feat: integrate end-to-end vector embeddings pipeline#12
Open
jithish-sekar wants to merge 1 commit intoAKSarav:devfrom
Open
feat: integrate end-to-end vector embeddings pipeline#12jithish-sekar wants to merge 1 commit intoAKSarav:devfrom
jithish-sekar wants to merge 1 commit intoAKSarav:devfrom
Conversation
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
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Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be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.
Backend:
New Endpoints:
GET /embeddings/providers: Returns a validated list of available embedding models (including connectivity checks for OpenAI, Ollama, and Local Transformers).
POST /embeddings/embed: High-performance endpoint accepting JSON bodies for batch-processing large sets of document chunks.
Frontend:
Embeddings Workspace: Added a dedicated "Embeddings" tab in the results container.
EmbeddingsPanel Component: Created a self-contained React component to manage provider selection, status indicators, and generation triggers.
Vector Preview: Implemented a preview mode that shows the first few dimensions and total dimensionality (e.g., 384d, 1536d) of generated vectors for debugging and verification.