chore: import upstream snapshot with attribution

2026-07-13 12:38:34 +08:00
commit 0549b088a4
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+# composio-google
+
+Adapts Composio tools to the Vertex AI SDK (`vertexai.generative_models`) as `FunctionDeclaration` objects for Gemini function calling.
+
+## Installation
+
+```bash
+pip install composio composio-google google-cloud-aiplatform
+```
+
+Set `COMPOSIO_API_KEY` (create one at https://dashboard.composio.dev/settings) in your environment. Vertex AI authenticates with Google Cloud credentials; run `gcloud auth application-default login` or set `GOOGLE_APPLICATION_CREDENTIALS`.
+
+## Quickstart
+
+`GoogleProvider` is non-agentic: the model returns function calls, and `composio.provider.handle_response` executes every function call in the response and returns the results.
+
+```python
+import vertexai
+from vertexai.generative_models import GenerativeModel, Tool
+
+from composio import Composio
+from composio_google import GoogleProvider
+
+vertexai.init(project="your-gcp-project", location="us-central1")
+
+composio = Composio(provider=GoogleProvider())
+
+# Create a session for your user
+session = composio.create(user_id="user_123")
+tools = session.tools()
+
+model = GenerativeModel(
+    "gemini-2.0-flash",
+    tools=[Tool(function_declarations=tools)],
+)
+chat = model.start_chat()
+
+response = chat.send_message(
+    "Send an email to john@example.com with the subject 'Hello' and body 'Hello from Composio!'"
+)
+
+# Execute the function calls the model requested
+results = composio.provider.handle_response(user_id="user_123", response=response)
+print(results)
+```
+
+To execute a single call instead of the whole response, use `composio.provider.execute_tool_call(user_id="user_123", function_call=part.function_call)`.
+
+## composio-google vs composio-gemini
+
+This package targets the Vertex AI SDK (`vertexai.generative_models`, installed via `google-cloud-aiplatform`). [`composio-gemini`](../gemini) targets the newer `google-genai` SDK with Automatic Function Calling. For new projects, use `composio-gemini`.
+
+## Links
+
+- Google provider docs: https://docs.composio.dev/docs/providers/google
+- Composio docs: https://docs.composio.dev
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+from composio_google.provider import GoogleProvider
+
+__all__ = ("GoogleProvider",)
@@ -0,0 +1,109 @@
+"""
+Google AI Python Gemini tool spec.
+"""
+
+import typing as t
+
+from proto.marshal.collections.maps import MapComposite
+from vertexai.generative_models import (
+    Content,
+    FunctionDeclaration,
+    GenerationResponse,
+    Part,
+)
+
+from composio.core.provider import NonAgenticProvider
+from composio.types import Modifiers, Tool, ToolExecutionResponse
+from composio.utils.shared import normalize_tool_arguments
+
+
+def _convert_map_composite(obj):
+    if isinstance(obj, MapComposite):
+        return {k: _convert_map_composite(v) for k, v in obj.items()}
+    if isinstance(obj, (list, tuple)):
+        return [_convert_map_composite(item) for item in obj]
+    return obj
+
+
+class GoogleProvider(
+    NonAgenticProvider[FunctionDeclaration, list[FunctionDeclaration]],
+    name="google",
+):
+    """
+    Composio toolset for Google AI Python Gemini framework.
+    """
+
+    def wrap_tool(self, tool: Tool) -> FunctionDeclaration:
+        """Wraps composio tool as Google AI Python Gemini FunctionDeclaration object."""
+        # Clean up properties by removing 'examples' field
+        properties = t.cast(
+            dict[str, dict],
+            tool.input_parameters.get("properties", {}),
+        )
+        cleaned_properties = {
+            prop_name: {k: v for k, v in prop_schema.items() if k != "examples"}
+            for prop_name, prop_schema in properties.items()
+        }
+        return FunctionDeclaration(
+            name=tool.slug,
+            description=tool.description,
+            parameters={
+                "type": "object",
+                "properties": cleaned_properties,
+                "required": tool.input_parameters.get("required", []),
+            },
+        )
+
+    def wrap_tools(self, tools: t.Sequence[Tool]) -> list[FunctionDeclaration]:
+        return [self.wrap_tool(tool) for tool in tools]
+
+    def execute_tool_call(
+        self,
+        user_id: str,
+        function_call: t.Any,
+        modifiers: t.Optional[Modifiers] = None,
+    ) -> ToolExecutionResponse:
+        """
+        Execute a function call.
+
+        :param function_call: Function call metadata from Gemini model response.
+        :param user_id: User ID to use for executing the function call.
+        :return: Object containing output data from the function call.
+        """
+        # Gemini returns args as a MapComposite; normalize after converting to a
+        # plain dict so a stringified payload is handled uniformly too (issue #2406).
+        return self.execute_tool(
+            slug=function_call.name,
+            arguments=normalize_tool_arguments(
+                _convert_map_composite(function_call.args)
+            ),
+            modifiers=modifiers,
+            user_id=user_id,
+        )
+
+    def handle_response(
+        self,
+        user_id: str,
+        response: GenerationResponse,
+        modifiers: t.Optional[Modifiers] = None,
+    ) -> t.List[ToolExecutionResponse]:
+        """
+        Handle response from Google AI Python Gemini model.
+
+        :param response: Generation response from the Gemini model.
+        :param user_id: User ID to use for executing the function call.
+        :return: A list of output objects from the function calls.
+        """
+        outputs = []
+        for candidate in response.candidates:
+            if isinstance(candidate.content, Content) and candidate.content.parts:
+                for part in candidate.content.parts:
+                    if isinstance(part, Part) and part.function_call:
+                        outputs.append(
+                            self.execute_tool_call(
+                                user_id=user_id,
+                                function_call=part.function_call,
+                                modifiers=modifiers,
+                            )
+                        )
+        return outputs
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+"""
+Google AI Python Gemini demo.
+"""
+
+import dotenv
+from composio_google import GoogleProvider
+from vertexai.generative_models import GenerativeModel
+
+from composio import Composio
+
+# Load environment variables from .env
+dotenv.load_dotenv()
+
+# Initialize tools
+composio = Composio(provider=GoogleProvider())
+
+# Get GitHub tools that are pre-configured
+tool = composio.tools.get(user_id="default", toolkits=["GITHUB"])
+
+# Initialize the Gemini model
+model = GenerativeModel("gemini-1.5-pro", tools=[tool])
+
+# Start a chat session
+chat = model.start_chat()
+
+
+def main():
+    # Define task
+    task = "Star a repo composiohq/composio on GitHub"
+
+    # Send a message to the model
+    response = chat.send_message(task)
+
+    print("Model response:")
+    print(response)
+
+    result = composio.provider.handle_response(user_id="default", response=response)
+    print("Function call result:")
+    print(result)
+
+
+if __name__ == "__main__":
+    main()
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+[project]
+name = "composio-google"
+version = "0.17.1"
+description = "Use Composio to get an array of tools with your Google AI Python Gemini model."
+readme = "README.md"
+requires-python = ">=3.10,<4"
+authors = [
+    { name = "Composio", email = "tech@composio.dev" }
+]
+classifiers = [
+    "Programming Language :: Python :: 3",
+    "License :: OSI Approved :: Apache Software License",
+    "Operating System :: OS Independent",
+]
+dependencies = [
+    "google-cloud-aiplatform>=1.158.0",
+    "composio",
+]
+
+[project.urls]
+Homepage = "https://github.com/ComposioHQ/composio"
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+"""
+Setup configuration for Composio Google AI Python Gemini plugin
+"""
+
+from pathlib import Path
+
+from setuptools import setup
+
+setup(
+    name="composio_google",
+    version="0.17.1",
+    author="Composio",
+    author_email="tech@composio.dev",
+    description="Use Composio to get an array of tools with your Google AI Python Gemini model.",
+    long_description=(Path(__file__).parent / "README.md").read_text(encoding="utf-8"),
+    long_description_content_type="text/markdown",
+    url="https://github.com/ComposioHQ/composio",
+    classifiers=[
+        "Programming Language :: Python :: 3",
+        "License :: OSI Approved :: Apache Software License",
+        "Operating System :: OS Independent",
+    ],
+    python_requires=">=3.10,<4",
+    install_requires=[
+        "google-cloud-aiplatform>=1.158.0",
+        "composio",
+    ],
+    include_package_data=True,
+)