> ## Documentation Index
> Fetch the complete documentation index at: https://futureagi.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# OpenAI

## 1. Installation

First install the traceAI package to access the observability framework

<CodeGroup>
  ```bash Python theme={null}
  pip install traceAI-openai
  ```

  ```bash JS/TS theme={null}
  npm install @traceai/openai
  ```
</CodeGroup>

***

## 2. Set Environment Variables

Set up your environment variables to authenticate with both FutureAGI and OpenAI services.

<CodeGroup>
  ```python Python theme={null}
  import os
  os.environ["OPENAI_API_KEY"] = "your-openai-api-key"
  os.environ["FI_API_KEY"] = "your-futureagi-api-key"
  os.environ["FI_SECRET_KEY"] = "your-futureagi-secret-key"
  ```

  ```typescript JS/TS theme={null}
  process.env.OPENAI_API_KEY = OPENAI_API_KEY;
  process.env.FI_API_KEY = FI_API_KEY;
  process.env.FI_SECRET_KEY = FI_SECRET_KEY;
  ```
</CodeGroup>

***

## 3. Initialize Trace Provider

Set up the trace provider to create a new project in FutureAGI, establish telemetry data pipelines .

<CodeGroup>
  ```python Python theme={null}
  from fi_instrumentation import register
  from fi_instrumentation.fi_types import ProjectType

  trace_provider = register(
      project_type=ProjectType.OBSERVE,
      project_name="openai_project",
  )
  ```

  ```typescript JS/TS theme={null}
  import { register, ProjectType } from "@traceai/fi-core";

  const tracerProvider = register({
      project_type: ProjectType.OBSERVE,
      project_name: "openai_project",
  });
  ```
</CodeGroup>

***

## 4. Instrument your Project

Instrument your Project with OpenAI Instrumentor. This step ensures that all interactions with the OpenAI are tracked and monitored.

<CodeGroup>
  ```python Python theme={null}
  from traceai_openai import OpenAIInstrumentor

  OpenAIInstrumentor().instrument(tracer_provider=trace_provider)
  ```

  ```typescript JS/TS theme={null}
  import { OpenAIInstrumentation } from "@traceai/openai";
  import { registerInstrumentations } from "@opentelemetry/instrumentation";

  const openaiInstrumentation = new OpenAIInstrumentation({});

    registerInstrumentations({
      instrumentations: [openaiInstrumentation],
      tracerProvider: tracerProvider,
    });
  ```
</CodeGroup>

***

## 5. Interact with OpenAI

Interact with the OpenAI as you normally would. Our Instrumentor will automatically trace and send the telemetry data to our platform.

### Chat Completion

<CodeGroup>
  ```python Python theme={null}
  import httpx
  import base64
  from openai import OpenAI

  client = OpenAI()

  image_url = "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
  image_media_type = "image/jpeg"
  image_data = base64.standard_b64encode(httpx.get(image_url).content).decode("utf-8")

  response = client.chat.completions.create(
      model="gpt-4o",
      messages=[
          {
              "role": "user",
              "content": [
                  {"type": "text", "text": "What is in this image?"},
                  {
                      "type": "image_url",
                      "image_url": {
                          "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg",
                      },
                  }
              ],
          },
      ],
  )

  print(response.choices[0].message.content)
  ```

  ```typescript JS/TS theme={null}
  import { OpenAI } from "openai";

  const client = new OpenAI();

  const response = await client.chat.completions.create({
      model: "gpt-4o",
      messages: [{ role: "user", content: "What is the capital of South Africa?" }],
  });

  console.log(response.choices[0].message.content);
  ```
</CodeGroup>

### Audio and speech

```python theme={null}
import requests
import base64
from openai import OpenAI

client = OpenAI()

# Fetch the audio file and convert it to a base64 encoded string
url = "https://cdn.openai.com/API/docs/audio/alloy.wav"
response = requests.get(url)
response.raise_for_status()
wav_data = response.content
encoded_string = base64.b64encode(wav_data).decode("utf-8")

completion = client.chat.completions.create(
    model="gpt-4o-audio-preview",
    modalities=["text", "audio"],
    audio={"voice": "alloy", "format": "wav"},
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "What is in this recording?"},
                {
                    "type": "input_audio",
                    "input_audio": {"data": encoded_string, "format": "wav"},
                },
            ],
        },
    ],
)
```

### Image Generation

```python theme={null}
from openai import OpenAI

client = OpenAI()

response = client.images.generate(
    model="dall-e-3",
    prompt="a horse running through a field of flowers",
    size="1024x1024",
    n=1,
)

print(response.data[0].url)
```

### Chat Streaming

```python theme={null}
from openai import OpenAI

client = OpenAI()

completion = client.chat.completions.create(
    model="gpt-4o",
    stream=True,
    messages=[
        {
            "role": "user",
            "content": "What is OpenAI?",
        },
    ],
)

for chunk in completion:
    print(chunk.choices[0].delta.content, end="")
```