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DeepResearch (Node implementation)

DeepResearch combines retrieval, webpage reading and multi-step reasoning to find accurate answers, available as a hosted service or self-hosted deployment.

Overview

DeepResearch (Node implementation) from Jina AI combines retrieval, webpage reading and multi-step reasoning to iteratively find accurate answers. It supports hosted demos and self-hosting, and integrates multiple LLM providers for hybrid reasoning.

Key features

  • Combines retrieval and LLM reasoning with evidence tracing and multi-step chains.
  • OpenAI-compatible API and local LLM support for flexible deployment.
  • Docker/Compose examples, Colab demos and sample data to accelerate experiments.

Use cases

Suitable for academic search, investigative research, regulatory compliance checks and multi-turn QA where evidence aggregation and explainability matter. It can act as a microservice for embedding generation, retrieval orchestration and reranking.

Technical details

Implemented in TypeScript, the project focuses on engineering quality and production readiness, providing adapters for multiple LLM providers and retrieval components, and supporting containerized and cloud deployments.

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DeepResearch (Node implementation)
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