Add agent tools tests

sdk/ai/azure-ai-projects/.env.template

@@ -44,6 +44,15 @@ AZURE_AI_PROJECTS_TESTS_CONTAINER_PROJECT_ENDPOINT=
 AZURE_AI_PROJECTS_TESTS_CONTAINER_APP_RESOURCE_ID=
 AZURE_AI_PROJECTS_TESTS_CONTAINER_INGRESS_SUBDOMAIN_SUFFIX=
 
+# Connection IDs and settings used in agent tool tests
+AZURE_AI_PROJECTS_TESTS_BING_PROJECT_CONNECTION_ID=
+AZURE_AI_PROJECTS_TESTS_AI_SEARCH_PROJECT_CONNECTION_ID=
+AZURE_AI_PROJECTS_TESTS_AI_SEARCH_INDEX_NAME=
+AZURE_AI_PROJECTS_TESTS_MCP_PROJECT_CONNECTION_ID=
+
+# Used in Image generation agent tools tests
+AZURE_AI_PROJECTS_TESTS_IMAGE_MODEL_DEPLOYMENT_NAME=
+
 # Used in tools
 BING_PROJECT_CONNECTION_ID=
 MCP_PROJECT_CONNECTION_ID=

sdk/ai/azure-ai-projects/samples/agents/tools/sample_agent_mcp_with_project_connection.py

@@ -22,7 +22,7 @@
     2) AZURE_AI_MODEL_DEPLOYMENT_NAME - The deployment name of the AI model, as found under the "Name" column in
        the "Models + endpoints" tab in your Microsoft Foundry project.
     3) MCP_PROJECT_CONNECTION_ID - The connection resource ID in Custom keys
-       with key equals to "Authorization" and value to be "Bear <your GitHub PAT token>".
+       with key equals to "Authorization" and value to be "Bearer <your GitHub PAT token>".
        Token can be created in https://github.com/settings/personal-access-tokens/new
 """
 

sdk/ai/azure-ai-projects/tests/agents/tools/__init__.py

@@ -0,0 +1,4 @@
+# ------------------------------------
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+# ------------------------------------

sdk/ai/azure-ai-projects/tests/agents/tools/multitool/test_agent_code_interpreter_and_function.py

@@ -0,0 +1,144 @@
+# pylint: disable=too-many-lines,line-too-long,useless-suppression
+# ------------------------------------
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+# ------------------------------------
+# cSpell:disable
+
+"""
+Multi-Tool Tests: Code Interpreter + Function Tool
+
+Tests various scenarios using an agent with Code Interpreter and Function Tool.
+All tests use the same tool combination but different inputs and workflows.
+"""
+
+import os
+import json
+import pytest
+from test_base import TestBase, servicePreparer
+from devtools_testutils import is_live_and_not_recording
+from azure.ai.projects.models import PromptAgentDefinition, CodeInterpreterTool, CodeInterpreterToolAuto, FunctionTool
+from openai.types.responses.response_input_param import FunctionCallOutput, ResponseInputParam
+
+
+class TestAgentCodeInterpreterAndFunction(TestBase):
+    """Tests for agents using Code Interpreter + Function Tool combination."""
+
+    @servicePreparer()
+    @pytest.mark.skipif(
+        condition=(not is_live_and_not_recording()),
+        reason="Skipped because we cannot record network calls with OpenAI client",
+    )
+    def test_calculate_and_save(self, **kwargs):
+        """
+        Test calculation with Code Interpreter and saving with Function Tool.
+        """
+
+        model = self.test_agents_params["model_deployment_name"]
+
+        # Setup
+        project_client = self.create_client(operation_group="agents", **kwargs)
+        openai_client = project_client.get_openai_client()
+
+        # Define function tool
+        func_tool = FunctionTool(
+            name="save_result",
+            description="Save analysis result",
+            parameters={
+                "type": "object",
+                "properties": {
+                    "result": {"type": "string", "description": "The result"},
+                },
+                "required": ["result"],
+                "additionalProperties": False,
+            },
+            strict=True,
+        )
+
+        # Create agent
+        agent = project_client.agents.create_version(
+            agent_name="code-func-agent",
+            definition=PromptAgentDefinition(
+                model=model,
+                instructions="Run calculations and save results.",
+                tools=[
+                    CodeInterpreterTool(container=CodeInterpreterToolAuto()),
+                    func_tool,
+                ],
+            ),
+            description="Agent with Code Interpreter and Function Tool.",
+        )
+        print(f"Agent created (id: {agent.id})")
+
+        # Use the agent
+        response = openai_client.responses.create(
+            input="Calculate 5 + 3 and save the result.",
+            extra_body={"agent": {"name": agent.name, "type": "agent_reference"}},
+        )
+        print(f"Response received (id: {response.id})")
+
+        assert response.id is not None
+        print("✓ Code Interpreter + Function Tool works!")
+
+        # Cleanup
+        project_client.agents.delete_version(agent_name=agent.name, agent_version=agent.version)
+
+    @servicePreparer()
+    @pytest.mark.skipif(
+        condition=(not is_live_and_not_recording()),
+        reason="Skipped because we cannot record network calls with OpenAI client",
+    )
+    def test_generate_data_and_report(self, **kwargs):
+        """
+        Test generating data with Code Interpreter and reporting with Function.
+        """
+
+        model = self.test_agents_params["model_deployment_name"]
+
+        # Setup
+        project_client = self.create_client(operation_group="agents", **kwargs)
+        openai_client = project_client.get_openai_client()
+
+        # Define function tool
+        report_function = FunctionTool(
+            name="generate_report",
+            description="Generate a report with the provided data",
+            parameters={
+                "type": "object",
+                "properties": {
+                    "title": {"type": "string", "description": "Report title"},
+                    "summary": {"type": "string", "description": "Report summary"},
+                },
+                "required": ["title", "summary"],
+                "additionalProperties": False,
+            },
+            strict=True,
+        )
+
+        # Create agent
+        agent = project_client.agents.create_version(
+            agent_name="code-func-report-agent",
+            definition=PromptAgentDefinition(
+                model=model,
+                instructions="Generate data using code and create reports with the generate_report function.",
+                tools=[
+                    CodeInterpreterTool(container=CodeInterpreterToolAuto()),
+                    report_function,
+                ],
+            ),
+            description="Agent for data generation and reporting.",
+        )
+        print(f"Agent created (id: {agent.id})")
+
+        # Request data generation and report
+        response = openai_client.responses.create(
+            input="Generate a list of 10 random numbers between 1 and 100, calculate their average, and create a report.",
+            extra_body={"agent": {"name": agent.name, "type": "agent_reference"}},
+        )
+
+        print(f"Response received (id: {response.id})")
+        assert response.id is not None
+        print("✓ Data generation and reporting works!")
+
+        # Cleanup
+        project_client.agents.delete_version(agent_name=agent.name, agent_version=agent.version)

sdk/ai/azure-ai-projects/tests/agents/tools/multitool/test_agent_file_search_and_code_interpreter.py

@@ -0,0 +1,156 @@
+# pylint: disable=too-many-lines,line-too-long,useless-suppression
+# ------------------------------------
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+# ------------------------------------
+# cSpell:disable
+
+"""
+Multi-Tool Tests: File Search + Code Interpreter
+
+Tests various scenarios using an agent with File Search and Code Interpreter.
+All tests use the same tool combination but different inputs and workflows.
+"""
+
+import os
+import pytest
+from io import BytesIO
+from test_base import TestBase, servicePreparer
+from devtools_testutils import is_live_and_not_recording
+from azure.ai.projects.models import PromptAgentDefinition, FileSearchTool, CodeInterpreterTool, CodeInterpreterToolAuto
+
+
+class TestAgentFileSearchAndCodeInterpreter(TestBase):
+    """Tests for agents using File Search + Code Interpreter combination."""
+
+    @servicePreparer()
+    @pytest.mark.skipif(
+        condition=(not is_live_and_not_recording()),
+        reason="Skipped because we cannot record network calls with OpenAI client",
+    )
+    def test_find_and_analyze_data(self, **kwargs):
+        """
+        Test finding data with File Search and analyzing with Code Interpreter.
+        """
+
+        model = self.test_agents_params["model_deployment_name"]
+
+        # Setup
+        project_client = self.create_client(operation_group="agents", **kwargs)
+        openai_client = project_client.get_openai_client()
+
+        # Create data file
+        txt_content = "Sample data: 10, 20, 30, 40, 50"
+        vector_store = openai_client.vector_stores.create(name="DataStore")
+
+        txt_file = BytesIO(txt_content.encode("utf-8"))
+        txt_file.name = "data.txt"
+
+        file = openai_client.vector_stores.files.upload_and_poll(
+            vector_store_id=vector_store.id,
+            file=txt_file,
+        )
+        print(f"File uploaded (id: {file.id})")
+
+        # Create agent
+        agent = project_client.agents.create_version(
+            agent_name="file-search-code-agent",
+            definition=PromptAgentDefinition(
+                model=model,
+                instructions="Find data and analyze it.",
+                tools=[
+                    FileSearchTool(vector_store_ids=[vector_store.id]),
+                    CodeInterpreterTool(container=CodeInterpreterToolAuto()),
+                ],
+            ),
+            description="Agent with File Search and Code Interpreter.",
+        )
+        print(f"Agent created (id: {agent.id})")
+
+        # Use the agent
+        response = openai_client.responses.create(
+            input="Find the data file and calculate the average.",
+            extra_body={"agent": {"name": agent.name, "type": "agent_reference"}},
+        )
+        print(f"Response received (id: {response.id})")
+
+        assert response.id is not None
+        assert len(response.output_text) > 20
+        print("✓ File Search + Code Interpreter works!")
+
+        # Cleanup
+        project_client.agents.delete_version(agent_name=agent.name, agent_version=agent.version)
+        openai_client.vector_stores.delete(vector_store.id)
+
+    @servicePreparer()
+    @pytest.mark.skipif(
+        condition=(not is_live_and_not_recording()),
+        reason="Skipped because we cannot record network calls with OpenAI client",
+    )
+    def test_analyze_code_file(self, **kwargs):
+        """
+        Test finding code file and analyzing it.
+        """
+
+        model = self.test_agents_params["model_deployment_name"]
+
+        # Setup
+        project_client = self.create_client(operation_group="agents", **kwargs)
+        openai_client = project_client.get_openai_client()
+
+        # Create Python code file
+        python_code = """def fibonacci(n):
+    if n <= 1:
+        return n
+    return fibonacci(n-1) + fibonacci(n-2)
+
+result = fibonacci(10)
+print(f"Fibonacci(10) = {result}")
+"""
+
+        vector_store = openai_client.vector_stores.create(name="CodeAnalysisStore")
+
+        code_file = BytesIO(python_code.encode("utf-8"))
+        code_file.name = "fibonacci.py"
+
+        file = openai_client.vector_stores.files.upload_and_poll(
+            vector_store_id=vector_store.id,
+            file=code_file,
+        )
+        print(f"Code file uploaded (id: {file.id})")
+
+        # Create agent
+        agent = project_client.agents.create_version(
+            agent_name="file-search-code-analysis-agent",
+            definition=PromptAgentDefinition(
+                model=model,
+                instructions="Find code files and analyze them. You can run code to test it.",
+                tools=[
+                    FileSearchTool(vector_store_ids=[vector_store.id]),
+                    CodeInterpreterTool(container=CodeInterpreterToolAuto()),
+                ],
+            ),
+            description="Agent for code analysis.",
+        )
+        print(f"Agent created (id: {agent.id})")
+
+        # Request analysis
+        response = openai_client.responses.create(
+            input="Find the fibonacci code and explain what it does. What is the computational complexity?",
+            extra_body={"agent": {"name": agent.name, "type": "agent_reference"}},
+        )
+
+        response_text = response.output_text
+        print(f"Response: {response_text[:300]}...")
+
+        assert len(response_text) > 50
+        response_lower = response_lower = response_text.lower()
+        assert any(
+            keyword in response_lower for keyword in ["fibonacci", "recursive", "complexity", "exponential"]
+        ), "Expected analysis of fibonacci algorithm"
+
+        print("✓ Code file analysis completed")
+
+        # Cleanup
+        project_client.agents.delete_version(agent_name=agent.name, agent_version=agent.version)
+        openai_client.vector_stores.delete(vector_store.id)