跳到主要内容
了解如何将 LangChain 与 Predibase 上的模型结合使用。

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设置

  • 创建一个 Predibase 帐户和 API 密钥。
  • 使用 pip install predibase 安装 Predibase Python 客户端
  • 使用您的 API 密钥进行身份验证

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LLM

Predibase 通过实现 LLM 模块与 LangChain 集成。您可以在下面看到一个简短示例，或在 LLM > 集成 > Predibase 下找到完整的笔记本。 
import os
os.environ["PREDIBASE_API_TOKEN"] = "{PREDIBASE_API_TOKEN}"

from langchain_community.llms import Predibase

model = Predibase(
    model="mistral-7b",
    predibase_api_key=os.environ.get("PREDIBASE_API_TOKEN"),
    predibase_sdk_version=None,  # optional parameter (defaults to the latest Predibase SDK version if omitted)
    """
    Optionally use `model_kwargs` to set new default "generate()" settings.  For example:
    {
        "api_token": os.environ.get("HUGGING_FACE_HUB_TOKEN"),
        "max_new_tokens": 5,  # default is 256
    }
    """
    **model_kwargs,
)

"""
Optionally use `kwargs` to dynamically overwrite "generate()" settings.  For example:
{
    "temperature": 0.5,  # default is the value in model_kwargs or 0.1 (initialization default)
    "max_new_tokens": 1024,  # default is the value in model_kwargs or 256 (initialization default)
}
"""
response = model.invoke("Can you recommend me a nice dry wine?", **kwargs)
print(response)
Predibase 还支持 Predibase 托管和 HuggingFace 托管的适配器，这些适配器在由 model 参数给出的基础模型上进行了微调 
import os
os.environ["PREDIBASE_API_TOKEN"] = "{PREDIBASE_API_TOKEN}"

from langchain_community.llms import Predibase

# The fine-tuned adapter is hosted at Predibase (adapter_version must be specified).
model = Predibase(
    model="mistral-7b",
    predibase_api_key=os.environ.get("PREDIBASE_API_TOKEN"),
    predibase_sdk_version=None,  # optional parameter (defaults to the latest Predibase SDK version if omitted)
    adapter_id="e2e_nlg",
    adapter_version=1,
    """
    Optionally use `model_kwargs` to set new default "generate()" settings.  For example:
    {
        "api_token": os.environ.get("HUGGING_FACE_HUB_TOKEN"),
        "max_new_tokens": 5,  # default is 256
    }
    """
    **model_kwargs,
)

"""
Optionally use `kwargs` to dynamically overwrite "generate()" settings.  For example:
{
    "temperature": 0.5,  # default is the value in model_kwargs or 0.1 (initialization default)
    "max_new_tokens": 1024,  # default is the value in model_kwargs or 256 (initialization default)
}
"""
response = model.invoke("Can you recommend me a nice dry wine?", **kwargs)
print(response)
Predibase 还支持在由 model 参数给出的基础模型上进行微调的适配器 
import os
os.environ["PREDIBASE_API_TOKEN"] = "{PREDIBASE_API_TOKEN}"

from langchain_community.llms import Predibase

# The fine-tuned adapter is hosted at HuggingFace (adapter_version does not apply and will be ignored).
model = Predibase(
    model="mistral-7b",
    predibase_api_key=os.environ.get("PREDIBASE_API_TOKEN"),
    predibase_sdk_version=None,  # optional parameter (defaults to the latest Predibase SDK version if omitted)
    adapter_id="predibase/e2e_nlg",
    """
    Optionally use `model_kwargs` to set new default "generate()" settings.  For example:
    {
        "api_token": os.environ.get("HUGGING_FACE_HUB_TOKEN"),
        "max_new_tokens": 5,  # default is 256
    }
    """
    **model_kwargs,
)

"""
Optionally use `kwargs` to dynamically overwrite "generate()" settings.  For example:
{
    "temperature": 0.5,  # default is the value in model_kwargs or 0.1 (initialization default)
    "max_new_tokens": 1024,  # default is the value in model_kwargs or 256 (initialization default)
}
"""
response = model.invoke("Can you recommend me a nice dry wine?", **kwargs)
print(response)
在 GitHub 上编辑此页面源文件。
以编程方式连接这些文档到 Claude、VSCode 等，通过 MCP 获取实时答案。
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