Updates & fixes to Agents samples that set response_format (#42872)

dargilco · web-flow · commit 3dc804ebf77e · 2025-09-05T16:26:15.000-07:00
diff --git a/sdk/ai/azure-ai-agents/samples/agents_async/sample_agents_json_schema_response_format_using_pydantic_async.py b/sdk/ai/azure-ai-agents/samples/agents_async/sample_agents_json_schema_response_format_using_pydantic_async.py
@@ -5,22 +5,23 @@
 
 """
 DESCRIPTION:
-    This sample demonstrates how to use agents with JSON schema output format.
+    This sample demonstrates how to use agents with JSON schema output format, using
+    an asynchronous client. It uses the Pydantic package to define the output JSON
+    schema from Python classes.
 
 USAGE:
-    python sample_agents_json_schema_async.py
+    python sample_agents_json_schema_response_format_using_pydantic_async.py
 
     Before running the sample:
 
-    pip install azure-ai-projects azure-ai-agents azure-identity pydantic
+    pip install azure-ai-projects azure-ai-agents azure-identity aiohttp pydantic
 
     Set these environment variables with your own values:
     1) PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the Overview
                           page of your Azure AI Foundry portal.
     2) MODEL_DEPLOYMENT_NAME - The deployment name of the AI model, as found under the "Name" column in
        the "Models + endpoints" tab in your Azure AI Foundry project.
 """
-
 import asyncio
 import os
 
@@ -30,7 +31,6 @@
 from azure.identity.aio import DefaultAzureCredential
 from azure.ai.agents.models import (
     ListSortOrder,
-    MessageTextContent,
     MessageRole,
     ResponseFormatJsonSchema,
     ResponseFormatJsonSchemaType,
@@ -39,17 +39,26 @@
 
 
 # Create the pydantic model to represent the planet names and there masses.
-class Planets(str, Enum):
+class PlanetName(str, Enum):
+    Mercury = "Mercury"
+    Venus = "Venus"
     Earth = "Earth"
     Mars = "Mars"
-    Jupyter = "Jupyter"
+    Jupiter = "Jupiter"
+    Saturn = "Saturn"
+    Uranus = "Uranus"
+    Neptune = "Neptune"
 
 
 class Planet(BaseModel):
-    planet: Planets
+    name: PlanetName
     mass: float
 
 
+class Planets(BaseModel):
+    planets: list[Planet]
+
+
 async def main():
     project_client = AIProjectClient(
         endpoint=os.environ["PROJECT_ENDPOINT"],
@@ -62,12 +71,12 @@ async def main():
         agent = await agents_client.create_agent(
             model=os.environ["MODEL_DEPLOYMENT_NAME"],
             name="my-agent",
-            instructions="Extract the information about planets.",
+            instructions="You are helpful agent. Your response is JSON formatted.",
             response_format=ResponseFormatJsonSchemaType(
                 json_schema=ResponseFormatJsonSchema(
                     name="planet_mass",
-                    description="Extract planet mass.",
-                    schema=Planet.model_json_schema(),
+                    description="Masses of Solar System planets.",
+                    schema=Planets.model_json_schema(),
                 )
             ),
         )
@@ -79,7 +88,7 @@ async def main():
         message = await agents_client.messages.create(
             thread_id=thread.id,
             role="user",
-            content=("The mass of the Mars is 6.4171E23 kg; the mass of the Earth is 5.972168E24 kg;"),
+            content="Hello, give me a list of planets in our solar system, and their mass in kilograms.",
         )
         print(f"Created message, message ID: {message.id}")
 
@@ -91,17 +100,16 @@ async def main():
         await agents_client.delete_agent(agent.id)
         print("Deleted agent")
 
-        messages = agents_client.messages.list(
-            thread_id=thread.id,
-            order=ListSortOrder.ASCENDING,
-        )
-
+        messages = agents_client.messages.list(thread_id=thread.id, order=ListSortOrder.ASCENDING)
         async for msg in messages:
-            if msg.role == MessageRole.AGENT:
-                last_part = msg.content[-1]
-                if isinstance(last_part, MessageTextContent):
-                    planet = TypeAdapter(Planet).validate_json(last_part.text.value)
-                    print(f"The mass of {planet.planet} is {planet.mass} kg.")
+            if msg.text_messages:
+                last_text = msg.text_messages[-1]
+                print(f"{msg.role}: {last_text.text.value}")
+                # Deserialize the Agent's JSON response to the `Planets` class defined above
+                if msg.role == MessageRole.AGENT:
+                    planets = TypeAdapter(Planets).validate_json(last_text.text.value)
+                    for planet in planets.planets:
+                        print(f"The mass of {planet.name.value} is {planet.mass} kg.")
 
 
 if __name__ == "__main__":
diff --git a/sdk/ai/azure-ai-agents/samples/agents_response_formats/sample_agents_json_object_response_format.py b/sdk/ai/azure-ai-agents/samples/agents_response_formats/sample_agents_json_object_response_format.py
@@ -21,7 +21,7 @@
        the "Models + endpoints" tab in your Azure AI Foundry project.
 """
 
-import os, time
+import os
 from azure.ai.projects import AIProjectClient
 from azure.identity import DefaultAzureCredential
 from azure.ai.agents.models import ListSortOrder, AgentsResponseFormat, RunStatus
@@ -45,11 +45,12 @@
     thread = agents_client.threads.create()
     print(f"Created thread, thread ID: {thread.id}")
 
-    # List all threads for the agent
     threads = agents_client.threads.list()
 
     message = agents_client.messages.create(
-        thread_id=thread.id, role="user", content="Hello, give me a list of planets in our solar system."
+        thread_id=thread.id,
+        role="user",
+        content="Hello, give me a list of planets in our solar system, and their mass in kilograms.",
     )
     print(f"Created message, message ID: {message.id}")
 
diff --git a/sdk/ai/azure-ai-agents/samples/agents_response_formats/sample_agents_json_schema_response_format.py b/sdk/ai/azure-ai-agents/samples/agents_response_formats/sample_agents_json_schema_response_format.py
@@ -12,7 +12,7 @@
 
     Before running the sample:
 
-    pip install azure-ai-projects azure-ai-agents azure-identity pydantic
+    pip install azure-ai-projects azure-ai-agents azure-identity
 
     Set these environment variables with your own values:
     1) PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the Overview
@@ -22,31 +22,55 @@
 """
 
 import os
-
-from enum import Enum
-from pydantic import BaseModel, TypeAdapter
+import json
+from typing import Dict, Any
 from azure.ai.projects import AIProjectClient
 from azure.identity import DefaultAzureCredential
 from azure.ai.agents.models import (
     ListSortOrder,
-    MessageTextContent,
     MessageRole,
     ResponseFormatJsonSchema,
     ResponseFormatJsonSchemaType,
     RunStatus,
 )
 
-
-# Create the pydantic model to represent the planet names and there masses.
-class Planets(str, Enum):
-    Earth = "Earth"
-    Mars = "Mars"
-    Mercury = "Mercury"
-
-
-class Planet(BaseModel):
-    planet: Planets
-    mass: float
+# Defines a JSON schema for listing Solar System planets and their masses. We would like the AI model to respond in this format.
+# See `sample_agents_json_schema_response_format_using_pydantic.py` for an alternative way to define the schema using Pydantic.
+json_schema: Dict[str, Any] = {
+    "$defs": {
+        "PlanetName": {
+            "type": "string",
+            "description": "The name of the planet",
+            "enum": ["Mercury", "Venus", "Earth", "Mars", "Jupiter", "Saturn", "Uranus", "Neptune"],
+        }
+    },
+    "type": "object",
+    "description": "Information about the planets in the Solar System",
+    "properties": {
+        "planets": {
+            "type": "array",
+            "items": {
+                "type": "object",
+                "description": "Information about a planet in the Solar System",
+                "properties": {
+                    "name": {"$ref": "#/$defs/PlanetName"},
+                    "mass": {
+                        "type": "number",
+                        "description": "Mass of the planet in kilograms",
+                    },
+                    "relative_mass": {
+                        "type": "number",
+                        "description": "Relative mass of the planet compared to Earth (for example, a value of 2.0 means the planet is twice as massive as Earth)",
+                    },
+                },
+                "required": ["name", "mass"],
+                "additionalProperties": False,
+            },
+        },
+    },
+    "required": ["planets"],
+    "additionalProperties": False,
+}
 
 
 project_client = AIProjectClient(
@@ -60,12 +84,12 @@ class Planet(BaseModel):
     agent = agents_client.create_agent(
         model=os.environ["MODEL_DEPLOYMENT_NAME"],
         name="my-agent",
-        instructions="Extract the information about planets.",
+        instructions="You are helpful agent. Your response is JSON formatted.",
         response_format=ResponseFormatJsonSchemaType(
             json_schema=ResponseFormatJsonSchema(
                 name="planet_mass",
-                description="Extract planet mass.",
-                schema=Planet.model_json_schema(),
+                description="Masses of Solar System planets",
+                schema=json_schema,
             )
         ),
     )
@@ -77,7 +101,7 @@ class Planet(BaseModel):
     message = agents_client.messages.create(
         thread_id=thread.id,
         role="user",
-        content=("The mass of the Mars is 6.4171E23 kg; the mass of the Earth is 5.972168E24 kg;"),
+        content="Hello, give me a list of planets in our solar system, and their mass in kilograms.",
     )
     print(f"Created message, message ID: {message.id}")
 
@@ -89,14 +113,13 @@ class Planet(BaseModel):
     agents_client.delete_agent(agent.id)
     print("Deleted agent")
 
-    messages = agents_client.messages.list(
-        thread_id=thread.id,
-        order=ListSortOrder.ASCENDING,
-    )
-
+    messages = agents_client.messages.list(thread_id=thread.id, order=ListSortOrder.ASCENDING)
     for msg in messages:
-        if msg.role == MessageRole.AGENT:
-            last_part = msg.content[-1]
-            if isinstance(last_part, MessageTextContent):
-                planet = TypeAdapter(Planet).validate_json(last_part.text.value)
-                print(f"The mass of {planet.planet} is {planet.mass} kg.")
+        if msg.text_messages:
+            last_text = msg.text_messages[-1]
+            print(f"{msg.role}: {last_text.text.value}")
+            # Convert the Agent's JSON response message to a Dict object, extract and print planet masses
+            if msg.role == MessageRole.AGENT:
+                response_dict = json.loads(last_text.text.value)
+                for planet in response_dict["planets"]:
+                    print(f"The mass of {planet['name']} is {planet['mass']} kg.")
diff --git a/sdk/ai/azure-ai-agents/samples/agents_response_formats/sample_agents_json_schema_response_format_using_pydantic.py b/sdk/ai/azure-ai-agents/samples/agents_response_formats/sample_agents_json_schema_response_format_using_pydantic.py
@@ -6,9 +6,10 @@
 """
 DESCRIPTION:
     This sample demonstrates how to use agents with JSON schema output format.
+    It uses the Pydantic package to define the output JSON schema from Python classes.
 
 USAGE:
-    python sample_agents_json_schema.py
+    python sample_agents_json_schema_response_format_using_pydantic.py
 
     Before running the sample:
 
@@ -28,45 +29,52 @@
 from azure.ai.projects import AIProjectClient
 from azure.identity import DefaultAzureCredential
 from azure.ai.agents.models import (
-    MessageTextContent,
+    ListSortOrder,
     MessageRole,
     ResponseFormatJsonSchema,
     ResponseFormatJsonSchemaType,
     RunStatus,
 )
 
-# [START create_agents_client]
-project_client = AIProjectClient(
-    endpoint=os.environ["PROJECT_ENDPOINT"],
-    credential=DefaultAzureCredential(),
-)
-# [END create_agents_client]
-
 
 # Create the pydantic model to represent the planet names and there masses.
-class Planets(str, Enum):
+class PlanetName(str, Enum):
+    Mercury = "Mercury"
+    Venus = "Venus"
     Earth = "Earth"
     Mars = "Mars"
-    Jupyter = "Jupyter"
+    Jupiter = "Jupiter"
+    Saturn = "Saturn"
+    Uranus = "Uranus"
+    Neptune = "Neptune"
 
 
 class Planet(BaseModel):
-    planet: Planets
+    name: PlanetName
     mass: float
 
 
+class Planets(BaseModel):
+    planets: list[Planet]
+
+
+project_client = AIProjectClient(
+    endpoint=os.environ["PROJECT_ENDPOINT"],
+    credential=DefaultAzureCredential(),
+)
+
 with project_client:
     agents_client = project_client.agents
 
     agent = agents_client.create_agent(
         model=os.environ["MODEL_DEPLOYMENT_NAME"],
         name="my-agent",
-        instructions="Extract the information about planets.",
+        instructions="You are helpful agent. Your response is JSON formatted.",
         response_format=ResponseFormatJsonSchemaType(
             json_schema=ResponseFormatJsonSchema(
                 name="planet_mass",
-                description="Extract planet mass.",
-                schema=Planet.model_json_schema(),
+                description="Masses of Solar System planets.",
+                schema=Planets.model_json_schema(),
             )
         ),
     )
@@ -78,7 +86,7 @@ class Planet(BaseModel):
     message = agents_client.messages.create(
         thread_id=thread.id,
         role="user",
-        content=("The mass of the Mars is 6.4171E23 kg; the mass of the Earth is 5.972168E24 kg;"),
+        content="Hello, give me a list of planets in our solar system, and their mass in kilograms.",
     )
     print(f"Created message, message ID: {message.id}")
 
@@ -90,13 +98,13 @@ class Planet(BaseModel):
     agents_client.delete_agent(agent.id)
     print("Deleted agent")
 
-    messages = agents_client.messages.list(thread_id=thread.id)
-
-    # The messages are following in the reverse order,
-    # we will iterate them and output only text contents.
+    messages = agents_client.messages.list(thread_id=thread.id, order=ListSortOrder.ASCENDING)
     for msg in messages:
-        if msg.role == MessageRole.AGENT:
-            last_part = msg.content[-1]
-            if isinstance(last_part, MessageTextContent):
-                planet = TypeAdapter(Planet).validate_json(last_part.text.value)
-                print(f"The mass of {planet.planet} is {planet.mass} kg.")
+        if msg.text_messages:
+            last_text = msg.text_messages[-1]
+            print(f"{msg.role}: {last_text.text.value}")
+            # Deserialize the Agent's JSON response to the `Planets` class defined above
+            if msg.role == MessageRole.AGENT:
+                planets = TypeAdapter(Planets).validate_json(last_text.text.value)
+                for planet in planets.planets:
+                    print(f"The mass of {planet.name.value} is {planet.mass} kg.")
diff --git a/sdk/ai/azure-ai-agents/samples/agents_response_formats/sample_agents_text_response_format.py b/sdk/ai/azure-ai-agents/samples/agents_response_formats/sample_agents_text_response_format.py
