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Setting default model providers #421

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merged 14 commits into from
Jan 26, 2024

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aws-khatria
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@aws-khatria aws-khatria commented Nov 1, 2023

This pull request introduces the setting of default model provider details in the Jupyter AI extension. The changes primarily involve extending the ConfigManager to initialize default values, and extension.py to initialize the values from CLI. Fixes #218.

The changes include:

  • Setting the model_provider_id
  • Setting the embedding_model_provider_id
  • Setting api_keys for corresponding model provider
  • Setting fields in cases where model provider requires additional details to model provider.
  • Support to merge default values provided in the CLI even when the config.json file exists. This is also tested using unit-test case.

Testing:

The changes were tested manually by running the Jupyter AI extension and verifying that the default model provider is correctly.

In addition to manual testing, unit tests are also included in this commit. The tests cover the changes made to the ConfigManager class and ensure that the default model provider details are correctly set.

These changes will improve the usability of the Jupyter AI extension by configuring the defaults for the model provider.

Command with which extension was tested:

jlpm dev --AiExtension.model_provider_id="bedrock-chat:anthropic.claude-v1"  --AiExtension.fields='{"bedrock-chat:anthropic.claude-v1":{"credentials_profile_name": "default","region_name": "us-west-2"},"bedrock:amazon.titan-embed-text-v1":{"credentials_profile_name": "default","region_name": "us-west-2"}}' --AiExtension.api_keys='{"OPENAI_API_KEY": "sk-xyz"}'

Executed unit-test using jlpm test command.

Next steps:

  • Review the changes and provide feedback.
  • Add relevant documentation
  • If everything looks good, merge the pull request.

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@JasonWeill JasonWeill added the enhancement New feature or request label Nov 1, 2023
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@aws-khatria Thank you very much for circulating this pull request! Is this something that we should document in our user documentation? We already document some other options in the user docs. I can help with this if you need.

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@aws-khatria Thank you very much for circulating this pull request! Is this something that we should document in our user documentation? We already document some other options in the user docs. I can help with this if you need.

Sure, I'll update the PR with doc details. Let me know if there are any other comments as well.

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@aws-khatria
Thanks for making this change. Can you rebase from main and fix the merge conflicts. Left some comments about using the model_parameters for the fields and api_keys. Let me know if you have questions.

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Awesome work! There's a few changes that need to be done before this can be merged however.

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@aws-khatria aws-khatria reopened this Jan 23, 2024
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Addressed comments.

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Generally looking OK; a couple of concerns about naming

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@aws-khatria
Thanks for making all the updates, it looks like we are almost there. Left some naming suggestions, and a few questions.
I still have to test your changes locally, will be able to get to this by later this week; feel free to make the rest of the updates in the mean time.

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3coins commented Jan 24, 2024

@aws-khatria
This branch seems to be out of date, can you rebase from latest main. Thanks.

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3coins commented Jan 24, 2024

@aws-khatria
I did some testing, and although the defaults seem to work when user doesn't have any values set, it breaks as soon as the user configures new values via the UI and restarts the server. For example,

  1. I started with no defaults and set the model provider (OpenAI) and API keys through the UI, then configured the defaults as OpenAI, but did not provide the API key; this resulted in a crash, even though api keys were written to the config before the restart.

    jupyter_ai.config_manager.AuthError: Missing API key for 'OPENAI_API_KEY' in the config.
    
  2. Start with default provider as OpenAI, and added default api keys, but then changed the provider to anthropic in the UI. Restarted the server, and see that OpenAI was selected again as the provider.

This is due to incorrect merge as pointed in my comments. Rather than doing a shallow merge, which overwrites the top level values directly, we should be using the Merger.merge function to do deep merge, and also make sure precedence is given to the existing config. See an example for similar merge in ConfigManager.

merged_config = Merge.merge(default_config, existing_config)

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@3coins - I do agree with the deep merge. Somehow, it got messed up in merge conflict.

Although, I think default's must be given priority over what's present in the config file. Consider this scenario:

  1. Start JL with no default
  2. Select any Open AI model
  3. Stop the server
  4. Start JL with default as Claude. By default, Claude should be selected.

Enterprise might have use-case where they want a default language model but user can change it via UI. In this case, if the server restarts then enterprise would expect user to have the default selected model. If this is not the case, then I would suggest adding force_update parameter too that will control if the CLI provided input takes precedence over what exist in the config. Let me know your thoughts!

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3coins commented Jan 25, 2024

@aws-khatria
Thanks for explaining that use-case. My understanding was to apply default values when the user hasn't specified one. In the case you have mentioned, since the user selected OpenAI and it was saved as an option, system should honor user's choice, most users will expect that.

Changing the saved choice to the default on restart seems like an anti-pattern, a surprise for users that will need to be communicated appropriately to the user when the change happens. This also adds friction to users who will have to re-enter their choice of model on each restart, when they don't want default. My suggestion is to explore the force_update option in another issue/PR, so we can discuss pros/cons and different scenarios affecting it; this will also give us time to get feedback from the community.

@3coins 3coins merged commit 84c074a into jupyterlab:main Jan 26, 2024
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3coins commented Jan 30, 2024

@meeseeksdev please backport to 1.x

meeseeksmachine pushed a commit to meeseeksmachine/jupyter-ai that referenced this pull request Jan 30, 2024
3coins pushed a commit that referenced this pull request Jan 30, 2024
Co-authored-by: aws-khatria <107514829+aws-khatria@users.noreply.github.com>
dbelgrod pushed a commit to dbelgrod/jupyter-ai that referenced this pull request Jun 10, 2024
* Setting default model providers

* Setting default model providers

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Setting default model providers

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Added default_ prefix to new attributes

* Added default_ prefix to docs as well

* Fix docs

* Removed redundant code

* Incorporated naming related comments

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Removing unnecessary files

* Corrected config names, simplified docs.

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Piyush Jain <piyushjain@duck.com>
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Configuration to set default provider
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