SambaNova

SambaNova 的 Sambastudio 是一个运行您自己的开源模型的平台

此示例介绍如何使用 LangChain 与 SambaNova 模型进行交互

SambaStudio

SambaStudio 允许您训练、运行批处理推理作业，以及部署在线推理端点以运行您自己微调的开源模型。

部署模型需要 SambaStudio 环境。在 sambanova.ai/products/enterprise-ai-platform-sambanova-suite 获取更多信息

运行流式预测需要 sseclient-py 包

%pip install --quiet sseclient-py==1.8.0

注册您的环境变量

import os

sambastudio_base_url = "<Your SambaStudio environment URL>"
sambastudio_base_uri = "<Your SambaStudio endpoint base URI>"  # optional, "api/predict/generic" set as default
sambastudio_project_id = "<Your SambaStudio project id>"
sambastudio_endpoint_id = "<Your SambaStudio endpoint id>"
sambastudio_api_key = "<Your SambaStudio endpoint API key>"

# Set the environment variables
os.environ["SAMBASTUDIO_BASE_URL"] = sambastudio_base_url
os.environ["SAMBASTUDIO_BASE_URI"] = sambastudio_base_uri
os.environ["SAMBASTUDIO_PROJECT_ID"] = sambastudio_project_id
os.environ["SAMBASTUDIO_ENDPOINT_ID"] = sambastudio_endpoint_id
os.environ["SAMBASTUDIO_API_KEY"] = sambastudio_api_key

直接从 LangChain 调用 SambaStudio 模型！

from langchain_community.llms.sambanova import SambaStudio

llm = SambaStudio(
    streaming=False,
    model_kwargs={
        "do_sample": True,
        "max_tokens_to_generate": 1000,
        "temperature": 0.01,
        # "repetition_penalty":  1.0,
        # "top_k": 50,
        # "top_logprobs": 0,
        # "top_p": 1.0
    },
)

print(llm.invoke("Why should I use open source models?"))

API 参考：SambaStudio

# Streaming response

from langchain_community.llms.sambanova import SambaStudio

llm = SambaStudio(
    streaming=True,
    model_kwargs={
        "do_sample": True,
        "max_tokens_to_generate": 1000,
        "temperature": 0.01,
        # "repetition_penalty":  1.0,
        # "top_k": 50,
        # "top_logprobs": 0,
        # "top_p": 1.0
    },
)

for chunk in llm.stream("Why should I use open source models?"):
    print(chunk, end="", flush=True)

API 参考：SambaStudio

您还可以调用 CoE 端点专家模型

# Using a CoE endpoint

from langchain_community.llms.sambanova import SambaStudio

llm = SambaStudio(
    streaming=False,
    model_kwargs={
        "do_sample": True,
        "max_tokens_to_generate": 1000,
        "temperature": 0.01,
        "process_prompt": False,
        "select_expert": "Meta-Llama-3-8B-Instruct",
        # "repetition_penalty":  1.0,
        # "top_k": 50,
        # "top_logprobs": 0,
        # "top_p": 1.0
    },
)

print(llm.invoke("Why should I use open source models?"))

API 参考：SambaStudio

相关

• LLM 概念指南
• LLM 操作指南