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By orbruno
Comprehensive toolkit for BAML development: project scaffolding, code generation, testing, framework integration, and Gemini batch processing
npx claudepluginhub orbruno/baml-ccpluginBatch process multiple files through BAML functions using Gemini's API
Create LLM client configuration for BAML
Create a new BAML function with proper structure and types
Create BAML type definitions (class, enum, or alias)
Generate client code from BAML definitions with optional file watching
Automatically regenerate BAML client code when .baml files are modified. Use after any changes to BAML definitions to keep generated code in sync.
Automatically integrate BAML into existing framework projects (React, FastAPI, Express, Django). Use when user wants to use BAML in their application.
Automatically create BAML functions, types, and clients when user describes LLM integration needs. Use when user wants to build LLM functionality without knowing BAML syntax.
Automatically suggest and execute Gemini batch processing when user needs to process many files through BAML functions. Use when user mentions processing multiple documents, PDFs, CSVs, or wants cost-effective LLM processing.
Modifies files
Hook triggers on file write and edit operations
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When calling LLM APIs from Python code. When connecting to llamafile or local LLM servers. When switching between OpenAI/Anthropic/local providers. When implementing retry/fallback logic for LLM calls. When code imports litellm or uses completion() patterns.
AI/ML capabilities including prompt engineering, RAG, and chunking strategies
Workflow development tools
Firebase Genkit expert for production-ready AI workflows with RAG and tool calling
LLM application development with RAG, embeddings, LangChain, and prompt engineering
Intelligent delegation framework for routing tasks to external LLM services while retaining strategic oversight
Toolkit for document extraction using Docling - convert PDFs and HTML into structured, citation-rich JSONL for AI processing pipelines
Personal knowledge management system for organizing files, cataloging literature, and maintaining consistent knowledge architecture. Configurable per-project via .claude/knowledge-management.local.md.
Converts Claude Code plugins into Gemini CLI extensions with full automation
Complete WooCommerce and WordPress API integration for managing sites without the dashboard. Includes backup management, security auditing, and multi-site support.
Execute Gemini-specific workflows: long context processing, image/video analysis, and batch data processing
Comprehensive toolkit for BAML (Boundary ML) development - build type-safe LLM integrations faster with project scaffolding, code generation, testing, and framework integration.
BAML is a domain-specific language for building LLM applications with:
Learn more: BAML Documentation
/baml-toolkit:init - Initialize new BAML project with structure and configuration/baml-toolkit:generate - Generate client code from BAML definitions (with watch mode)/baml-toolkit:test - Run BAML function tests and display results/baml-toolkit:create-function - Scaffold new BAML function with types and prompts/baml-toolkit:create-type - Create BAML type definitions (class, enum, alias)/baml-toolkit:create-client - Configure LLM client (OpenAI, Anthropic, Google, etc.)/baml-toolkit:integrate - Integrate with frameworks (React, FastAPI, Express, Django, etc.)/baml-toolkit:batch-gemini - NEW! Batch process multiple files through BAML functions using GeminiClaude will automatically help with BAML when:
The plugin automatically regenerates client code when you modify .baml files - no manual steps needed!
# Using npm (recommended)
npm install -g @boundaryml/baml
# Or using pip
pip install baml-py
# Install from directory
claude plugin install /Users/orlandobruno/Documents/Dev/baml-toolkit --scope user
# Restart Claude Code to load the plugin
# Check plugin is loaded
claude plugin list
# Should see "baml-toolkit" in the list
Process thousands of documents cost-effectively!
The plugin now includes powerful batch processing capabilities using Google's Gemini API:
# Process 500 invoices for ~$0.50
/baml-toolkit:batch-gemini ExtractInvoice invoices/*.pdf --output results.jsonl
# Classify 1000 reviews for ~$0.08
/baml-toolkit:batch-gemini ClassifyReview reviews.csv --column "text" --output classified.csv
See Batch Processing Examples below!
/baml-toolkit:init my-llm-app
This creates:
my-llm-app/
├── baml_src/
│ ├── main.baml # Your function definitions
│ └── clients.baml # LLM client configurations
├── baml_client/ # Generated code (auto-created)
└── baml.config.json # BAML configuration
# Set your API key
export OPENAI_API_KEY="sk-..."
# Or for Gemini batch processing
export GOOGLE_API_KEY="your-gemini-key"
# Create a client configuration
/baml-toolkit:create-client "GPT4 client for OpenAI"
# Or use Gemini for cost-effective batch processing
/baml-toolkit:create-client "Gemini for batch processing"
/baml-toolkit:create-function "ExtractReceipt that takes an image and returns vendor, items, and total"
Or just describe what you need:
User: "I need to extract contact info from emails"
Claude: [Uses baml-scaffolder skill to create function automatically]
/baml-toolkit:generate --watch
The plugin automatically regenerates code when you edit .baml files!
/baml-toolkit:test ExtractReceipt
/baml-toolkit:integrate react
# or fastapi, express, django, etc.
Create function (automatically done by Claude):
class Receipt {
vendor string
date string
items ReceiptItem[]
total float
}
class ReceiptItem {
name string
quantity int
price float
}