80 lines
1.7 KiB
Markdown
80 lines
1.7 KiB
Markdown
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---
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title: SambaNova
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description: Use Instructor with SambaNova's LLM API for structured outputs.
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---
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## See Also
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- [Getting Started](../getting-started.md) - Quick start guide
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- [from_provider Guide](../concepts/from_provider.md) - Detailed client configuration
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- [Provider Examples](../index.md#provider-examples) - Quick examples for all providers
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- [Enterprise Integration](../examples/index.md#enterprise-integration) - More enterprise examples
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# SambaNova Integration
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Instructor supports SambaNova's LLM API, allowing you to use structured outputs with their models.
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## Installation
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```bash
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pip install "instructor[openai]"
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```
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## Basic Usage
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```python
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import instructor
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from pydantic import BaseModel
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client = instructor.from_provider("sambanova/Meta-Llama-3.1-405B-Instruct")
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class User(BaseModel):
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name: str
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age: int
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user = client.create(
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messages=[
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{"role": "user", "content": "Ivan is 28"},
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],
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response_model=User,
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)
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print(user)
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# > User(name='Ivan', age=28)
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```
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## Async Usage
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```python
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import instructor
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from pydantic import BaseModel
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client = instructor.from_provider(
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"sambanova/Meta-Llama-3.1-405B-Instruct",
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async_client=True,
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)
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class User(BaseModel):
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name: str
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age: int
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async def get_user():
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user = await client.create(
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messages=[
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{"role": "user", "content": "Ivan is 28"},
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],
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response_model=User,
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)
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return user
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# Run with asyncio
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import asyncio
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user = asyncio.run(get_user())
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print(user)
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# > User(name='Ivan', age=28)
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```
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## Available Models
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Check the [SambaNova documentation](https://docs.sambanova.ai/cloud/docs/get-started/supported-models) for the latest model offerings and capabilities.
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