cookbook: add MLflow observability integration via OpenInference

cookbook/92_integrations/observability/README.md

@@ -16,6 +16,7 @@ Observability examples for tracing and monitoring Agno agents, teams, and workfl
 - `langtrace_op.py`
 - `langwatch_op.py`
 - `logfire_via_openinference.py`
+- `mlflow_via_openinference.py`
 - `maxim_ops.py`
 - `opik_via_openinference.py`
 - `trace_to_database.py`

cookbook/92_integrations/observability/mlflow_via_openinference.py

@@ -0,0 +1,63 @@
+"""
+MLflow Via OpenInference
+========================
+
+Demonstrates instrumenting an Agno agent with OpenInference and sending traces to MLflow.
+
+Requirements:
+    pip install mlflow opentelemetry-exporter-otlp-proto-http openinference-instrumentation-agno
+
+Start MLflow with OTLP tracing enabled:
+    mlflow server --host 127.0.0.1 --port 5000
+"""
+
+import asyncio
+import os
+
+from agno.agent import Agent
+from agno.models.openai import OpenAIChat
+from agno.tools.yfinance import YFinanceTools
+from openinference.instrumentation.agno import AgnoInstrumentor
+from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
+from opentelemetry.sdk.trace import TracerProvider
+from opentelemetry.sdk.trace.export import SimpleSpanProcessor
+
+# ---------------------------------------------------------------------------
+# Setup
+# ---------------------------------------------------------------------------
+MLFLOW_TRACKING_URI = os.getenv("MLFLOW_TRACKING_URI", "http://127.0.0.1:5000")
+
+endpoint = f"{MLFLOW_TRACKING_URI}/api/2.0/mlflow/traces"
+
+tracer_provider = TracerProvider()
+tracer_provider.add_span_processor(
+    SimpleSpanProcessor(OTLPSpanExporter(endpoint=endpoint))
+)
+
+# Start instrumenting agno
+AgnoInstrumentor().instrument(tracer_provider=tracer_provider)
+
+
+# ---------------------------------------------------------------------------
+# Create Agent
+# ---------------------------------------------------------------------------
+agent = Agent(
+    name="Stock Price Agent",
+    model=OpenAIChat(id="gpt-4o"),
+    tools=[YFinanceTools()],
+    instructions="You are a stock price agent. Answer questions in the style of a stock analyst.",
+)
+
+
+# ---------------------------------------------------------------------------
+# Run Example
+# ---------------------------------------------------------------------------
+async def main() -> None:
+    await agent.aprint_response(
+        "What is the current price of Tesla? Then find the current price of NVIDIA",
+        stream=True,
+    )
+
+
+if __name__ == "__main__":
+    asyncio.run(main())