pb-dolphin 0.1.9

Full-stack AI enablement platform

🐬 dolphin

⚠️ EXPERIMENTAL - This is a developmental library under active development. APIs and interfaces are unstable and subject to change without notice.

A semantic code search and knowledge management system with AI-native interfaces (MCP, REST API, CLI).

Quick Start

Installation

# Install from PyPI
uvx install pb-dolphin

# ⚠️ IMPORTANT: Ensure OPENAI_API_KEY is set as env var

Basic Usage

# Initialize global knowledge store and index a repository
dolphin init
dolphin add-repo my-project /path/to/project
dolphin index my-project

# Search your indexed code
dolphin search "authentication logic"

# Start API server
dolphin serve

Core Commands

• dolphin init - Initialize configuration (auto-creates ~/.dolphin/config.toml)
• dolphin init --repo - Create repo-specific config in current directory
• dolphin add-repo <name> <path> - Register a repository for indexing
• dolphin index <name> - Index a repository with language-aware chunking
• dolphin search <query> - Search indexed code semantically
• dolphin serve - Start REST API server (port 7777)
• dolphin config --show - Display current configuration

Architecture

High-Level Overview

┌──────────────────────────────────────────┐
│   AI Interfaces (Claude, Continue, etc)  │
└──────────────┬───────────────────────────┘
               │ MCP Protocol
               ▼
┌──────────────────────────────────────────┐
│          Dolphin Knowledge Base          │
│  ┌─────────────┐    ┌────────────────┐  │
│  │ MCP Bridge  │◄──►│ REST API       │  │
│  │ (TypeScript)│    │ (Python/FastAPI)│  │
│  └─────────────┘    └────────┬────────┘  │
└──────────────────────────────┼───────────┘
                               │
               ┌───────────────┴────────────┐
               ▼                            ▼
          ┌─────────┐                ┌──────────┐
          │LanceDB  │                │ SQLite   │
          │(Vectors)│                │(Metadata)│
          └─────────┘                └──────────┘

Key Features

• Language-Aware Chunking - Intelligent code parsing for Python, TypeScript, JavaScript, Markdown
• Semantic Search - OpenAI embeddings with LanceDB vector storage
• MCP Support - Native Model Context Protocol integration for Claude Desktop
• REST API - FastAPI server with search, retrieval, and metadata endpoints
• Unified CLI - Single dolphin command for all operations
• Auto-Configuration - Smart config hierarchy (repo → user → defaults)

Environment Variables

Dolphin requires the following environment variables depending on your usage:

Required for OpenAI Embeddings

# Required when using OpenAI embeddings (recommended for production)
export OPENAI_API_KEY="sk-your-openai-api-key-here"

Getting Your OpenAI API Key

1. Visit OpenAI Platform
2. Sign up or log in to your account
3. Navigate to API Keys
4. Click "Create new secret key"
5. Copy the key and set it as OPENAI_API_KEY

Configuration

Dolphin uses a multi-level configuration system:

1. Repo-specific (./.dolphin/config.toml) - Per-repository chunking settings
2. User-global (~/.dolphin/config.toml) - Auto-created on first use

Example Config

# ~/.dolphin/config.toml
default_embed_model = "large"  # or "small"

[embedding]
provider = "openai"
batch_size = 100

[retrieval]
top_k = 8
score_cutoff = 0.15

Claude Desktop Integration (MCP)

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "dolphin": {
      "command": "bun",
      "args": ["run", "/path/to/dolphin/mcp-bridge/src/index.ts"],
      "env": {
        "OPENAI_API_KEY": "sk-..."
      }
    }
  }
}

Start the server: dolphin serve

Available MCP tools: search_knowledge, fetch_chunk, fetch_lines, get_vector_store_info

REST API

# Start server
dolphin serve

# Search
curl -X POST http://127.0.0.1:7777/v1/search \
  -H "Content-Type: application/json" \
  -d '{"query": "authentication", "top_k": 5}'

# List repositories
curl http://127.0.0.1:7777/v1/repos

# Health check
curl http://127.0.0.1:7777/v1/health

Development Status

Current: Pre-alpha (0.1.x)

• ✅ Core indexing and search pipeline
• ✅ Language-aware chunking (Python, TS, JS, Markdown)
• ✅ REST API with MCP bridge
• ⚠️ Developmental stage

Upcoming:

• Performance optimization
• Production hardening
• Evaluation framework
• Expanded language support

Requirements

• Python ≥3.12
• OpenAI API key (for embeddings)
• Bun (for MCP bridge)
• Git (for repository scanning)

Testing

# Run all tests
uv run pytest

# Run specific test suite
uv run pytest tests/unit/
uv run pytest tests/integration/

License

MIT License

Acknowledgments

Built with LanceDB, OpenAI, FastAPI, and Bun

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⚠️ Remember: This is experimental software under active development. Use at your own risk.