fix(llm): Fix when use custom embedding providers.#339
Merged
qin-ctx merged 4 commits intovolcengine:mainfrom Mar 10, 2026
Merged
fix(llm): Fix when use custom embedding providers.#339qin-ctx merged 4 commits intovolcengine:mainfrom
qin-ctx merged 4 commits intovolcengine:mainfrom
Conversation
MaojiaSheng
approved these changes
Mar 6, 2026
auto-merge was automatically disabled
March 9, 2026 08:23
Head branch was pushed to by a user without write access
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
3 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Description
This pull request updates the embedding request logic in
opencontext/llm/llm_client.pyto better handle different LLM providers. The main change is switching the order of provider checks and ensuring that multimodal embeddings are used only for theDOUBAOprovider.Embedding provider logic update:
LLMProvider.DOUBAOand usemultimodal_embeddingsonly for this provider, while other providers (likeOPENAI) continue to use the standard embedding API.