harvester-sdk 1.0.2

Harvester SDK - The Complete AI Processing Platform. Unified interface for all AI processing paradigms with enterprise-grade reliability.

🚀 Harvester SDK - Complete AI Processing Platform

"The unified interface for all AI providers with enterprise-grade reliability."

🌟 What is Harvester SDK?

Harvester SDK is a comprehensive AI processing platform that provides a unified interface to all major AI providers. Whether you need text generation, image creation, batch processing, or real-time conversations, Harvester SDK handles the complexity so you can focus on building.

⚡ Key Features

• Multi-Provider Support - OpenAI, Anthropic, Google AI Studio, Vertex AI, XAI, DeepSeek
• Dual Authentication - API keys (GenAI) and service accounts (Vertex AI)
• Turn-Based Chat - Non-streaming conversations with any model
• Batch Processing - Cost-effective bulk operations with 50% savings
• Template System - AI-powered code transformation
• Image Generation - DALL-E, Imagen, GPT Image support
• Enterprise Ready - Rate limiting, retries, error handling

🚀 Quick Start

Installation

# Install the SDK
pip install harvester-sdk

# Install with all providers
pip install harvester-sdk[all]

# Install specific providers
pip install harvester-sdk[openai,anthropic,genai]

Basic Usage

# Main CLI conductor
harvester --help

# Turn-based conversation (non-streaming)
harvester message --model gemini-2.5-flash
harvester message --model claude-sonnet-4-20250514 --system "You are a helpful assistant"

# Batch processing from CSV
harvester batch data.csv --model gpt-4o --template quick

# Process directory with templates
harvester process ./src --template refactor --model gemini-2.5-pro

# Generate images
harvester image "A beautiful sunset" --provider dalle3 --size 1024x1024

🔧 Provider Configuration

Google AI Studio (GenAI) - API Key Authentication

export GEMINI_API_KEY=your_api_key
harvester message --model gemini-2.5-flash

Google Vertex AI - Service Account Authentication

export GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account.json
harvester message --model vtx-gemini-2.5-flash

Other Providers

export OPENAI_API_KEY=your_openai_key
export ANTHROPIC_API_KEY=your_anthropic_key
export XAI_API_KEY=your_xai_key
export DEEPSEEK_API_KEY=your_deepseek_key

📋 Available Commands

Core Commands

• harvester message - Turn-based conversations (non-streaming)
• harvester chat - Interactive streaming chat
• harvester batch - Batch process CSV files
• harvester process - Directory processing with templates
• harvester image - Image generation
• harvester search - AI-enhanced web search (Grok)

Utility Commands

• harvester list-models - Show available models
• harvester config --show - Display configuration
• harvester tier - Show license information
• harvester status - Check batch job status

🎯 Model Selection Guide

Google AI Models

API Key (GenAI)	Service Account (Vertex)	Use Case
gemini-2.5-flash	vtx-gemini-2.5-flash	Fast, cost-effective
gemini-2.5-pro	vtx-gemini-2.5-pro	High-quality reasoning
gemini-1.5-flash	vtx-gemini-1.5-flash	Legacy support

Other Providers

• OpenAI: gpt-4o, gpt-4o-mini
• Anthropic: claude-sonnet-4-20250514, claude-opus-4-1-20250805
• XAI: grok-4-0709, grok-3, grok-3-mini
• DeepSeek: deepseek-chat, deepseek-reasoner

💼 Programming Interface

Python SDK Usage

from harvester_sdk import HarvesterSDK

# Initialize SDK
sdk = HarvesterSDK()

# Quick processing
result = await sdk.quick_process(
    prompt="Explain quantum computing",
    model="gemini-2.5-pro"
)

# Batch processing
results = await sdk.process_batch(
    requests=["What is AI?", "Explain ML", "Define neural networks"],
    model="claude-sonnet-4-20250514"
)

# Multi-provider council (get consensus)
consensus = await sdk.quick_council(
    prompt="What is consciousness?",
    models=["gemini-2.5-pro", "claude-sonnet-4-20250514", "gpt-4o"]
)

Provider Factory

from providers.provider_factory import ProviderFactory

# Create provider factory
factory = ProviderFactory()

# Get provider for specific model
provider = factory.get_provider("gemini-2.5-flash")  # -> GenAI provider
provider = factory.get_provider("vtx-gemini-2.5-flash")  # -> Vertex AI provider

# Generate completion
response = await provider.complete("Hello, world!", "gemini-2.5-flash")

🏗️ Architecture

┌─────────────────────────────────────────────────────────┐
│                    HARVESTER SDK                        │
├─────────────────────────────────────────────────────────┤
│                 Main CLI Conductor                      │
│              (harvester command)                        │
├──────────┬──────────┬──────────┬──────────┬────────────┤
│ Message  │  Batch   │ Process  │  Image   │   Search   │
│(Non-str) │   CSV    │   Dir    │   Gen    │ Enhanced   │
├──────────┴──────────┴──────────┴──────────┴────────────┤
│                  Provider Factory                       │
├──────────┬──────────┬──────────┬──────────┬────────────┤
│  GenAI   │ Vertex   │  OpenAI  │Anthropic │    XAI     │
│(API Key) │(Service) │          │          │ DeepSeek   │
└──────────┴──────────┴──────────┴──────────┴────────────┘

🔒 Authentication Methods

Clear Separation for Google Services

Google AI Studio (GenAI):

• ✅ Simple API key: GEMINI_API_KEY
• ✅ Models: gemini-2.5-flash, gemini-2.5-pro
• ✅ Best for: Personal use, quick setup

Google Vertex AI:

• ✅ Service account: GOOGLE_APPLICATION_CREDENTIALS
• ✅ Models: vtx-gemini-2.5-flash, vtx-gemini-2.5-pro
• ✅ Best for: Enterprise, GCP integration

💰 License Tiers

Tier	Features	Max Workers	Providers
Freemium	Basic tools	5	Limited
Professional	Full access	20	All
Premium	Advanced features	75	All + Priority
Enterprise	Unlimited	∞	All + SLA

Check your tier: harvester tier

📖 Examples

Turn-Based Conversation

# Start a conversation with Gemini
harvester message --model gemini-2.5-flash --save

# Chat with Claude
harvester message --model claude-sonnet-4-20250514 --temperature 0.3

# System prompt example
harvester message --model grok-4-0709 --system "You are an expert programmer"

Batch Processing

# Process CSV with AI
harvester batch questions.csv --model gemini-2.5-pro --template analysis

# Directory transformation
harvester process ./legacy_code --template modernize --model claude-sonnet-4-20250514

Image Generation

# DALL-E 3
harvester image "A futuristic city" --provider dalle3 --quality hd

# Imagen 4
harvester image "Abstract art" --provider vertex_image --model imagen-4

🤝 Support & Contributing

• Documentation: Full guides in /docs
• Issues: Report bugs via GitHub issues
• Enterprise: Contact [e-mail]
• License: Commercial - see LICENSE file

🌟 Why Harvester SDK?

1. Unified Interface - One API for all providers
2. Authentication Clarity - Clear separation of auth methods
3. Production Ready - Error handling, retries, rate limiting
4. Flexible Deployment - CLI tools + Python SDK
5. Cost Optimization - Batch processing with 50% savings
6. Multi-Modal - Text, images, and more
7. Enterprise Grade - Licensed, supported, documented

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© 2025 QUANTUM ENCODING LTD
📧 Contact: [e-mail]
🌐 Website: https://quantumencoding.io

The complete AI processing platform for modern applications.