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Support for More LLms / configurable ExcecutableID #243
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Hi @MichaelSchmid-AGI , I guess the feature request is about supporting more direct LLM consumption. Are you aware our orchestration package: |
@jjtang1985 the idea of using orchestration is good to have a unified entry point. However, I'm not clear how multimodal capabilities are provided by the orchestration. I tried to pass an image into it and it gave a strange error. I think it's just not working. Also it might add unwanted latency. Next, not sure how compatible it is with langchain? So far I need to rely on the Python SDK as it offers most models. Would be great to see Anthropic and Gemini supported soon. |
Agreed, it’s crucial that the |
Hi @skye0402 , Thank you for reaching out!
Using image as input, as a feature has been supported by orchestration from last month.
As far as I know, the team did some tests and there are no major findings in terms of the latency.
So far, not supported. |
Hi @Mohan-Sharma ,
Here is the #176, please add your detailed requirements there, if possible. Thank you! |
Describe the Problem
Hi there,
i am struggling to get LLMS running that arent from OpenAI with your langchain module. Per default you seem to filter out LLMS which are in a different "excecutableId" than "azure-openai"
This makes using different Models seemingly impossible (for now)
Propose a Solution
I would suggest that you allow to pass a excecutableId when initializing a langchain chat client
this should allow the usage of other models quite easily without having to rewrite much.
The chat-completion api ( for example when using llama or mixtral) seems identical to payloads working with OpenAI models.
POST {baseurl}/v2/inference/deployments/{deploymentID}/chat/completions
Body for GPT 4o:
Body For Llama 3.1 Instruct
Describe Alternatives
No response
Affected Development Phase
Development
Impact
Inconvenience
Timeline
No response
Additional Context
No response
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