mirror of
https://github.com/BerriAI/litellm.git
synced 2025-04-25 18:54:30 +00:00
08a3620414
* http passthrough file handling * fix make_multipart_http_request * test_pass_through_file_operations * unit tests for file handling
98 lines
3.2 KiB
Python
98 lines
3.2 KiB
Python
import pytest
|
|
import openai
|
|
import aiohttp
|
|
import asyncio
|
|
import tempfile
|
|
from typing_extensions import override
|
|
from openai import AssistantEventHandler
|
|
|
|
|
|
client = openai.OpenAI(base_url="http://0.0.0.0:4000/openai", api_key="sk-1234")
|
|
|
|
def test_pass_through_file_operations():
|
|
# Create a temporary file
|
|
with tempfile.NamedTemporaryFile(mode='w+', suffix='.txt', delete=False) as temp_file:
|
|
temp_file.write("This is a test file for the OpenAI Assistants API.")
|
|
temp_file.flush()
|
|
|
|
# create a file
|
|
file = client.files.create(
|
|
file=open(temp_file.name, "rb"),
|
|
purpose="assistants",
|
|
)
|
|
print("file created", file)
|
|
|
|
# delete the file
|
|
delete_file = client.files.delete(file.id)
|
|
print("file deleted", delete_file)
|
|
|
|
def test_openai_assistants_e2e_operations():
|
|
assistant = client.beta.assistants.create(
|
|
name="Math Tutor",
|
|
instructions="You are a personal math tutor. Write and run code to answer math questions.",
|
|
tools=[{"type": "code_interpreter"}],
|
|
model="gpt-4o",
|
|
)
|
|
print("assistant created", assistant)
|
|
|
|
get_assistant = client.beta.assistants.retrieve(assistant.id)
|
|
print(get_assistant)
|
|
|
|
delete_assistant = client.beta.assistants.delete(assistant.id)
|
|
print(delete_assistant)
|
|
|
|
|
|
class EventHandler(AssistantEventHandler):
|
|
@override
|
|
def on_text_created(self, text) -> None:
|
|
print(f"\nassistant > ", end="", flush=True)
|
|
|
|
@override
|
|
def on_text_delta(self, delta, snapshot):
|
|
print(delta.value, end="", flush=True)
|
|
|
|
def on_tool_call_created(self, tool_call):
|
|
print(f"\nassistant > {tool_call.type}\n", flush=True)
|
|
|
|
def on_tool_call_delta(self, delta, snapshot):
|
|
if delta.type == "code_interpreter":
|
|
if delta.code_interpreter.input:
|
|
print(delta.code_interpreter.input, end="", flush=True)
|
|
if delta.code_interpreter.outputs:
|
|
print(f"\n\noutput >", flush=True)
|
|
for output in delta.code_interpreter.outputs:
|
|
if output.type == "logs":
|
|
print(f"\n{output.logs}", flush=True)
|
|
|
|
|
|
def test_openai_assistants_e2e_operations_stream():
|
|
|
|
assistant = client.beta.assistants.create(
|
|
name="Math Tutor",
|
|
instructions="You are a personal math tutor. Write and run code to answer math questions.",
|
|
tools=[{"type": "code_interpreter"}],
|
|
model="gpt-4o",
|
|
)
|
|
print("assistant created", assistant)
|
|
|
|
thread = client.beta.threads.create()
|
|
print("thread created", thread)
|
|
|
|
message = client.beta.threads.messages.create(
|
|
thread_id=thread.id,
|
|
role="user",
|
|
content="I need to solve the equation `3x + 11 = 14`. Can you help me?",
|
|
)
|
|
print("message created", message)
|
|
|
|
# Then, we use the `stream` SDK helper
|
|
# with the `EventHandler` class to create the Run
|
|
# and stream the response.
|
|
|
|
with client.beta.threads.runs.stream(
|
|
thread_id=thread.id,
|
|
assistant_id=assistant.id,
|
|
instructions="Please address the user as Jane Doe. The user has a premium account.",
|
|
event_handler=EventHandler(),
|
|
) as stream:
|
|
stream.until_done()
|