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7 Commits

Author SHA1 Message Date
James Hush
c6d759e043 Save 2025-05-09 12:17:15 +08:00
kompfner
9643296e29 Merge pull request #1779 from pipecat-ai/pk/aws-nova-sonic-missing-params-export
Add missing `Params` export to AWS Nova Sonic module
2025-05-08 16:04:38 -04:00
Paul Kompfner
c83c5b5a34 Add missing Params export to AWS Nova Sonic module 2025-05-08 15:23:25 -04:00
Mark Backman
7280e390d9 Merge pull request #1774 from pipecat-ai/mb/moondream-ex-server
Add load_dotenv to moondream example server
2025-05-07 19:02:30 -04:00
Mark Backman
4efc3f0a39 Merge pull request #1775 from pipecat-ai/mb/patient-ex-env
Add load_dotenv to patient-intake server file
2025-05-07 19:02:20 -04:00
Mark Backman
cb7e7a8aa3 Add load_dotenv to patient-intake server file 2025-05-07 18:40:04 -04:00
Mark Backman
9136402846 Add load_dotenv to moondream example server 2025-05-07 18:29:27 -04:00
4 changed files with 22 additions and 11 deletions

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@@ -34,6 +34,7 @@ from pipecat.processors.aggregators.openai_llm_context import (
from pipecat.processors.frame_processor import FrameProcessor
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.google.llm import GoogleLLMContext, GoogleLLMService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
@@ -286,16 +287,18 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
)
conversation_llm = GoogleLLMService(
name="Conversation",
model="gemini-2.0-flash-001",
# model="gemini-exp-1121",
api_key=os.getenv("GOOGLE_API_KEY"),
# we can give the GoogleLLMService a system instruction to use directly
# in the GenerativeModel constructor. Let's do that rather than put
# our system message in the messages list.
system_instruction=conversation_system_message,
)
# conversation_llm = GoogleLLMService(
# name="Conversation",
# model="gemini-2.0-flash-001",
# # model="gemini-exp-1121",
# api_key=os.getenv("GOOGLE_API_KEY"),
# # we can give the GoogleLLMService a system instruction to use directly
# # in the GenerativeModel constructor. Let's do that rather than put
# # our system message in the messages list.
# system_instruction=conversation_system_message,
# )
conversation_llm = OpenAILLMService(name="Conversation", api_key=os.getenv("OPENAI_API_KEY"))
input_transcription_llm = GoogleLLMService(
name="Transcription",

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@@ -10,12 +10,16 @@ import subprocess
from contextlib import asynccontextmanager
import aiohttp
from dotenv import load_dotenv
from fastapi import FastAPI, HTTPException, Request
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import JSONResponse, RedirectResponse
from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper, DailyRoomParams
# Load environment variables from .env file
load_dotenv(override=True)
MAX_BOTS_PER_ROOM = 1
# Bot sub-process dict for status reporting and concurrency control

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@@ -10,12 +10,16 @@ import subprocess
from contextlib import asynccontextmanager
import aiohttp
from dotenv import load_dotenv
from fastapi import FastAPI, HTTPException, Request
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import JSONResponse, RedirectResponse
from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper, DailyRoomParams
# Load environment variables from .env file
load_dotenv(override=True)
MAX_BOTS_PER_ROOM = 1
# Bot sub-process dict for status reporting and concurrency control

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@@ -1 +1 @@
from .aws import AWSNovaSonicLLMService
from .aws import AWSNovaSonicLLMService, Params