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Getting Started

This guide will help you get up and running with the LLM Client quickly.

1. Installation

The first step is to install the LLM Client. You can do this easily using pip:

pip install llm-client

For more detailed instructions and optional dependencies, see the Installation Guide.

2. Configure API Keys

To use most LLM providers, you will need an API key. Create a secrets.env file in your project directory with your keys:

# OpenAI
OPENAI_API_KEY=sk-xxxxxxxx

# Groq (optional)
GROQ_API_KEY=gsk-xxxxxxxx

# Google Gemini (optional)
GEMINI_API_KEY=AIzaSy-xxxxxxxx

Detailed instructions on how to obtain keys for each provider can be found in the Providers Section.

3. First Example

from llm_client import LLMClient

# Automatic API detection
client = LLMClient()

messages = [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "What is machine learning?"}
]

response = client.chat_completion(messages)
print(response)

Key Concepts

Automatic Provider Selection

The client automatically selects the first available API key:

  1. OpenAI (if OPENAI_API_KEY is set)
  2. Groq (if GROQ_API_KEY is set)
  3. Gemini (if GEMINI_API_KEY is set)
  4. Ollama (Fallback, requires local installation)

Manual Selection

# Force specific provider
client = LLMClient(api_choice="gemini")

# With custom model and parameters
client = LLMClient(
    api_choice="openai",
    llm="gpt-4o",
    temperature=0.5,
    max_tokens=2048
)

Core Features

  • Chat Completion: Standard requests to LLMs.
  • Streaming: Get responses in real-time.
  • Token Counting: Monitor your usage and costs.
  • Provider Switching: Change the API at runtime.
  • Configuration Files: Load settings from YAML or JSON.
  • Async Support: Use async/await for high-performance applications.

Next Steps