copilot-swe-agent[bot]
b62ac7672a
Agent-Logs-Url: https://github.com/bytedance/deer-flow/sessions/a5f192e7-8034-4e46-af22-60b90ee27d40 Co-authored-by: foreleven <4785594+foreleven@users.noreply.github.com>
60 lines
1.7 KiB
Plaintext
60 lines
1.7 KiB
Plaintext
import { Callout, Steps } from "nextra/components";
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# First Conversation
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This tutorial walks you through your first complete agent conversation in DeerFlow — from launching the app to getting meaningful work done with the agent.
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## Prerequisites
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- DeerFlow app is running (see [Quick Start](/docs/application/quick-start))
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- At least one model is configured in `config.yaml`
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## Steps
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<Steps>
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### Open the workspace
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Open [http://localhost:2026](http://localhost:2026) in your browser. You will see the conversation workspace.
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### Send your first message
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Type a question in the input box, for example:
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```
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Research the top 3 most popular open-source LLM frameworks in 2024 and compare their strengths and weaknesses.
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```
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Press Enter to send.
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### Watch the agent work
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You will see the agent start working:
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- Expand the **thinking steps** to see which tools it is calling
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- Watch search results stream in
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- Wait for the final report to be generated
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### Interact with the result
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Once the report is generated, you can:
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- Ask for more detail on a specific section
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- Ask to export the report as a file (the agent will use the `present_files` tool)
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- Ask to create a chart based on the research findings
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</Steps>
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## What just happened
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The agent used the DeerFlow Harness to:
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1. Receive your message and add it to the thread state
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2. Run the middleware chain (memory injection, title generation)
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3. Call the LLM, which decided to search the web
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4. Execute web search tool calls
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5. Synthesize results into a structured response
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6. Update the thread state with any artifacts produced
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## Next steps
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- [Use Tools and Skills](/docs/tutorials/use-tools-and-skills)
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- [Workspace Usage](/docs/application/workspace-usage)
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