LLM Settings

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import os
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from smallestai.atoms.crew.clients.openai import OpenAIClient
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self.llm = OpenAIClient(
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    model="gpt-4o-mini",
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    temperature=0.7,
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    api_key=os.getenv("OPENAI_API_KEY")
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)

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# Consistent support agent
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self.llm = OpenAIClient(model="gpt-4o-mini", temperature=0.3)
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# Engaging sales agent
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self.llm = OpenAIClient(model="gpt-4o-mini", temperature=0.8)

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import os
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from smallestai.atoms.crew.clients.openai import OpenAIClient
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# Example: Using Groq
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self.llm = OpenAIClient(
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    model="llama-3.1-70b-versatile",
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    base_url="https://api.groq.com/openai/v1",
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    api_key=os.getenv("GROQ_API_KEY")
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)

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async def generate_response(self):
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    response = await self.llm.chat(
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        messages=self.context.messages,
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        stream=True
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    )
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    async for chunk in response:
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        if chunk.content:
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            yield chunk.content

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response = await self.llm.chat(
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    messages=self.context.messages,
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    stream=True,
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    tools=self.tool_registry.get_schemas()
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)

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from openai import RateLimitError, APIError
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async def generate_response(self):
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    try:
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        response = await self.llm.chat(
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            messages=self.context.messages,
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            stream=True
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        )
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        async for chunk in response:
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            if chunk.content:
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                yield chunk.content
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    except RateLimitError:
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        yield "I'm experiencing high demand. Please try again."
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    except APIError as e:
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        logger.error(f"LLM error: {e}")
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        yield "I'm having trouble. Let me try again."

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from smallestai.atoms.models import CreateAgentRequest
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agent = CreateAgentRequest(
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    name="SupportAgent",
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    synthesizer={
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        "provider": "smallest",  # Use Waves
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        "model": "waves_lightning_v2",
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        "voice_id": "zorin",     # Male, professional
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        "speed": 1.0
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    },
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    # ... other config
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)