85 lines
2.2 KiB
Markdown
85 lines
2.2 KiB
Markdown
# open-research-ANA 🔍
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This demo showcases ANA (Agent Native Application), a research canvas app that combines Human-in-the-Loop capabilities with [Tavily's](https://tavily.com/) real-time search and [CopilotKit's](https://copilotkit.ai) agentic interface.
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Powered by [LangGraph](https://www.langchain.com/langgraph), it simplifies complex research tasks, making them more interactive and efficient.
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<p align="left">
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<a href="https://docs.copilotkit.ai/coagents" rel="dofollow">
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<strong>Explore the CopilotKit docs »</strong>
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</a>
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</p>
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## Quick Start 🚀
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### 1. Prerequisites
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This projects uses the following tools:
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- [pnpm](https://pnpm.io/installation)
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- [Docker](https://docs.docker.com/get-docker/)
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- [Langgraph CLI](https://langchain-ai.github.io/langgraph/cloud/reference/cli/)
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### 2. API Keys Needed
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Running locally, you'll need the following API keys:
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- [OpenAI](https://platform.openai.com/api-keys)
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- [Tavily](https://tavily.com/#pricing)
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- [LangSmith](https://docs.smith.langchain.com/administration/how_to_guides/organization_management/create_account_api_key)
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- [CopilotKit](https://dashboard.operations.copilotkit.ai)
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### 3. Start the Agent
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There are two main components to this project: the agent and the frontend. First, we'll start the agent.
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```bash
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cd agent
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# Create and populate .env
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cat << EOF > .env
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OPENAI_API_KEY=your_key
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TAVILY_API_KEY=your_key
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LANGSMITH_API_KEY=your_key
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EOF
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## Start the agent
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langgraph up
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# Note the API URL from the output (e.g., http://localhost:8123)
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```
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### 4. Open a tunnel to your local agent
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Create a tunnel to your local agent:
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```bash
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npx copilotkit@latest dev --port 8123
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```
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### 5. Start the Frontend
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Next, we'll start the frontend.
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```bash
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cd frontend
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pnpm install
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# Create and populate .env
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cat << EOF > .env
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OPENAI_API_KEY=your_openai_key
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LANGSMITH_API_KEY=your_langsmith_key
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NEXT_PUBLIC_COPILOT_CLOUD_API_KEY=your_copilot_cloud_key
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EOF
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# Start the app
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pnpm run dev
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```
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## Documentation 📚
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- [CopilotKit Docs](https://docs.copilotkit.ai/coagents)
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- [LangGraph Platform Docs](https://langchain-ai.github.io/langgraph/cloud/deployment/cloud/)
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