amazon_bedrock

Connect the call to an Amazon Bedrock AI agent. Similar to ai() but uses Amazon Bedrock as the LLM backend.

Parameters

prompt

Optional[Any]

The prompt configuration for the Bedrock agent.

SWAIG

Optional[dict]

SWAIG configuration for tool/function definitions.

ai_params

Optional[dict]

AI parameters for the Bedrock session.

global_data

Optional[dict]

Data accessible to the AI and SWAIG functions.

post_prompt

Optional[dict]

Post-prompt configuration.

post_prompt_url

Optional[str]

URL to receive the post-prompt result.

Returns

dict — Server response confirming the Bedrock session.

Example

1 from signalwire.relay import RelayClient
2 
3 client = RelayClient(
4     project="your-project-id",
5     token="your-api-token",
6     host="your-space.signalwire.com",
7     contexts=["default"],
8 )
9 
10 @client.on_call
11 async def handle_call(call):
12     await call.answer()
13 
14     # Start an Amazon Bedrock AI agent
15     result = await call.amazon_bedrock(
16         prompt={"text": "You are a helpful assistant."},
17         ai_params={"barge_confidence": 0.02},
18     )
19 
20 client.run()

1	from signalwire.relay import RelayClient
2
3	client = RelayClient(
4	project="your-project-id",
5	token="your-api-token",
6	host="your-space.signalwire.com",
7	contexts=["default"],
8	)
9
10	@client.on_call
11	async def handle_call(call):
12	await call.answer()
13
14	# Start an Amazon Bedrock AI agent
15	result = await call.amazon_bedrock(
16	prompt={"text": "You are a helpful assistant."},
17	ai_params={"barge_confidence": 0.02},
18	)
19
20	client.run()