vision-agents-plugins-aws


Namevision-agents-plugins-aws JSON
Version 0.1.8 PyPI version JSON
download
home_pageNone
SummaryAWS (Bedrock) LLM integration for Vision Agents
upload_time2025-10-22 01:50:58
maintainerNone
docs_urlNone
authorNone
requires_python>=3.12
licenseNone
keywords ai llm agents aws bedrock voice agents
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # AWS Plugin for Vision Agents

AWS (Bedrock) LLM integration for Vision Agents framework with support for both standard and realtime interactions.

## Installation

```bash
pip install vision-agents-plugins-aws
```

## Usage

### Standard LLM Usage

This example shows how to use qwen3 on bedrock for the LLM.

```python
agent = Agent(
    edge=getstream.Edge(),
    agent_user=User(name="Friendly AI"),
    instructions="Be nice to the user",
    llm=aws.LLM(model="qwen.qwen3-32b-v1:0"),
    tts=cartesia.TTS(),
    stt=deepgram.STT(),
    turn_detection=smart_turn.TurnDetection(buffer_duration=2.0, confidence_threshold=0.5),
)
```

The full example is available in example/aws_qwen_example.py

### Realtime Text/Image Usage

Nova sonic audio realtime STS is also supported:

```python    
agent = Agent(
    edge=getstream.Edge(),
    agent_user=User(name="Story Teller AI"),
    instructions="Tell a story suitable for a 7 year old about a dragon and a princess",
    llm=aws.Realtime(),
)
```

## Running the examples

Create a `.env` file, or cp .env.example to .env and fill in

```
STREAM_API_KEY=your_stream_api_key_here
STREAM_API_SECRET=your_stream_api_secret_here

AWS_BEARER_TOKEN_BEDROCK=
AWS_ACCESS_KEY_ID=
AWS_SECRET_ACCESS_KEY=

FAL_KEY=
CARTESIA_API_KEY=
DEEPGRAM_API_KEY=
```
            

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    "description": "# AWS Plugin for Vision Agents\n\nAWS (Bedrock) LLM integration for Vision Agents framework with support for both standard and realtime interactions.\n\n## Installation\n\n```bash\npip install vision-agents-plugins-aws\n```\n\n## Usage\n\n### Standard LLM Usage\n\nThis example shows how to use qwen3 on bedrock for the LLM.\n\n```python\nagent = Agent(\n    edge=getstream.Edge(),\n    agent_user=User(name=\"Friendly AI\"),\n    instructions=\"Be nice to the user\",\n    llm=aws.LLM(model=\"qwen.qwen3-32b-v1:0\"),\n    tts=cartesia.TTS(),\n    stt=deepgram.STT(),\n    turn_detection=smart_turn.TurnDetection(buffer_duration=2.0, confidence_threshold=0.5),\n)\n```\n\nThe full example is available in example/aws_qwen_example.py\n\n### Realtime Text/Image Usage\n\nNova sonic audio realtime STS is also supported:\n\n```python    \nagent = Agent(\n    edge=getstream.Edge(),\n    agent_user=User(name=\"Story Teller AI\"),\n    instructions=\"Tell a story suitable for a 7 year old about a dragon and a princess\",\n    llm=aws.Realtime(),\n)\n```\n\n## Running the examples\n\nCreate a `.env` file, or cp .env.example to .env and fill in\n\n```\nSTREAM_API_KEY=your_stream_api_key_here\nSTREAM_API_SECRET=your_stream_api_secret_here\n\nAWS_BEARER_TOKEN_BEDROCK=\nAWS_ACCESS_KEY_ID=\nAWS_SECRET_ACCESS_KEY=\n\nFAL_KEY=\nCARTESIA_API_KEY=\nDEEPGRAM_API_KEY=\n```",
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