Introduction
Introduction to gollm
gollm is a powerful Go package designed to simplify and streamline interactions with various Large Language Model (LLM) providers. It offers a unified, flexible, and feature-rich interface for AI engineers and developers to work with multiple LLM APIs efficiently.
Key Features
Unified API for Multiple LLM Providers: gollm supports various providers, including OpenAI and Anthropic, allowing you to switch between models like GPT-4, GPT-3.5-turbo, and Claude seamlessly.
Easy Provider and Model Switching: Configure your preferred provider and model with simple function calls, making it effortless to experiment with different LLMs.
Flexible Configuration Options: Set up your LLM interactions using environment variables, code-based configuration, or configuration files to suit your project's needs.
Advanced Prompt Engineering: Create sophisticated prompts with context, directives, output specifications, and examples to guide the LLM's responses effectively.
Memory Retention: Maintain context across multiple interactions for more coherent conversations.
Structured Output and Validation: Generate and validate JSON schemas for structured outputs, ensuring consistency and reliability in LLM responses.
Provider Comparison Tools: Easily compare responses from different LLM providers and models for the same prompt, helping you choose the best option for your use case.
High-Level AI Functions: Utilize pre-built functions like ChainOfThought for complex reasoning tasks.
Robust Error Handling and Retries: Built-in retry mechanisms with customizable delays to handle API rate limits and transient errors gracefully.
Extensible Architecture: Designed to be easily extended to support new LLM providers and features.
Debug Logging: Configurable debug levels to help you troubleshoot and optimize your LLM interactions.
Real-World Applications
gollm is versatile enough to handle a wide range of AI-powered tasks, including:
Content Creation Workflows: Generate research summaries, article ideas, and refined paragraphs for writing projects.
Complex Reasoning Tasks: Use the ChainOfThought function to break down and analyze complex problems step-by-step.
Structured Data Generation: Create and validate complex data structures with customizable JSON schemas.
Model Performance Analysis: Compare different models' performance for specific tasks to optimize your AI pipeline.
Whether you're building sophisticated AI applications or just getting started with LLMs, gollm provides the tools and flexibility you need to interact with language models effectively and efficiently. Its intuitive API and robust feature set make it an invaluable asset for any Go developer working with AI and natural language processing.
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