125 lines
3.3 KiB
Python
125 lines
3.3 KiB
Python
"""Example demonstrating LLMClient usage.
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This example shows how to use LLMClient for simple LLM calls
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without the overhead of an Agent.
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"""
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import asyncio
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from agentlite import LLMClient
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from agentlite.config import AgentConfig, ProviderConfig, ModelConfig
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async def main():
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"""Run LLM client examples."""
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# Example 1: Using simple function interface
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print("=== Example 1: Simple Function ===")
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print("Using llm_complete() function:")
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# Note: This requires a valid API key
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# response = await llm_complete(
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# user_prompt="What is Python?",
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# api_key="your-api-key",
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# model="gpt-4",
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# )
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# print(response)
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print("(Requires API key - uncomment to run)")
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# Example 2: Using configuration-based client
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print("\n=== Example 2: Configuration-Based Client ===")
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config = AgentConfig(
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name="simple_llm",
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system_prompt="You are a helpful coding assistant.",
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providers={
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"openai": ProviderConfig(
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type="openai",
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api_key="your-api-key", # Replace with actual key
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)
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},
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models={
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"gpt4": ModelConfig(
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provider="openai",
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model="gpt-4",
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temperature=0.7,
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),
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"gpt35": ModelConfig(
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provider="openai",
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model="gpt-3.5-turbo",
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temperature=0.5,
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),
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},
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default_model="gpt4",
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)
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# Create client
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LLMClient(config)
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# Make a call
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# response = await client.complete(
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# user_prompt="Explain async/await in Python",
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# )
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# print(f"Response: {response.content}")
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# print(f"Model: {response.model}")
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# if response.usage:
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# print(f"Tokens: {response.usage.total}")
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print("(Requires API key - uncomment to run)")
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# Example 3: Streaming
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print("\n=== Example 3: Streaming ===")
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print("Using llm_stream() function:")
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# async for chunk in llm_stream(
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# user_prompt="Write a haiku about programming",
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# api_key="your-api-key",
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# ):
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# print(chunk, end="")
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print("\n(Requires API key - uncomment to run)")
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# Example 4: Direct provider usage
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print("\n=== Example 4: Direct Provider ===")
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from agentlite import OpenAIProvider
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provider = OpenAIProvider(
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api_key="your-api-key",
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model="gpt-4",
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temperature=0.8,
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)
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LLMClient(provider=provider)
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# response = await client.complete(
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# user_prompt="What are the benefits of type hints?",
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# system_prompt="You are a Python expert.",
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# )
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# print(response.content)
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print("(Requires API key - uncomment to run)")
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# Example 5: Model switching
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print("\n=== Example 5: Model Switching ===")
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# Use default model (gpt4)
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# response1 = await client.complete(user_prompt="Hello!")
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# Switch to different model
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# client_gpt35 = LLMClient(config, model="gpt35")
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# response2 = await client_gpt35.complete(user_prompt="Hello!")
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print("(Requires API key - uncomment to run)")
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print("\n=== Examples Complete ===")
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print("To run these examples:")
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print("1. Set your OpenAI API key")
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print("2. Uncomment the example code")
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print("3. Run: python examples/llm_client_example.py")
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if __name__ == "__main__":
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asyncio.run(main())
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