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(test) parallel tool calling

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ishaan-jaff 2023-11-17 17:03:24 -08:00
parent fdbaceab8e
commit d2bac07b48
1 changed files with 73 additions and 63 deletions
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22
litellm/tests/test_function_calling.py
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@ -12,14 +12,12 @@ import pytest
import litellm import litellm
from litellm import embedding, completion, completion_cost, Timeout from litellm import embedding, completion, completion_cost, Timeout
from litellm import RateLimitError from litellm import RateLimitError
import pytest
litellm.num_retries = 3 litellm.num_retries = 3
litellm.cache = None litellm.cache = None
litellm.set_verbose=True litellm.set_verbose=False
import json import json
# Example dummy function hard coded to return the same weather
# In production, this could be your backend API or an external API
def get_current_weather(location, unit="fahrenheit"): def get_current_weather(location, unit="fahrenheit"):
"""Get the current weather in a given location""" """Get the current weather in a given location"""
if "tokyo" in location.lower(): if "tokyo" in location.lower():
@ -31,7 +29,10 @@ def get_current_weather(location, unit="fahrenheit"):
else: else:
return json.dumps({"location": location, "temperature": "unknown"}) return json.dumps({"location": location, "temperature": "unknown"})
def run_conversation(): # Example dummy function hard coded to return the same weather
# In production, this could be your backend API or an external API
def test_parallel_function_call():
try:
# Step 1: send the conversation and available functions to the model # Step 1: send the conversation and available functions to the model
messages = [{"role": "user", "content": "What's the weather like in San Francisco, Tokyo, and Paris?"}] messages = [{"role": "user", "content": "What's the weather like in San Francisco, Tokyo, and Paris?"}]
tools = [ tools = [
@ -63,6 +64,11 @@ def run_conversation():
print("Response\n", response) print("Response\n", response)
response_message = response.choices[0].message response_message = response.choices[0].message
tool_calls = response_message.tool_calls tool_calls = response_message.tool_calls
print("length of tool calls", len(tool_calls))
print("Expecting there to be 3 tool calls")
assert len(tool_calls) > 1 # this has to call the function for SF, Tokyo and parise
# Step 2: check if the model wanted to call a function # Step 2: check if the model wanted to call a function
if tool_calls: if tool_calls:
# Step 3: call the function # Step 3: call the function
@ -93,5 +99,9 @@ def run_conversation():
model="gpt-3.5-turbo-1106", model="gpt-3.5-turbo-1106",
messages=messages, messages=messages,
) # get a new response from the model where it can see the function response ) # get a new response from the model where it can see the function response
print("second response\n", second_response)
return second_response return second_response
print(run_conversation()) except Exception as e:
pytest.fail(f"Error occurred: {e}")
test_parallel_function_call()