google-gemini/gemini-fullstack-langgraph-quickstart resource
Get started with building Fullstack Agents using Gemini 2.5 and LangGraph observed · 2026-08-28
Health v2 · maintenance only
58/100
- Activity 87
- Release rhythm 35
- Longevity 33
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 468
- days_rel: n/a
- days_push: 80
- n_releases_24m: 0
Adoption not part of the score
18322 stars · 3071 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
A quickstart template demonstrating a fullstack AI research agent built with a React frontend and a LangGraph backend powered by Google Gemini. The agent iteratively generates search queries, grounds answers with Google Search, reflects on gaps, and returns cited answers.
Use cases
- build a fullstack AI agent with Gemini and LangGraph
- learn how to build a research agent with citations
- get started with LangGraph and Gemini 2.5
- create a chatbot that searches the web and cites sources
- example React frontend with LangGraph backend
- build a deep research app with Gemini
When to choose
- you want a working template for a Gemini + LangGraph research agent
- you want to learn agentic search-reflection loops with citations
- you want a React + FastAPI/LangGraph fullstack starting point
When to avoid
- you need a production-ready application rather than a demo template
- you use LLM providers other than Gemini
- you want a framework or library rather than example code
Facets
learning-resource · maturity active
agent-framework rag web-framework chatbot artificial-intelligence web-development tutorials python cross-platform gemini langgraph react fastapi quickstart fullstack google-search-grounding ai-agents retrieval-augmented-generation nodejs web-server
10 sources
- readme: https://github.com/google-gemini/gemini-fullstack-langgraph-quickstart · fetched 2026-08-28 · e226f47f892b
- homepage: https://ai.google.dev/gemini-api/docs/google-search · fetched 2026-08-29 · 6cf70e5eecb4
- site_page: https://ai.google.dev/gemini-api/docs · fetched 2026-08-29 · 11489b3a3b69
- site_page: https://ai.google.dev/gemini-api/docs/get-started · fetched 2026-08-29 · 0d97879d85d3
- site_page: https://ai.google.dev/gemini-api/docs/api-key · fetched 2026-08-29 · 7aacb7b0841e
- site_page: https://ai.google.dev/gemini-api/docs/pricing · fetched 2026-08-29 · 63fb7a02921f
- site_page: https://ai.google.dev/gemini-api/docs/coding-agents · fetched 2026-08-29 · 3c57684e19de
- site_page: https://ai.google.dev/gemini-api/docs/models · fetched 2026-08-29 · 6415425758d4
- site_page: https://ai.google.dev/gemini-api/docs/latest-model · fetched 2026-08-29 · f4ac326d927e
- site_page: https://ai.google.dev/gemini-api/docs/image-generation · fetched 2026-08-29 · 417b11c2f0da
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| google-gemini/gemini-fullstack-langgraph-quickstart | main | 58 |
For agents
markdown · JSON · MCP: product_card(name="google-gemini/gemini-fullstack-langgraph-quickstart")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem