chat-js vs langchain-nextjs-template
Two of the top projects in Chat apps, side by side: who leads on each score part and who each one suits, then setup, license, activity and what each review found.
chat-js
Next.js AI chat app scaffold with auth, branching and sharing
langchain-nextjs-template
Next.js routes for LangChain.js chat, agents, structured output and RAG
Verdict
chat-js ranks higher, 72 to 58. Of the 4 score parts we measure for both, chat-js leads on 2, langchain-nextjs-template on 1 and 1 is even.
- Adoptionlangchain-nextjs-template leads by 27 points, 58 to 31: a wide gap.
- FreshnessEven at 100.
- Maintenancechat-js leads by 48 points, 81 to 33: a wide gap.
- Agent-readychat-js leads by 85 points, 85 to 0: a wide gap.
Pick chat-js if you are
Developers building a Next.js AI chat product on Vercel and Postgres
- Scaffold CLI generates chat.config.ts and lists env vars for the chosen options
- Covers branching, public sharing, attachments, MCP and sandboxed code execution
Pick langchain-nextjs-template if you are
Developers learning LangChain.js on Next.js
- Each pattern is one route file you can lift into your own app
- Hosted demo on Vercel
| What we compare | chat-js | langchain-nextjs-template |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 31, known | 58, popular |
| Freshness | 100, active | 100, active |
| Maintenance | 81, healthy | 33, patchy |
| Agent-ready | 85, ready | 0, none |
| Facts from GitHub and the README | ||
| Stars | 1.2k | 2.5k |
| License | Apache-2.0 (permissive) | MIT (permissive) |
| Last commit | Nov 2026 | Nov 2026 |
| Last release | Sep 2026 | None published |
| Language | TypeScript | TypeScript |
| Docker | No | No |
| GPU | Not needed | Not needed |
| arm64 or Apple Silicon | Not stated | Not stated |
chat-js
ChatJS is a Next.js chat application generated with `npx chat-js@alpha create`, which asks for gateway, feature and auth choices and writes a `chat.config.ts`. It uses the AI SDK with Vercel AI Gateway for 120+ models, Better Auth, Drizzle on PostgreSQL, and the EVE runtime for durable conversations and approvals. Chat features include attachments, branching, public sharing, web search, image generation, code execution and MCP.
Who it is for: Developers building a Next.js AI chat product on Vercel and Postgres
Strengths
- Scaffold CLI generates chat.config.ts and lists env vars for the chosen options
- Covers branching, public sharing, attachments, MCP and sandboxed code execution
- EVE runtime provides durable transcripts, approvals and stream recovery
- Optional Electron packaging for macOS, Windows and Linux desktop apps
Weaknesses
- CLI is alpha and its APIs are still changing; no stable 1.0 yet
- README says the EVE-only runtime is not yet established as production-ready
- Historical ChatJS conversations are not imported into the EVE runtime
- Built around Vercel AI Gateway and Blob; needs PostgreSQL and Node 24+
- TypeScript, Claude, GPT, Gemini, Grok
- Needs PostgreSQL, Vercel AI Gateway, Vercel Blob, EVE runtime, Node 24+, Bun
langchain-nextjs-template
Five Next.js API routes that each show one LangChain.js pattern: plain chat, Zod structured output, a prebuilt LangGraph.js agent with Tavily search, and RAG as a chain and as an agent over a Supabase pgvector table. Tokens stream to the client through the AI SDK, routes run on Edge functions, and there is no auth or persistence beyond the vector table. For developers learning LangChain.js who want runnable routes to copy.
Who it is for: Developers learning LangChain.js on Next.js
Strengths
- Each pattern is one route file you can lift into your own app
- Hosted demo on Vercel
- Mock-backed integration tests run without API keys or a live database
- Supabase adapter reuses the documents table and match_documents function; no migration
Weaknesses
- No auth and no chat history persistence
- OpenAI only out of the box; other providers need code changes
- Re-ingesting the same text duplicates vectors; no dedupe
- Agent and search examples need a Tavily key
- TypeScript, openai, langchain, langgraph, ai-sdk
- Needs openai-api-key, supabase, tavily-api-key
- GitHub template
- env example file
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