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Python: Fix ag-ui state handling issues (#2289)
* Fix ag-ui state handling * Bump package version and update changelog * Update changelog
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@@ -7,6 +7,12 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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## [Unreleased]
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## [1.0.0b251117] - 2025-11-17
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### Fixed
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- **agent-framework-ag-ui**: Fix ag-ui state handling issues ([#2289](https://github.com/microsoft/agent-framework/pull/2289))
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## [1.0.0b251114] - 2025-11-14
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### Added
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@@ -86,6 +86,7 @@ class AgentFrameworkEventBridge:
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self.pending_tool_calls: list[dict[str, Any]] = [] # Track tool calls for assistant message
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self.tool_results: list[dict[str, Any]] = [] # Track tool results
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self.tool_calls_ended: set[str] = set() # Track which tool calls have had ToolCallEndEvent emitted
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self.accumulated_text_content: str = "" # Track accumulated text for final MessagesSnapshotEvent
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async def from_agent_run_update(self, update: AgentRunResponseUpdate) -> list[BaseEvent]:
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"""
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@@ -99,18 +100,29 @@ class AgentFrameworkEventBridge:
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"""
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events: list[BaseEvent] = []
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for content in update.contents:
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logger.info(f"Processing AgentRunUpdate with {len(update.contents)} content items")
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for idx, content in enumerate(update.contents):
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logger.info(f" Content {idx}: type={type(content).__name__}")
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if isinstance(content, TextContent):
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logger.info(
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f" TextContent found: text_length={len(content.text)}, text_preview='{content.text[:100]}'"
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)
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logger.info(
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f" Flags: skip_text_content={self.skip_text_content}, should_stop_after_confirm={self.should_stop_after_confirm}"
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)
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# Skip text content if using structured outputs (it's just the JSON)
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if self.skip_text_content:
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logger.info(" SKIPPING TextContent: skip_text_content is True")
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continue
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# Skip text content if we're about to emit confirm_changes
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# The summary should only appear after user confirms
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if self.should_stop_after_confirm:
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logger.debug("Skipping text content - waiting for confirm_changes response")
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logger.info(" SKIPPING TextContent: waiting for confirm_changes response")
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# Save the summary text to show after confirmation
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self.suppressed_summary += content.text
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logger.info(f" Suppressed summary now has {len(self.suppressed_summary)} chars")
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continue
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if not self.current_message_id:
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@@ -119,14 +131,16 @@ class AgentFrameworkEventBridge:
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message_id=self.current_message_id,
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role="assistant",
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)
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logger.debug(f"Emitting TextMessageStartEvent with message_id={self.current_message_id}")
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logger.info(f" EMITTING TextMessageStartEvent with message_id={self.current_message_id}")
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events.append(start_event)
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event = TextMessageContentEvent(
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message_id=self.current_message_id,
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delta=content.text,
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)
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logger.debug(f"Emitting TextMessageContentEvent with delta: {content.text}")
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# Accumulate text content for final MessagesSnapshotEvent
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self.accumulated_text_content += content.text
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logger.info(f" EMITTING TextMessageContentEvent with delta: '{content.text}'")
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events.append(event)
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elif isinstance(content, FunctionCallContent):
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@@ -427,7 +441,24 @@ class AgentFrameworkEventBridge:
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# Emit MessagesSnapshotEvent with the complete conversation including tool calls and results
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# This is required for CopilotKit's useCopilotAction to detect tool result
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if self.pending_tool_calls and self.tool_results:
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# HOWEVER: Skip this for predictive tools when require_confirmation=False, because
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# the agent will generate a follow-up text message and we'll emit a complete snapshot at the end.
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# Emitting here would create an incomplete snapshot that gets replaced, causing UI flicker.
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should_emit_snapshot = self.pending_tool_calls and self.tool_results
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# Check if this is a predictive tool that will have a follow-up message
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is_predictive_without_confirmation = False
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if should_emit_snapshot and self.current_tool_call_name and self.predict_state_config:
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for state_key, config in self.predict_state_config.items():
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if config["tool"] == self.current_tool_call_name and not self.require_confirmation:
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is_predictive_without_confirmation = True
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logger.info(
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f"Skipping intermediate MessagesSnapshotEvent for predictive tool '{self.current_tool_call_name}' "
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"- will emit complete snapshot after follow-up message"
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)
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break
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if should_emit_snapshot and not is_predictive_without_confirmation:
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# Import message adapter
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from ._message_adapters import agent_framework_messages_to_agui
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@@ -283,8 +283,62 @@ def extract_text_from_contents(contents: list[Any]) -> str:
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return "".join(text_parts)
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def agui_messages_to_snapshot_format(messages: list[dict[str, Any]]) -> list[dict[str, Any]]:
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"""Normalize AG-UI messages for MessagesSnapshotEvent.
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Converts AG-UI input format (with 'input_text' type) to snapshot format (with 'text' type).
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Args:
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messages: List of AG-UI messages in input format
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Returns:
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List of normalized messages suitable for MessagesSnapshotEvent
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"""
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from ._utils import generate_event_id
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result: list[dict[str, Any]] = []
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for msg in messages:
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normalized_msg = msg.copy()
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# Ensure ID exists
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if "id" not in normalized_msg:
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normalized_msg["id"] = generate_event_id()
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# Normalize content field
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content = normalized_msg.get("content")
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if isinstance(content, list):
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# Convert content array format to simple string
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text_parts = []
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for item in content:
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if isinstance(item, dict):
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# Convert 'input_text' to 'text' type
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if item.get("type") == "input_text":
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text_parts.append(item.get("text", ""))
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elif item.get("type") == "text":
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text_parts.append(item.get("text", ""))
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else:
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# Other types - just extract text field if present
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text_parts.append(item.get("text", ""))
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normalized_msg["content"] = "".join(text_parts)
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elif content is None:
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normalized_msg["content"] = ""
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# Normalize tool_call_id to toolCallId for tool messages
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if normalized_msg.get("role") == "tool":
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if "tool_call_id" in normalized_msg:
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normalized_msg["toolCallId"] = normalized_msg["tool_call_id"]
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del normalized_msg["tool_call_id"]
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elif "toolCallId" not in normalized_msg:
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normalized_msg["toolCallId"] = ""
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result.append(normalized_msg)
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return result
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__all__ = [
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"agui_messages_to_agent_framework",
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"agent_framework_messages_to_agui",
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"agui_messages_to_snapshot_format",
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"extract_text_from_contents",
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]
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@@ -11,6 +11,7 @@ from typing import TYPE_CHECKING, Any
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from ag_ui.core import (
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BaseEvent,
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MessagesSnapshotEvent,
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RunErrorEvent,
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TextMessageContentEvent,
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TextMessageEndEvent,
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@@ -588,32 +589,37 @@ class DefaultOrchestrator(Orchestrator):
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# We should NOT add to thread.on_new_messages() as that would cause duplication.
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# Instead, we pass messages directly to the agent via messages_to_run.
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# Inject current state as system message context if we have state
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# Inject current state as system message context if we have state and this is a new user turn
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messages_to_run: list[Any] = []
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# Check if the last message is from the user (new turn) vs assistant/tool (mid-execution)
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is_new_user_turn = False
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if provider_messages:
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last_msg = provider_messages[-1]
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is_new_user_turn = last_msg.role.value == "user"
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# Check if conversation has tool calls (indicates mid-execution)
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conversation_has_tool_calls = False
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logger.debug(f"Checking {len(provider_messages)} provider messages for tool calls")
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for i, msg in enumerate(provider_messages):
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logger.debug(
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f" Message {i}: role={msg.role.value}, contents={len(msg.contents) if hasattr(msg, 'contents') and msg.contents else 0}"
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)
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for msg in provider_messages:
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if msg.role.value == "assistant" and hasattr(msg, "contents") and msg.contents:
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if any(isinstance(content, FunctionCallContent) for content in msg.contents):
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conversation_has_tool_calls = True
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break
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if current_state and context.config.state_schema and not conversation_has_tool_calls:
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# Only inject state context on new user turns AND when conversation doesn't have tool calls
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# (tool calls indicate we're mid-execution, so state context was already injected)
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if current_state and context.config.state_schema and is_new_user_turn and not conversation_has_tool_calls:
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state_json = json.dumps(current_state, indent=2)
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state_context_msg = ChatMessage(
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role="system",
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contents=[
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TextContent(
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text=f"""Current state of the application:
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{state_json}
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{state_json}
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When modifying state, you MUST include ALL existing data plus your changes.
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For example, if adding a new ingredient, include all existing ingredients PLUS the new one.
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Never replace existing data - always append or merge."""
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When modifying state, you MUST include ALL existing data plus your changes.
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For example, if adding one new item to a list, include ALL existing items PLUS the one new item.
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Never replace existing data - always preserve and append or merge."""
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)
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],
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)
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@@ -714,12 +720,19 @@ Never replace existing data - always append or merge."""
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# Collect all updates to get the final structured output
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all_updates: list[Any] = []
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update_count = 0
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async for update in context.agent.run_stream(messages_to_run, thread=thread, tools=tools_param):
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update_count += 1
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logger.info(f"[STREAM] Received update #{update_count} from agent")
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all_updates.append(update)
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events = await event_bridge.from_agent_run_update(update)
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logger.info(f"[STREAM] Update #{update_count} produced {len(events)} events")
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for event in events:
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logger.info(f"[STREAM] Yielding event: {type(event).__name__}")
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yield event
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logger.info(f"[STREAM] Agent stream completed. Total updates: {update_count}")
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# After agent completes, check if we should stop (waiting for user to confirm changes)
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if event_bridge.should_stop_after_confirm:
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logger.info("Stopping run after confirm_changes - waiting for user response")
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@@ -793,9 +806,56 @@ Never replace existing data - always append or merge."""
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yield TextMessageEndEvent(message_id=message_id)
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logger.info(f"Emitted conversational message: {response_dict['message'][:100]}...")
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logger.info(f"[FINALIZE] Checking for unclosed message. current_message_id={event_bridge.current_message_id}")
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if event_bridge.current_message_id:
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logger.info(f"[FINALIZE] Emitting TextMessageEndEvent for message_id={event_bridge.current_message_id}")
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yield event_bridge.create_message_end_event(event_bridge.current_message_id)
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# Emit MessagesSnapshotEvent to persist the final assistant text message
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from ._message_adapters import agui_messages_to_snapshot_format
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# Build the final assistant message with accumulated text content
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assistant_text_message = {
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"id": event_bridge.current_message_id,
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"role": "assistant",
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"content": event_bridge.accumulated_text_content,
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}
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# Convert input messages to snapshot format (normalize content structure)
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# event_bridge.input_messages are already in AG-UI format, just need normalization
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converted_input_messages = agui_messages_to_snapshot_format(event_bridge.input_messages)
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# Build complete messages array
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# Include: input messages + any pending tool calls/results + final text message
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all_messages = converted_input_messages.copy()
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# Add assistant message with tool calls if any
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if event_bridge.pending_tool_calls:
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tool_call_message = {
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"id": generate_event_id(),
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"role": "assistant",
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"tool_calls": event_bridge.pending_tool_calls.copy(),
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}
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all_messages.append(tool_call_message)
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# Add tool results if any
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all_messages.extend(event_bridge.tool_results.copy())
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# Add final text message
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all_messages.append(assistant_text_message)
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messages_snapshot = MessagesSnapshotEvent(
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messages=all_messages, # type: ignore[arg-type]
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)
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logger.info(
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f"[FINALIZE] Emitting MessagesSnapshotEvent with {len(all_messages)} messages "
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f"(text content length: {len(event_bridge.accumulated_text_content)})"
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)
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yield messages_snapshot
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else:
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logger.info("[FINALIZE] No current_message_id - skipping TextMessageEndEvent")
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logger.info("[FINALIZE] Emitting RUN_FINISHED event")
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yield event_bridge.create_run_finished_event()
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logger.info(f"Completed agent run for thread_id={context.thread_id}, run_id={context.run_id}")
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@@ -130,4 +130,5 @@ def recipe_agent(chat_client: ChatClientProtocol) -> AgentFrameworkAgent:
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"recipe": {"tool": "update_recipe", "tool_argument": "recipe"},
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},
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confirmation_strategy=RecipeConfirmationStrategy(),
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require_confirmation=False,
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)
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@@ -1,6 +1,6 @@
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[project]
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name = "agent-framework-ag-ui"
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version = "1.0.0b251114"
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version = "1.0.0b251117"
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description = "AG-UI protocol integration for Agent Framework"
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readme = "README.md"
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license-files = ["LICENSE"]
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