> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Audio To Text

> Demonstrates team-based audio transcription and follow-up content analysis.

```python audio_to_text.py theme={null}
"""
Audio To Text
=============================

Demonstrates team-based audio transcription and follow-up content analysis.
"""

import requests
from agno.agent import Agent
from agno.media import Audio
from agno.models.google import Gemini
from agno.team import Team

# ---------------------------------------------------------------------------
# Create Members
# ---------------------------------------------------------------------------
transcription_specialist = Agent(
    name="Transcription Specialist",
    role="Convert audio to accurate text transcriptions",
    model=Gemini(id="gemini-3.5-flash"),
    instructions=[
        "Transcribe audio with high accuracy",
        "Identify speakers clearly as Speaker A, Speaker B, etc.",
        "Maintain conversation flow and context",
    ],
)

content_analyzer = Agent(
    name="Content Analyzer",
    role="Analyze transcribed content for insights",
    model=Gemini(id="gemini-3.5-flash"),
    instructions=[
        "Analyze transcription for key themes and insights",
        "Provide summaries and extract important information",
    ],
)

# ---------------------------------------------------------------------------
# Create Team
# ---------------------------------------------------------------------------
audio_team = Team(
    name="Audio Analysis Team",
    model=Gemini(id="gemini-3.5-flash"),
    members=[transcription_specialist, content_analyzer],
    instructions=[
        "Work together to transcribe and analyze audio content.",
        "Transcription Specialist: First convert audio to accurate text with speaker identification.",
        "Content Analyzer: Analyze transcription for insights and key themes.",
    ],
    markdown=True,
)

# ---------------------------------------------------------------------------
# Run Team
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    url = "https://agno-public.s3.us-east-1.amazonaws.com/demo_data/QA-01.mp3"
    response = requests.get(url)
    audio_content = response.content

    audio_team.print_response(
        "Give a transcript of this audio conversation. Use speaker A, speaker B to identify speakers.",
        audio=[Audio(content=audio_content)],
        stream=True,
    )
```

## Run the Example

<Snippet file="create-venv-step.mdx" />

**1. Install dependencies**

```bash theme={null}
uv pip install -U agno google-genai requests
```

**2. Export your Google API key**

```bash Mac/Linux theme={null}
export GOOGLE_API_KEY="your_google_api_key_here"
```

```bash Windows theme={null}
$Env:GOOGLE_API_KEY="your_google_api_key_here"
```

**3. Run the example**

Save the code above as `audio_to_text.py`, then run:

```bash theme={null}
python audio_to_text.py
```

Full source: [cookbook/03\_teams/19\_multimodal/audio\_to\_text.py](https://github.com/agno-agi/agno/blob/v3.0.4/cookbook/03_teams/19_multimodal/audio_to_text.py)


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