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★ 24.9k スターCustom (check repo)
ガイドを見る →personalized-travel-itinerary-plannerは、aws-samplesが公開しているオープンソースの簡単インストールプロジェクトです（GitHub: aws-samples/personalized-travel-itinerary-planner）。GitHubスターは55、フォークは15で、MIT-0ライセンスの下で公開されています。GitHubでの最終更新は2026年2月12日です。
Run personalized-travel-itinerary-planner locally: a generative ai chatbot application...
Fetch the source code onto your machine.
Set up the Python environment the project needs.
Copy the sample config or env file and adjust it.
Start the app from the source directory.
Built around bedrock for a focused workflow.
Built around claude2 for a focused workflow.
Built around redshift for a focused workflow.
Built around redshift serverless for a focused workflow.
Inspect, fork, and modify every line of the code.
Run it on your own machine — no account lock-in.
Get the source on your machine.
git clone https://github.com/aws-samples/personalized-travel-itinerary-planner.gitSet up Python dependencies.
cd personalized-travel-itinerary-planner && pip install -r requirements.txtLaunch the application.
cd personalized-travel-itinerary-planner && python main.pyIt a Generative AI Chatbot application to provide personalized travel recommendations using Amazon Redshift and Amazon Bedrock, giving you a working starting point you can run and adapt.
Yes — the code is open-source, so you can use and modify it without a license fee.
Clone the GitHub repository and follow the README; the typical flow is install dependencies, configure, and run.
It is primarily written in Python, so you will need that toolchain to build or extend it.
The GitHub repository is the hub: open issues for bugs and check the README and discussions for guidance.
AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI…
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A multi-agent travel planner built on Spring Boot and Spring AI.
LibreAIカタログに掲載された簡単インストールプロジェクトの中で最もスターの多いもの — personalized-travel-itinerary-plannerが合わなかった場合に検討したい、現実的な候補リストです。
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カタログの中でpersonalized-travel-itinerary-plannerとスター数が近い簡単インストールプロジェクト — 前後の棚もそのまま見て回れます。
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