code files · 55 min skim
Setup
Light setup
Runs with Docker — add your API keys to .env.
Runs on
Python · Docker
Needs API keys (.env)
Jupyter Notebook 68%Python 28%HTML 3%
Where to start reading
  1. 1
    README.md
    Start here — what it does and how to install it
  2. 2
    server.py
    Where the program starts running
  3. 3
    pyproject.toml
    Dependencies and the commands it exposes
  4. 4
    .env.example
    The API keys and settings you must provide
  5. 5
    src/slashgpt/__init__.py
    Inside src/ — the main logic begins here
What's in each folder
src/Core code — the actual logic44 files
plugins/Sub-packages / plugins3 files
samples/Examples you can copy14 files
docs/Documentation3 files
templates/Templates1 files
manifests/Folder120 files
resources/Folder47 files
notebooks/Research & notebooks6 files
READMEHas testsDocumentedCI checksDocker readyExamples includedMIT licenseUpdated 4 mo ago
Quick Actions
Details
Creator
receptron
Language
Jupyter Notebook
Category
ai-agent
Published
4/19/2023

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