Save progress
This commit is contained in:
James Hush
@@ -4,15 +4,18 @@
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import argparse
|
||||
import os
|
||||
from abc import ABC, abstractmethod
|
||||
from dataclasses import field
|
||||
from typing import Literal, Optional
|
||||
from typing import List, Literal, Optional
|
||||
|
||||
import httpx
|
||||
from agents import Agent, Runner
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from openai import BaseModel
|
||||
from openai import AsyncStream, BaseModel
|
||||
from openai.types.chat import ChatCompletionChunk, ChatCompletionMessageParam
|
||||
|
||||
from pipecat.adapters.schemas.tools_schema import ToolsSchema
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
@@ -70,10 +73,27 @@ class BackendBase(ABC):
|
||||
raise NotImplementedError("The method get_resp is not implemented.")
|
||||
|
||||
|
||||
class CompassLLMService(AIService):
|
||||
def __init__(self, backend: BackendBase):
|
||||
super().__init__()
|
||||
self.backend = backend
|
||||
class ChoiceDelta(BaseModel):
|
||||
content: Optional[str] = None
|
||||
"""The contents of the chunk message."""
|
||||
|
||||
|
||||
class Choice(BaseModel):
|
||||
delta: ChoiceDelta
|
||||
"""The contents of the chunk message."""
|
||||
|
||||
index: int
|
||||
"""The index of the choice in the list of choices."""
|
||||
|
||||
|
||||
class CustomLLMService(BaseOpenAILLMService):
|
||||
def __init__(self, **kwargs):
|
||||
super().__init__(**kwargs)
|
||||
self._client = Agent(
|
||||
name="Assistant agent",
|
||||
instructions="Respond with haikus.",
|
||||
# tools=[get_weather],
|
||||
)
|
||||
|
||||
def create_context_aggregator(
|
||||
self,
|
||||
@@ -82,7 +102,9 @@ class CompassLLMService(AIService):
|
||||
user_params: LLMUserAggregatorParams = LLMUserAggregatorParams(),
|
||||
assistant_params: LLMAssistantAggregatorParams = LLMAssistantAggregatorParams(),
|
||||
) -> OpenAIContextAggregatorPair:
|
||||
"""Create an instance of OpenAIContextAggregatorPair from an
|
||||
"""Create an instance of OpenAIContextAggregatorPair.
|
||||
|
||||
from an
|
||||
OpenAILLMContext. Constructor keyword arguments for both the user and
|
||||
assistant aggregators can be provided.
|
||||
|
||||
@@ -102,52 +124,63 @@ class CompassLLMService(AIService):
|
||||
assistant = OpenAIAssistantContextAggregator(context, params=assistant_params)
|
||||
return OpenAIContextAggregatorPair(_user=user, _assistant=assistant)
|
||||
|
||||
async def process_frame(self, frame: Frame, direction: FrameDirection):
|
||||
await super().process_frame(frame, direction)
|
||||
def create_client(
|
||||
self,
|
||||
api_key=None,
|
||||
base_url=None,
|
||||
organization=None,
|
||||
project=None,
|
||||
default_headers=None,
|
||||
**kwargs,
|
||||
):
|
||||
return Agent(
|
||||
name="Assistant agent",
|
||||
instructions="Respond with haikus.",
|
||||
# tools=[get_weather],
|
||||
)
|
||||
|
||||
context = None
|
||||
if isinstance(frame, OpenAILLMContextFrame):
|
||||
context: OpenAILLMContext = frame.context
|
||||
elif isinstance(frame, LLMMessagesFrame):
|
||||
context = OpenAILLMContext.from_messages(frame.messages)
|
||||
elif isinstance(frame, LLMUpdateSettingsFrame):
|
||||
await self._update_settings(frame.settings)
|
||||
else:
|
||||
await self.push_frame(frame, direction)
|
||||
async def get_chat_completions(
|
||||
self, context: OpenAILLMContext, messages: List[ChatCompletionMessageParam]
|
||||
) -> AsyncStream[ChatCompletionChunk]:
|
||||
# self._client.tools = context.tools
|
||||
logger.info(f"get_chat_completions: {self._client}")
|
||||
|
||||
if context:
|
||||
try:
|
||||
await self.push_frame(LLMFullResponseStartFrame())
|
||||
await self.start_processing_metrics()
|
||||
# await self._process_context(context)
|
||||
result = Runner.run_streamed(
|
||||
# context=context,
|
||||
starting_agent=self._client,
|
||||
input="Tell a joke about pirates.", # messages
|
||||
# ---
|
||||
# no func tool
|
||||
# input="give me a 2 sentences about life",
|
||||
)
|
||||
|
||||
msgs = []
|
||||
for contmsg in context.messages:
|
||||
msgs.append(
|
||||
LlmMessage(
|
||||
role=contmsg["role"],
|
||||
content=contmsg["content"],
|
||||
)
|
||||
logger.info(f"get_chat_completions: {result}")
|
||||
|
||||
if result is None:
|
||||
logger.error("Runner.run_streamed returned None")
|
||||
return
|
||||
|
||||
async for event in result.stream_events():
|
||||
# if not event.type == "raw_response_event":
|
||||
# break
|
||||
if event.type == "raw_response_event":
|
||||
if event.data.type == "response.output_text.delta":
|
||||
delta = ChoiceDelta(content=event.data.delta)
|
||||
choice = Choice(delta=delta, index=event.data.output_index)
|
||||
|
||||
converted_message = ChatCompletionChunk(
|
||||
id=event.data.item_id,
|
||||
choices=[choice],
|
||||
)
|
||||
resp = await self.backend.get_resp(
|
||||
msgs,
|
||||
{
|
||||
"conversation_id": "fake_conversation_id",
|
||||
"user_id": "fake_user_id",
|
||||
},
|
||||
)
|
||||
return converted_message
|
||||
else:
|
||||
break
|
||||
|
||||
context.add_messages(resp.msgs)
|
||||
await self.push_frame(LLMTextFrame(resp.content))
|
||||
|
||||
except httpx.TimeoutException:
|
||||
await self._call_event_handler("on_completion_timeout")
|
||||
finally:
|
||||
await self.stop_processing_metrics()
|
||||
await self.push_frame(LLMFullResponseEndFrame())
|
||||
# chunks = await self._client.chat.completions.create(**params)
|
||||
# return chunks
|
||||
|
||||
|
||||
async def run_bot(webrtc_connection: SmallWebRTCConnection):
|
||||
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
|
||||
logger.info(f"Starting bot")
|
||||
|
||||
transport = SmallWebRTCTransport(
|
||||
@@ -155,9 +188,7 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection):
|
||||
params=TransportParams(
|
||||
audio_in_enabled=True,
|
||||
audio_out_enabled=True,
|
||||
vad_enabled=True,
|
||||
vad_analyzer=SileroVADAnalyzer(),
|
||||
vad_audio_passthrough=True,
|
||||
),
|
||||
)
|
||||
|
||||
@@ -168,7 +199,7 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection):
|
||||
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||||
)
|
||||
|
||||
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
|
||||
llm = CustomLLMService(model="gpt-4.1", api_key=os.getenv("OPENAI_API_KEY"))
|
||||
|
||||
messages = [
|
||||
{
|
||||
@@ -206,8 +237,8 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection):
|
||||
async def on_client_connected(transport, client):
|
||||
logger.info(f"Client connected")
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
# messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
# await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_client_disconnected")
|
||||
async def on_client_disconnected(transport, client):
|
||||
|
||||
Reference in New Issue
Block a user