Python: [Breaking] Simplified Content types to a single class with classmethod constructors. (#3252)

* ported Content to a new model

* fixed linting

* fixes

* fixed data format handling

* fix for 3.10 mypy

* fix

* fix int test

python/samples/getting_started/agents/anthropic/anthropic_advanced.py

@@ -43,7 +43,7 @@ async def main() -> None:
             if isinstance(content, TextReasoningContent):
                 print(f"\033[32m{content.text}\033[0m", end="", flush=True)
             if isinstance(content, UsageContent):
-                print(f"\n\033[34m[Usage so far: {content.details}]\033[0m\n", end="", flush=True)
+                print(f"\n\033[34m[Usage so far: {content.usage_details}]\033[0m\n", end="", flush=True)
         if chunk.text:
             print(chunk.text, end="", flush=True)
 

python/samples/getting_started/agents/anthropic/anthropic_foundry.py

@@ -54,7 +54,7 @@ async def main() -> None:
             if isinstance(content, TextReasoningContent):
                 print(f"\033[32m{content.text}\033[0m", end="", flush=True)
             if isinstance(content, UsageContent):
-                print(f"\n\033[34m[Usage so far: {content.details}]\033[0m\n", end="", flush=True)
+                print(f"\n\033[34m[Usage so far: {content.usage_details}]\033[0m\n", end="", flush=True)
         if chunk.text:
             print(chunk.text, end="", flush=True)
 

python/samples/getting_started/agents/anthropic/anthropic_skills.py

@@ -61,7 +61,7 @@ async def main() -> None:
                 case "text_reasoning":
                     print(f"\033[32m{content.text}\033[0m", end="", flush=True)
                 case "usage":
-                    print(f"\n\033[34m[Usage so far: {content.details}]\033[0m\n", end="", flush=True)
+                    print(f"\n\033[34m[Usage so far: {content.usage_details}]\033[0m\n", end="", flush=True)
                 case "hosted_file":
                     # Catch generated files
                     files.append(content)

python/samples/getting_started/agents/azure_ai/azure_ai_with_code_interpreter_file_generation.py

@@ -4,10 +4,7 @@ import asyncio
 
 from agent_framework import (
     AgentResponseUpdate,
-    CitationAnnotation,
     HostedCodeInterpreterTool,
-    HostedFileContent,
-    TextContent,
 )
 from agent_framework.azure import AzureAIProjectAgentProvider
 from azure.identity.aio import AzureCliCredential
@@ -50,9 +47,9 @@ async def non_streaming_example() -> None:
         # AgentResponse has messages property, which contains ChatMessage objects
         for message in result.messages:
             for content in message.contents:
-                if isinstance(content, TextContent) and content.annotations:
+                if content.type == "text" and content.annotations:
                     for annotation in content.annotations:
-                        if isinstance(annotation, CitationAnnotation) and annotation.file_id:
+                        if annotation.file_id:
                             annotations_found.append(annotation.file_id)
                             print(f"Found file annotation: file_id={annotation.file_id}")
 
@@ -84,15 +81,15 @@ async def streaming_example() -> None:
         async for update in agent.run_stream(QUERY):
             if isinstance(update, AgentResponseUpdate):
                 for content in update.contents:
-                    if isinstance(content, TextContent):
+                    if content.type == "text":
                         if content.text:
                             text_chunks.append(content.text)
                         if content.annotations:
                             for annotation in content.annotations:
-                                if isinstance(annotation, CitationAnnotation) and annotation.file_id:
+                                if annotation.file_id:
                                     annotations_found.append(annotation.file_id)
                                     print(f"Found streaming annotation: file_id={annotation.file_id}")
-                    elif isinstance(content, HostedFileContent):
+                    elif content.type == "hosted_file":
                         file_ids_found.append(content.file_id)
                         print(f"Found streaming HostedFileContent: file_id={content.file_id}")
 

python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_azure_ai_search.py

@@ -3,7 +3,7 @@
 import asyncio
 import os
 
-from agent_framework import CitationAnnotation
+from agent_framework import Annotation
 from agent_framework.azure import AzureAIAgentsProvider
 from azure.ai.agents.aio import AgentsClient
 from azure.ai.projects.aio import AIProjectClient
@@ -85,13 +85,11 @@ async def main() -> None:
             )
             print(f"User: {user_input}")
             print("Agent: ", end="", flush=True)
-
             # Stream the response and collect citations
-            citations: list[CitationAnnotation] = []
+            citations: list[Annotation] = []
             async for chunk in agent.run_stream(user_input):
                 if chunk.text:
                     print(chunk.text, end="", flush=True)
-
                 # Collect citations from Azure AI Search responses
                 for content in getattr(chunk, "contents", []):
                     annotations = getattr(content, "annotations", [])
@@ -104,7 +102,7 @@ async def main() -> None:
             if citations:
                 print("\n\nCitation:")
                 for i, citation in enumerate(citations, 1):
-                    print(f"[{i}] {citation.url}")
+                    print(f"[{i}] {citation.get('url')}")
 
             print("\n" + "=" * 50 + "\n")
             print("Hotel search conversation completed!")

python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_bing_grounding_citations.py

@@ -2,7 +2,7 @@
 
 import asyncio
 
-from agent_framework import CitationAnnotation, HostedWebSearchTool
+from agent_framework import Annotation, HostedWebSearchTool
 from agent_framework.azure import AzureAIAgentsProvider
 from azure.identity.aio import AzureCliCredential
 
@@ -57,7 +57,7 @@ async def main() -> None:
         print("Agent: ", end="", flush=True)
 
         # Stream the response and collect citations
-        citations: list[CitationAnnotation] = []
+        citations: list[Annotation] = []
         async for chunk in agent.run_stream(user_input):
             if chunk.text:
                 print(chunk.text, end="", flush=True)
@@ -74,9 +74,9 @@ async def main() -> None:
         if citations:
             print("\n\nCitations:")
             for i, citation in enumerate(citations, 1):
-                print(f"[{i}] {citation.title}: {citation.url}")
-                if citation.snippet:
-                    print(f"    Snippet: {citation.snippet}")
+                print(f"[{i}] {citation['title']}: {citation.get('url')}")
+                if "snippet" in citation:
+                    print(f"    Snippet: {citation.get('snippet')}")
         else:
             print("\nNo citations found in the response.")
 

python/samples/getting_started/agents/ollama/ollama_chat_multimodal.py

@@ -2,7 +2,7 @@
 
 import asyncio
 
-from agent_framework import ChatMessage, DataContent, Role, TextContent
+from agent_framework import ChatMessage, Content, Role
 from agent_framework.ollama import OllamaChatClient
 
 """
@@ -35,8 +35,8 @@ async def test_image() -> None:
     message = ChatMessage(
         role=Role.USER,
         contents=[
-            TextContent(text="What's in this image?"),
-            DataContent(uri=image_uri, media_type="image/png"),
+            Content.from_text(text="What's in this image?"),
+            Content.from_uri(uri=image_uri, media_type="image/png"),
         ],
     )
 

python/samples/getting_started/agents/openai/openai_responses_client_reasoning.py

@@ -66,7 +66,7 @@ async def streaming_reasoning_example() -> None:
                     usage = content
     print("\n")
     if usage:
-        print(f"Usage: {usage.details}")
+        print(f"Usage: {usage.usage_details}")
 
 
 async def main() -> None:

python/samples/getting_started/multimodal_input/README.md

@@ -82,7 +82,7 @@ with open("path/to/your/image.jpg", "rb") as f:
     image_uri = f"data:image/jpeg;base64,{image_base64}"
 
 # Use in DataContent
-DataContent(
+Content.from_uri(
     uri=image_uri,
     media_type="image/jpeg"
 )
@@ -96,7 +96,7 @@ with open("path/to/your/image.jpg", "rb") as f:
     image_bytes = f.read()
 
 # Use in DataContent
-DataContent(
+Content.from_data(
     data=image_bytes,
     media_type="image/jpeg"
 )

python/samples/getting_started/multimodal_input/azure_chat_multimodal.py

@@ -2,7 +2,7 @@
 
 import asyncio
 
-from agent_framework import ChatMessage, DataContent, Role, TextContent
+from agent_framework import ChatMessage, Content, Role
 from agent_framework.azure import AzureOpenAIChatClient
 from azure.identity import AzureCliCredential
 
@@ -26,7 +26,10 @@ async def test_image() -> None:
     image_uri = create_sample_image()
     message = ChatMessage(
         role=Role.USER,
-        contents=[TextContent(text="What's in this image?"), DataContent(uri=image_uri, media_type="image/png")],
+        contents=[
+            Content.from_text(text="What's in this image?"),
+            Content.from_uri(uri=image_uri, media_type="image/png"),
+        ],
     )
 
     response = await client.get_response(message)

python/samples/getting_started/multimodal_input/azure_responses_multimodal.py

@@ -3,7 +3,7 @@
 import asyncio
 from pathlib import Path
 
-from agent_framework import ChatMessage, DataContent, Role, TextContent
+from agent_framework import ChatMessage, Content, Role
 from agent_framework.azure import AzureOpenAIResponsesClient
 from azure.identity import AzureCliCredential
 
@@ -35,7 +35,10 @@ async def test_image() -> None:
     image_uri = create_sample_image()
     message = ChatMessage(
         role=Role.USER,
-        contents=[TextContent(text="What's in this image?"), DataContent(uri=image_uri, media_type="image/png")],
+        contents=[
+            Content.from_text(text="What's in this image?"),
+            Content.from_uri(uri=image_uri, media_type="image/png"),
+        ],
     )
 
     response = await client.get_response(message)
@@ -50,8 +53,8 @@ async def test_pdf() -> None:
     message = ChatMessage(
         role=Role.USER,
         contents=[
-            TextContent(text="What information can you extract from this document?"),
-            DataContent(
+            Content.from_text(text="What information can you extract from this document?"),
+            Content.from_data(
                 data=pdf_bytes,
                 media_type="application/pdf",
                 additional_properties={"filename": "sample.pdf"},

python/samples/getting_started/multimodal_input/openai_chat_multimodal.py

@@ -5,7 +5,7 @@ import base64
 import struct
 from pathlib import Path
 
-from agent_framework import ChatMessage, DataContent, Role, TextContent
+from agent_framework import ChatMessage, Content, Role
 from agent_framework.openai import OpenAIChatClient
 
 ASSETS_DIR = Path(__file__).resolve().parent.parent / "sample_assets"
@@ -47,7 +47,10 @@ async def test_image() -> None:
     image_uri = create_sample_image()
     message = ChatMessage(
         role=Role.USER,
-        contents=[TextContent(text="What's in this image?"), DataContent(uri=image_uri, media_type="image/png")],
+        contents=[
+            Content.from_text(text="What's in this image?"),
+            Content.from_uri(uri=image_uri, media_type="image/png"),
+        ],
     )
 
     response = await client.get_response(message)
@@ -62,8 +65,8 @@ async def test_audio() -> None:
     message = ChatMessage(
         role=Role.USER,
         contents=[
-            TextContent(text="What do you hear in this audio?"),
-            DataContent(uri=audio_uri, media_type="audio/wav"),
+            Content.from_text(text="What do you hear in this audio?"),
+            Content.from_uri(uri=audio_uri, media_type="audio/wav"),
         ],
     )
 
@@ -79,8 +82,8 @@ async def test_pdf() -> None:
     message = ChatMessage(
         role=Role.USER,
         contents=[
-            TextContent(text="What information can you extract from this document?"),
-            DataContent(
+            Content.from_text(text="What information can you extract from this document?"),
+            Content.from_data(
                 data=pdf_bytes, media_type="application/pdf", additional_properties={"filename": "employee_report.pdf"}
             ),
         ],

python/samples/getting_started/workflows/agents/workflow_as_agent_reflection_pattern.py

@@ -9,7 +9,7 @@ from agent_framework import (
     AgentRunUpdateEvent,
     ChatClientProtocol,
     ChatMessage,
-    Contents,
+    Content,
     Executor,
     Role,
     WorkflowBuilder,
@@ -155,7 +155,7 @@ class Worker(Executor):
 
         if review.approved:
             print("Worker: Response approved. Emitting to external consumer...")
-            contents: list[Contents] = []
+            contents: list[Content] = []
             for message in request.agent_messages:
                 contents.extend(message.contents)