Copy as Markdown[Open in ChatGPT](https://chatgpt.com/?q=Read%20https%3A%2F%2Fcoralogix.com%2Fdocs%2Fintegrations%2Fai-observability%2Fopenai.md%20and%20help%20me%20with%20my%20question%20about%20this%20Coralogix%20documentation%20page.)[Open in Claude](https://claude.ai/new?q=Read%20https%3A%2F%2Fcoralogix.com%2Fdocs%2Fintegrations%2Fai-observability%2Fopenai.md%20and%20help%20me%20with%20my%20question%20about%20this%20Coralogix%20documentation%20page.)

# OpenAI

Coralogix's AI Observability integrations enable organizations to gain deep insight into their AI applications, helping them monitor, analyze, and optimize performance across the stack. Through integrations with OpenAI, Coralogix delivers end-to-end visibility into AI workloads, supporting proactive issue detection and efficient performance tuning.

## Overview[​](#overview "Direct link to Overview")

This library offers customized [OpenTelemetry instrumentation](https://github.com/open-telemetry/opentelemetry-python-contrib/) for the OpenAI SDK, optimized to support large language model (LLM) application development with streamlined integration, detailed production tracing, and effective debugging capabilities.

## Requirements[​](#requirements "Direct link to Requirements")

* Python 3.10–3.13.
* Coralogix [API keys](https://coralogix.com/docs/docs/user-guides/account-management/api-keys/api-keys/.md).

## Installation[​](#installation "Direct link to Installation")

Run the following command.

```
pip install "llm-tracekit-openai"
```

## Authentication[​](#authentication "Direct link to Authentication")

Authentication data is passed during OTel Span Exporter definition:

1. Choose the
   <!-- -->
   ingress.:443
   <!-- -->
   endpoint that corresponds to your Coralogix [domain](https://coralogix.com/docs/docs/user-guides/account-management/account-settings/coralogix-domain/.md) using the domain selector at the top of the page.
2. Use your [customized API key](https://coralogix.com/docs/docs/user-guides/account-management/api-keys/api-keys/.md) in the authorization request header.
3. Provide the [application and subsystem names](https://coralogix.com/docs/docs/user-guides/account-management/account-settings/application-and-subsystem-names/.md).

```
from llm_tracekit.openai import setup_export_to_coralogix



setup_export_to_coralogix(

    coralogix_token=<your_coralogix_token>,

    coralogix_endpoint="ingress.eu2.coralogix.com:443",

    service_name="ai-service",

    application_name="ai-application",

    subsystem_name="ai-subsystem",

    capture_content=True,

)
```

Note

All of the authentication parameters can also be provided through environment variables (`CX_TOKEN`, `CX_ENDPOINT`, etc.).

## Usage[​](#usage "Direct link to Usage")

This section describes how to set up instrumentation for OpenAI.

### Set up tracing[​](#set-up-tracing "Direct link to Set up tracing")

**Automatic**

Use the `setup_export_to_coralogix` function to set up tracing and export traces to Coralogix. See the code snippet in the [Authentication](#authentication) section.

**Manual**

Alternatively, you can set up tracing manually.

```
from opentelemetry import trace

from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter

from opentelemetry.sdk.resources import SERVICE_NAME, Resource

from opentelemetry.sdk.trace import TracerProvider

from opentelemetry.sdk.trace.export import SimpleSpanProcessor



tracer_provider = TracerProvider(

    resource=Resource.create({SERVICE_NAME: "ai-service"}),

)

exporter = OTLPSpanExporter()

span_processor = SimpleSpanProcessor(exporter)

tracer_provider.add_span_processor(span_processor)

trace.set_tracer_provider(tracer_provider)
```

### Instrument[​](#instrument "Direct link to Instrument")

To instrument all clients, call the `instrument` method.

```
from llm_tracekit.openai import OpenAIInstrumentor



OpenAIInstrumentor().instrument()
```

### Uninstrument[​](#uninstrument "Direct link to Uninstrument")

To uninstrument clients, call the `uninstrument` method.

```
OpenAIInstrumentor().uninstrument()
```

### Full example[​](#full-example "Direct link to Full example")

```
from llm_tracekit.openai import OpenAIInstrumentor, setup_export_to_coralogix

from openai import OpenAI



# Optional: Configure sending spans to Coralogix

# Reads Coralogix connection details from the following environment variables:

# - CX_TOKEN

# - CX_ENDPOINT

setup_export_to_coralogix(

    service_name="ai-service",

    application_name="ai-application",

    subsystem_name="ai-subsystem",

    capture_content=True,

)



# Activate instrumentation

OpenAIInstrumentor().instrument()



# OpenAI usage example

client = OpenAI()

response = client.chat.completions.create(

    model="gpt-4o-mini",

    messages=[

        {"role": "user", "content": "Write a short poem on open telemetry."},

    ],

)
```

### Responses API[​](#responses-api "Direct link to Responses API")

The instrumentation also covers the OpenAI Responses API.

```
from openai import OpenAI



client = OpenAI()

response = client.responses.create(

    model="gpt-4o-mini",

    input="Write a haiku about OpenTelemetry.",

)
```

Streaming is supported:

```
from openai import OpenAI



client = OpenAI()

with client.responses.stream(

    model="gpt-4o-mini",

    input="Write a haiku about OpenTelemetry.",

) as stream:

    for event in stream:

        pass

    response = stream.get_final_response()
```

### Enable message content capture[​](#enable-message-content-capture "Direct link to Enable message content capture")

By default, message content, such as the contents of the prompt, completion, function arguments and return values, are not captured. To capture message content as span attributes:

* Pass `capture_content=True` when calling `setup_export_to_coralogix`.

* Set the environment variable `OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT` to `true`.

Most Coralogix AI evaluations require message contents to function properly, so enabling message capture is strongly recommended.

### Key differences from OpenTelemetry[​](#key-differences-from-opentelemetry "Direct link to Key differences from OpenTelemetry")

* The `user` parameter in the OpenAI Chat Completions API is captured in the span as the `gen_ai.request.user` attribute.
* User prompts and model responses are captured as span attributes instead of log events, as detailed below.

## Semantic conventions[​](#semantic-conventions "Direct link to Semantic conventions")

| Attribute                                                                            | Type   | Description                                                                               | Example                                                                                        |
| ------------------------------------------------------------------------------------ | ------ | ----------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------- |
| `gen_ai.prompt.<message_number>.role`                                                | string | Role of message author for user message `<message_number>`                                | `system`, `user`, `assistant`, `tool`                                                          |
| `gen_ai.prompt.<message_number>.content`                                             | string | Contents of user message `<message_number>`                                               | `What's the weather in Paris?`                                                                 |
| `gen_ai.prompt.<message_number>.tool_calls.<tool_call_number>.id`                    | string | ID of tool call in user message `<message_number>`                                        | `call_O8NOz8VlxosSASEsOY7LDUcP`                                                                |
| `gen_ai.prompt.<message_number>.tool_calls.<tool_call_number>.type`                  | string | Type of tool call in user message `<message_number>`                                      | `function`                                                                                     |
| `gen_ai.prompt.<message_number>.tool_calls.<tool_call_number>.function.name`         | string | The name of the function used in tool call within user message `<message_number>`         | `get_current_weather`                                                                          |
| `gen_ai.prompt.<message_number>.tool_calls.<tool_call_number>.function.arguments`    | string | Arguments passed to the function used in tool call within user message `<message_number>` | `{"location": "Seattle, WA"}`                                                                  |
| `gen_ai.prompt.<message_number>.tool_call_id`                                        | string | Tool call ID in user message `<message_number>`                                           | `call_mszuSIzqtI65i1wAUOE8w5H4`                                                                |
| `gen_ai.completion.<choice_number>.role`                                             | string | Role of message author for choice `<choice_number>` in model response                     | `assistant`                                                                                    |
| `gen_ai.completion.<choice_number>.finish_reason`                                    | string | Finish reason for choice `<choice_number>` in model response                              | `stop`, `tool_calls`, `error`                                                                  |
| `gen_ai.completion.<choice_number>.content`                                          | string | Contents of choice `<choice_number>` in model response                                    | `The weather in Paris is rainy and overcast, with temperatures around 57°F`                    |
| `gen_ai.completion.<choice_number>.tool_calls.<tool_call_number>.id`                 | string | ID of tool call in choice `<choice_number>`                                               | `call_O8NOz8VlxosSASEsOY7LDUcP`                                                                |
| `gen_ai.completion.<choice_number>.tool_calls.<tool_call_number>.type`               | string | Type of tool call in choice `<choice_number>`                                             | `function`                                                                                     |
| `gen_ai.completion.<choice_number>.tool_calls.<tool_call_number>.function.name`      | string | The name of the function used in tool call within choice `<choice_number>`                | `get_current_weather`                                                                          |
| `gen_ai.completion.<choice_number>.tool_calls.<tool_call_number>.function.arguments` | string | Arguments passed to the function used in tool call within choice `<choice_number>`        | `{"location": "Seattle, WA"}`                                                                  |
| `gen_ai.request.tools.<tool_number>.type`                                            | string | Type of tool entry in tools list                                                          | `function`                                                                                     |
| `gen_ai.request.tools.<tool_number>.function.name`                                   | string | The name of the function to use in tool calls                                             | `get_current_weather`                                                                          |
| `gen_ai.request.tools.<tool_number>.function.description`                            | string | Description of the function                                                               | `Get the current weather in a given location`                                                  |
| `gen_ai.request.tools.<tool_number>.function.parameters`                             | string | JSON describing the schema of the function parameters                                     | `{"type": "object", "properties": {"location": {"type": "string"}}, "required": ["location"]}` |
| `gen_ai.request.user`                                                                | string | A unique identifier representing the end user                                             | `user@company.com`                                                                             |

### Function spans[​](#function-spans "Direct link to Function spans")

These spans represent the execution of a tool (a Python function).

| Attribute | Type   | Description                                               | Example                                      |
| --------- | ------ | --------------------------------------------------------- | -------------------------------------------- |
| `type`    | string | The type of the span, identifying it as a function.       | `function`                                   |
| `name`    | string | The name of the function that was called.                 | `get_current_weather`                        |
| `input`   | string | The JSON string of arguments passed to the function.      | `{"city":"Tel Aviv"}`                        |
| `output`  | string | The string representation of the function's return value. | `The weather in Tel Aviv is 30°C and sunny.` |

### Enriched LLM call spans[​](#enriched-llm-call-spans "Direct link to Enriched LLM call spans")

These attributes are added to the existing span to link LLM calls back to the responsible agent.

| Attribute           | Type   | Description                                         | Example                     |
| ------------------- | ------ | --------------------------------------------------- | --------------------------- |
| `gen_ai.agent.name` | string | The name of the agent that initiated this LLM call. | `Assistant`, `WeatherAgent` |

## Next steps[​](#next-steps "Direct link to Next steps")

Once your integration is set up, explore the [AI Center Overview](https://coralogix.com/docs/docs/user-guides/ai/monitor/.md) to monitor performance, costs, quality issues, and security across all your AI applications — and to set up [Guardrails](https://coralogix.com/docs/docs/user-guides/ai/guardrails/.md) for real-time policy enforcement.