docs: add Langfuse integration section to README for tracing and observability
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README.md
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README.md
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- **LangGraph**: Framework for building stateful, multi-agent workflows
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- **ReactFlow**: Library for building node-based visual workflows
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## 📊 Langfuse Integration (Tracing & Observability)
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Evo AI platform natively supports integration with [Langfuse](https://langfuse.com/) for detailed tracing of agent executions, prompts, model responses, and tool calls, using the OpenTelemetry (OTel) standard.
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### Why use Langfuse?
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- Visual dashboard for agent traces, prompts, and executions
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- Detailed analytics for debugging and evaluating LLM apps
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- Easy integration with Google ADK and other frameworks
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### How it works
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- Every agent execution (including streaming) is automatically traced via OpenTelemetry spans
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- Data is sent to Langfuse, where it can be visualized and analyzed
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### How to configure
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1. **Set environment variables in your `.env`:**
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```env
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LANGFUSE_PUBLIC_KEY="pk-lf-..." # Your Langfuse public key
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LANGFUSE_SECRET_KEY="sk-lf-..." # Your Langfuse secret key
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OTEL_EXPORTER_OTLP_ENDPOINT="https://cloud.langfuse.com/api/public/otel" # (or us.cloud... for US region)
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```
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> **Attention:** Do not swap the keys! `pk-...` is public, `sk-...` is secret.
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2. **Automatic initialization**
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- Tracing is automatically initialized when the application starts (`src/main.py`).
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- Agent execution functions are already instrumented with spans (`src/services/agent_runner.py`).
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3. **View in the Langfuse dashboard**
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- Access your Langfuse dashboard to see real-time traces.
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### Troubleshooting
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- **401 Error (Invalid credentials):**
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- Check if the keys are correct and not swapped in your `.env`.
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- Make sure the endpoint matches your region (EU or US).
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- **Context error in async generator:**
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- The code is already adjusted to avoid OpenTelemetry context issues in async generators.
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- **Questions about integration:**
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- See the [official Langfuse documentation - Google ADK](https://langfuse.com/docs/integrations/google-adk)
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## 🤖 Agent 2 Agent (A2A) Protocol Support
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Evo AI implements the Google's Agent 2 Agent (A2A) protocol, enabling seamless communication and interoperability between AI agents. This implementation includes:
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