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

# Audio Sentiment Analysis Team

This example demonstrates how an Agno Agent Team can collaborate to perform sentiment analysis on audio conversations using transcription and sentiment analysis agents working together.

## Code

```python cookbook/02_examples/teams/multimodal/audio_sentiment_analysis.py theme={null}
import requests
from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.media import Audio
from agno.models.google import Gemini
from agno.team import Team

transcription_agent = Agent(
    name="Audio Transcriber",
    role="Transcribe audio conversations accurately",
    model=Gemini(id="gemini-2.0-flash-exp"),
    instructions=[
        "Transcribe audio with speaker identification",
        "Maintain conversation structure and flow",
    ],
)

sentiment_analyst = Agent(
    name="Sentiment Analyst",
    role="Analyze emotional tone and sentiment in conversations",
    model=Gemini(id="gemini-2.0-flash-exp"),
    instructions=[
        "Analyze sentiment for each speaker separately",
        "Identify emotional patterns and conversation dynamics",
        "Provide detailed sentiment insights",
    ],
)

# Create a team for collaborative audio sentiment analysis
sentiment_team = Team(
    name="Audio Sentiment Team",
    members=[transcription_agent, sentiment_analyst],
    model=Gemini(id="gemini-2.0-flash-exp"),
    instructions=[
        "Analyze audio sentiment with conversation memory.",
        "Audio Transcriber: First transcribe audio with speaker identification.",
        "Sentiment Analyst: Analyze emotional tone and conversation dynamics.",
    ],
    add_history_to_context=True,
    markdown=True,
    db=SqliteDb(
        session_table="audio_sentiment_team_sessions",
        db_file="tmp/audio_sentiment_team.db",
    ),
)

url = "https://agno-public.s3.amazonaws.com/demo_data/sample_conversation.wav"

response = requests.get(url)
audio_content = response.content

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

sentiment_team.print_response(
    "What else can you tell me about this audio conversation?",
    stream=True,
)
```

## Usage

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

  <Step title="Install required libraries">
    ```bash theme={null}
    uv pip install agno requests google-generativeai
    ```
  </Step>

  <Step title="Set environment variables">
    ```bash theme={null}
    export GOOGLE_API_KEY=****
    ```
  </Step>

  <Step title="Run the agent">
    ```bash theme={null}
    python cookbook/02_examples/teams/multimodal/audio_sentiment_analysis.py
    ```
  </Step>
</Steps>