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[FEAT]: APIPie provider improvements #2592

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timothycarambat opened this issue Nov 6, 2024 · 2 comments · May be fixed by #2695
Open

[FEAT]: APIPie provider improvements #2592

timothycarambat opened this issue Nov 6, 2024 · 2 comments · May be fixed by #2695
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enhancement New feature or request feature request Integration Request Request for support of a new LLM, Embedder, or Vector database

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@timothycarambat
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What would you like to see?

Refer to #2464 (comment) to end for more details or scope.

  1. Enable streaming on Apipie providers
  2. File chat model providers with the query param for chatx so we can reduce model selection for LLM Options.
  • Keep the full .cache of models, apply the post-filter after that request on the resulting file contents. We can reuse this cache for Embedding and Voice Support
  1. Investigate Voice and Embedder model support (filter appropriate models for each). If Embedding, TTS, or STT are viable break them into separate issues from this issue.
@timothycarambat timothycarambat added enhancement New feature or request Integration Request Request for support of a new LLM, Embedder, or Vector database feature request labels Nov 6, 2024
@Toocky
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Toocky commented Nov 8, 2024

@timothycarambat

Thanks for this would be amazing to see, one other feature that might be worth looking at is we also provide Pinecone Vector DBs for our users so if you are looking to implement TTS and Embedding it might also be worth looking at our Pinecone integration also.

Docs available here https://apipie.ai/docs/Features/Pinecone

@timothycarambat
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We currently have a pinecone integration available for the user to use as their vectordb if they have an account, something like 97% of people never change from the default lancedb!

@shatfield4 shatfield4 linked a pull request Nov 22, 2024 that will close this issue
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@shatfield4 shatfield4 linked a pull request Nov 22, 2024 that will close this issue
10 tasks
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Labels
enhancement New feature or request feature request Integration Request Request for support of a new LLM, Embedder, or Vector database
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