[Feat] Add new RAG API on LiteLLM AI Gateway - #17109
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Jun 24, 2026
* init RAG api types * add RAG endpoints * init main.py for RAG ingest API * init RecursiveCharacterTextSplitter * add BaseRAGIngestion * fix OpenAIRAGIngestion * fix img handler * init OpenAIRAGIngestion * init BedrockRAGIngestion * init BedrockRAGIngestion * init rag tests * init BedrockVectorStoreOptions * implement BedrockRAGIngestion * add BaseRAGAPI * add endpoint for RAG ingest * add ingest RAG endpoints * add test doc * add parse_rag_ingest_request * update endpoints * docs add docs for new RAG API * fix qa check * fix linting * docs ficx * docs * add max depth checks * docs anthropic
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[Feat] Add new RAG API on LiteLLM AI Gateway
This PR adds a new
/v1/rag/ingestAPI endpoint for all-in-one document ingestion into vector stores. The pipeline handles: Upload -> Chunk -> Embed -> Vector Store.The implementation uses a provider-specific class architecture where each vector store provider (OpenAI, Bedrock) can override ingestion behavior. For example, OpenAI handles embedding internally when files are attached to vector stores, while other providers may require explicit embedding calls.
Usage
Response
Query the Ingested Data
Relevant issues
Pre-Submission checklist
Please complete all items before asking a LiteLLM maintainer to review your PR
tests/litellm/directory, Adding at least 1 test is a hard requirement - see detailsmake test-unitType
🆕 New Feature
✅ Test
Changes