langchain-nextjs-template vs gemini-chatbot
Two of the top chat apps, side by side: score, setup, license, activity and what each review found.
langchain-nextjs-template
Next.js routes for LangChain.js chat, agents, structured output and RAG
gemini-chatbot
Next.js chatbot template defaulting to Gemini with NextAuth and Postgres
| What we compare | langchain-nextjs-template | gemini-chatbot |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 64, popular | 46, known |
| Freshness | 100, active | 83, active |
| Maintenance | 33, patchy | 0, weak |
| Easy to run | 67, easy | 67, easy |
| Agent-ready | 0, none | 0, none |
| Facts from GitHub and the README | ||
| Stars | 2.5k | 1.4k |
| License | MIT (permissive) | Apache-2.0 (permissive) |
| Last commit | Oct 2026 | May 2026 |
| Last release | None published | None published |
| Language | TypeScript | TypeScript |
| Docker | No | No |
| GPU | Not needed | Not needed |
| arm64 or Apple Silicon | Not stated | Not stated |
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
gemini-chatbot
An earlier cut of the Vercel chatbot template pinned to Google Gemini: Next.js App Router, AI SDK streaming with tool calls, NextAuth.js login, chat history in Vercel Postgres through Drizzle, and file storage on Vercel Blob. The default model is gemini-1.5-pro; the AI SDK lets you switch to OpenAI, Anthropic or Cohere. For teams on Google models who want the Vercel chat stack.
Who it is for: Teams on Gemini who want the Vercel chat stack
Strengths
- Auth, Postgres history and Blob uploads already wired
- Two env vars to deploy: AUTH_SECRET and GOOGLE_GENERATIVE_AI_API_KEY
- Deployed demo at gemini.vercel.ai
Weaknesses
- Default model gemini-1.5-pro is dated; update before shipping
- Tied to Vercel Postgres and Blob; self-hosting means swapping both
- No tests, no Docker
- vercel/chatbot is the maintained successor for most uses
- TypeScript, google, ai-sdk
- Needs postgres, vercel-blob, google-api-key
- GitHub template
- env example file
- sign-in: Auth.js