Comments (1)
Yes you can pass any constructor parameters, just edit a LLM in the frontend and change the options field with a json with all the options accepted by the class you selected.
Example:
{model="gpt-35-turbo-16k", deployment_name="my-custom-llm", api_key="xxxxxxxxx", azure_endpoint="https://<your-resource-name>.openai.azure.com/", api_version="2023-07-01-preview"}
Additionally I added llamaindex's AzureOpenAI class to the supported LLMs, it allows a better integration with Azure:
e853a34#diff-08524b3ea22905074b8c7494a1dfc7d8f430f76f38b14d443d3eb0ae99093348R40
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Related Issues (11)
- questionsql returns error 500 HOT 1
- Please add support for LiteLLM to this project HOT 4
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