Haystack by deepset Integration

Updated on Aug 14, 2026

Use this integration when your Haystack application is implemented in Python.

Setup

1. Install SDK

bash

pip install progress-observability

2. Instrument your app

python

Observability.instrument(
    app_name=os.getenv("OBSERVABILITY_APP_NAME"),
    api_key=os.getenv("OBSERVABILITY_API_KEY")
)

3. Complete example

Note: Haystack doesn't emit OpenTelemetry spans natively. Calling tracing.enable_tracing(OpenTelemetryTracer(...)) after Observability.instrument() connects Haystack's internal tracer to the OTel pipeline, giving you a structured trace tree with LLM calls and tool invocations under the same trace.

python

import os
from dotenv import load_dotenv

load_dotenv()
os.environ["HAYSTACK_CONTENT_TRACING_ENABLED"] = "true"

from haystack.components.agents import Agent
from haystack.tools import Tool
from haystack.components.generators.chat import OpenAIChatGenerator
from haystack.utils import Secret
from haystack.dataclasses import ChatMessage
from haystack import tracing
from haystack_integrations.tracing.opentelemetry import OpenTelemetryTracer
from opentelemetry import trace as otel_trace

from progress.observability import Observability

# Instrument: sets up the exporter and patches the OpenAI client for LLM spans.
Observability.instrument(
    app_name=os.getenv("OBSERVABILITY_APP_NAME"),
    api_key=os.getenv("OBSERVABILITY_API_KEY"),
)

# Enable Haystack's OTel tracer so agent and tool spans are part of the same trace.
tracing.enable_tracing(OpenTelemetryTracer(otel_trace.get_tracer("haystack")))


def get_weather(location: str) -> str:
    """Get the weather for a given location."""
    return f"The weather in {location} is cloudy with a high of 15°C."


weather_tool = Tool(
    name="get_weather",
    description="Get the weather for a given location.",
    parameters={
        "type": "object",
        "properties": {"location": {"type": "string", "description": "City or location name"}},
        "required": ["location"],
    },
    function=get_weather,
)

model = os.getenv("OPENAI_MODEL", "gpt-4o-mini")

agent = Agent(
    chat_generator=OpenAIChatGenerator(
        api_key=Secret.from_token(os.getenv("OPENAI_API_KEY", "")),
        model=model,
    ),
    tools=[weather_tool],
    system_prompt="You are a helpful AI assistant.",
    tool_concurrency_limit=1,
)

result = agent.run(messages=[ChatMessage.from_user("What's the weather in Paris?")])

Observability.shutdown()