Appendix

Reference materials, patterns, best practices, and troubleshooting guides for the SignalWire Agents SDK.

About This Chapter

This appendix provides supplementary reference materials to support your development with the SignalWire Agents SDK.

Quick Reference

Chapter Contents

Overview

Setting Parameters in Python

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from signalwire_agents import AgentBase
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agent = AgentBase(name="assistant", route="/assistant")
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# Set AI parameters
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agent.set_params({
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    "temperature": 0.7,
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    "confidence": 0.6,
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    "end_of_speech_timeout": 2000,
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    "attention_timeout": 10000
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})

LLM API Parameters

These parameters control the AI model’s behavior. Set in prompt or post_prompt sections.

Temperature

Controls randomness in output generation:

• 0.0: Deterministic, consistent responses
• 0.3 (default): Balanced creativity
• 1.0+: More creative, less predictable

Reasoning Effort

For o1-style models only:

• "low": Quick responses
• "medium": Balanced reasoning
• "high": Deep analysis

ASR (Speech Recognition) Parameters

Control automatic speech recognition behavior.

Timing Parameters

Control various timeouts and timing behaviors.

Key Timeouts

• end_of_speech_timeout: Milliseconds of silence to detect end of speech
• attention_timeout: How long to wait before prompting user (0 disables)
• inactivity_timeout: How long before auto-hangup (default 10 minutes)

Hard Stop Time

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# Time expression format
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agent.set_params({
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    "hard_stop_time": "5m",      # 5 minutes
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    "hard_stop_time": "1h30m",   # 1 hour 30 minutes
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    "hard_stop_prompt": "We need to wrap up now."
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})

Behavior Parameters

Control various AI agent behaviors.

SWAIG Control Parameters

Interrupt Parameters

Debug Parameters

Audio Parameters

Hold Music with Tone

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# Use tone generator
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agent.set_params({
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    "hold_music": "tone:440"  # 440Hz tone
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})
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# Use audio file
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agent.set_params({
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    "hold_music": "https://example.com/hold-music.mp3"
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})

Video Parameters

String Parameters

VAD Configuration

Voice Activity Detection uses a string format: silero_thresh:frame_ms

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agent.set_params({
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    "vad_config": "0.5:30"  # threshold 0.5, 30ms frames
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})

Post-Prompt Parameter Defaults

Parameters have different defaults in post_prompt for more deterministic summaries:

Model-Specific Overrides

Different models support different parameters:

Complete Example

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#!/usr/bin/env python3
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# configured_agent.py - Agent with all AI parameters configured
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from signalwire_agents import AgentBase
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agent = AgentBase(name="configured", route="/configured")
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agent.prompt_add_section("Role", "You are a customer service agent.")
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agent.add_language("English", "en-US", "rime.spore")
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# Configure all parameters
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agent.set_params({
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    # LLM settings
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    "max_tokens": 300,
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    # Timing
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    "end_of_speech_timeout": 1500,
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    "attention_timeout": 8000,
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    "inactivity_timeout": 300000,
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    # Behavior
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    "wait_for_user": False,
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    "conscience": True,
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    "local_tz": "America/New_York",
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    # Audio
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    "background_file": "https://example.com/ambient.mp3",
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    "background_file_volume": -30
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})
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if __name__ == "__main__":
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    agent.run()

SWML Example

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{
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  "version": "1.0.0",
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  "sections": {
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    "main": [{
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      "ai": {
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        "params": {
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          "end_of_speech_timeout": 2000,
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          "attention_timeout": 10000,
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          "inactivity_timeout": 600000,
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          "wait_for_user": false,
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          "conscience": true,
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          "local_tz": "America/Chicago",
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          "background_file": "https://example.com/music.mp3",
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          "background_file_volume": -25
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        },
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        "prompt": {
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          "temperature": 0.3,
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          "top_p": 1.0,
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          "frequency_penalty": 0.1,
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          "presence_penalty": 0.1,
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          "text": "You are a helpful assistant."
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        },
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        "post_prompt": {
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          "temperature": 0.0,
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          "frequency_penalty": 0.0,
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          "presence_penalty": 0.0,
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          "text": "Summarize the conversation."
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        }
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      }
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    }]
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  }
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}