130 lines
4.7 KiB
Python
130 lines
4.7 KiB
Python
import asyncio
|
|
import json
|
|
import os
|
|
from typing import List
|
|
|
|
from pipecat.services.openai import OpenAILLMContextFrame, OpenAILLMContext
|
|
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
|
|
from pipecat.frames.frames import LLMFullResponseStartFrame, LLMFullResponseEndFrame, TextFrame
|
|
from pipecat.utils.test_frame_processor import TestFrameProcessor
|
|
from openai.types.chat import (
|
|
ChatCompletionSystemMessageParam,
|
|
ChatCompletionToolParam,
|
|
ChatCompletionUserMessageParam,
|
|
)
|
|
|
|
from pipecat.services.openai import OpenAILLMService
|
|
|
|
tools = [
|
|
ChatCompletionToolParam(
|
|
type="function",
|
|
function={
|
|
"name": "get_current_weather",
|
|
"description": "Get the current weather",
|
|
"parameters": {
|
|
"type": "object",
|
|
"properties": {
|
|
"location": {
|
|
"type": "string",
|
|
"description": "The city and state, e.g. San Francisco, CA",
|
|
},
|
|
"format": {
|
|
"type": "string",
|
|
"enum": ["celsius", "fahrenheit"],
|
|
"description": "The temperature unit to use. Infer this from the users location.",
|
|
},
|
|
},
|
|
"required": ["location", "format"],
|
|
},
|
|
},
|
|
)
|
|
]
|
|
|
|
if __name__ == "__main__":
|
|
|
|
async def test_simple_functions():
|
|
async def get_weather_from_api(llm, args):
|
|
return json.dumps({"conditions": "nice", "temperature": "75"})
|
|
|
|
api_key = os.getenv("OPENAI_API_KEY")
|
|
|
|
llm = OpenAILLMService(
|
|
api_key=api_key or "",
|
|
model="gpt-4-1106-preview",
|
|
)
|
|
|
|
llm.register_function("get_current_weather", get_weather_from_api)
|
|
t = TestFrameProcessor([LLMFullResponseStartFrame, TextFrame, LLMFullResponseEndFrame])
|
|
llm.link(t)
|
|
|
|
context = OpenAILLMContext(tools=tools)
|
|
system_message: ChatCompletionSystemMessageParam = ChatCompletionSystemMessageParam(
|
|
content="Ask the user to ask for a weather report", name="system", role="system"
|
|
)
|
|
user_message: ChatCompletionUserMessageParam = ChatCompletionUserMessageParam(
|
|
content="Could you tell me the weather for Boulder, Colorado",
|
|
name="user",
|
|
role="user",
|
|
)
|
|
context.add_message(system_message)
|
|
context.add_message(user_message)
|
|
frame = OpenAILLMContextFrame(context)
|
|
await llm.process_frame(frame, FrameDirection.DOWNSTREAM)
|
|
|
|
async def test_advanced_functions():
|
|
async def get_weather_from_api(llm, args):
|
|
return [
|
|
{
|
|
"role": "system",
|
|
"content": "The user has asked for live weather. Respond by telling them we don't currently support live weather for that area, but it's coming soon.",
|
|
}
|
|
]
|
|
|
|
api_key = os.getenv("OPENAI_API_KEY")
|
|
|
|
llm = OpenAILLMService(
|
|
api_key=api_key or "",
|
|
model="gpt-4-1106-preview",
|
|
)
|
|
|
|
llm.register_function("get_current_weather", get_weather_from_api)
|
|
t = TestFrameProcessor([LLMFullResponseStartFrame, TextFrame, LLMFullResponseEndFrame])
|
|
llm.link(t)
|
|
|
|
context = OpenAILLMContext(tools=tools)
|
|
system_message: ChatCompletionSystemMessageParam = ChatCompletionSystemMessageParam(
|
|
content="Ask the user to ask for a weather report", name="system", role="system"
|
|
)
|
|
user_message: ChatCompletionUserMessageParam = ChatCompletionUserMessageParam(
|
|
content="Could you tell me the weather for Boulder, Colorado",
|
|
name="user",
|
|
role="user",
|
|
)
|
|
context.add_message(system_message)
|
|
context.add_message(user_message)
|
|
frame = OpenAILLMContextFrame(context)
|
|
await llm.process_frame(frame, FrameDirection.DOWNSTREAM)
|
|
|
|
async def test_chat():
|
|
api_key = os.getenv("OPENAI_API_KEY")
|
|
t = TestFrameProcessor([LLMFullResponseStartFrame, TextFrame, LLMFullResponseEndFrame])
|
|
llm = OpenAILLMService(
|
|
api_key=api_key or "",
|
|
model="gpt-4o",
|
|
)
|
|
llm.link(t)
|
|
context = OpenAILLMContext()
|
|
message: ChatCompletionSystemMessageParam = ChatCompletionSystemMessageParam(
|
|
content="Please tell the world hello.", name="system", role="system"
|
|
)
|
|
context.add_message(message)
|
|
frame = OpenAILLMContextFrame(context)
|
|
await llm.process_frame(frame, FrameDirection.DOWNSTREAM)
|
|
|
|
async def run_tests():
|
|
await test_simple_functions()
|
|
await test_advanced_functions()
|
|
await test_chat()
|
|
|
|
asyncio.run(run_tests())
|