OpenLLMetry Vector Database Instrumentations

Instrumentations for vector databases used in retrieval-augmented generation pipelines — Chroma, Pinecone, Qdrant, Weaviate, LanceDB, Milvus, and Marqo. Captures query, upsert, and similarity- search operations with vector-DB-specific attributes so RAG retrievals can be correlated with the LLM calls that consumed them.

OpenLLMetry Vector Database Instrumentations is one of 6 APIs that OpenLLMetry publishes on the APIs.io network.

Tagged areas include Instrumentation, Vector Databases, and RAG. The published artifact set on APIs.io includes API documentation, a GitHub repository, and SDKs.

API entry from apis.yml

apis.yml Raw ↑
aid: openllmetry:openllmetry-vector-db-instrumentations
name: OpenLLMetry Vector Database Instrumentations
tags:
- Instrumentation
- Vector Databases
- RAG
image: https://kinlane-productions.s3.amazonaws.com/apis-json/apis-json-logo.jpg
humanURL: https://www.traceloop.com/docs/openllmetry/tracing/decorators
properties:
- url: https://www.traceloop.com/docs/openllmetry/tracing/decorators
  type: Documentation
- url: https://github.com/traceloop/openllmetry/tree/main/packages
  type: GitHubRepository
- url: https://pypi.org/project/opentelemetry-instrumentation-chromadb/
  type: SDK
- url: https://pypi.org/project/opentelemetry-instrumentation-pinecone/
  type: SDK
- url: https://pypi.org/project/opentelemetry-instrumentation-qdrant/
  type: SDK
- url: https://pypi.org/project/opentelemetry-instrumentation-weaviate/
  type: SDK
- url: https://pypi.org/project/opentelemetry-instrumentation-lancedb/
  type: SDK
- url: https://pypi.org/project/opentelemetry-instrumentation-milvus/
  type: SDK
- url: https://pypi.org/project/opentelemetry-instrumentation-marqo/
  type: SDK
description: Instrumentations for vector databases used in retrieval-augmented generation pipelines —
  Chroma, Pinecone, Qdrant, Weaviate, LanceDB, Milvus, and Marqo. Captures query, upsert, and similarity-
  search operations with vector-DB-specific attributes so RAG retrievals can be correlated with the LLM
  calls that consumed them.