wx44wx/pipecat
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

tests: remove TestFrameProcessor, reimplement with run_test()

Browse Source
This commit is contained in:
Aleix Conchillo Flaqué
2025-03-18 15:52:37 -07:00
parent c15286b148
commit d1550d5a85
6 changed files with 37 additions and 269 deletions
Download Patch File Download Diff File Expand all files Collapse all files

33
tests/integration/integration_azure_llm.py
View File

@@ -1,33 +0,0 @@
import asyncio
import os
import unittest
from openai.types.chat import (
ChatCompletionSystemMessageParam,
)
from pipecat.processors.aggregators.openai_llm_context import (
OpenAILLMContext,
OpenAILLMContextFrame,
)
from pipecat.services.azure import AzureLLMService
if __name__ == "__main__":
@unittest.skip("Skip azure integration test")
async def test_chat():
llm = AzureLLMService(
api_key=os.getenv("AZURE_CHATGPT_API_KEY"),
endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"),
model=os.getenv("AZURE_CHATGPT_MODEL"),
)
context = OpenAILLMContext()
message: ChatCompletionSystemMessageParam = ChatCompletionSystemMessageParam(
content="Please tell the world hello.", name="system", role="system"
)
context.add_message(message)
frame = OpenAILLMContextFrame(context)
async for s in llm.process_frame(frame):
print(s)
asyncio.run(test_chat())

28
tests/integration/integration_ollama_llm.py
View File

@@ -1,28 +0,0 @@
import asyncio
import unittest
from openai.types.chat import (
ChatCompletionSystemMessageParam,
)
from pipecat.processors.aggregators.openai_llm_context import (
OpenAILLMContext,
OpenAILLMContextFrame,
)
from pipecat.services.ollama import OLLamaLLMService
if __name__ == "__main__":
@unittest.skip("Skip azure integration test")
async def test_chat():
llm = OLLamaLLMService()
context = OpenAILLMContext()
message: ChatCompletionSystemMessageParam = ChatCompletionSystemMessageParam(
content="Please tell the world hello.", name="system", role="system"
)
context.add_message(message)
frame = OpenAILLMContextFrame(context)
async for s in llm.process_frame(frame):
print(s)
asyncio.run(test_chat())

128
tests/integration/integration_openai_llm.py
View File

@@ -1,128 +0,0 @@
import asyncio
import json
import os
from typing import List
from openai.types.chat import (
ChatCompletionSystemMessageParam,
ChatCompletionToolParam,
ChatCompletionUserMessageParam,
)
from pipecat.frames.frames import LLMFullResponseEndFrame, LLMFullResponseStartFrame, TextFrame
from pipecat.processors.frame_processor import FrameDirection
from pipecat.services.openai import OpenAILLMContext, OpenAILLMContextFrame, OpenAILLMService
from pipecat.utils.test_frame_processor import TestFrameProcessor
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())

27
tests/integration/test_integration_unified_function_calling.py
View File

@@ -1,3 +1,9 @@
#
# Copyright (c) 2024-2025 Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
import os
from unittest.mock import AsyncMock
@@ -6,17 +12,12 @@ from dotenv import load_dotenv
from pipecat.adapters.schemas.function_schema import FunctionSchema
from pipecat.adapters.schemas.tools_schema import ToolsSchema
from pipecat.frames.frames import (
LLMFullResponseEndFrame,
LLMFullResponseStartFrame,
LLMTextFrame,
)
from pipecat.processors.frame_processor import FrameDirection
from pipecat.pipeline.pipeline import Pipeline
from pipecat.services.ai_services import LLMService
from pipecat.services.anthropic import AnthropicLLMService
from pipecat.services.google import GoogleLLMService
from pipecat.services.openai import OpenAILLMContext, OpenAILLMContextFrame, OpenAILLMService
from pipecat.utils.test_frame_processor import TestFrameProcessor
from pipecat.tests.utils import run_test
load_dotenv(override=True)
@@ -47,8 +48,6 @@ async def _test_llm_function_calling(llm: LLMService):
mock_fetch_weather = AsyncMock()
llm.register_function(None, mock_fetch_weather)
t = TestFrameProcessor([LLMFullResponseStartFrame, LLMTextFrame, LLMFullResponseEndFrame])
llm.link(t)
messages = [
{
@@ -61,10 +60,14 @@ async def _test_llm_function_calling(llm: LLMService):
# This is done by default inside the create_context_aggregator
context.set_llm_adapter(llm.get_llm_adapter())
frame = OpenAILLMContextFrame(context)
pipeline = Pipeline([llm])
# This will fail if an exception is raised
await llm.process_frame(frame, FrameDirection.DOWNSTREAM)
frames_to_send = [OpenAILLMContextFrame(context)]
await run_test(
pipeline,
frames_to_send=frames_to_send,
expected_down_frames=None,
)
# Assert that the mock function was called
mock_fetch_weather.assert_called_once()