mirror of
https://github.com/FuzzingLabs/fuzzforge_ai.git
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baace0eac4
- Disable FuzzForge MCP connection (no Prefect backend) - Add a2a_wrapper module for programmatic A2A agent tasks - Add task_agent (LiteLLM A2A agent) on port 10900 - Create volumes/env/ for centralized Docker config - Update docker-compose.yml with task-agent service - Remove workflow_automation_skill from agent card
62 lines
1.5 KiB
Markdown
62 lines
1.5 KiB
Markdown
# Quick Start Guide
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## Launch the Agent
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From the repository root you can expose the agent through any ADK entry point:
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```bash
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# A2A / HTTP server
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adk api_server --a2a --port 8000 agent_with_adk_format
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# Browser UI
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adk web agent_with_adk_format
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# Interactive terminal
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adk run agent_with_adk_format
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```
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The A2A server exposes the JSON-RPC endpoint at `http://localhost:8000/a2a/litellm_agent`.
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## Hot-Swap from the Command Line
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Use the bundled helper to change model and prompt via A2A without touching the UI:
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```bash
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python agent_with_adk_format/a2a_hot_swap.py \
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--model openai gpt-4o \
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--prompt "You are concise." \
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--config \
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--context demo-session
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```
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The script sends the control messages for you and prints the server’s responses. The `--context` flag lets you reuse the same conversation across multiple invocations.
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### Follow-up Messages
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Once the swaps are applied you can send a user message on the same session:
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```bash
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python agent_with_adk_format/a2a_hot_swap.py \
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--context demo-session \
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--message "Summarise the current configuration in five words."
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```
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### Clearing the Prompt
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```bash
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python agent_with_adk_format/a2a_hot_swap.py \
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--context demo-session \
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--prompt "" \
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--config
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```
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## Control Messages (for reference)
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Behind the scenes the helper sends plain text messages understood by the callbacks:
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- `[HOTSWAP:MODEL:provider/model]`
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- `[HOTSWAP:PROMPT:text]`
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- `[HOTSWAP:GET_CONFIG]`
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You can craft the same messages from any A2A client if you prefer.
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