Merge branch 'main' into groundingMetadata

This commit is contained in:
Pete
2025-06-30 19:48:55 -04:00
committed by GitHub
148 changed files with 9172 additions and 1291 deletions

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@@ -61,7 +61,12 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"),
)
llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"))
llm = GoogleLLMService(
api_key=os.getenv("GOOGLE_API_KEY"),
model="gemini-2.5-flash",
# turn on thinking if you want it
# params=GoogleLLMService.InputParams(extra={"thinking_config": {"thinking_budget": 4096}}),)
)
messages = [
{

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@@ -214,7 +214,12 @@ transport_params = {
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"), model="gemini-2.0-flash-001")
llm = GoogleLLMService(
api_key=os.getenv("GOOGLE_API_KEY"),
model="gemini-2.5-flash",
# turn on thinking if you want it
# params=GoogleLLMService.InputParams(extra={"thinking_config": {"thinking_budget": 4096}}),
)
tts = GoogleTTSService(
voice_id="en-US-Chirp3-HD-Charon",

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@@ -0,0 +1,133 @@
#
# Copyright (c) 20242025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
import argparse
import os
from dotenv import load_dotenv
from loguru import logger
from mcp.client.session_group import StreamableHttpParameters
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.mcp_service import MCPClient
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
)
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o-mini")
try:
# Github MCP docs: https://github.com/github/github-mcp-server
# Enable Github Copilot on your GitHub account. Free tier is ok. (https://github.com/settings/copilot)
# Generate a personal access token. It must be a Fine-grained token, classic tokens are not supported. (https://github.com/settings/personal-access-tokens)
# Set permissions you want to use (eg. "all repositories", "profile: read/write", etc)
mcp = MCPClient(
server_params=StreamableHttpParameters(
url="https://api.githubcopilot.com/mcp/",
headers={"Authorization": f"Bearer {os.getenv('GITHUB_PERSONAL_ACCESS_TOKEN')}"},
)
)
except Exception as e:
logger.error(f"error setting up mcp")
logger.exception("error trace:")
tools = await mcp.register_tools(llm)
system = f"""
You are a helpful LLM in a WebRTC call.
Your goal is to answer questions about the user's GitHub repositories and account.
You have access to a number of tools provided by Github. Use any and all tools to help users.
Your output will be converted to audio so don't include special characters in your answers.
Don't overexplain what you are doing.
Just respond with short sentences when you are carrying out tool calls.
"""
messages = [{"role": "system", "content": system}]
context = OpenAILLMContext(messages, tools)
context_aggregator = llm.create_context_aggregator(context)
pipeline = Pipeline(
[
transport.input(), # Transport user input
stt,
context_aggregator.user(), # User spoken responses
llm, # LLM
tts, # TTS
transport.output(), # Transport bot output
context_aggregator.assistant(), # Assistant spoken responses and tool context
]
)
task = PipelineTask(
pipeline,
params=PipelineParams(
enable_metrics=True,
enable_usage_metrics=True,
),
)
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
logger.info(f"Client connected: {client}")
# Kick off the conversation.
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
await task.cancel()
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from pipecat.examples.run import main
main(run_example, transport_params=transport_params)

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@@ -10,8 +10,8 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.interruptions.min_words_interruption_strategy import MinWordsInterruptionStrategy
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import MinWordsInterruptionStrategy
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask

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@@ -7,9 +7,11 @@
import argparse
import asyncio
import os
import random
from contextlib import asynccontextmanager
from typing import Any, Dict
import sentry_sdk
import uvicorn
from dotenv import load_dotenv
from fastapi import FastAPI, Request, WebSocket
@@ -44,6 +46,7 @@ from pipecat.processors.aggregators.openai_llm_context import (
)
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIProcessor
from pipecat.processors.metrics.sentry import SentryMetrics
from pipecat.serializers.protobuf import ProtobufFrameSerializer
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
@@ -125,6 +128,7 @@ class SimulateFreezeInput(FrameProcessor):
self._send_frames_task = None
async def _send_user_text(self, text: str):
self.reset_watchdog()
# Emulation as if the user has spoken and the stt transcribed
await self.push_frame(UserStartedSpeakingFrame())
await self.push_frame(StartInterruptionFrame())
@@ -149,14 +153,13 @@ class SimulateFreezeInput(FrameProcessor):
logger.debug("SimulateFreezeInput _send_frames")
await self._send_user_text("Tell me a brief history of Brazil!")
await asyncio.sleep(3)
await self._send_user_text("")
break
# i += 1
# if i >= 5:
# break
await self._send_user_text("and who has discovered it")
i += 1
if i >= 20:
break
# sleeping 1s before interrupting
# wait_time = random.uniform(1, 10)
# await asyncio.sleep(wait_time)
wait_time = random.uniform(1, 10)
await asyncio.sleep(wait_time)
except Exception as e:
logger.error(f"{self} exception receiving data: {e.__class__.__name__} ({e})")
@@ -176,6 +179,11 @@ async def run_example(websocket_client):
),
)
sentry_sdk.init(
dsn=os.getenv("SENTRY_DSN"),
traces_sample_rate=1.0,
)
freeze = SimulateFreezeInput()
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -183,9 +191,13 @@ async def run_example(websocket_client):
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
metrics=SentryMetrics(),
)
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
llm = OpenAILLMService(
api_key=os.getenv("OPENAI_API_KEY"),
metrics=SentryMetrics(),
)
rtvi = RTVIProcessor(config=RTVIConfig(config=[]))
@@ -247,6 +259,7 @@ async def run_example(websocket_client):
},
),
],
enable_watchdog_timers=True,
)
@transport.event_handler("on_client_connected")