Python: [BREAKING] update to v1.0.0 (#5062)

* updates to final deprecated pieces and versions

* fix mypy

* fix readme links

python/samples/03-workflows/human-in-the-loop/agents_with_HITL.py

@@ -103,7 +103,8 @@ class Coordinator(Executor):
             # Human approved the draft as-is; forward it unchanged.
             await ctx.send_message(
                 AgentExecutorRequest(
-                    messages=original_request.conversation + [Message("user", text="The draft is approved as-is.")],
+                    messages=original_request.conversation
+                    + [Message("user", contents=["The draft is approved as-is."])],
                     should_respond=True,
                 ),
                 target_id=self.final_editor_name,
@@ -118,7 +119,7 @@ class Coordinator(Executor):
             "Rewrite the draft from the previous assistant message into a polished final version. "
             "Keep the response under 120 words and reflect any requested tone adjustments."
         )
-        conversation.append(Message("user", text=instruction))
+        conversation.append(Message("user", contents=[instruction]))
         await ctx.send_message(
             AgentExecutorRequest(messages=conversation, should_respond=True),
             target_id=self.writer_name,

python/samples/03-workflows/human-in-the-loop/concurrent_request_info.py

@@ -85,13 +85,15 @@ async def aggregate_with_synthesis(results: list[AgentExecutorResponse]) -> Any:
 
     system_msg = Message(
         "system",
-        text=(
-            "You are a synthesis expert. Consolidate the following analyst perspectives "
-            "into one cohesive, balanced summary (3-4 sentences). If human guidance is provided, "
-            "prioritize aspects as directed."
-        ),
+        contents=[
+            (
+                "You are a synthesis expert. Consolidate the following analyst perspectives "
+                "into one cohesive, balanced summary (3-4 sentences). If human guidance is provided, "
+                "prioritize aspects as directed."
+            )
+        ],
     )
-    user_msg = Message("user", text="\n\n".join(expert_sections) + guidance_text)
+    user_msg = Message("user", contents=["\n\n".join(expert_sections) + guidance_text])
 
     response = await _chat_client.get_response([system_msg, user_msg])
     return response.messages[-1].text if response.messages else ""

python/samples/03-workflows/human-in-the-loop/guessing_game_with_human_input.py

@@ -91,7 +91,7 @@ class TurnManager(Executor):
         - Input is a simple starter token (ignored here).
         - Output is an AgentExecutorRequest that triggers the agent to produce a guess.
         """
-        user = Message("user", text="Start by making your first guess.")
+        user = Message("user", contents=["Start by making your first guess."])
         await ctx.send_message(AgentExecutorRequest(messages=[user], should_respond=True))
 
     @handler
@@ -150,7 +150,7 @@ class TurnManager(Executor):
             f"Feedback: {reply}. Your last guess was {last_guess}. "
             f"Use this feedback to adjust and make your next guess (1-10)."
         )
-        user_msg = Message("user", text=feedback_text)
+        user_msg = Message("user", contents=[feedback_text])
         await ctx.send_message(AgentExecutorRequest(messages=[user_msg], should_respond=True))