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Merged
merged 10 commits into from
Dec 13, 2023
Merged

fix(generative-ai): Add tests for function_calling code snippet #11019

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Add tests for function_calling.py
koverholt Dec 13, 2023
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Add test file
koverholt Dec 13, 2023
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Update test
koverholt Dec 13, 2023
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Merge remote-tracking branch 'origin' into generative-ai-function-cal…
koverholt Dec 13, 2023
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Move main construct out of region tag
koverholt Dec 13, 2023
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🦉 Updates from OwlBot post-processor
gcf-owl-bot[bot] Dec 13, 2023
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Merge remote-tracking branch 'refs/remotes/origin/generative-ai-funct…
koverholt Dec 13, 2023
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🦉 Updates from OwlBot post-processor
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Update google-cloud-aiplatform to 1.38.0
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Update sample region tag
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65 changes: 34 additions & 31 deletions generative_ai/function_calling.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,45 +12,48 @@
# See the License for the specific language governing permissions and
# limitations under the License.

# [START aiplatform_function_calling]
# [START aiplatform_gemini_function_calling]
from vertexai.preview.generative_models import (
FunctionDeclaration,
GenerativeModel,
Tool,
)

# Load the Vertex AI Gemini API to use function calling
model = GenerativeModel("gemini-pro")

# Specify a function declaration and parameters for an API request
get_current_weather_func = FunctionDeclaration(
name="get_current_weather",
description="Get the current weather in a given location",
# Function parameters are specified in OpenAPI JSON schema format
parameters={
"type": "object",
"properties": {"location": {"type": "string", "description": "Location"}},
},
)

# Define a tool that includes the above get_current_weather_func
weather_tool = Tool(
function_declarations=[get_current_weather_func],
)
def generate_function_call(prompt: str) -> str:
# Load the Vertex AI Gemini API to use function calling
model = GenerativeModel("gemini-pro")

# Prompt to ask the model about weather, which will invoke the Tool
prompt = "What is the weather like in Boston?"
# Specify a function declaration and parameters for an API request
get_current_weather_func = FunctionDeclaration(
name="get_current_weather",
description="Get the current weather in a given location",
# Function parameters are specified in OpenAPI JSON schema format
parameters={
"type": "object",
"properties": {"location": {"type": "string", "description": "Location"}},
},
)

# Define a tool that includes the above get_current_weather_func
weather_tool = Tool(
function_declarations=[get_current_weather_func],
)

# Prompt to ask the model about weather, which will invoke the Tool
prompt = prompt

# Instruct the model to generate content using the Tool that you just created:
response = model.generate_content(
prompt,
generation_config={"temperature": 0},
tools=[weather_tool],
)

return str(response)

# Instruct the model to generate content using the Tool that you just created:
response = model.generate_content(
prompt,
generation_config={"temperature": 0},
tools=[weather_tool],
)

# Print the entire response
print(response)
# [END aiplatform_gemini_function_calling]

# Print the part of the response that contains info about the function call
print(response.candidates[0].content.parts[0].function_call)
# [END aiplatform_function_calling]
if __name__ == "__main__":
generate_function_call("What is the weather like in Boston?")
42 changes: 42 additions & 0 deletions generative_ai/function_calling_test.py
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@@ -0,0 +1,42 @@
# Copyright 2023 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import os

import backoff
from google.api_core.exceptions import ResourceExhausted

import function_calling


_PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")
_LOCATION = "us-central1"


function_expected_responses = [
"function_call",
"get_current_weather",
"args",
"fields",
"location",
"Boston",
]


@backoff.on_exception(backoff.expo, ResourceExhausted, max_time=10)
def test_interview() -> None:
content = function_calling.generate_function_call(
prompt="What is the weather like in Boston?"
)
assert all(x in content for x in function_expected_responses)
2 changes: 1 addition & 1 deletion generative_ai/requirements.txt
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@@ -1,4 +1,4 @@
pandas==1.3.5; python_version == '3.7'
pandas==2.0.1; python_version > '3.7'
google-cloud-aiplatform[pipelines]==1.31.0
google-cloud-aiplatform[pipelines]==1.38.0
google-auth==2.17.3