Below, organized by pipeline stage, are common tools and platforms as of 2026, listed for reference. This field moves fast — the maintenance status, naming, and pricing of specific tools can change at any time, so verify before making production decisions.
By pipeline stage (common tools/platforms for each):
| Stage | What This Step Does | Common Tools / Platforms |
|---|---|---|
| Document parsing / chunking | Reading formats like PDF and Word into text, and splitting into small segments | Unstructured, LlamaParse, LlamaIndex's loader ecosystem, Docling |
| Embedding models | Converting text into vectors | OpenAI embeddings, Cohere, BGE, Voyage, sentence-transformers |
| Vector databases | Storing vectors and performing similarity search | Pinecone, Weaviate, Milvus, Chroma, Qdrant, pgvector |
| Reranking models | Precision-ranking rough-screened results, keeping only the most relevant few | Cohere Rerank, BGE-reranker, Jina Reranker |
| Orchestration / RAG frameworks | Development frameworks that wire the entire pipeline together | LangChain, LlamaIndex, Haystack, RAGFlow |
| Agent frameworks | Development frameworks supporting ReAct loops and multi-agent collaboration | LangGraph, AutoGen, CrewAI |
| Inference serving | Running large models and exposing them as a service | vLLM, TGI (Text Generation Inference), SGLang |
| Evaluation | Measuring how well a RAG/Agent system performs | RAGAS, DeepEval, TruLens, promptfoo |
| Observability | Logging, tracing, and debugging the entire system's operation | LangSmith, Langfuse, Arize Phoenix |
("Reranking models" correspond to the precision-ranking stage of the Section 3.2 funnel; "evaluation" and "observability" correspond to the log-feedback mechanism described in Chapter One's Loop D — the tools are simply off-the-shelf products that implement these mechanisms.)
By brand ecosystem (product suites from the same company/community):
- LangChain family: LangChain (base framework) + LangGraph (purpose-built for agent orchestration) + LangSmith (observability / debugging) — three products within the same ecosystem designed to work together.
- Hugging Face family: the Model Hub (the world's largest open-source model repository) + Transformers (a library for conveniently loading various models) + TGI (inference serving) + a full suite of open-source tools.
- Cloud-provider MaaS: AWS Bedrock, Azure AI Foundry, Google Vertex AI, and similar services package embedding and generation models as managed cloud services, allowing enterprises to make API calls without building their own servers.
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