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| 1 | +# |
| 2 | +# Copyright (c) 2024–2025, Daily |
| 3 | +# |
| 4 | +# SPDX-License-Identifier: BSD 2-Clause License |
| 5 | +# |
| 6 | + |
| 7 | +import os |
| 8 | + |
| 9 | +from dotenv import load_dotenv |
| 10 | +from loguru import logger |
| 11 | +from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter |
| 12 | +from pipecat.adapters.schemas.function_schema import FunctionSchema |
| 13 | +from pipecat.adapters.schemas.tools_schema import ToolsSchema |
| 14 | +from pipecat.audio.vad.silero import SileroVADAnalyzer |
| 15 | +from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame |
| 16 | +from pipecat.pipeline.pipeline import Pipeline |
| 17 | +from pipecat.pipeline.runner import PipelineRunner |
| 18 | +from pipecat.pipeline.task import PipelineParams, PipelineTask |
| 19 | +from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext |
| 20 | +from pipecat.runner.types import RunnerArguments |
| 21 | +from pipecat.runner.utils import create_transport |
| 22 | +from pipecat.services.cartesia.tts import CartesiaTTSService |
| 23 | +from pipecat.services.deepgram.stt import DeepgramSTTService |
| 24 | +from pipecat.services.llm_service import FunctionCallParams |
| 25 | +from pipecat.services.openai.llm import OpenAILLMService |
| 26 | +from pipecat.transports.base_transport import BaseTransport, TransportParams |
| 27 | +from pipecat.transports.daily.transport import DailyParams |
| 28 | +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams |
| 29 | +from pipecat.utils.tracing.setup import setup_tracing |
| 30 | + |
| 31 | +load_dotenv(override=True) |
| 32 | + |
| 33 | +IS_TRACING_ENABLED = bool(os.getenv("ENABLE_TRACING")) |
| 34 | + |
| 35 | +# Initialize tracing if enabled |
| 36 | +if IS_TRACING_ENABLED: |
| 37 | + # Create the exporter for Opik (HTTP/JSON only) |
| 38 | + # Opik supports HTTP transport for traces only (no logs or metrics) |
| 39 | + # Headers are configured via OTEL_EXPORTER_OTLP_HEADERS environment variable |
| 40 | + otlp_exporter = OTLPSpanExporter( |
| 41 | + endpoint=os.getenv( |
| 42 | + "OTEL_EXPORTER_OTLP_ENDPOINT", |
| 43 | + "https://www.comet.com/opik/api/v1/private/otel/v1/traces", |
| 44 | + ), |
| 45 | + ) |
| 46 | + |
| 47 | + # Set up tracing with the exporter |
| 48 | + setup_tracing( |
| 49 | + service_name="pipecat-demo", |
| 50 | + exporter=otlp_exporter, |
| 51 | + console_export=bool(os.getenv("OTEL_CONSOLE_EXPORT")), |
| 52 | + ) |
| 53 | + logger.info("OpenTelemetry tracing initialized for Opik") |
| 54 | + |
| 55 | + |
| 56 | +async def fetch_weather_from_api(params: FunctionCallParams): |
| 57 | + await params.result_callback({"conditions": "nice", "temperature": "75"}) |
| 58 | + |
| 59 | + |
| 60 | +# We store functions so objects (e.g. SileroVADAnalyzer) don't get |
| 61 | +# instantiated. The function will be called when the desired transport gets |
| 62 | +# selected. |
| 63 | +transport_params = { |
| 64 | + "daily": lambda: DailyParams( |
| 65 | + audio_in_enabled=True, |
| 66 | + audio_out_enabled=True, |
| 67 | + vad_analyzer=SileroVADAnalyzer(), |
| 68 | + ), |
| 69 | + "twilio": lambda: FastAPIWebsocketParams( |
| 70 | + audio_in_enabled=True, |
| 71 | + audio_out_enabled=True, |
| 72 | + vad_analyzer=SileroVADAnalyzer(), |
| 73 | + ), |
| 74 | + "webrtc": lambda: TransportParams( |
| 75 | + audio_in_enabled=True, |
| 76 | + audio_out_enabled=True, |
| 77 | + vad_analyzer=SileroVADAnalyzer(), |
| 78 | + ), |
| 79 | +} |
| 80 | + |
| 81 | + |
| 82 | +async def run_bot(transport: BaseTransport): |
| 83 | + logger.info(f"Starting bot") |
| 84 | + |
| 85 | + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) |
| 86 | + |
| 87 | + tts = CartesiaTTSService( |
| 88 | + api_key=os.getenv("CARTESIA_API_KEY"), |
| 89 | + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady |
| 90 | + ) |
| 91 | + |
| 92 | + llm = OpenAILLMService( |
| 93 | + api_key=os.getenv("OPENAI_API_KEY"), params=OpenAILLMService.InputParams(temperature=0.5) |
| 94 | + ) |
| 95 | + |
| 96 | + # You can also register a function_name of None to get all functions |
| 97 | + # sent to the same callback with an additional function_name parameter. |
| 98 | + llm.register_function("get_current_weather", fetch_weather_from_api) |
| 99 | + |
| 100 | + @llm.event_handler("on_function_calls_started") |
| 101 | + async def on_function_calls_started(service, function_calls): |
| 102 | + await tts.queue_frame(TTSSpeakFrame("Let me check on that.")) |
| 103 | + |
| 104 | + weather_function = FunctionSchema( |
| 105 | + name="get_current_weather", |
| 106 | + description="Get the current weather", |
| 107 | + properties={ |
| 108 | + "location": { |
| 109 | + "type": "string", |
| 110 | + "description": "The city and state, e.g. San Francisco, CA", |
| 111 | + }, |
| 112 | + "format": { |
| 113 | + "type": "string", |
| 114 | + "enum": ["celsius", "fahrenheit"], |
| 115 | + "description": "The temperature unit to use. Infer this from the user's location.", |
| 116 | + }, |
| 117 | + }, |
| 118 | + required=["location", "format"], |
| 119 | + ) |
| 120 | + tools = ToolsSchema(standard_tools=[weather_function]) |
| 121 | + |
| 122 | + messages = [ |
| 123 | + { |
| 124 | + "role": "system", |
| 125 | + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.", |
| 126 | + }, |
| 127 | + ] |
| 128 | + |
| 129 | + context = OpenAILLMContext(messages, tools) |
| 130 | + context_aggregator = llm.create_context_aggregator(context) |
| 131 | + |
| 132 | + pipeline = Pipeline( |
| 133 | + [ |
| 134 | + transport.input(), |
| 135 | + stt, |
| 136 | + context_aggregator.user(), |
| 137 | + llm, |
| 138 | + tts, |
| 139 | + transport.output(), |
| 140 | + context_aggregator.assistant(), |
| 141 | + ] |
| 142 | + ) |
| 143 | + |
| 144 | + task = PipelineTask( |
| 145 | + pipeline, |
| 146 | + params=PipelineParams( |
| 147 | + enable_metrics=True, |
| 148 | + enable_usage_metrics=True, |
| 149 | + ), |
| 150 | + enable_tracing=IS_TRACING_ENABLED, |
| 151 | + # Optionally, add a conversation ID to track the conversation |
| 152 | + # conversation_id="8df26cc1-6db0-4a7a-9930-1e037c8f1fa2", |
| 153 | + ) |
| 154 | + |
| 155 | + @transport.event_handler("on_client_connected") |
| 156 | + async def on_client_connected(transport, client): |
| 157 | + logger.info(f"Client connected") |
| 158 | + # Kick off the conversation. |
| 159 | + await task.queue_frames([LLMRunFrame()]) |
| 160 | + |
| 161 | + @transport.event_handler("on_client_disconnected") |
| 162 | + async def on_client_disconnected(transport, client): |
| 163 | + logger.info(f"Client disconnected") |
| 164 | + await task.cancel() |
| 165 | + |
| 166 | + runner = PipelineRunner(handle_sigint=False) |
| 167 | + |
| 168 | + await runner.run(task) |
| 169 | + |
| 170 | + |
| 171 | +async def bot(runner_args: RunnerArguments): |
| 172 | + """Main bot entry point compatible with Pipecat Cloud.""" |
| 173 | + transport = await create_transport(runner_args, transport_params) |
| 174 | + await run_bot(transport) |
| 175 | + |
| 176 | + |
| 177 | +if __name__ == "__main__": |
| 178 | + from pipecat.runner.run import main |
| 179 | + |
| 180 | + main() |
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