{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/3"}],"enrichment":{"capability":"Provides Amazon Bedrock embedding models integration for LlamaIndex, enabling text-to-vector conversion using Titan and Cohere embeddings through AWS.","skillfed_tags":["bedrock-integration","embeddings","rag"],"use_cases":["Embed documents in a RAG pipeline using Bedrock models without running your own embedding server.","Build semantic search over text corpora by generating embeddings via Cohere or Titan through the integration.","Use Cohere v4 multimodal embeddings to embed both text and images in a single unified vector space.","Integrate Bedrock embeddings with automatic response format handling across model versions.","Track embedding costs and usage through AWS Application Inference Profiles in governed environments."],"what_it_does":"This package integrates Amazon Bedrock embedding models with the embedding interface, letting you generate text embeddings using AWS-hosted models without managing your own embedding infrastructure. It supports multiple Bedrock foundation models\u2014Amazon Titan variants and Cohere v3/v4\u2014and handles the API differences between them transparently, including Cohere v4's multimodal capabilities and response format changes.\n\nYou configure it with a model name and AWS region, then call `get_text_embedding()` or `get_text_embedding_batch()` to convert text into vectors. AWS credentials flow through boto3's standard chain (environment variables, IAM roles, profiles, or explicit parameters). The integration also supports Application Inference Profiles for cost tracking and model usage governance in enterprise Bedrock deployments.","worth_installing":"Yes. Low install friction, active maintenance, no known vulnerabilities, and permissive MIT license. Install if you need Bedrock embeddings and have AWS access. Skip if you prefer self-hosted embeddings or use a different embedding provider."},"id":"llama-index-embeddings-bedrock","links":{"html":"https://skillfed.io/packages/llama-index-embeddings-bedrock","md":"https://skillfed.io/packages/llama-index-embeddings-bedrock.md","pypi":"https://pypi.org/project/llama-index-embeddings-bedrock/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-14","license_spdx":"MIT","license_treatment":"permissive","name":"llama-index-embeddings-bedrock","python_support":"supports_current","summary":"llama-index embeddings bedrock integration"},"popularity":{"monthly_downloads":2304795,"position":3154,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.8.3"}