From 642d34a0b015dd3252fdd1f9c4f028893e07dfca Mon Sep 17 00:00:00 2001 From: krassowski <5832902+krassowski@users.noreply.github.com> Date: Sun, 29 Oct 2023 14:27:06 +0000 Subject: [PATCH 1/2] Document how to add custom model providers --- docs/source/users/index.md | 90 ++++++++++++++++++- .../jupyter_ai_magics/utils.py | 10 ++- packages/jupyter-ai/jupyter_ai/handlers.py | 2 +- 3 files changed, 96 insertions(+), 6 deletions(-) diff --git a/docs/source/users/index.md b/docs/source/users/index.md index 72b826a67..679eb898a 100644 --- a/docs/source/users/index.md +++ b/docs/source/users/index.md @@ -159,6 +159,94 @@ responsible for all charges they incur when they make API requests. Review your provider's pricing information before submitting requests via Jupyter AI. ::: +### Custom model providers + +You can define a new provider building upon LangChain framework API. The provider +inherit from both `jupyter-ai`'s ``BaseProvider`` and `langchain`'s [``LLM``][LLM]. +You can either import a pre-defined model from [LangChain LLM list][langchain_llms], +or define a [custom LLM][custom_llm]. +In the example below, we demonstrate defining a provider with two models using +a dummy ``FakeListLLM`` model, which returns responses from the ``responses`` +keyword argument. + +```python +# my_package/my_provider.py +from jupyter_ai_magics import BaseProvider +from langchain.llms import FakeListLLM + + +class MyProvider(BaseProvider, FakeListLLM): + id = "my_provider" + name = "My Provider" + model_id_key = "model" + models = [ + "model_a", + "model_b" + ] + 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 provider will be available for both chat and magic usage if it inherits from +[``BaseChatModel``][BaseChatModel] or otherwise only in the magic. + +To plug the new provider you will need declare it via an [entry point](https://setuptools.pypa.io/en/latest/userguide/entry_point.html): + +```toml +# my_package/pyproject.toml +[project] +name = "my_package" +version = "0.0.1" + +[project.entry-points."jupyter_ai.model_providers"] +my-provider = "my_provider:MyProvider" +``` + +To test that the above minimal provider package works, install it with: + +```sh +# from `my_package` directory +pip install -e . +``` + +and restart JupyterLab which now should include a log with: + +``` +[I 2023-10-29 13:56:16.915 AiExtension] Registered model provider `ai21`. +``` + +[langchain_llms]: https://api.python.langchain.com/en/latest/api_reference.html#module-langchain.llms +[custom_llm]: https://python.langchain.com/docs/modules/model_io/models/llms/custom_llm +[LLM]: https://api.python.langchain.com/en/latest/llms/langchain.llms.base.LLM.html#langchain.llms.base.LLM +[BaseChatModel]: https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.BaseChatModel.html + + +### Customising prompt templates + +To modify the prompt template for a given format, override the implementation of ``get_prompt_template`` method: + +```python +from langchain.prompts import PromptTemplate + + +class MyProvider(BaseProvider, FakeListLLM): + # (... properties as above ...) + def get_prompt_template(self, format) -> PromptTemplate: + if format === "code": + return PromptTemplate.from_template( + "{prompt}\n\nProduce output as source code only, " + "with no text or explanation before or after it." + ) + return super().get_prompt_template(format) +``` + ## The chat interface The easiest way to get started with Jupyter AI is to use the chat interface. @@ -689,7 +777,7 @@ Write a poem about C++. You can also define a custom LangChain chain: -``` +```python from langchain.chains import LLMChain from langchain.prompts import PromptTemplate from langchain.llms import OpenAI diff --git a/packages/jupyter-ai-magics/jupyter_ai_magics/utils.py b/packages/jupyter-ai-magics/jupyter_ai_magics/utils.py index c651581bc..0441d707c 100644 --- a/packages/jupyter-ai-magics/jupyter_ai_magics/utils.py +++ b/packages/jupyter-ai-magics/jupyter_ai_magics/utils.py @@ -30,9 +30,10 @@ def get_lm_providers( for model_provider_ep in model_provider_eps: try: provider = model_provider_ep.load() - except: + except Exception as e: log.error( - f"Unable to load model provider class from entry point `{model_provider_ep.name}`." + f"Unable to load model provider class from entry point `{model_provider_ep.name}`: %s.", + e, ) continue if not is_provider_allowed(provider.id, restrictions): @@ -58,9 +59,10 @@ def get_em_providers( for model_provider_ep in model_provider_eps: try: provider = model_provider_ep.load() - except: + except Exception as e: log.error( - f"Unable to load embeddings model provider class from entry point `{model_provider_ep.name}`." + f"Unable to load embeddings model provider class from entry point `{model_provider_ep.name}`: %s.", + e, ) continue if not is_provider_allowed(provider.id, restrictions): diff --git a/packages/jupyter-ai/jupyter_ai/handlers.py b/packages/jupyter-ai/jupyter_ai/handlers.py index ddc4c6255..23b96ad7a 100644 --- a/packages/jupyter-ai/jupyter_ai/handlers.py +++ b/packages/jupyter-ai/jupyter_ai/handlers.py @@ -182,7 +182,7 @@ def broadcast_message(self, message: Message): self.chat_history.append(message) async def on_message(self, message): - self.log.debug("Message recieved: %s", message) + self.log.debug("Message received: %s", message) try: message = json.loads(message) From fa06f169208a6e927824111a5c4b6819e6d42a8e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Micha=C5=82=20Krassowski?= <5832902+krassowski@users.noreply.github.com> Date: Mon, 30 Oct 2023 22:12:02 +0000 Subject: [PATCH 2/2] Apply suggestions from review Co-authored-by: Jason Weill <93281816+JasonWeill@users.noreply.github.com> --- docs/source/users/index.md | 20 +++++++++++--------- 1 file changed, 11 insertions(+), 9 deletions(-) diff --git a/docs/source/users/index.md b/docs/source/users/index.md index 679eb898a..b519f6ea4 100644 --- a/docs/source/users/index.md +++ b/docs/source/users/index.md @@ -161,11 +161,11 @@ provider's pricing information before submitting requests via Jupyter AI. ### Custom model providers -You can define a new provider building upon LangChain framework API. The provider +You can define new providers using the LangChain framework API. Custom providers inherit from both `jupyter-ai`'s ``BaseProvider`` and `langchain`'s [``LLM``][LLM]. You can either import a pre-defined model from [LangChain LLM list][langchain_llms], or define a [custom LLM][custom_llm]. -In the example below, we demonstrate defining a provider with two models using +In the example below, we define a provider with two models using a dummy ``FakeListLLM`` model, which returns responses from the ``responses`` keyword argument. @@ -194,10 +194,11 @@ class MyProvider(BaseProvider, FakeListLLM): ``` -The provider will be available for both chat and magic usage if it inherits from -[``BaseChatModel``][BaseChatModel] or otherwise only in the magic. +If the new provider inherits from [``BaseChatModel``][BaseChatModel], it will be available +both in the chat UI and with magic commands. Otherwise, users can only use the new provider +with magic commands. -To plug the new provider you will need declare it via an [entry point](https://setuptools.pypa.io/en/latest/userguide/entry_point.html): +To make the new provider available, you need to declare it as an [entry point](https://setuptools.pypa.io/en/latest/userguide/entry_point.html): ```toml # my_package/pyproject.toml @@ -216,10 +217,11 @@ To test that the above minimal provider package works, install it with: pip install -e . ``` -and restart JupyterLab which now should include a log with: +Then, restart JupyterLab. You should now see an info message in the log that mentions +your new provider's `id`: ``` -[I 2023-10-29 13:56:16.915 AiExtension] Registered model provider `ai21`. +[I 2023-10-29 13:56:16.915 AiExtension] Registered model provider `my_provider`. ``` [langchain_llms]: https://api.python.langchain.com/en/latest/api_reference.html#module-langchain.llms @@ -228,9 +230,9 @@ and restart JupyterLab which now should include a log with: [BaseChatModel]: https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.BaseChatModel.html -### Customising prompt templates +### Customizing prompt templates -To modify the prompt template for a given format, override the implementation of ``get_prompt_template`` method: +To modify the prompt template for a given format, override the ``get_prompt_template`` method: ```python from langchain.prompts import PromptTemplate