Add examples of using Fields and EnvAuthStrategy to developer documen…

…tation (#1056) * Add example of using fields for configuration. I have created this example based on some delving into the code and looking at examples of some of the community providers. I haven't included the IntegerField, as I couldn't get it to work properly, suggesting that I don't understand it properly, whereas I have successfully tested the TextField and MultilineTextField. * Add example of using the EnvAuthStrategy to provide API Keys * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Combined sections for API Keys and for Fields into a single section. As per review feedback, combined the two sections and examples for brevity. Also added a couple of missing imports to the example. * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113 pre-commit-ci[bot]@users.noreply.github.com>
jupyterlab · Oct 31, 2024 · bafccef · bafccef
1 parent ec34146
commit bafccef
Showing 1 changed file with 55 additions and 0 deletions.
diff --git a/docs/source/developers/index.md b/docs/source/developers/index.md
@@ -121,6  121,61 @@ your new provider's `id`:
 [LLM]: https://api.python.langchain.com/en/v0.0.339/llms/langchain.llms.base.LLM.html#langchain.llms.base.LLM
 [BaseChatModel]: https://api.python.langchain.com/en/v0.0.339/chat_models/langchain.chat_models.base.BaseChatModel.html
 
 ### API keys and fields for custom providers
 
 You can add handle authentication via API keys, and configuration with
 custom parameters using an auth strategy and fields as shown in the example
 below.
 
 ```python
 from typing import ClassVar, List
 from jupyter_ai_magics import BaseProvider
 from jupyter_ai_magics.providers import EnvAuthStrategy, Field, TextField, MultilineTextField
 from langchain_community.llms import FakeListLLM
 
 
 class MyProvider(BaseProvider, FakeListLLM):
     id = "my_provider"
     name = "My Provider"
     model_id_key = "model"
     models = [
         "model_a",
         "model_b"
     ]
 
     auth_strategy = EnvAuthStrategy(
         name="MY_API_KEY", keyword_param="my_api_key_param"
     )
 
     fields: ClassVar[List[Field]] = [
         TextField(key="my_llm_parameter", label="The name for my_llm_parameter to show in the UI"),
         MultilineTextField(key="custom_config", label="Custom Json Config", format="json"),
     ]
 
     def __init__(self, **kwargs):
         model = kwargs.get("model_id")
         kwargs["responses"] = (
             ["This is a response from model 'a'"]
             if model == "model_a" else
             ["This is a response from model 'b'"]
         )
         super().__init__(**kwargs)
 ```
 
 The `auth_strategy` handles specifying API keys for providers and models.
 The example shows the `EnvAuthStrategy` which takes the API key from the
 environment variable with the name specified in `name` and be provided to the
 model's `__init__` as a kwarg with the name specified in `keyword_param`.
 This will also cause a field to be present in the configuration UI with the
 `name` of the environment variable as the label.
 
 Further configuration can be handled adding `fields` into the settings
 dialogue for your custom model by specifying a list of fields as shown in
 the example.  These will be passed into the `__init__` as kwargs, with the
 key specified by the key in the field object. The label specified in the field
 object determines the text shown in the configuration section of the user
 interface.
 
 ### Custom embeddings providers
 
 To provide a custom embeddings model an embeddings providers should be defined implementing the API of `jupyter-ai`'s `BaseEmbeddingsProvider` and of `langchain`'s [`Embeddings`][Embeddings] abstract class.