RAG Frameworks · yokingma

SearChat

SearChat is an open-source conversational search engine that integrates multiple AI models (OpenAI, Anthropic, Gemini, Vertex AI) with search engines (SearXNG, Bing, Google) to provide chat-based research. It includes a Deep Research mode for iterative analysis and generates structured reports with citations.

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Source: GitHub — github.com/yokingma/SearChat

1.1k

GitHub stars

180

Forks

TypeScript

Primary language

MIT

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	yokingma/SearChat
Owner	yokingma
Primary language	TypeScript
License	MIT — OSI-approved
Stars	1.1k
Forks	180
Open issues	2
Latest release	v1.2.3 (2026-05-13)
Last updated	2026-05-13
Source	https://github.com/yokingma/SearChat

What SearChat is

TypeScript-based Turborepo monorepo (Node.js/Koa backend, Vue 3 frontend) supporting multi-model LLM APIs, LangChain/LangGraph orchestration for agentic research workflows, IndexedDB/LocalStorage chat persistence, and pluggable search engine backends. Docker deployment available with configurable model.json.

Quickstart

Get the SearChat source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/yokingma/SearChat.git2cd SearChat3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Conversational Research & Knowledge Synthesis

Users seeking deep, multi-turn research on topics can leverage iterative search combined with LLM analysis to generate structured reports with citations, reducing manual research effort.

Multi-Model AI Evaluation & Cost Optimization

Teams evaluating different LLM providers (OpenAI, Anthropic, Google) can run identical searches across models from a single interface, comparing output quality and managing API costs through unified configuration.

Self-Hosted Search Intelligence without Vendor Lock-In

Organizations preferring on-premise or self-hosted infrastructure can deploy SearChat via Docker with local SearXNG, avoiding third-party search API dependencies while integrating their choice of LLM providers.

Implementation considerations

Requires API keys for at least one LLM provider (OpenAI, Anthropic, Google, etc.) and optionally for search engines (Bing, Google, Tavily). Costs scale with query volume and token usage.
Deep Research mode relies on agentic workflows (LangChain/LangGraph); research quality depends on prompt engineering and model capability. Refactoring is noted as in-progress.
Browser-side chat history uses IndexedDB/LocalStorage; no server-side persistence by default. Multi-device or persistent conversation history requires additional implementation.
SearXNG integration assumes network access to Google (for SearXNG indexing). Firewall or proxy configuration may be needed in restricted environments.
Model configuration is file-based (model.json); no runtime UI for adding/removing models. Changes require Docker restart.

When to avoid it — and what to weigh

Real-Time, Sub-Second Latency Search Required — Deep Research mode performs iterative queries and LLM inference sequentially. If microsecond response times or high-frequency search are critical, this design may introduce unacceptable latency.
Enterprise Security Compliance (HIPAA, FedRAMP, SOC 2) — No security audit, compliance certification, or formal security posture documentation is evident from public repository. Use in regulated environments requires independent security review.
Requires Minimal External Dependency Management — SearChat relies on external LLM APIs (OpenAI, Anthropic, etc.), SearXNG or third-party search APIs, and Docker orchestration. Offline-only or air-gapped deployments would require significant rework.
Production Support & SLA Requirements — This is a community-maintained open-source project (1053 stars, 180 forks, 2 open issues). No commercial support, SLA, or guaranteed response times; maintenance depends on volunteer contributors.

License & commercial use

MIT License. Permissive OSI-approved license allowing commercial use, modification, and distribution with attribution. No restrictions on proprietary derivative works.

MIT License permits commercial use. However, dependency on third-party LLM APIs (OpenAI, Anthropic, etc.) and search services introduces external cost and licensing obligations. Users must ensure compliance with those providers' terms. No warranty or indemnification from SearChat itself.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Adequate
License clarity	Clear
Deployment complexity	Moderate
DEV.co fit	Strong
Assessment confidence	High

Security considerations

No formal security audit or threat model disclosed. Consider: (1) API keys stored in model.json and environment variables—protect file access and use secrets manager in production; (2) IndexedDB stores chat history client-side; sanitize user input to prevent XSS; (3) LLM API calls include user queries—review provider data retention policies; (4) SearXNG may expose search queries to search engines; (5) No input validation or rate limiting evident in README. Conduct security review before exposing to untrusted users.

Alternatives to consider

Perplexity AI / You.com

Closed-source commercial conversational search with similar UX. Proprietary models and search, no self-hosting or API customization. Simpler deployment, managed SLA, but vendor lock-in and higher per-query cost.

LangChain + Streamlit / Gradio

Open-source, developer-friendly frameworks for building custom agentic search UIs. More flexible but requires significant engineering to replicate SearChat's features; no pre-built UI.

Retrieval-Augmented Generation (RAG) frameworks (e.g., LlamaIndex, HayStack)

Focused on document retrieval and indexing rather than conversational web search. Better for closed-domain knowledge bases; different use case but overlapping technology stack.

Software development agency

Build on SearChat with DEV.co software developers

SearChat offers rapid Docker deployment for teams building custom search experiences. Evaluate licensing, API costs, and security requirements with your compliance team before production use.

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SearChat FAQ

Can I use SearChat without LLM API keys?

No. At least one LLM provider (OpenAI, Anthropic, Google, Vertex AI) must be configured. Search engines (SearXNG, Bing, Google) are optional but search features require at least one backend.

Does SearChat store conversations on a server?

By default, chat history is stored in the browser (IndexedDB/LocalStorage) and not persisted to a server. Server-side persistence is not mentioned and would require custom implementation.

What is the deepsearcher NPM package?

Standalone Node.js package extracting SearChat's Deep Research functionality. Allows embedding iterative research workflows in other projects; requires custom searcher function implementation.

Is MCP (Model Context Protocol) supported?

MCP support is listed as TODO in the feature roadmap. Currently not implemented; external tool integrations require custom code.

Custom software development services

DEV.co is a software development agency delivering custom software development services to companies building on open source. Our software developers and web developers design, integrate, and ship production systems — spanning web development, APIs, AI, data, and cloud. If SearChat is part of your rag frameworks roadmap, our team can implement, customize, migrate, and maintain it.

Ready to Deploy AI-Powered Search?

SearChat offers rapid Docker deployment for teams building custom search experiences. Evaluate licensing, API costs, and security requirements with your compliance team before production use.

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