# Potpie — Spec-Driven Development for Large Codebases

> An open-source AI development platform that uses specification-driven workflows and knowledge graphs to help developers understand and modify large codebases efficiently.

## Install

Save as a script file and run:

# Potpie — Spec-Driven Development for Large Codebases

## Quick Use
```bash
# Install Potpie CLI
pip install potpie

# Index your codebase
potpie index ./my-project

# Ask questions or generate specs
potpie chat "How does the authentication flow work?"
```

## Introduction
Potpie is an open-source AI development platform that builds a knowledge graph of your codebase to enable spec-driven development. It helps developers understand complex codebases, generate implementation specifications, and make changes with full context awareness across large projects.

## What Potpie Does
- Builds a knowledge graph from your source code for deep context
- Answers questions about codebase architecture and implementation details
- Generates implementation specifications before writing code changes
- Provides specialized AI agents for debugging, testing, and code review
- Supports custom agent creation for project-specific workflows

## Architecture Overview
Potpie parses your codebase into an abstract syntax tree and builds a graph representation capturing relationships between modules, classes, functions, and data flows. This knowledge graph powers RAG-based retrieval for AI agent conversations. The system uses multiple specialized agents that can be composed for complex multi-step development tasks.

## Self-Hosting & Configuration
- Install via pip and run the indexer against your repository
- Configure LLM provider credentials for the AI agents
- Set indexing scope to include or exclude specific directories
- Deploy the web dashboard for team-wide codebase exploration
- Customize agent behaviors through configuration files

## Key Features
- Knowledge graph that captures code relationships beyond text search
- Spec-first workflow ensuring changes are planned before implementation
- Multiple specialized agents (debug, test, review, explain)
- Works with any programming language through AST parsing
- Self-hosted with full control over your code and data

## Comparison with Similar Tools
- **Cursor** — IDE-integrated AI, but no persistent knowledge graph
- **Sourcegraph Cody** — code search with AI, less focus on spec-driven flow
- **Aider** — terminal AI coding, no knowledge graph or spec workflow
- **Continue** — IDE extension, less structured approach to large codebases
- **CodeRabbit** — focused on PR review, not codebase exploration

## FAQ
**Q: Which programming languages are supported?**
A: Potpie supports major languages through tree-sitter parsing including Python, TypeScript, Java, Go, and Rust.

**Q: Does it send my code to external services?**
A: Code stays local during indexing. Only relevant context snippets are sent to the configured LLM provider during queries.

**Q: How large a codebase can it handle?**
A: The knowledge graph approach scales to repositories with hundreds of thousands of lines.

**Q: Can I create custom AI agents?**
A: Yes. You can define custom agents with specific tools and instructions for your project needs.

## Sources
- https://github.com/potpie-ai/potpie

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Source: https://tokrepo.com/en/workflows/potpie-spec-driven-development-large-codebases-918d2073
Author: Script Depot