fix(frontend): auto-poll for long-running tool completion (#11866)

## Summary
Fixes the issue where the "Creating Agent" spinner doesn't auto-update
when agent generation completes - user had to refresh the browser.

**Changes:**
- **Frontend polling**: Add `onOperationStarted` callback to trigger
polling when `operation_started` is received via SSE
- **Polling backoff**: 2s, 4s, 6s, 8s... up to 30s max
- **Message deduplication**: Use content-based keys (role + content)
instead of timestamps to prevent duplicate messages
- **Message ordering**: Preserve server message order instead of
timestamp-based sorting
- **Debug cleanup**: Remove verbose console.log/console.info statements

## Test plan
- [ ] Start agent generation in copilot
- [ ] Verify "Creating Agent" spinner appears
- [ ] Wait for completion (2-5 min) WITHOUT refreshing
- [ ] Verify agent carousel appears automatically when done
- [ ] Verify no duplicate messages in chat
- [ ] Verify message order is correct (user → assistant → tool_call →
tool_response)

autogpt_platform/backend/backend/api/features/chat/config.py

@@ -33,9 +33,15 @@ class ChatConfig(BaseSettings):
 
     stream_timeout: int = Field(default=300, description="Stream timeout in seconds")
     max_retries: int = Field(default=3, description="Maximum number of retries")
-    max_agent_runs: int = Field(default=3, description="Maximum number of agent runs")
+    max_agent_runs: int = Field(default=30, description="Maximum number of agent runs")
     max_agent_schedules: int = Field(
-        default=3, description="Maximum number of agent schedules"
+        default=30, description="Maximum number of agent schedules"
+    )
+
+    # Long-running operation configuration
+    long_running_operation_ttl: int = Field(
+        default=600,
+        description="TTL in seconds for long-running operation tracking in Redis (safety net if pod dies)",
     )
 
     # Langfuse Prompt Management Configuration

autogpt_platform/backend/backend/api/features/chat/db.py

@@ -247,3 +247,45 @@ async def get_chat_session_message_count(session_id: str) -> int:
     """Get the number of messages in a chat session."""
     count = await PrismaChatMessage.prisma().count(where={"sessionId": session_id})
     return count
+
+
+async def update_tool_message_content(
+    session_id: str,
+    tool_call_id: str,
+    new_content: str,
+) -> bool:
+    """Update the content of a tool message in chat history.
+
+    Used by background tasks to update pending operation messages with final results.
+
+    Args:
+        session_id: The chat session ID.
+        tool_call_id: The tool call ID to find the message.
+        new_content: The new content to set.
+
+    Returns:
+        True if a message was updated, False otherwise.
+    """
+    try:
+        result = await PrismaChatMessage.prisma().update_many(
+            where={
+                "sessionId": session_id,
+                "toolCallId": tool_call_id,
+            },
+            data={
+                "content": new_content,
+            },
+        )
+        if result == 0:
+            logger.warning(
+                f"No message found to update for session {session_id}, "
+                f"tool_call_id {tool_call_id}"
+            )
+            return False
+        return True
+    except Exception as e:
+        logger.error(
+            f"Failed to update tool message for session {session_id}, "
+            f"tool_call_id {tool_call_id}: {e}"
+        )
+        return False

autogpt_platform/backend/backend/api/features/chat/model.py

@@ -295,6 +295,21 @@ async def cache_chat_session(session: ChatSession) -> None:
     await _cache_session(session)
 
 
+async def invalidate_session_cache(session_id: str) -> None:
+    """Invalidate a chat session from Redis cache.
+
+    Used by background tasks to ensure fresh data is loaded on next access.
+    This is best-effort - Redis failures are logged but don't fail the operation.
+    """
+    try:
+        redis_key = _get_session_cache_key(session_id)
+        async_redis = await get_redis_async()
+        await async_redis.delete(redis_key)
+    except Exception as e:
+        # Best-effort: log but don't fail - cache will expire naturally
+        logger.warning(f"Failed to invalidate session cache for {session_id}: {e}")
+
+
 async def _get_session_from_db(session_id: str) -> ChatSession | None:
     """Get a chat session from the database."""
     prisma_session = await chat_db.get_chat_session(session_id)

autogpt_platform/backend/backend/api/features/chat/service.py

@@ -17,6 +17,7 @@ from openai import (
 )
 from openai.types.chat import ChatCompletionChunk, ChatCompletionToolParam
 
+from backend.data.redis_client import get_redis_async
 from backend.data.understanding import (
     format_understanding_for_prompt,
     get_business_understanding,
@@ -24,6 +25,7 @@ from backend.data.understanding import (
 from backend.util.exceptions import NotFoundError
 from backend.util.settings import Settings
 
+from . import db as chat_db
 from .config import ChatConfig
 from .model import (
     ChatMessage,
@@ -31,6 +33,7 @@ from .model import (
     Usage,
     cache_chat_session,
     get_chat_session,
+    invalidate_session_cache,
     update_session_title,
     upsert_chat_session,
 )
@@ -48,8 +51,13 @@ from .response_model import (
     StreamToolOutputAvailable,
     StreamUsage,
 )
-from .tools import execute_tool, tools
-from .tools.models import ErrorResponse
+from .tools import execute_tool, get_tool, tools
+from .tools.models import (
+    ErrorResponse,
+    OperationInProgressResponse,
+    OperationPendingResponse,
+    OperationStartedResponse,
+)
 from .tracking import track_user_message
 
 logger = logging.getLogger(__name__)
@@ -61,11 +69,126 @@ client = openai.AsyncOpenAI(api_key=config.api_key, base_url=config.base_url)
 
 langfuse = get_client()
 
+# Redis key prefix for tracking running long-running operations
+# Used for idempotency across Kubernetes pods - prevents duplicate executions on browser refresh
+RUNNING_OPERATION_PREFIX = "chat:running_operation:"
 
-class LangfuseNotConfiguredError(Exception):
-    """Raised when Langfuse is required but not configured."""
+# Default system prompt used when Langfuse is not configured
+# This is a snapshot of the "CoPilot Prompt" from Langfuse (version 11)
+DEFAULT_SYSTEM_PROMPT = """You are **Otto**, an AI Co-Pilot for AutoGPT and a Forward-Deployed Automation Engineer serving small business owners. Your mission is to help users automate business tasks with AI by delivering tangible value through working automations—not through documentation or lengthy explanations.
 
-    pass
+Here is everything you know about the current user from previous interactions:
+
+<users_information>
+{users_information}
+</users_information>
+
+## YOUR CORE MANDATE
+
+You are action-oriented. Your success is measured by:
+- **Value Delivery**: Does the user think "wow, that was amazing" or "what was the point"?
+- **Demonstrable Proof**: Show working automations, not descriptions of what's possible
+- **Time Saved**: Focus on tangible efficiency gains
+- **Quality Output**: Deliver results that meet or exceed expectations
+
+## YOUR WORKFLOW
+
+Adapt flexibly to the conversation context. Not every interaction requires all stages:
+
+1. **Explore & Understand**: Learn about the user's business, tasks, and goals. Use `add_understanding` to capture important context that will improve future conversations.
+
+2. **Assess Automation Potential**: Help the user understand whether and how AI can automate their task.
+
+3. **Prepare for AI**: Provide brief, actionable guidance on prerequisites (data, access, etc.).
+
+4. **Discover or Create Agents**:
+   - **Always check the user's library first** with `find_library_agent` (these may be customized to their needs)
+   - Search the marketplace with `find_agent` for pre-built automations
+   - Find reusable components with `find_block`
+   - Create custom solutions with `create_agent` if nothing suitable exists
+   - Modify existing library agents with `edit_agent`
+
+5. **Execute**: Run automations immediately, schedule them, or set up webhooks using `run_agent`. Test specific components with `run_block`.
+
+6. **Show Results**: Display outputs using `agent_output`.
+
+## AVAILABLE TOOLS
+
+**Understanding & Discovery:**
+- `add_understanding`: Create a memory about the user's business or use cases for future sessions
+- `search_docs`: Search platform documentation for specific technical information
+- `get_doc_page`: Retrieve full text of a specific documentation page
+
+**Agent Discovery:**
+- `find_library_agent`: Search the user's existing agents (CHECK HERE FIRST—these may be customized)
+- `find_agent`: Search the marketplace for pre-built automations
+- `find_block`: Find pre-written code units that perform specific tasks (agents are built from blocks)
+
+**Agent Creation & Editing:**
+- `create_agent`: Create a new automation agent
+- `edit_agent`: Modify an agent in the user's library
+
+**Execution & Output:**
+- `run_agent`: Run an agent now, schedule it, or set up a webhook trigger
+- `run_block`: Test or run a specific block independently
+- `agent_output`: View results from previous agent runs
+
+## BEHAVIORAL GUIDELINES
+
+**Be Concise:**
+- Target 2-5 short lines maximum
+- Make every word count—no repetition or filler
+- Use lightweight structure for scannability (bullets, numbered lists, short prompts)
+- Avoid jargon (blocks, slugs, cron) unless the user asks
+
+**Be Proactive:**
+- Suggest next steps before being asked
+- Anticipate needs based on conversation context and user information
+- Look for opportunities to expand scope when relevant
+- Reveal capabilities through action, not explanation
+
+**Use Tools Effectively:**
+- Select the right tool for each task
+- **Always check `find_library_agent` before searching the marketplace**
+- Use `add_understanding` to capture valuable business context
+- When tool calls fail, try alternative approaches
+
+## CRITICAL REMINDER
+
+You are NOT a chatbot. You are NOT documentation. You are a partner who helps busy business owners get value quickly by showing proof through working automations. Bias toward action over explanation."""
+
+# Module-level set to hold strong references to background tasks.
+# This prevents asyncio from garbage collecting tasks before they complete.
+# Tasks are automatically removed on completion via done_callback.
+_background_tasks: set[asyncio.Task] = set()
+
+
+async def _mark_operation_started(tool_call_id: str) -> bool:
+    """Mark a long-running operation as started (Redis-based).
+
+    Returns True if successfully marked (operation was not already running),
+    False if operation was already running (lost race condition).
+    Raises exception if Redis is unavailable (fail-closed).
+    """
+    redis = await get_redis_async()
+    key = f"{RUNNING_OPERATION_PREFIX}{tool_call_id}"
+    # SETNX with TTL - atomic "set if not exists"
+    result = await redis.set(key, "1", ex=config.long_running_operation_ttl, nx=True)
+    return result is not None
+
+
+async def _mark_operation_completed(tool_call_id: str) -> None:
+    """Mark a long-running operation as completed (remove Redis key).
+
+    This is best-effort - if Redis fails, the TTL will eventually clean up.
+    """
+    try:
+        redis = await get_redis_async()
+        key = f"{RUNNING_OPERATION_PREFIX}{tool_call_id}"
+        await redis.delete(key)
+    except Exception as e:
+        # Non-critical: TTL will clean up eventually
+        logger.warning(f"Failed to delete running operation key {tool_call_id}: {e}")
 
 
 def _is_langfuse_configured() -> bool:
@@ -75,6 +198,30 @@ def _is_langfuse_configured() -> bool:
     )
 
 
+async def _get_system_prompt_template(context: str) -> str:
+    """Get the system prompt, trying Langfuse first with fallback to default.
+
+    Args:
+        context: The user context/information to compile into the prompt.
+
+    Returns:
+        The compiled system prompt string.
+    """
+    if _is_langfuse_configured():
+        try:
+            # cache_ttl_seconds=0 disables SDK caching to always get the latest prompt
+            # Use asyncio.to_thread to avoid blocking the event loop
+            prompt = await asyncio.to_thread(
+                langfuse.get_prompt, config.langfuse_prompt_name, cache_ttl_seconds=0
+            )
+            return prompt.compile(users_information=context)
+        except Exception as e:
+            logger.warning(f"Failed to fetch prompt from Langfuse, using default: {e}")
+
+    # Fallback to default prompt
+    return DEFAULT_SYSTEM_PROMPT.format(users_information=context)
+
+
 async def _build_system_prompt(user_id: str | None) -> tuple[str, Any]:
     """Build the full system prompt including business understanding if available.
 
@@ -83,12 +230,8 @@ async def _build_system_prompt(user_id: str | None) -> tuple[str, Any]:
                      If "default" and this is the user's first session, will use "onboarding" instead.
 
     Returns:
-        Tuple of (compiled prompt string, Langfuse prompt object for tracing)
+        Tuple of (compiled prompt string, business understanding object)
     """
-
-    # cache_ttl_seconds=0 disables SDK caching to always get the latest prompt
-    prompt = langfuse.get_prompt(config.langfuse_prompt_name, cache_ttl_seconds=0)
-
     # If user is authenticated, try to fetch their business understanding
     understanding = None
     if user_id:
@@ -97,12 +240,13 @@ async def _build_system_prompt(user_id: str | None) -> tuple[str, Any]:
         except Exception as e:
             logger.warning(f"Failed to fetch business understanding: {e}")
             understanding = None
+
     if understanding:
         context = format_understanding_for_prompt(understanding)
     else:
         context = "This is the first time you are meeting the user. Greet them and introduce them to the platform"
 
-    compiled = prompt.compile(users_information=context)
+    compiled = await _get_system_prompt_template(context)
     return compiled, understanding
 
 
@@ -210,16 +354,6 @@ async def stream_chat_completion(
         f"Streaming chat completion for session {session_id} for message {message} and user id {user_id}. Message is user message: {is_user_message}"
     )
 
-    # Check if Langfuse is configured - required for chat functionality
-    if not _is_langfuse_configured():
-        logger.error("Chat request failed: Langfuse is not configured")
-        yield StreamError(
-            errorText="Chat service is not available. Langfuse must be configured "
-            "with LANGFUSE_PUBLIC_KEY and LANGFUSE_SECRET_KEY environment variables."
-        )
-        yield StreamFinish()
-        return
-
     # Only fetch from Redis if session not provided (initial call)
     if session is None:
         session = await get_chat_session(session_id, user_id)
@@ -315,6 +449,7 @@ async def stream_chat_completion(
     has_yielded_end = False
     has_yielded_error = False
     has_done_tool_call = False
+    has_long_running_tool_call = False  # Track if we had a long-running tool call
     has_received_text = False
     text_streaming_ended = False
     tool_response_messages: list[ChatMessage] = []
@@ -336,7 +471,6 @@ async def stream_chat_completion(
             system_prompt=system_prompt,
             text_block_id=text_block_id,
         ):
-
             if isinstance(chunk, StreamTextStart):
                 # Emit text-start before first text delta
                 if not has_received_text:
@@ -394,13 +528,34 @@ async def stream_chat_completion(
                     if isinstance(chunk.output, str)
                     else orjson.dumps(chunk.output).decode("utf-8")
                 )
-                tool_response_messages.append(
-                    ChatMessage(
-                        role="tool",
-                        content=result_content,
-                        tool_call_id=chunk.toolCallId,
+                # Skip saving long-running operation responses - messages already saved in _yield_tool_call
+                # Use JSON parsing instead of substring matching to avoid false positives
+                is_long_running_response = False
+                try:
+                    parsed = orjson.loads(result_content)
+                    if isinstance(parsed, dict) and parsed.get("type") in (
+                        "operation_started",
+                        "operation_in_progress",
+                    ):
+                        is_long_running_response = True
+                except (orjson.JSONDecodeError, TypeError):
+                    pass  # Not JSON or not a dict - treat as regular response
+                if is_long_running_response:
+                    # Remove from accumulated_tool_calls since assistant message was already saved
+                    accumulated_tool_calls[:] = [
+                        tc
+                        for tc in accumulated_tool_calls
+                        if tc["id"] != chunk.toolCallId
+                    ]
+                    has_long_running_tool_call = True
+                else:
+                    tool_response_messages.append(
+                        ChatMessage(
+                            role="tool",
+                            content=result_content,
+                            tool_call_id=chunk.toolCallId,
+                        )
                     )
-                )
                 has_done_tool_call = True
                 # Track if any tool execution failed
                 if not chunk.success:
@@ -576,7 +731,14 @@ async def stream_chat_completion(
             logger.info(
                 f"Extended session messages, new message_count={len(session.messages)}"
             )
-        if messages_to_save or has_appended_streaming_message:
+        # Save if there are regular (non-long-running) tool responses or streaming message.
+        # Long-running tools save their own state, but we still need to save regular tools
+        # that may be in the same response.
+        has_regular_tool_responses = len(tool_response_messages) > 0
+        if has_regular_tool_responses or (
+            not has_long_running_tool_call
+            and (messages_to_save or has_appended_streaming_message)
+        ):
             await upsert_chat_session(session)
     else:
         logger.info(
@@ -585,7 +747,9 @@ async def stream_chat_completion(
         )
 
     # If we did a tool call, stream the chat completion again to get the next response
-    if has_done_tool_call:
+    # Skip only if ALL tools were long-running (they handle their own completion)
+    has_regular_tools = len(tool_response_messages) > 0
+    if has_done_tool_call and (has_regular_tools or not has_long_running_tool_call):
         logger.info(
             "Tool call executed, streaming chat completion again to get assistant response"
         )
@@ -725,6 +889,114 @@ async def _summarize_messages(
     return summary or "No summary available."
 
 
+def _ensure_tool_pairs_intact(
+    recent_messages: list[dict],
+    all_messages: list[dict],
+    start_index: int,
+) -> list[dict]:
+    """
+    Ensure tool_call/tool_response pairs stay together after slicing.
+
+    When slicing messages for context compaction, a naive slice can separate
+    an assistant message containing tool_calls from its corresponding tool
+    response messages. This causes API validation errors (e.g., Anthropic's
+    "unexpected tool_use_id found in tool_result blocks").
+
+    This function checks for orphan tool responses in the slice and extends
+    backwards to include their corresponding assistant messages.
+
+    Args:
+        recent_messages: The sliced messages to validate
+        all_messages: The complete message list (for looking up missing assistants)
+        start_index: The index in all_messages where recent_messages begins
+
+    Returns:
+        A potentially extended list of messages with tool pairs intact
+    """
+    if not recent_messages:
+        return recent_messages
+
+    # Collect all tool_call_ids from assistant messages in the slice
+    available_tool_call_ids: set[str] = set()
+    for msg in recent_messages:
+        if msg.get("role") == "assistant" and msg.get("tool_calls"):
+            for tc in msg["tool_calls"]:
+                tc_id = tc.get("id")
+                if tc_id:
+                    available_tool_call_ids.add(tc_id)
+
+    # Find orphan tool responses (tool messages whose tool_call_id is missing)
+    orphan_tool_call_ids: set[str] = set()
+    for msg in recent_messages:
+        if msg.get("role") == "tool":
+            tc_id = msg.get("tool_call_id")
+            if tc_id and tc_id not in available_tool_call_ids:
+                orphan_tool_call_ids.add(tc_id)
+
+    if not orphan_tool_call_ids:
+        # No orphans, slice is valid
+        return recent_messages
+
+    # Find the assistant messages that contain the orphan tool_call_ids
+    # Search backwards from start_index in all_messages
+    messages_to_prepend: list[dict] = []
+    for i in range(start_index - 1, -1, -1):
+        msg = all_messages[i]
+        if msg.get("role") == "assistant" and msg.get("tool_calls"):
+            msg_tool_ids = {tc.get("id") for tc in msg["tool_calls"] if tc.get("id")}
+            if msg_tool_ids & orphan_tool_call_ids:
+                # This assistant message has tool_calls we need
+                # Also collect its contiguous tool responses that follow it
+                assistant_and_responses: list[dict] = [msg]
+
+                # Scan forward from this assistant to collect tool responses
+                for j in range(i + 1, start_index):
+                    following_msg = all_messages[j]
+                    if following_msg.get("role") == "tool":
+                        tool_id = following_msg.get("tool_call_id")
+                        if tool_id and tool_id in msg_tool_ids:
+                            assistant_and_responses.append(following_msg)
+                    else:
+                        # Stop at first non-tool message
+                        break
+
+                # Prepend the assistant and its tool responses (maintain order)
+                messages_to_prepend = assistant_and_responses + messages_to_prepend
+                # Mark these as found
+                orphan_tool_call_ids -= msg_tool_ids
+                # Also add this assistant's tool_call_ids to available set
+                available_tool_call_ids |= msg_tool_ids
+
+        if not orphan_tool_call_ids:
+            # Found all missing assistants
+            break
+
+    if orphan_tool_call_ids:
+        # Some tool_call_ids couldn't be resolved - remove those tool responses
+        # This shouldn't happen in normal operation but handles edge cases
+        logger.warning(
+            f"Could not find assistant messages for tool_call_ids: {orphan_tool_call_ids}. "
+            "Removing orphan tool responses."
+        )
+        recent_messages = [
+            msg
+            for msg in recent_messages
+            if not (
+                msg.get("role") == "tool"
+                and msg.get("tool_call_id") in orphan_tool_call_ids
+            )
+        ]
+
+    if messages_to_prepend:
+        logger.info(
+            f"Extended recent messages by {len(messages_to_prepend)} to preserve "
+            f"tool_call/tool_response pairs"
+        )
+        return messages_to_prepend + recent_messages
+
+    return recent_messages
+
+
 async def _stream_chat_chunks(
     session: ChatSession,
     tools: list[ChatCompletionToolParam],
@@ -816,7 +1088,15 @@ async def _stream_chat_chunks(
             # Always attempt mitigation when over limit, even with few messages
             if messages:
                 # Split messages based on whether system prompt exists
-                recent_messages = messages[-KEEP_RECENT:]
+                # Calculate start index for the slice
+                slice_start = max(0, len(messages_dict) - KEEP_RECENT)
+                recent_messages = messages_dict[-KEEP_RECENT:]
+
+                # Ensure tool_call/tool_response pairs stay together
+                # This prevents API errors from orphan tool responses
+                recent_messages = _ensure_tool_pairs_intact(
+                    recent_messages, messages_dict, slice_start
+                )
 
                 if has_system_prompt:
                     # Keep system prompt separate, summarize everything between system and recent
@@ -903,6 +1183,13 @@ async def _stream_chat_chunks(
                                     if len(recent_messages) >= keep_count
                                     else recent_messages
                                 )
+                                # Ensure tool pairs stay intact in the reduced slice
+                                reduced_slice_start = max(
+                                    0, len(recent_messages) - keep_count
+                                )
+                                reduced_recent = _ensure_tool_pairs_intact(
+                                    reduced_recent, recent_messages, reduced_slice_start
+                                )
                                 if has_system_prompt:
                                     messages = [
                                         system_msg,
@@ -961,7 +1248,10 @@ async def _stream_chat_chunks(
 
                     # Create a base list excluding system prompt to avoid duplication
                     # This is the pool of messages we'll slice from in the loop
-                    base_msgs = messages[1:] if has_system_prompt else messages
+                    # Use messages_dict for type consistency with _ensure_tool_pairs_intact
+                    base_msgs = (
+                        messages_dict[1:] if has_system_prompt else messages_dict
+                    )
 
                     # Try progressively smaller keep counts
                     new_token_count = token_count  # Initialize with current count
@@ -984,6 +1274,12 @@ async def _stream_chat_chunks(
                             # Slice from base_msgs to get recent messages (without system prompt)
                             recent_messages = base_msgs[-keep_count:]
 
+                            # Ensure tool pairs stay intact in the reduced slice
+                            reduced_slice_start = max(0, len(base_msgs) - keep_count)
+                            recent_messages = _ensure_tool_pairs_intact(
+                                recent_messages, base_msgs, reduced_slice_start
+                            )
+
                             if has_system_prompt:
                                 messages = [system_msg] + recent_messages
                             else:
@@ -1260,17 +1556,19 @@ async def _yield_tool_call(
     """
     Yield a tool call and its execution result.
 
-    For long-running tools, yields heartbeat events every 15 seconds to keep
-    the SSE connection alive through proxies and load balancers.
+    For tools marked with `is_long_running=True` (like agent generation), spawns a
+    background task so the operation survives SSE disconnections. For other tools,
+    yields heartbeat events every 15 seconds to keep the SSE connection alive.
 
     Raises:
         orjson.JSONDecodeError: If tool call arguments cannot be parsed as JSON
         KeyError: If expected tool call fields are missing
         TypeError: If tool call structure is invalid
     """
+    import uuid as uuid_module
+
     tool_name = tool_calls[yield_idx]["function"]["name"]
     tool_call_id = tool_calls[yield_idx]["id"]
-    logger.info(f"Yielding tool call: {tool_calls[yield_idx]}")
 
     # Parse tool call arguments - handle empty arguments gracefully
     raw_arguments = tool_calls[yield_idx]["function"]["arguments"]
@@ -1285,7 +1583,151 @@ async def _yield_tool_call(
         input=arguments,
     )
 
-    # Run tool execution in background task with heartbeats to keep connection alive
+    # Check if this tool is long-running (survives SSE disconnection)
+    tool = get_tool(tool_name)
+    if tool and tool.is_long_running:
+        # Atomic check-and-set: returns False if operation already running (lost race)
+        if not await _mark_operation_started(tool_call_id):
+            logger.info(
+                f"Tool call {tool_call_id} already in progress, returning status"
+            )
+            # Build dynamic message based on tool name
+            if tool_name == "create_agent":
+                in_progress_msg = "Agent creation already in progress. Please wait..."
+            elif tool_name == "edit_agent":
+                in_progress_msg = "Agent edit already in progress. Please wait..."
+            else:
+                in_progress_msg = f"{tool_name} already in progress. Please wait..."
+
+            yield StreamToolOutputAvailable(
+                toolCallId=tool_call_id,
+                toolName=tool_name,
+                output=OperationInProgressResponse(
+                    message=in_progress_msg,
+                    tool_call_id=tool_call_id,
+                ).model_dump_json(),
+                success=True,
+            )
+            return
+
+        # Generate operation ID
+        operation_id = str(uuid_module.uuid4())
+
+        # Build a user-friendly message based on tool and arguments
+        if tool_name == "create_agent":
+            agent_desc = arguments.get("description", "")
+            # Truncate long descriptions for the message
+            desc_preview = (
+                (agent_desc[:100] + "...") if len(agent_desc) > 100 else agent_desc
+            )
+            pending_msg = (
+                f"Creating your agent: {desc_preview}"
+                if desc_preview
+                else "Creating agent... This may take a few minutes."
+            )
+            started_msg = (
+                "Agent creation started. You can close this tab - "
+                "check your library in a few minutes."
+            )
+        elif tool_name == "edit_agent":
+            changes = arguments.get("changes", "")
+            changes_preview = (changes[:100] + "...") if len(changes) > 100 else changes
+            pending_msg = (
+                f"Editing agent: {changes_preview}"
+                if changes_preview
+                else "Editing agent... This may take a few minutes."
+            )
+            started_msg = (
+                "Agent edit started. You can close this tab - "
+                "check your library in a few minutes."
+            )
+        else:
+            pending_msg = f"Running {tool_name}... This may take a few minutes."
+            started_msg = (
+                f"{tool_name} started. You can close this tab - "
+                "check back in a few minutes."
+            )
+
+        # Track appended messages for rollback on failure
+        assistant_message: ChatMessage | None = None
+        pending_message: ChatMessage | None = None
+
+        # Wrap session save and task creation in try-except to release lock on failure
+        try:
+            # Save assistant message with tool_call FIRST (required by LLM)
+            assistant_message = ChatMessage(
+                role="assistant",
+                content="",
+                tool_calls=[tool_calls[yield_idx]],
+            )
+            session.messages.append(assistant_message)
+
+            # Then save pending tool result
+            pending_message = ChatMessage(
+                role="tool",
+                content=OperationPendingResponse(
+                    message=pending_msg,
+                    operation_id=operation_id,
+                    tool_name=tool_name,
+                ).model_dump_json(),
+                tool_call_id=tool_call_id,
+            )
+            session.messages.append(pending_message)
+            await upsert_chat_session(session)
+            logger.info(
+                f"Saved pending operation {operation_id} for tool {tool_name} "
+                f"in session {session.session_id}"
+            )
+
+            # Store task reference in module-level set to prevent GC before completion
+            task = asyncio.create_task(
+                _execute_long_running_tool(
+                    tool_name=tool_name,
+                    parameters=arguments,
+                    tool_call_id=tool_call_id,
+                    operation_id=operation_id,
+                    session_id=session.session_id,
+                    user_id=session.user_id,
+                )
+            )
+            _background_tasks.add(task)
+            task.add_done_callback(_background_tasks.discard)
+        except Exception as e:
+            # Roll back appended messages to prevent data corruption on subsequent saves
+            if (
+                pending_message
+                and session.messages
+                and session.messages[-1] == pending_message
+            ):
+                session.messages.pop()
+            if (
+                assistant_message
+                and session.messages
+                and session.messages[-1] == assistant_message
+            ):
+                session.messages.pop()
+
+            # Release the Redis lock since the background task won't be spawned
+            await _mark_operation_completed(tool_call_id)
+            logger.error(
+                f"Failed to setup long-running tool {tool_name}: {e}", exc_info=True
+            )
+            raise
+
+        # Return immediately - don't wait for completion
+        yield StreamToolOutputAvailable(
+            toolCallId=tool_call_id,
+            toolName=tool_name,
+            output=OperationStartedResponse(
+                message=started_msg,
+                operation_id=operation_id,
+                tool_name=tool_name,
+            ).model_dump_json(),
+            success=True,
+        )
+        return
+
+    # Normal flow: Run tool execution in background task with heartbeats
     tool_task = asyncio.create_task(
         execute_tool(
             tool_name=tool_name,
@@ -1335,3 +1777,190 @@ async def _yield_tool_call(
         )
 
     yield tool_execution_response
+
+
+async def _execute_long_running_tool(
+    tool_name: str,
+    parameters: dict[str, Any],
+    tool_call_id: str,
+    operation_id: str,
+    session_id: str,
+    user_id: str | None,
+) -> None:
+    """Execute a long-running tool in background and update chat history with result.
+
+    This function runs independently of the SSE connection, so the operation
+    survives if the user closes their browser tab.
+    """
+    try:
+        # Load fresh session (not stale reference)
+        session = await get_chat_session(session_id, user_id)
+        if not session:
+            logger.error(f"Session {session_id} not found for background tool")
+            return
+
+        # Execute the actual tool
+        result = await execute_tool(
+            tool_name=tool_name,
+            parameters=parameters,
+            tool_call_id=tool_call_id,
+            user_id=user_id,
+            session=session,
+        )
+
+        # Update the pending message with result
+        await _update_pending_operation(
+            session_id=session_id,
+            tool_call_id=tool_call_id,
+            result=(
+                result.output
+                if isinstance(result.output, str)
+                else orjson.dumps(result.output).decode("utf-8")
+            ),
+        )
+
+        logger.info(f"Background tool {tool_name} completed for session {session_id}")
+
+        # Generate LLM continuation so user sees response when they poll/refresh
+        await _generate_llm_continuation(session_id=session_id, user_id=user_id)
+
+    except Exception as e:
+        logger.error(f"Background tool {tool_name} failed: {e}", exc_info=True)
+        error_response = ErrorResponse(
+            message=f"Tool {tool_name} failed: {str(e)}",
+        )
+        await _update_pending_operation(
+            session_id=session_id,
+            tool_call_id=tool_call_id,
+            result=error_response.model_dump_json(),
+        )
+    finally:
+        await _mark_operation_completed(tool_call_id)
+
+
+async def _update_pending_operation(
+    session_id: str,
+    tool_call_id: str,
+    result: str,
+) -> None:
+    """Update the pending tool message with final result.
+
+    This is called by background tasks when long-running operations complete.
+    """
+    # Update the message in database
+    updated = await chat_db.update_tool_message_content(
+        session_id=session_id,
+        tool_call_id=tool_call_id,
+        new_content=result,
+    )
+
+    if updated:
+        # Invalidate Redis cache so next load gets fresh data
+        # Wrap in try/except to prevent cache failures from triggering error handling
+        # that would overwrite our successful DB update
+        try:
+            await invalidate_session_cache(session_id)
+        except Exception as e:
+            # Non-critical: cache will eventually be refreshed on next load
+            logger.warning(f"Failed to invalidate cache for session {session_id}: {e}")
+        logger.info(
+            f"Updated pending operation for tool_call_id {tool_call_id} "
+            f"in session {session_id}"
+        )
+    else:
+        logger.warning(
+            f"Failed to update pending operation for tool_call_id {tool_call_id} "
+            f"in session {session_id}"
+        )
+
+
+async def _generate_llm_continuation(
+    session_id: str,
+    user_id: str | None,
+) -> None:
+    """Generate an LLM response after a long-running tool completes.
+
+    This is called by background tasks to continue the conversation
+    after a tool result is saved. The response is saved to the database
+    so users see it when they refresh or poll.
+    """
+    try:
+        # Load fresh session from DB (bypass cache to get the updated tool result)
+        await invalidate_session_cache(session_id)
+        session = await get_chat_session(session_id, user_id)
+        if not session:
+            logger.error(f"Session {session_id} not found for LLM continuation")
+            return
+
+        # Build system prompt
+        system_prompt, _ = await _build_system_prompt(user_id)
+
+        # Build messages in OpenAI format
+        messages = session.to_openai_messages()
+        if system_prompt:
+            from openai.types.chat import ChatCompletionSystemMessageParam
+
+            system_message = ChatCompletionSystemMessageParam(
+                role="system",
+                content=system_prompt,
+            )
+            messages = [system_message] + messages
+
+        # Build extra_body for tracing
+        extra_body: dict[str, Any] = {
+            "posthogProperties": {
+                "environment": settings.config.app_env.value,
+            },
+        }
+        if user_id:
+            extra_body["user"] = user_id[:128]
+            extra_body["posthogDistinctId"] = user_id
+        if session_id:
+            extra_body["session_id"] = session_id[:128]
+
+        # Make non-streaming LLM call (no tools - just text response)
+        from typing import cast
+
+        from openai.types.chat import ChatCompletionMessageParam
+
+        # No tools parameter = text-only response (no tool calls)
+        response = await client.chat.completions.create(
+            model=config.model,
+            messages=cast(list[ChatCompletionMessageParam], messages),
+            extra_body=extra_body,
+        )
+
+        if response.choices and response.choices[0].message.content:
+            assistant_content = response.choices[0].message.content
+
+            # Reload session from DB to avoid race condition with user messages
+            # that may have been sent while we were generating the LLM response
+            fresh_session = await get_chat_session(session_id, user_id)
+            if not fresh_session:
+                logger.error(
+                    f"Session {session_id} disappeared during LLM continuation"
+                )
+                return
+
+            # Save assistant message to database
+            assistant_message = ChatMessage(
+                role="assistant",
+                content=assistant_content,
+            )
+            fresh_session.messages.append(assistant_message)
+
+            # Save to database (not cache) to persist the response
+            await upsert_chat_session(fresh_session)
+
+            # Invalidate cache so next poll/refresh gets fresh data
+            await invalidate_session_cache(session_id)
+
+            logger.info(
+                f"Generated LLM continuation for session {session_id}, "
+                f"response length: {len(assistant_content)}"
+            )
+        else:
+            logger.warning(f"LLM continuation returned empty response for {session_id}")
+
+    except Exception as e:
+        logger.error(f"Failed to generate LLM continuation: {e}", exc_info=True)

autogpt_platform/backend/backend/api/features/chat/tools/__init__.py

@@ -49,6 +49,11 @@ tools: list[ChatCompletionToolParam] = [
 ]
 
 
+def get_tool(tool_name: str) -> BaseTool | None:
+    """Get a tool instance by name."""
+    return TOOL_REGISTRY.get(tool_name)
+
+
 async def execute_tool(
     tool_name: str,
     parameters: dict[str, Any],
@@ -57,7 +62,7 @@ async def execute_tool(
     tool_call_id: str,
 ) -> "StreamToolOutputAvailable":
     """Execute a tool by name."""
-    tool = TOOL_REGISTRY.get(tool_name)
+    tool = get_tool(tool_name)
     if not tool:
         raise ValueError(f"Tool {tool_name} not found")
 

autogpt_platform/backend/backend/api/features/chat/tools/base.py

@@ -36,6 +36,16 @@ class BaseTool:
         """Whether this tool requires authentication."""
         return False
 
+    @property
+    def is_long_running(self) -> bool:
+        """Whether this tool is long-running and should execute in background.
+
+        Long-running tools (like agent generation) are executed via background
+        tasks to survive SSE disconnections. The result is persisted to chat
+        history and visible when the user refreshes.
+        """
+        return False
+
     def as_openai_tool(self) -> ChatCompletionToolParam:
         """Convert to OpenAI tool format."""
         return ChatCompletionToolParam(

autogpt_platform/backend/backend/api/features/chat/tools/create_agent.py

@@ -42,6 +42,10 @@ class CreateAgentTool(BaseTool):
     def requires_auth(self) -> bool:
         return True
 
+    @property
+    def is_long_running(self) -> bool:
+        return True
+
     @property
     def parameters(self) -> dict[str, Any]:
         return {

autogpt_platform/backend/backend/api/features/chat/tools/edit_agent.py

@@ -42,6 +42,10 @@ class EditAgentTool(BaseTool):
     def requires_auth(self) -> bool:
         return True
 
+    @property
+    def is_long_running(self) -> bool:
+        return True
+
     @property
     def parameters(self) -> dict[str, Any]:
         return {

autogpt_platform/backend/backend/api/features/chat/tools/find_block.py

@@ -107,7 +107,8 @@ class FindBlockTool(BaseTool):
                 block_id = result["content_id"]
                 block = get_block(block_id)
 
-                if block:
+                # Skip disabled blocks
+                if block and not block.disabled:
                     # Get input/output schemas
                     input_schema = {}
                     output_schema = {}

autogpt_platform/backend/backend/api/features/chat/tools/models.py

@@ -28,6 +28,10 @@ class ResponseType(str, Enum):
     BLOCK_OUTPUT = "block_output"
     DOC_SEARCH_RESULTS = "doc_search_results"
     DOC_PAGE = "doc_page"
+    # Long-running operation types
+    OPERATION_STARTED = "operation_started"
+    OPERATION_PENDING = "operation_pending"
+    OPERATION_IN_PROGRESS = "operation_in_progress"
 
 
 # Base response model
@@ -334,3 +338,39 @@ class BlockOutputResponse(ToolResponseBase):
     block_name: str
     outputs: dict[str, list[Any]]
     success: bool = True
+
+
+# Long-running operation models
+class OperationStartedResponse(ToolResponseBase):
+    """Response when a long-running operation has been started in the background.
+
+    This is returned immediately to the client while the operation continues
+    to execute. The user can close the tab and check back later.
+    """
+
+    type: ResponseType = ResponseType.OPERATION_STARTED
+    operation_id: str
+    tool_name: str
+
+
+class OperationPendingResponse(ToolResponseBase):
+    """Response stored in chat history while a long-running operation is executing.
+
+    This is persisted to the database so users see a pending state when they
+    refresh before the operation completes.
+    """
+
+    type: ResponseType = ResponseType.OPERATION_PENDING
+    operation_id: str
+    tool_name: str
+
+
+class OperationInProgressResponse(ToolResponseBase):
+    """Response when an operation is already in progress.
+
+    Returned for idempotency when the same tool_call_id is requested again
+    while the background task is still running.
+    """
+
+    type: ResponseType = ResponseType.OPERATION_IN_PROGRESS
+    tool_call_id: str

autogpt_platform/backend/backend/api/features/executions/review/review_routes_test.py

@@ -164,9 +164,9 @@ async def test_process_review_action_approve_success(
     """Test successful review approval"""
     # Mock the route functions
 
-    # Mock get_pending_reviews_by_node_exec_ids (called to find the graph_exec_id)
+    # Mock get_reviews_by_node_exec_ids (called to find the graph_exec_id)
     mock_get_reviews_for_user = mocker.patch(
-        "backend.api.features.executions.review.routes.get_pending_reviews_by_node_exec_ids"
+        "backend.api.features.executions.review.routes.get_reviews_by_node_exec_ids"
     )
     mock_get_reviews_for_user.return_value = {"test_node_123": sample_pending_review}
 
@@ -244,9 +244,9 @@ async def test_process_review_action_reject_success(
     """Test successful review rejection"""
     # Mock the route functions
 
-    # Mock get_pending_reviews_by_node_exec_ids (called to find the graph_exec_id)
+    # Mock get_reviews_by_node_exec_ids (called to find the graph_exec_id)
     mock_get_reviews_for_user = mocker.patch(
-        "backend.api.features.executions.review.routes.get_pending_reviews_by_node_exec_ids"
+        "backend.api.features.executions.review.routes.get_reviews_by_node_exec_ids"
     )
     mock_get_reviews_for_user.return_value = {"test_node_123": sample_pending_review}
 
@@ -339,9 +339,9 @@ async def test_process_review_action_mixed_success(
 
     # Mock the route functions
 
-    # Mock get_pending_reviews_by_node_exec_ids (called to find the graph_exec_id)
+    # Mock get_reviews_by_node_exec_ids (called to find the graph_exec_id)
     mock_get_reviews_for_user = mocker.patch(
-        "backend.api.features.executions.review.routes.get_pending_reviews_by_node_exec_ids"
+        "backend.api.features.executions.review.routes.get_reviews_by_node_exec_ids"
     )
     mock_get_reviews_for_user.return_value = {
         "test_node_123": sample_pending_review,
@@ -463,9 +463,9 @@ async def test_process_review_action_review_not_found(
     test_user_id: str,
 ) -> None:
     """Test error when review is not found"""
-    # Mock get_pending_reviews_by_node_exec_ids (called to find the graph_exec_id)
+    # Mock get_reviews_by_node_exec_ids (called to find the graph_exec_id)
     mock_get_reviews_for_user = mocker.patch(
-        "backend.api.features.executions.review.routes.get_pending_reviews_by_node_exec_ids"
+        "backend.api.features.executions.review.routes.get_reviews_by_node_exec_ids"
     )
     # Return empty dict to simulate review not found
     mock_get_reviews_for_user.return_value = {}
@@ -506,7 +506,7 @@ async def test_process_review_action_review_not_found(
     response = await client.post("/api/review/action", json=request_data)
 
     assert response.status_code == 404
-    assert "No pending review found" in response.json()["detail"]
+    assert "Review(s) not found" in response.json()["detail"]
 
 
 @pytest.mark.asyncio(loop_scope="session")
@@ -517,9 +517,9 @@ async def test_process_review_action_partial_failure(
     test_user_id: str,
 ) -> None:
     """Test handling of partial failures in review processing"""
-    # Mock get_pending_reviews_by_node_exec_ids (called to find the graph_exec_id)
+    # Mock get_reviews_by_node_exec_ids (called to find the graph_exec_id)
     mock_get_reviews_for_user = mocker.patch(
-        "backend.api.features.executions.review.routes.get_pending_reviews_by_node_exec_ids"
+        "backend.api.features.executions.review.routes.get_reviews_by_node_exec_ids"
     )
     mock_get_reviews_for_user.return_value = {"test_node_123": sample_pending_review}
 
@@ -567,9 +567,9 @@ async def test_process_review_action_invalid_node_exec_id(
     test_user_id: str,
 ) -> None:
     """Test failure when trying to process review with invalid node execution ID"""
-    # Mock get_pending_reviews_by_node_exec_ids (called to find the graph_exec_id)
+    # Mock get_reviews_by_node_exec_ids (called to find the graph_exec_id)
     mock_get_reviews_for_user = mocker.patch(
-        "backend.api.features.executions.review.routes.get_pending_reviews_by_node_exec_ids"
+        "backend.api.features.executions.review.routes.get_reviews_by_node_exec_ids"
     )
     # Return empty dict to simulate review not found
     mock_get_reviews_for_user.return_value = {}
@@ -596,7 +596,7 @@ async def test_process_review_action_invalid_node_exec_id(
 
     # Returns 404 when review is not found
     assert response.status_code == 404
-    assert "No pending review found" in response.json()["detail"]
+    assert "Review(s) not found" in response.json()["detail"]
 
 
 @pytest.mark.asyncio(loop_scope="session")
@@ -607,9 +607,9 @@ async def test_process_review_action_auto_approve_creates_auto_approval_records(
     test_user_id: str,
 ) -> None:
     """Test that auto_approve_future_actions flag creates auto-approval records"""
-    # Mock get_pending_reviews_by_node_exec_ids (called to find the graph_exec_id)
+    # Mock get_reviews_by_node_exec_ids (called to find the graph_exec_id)
     mock_get_reviews_for_user = mocker.patch(
-        "backend.api.features.executions.review.routes.get_pending_reviews_by_node_exec_ids"
+        "backend.api.features.executions.review.routes.get_reviews_by_node_exec_ids"
     )
     mock_get_reviews_for_user.return_value = {"test_node_123": sample_pending_review}
 
@@ -737,9 +737,9 @@ async def test_process_review_action_without_auto_approve_still_loads_settings(
     test_user_id: str,
 ) -> None:
     """Test that execution context is created with settings even without auto-approve"""
-    # Mock get_pending_reviews_by_node_exec_ids (called to find the graph_exec_id)
+    # Mock get_reviews_by_node_exec_ids (called to find the graph_exec_id)
     mock_get_reviews_for_user = mocker.patch(
-        "backend.api.features.executions.review.routes.get_pending_reviews_by_node_exec_ids"
+        "backend.api.features.executions.review.routes.get_reviews_by_node_exec_ids"
     )
     mock_get_reviews_for_user.return_value = {"test_node_123": sample_pending_review}
 
@@ -885,9 +885,9 @@ async def test_process_review_action_auto_approve_only_applies_to_approved_revie
         reviewed_at=FIXED_NOW,
     )
 
-    # Mock get_pending_reviews_by_node_exec_ids (called to find the graph_exec_id)
+    # Mock get_reviews_by_node_exec_ids (called to find the graph_exec_id)
     mock_get_reviews_for_user = mocker.patch(
-        "backend.api.features.executions.review.routes.get_pending_reviews_by_node_exec_ids"
+        "backend.api.features.executions.review.routes.get_reviews_by_node_exec_ids"
     )
     # Need to return both reviews in WAITING state (before processing)
     approved_review_waiting = PendingHumanReviewModel(
@@ -1031,9 +1031,9 @@ async def test_process_review_action_per_review_auto_approve_granularity(
     test_user_id: str,
 ) -> None:
     """Test that auto-approval can be set per-review (granular control)"""
-    # Mock get_pending_reviews_by_node_exec_ids - return different reviews based on node_exec_id
+    # Mock get_reviews_by_node_exec_ids - return different reviews based on node_exec_id
     mock_get_reviews_for_user = mocker.patch(
-        "backend.api.features.executions.review.routes.get_pending_reviews_by_node_exec_ids"
+        "backend.api.features.executions.review.routes.get_reviews_by_node_exec_ids"
     )
 
     # Create a mapping of node_exec_id to review

autogpt_platform/backend/backend/api/features/executions/review/routes.py

@@ -14,9 +14,9 @@ from backend.data.execution import (
 from backend.data.graph import get_graph_settings
 from backend.data.human_review import (
     create_auto_approval_record,
-    get_pending_reviews_by_node_exec_ids,
     get_pending_reviews_for_execution,
     get_pending_reviews_for_user,
+    get_reviews_by_node_exec_ids,
     has_pending_reviews_for_graph_exec,
     process_all_reviews_for_execution,
 )
@@ -137,17 +137,17 @@ async def process_review_action(
             detail="At least one review must be provided",
         )
 
-    # Batch fetch all requested reviews
-    reviews_map = await get_pending_reviews_by_node_exec_ids(
+    # Batch fetch all requested reviews (regardless of status for idempotent handling)
+    reviews_map = await get_reviews_by_node_exec_ids(
         list(all_request_node_ids), user_id
     )
 
-    # Validate all reviews were found
+    # Validate all reviews were found (must exist, any status is OK for now)
     missing_ids = all_request_node_ids - set(reviews_map.keys())
     if missing_ids:
         raise HTTPException(
             status_code=status.HTTP_404_NOT_FOUND,
-            detail=f"No pending review found for node execution(s): {', '.join(missing_ids)}",
+            detail=f"Review(s) not found: {', '.join(missing_ids)}",
         )
 
     # Validate all reviews belong to the same execution

autogpt_platform/backend/backend/api/features/store/content_handlers.py

@@ -188,6 +188,10 @@ class BlockHandler(ContentHandler):
             try:
                 block_instance = block_cls()
 
+                # Skip disabled blocks - they shouldn't be indexed
+                if block_instance.disabled:
+                    continue
+
                 # Build searchable text from block metadata
                 parts = []
                 if hasattr(block_instance, "name") and block_instance.name:
@@ -248,12 +252,19 @@ class BlockHandler(ContentHandler):
         from backend.data.block import get_blocks
 
         all_blocks = get_blocks()
-        total_blocks = len(all_blocks)
+
+        # Filter out disabled blocks - they're not indexed
+        enabled_block_ids = [
+            block_id
+            for block_id, block_cls in all_blocks.items()
+            if not block_cls().disabled
+        ]
+        total_blocks = len(enabled_block_ids)
 
         if total_blocks == 0:
             return {"total": 0, "with_embeddings": 0, "without_embeddings": 0}
 
-        block_ids = list(all_blocks.keys())
+        block_ids = enabled_block_ids
         placeholders = ",".join([f"${i+1}" for i in range(len(block_ids))])
 
         embedded_result = await query_raw_with_schema(

autogpt_platform/backend/backend/api/features/store/content_handlers_test.py

@@ -81,6 +81,7 @@ async def test_block_handler_get_missing_items(mocker):
     mock_block_instance.name = "Calculator Block"
     mock_block_instance.description = "Performs calculations"
     mock_block_instance.categories = [MagicMock(value="MATH")]
+    mock_block_instance.disabled = False
     mock_block_instance.input_schema.model_json_schema.return_value = {
         "properties": {"expression": {"description": "Math expression to evaluate"}}
     }
@@ -116,11 +117,18 @@ async def test_block_handler_get_stats(mocker):
     """Test BlockHandler returns correct stats."""
     handler = BlockHandler()
 
-    # Mock get_blocks
+    # Mock get_blocks - each block class returns an instance with disabled=False
+    def make_mock_block_class():
+        mock_class = MagicMock()
+        mock_instance = MagicMock()
+        mock_instance.disabled = False
+        mock_class.return_value = mock_instance
+        return mock_class
+
     mock_blocks = {
-        "block-1": MagicMock(),
-        "block-2": MagicMock(),
-        "block-3": MagicMock(),
+        "block-1": make_mock_block_class(),
+        "block-2": make_mock_block_class(),
+        "block-3": make_mock_block_class(),
     }
 
     # Mock embedded count query (2 blocks have embeddings)
@@ -309,6 +317,7 @@ async def test_block_handler_handles_missing_attributes():
     mock_block_class = MagicMock()
     mock_block_instance = MagicMock()
     mock_block_instance.name = "Minimal Block"
+    mock_block_instance.disabled = False
     # No description, categories, or schema
     del mock_block_instance.description
     del mock_block_instance.categories
@@ -342,6 +351,7 @@ async def test_block_handler_skips_failed_blocks():
     good_instance.name = "Good Block"
     good_instance.description = "Works fine"
     good_instance.categories = []
+    good_instance.disabled = False
     good_block.return_value = good_instance
 
     bad_block = MagicMock()

autogpt_platform/backend/backend/data/human_review.py

@@ -263,11 +263,14 @@ async def get_pending_review_by_node_exec_id(
     return PendingHumanReviewModel.from_db(review, node_id=node_id)
 
 
-async def get_pending_reviews_by_node_exec_ids(
+async def get_reviews_by_node_exec_ids(
     node_exec_ids: list[str], user_id: str
 ) -> dict[str, "PendingHumanReviewModel"]:
     """
-    Get multiple pending reviews by their node execution IDs in a single batch query.
+    Get multiple reviews by their node execution IDs regardless of status.
+
+    Unlike get_pending_reviews_by_node_exec_ids, this returns reviews in any status
+    (WAITING, APPROVED, REJECTED). Used for validation in idempotent operations.
 
     Args:
         node_exec_ids: List of node execution IDs to look up
@@ -283,7 +286,6 @@ async def get_pending_reviews_by_node_exec_ids(
         where={
             "nodeExecId": {"in": node_exec_ids},
             "userId": user_id,
-            "status": ReviewStatus.WAITING,
         }
     )
 
@@ -407,38 +409,68 @@ async def process_all_reviews_for_execution(
 ) -> dict[str, PendingHumanReviewModel]:
     """Process all pending reviews for an execution with approve/reject decisions.
 
+    Handles race conditions gracefully: if a review was already processed with the
+    same decision by a concurrent request, it's treated as success rather than error.
+
     Args:
         user_id: User ID for ownership validation
         review_decisions: Map of node_exec_id -> (status, reviewed_data, message)
 
     Returns:
-        Dict of node_exec_id -> updated review model
+        Dict of node_exec_id -> updated review model (includes already-processed reviews)
     """
     if not review_decisions:
         return {}
 
     node_exec_ids = list(review_decisions.keys())
 
-    # Get all reviews for validation
-    reviews = await PendingHumanReview.prisma().find_many(
+    # Get all reviews (both WAITING and already processed) for the user
+    all_reviews = await PendingHumanReview.prisma().find_many(
         where={
             "nodeExecId": {"in": node_exec_ids},
             "userId": user_id,
-            "status": ReviewStatus.WAITING,
         },
     )
 
-    # Validate all reviews can be processed
-    if len(reviews) != len(node_exec_ids):
-        missing_ids = set(node_exec_ids) - {review.nodeExecId for review in reviews}
+    # Separate into pending and already-processed reviews
+    reviews_to_process = []
+    already_processed = []
+    for review in all_reviews:
+        if review.status == ReviewStatus.WAITING:
+            reviews_to_process.append(review)
+        else:
+            already_processed.append(review)
+
+    # Check for truly missing reviews (not found at all)
+    found_ids = {review.nodeExecId for review in all_reviews}
+    missing_ids = set(node_exec_ids) - found_ids
+    if missing_ids:
         raise ValueError(
-            f"Reviews not found, access denied, or not in WAITING status: {', '.join(missing_ids)}"
+            f"Reviews not found or access denied: {', '.join(missing_ids)}"
         )
 
-    # Create parallel update tasks
+    # Validate already-processed reviews have compatible status (same decision)
+    # This handles race conditions where another request processed the same reviews
+    for review in already_processed:
+        requested_status = review_decisions[review.nodeExecId][0]
+        if review.status != requested_status:
+            raise ValueError(
+                f"Review {review.nodeExecId} was already processed with status "
+                f"{review.status}, cannot change to {requested_status}"
+            )
+
+    # Log if we're handling a race condition (some reviews already processed)
+    if already_processed:
+        already_processed_ids = [r.nodeExecId for r in already_processed]
+        logger.info(
+            f"Race condition handled: {len(already_processed)} review(s) already "
+            f"processed by concurrent request: {already_processed_ids}"
+        )
+
+    # Create parallel update tasks for reviews that still need processing
     update_tasks = []
 
-    for review in reviews:
+    for review in reviews_to_process:
         new_status, reviewed_data, message = review_decisions[review.nodeExecId]
         has_data_changes = reviewed_data is not None and reviewed_data != review.payload
 
@@ -463,7 +495,7 @@ async def process_all_reviews_for_execution(
         update_tasks.append(task)
 
     # Execute all updates in parallel and get updated reviews
-    updated_reviews = await asyncio.gather(*update_tasks)
+    updated_reviews = await asyncio.gather(*update_tasks) if update_tasks else []
 
     # Note: Execution resumption is now handled at the API layer after ALL reviews
     # for an execution are processed (both approved and rejected)
@@ -472,8 +504,11 @@ async def process_all_reviews_for_execution(
     # Local import to avoid event loop conflicts in tests
     from backend.data.execution import get_node_execution
 
+    # Combine updated reviews with already-processed ones (for idempotent response)
+    all_result_reviews = list(updated_reviews) + already_processed
+
     result = {}
-    for review in updated_reviews:
+    for review in all_result_reviews:
         node_exec = await get_node_execution(review.nodeExecId)
         node_id = node_exec.node_id if node_exec else review.nodeExecId
         result[review.nodeExecId] = PendingHumanReviewModel.from_db(

autogpt_platform/backend/backend/util/settings.py

@@ -359,8 +359,8 @@ class Config(UpdateTrackingModel["Config"], BaseSettings):
         description="The port for the Agent Generator service",
     )
     agentgenerator_timeout: int = Field(
-        default=120,
-        description="The timeout in seconds for Agent Generator service requests",
+        default=600,
+        description="The timeout in seconds for Agent Generator service requests (includes retries for rate limits)",
     )
 
     enable_example_blocks: bool = Field(

autogpt_platform/frontend/src/app/(platform)/copilot/NewChatContext.tsx

@@ -1,41 +0,0 @@
-"use client";
-
-import { createContext, useContext, useRef, type ReactNode } from "react";
-
-interface NewChatContextValue {
-  onNewChatClick: () => void;
-  setOnNewChatClick: (handler?: () => void) => void;
-  performNewChat?: () => void;
-  setPerformNewChat: (handler?: () => void) => void;
-}
-
-const NewChatContext = createContext<NewChatContextValue | null>(null);
-
-export function NewChatProvider({ children }: { children: ReactNode }) {
-  const onNewChatRef = useRef<(() => void) | undefined>();
-  const performNewChatRef = useRef<(() => void) | undefined>();
-  const contextValueRef = useRef<NewChatContextValue>({
-    onNewChatClick() {
-      onNewChatRef.current?.();
-    },
-    setOnNewChatClick(handler?: () => void) {
-      onNewChatRef.current = handler;
-    },
-    performNewChat() {
-      performNewChatRef.current?.();
-    },
-    setPerformNewChat(handler?: () => void) {
-      performNewChatRef.current = handler;
-    },
-  });
-
-  return (
-    <NewChatContext.Provider value={contextValueRef.current}>
-      {children}
-    </NewChatContext.Provider>
-  );
-}
-
-export function useNewChat() {
-  return useContext(NewChatContext);
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/CopilotShell.tsx

@@ -1,12 +1,10 @@
 "use client";
 
 import { ChatLoader } from "@/components/contextual/Chat/components/ChatLoader/ChatLoader";
+import { Text } from "@/components/atoms/Text/Text";
 import { NAVBAR_HEIGHT_PX } from "@/lib/constants";
 import type { ReactNode } from "react";
-import { useEffect } from "react";
-import { useNewChat } from "../../NewChatContext";
 import { DesktopSidebar } from "./components/DesktopSidebar/DesktopSidebar";
-import { LoadingState } from "./components/LoadingState/LoadingState";
 import { MobileDrawer } from "./components/MobileDrawer/MobileDrawer";
 import { MobileHeader } from "./components/MobileHeader/MobileHeader";
 import { useCopilotShell } from "./useCopilotShell";
@@ -20,36 +18,21 @@ export function CopilotShell({ children }: Props) {
     isMobile,
     isDrawerOpen,
     isLoading,
+    isCreatingSession,
     isLoggedIn,
     hasActiveSession,
     sessions,
     currentSessionId,
-    handleSelectSession,
     handleOpenDrawer,
     handleCloseDrawer,
     handleDrawerOpenChange,
-    handleNewChat,
+    handleNewChatClick,
+    handleSessionClick,
     hasNextPage,
     isFetchingNextPage,
     fetchNextPage,
-    isReadyToShowContent,
   } = useCopilotShell();
 
-  const newChatContext = useNewChat();
-  const handleNewChatClickWrapper =
-    newChatContext?.onNewChatClick || handleNewChat;
-
-  useEffect(
-    function registerNewChatHandler() {
-      if (!newChatContext) return;
-      newChatContext.setPerformNewChat(handleNewChat);
-      return function cleanup() {
-        newChatContext.setPerformNewChat(undefined);
-      };
-    },
-    [newChatContext, handleNewChat],
-  );
-
   if (!isLoggedIn) {
     return (
       <div className="flex h-full items-center justify-center">
@@ -70,9 +53,9 @@ export function CopilotShell({ children }: Props) {
           isLoading={isLoading}
           hasNextPage={hasNextPage}
           isFetchingNextPage={isFetchingNextPage}
-          onSelectSession={handleSelectSession}
+          onSelectSession={handleSessionClick}
           onFetchNextPage={fetchNextPage}
-          onNewChat={handleNewChatClickWrapper}
+          onNewChat={handleNewChatClick}
           hasActiveSession={Boolean(hasActiveSession)}
         />
       )}
@@ -80,7 +63,18 @@ export function CopilotShell({ children }: Props) {
       <div className="relative flex min-h-0 flex-1 flex-col">
         {isMobile && <MobileHeader onOpenDrawer={handleOpenDrawer} />}
         <div className="flex min-h-0 flex-1 flex-col">
-          {isReadyToShowContent ? children : <LoadingState />}
+          {isCreatingSession ? (
+            <div className="flex h-full flex-1 flex-col items-center justify-center bg-[#f8f8f9]">
+              <div className="flex flex-col items-center gap-4">
+                <ChatLoader />
+                <Text variant="body" className="text-zinc-500">
+                  Creating your chat...
+                </Text>
+              </div>
+            </div>
+          ) : (
+            children
+          )}
         </div>
       </div>
 
@@ -92,9 +86,9 @@ export function CopilotShell({ children }: Props) {
           isLoading={isLoading}
           hasNextPage={hasNextPage}
           isFetchingNextPage={isFetchingNextPage}
-          onSelectSession={handleSelectSession}
+          onSelectSession={handleSessionClick}
           onFetchNextPage={fetchNextPage}
-          onNewChat={handleNewChatClickWrapper}
+          onNewChat={handleNewChatClick}
           onClose={handleCloseDrawer}
           onOpenChange={handleDrawerOpenChange}
           hasActiveSession={Boolean(hasActiveSession)}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/LoadingState/LoadingState.tsx

@@ -1,15 +0,0 @@
-import { Text } from "@/components/atoms/Text/Text";
-import { ChatLoader } from "@/components/contextual/Chat/components/ChatLoader/ChatLoader";
-
-export function LoadingState() {
-  return (
-    <div className="flex flex-1 items-center justify-center">
-      <div className="flex flex-col items-center gap-4">
-        <ChatLoader />
-        <Text variant="body" className="text-zinc-500">
-          Loading your chats...
-        </Text>
-      </div>
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/MobileDrawer/useMobileDrawer.ts

@@ -3,17 +3,17 @@ import { useState } from "react";
 export function useMobileDrawer() {
   const [isDrawerOpen, setIsDrawerOpen] = useState(false);
 
-  function handleOpenDrawer() {
+  const handleOpenDrawer = () => {
     setIsDrawerOpen(true);
-  }
+  };
 
-  function handleCloseDrawer() {
+  const handleCloseDrawer = () => {
     setIsDrawerOpen(false);
-  }
+  };
 
-  function handleDrawerOpenChange(open: boolean) {
+  const handleDrawerOpenChange = (open: boolean) => {
     setIsDrawerOpen(open);
-  }
+  };
 
   return {
     isDrawerOpen,

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/SessionsList/useSessionsPagination.ts

@@ -1,7 +1,7 @@
 import { useGetV2ListSessions } from "@/app/api/__generated__/endpoints/chat/chat";
 import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
 import { okData } from "@/app/api/helpers";
-import { useEffect, useMemo, useState } from "react";
+import { useEffect, useState } from "react";
 
 const PAGE_SIZE = 50;
 
@@ -11,9 +11,11 @@ export interface UseSessionsPaginationArgs {
 
 export function useSessionsPagination({ enabled }: UseSessionsPaginationArgs) {
   const [offset, setOffset] = useState(0);
+
   const [accumulatedSessions, setAccumulatedSessions] = useState<
     SessionSummaryResponse[]
   >([]);
+
   const [totalCount, setTotalCount] = useState<number | null>(null);
 
   const { data, isLoading, isFetching, isError } = useGetV2ListSessions(
@@ -43,17 +45,14 @@ export function useSessionsPagination({ enabled }: UseSessionsPaginationArgs) {
     }
   }, [data, offset, enabled]);
 
-  const hasNextPage = useMemo(() => {
-    if (totalCount === null) return false;
-    return accumulatedSessions.length < totalCount;
-  }, [accumulatedSessions.length, totalCount]);
+  const hasNextPage =
+    totalCount !== null && accumulatedSessions.length < totalCount;
 
-  const areAllSessionsLoaded = useMemo(() => {
-    if (totalCount === null) return false;
-    return (
-      accumulatedSessions.length >= totalCount && !isFetching && !isLoading
-    );
-  }, [accumulatedSessions.length, totalCount, isFetching, isLoading]);
+  const areAllSessionsLoaded =
+    totalCount !== null &&
+    accumulatedSessions.length >= totalCount &&
+    !isFetching &&
+    !isLoading;
 
   useEffect(() => {
     if (
@@ -67,17 +66,17 @@ export function useSessionsPagination({ enabled }: UseSessionsPaginationArgs) {
     }
   }, [hasNextPage, isFetching, isLoading, isError, totalCount]);
 
-  function fetchNextPage() {
+  const fetchNextPage = () => {
     if (hasNextPage && !isFetching) {
       setOffset((prev) => prev + PAGE_SIZE);
     }
-  }
+  };
 
-  function reset() {
+  const reset = () => {
     setOffset(0);
     setAccumulatedSessions([]);
     setTotalCount(null);
-  }
+  };
 
   return {
     sessions: accumulatedSessions,

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/helpers.ts

@@ -2,9 +2,7 @@ import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessi
 import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
 import { format, formatDistanceToNow, isToday } from "date-fns";
 
-export function convertSessionDetailToSummary(
-  session: SessionDetailResponse,
-): SessionSummaryResponse {
+export function convertSessionDetailToSummary(session: SessionDetailResponse) {
   return {
     id: session.id,
     created_at: session.created_at,
@@ -13,17 +11,25 @@ export function convertSessionDetailToSummary(
   };
 }
 
-export function filterVisibleSessions(
-  sessions: SessionSummaryResponse[],
-): SessionSummaryResponse[] {
-  return sessions.filter(
-    (session) => session.updated_at !== session.created_at,
-  );
+export function filterVisibleSessions(sessions: SessionSummaryResponse[]) {
+  const fiveMinutesAgo = Date.now() - 5 * 60 * 1000;
+  return sessions.filter((session) => {
+    const hasBeenUpdated = session.updated_at !== session.created_at;
+
+    if (hasBeenUpdated) return true;
+
+    const isRecentlyCreated =
+      new Date(session.created_at).getTime() > fiveMinutesAgo;
+
+    return isRecentlyCreated;
+  });
 }
 
-export function getSessionTitle(session: SessionSummaryResponse): string {
+export function getSessionTitle(session: SessionSummaryResponse) {
   if (session.title) return session.title;
+
   const isNewSession = session.updated_at === session.created_at;
+
   if (isNewSession) {
     const createdDate = new Date(session.created_at);
     if (isToday(createdDate)) {
@@ -31,12 +37,11 @@ export function getSessionTitle(session: SessionSummaryResponse): string {
     }
     return format(createdDate, "MMM d, yyyy");
   }
+
   return "Untitled Chat";
 }
 
-export function getSessionUpdatedLabel(
-  session: SessionSummaryResponse,
-): string {
+export function getSessionUpdatedLabel(session: SessionSummaryResponse) {
   if (!session.updated_at) return "";
   return formatDistanceToNow(new Date(session.updated_at), { addSuffix: true });
 }
@@ -45,8 +50,10 @@ export function mergeCurrentSessionIntoList(
   accumulatedSessions: SessionSummaryResponse[],
   currentSessionId: string | null,
   currentSessionData: SessionDetailResponse | null | undefined,
-): SessionSummaryResponse[] {
+  recentlyCreatedSessions?: Map<string, SessionSummaryResponse>,
+) {
   const filteredSessions: SessionSummaryResponse[] = [];
+  const addedIds = new Set<string>();
 
   if (accumulatedSessions.length > 0) {
     const visibleSessions = filterVisibleSessions(accumulatedSessions);
@@ -61,105 +68,39 @@ export function mergeCurrentSessionIntoList(
         );
         if (!isInVisible) {
           filteredSessions.push(currentInAll);
+          addedIds.add(currentInAll.id);
         }
       }
     }
 
-    filteredSessions.push(...visibleSessions);
+    for (const session of visibleSessions) {
+      if (!addedIds.has(session.id)) {
+        filteredSessions.push(session);
+        addedIds.add(session.id);
+      }
+    }
   }
 
   if (currentSessionId && currentSessionData) {
-    const isCurrentInList = filteredSessions.some(
-      (s) => s.id === currentSessionId,
-    );
-    if (!isCurrentInList) {
+    if (!addedIds.has(currentSessionId)) {
       const summarySession = convertSessionDetailToSummary(currentSessionData);
       filteredSessions.unshift(summarySession);
+      addedIds.add(currentSessionId);
+    }
+  }
+
+  if (recentlyCreatedSessions) {
+    for (const [sessionId, sessionData] of recentlyCreatedSessions) {
+      if (!addedIds.has(sessionId)) {
+        filteredSessions.unshift(sessionData);
+        addedIds.add(sessionId);
+      }
     }
   }
 
   return filteredSessions;
 }
 
-export function getCurrentSessionId(
-  searchParams: URLSearchParams,
-): string | null {
+export function getCurrentSessionId(searchParams: URLSearchParams) {
   return searchParams.get("sessionId");
 }
-
-export function shouldAutoSelectSession(
-  areAllSessionsLoaded: boolean,
-  hasAutoSelectedSession: boolean,
-  paramSessionId: string | null,
-  visibleSessions: SessionSummaryResponse[],
-  accumulatedSessions: SessionSummaryResponse[],
-  isLoading: boolean,
-  totalCount: number | null,
-): {
-  shouldSelect: boolean;
-  sessionIdToSelect: string | null;
-  shouldCreate: boolean;
-} {
-  if (!areAllSessionsLoaded || hasAutoSelectedSession) {
-    return {
-      shouldSelect: false,
-      sessionIdToSelect: null,
-      shouldCreate: false,
-    };
-  }
-
-  if (paramSessionId) {
-    return {
-      shouldSelect: false,
-      sessionIdToSelect: null,
-      shouldCreate: false,
-    };
-  }
-
-  if (visibleSessions.length > 0) {
-    return {
-      shouldSelect: true,
-      sessionIdToSelect: visibleSessions[0].id,
-      shouldCreate: false,
-    };
-  }
-
-  if (accumulatedSessions.length === 0 && !isLoading && totalCount === 0) {
-    return { shouldSelect: false, sessionIdToSelect: null, shouldCreate: true };
-  }
-
-  if (totalCount === 0) {
-    return {
-      shouldSelect: false,
-      sessionIdToSelect: null,
-      shouldCreate: false,
-    };
-  }
-
-  return { shouldSelect: false, sessionIdToSelect: null, shouldCreate: false };
-}
-
-export function checkReadyToShowContent(
-  areAllSessionsLoaded: boolean,
-  paramSessionId: string | null,
-  accumulatedSessions: SessionSummaryResponse[],
-  isCurrentSessionLoading: boolean,
-  currentSessionData: SessionDetailResponse | null | undefined,
-  hasAutoSelectedSession: boolean,
-): boolean {
-  if (!areAllSessionsLoaded) return false;
-
-  if (paramSessionId) {
-    const sessionFound = accumulatedSessions.some(
-      (s) => s.id === paramSessionId,
-    );
-    return (
-      sessionFound ||
-      (!isCurrentSessionLoading &&
-        currentSessionData !== undefined &&
-        currentSessionData !== null)
-    );
-  }
-
-  return hasAutoSelectedSession;
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/useCopilotShell.ts

@@ -1,26 +1,24 @@
 "use client";
 
 import {
+  getGetV2GetSessionQueryKey,
   getGetV2ListSessionsQueryKey,
   useGetV2GetSession,
 } from "@/app/api/__generated__/endpoints/chat/chat";
 import { okData } from "@/app/api/helpers";
+import { useChatStore } from "@/components/contextual/Chat/chat-store";
 import { useBreakpoint } from "@/lib/hooks/useBreakpoint";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
 import { useQueryClient } from "@tanstack/react-query";
-import { usePathname, useRouter, useSearchParams } from "next/navigation";
-import { useEffect, useRef, useState } from "react";
+import { usePathname, useSearchParams } from "next/navigation";
+import { useRef } from "react";
+import { useCopilotStore } from "../../copilot-page-store";
+import { useCopilotSessionId } from "../../useCopilotSessionId";
 import { useMobileDrawer } from "./components/MobileDrawer/useMobileDrawer";
-import { useSessionsPagination } from "./components/SessionsList/useSessionsPagination";
-import {
-  checkReadyToShowContent,
-  filterVisibleSessions,
-  getCurrentSessionId,
-  mergeCurrentSessionIntoList,
-} from "./helpers";
+import { getCurrentSessionId } from "./helpers";
+import { useShellSessionList } from "./useShellSessionList";
 
 export function useCopilotShell() {
-  const router = useRouter();
   const pathname = usePathname();
   const searchParams = useSearchParams();
   const queryClient = useQueryClient();
@@ -29,6 +27,8 @@ export function useCopilotShell() {
   const isMobile =
     breakpoint === "base" || breakpoint === "sm" || breakpoint === "md";
 
+  const { urlSessionId, setUrlSessionId } = useCopilotSessionId();
+
   const isOnHomepage = pathname === "/copilot";
   const paramSessionId = searchParams.get("sessionId");
 
@@ -41,114 +41,113 @@ export function useCopilotShell() {
 
   const paginationEnabled = !isMobile || isDrawerOpen || !!paramSessionId;
 
-  const {
-    sessions: accumulatedSessions,
-    isLoading: isSessionsLoading,
-    isFetching: isSessionsFetching,
-    hasNextPage,
-    areAllSessionsLoaded,
-    fetchNextPage,
-    reset: resetPagination,
-  } = useSessionsPagination({
-    enabled: paginationEnabled,
-  });
-
   const currentSessionId = getCurrentSessionId(searchParams);
 
-  const { data: currentSessionData, isLoading: isCurrentSessionLoading } =
-    useGetV2GetSession(currentSessionId || "", {
+  const { data: currentSessionData } = useGetV2GetSession(
+    currentSessionId || "",
+    {
       query: {
         enabled: !!currentSessionId,
         select: okData,
       },
-    });
-
-  const [hasAutoSelectedSession, setHasAutoSelectedSession] = useState(false);
-  const hasAutoSelectedRef = useRef(false);
-
-  // Mark as auto-selected when sessionId is in URL
-  useEffect(() => {
-    if (paramSessionId && !hasAutoSelectedRef.current) {
-      hasAutoSelectedRef.current = true;
-      setHasAutoSelectedSession(true);
-    }
-  }, [paramSessionId]);
-
-  // On homepage without sessionId, mark as ready immediately
-  useEffect(() => {
-    if (isOnHomepage && !paramSessionId && !hasAutoSelectedRef.current) {
-      hasAutoSelectedRef.current = true;
-      setHasAutoSelectedSession(true);
-    }
-  }, [isOnHomepage, paramSessionId]);
-
-  // Invalidate sessions list when navigating to homepage (to show newly created sessions)
-  useEffect(() => {
-    if (isOnHomepage && !paramSessionId) {
-      queryClient.invalidateQueries({
-        queryKey: getGetV2ListSessionsQueryKey(),
-      });
-    }
-  }, [isOnHomepage, paramSessionId, queryClient]);
-
-  // Reset pagination when query becomes disabled
-  const prevPaginationEnabledRef = useRef(paginationEnabled);
-  useEffect(() => {
-    if (prevPaginationEnabledRef.current && !paginationEnabled) {
-      resetPagination();
-      resetAutoSelect();
-    }
-    prevPaginationEnabledRef.current = paginationEnabled;
-  }, [paginationEnabled, resetPagination]);
-
-  const sessions = mergeCurrentSessionIntoList(
-    accumulatedSessions,
-    currentSessionId,
-    currentSessionData,
+    },
   );
 
-  const visibleSessions = filterVisibleSessions(sessions);
+  const {
+    sessions,
+    isLoading,
+    isSessionsFetching,
+    hasNextPage,
+    fetchNextPage,
+    resetPagination,
+    recentlyCreatedSessionsRef,
+  } = useShellSessionList({
+    paginationEnabled,
+    currentSessionId,
+    currentSessionData,
+    isOnHomepage,
+    paramSessionId,
+  });
 
-  const sidebarSelectedSessionId =
-    isOnHomepage && !paramSessionId ? null : currentSessionId;
+  const stopStream = useChatStore((s) => s.stopStream);
+  const onStreamComplete = useChatStore((s) => s.onStreamComplete);
+  const isStreaming = useCopilotStore((s) => s.isStreaming);
+  const isCreatingSession = useCopilotStore((s) => s.isCreatingSession);
+  const setIsSwitchingSession = useCopilotStore((s) => s.setIsSwitchingSession);
+  const openInterruptModal = useCopilotStore((s) => s.openInterruptModal);
 
-  const isReadyToShowContent = isOnHomepage
-    ? true
-    : checkReadyToShowContent(
-        areAllSessionsLoaded,
-        paramSessionId,
-        accumulatedSessions,
-        isCurrentSessionLoading,
-        currentSessionData,
-        hasAutoSelectedSession,
-      );
+  const pendingActionRef = useRef<(() => void) | null>(null);
 
-  function handleSelectSession(sessionId: string) {
-    // Navigate using replaceState to avoid full page reload
-    window.history.replaceState(null, "", `/copilot?sessionId=${sessionId}`);
-    // Force a re-render by updating the URL through router
-    router.replace(`/copilot?sessionId=${sessionId}`);
+  async function stopCurrentStream() {
+    if (!currentSessionId) return;
+
+    setIsSwitchingSession(true);
+    await new Promise<void>((resolve) => {
+      const unsubscribe = onStreamComplete((completedId) => {
+        if (completedId === currentSessionId) {
+          clearTimeout(timeout);
+          unsubscribe();
+          resolve();
+        }
+      });
+      const timeout = setTimeout(() => {
+        unsubscribe();
+        resolve();
+      }, 3000);
+      stopStream(currentSessionId);
+    });
+
+    queryClient.invalidateQueries({
+      queryKey: getGetV2GetSessionQueryKey(currentSessionId),
+    });
+    setIsSwitchingSession(false);
+  }
+
+  function selectSession(sessionId: string) {
+    if (sessionId === currentSessionId) return;
+    if (recentlyCreatedSessionsRef.current.has(sessionId)) {
+      queryClient.invalidateQueries({
+        queryKey: getGetV2GetSessionQueryKey(sessionId),
+      });
+    }
+    setUrlSessionId(sessionId, { shallow: false });
     if (isMobile) handleCloseDrawer();
   }
 
-  function handleNewChat() {
-    resetAutoSelect();
+  function startNewChat() {
     resetPagination();
-    // Invalidate and refetch sessions list to ensure newly created sessions appear
     queryClient.invalidateQueries({
       queryKey: getGetV2ListSessionsQueryKey(),
     });
-    window.history.replaceState(null, "", "/copilot");
-    router.replace("/copilot");
+    setUrlSessionId(null, { shallow: false });
     if (isMobile) handleCloseDrawer();
   }
 
-  function resetAutoSelect() {
-    hasAutoSelectedRef.current = false;
-    setHasAutoSelectedSession(false);
+  function handleSessionClick(sessionId: string) {
+    if (sessionId === currentSessionId) return;
+
+    if (isStreaming) {
+      pendingActionRef.current = async () => {
+        await stopCurrentStream();
+        selectSession(sessionId);
+      };
+      openInterruptModal(pendingActionRef.current);
+    } else {
+      selectSession(sessionId);
+    }
   }
 
-  const isLoading = isSessionsLoading && accumulatedSessions.length === 0;
+  function handleNewChatClick() {
+    if (isStreaming) {
+      pendingActionRef.current = async () => {
+        await stopCurrentStream();
+        startNewChat();
+      };
+      openInterruptModal(pendingActionRef.current);
+    } else {
+      startNewChat();
+    }
+  }
 
   return {
     isMobile,
@@ -156,17 +155,17 @@ export function useCopilotShell() {
     isLoggedIn,
     hasActiveSession:
       Boolean(currentSessionId) && (!isOnHomepage || Boolean(paramSessionId)),
-    isLoading,
-    sessions: visibleSessions,
-    currentSessionId: sidebarSelectedSessionId,
-    handleSelectSession,
+    isLoading: isLoading || isCreatingSession,
+    isCreatingSession,
+    sessions,
+    currentSessionId: urlSessionId,
     handleOpenDrawer,
     handleCloseDrawer,
     handleDrawerOpenChange,
-    handleNewChat,
+    handleNewChatClick,
+    handleSessionClick,
     hasNextPage,
     isFetchingNextPage: isSessionsFetching,
     fetchNextPage,
-    isReadyToShowContent,
   };
 }

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/useShellSessionList.ts

@@ -0,0 +1,113 @@
+import { getGetV2ListSessionsQueryKey } from "@/app/api/__generated__/endpoints/chat/chat";
+import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
+import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
+import { useChatStore } from "@/components/contextual/Chat/chat-store";
+import { useQueryClient } from "@tanstack/react-query";
+import { useEffect, useMemo, useRef } from "react";
+import { useSessionsPagination } from "./components/SessionsList/useSessionsPagination";
+import {
+  convertSessionDetailToSummary,
+  filterVisibleSessions,
+  mergeCurrentSessionIntoList,
+} from "./helpers";
+
+interface UseShellSessionListArgs {
+  paginationEnabled: boolean;
+  currentSessionId: string | null;
+  currentSessionData: SessionDetailResponse | null | undefined;
+  isOnHomepage: boolean;
+  paramSessionId: string | null;
+}
+
+export function useShellSessionList({
+  paginationEnabled,
+  currentSessionId,
+  currentSessionData,
+  isOnHomepage,
+  paramSessionId,
+}: UseShellSessionListArgs) {
+  const queryClient = useQueryClient();
+  const onStreamComplete = useChatStore((s) => s.onStreamComplete);
+
+  const {
+    sessions: accumulatedSessions,
+    isLoading: isSessionsLoading,
+    isFetching: isSessionsFetching,
+    hasNextPage,
+    fetchNextPage,
+    reset: resetPagination,
+  } = useSessionsPagination({
+    enabled: paginationEnabled,
+  });
+
+  const recentlyCreatedSessionsRef = useRef<
+    Map<string, SessionSummaryResponse>
+  >(new Map());
+
+  useEffect(() => {
+    if (isOnHomepage && !paramSessionId) {
+      queryClient.invalidateQueries({
+        queryKey: getGetV2ListSessionsQueryKey(),
+      });
+    }
+  }, [isOnHomepage, paramSessionId, queryClient]);
+
+  useEffect(() => {
+    if (currentSessionId && currentSessionData) {
+      const isNewSession =
+        currentSessionData.updated_at === currentSessionData.created_at;
+      const isNotInAccumulated = !accumulatedSessions.some(
+        (s) => s.id === currentSessionId,
+      );
+      if (isNewSession || isNotInAccumulated) {
+        const summary = convertSessionDetailToSummary(currentSessionData);
+        recentlyCreatedSessionsRef.current.set(currentSessionId, summary);
+      }
+    }
+  }, [currentSessionId, currentSessionData, accumulatedSessions]);
+
+  useEffect(() => {
+    for (const sessionId of recentlyCreatedSessionsRef.current.keys()) {
+      if (accumulatedSessions.some((s) => s.id === sessionId)) {
+        recentlyCreatedSessionsRef.current.delete(sessionId);
+      }
+    }
+  }, [accumulatedSessions]);
+
+  useEffect(() => {
+    const unsubscribe = onStreamComplete(() => {
+      queryClient.invalidateQueries({
+        queryKey: getGetV2ListSessionsQueryKey(),
+      });
+    });
+    return unsubscribe;
+  }, [onStreamComplete, queryClient]);
+
+  const sessions = useMemo(
+    () =>
+      mergeCurrentSessionIntoList(
+        accumulatedSessions,
+        currentSessionId,
+        currentSessionData,
+        recentlyCreatedSessionsRef.current,
+      ),
+    [accumulatedSessions, currentSessionId, currentSessionData],
+  );
+
+  const visibleSessions = useMemo(
+    () => filterVisibleSessions(sessions),
+    [sessions],
+  );
+
+  const isLoading = isSessionsLoading && accumulatedSessions.length === 0;
+
+  return {
+    sessions: visibleSessions,
+    isLoading,
+    isSessionsFetching,
+    hasNextPage,
+    fetchNextPage,
+    resetPagination,
+    recentlyCreatedSessionsRef,
+  };
+}

autogpt_platform/frontend/src/app/(platform)/copilot/copilot-page-store.ts

@@ -0,0 +1,56 @@
+"use client";
+
+import { create } from "zustand";
+
+interface CopilotStoreState {
+  isStreaming: boolean;
+  isSwitchingSession: boolean;
+  isCreatingSession: boolean;
+  isInterruptModalOpen: boolean;
+  pendingAction: (() => void) | null;
+}
+
+interface CopilotStoreActions {
+  setIsStreaming: (isStreaming: boolean) => void;
+  setIsSwitchingSession: (isSwitchingSession: boolean) => void;
+  setIsCreatingSession: (isCreating: boolean) => void;
+  openInterruptModal: (onConfirm: () => void) => void;
+  confirmInterrupt: () => void;
+  cancelInterrupt: () => void;
+}
+
+type CopilotStore = CopilotStoreState & CopilotStoreActions;
+
+export const useCopilotStore = create<CopilotStore>((set, get) => ({
+  isStreaming: false,
+  isSwitchingSession: false,
+  isCreatingSession: false,
+  isInterruptModalOpen: false,
+  pendingAction: null,
+
+  setIsStreaming(isStreaming) {
+    set({ isStreaming });
+  },
+
+  setIsSwitchingSession(isSwitchingSession) {
+    set({ isSwitchingSession });
+  },
+
+  setIsCreatingSession(isCreatingSession) {
+    set({ isCreatingSession });
+  },
+
+  openInterruptModal(onConfirm) {
+    set({ isInterruptModalOpen: true, pendingAction: onConfirm });
+  },
+
+  confirmInterrupt() {
+    const { pendingAction } = get();
+    set({ isInterruptModalOpen: false, pendingAction: null });
+    if (pendingAction) pendingAction();
+  },
+
+  cancelInterrupt() {
+    set({ isInterruptModalOpen: false, pendingAction: null });
+  },
+}));

autogpt_platform/frontend/src/app/(platform)/copilot/helpers.ts

@@ -1,28 +1,5 @@
 import type { User } from "@supabase/supabase-js";
 
-export type PageState =
-  | { type: "welcome" }
-  | { type: "newChat" }
-  | { type: "creating"; prompt: string }
-  | { type: "chat"; sessionId: string; initialPrompt?: string };
-
-export function getInitialPromptFromState(
-  pageState: PageState,
-  storedInitialPrompt: string | undefined,
-) {
-  if (storedInitialPrompt) return storedInitialPrompt;
-  if (pageState.type === "creating") return pageState.prompt;
-  if (pageState.type === "chat") return pageState.initialPrompt;
-}
-
-export function shouldResetToWelcome(pageState: PageState) {
-  return (
-    pageState.type !== "newChat" &&
-    pageState.type !== "creating" &&
-    pageState.type !== "welcome"
-  );
-}
-
 export function getGreetingName(user?: User | null): string {
   if (!user) return "there";
   const metadata = user.user_metadata as Record<string, unknown> | undefined;

autogpt_platform/frontend/src/app/(platform)/copilot/layout.tsx

@@ -1,11 +1,6 @@
 import type { ReactNode } from "react";
-import { NewChatProvider } from "./NewChatContext";
 import { CopilotShell } from "./components/CopilotShell/CopilotShell";
 
 export default function CopilotLayout({ children }: { children: ReactNode }) {
-  return (
-    <NewChatProvider>
-      <CopilotShell>{children}</CopilotShell>
-    </NewChatProvider>
-  );
+  return <CopilotShell>{children}</CopilotShell>;
 }

autogpt_platform/frontend/src/app/(platform)/copilot/page.tsx

@@ -1,22 +1,25 @@
 "use client";
 
-import { Skeleton } from "@/components/__legacy__/ui/skeleton";
 import { Button } from "@/components/atoms/Button/Button";
+import { Skeleton } from "@/components/atoms/Skeleton/Skeleton";
 import { Text } from "@/components/atoms/Text/Text";
 import { Chat } from "@/components/contextual/Chat/Chat";
 import { ChatInput } from "@/components/contextual/Chat/components/ChatInput/ChatInput";
-import { ChatLoader } from "@/components/contextual/Chat/components/ChatLoader/ChatLoader";
 import { Dialog } from "@/components/molecules/Dialog/Dialog";
+import { useCopilotStore } from "./copilot-page-store";
 import { useCopilotPage } from "./useCopilotPage";
 
 export default function CopilotPage() {
   const { state, handlers } = useCopilotPage();
+  const isInterruptModalOpen = useCopilotStore((s) => s.isInterruptModalOpen);
+  const confirmInterrupt = useCopilotStore((s) => s.confirmInterrupt);
+  const cancelInterrupt = useCopilotStore((s) => s.cancelInterrupt);
   const {
     greetingName,
     quickActions,
     isLoading,
-    pageState,
-    isNewChatModalOpen,
+    hasSession,
+    initialPrompt,
     isReady,
   } = state;
   const {
@@ -24,24 +27,16 @@ export default function CopilotPage() {
     startChatWithPrompt,
     handleSessionNotFound,
     handleStreamingChange,
-    handleCancelNewChat,
-    proceedWithNewChat,
-    handleNewChatModalOpen,
   } = handlers;
 
-  if (!isReady) {
-    return null;
-  }
+  if (!isReady) return null;
 
-  // Show Chat when we have an active session
-  if (pageState.type === "chat") {
+  if (hasSession) {
     return (
       <div className="flex h-full flex-col">
         <Chat
-          key={pageState.sessionId ?? "welcome"}
           className="flex-1"
-          urlSessionId={pageState.sessionId}
-          initialPrompt={pageState.initialPrompt}
+          initialPrompt={initialPrompt}
           onSessionNotFound={handleSessionNotFound}
           onStreamingChange={handleStreamingChange}
         />
@@ -49,31 +44,33 @@ export default function CopilotPage() {
           title="Interrupt current chat?"
           styling={{ maxWidth: 300, width: "100%" }}
           controlled={{
-            isOpen: isNewChatModalOpen,
-            set: handleNewChatModalOpen,
+            isOpen: isInterruptModalOpen,
+            set: (open) => {
+              if (!open) cancelInterrupt();
+            },
           }}
-          onClose={handleCancelNewChat}
+          onClose={cancelInterrupt}
         >
           <Dialog.Content>
             <div className="flex flex-col gap-4">
               <Text variant="body">
                 The current chat response will be interrupted. Are you sure you
-                want to start a new chat?
+                want to continue?
               </Text>
               <Dialog.Footer>
                 <Button
                   type="button"
                   variant="outline"
-                  onClick={handleCancelNewChat}
+                  onClick={cancelInterrupt}
                 >
                   Cancel
                 </Button>
                 <Button
                   type="button"
                   variant="primary"
-                  onClick={proceedWithNewChat}
+                  onClick={confirmInterrupt}
                 >
-                  Start new chat
+                  Continue
                 </Button>
               </Dialog.Footer>
             </div>
@@ -83,34 +80,6 @@ export default function CopilotPage() {
     );
   }
 
-  if (pageState.type === "newChat") {
-    return (
-      <div className="flex h-full flex-1 flex-col items-center justify-center bg-[#f8f8f9]">
-        <div className="flex flex-col items-center gap-4">
-          <ChatLoader />
-          <Text variant="body" className="text-zinc-500">
-            Loading your chats...
-          </Text>
-        </div>
-      </div>
-    );
-  }
-
-  // Show loading state while creating session and sending first message
-  if (pageState.type === "creating") {
-    return (
-      <div className="flex h-full flex-1 flex-col items-center justify-center bg-[#f8f8f9]">
-        <div className="flex flex-col items-center gap-4">
-          <ChatLoader />
-          <Text variant="body" className="text-zinc-500">
-            Loading your chats...
-          </Text>
-        </div>
-      </div>
-    );
-  }
-
-  // Show Welcome screen
   return (
     <div className="flex h-full flex-1 items-center justify-center overflow-y-auto bg-[#f8f8f9] px-6 py-10">
       <div className="w-full text-center">

autogpt_platform/frontend/src/app/(platform)/copilot/useCopilotPage.ts

@@ -1,4 +1,7 @@
-import { postV2CreateSession } from "@/app/api/__generated__/endpoints/chat/chat";
+import {
+  getGetV2ListSessionsQueryKey,
+  postV2CreateSession,
+} from "@/app/api/__generated__/endpoints/chat/chat";
 import { useToast } from "@/components/molecules/Toast/use-toast";
 import { getHomepageRoute } from "@/lib/constants";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
@@ -7,81 +10,27 @@ import {
   type FlagValues,
   useGetFlag,
 } from "@/services/feature-flags/use-get-flag";
+import { SessionKey, sessionStorage } from "@/services/storage/session-storage";
 import * as Sentry from "@sentry/nextjs";
+import { useQueryClient } from "@tanstack/react-query";
 import { useFlags } from "launchdarkly-react-client-sdk";
 import { useRouter } from "next/navigation";
-import { useEffect, useReducer } from "react";
-import { useNewChat } from "./NewChatContext";
-import { getGreetingName, getQuickActions, type PageState } from "./helpers";
-import { useCopilotURLState } from "./useCopilotURLState";
-
-type CopilotState = {
-  pageState: PageState;
-  isStreaming: boolean;
-  isNewChatModalOpen: boolean;
-  initialPrompts: Record<string, string>;
-  previousSessionId: string | null;
-};
-
-type CopilotAction =
-  | { type: "setPageState"; pageState: PageState }
-  | { type: "setStreaming"; isStreaming: boolean }
-  | { type: "setNewChatModalOpen"; isOpen: boolean }
-  | { type: "setInitialPrompt"; sessionId: string; prompt: string }
-  | { type: "setPreviousSessionId"; sessionId: string | null };
-
-function isSamePageState(next: PageState, current: PageState) {
-  if (next.type !== current.type) return false;
-  if (next.type === "creating" && current.type === "creating") {
-    return next.prompt === current.prompt;
-  }
-  if (next.type === "chat" && current.type === "chat") {
-    return (
-      next.sessionId === current.sessionId &&
-      next.initialPrompt === current.initialPrompt
-    );
-  }
-  return true;
-}
-
-function copilotReducer(
-  state: CopilotState,
-  action: CopilotAction,
-): CopilotState {
-  if (action.type === "setPageState") {
-    if (isSamePageState(action.pageState, state.pageState)) return state;
-    return { ...state, pageState: action.pageState };
-  }
-  if (action.type === "setStreaming") {
-    if (action.isStreaming === state.isStreaming) return state;
-    return { ...state, isStreaming: action.isStreaming };
-  }
-  if (action.type === "setNewChatModalOpen") {
-    if (action.isOpen === state.isNewChatModalOpen) return state;
-    return { ...state, isNewChatModalOpen: action.isOpen };
-  }
-  if (action.type === "setInitialPrompt") {
-    if (state.initialPrompts[action.sessionId] === action.prompt) return state;
-    return {
-      ...state,
-      initialPrompts: {
-        ...state.initialPrompts,
-        [action.sessionId]: action.prompt,
-      },
-    };
-  }
-  if (action.type === "setPreviousSessionId") {
-    if (state.previousSessionId === action.sessionId) return state;
-    return { ...state, previousSessionId: action.sessionId };
-  }
-  return state;
-}
+import { useEffect } from "react";
+import { useCopilotStore } from "./copilot-page-store";
+import { getGreetingName, getQuickActions } from "./helpers";
+import { useCopilotSessionId } from "./useCopilotSessionId";
 
 export function useCopilotPage() {
   const router = useRouter();
+  const queryClient = useQueryClient();
   const { user, isLoggedIn, isUserLoading } = useSupabase();
   const { toast } = useToast();
 
+  const { urlSessionId, setUrlSessionId } = useCopilotSessionId();
+  const setIsStreaming = useCopilotStore((s) => s.setIsStreaming);
+  const isCreating = useCopilotStore((s) => s.isCreatingSession);
+  const setIsCreating = useCopilotStore((s) => s.setIsCreatingSession);
+
   const isChatEnabled = useGetFlag(Flag.CHAT);
   const flags = useFlags<FlagValues>();
   const homepageRoute = getHomepageRoute(isChatEnabled);
@@ -91,86 +40,27 @@ export function useCopilotPage() {
   const isFlagReady =
     !isLaunchDarklyConfigured || flags[Flag.CHAT] !== undefined;
 
-  const [state, dispatch] = useReducer(copilotReducer, {
-    pageState: { type: "welcome" },
-    isStreaming: false,
-    isNewChatModalOpen: false,
-    initialPrompts: {},
-    previousSessionId: null,
-  });
-
-  const newChatContext = useNewChat();
   const greetingName = getGreetingName(user);
   const quickActions = getQuickActions();
 
-  function setPageState(pageState: PageState) {
-    dispatch({ type: "setPageState", pageState });
-  }
+  const hasSession = Boolean(urlSessionId);
+  const initialPrompt = urlSessionId
+    ? getInitialPrompt(urlSessionId)
+    : undefined;
 
-  function setInitialPrompt(sessionId: string, prompt: string) {
-    dispatch({ type: "setInitialPrompt", sessionId, prompt });
-  }
-
-  function setPreviousSessionId(sessionId: string | null) {
-    dispatch({ type: "setPreviousSessionId", sessionId });
-  }
-
-  const { setUrlSessionId } = useCopilotURLState({
-    pageState: state.pageState,
-    initialPrompts: state.initialPrompts,
-    previousSessionId: state.previousSessionId,
-    setPageState,
-    setInitialPrompt,
-    setPreviousSessionId,
-  });
-
-  useEffect(
-    function registerNewChatHandler() {
-      if (!newChatContext) return;
-      newChatContext.setOnNewChatClick(handleNewChatClick);
-      return function cleanup() {
-        newChatContext.setOnNewChatClick(undefined);
-      };
-    },
-    [newChatContext, handleNewChatClick],
-  );
-
-  useEffect(
-    function transitionNewChatToWelcome() {
-      if (state.pageState.type === "newChat") {
-        function setWelcomeState() {
-          dispatch({ type: "setPageState", pageState: { type: "welcome" } });
-        }
-
-        const timer = setTimeout(setWelcomeState, 300);
-
-        return function cleanup() {
-          clearTimeout(timer);
-        };
-      }
-    },
-    [state.pageState.type],
-  );
-
-  useEffect(
-    function ensureAccess() {
-      if (!isFlagReady) return;
-      if (isChatEnabled === false) {
-        router.replace(homepageRoute);
-      }
-    },
-    [homepageRoute, isChatEnabled, isFlagReady, router],
-  );
+  useEffect(() => {
+    if (!isFlagReady) return;
+    if (isChatEnabled === false) {
+      router.replace(homepageRoute);
+    }
+  }, [homepageRoute, isChatEnabled, isFlagReady, router]);
 
   async function startChatWithPrompt(prompt: string) {
     if (!prompt?.trim()) return;
-    if (state.pageState.type === "creating") return;
+    if (isCreating) return;
 
     const trimmedPrompt = prompt.trim();
-    dispatch({
-      type: "setPageState",
-      pageState: { type: "creating", prompt: trimmedPrompt },
-    });
+    setIsCreating(true);
 
     try {
       const sessionResponse = await postV2CreateSession({
@@ -182,23 +72,19 @@ export function useCopilotPage() {
       }
 
       const sessionId = sessionResponse.data.id;
+      setInitialPrompt(sessionId, trimmedPrompt);
 
-      dispatch({
-        type: "setInitialPrompt",
-        sessionId,
-        prompt: trimmedPrompt,
+      await queryClient.invalidateQueries({
+        queryKey: getGetV2ListSessionsQueryKey(),
       });
 
-      await setUrlSessionId(sessionId, { shallow: false });
-      dispatch({
-        type: "setPageState",
-        pageState: { type: "chat", sessionId, initialPrompt: trimmedPrompt },
-      });
+      await setUrlSessionId(sessionId, { shallow: true });
     } catch (error) {
       console.error("[CopilotPage] Failed to start chat:", error);
       toast({ title: "Failed to start chat", variant: "destructive" });
       Sentry.captureException(error);
-      dispatch({ type: "setPageState", pageState: { type: "welcome" } });
+    } finally {
+      setIsCreating(false);
     }
   }
 
@@ -211,37 +97,7 @@ export function useCopilotPage() {
   }
 
   function handleStreamingChange(isStreamingValue: boolean) {
-    dispatch({ type: "setStreaming", isStreaming: isStreamingValue });
-  }
-
-  async function proceedWithNewChat() {
-    dispatch({ type: "setNewChatModalOpen", isOpen: false });
-    if (newChatContext?.performNewChat) {
-      newChatContext.performNewChat();
-      return;
-    }
-    try {
-      await setUrlSessionId(null, { shallow: false });
-    } catch (error) {
-      console.error("[CopilotPage] Failed to clear session:", error);
-    }
-    router.replace("/copilot");
-  }
-
-  function handleCancelNewChat() {
-    dispatch({ type: "setNewChatModalOpen", isOpen: false });
-  }
-
-  function handleNewChatModalOpen(isOpen: boolean) {
-    dispatch({ type: "setNewChatModalOpen", isOpen });
-  }
-
-  function handleNewChatClick() {
-    if (state.isStreaming) {
-      dispatch({ type: "setNewChatModalOpen", isOpen: true });
-    } else {
-      proceedWithNewChat();
-    }
+    setIsStreaming(isStreamingValue);
   }
 
   return {
@@ -249,8 +105,8 @@ export function useCopilotPage() {
       greetingName,
       quickActions,
       isLoading: isUserLoading,
-      pageState: state.pageState,
-      isNewChatModalOpen: state.isNewChatModalOpen,
+      hasSession,
+      initialPrompt,
       isReady: isFlagReady && isChatEnabled !== false && isLoggedIn,
     },
     handlers: {
@@ -258,9 +114,32 @@ export function useCopilotPage() {
       startChatWithPrompt,
       handleSessionNotFound,
       handleStreamingChange,
-      handleCancelNewChat,
-      proceedWithNewChat,
-      handleNewChatModalOpen,
     },
   };
 }
+
+function getInitialPrompt(sessionId: string): string | undefined {
+  try {
+    const prompts = JSON.parse(
+      sessionStorage.get(SessionKey.CHAT_INITIAL_PROMPTS) || "{}",
+    );
+    return prompts[sessionId];
+  } catch {
+    return undefined;
+  }
+}
+
+function setInitialPrompt(sessionId: string, prompt: string): void {
+  try {
+    const prompts = JSON.parse(
+      sessionStorage.get(SessionKey.CHAT_INITIAL_PROMPTS) || "{}",
+    );
+    prompts[sessionId] = prompt;
+    sessionStorage.set(
+      SessionKey.CHAT_INITIAL_PROMPTS,
+      JSON.stringify(prompts),
+    );
+  } catch {
+    // Ignore storage errors
+  }
+}

autogpt_platform/frontend/src/app/(platform)/copilot/useCopilotSessionId.ts

@@ -0,0 +1,10 @@
+import { parseAsString, useQueryState } from "nuqs";
+
+export function useCopilotSessionId() {
+  const [urlSessionId, setUrlSessionId] = useQueryState(
+    "sessionId",
+    parseAsString,
+  );
+
+  return { urlSessionId, setUrlSessionId };
+}

autogpt_platform/frontend/src/app/(platform)/copilot/useCopilotURLState.ts

@@ -1,80 +0,0 @@
-import { parseAsString, useQueryState } from "nuqs";
-import { useLayoutEffect } from "react";
-import {
-  getInitialPromptFromState,
-  type PageState,
-  shouldResetToWelcome,
-} from "./helpers";
-
-interface UseCopilotUrlStateArgs {
-  pageState: PageState;
-  initialPrompts: Record<string, string>;
-  previousSessionId: string | null;
-  setPageState: (pageState: PageState) => void;
-  setInitialPrompt: (sessionId: string, prompt: string) => void;
-  setPreviousSessionId: (sessionId: string | null) => void;
-}
-
-export function useCopilotURLState({
-  pageState,
-  initialPrompts,
-  previousSessionId,
-  setPageState,
-  setInitialPrompt,
-  setPreviousSessionId,
-}: UseCopilotUrlStateArgs) {
-  const [urlSessionId, setUrlSessionId] = useQueryState(
-    "sessionId",
-    parseAsString,
-  );
-
-  function syncSessionFromUrl() {
-    if (urlSessionId) {
-      if (pageState.type === "chat" && pageState.sessionId === urlSessionId) {
-        setPreviousSessionId(urlSessionId);
-        return;
-      }
-
-      const storedInitialPrompt = initialPrompts[urlSessionId];
-      const currentInitialPrompt = getInitialPromptFromState(
-        pageState,
-        storedInitialPrompt,
-      );
-
-      if (currentInitialPrompt) {
-        setInitialPrompt(urlSessionId, currentInitialPrompt);
-      }
-
-      setPageState({
-        type: "chat",
-        sessionId: urlSessionId,
-        initialPrompt: currentInitialPrompt,
-      });
-      setPreviousSessionId(urlSessionId);
-      return;
-    }
-
-    const wasInChat = previousSessionId !== null && pageState.type === "chat";
-    setPreviousSessionId(null);
-    if (wasInChat) {
-      setPageState({ type: "newChat" });
-      return;
-    }
-
-    if (shouldResetToWelcome(pageState)) {
-      setPageState({ type: "welcome" });
-    }
-  }
-
-  useLayoutEffect(syncSessionFromUrl, [
-    urlSessionId,
-    pageState.type,
-    previousSessionId,
-    initialPrompts,
-  ]);
-
-  return {
-    urlSessionId,
-    setUrlSessionId,
-  };
-}

autogpt_platform/frontend/src/app/(platform)/layout.tsx

@@ -1,10 +1,12 @@
 import { Navbar } from "@/components/layout/Navbar/Navbar";
+import { NetworkStatusMonitor } from "@/services/network-status/NetworkStatusMonitor";
 import { ReactNode } from "react";
 import { AdminImpersonationBanner } from "./admin/components/AdminImpersonationBanner";
 
 export default function PlatformLayout({ children }: { children: ReactNode }) {
   return (
     <main className="flex h-screen w-full flex-col">
+      <NetworkStatusMonitor />
       <Navbar />
       <AdminImpersonationBanner />
       <section className="flex-1">{children}</section>

autogpt_platform/frontend/src/components/atoms/Skeleton/Skeleton.tsx

@@ -0,0 +1,14 @@
+import { cn } from "@/lib/utils";
+
+interface Props extends React.HTMLAttributes<HTMLDivElement> {
+  className?: string;
+}
+
+export function Skeleton({ className, ...props }: Props) {
+  return (
+    <div
+      className={cn("animate-pulse rounded-md bg-zinc-100", className)}
+      {...props}
+    />
+  );
+}

autogpt_platform/frontend/src/components/atoms/Skeleton/skeleton.stories.tsx

@@ -1,4 +1,4 @@
-import { Skeleton } from "@/components/__legacy__/ui/skeleton";
+import { Skeleton } from "./Skeleton";
 import type { Meta, StoryObj } from "@storybook/nextjs";
 
 const meta: Meta<typeof Skeleton> = {

autogpt_platform/frontend/src/components/contextual/Chat/Chat.tsx

@@ -1,16 +1,17 @@
 "use client";
 
+import { useCopilotSessionId } from "@/app/(platform)/copilot/useCopilotSessionId";
+import { useCopilotStore } from "@/app/(platform)/copilot/copilot-page-store";
+import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
 import { Text } from "@/components/atoms/Text/Text";
 import { cn } from "@/lib/utils";
 import { useEffect, useRef } from "react";
 import { ChatContainer } from "./components/ChatContainer/ChatContainer";
 import { ChatErrorState } from "./components/ChatErrorState/ChatErrorState";
-import { ChatLoader } from "./components/ChatLoader/ChatLoader";
 import { useChat } from "./useChat";
 
 export interface ChatProps {
   className?: string;
-  urlSessionId?: string | null;
   initialPrompt?: string;
   onSessionNotFound?: () => void;
   onStreamingChange?: (isStreaming: boolean) => void;
@@ -18,12 +19,13 @@ export interface ChatProps {
 
 export function Chat({
   className,
-  urlSessionId,
   initialPrompt,
   onSessionNotFound,
   onStreamingChange,
 }: ChatProps) {
+  const { urlSessionId } = useCopilotSessionId();
   const hasHandledNotFoundRef = useRef(false);
+  const isSwitchingSession = useCopilotStore((s) => s.isSwitchingSession);
   const {
     messages,
     isLoading,
@@ -33,49 +35,59 @@ export function Chat({
     sessionId,
     createSession,
     showLoader,
+    startPollingForOperation,
   } = useChat({ urlSessionId });
 
-  useEffect(
-    function handleMissingSession() {
-      if (!onSessionNotFound) return;
-      if (!urlSessionId) return;
-      if (!isSessionNotFound || isLoading || isCreating) return;
-      if (hasHandledNotFoundRef.current) return;
-      hasHandledNotFoundRef.current = true;
-      onSessionNotFound();
-    },
-    [onSessionNotFound, urlSessionId, isSessionNotFound, isLoading, isCreating],
-  );
+  useEffect(() => {
+    if (!onSessionNotFound) return;
+    if (!urlSessionId) return;
+    if (!isSessionNotFound || isLoading || isCreating) return;
+    if (hasHandledNotFoundRef.current) return;
+    hasHandledNotFoundRef.current = true;
+    onSessionNotFound();
+  }, [
+    onSessionNotFound,
+    urlSessionId,
+    isSessionNotFound,
+    isLoading,
+    isCreating,
+  ]);
+
+  const shouldShowLoader =
+    (showLoader && (isLoading || isCreating)) || isSwitchingSession;
 
   return (
     <div className={cn("flex h-full flex-col", className)}>
       {/* Main Content */}
       <main className="flex min-h-0 w-full flex-1 flex-col overflow-hidden bg-[#f8f8f9]">
         {/* Loading State */}
-        {showLoader && (isLoading || isCreating) && (
+        {shouldShowLoader && (
           <div className="flex flex-1 items-center justify-center">
-            <div className="flex flex-col items-center gap-4">
-              <ChatLoader />
+            <div className="flex flex-col items-center gap-3">
+              <LoadingSpinner size="large" className="text-neutral-400" />
               <Text variant="body" className="text-zinc-500">
-                Loading your chats...
+                {isSwitchingSession
+                  ? "Switching chat..."
+                  : "Loading your chat..."}
               </Text>
             </div>
           </div>
         )}
 
         {/* Error State */}
-        {error && !isLoading && (
+        {error && !isLoading && !isSwitchingSession && (
           <ChatErrorState error={error} onRetry={createSession} />
         )}
 
         {/* Session Content */}
-        {sessionId && !isLoading && !error && (
+        {sessionId && !isLoading && !error && !isSwitchingSession && (
           <ChatContainer
             sessionId={sessionId}
             initialMessages={messages}
             initialPrompt={initialPrompt}
             className="flex-1"
             onStreamingChange={onStreamingChange}
+            onOperationStarted={startPollingForOperation}
           />
         )}
       </main>

autogpt_platform/frontend/src/components/contextual/Chat/chat-store.ts

@@ -0,0 +1,289 @@
+"use client";
+
+import { create } from "zustand";
+import type {
+  ActiveStream,
+  StreamChunk,
+  StreamCompleteCallback,
+  StreamResult,
+  StreamStatus,
+} from "./chat-types";
+import { executeStream } from "./stream-executor";
+
+const COMPLETED_STREAM_TTL = 5 * 60 * 1000; // 5 minutes
+
+interface ChatStoreState {
+  activeStreams: Map<string, ActiveStream>;
+  completedStreams: Map<string, StreamResult>;
+  activeSessions: Set<string>;
+  streamCompleteCallbacks: Set<StreamCompleteCallback>;
+}
+
+interface ChatStoreActions {
+  startStream: (
+    sessionId: string,
+    message: string,
+    isUserMessage: boolean,
+    context?: { url: string; content: string },
+    onChunk?: (chunk: StreamChunk) => void,
+  ) => Promise<void>;
+  stopStream: (sessionId: string) => void;
+  subscribeToStream: (
+    sessionId: string,
+    onChunk: (chunk: StreamChunk) => void,
+    skipReplay?: boolean,
+  ) => () => void;
+  getStreamStatus: (sessionId: string) => StreamStatus;
+  getCompletedStream: (sessionId: string) => StreamResult | undefined;
+  clearCompletedStream: (sessionId: string) => void;
+  isStreaming: (sessionId: string) => boolean;
+  registerActiveSession: (sessionId: string) => void;
+  unregisterActiveSession: (sessionId: string) => void;
+  isSessionActive: (sessionId: string) => boolean;
+  onStreamComplete: (callback: StreamCompleteCallback) => () => void;
+}
+
+type ChatStore = ChatStoreState & ChatStoreActions;
+
+function notifyStreamComplete(
+  callbacks: Set<StreamCompleteCallback>,
+  sessionId: string,
+) {
+  for (const callback of callbacks) {
+    try {
+      callback(sessionId);
+    } catch (err) {
+      console.warn("[ChatStore] Stream complete callback error:", err);
+    }
+  }
+}
+
+function cleanupExpiredStreams(
+  completedStreams: Map<string, StreamResult>,
+): Map<string, StreamResult> {
+  const now = Date.now();
+  const cleaned = new Map(completedStreams);
+  for (const [sessionId, result] of cleaned) {
+    if (now - result.completedAt > COMPLETED_STREAM_TTL) {
+      cleaned.delete(sessionId);
+    }
+  }
+  return cleaned;
+}
+
+export const useChatStore = create<ChatStore>((set, get) => ({
+  activeStreams: new Map(),
+  completedStreams: new Map(),
+  activeSessions: new Set(),
+  streamCompleteCallbacks: new Set(),
+
+  startStream: async function startStream(
+    sessionId,
+    message,
+    isUserMessage,
+    context,
+    onChunk,
+  ) {
+    const state = get();
+    const newActiveStreams = new Map(state.activeStreams);
+    let newCompletedStreams = new Map(state.completedStreams);
+    const callbacks = state.streamCompleteCallbacks;
+
+    const existingStream = newActiveStreams.get(sessionId);
+    if (existingStream) {
+      existingStream.abortController.abort();
+      const normalizedStatus =
+        existingStream.status === "streaming"
+          ? "completed"
+          : existingStream.status;
+      const result: StreamResult = {
+        sessionId,
+        status: normalizedStatus,
+        chunks: existingStream.chunks,
+        completedAt: Date.now(),
+        error: existingStream.error,
+      };
+      newCompletedStreams.set(sessionId, result);
+      newActiveStreams.delete(sessionId);
+      newCompletedStreams = cleanupExpiredStreams(newCompletedStreams);
+      if (normalizedStatus === "completed" || normalizedStatus === "error") {
+        notifyStreamComplete(callbacks, sessionId);
+      }
+    }
+
+    const abortController = new AbortController();
+    const initialCallbacks = new Set<(chunk: StreamChunk) => void>();
+    if (onChunk) initialCallbacks.add(onChunk);
+
+    const stream: ActiveStream = {
+      sessionId,
+      abortController,
+      status: "streaming",
+      startedAt: Date.now(),
+      chunks: [],
+      onChunkCallbacks: initialCallbacks,
+    };
+
+    newActiveStreams.set(sessionId, stream);
+    set({
+      activeStreams: newActiveStreams,
+      completedStreams: newCompletedStreams,
+    });
+
+    try {
+      await executeStream(stream, message, isUserMessage, context);
+    } finally {
+      if (onChunk) stream.onChunkCallbacks.delete(onChunk);
+      if (stream.status !== "streaming") {
+        const currentState = get();
+        const finalActiveStreams = new Map(currentState.activeStreams);
+        let finalCompletedStreams = new Map(currentState.completedStreams);
+
+        const storedStream = finalActiveStreams.get(sessionId);
+        if (storedStream === stream) {
+          const result: StreamResult = {
+            sessionId,
+            status: stream.status,
+            chunks: stream.chunks,
+            completedAt: Date.now(),
+            error: stream.error,
+          };
+          finalCompletedStreams.set(sessionId, result);
+          finalActiveStreams.delete(sessionId);
+          finalCompletedStreams = cleanupExpiredStreams(finalCompletedStreams);
+          set({
+            activeStreams: finalActiveStreams,
+            completedStreams: finalCompletedStreams,
+          });
+          if (stream.status === "completed" || stream.status === "error") {
+            notifyStreamComplete(
+              currentState.streamCompleteCallbacks,
+              sessionId,
+            );
+          }
+        }
+      }
+    }
+  },
+
+  stopStream: function stopStream(sessionId) {
+    const state = get();
+    const stream = state.activeStreams.get(sessionId);
+    if (!stream) return;
+
+    stream.abortController.abort();
+    stream.status = "completed";
+
+    const newActiveStreams = new Map(state.activeStreams);
+    let newCompletedStreams = new Map(state.completedStreams);
+
+    const result: StreamResult = {
+      sessionId,
+      status: stream.status,
+      chunks: stream.chunks,
+      completedAt: Date.now(),
+      error: stream.error,
+    };
+    newCompletedStreams.set(sessionId, result);
+    newActiveStreams.delete(sessionId);
+    newCompletedStreams = cleanupExpiredStreams(newCompletedStreams);
+
+    set({
+      activeStreams: newActiveStreams,
+      completedStreams: newCompletedStreams,
+    });
+
+    notifyStreamComplete(state.streamCompleteCallbacks, sessionId);
+  },
+
+  subscribeToStream: function subscribeToStream(
+    sessionId,
+    onChunk,
+    skipReplay = false,
+  ) {
+    const state = get();
+    const stream = state.activeStreams.get(sessionId);
+
+    if (stream) {
+      if (!skipReplay) {
+        for (const chunk of stream.chunks) {
+          onChunk(chunk);
+        }
+      }
+
+      stream.onChunkCallbacks.add(onChunk);
+
+      return function unsubscribe() {
+        stream.onChunkCallbacks.delete(onChunk);
+      };
+    }
+
+    return function noop() {};
+  },
+
+  getStreamStatus: function getStreamStatus(sessionId) {
+    const { activeStreams, completedStreams } = get();
+
+    const active = activeStreams.get(sessionId);
+    if (active) return active.status;
+
+    const completed = completedStreams.get(sessionId);
+    if (completed) return completed.status;
+
+    return "idle";
+  },
+
+  getCompletedStream: function getCompletedStream(sessionId) {
+    return get().completedStreams.get(sessionId);
+  },
+
+  clearCompletedStream: function clearCompletedStream(sessionId) {
+    const state = get();
+    if (!state.completedStreams.has(sessionId)) return;
+
+    const newCompletedStreams = new Map(state.completedStreams);
+    newCompletedStreams.delete(sessionId);
+    set({ completedStreams: newCompletedStreams });
+  },
+
+  isStreaming: function isStreaming(sessionId) {
+    const stream = get().activeStreams.get(sessionId);
+    return stream?.status === "streaming";
+  },
+
+  registerActiveSession: function registerActiveSession(sessionId) {
+    const state = get();
+    if (state.activeSessions.has(sessionId)) return;
+
+    const newActiveSessions = new Set(state.activeSessions);
+    newActiveSessions.add(sessionId);
+    set({ activeSessions: newActiveSessions });
+  },
+
+  unregisterActiveSession: function unregisterActiveSession(sessionId) {
+    const state = get();
+    if (!state.activeSessions.has(sessionId)) return;
+
+    const newActiveSessions = new Set(state.activeSessions);
+    newActiveSessions.delete(sessionId);
+    set({ activeSessions: newActiveSessions });
+  },
+
+  isSessionActive: function isSessionActive(sessionId) {
+    return get().activeSessions.has(sessionId);
+  },
+
+  onStreamComplete: function onStreamComplete(callback) {
+    const state = get();
+    const newCallbacks = new Set(state.streamCompleteCallbacks);
+    newCallbacks.add(callback);
+    set({ streamCompleteCallbacks: newCallbacks });
+
+    return function unsubscribe() {
+      const currentState = get();
+      const cleanedCallbacks = new Set(currentState.streamCompleteCallbacks);
+      cleanedCallbacks.delete(callback);
+      set({ streamCompleteCallbacks: cleanedCallbacks });
+    };
+  },
+}));

autogpt_platform/frontend/src/components/contextual/Chat/chat-types.ts

@@ -0,0 +1,94 @@
+import type { ToolArguments, ToolResult } from "@/types/chat";
+
+export type StreamStatus = "idle" | "streaming" | "completed" | "error";
+
+export interface StreamChunk {
+  type:
+    | "text_chunk"
+    | "text_ended"
+    | "tool_call"
+    | "tool_call_start"
+    | "tool_response"
+    | "login_needed"
+    | "need_login"
+    | "credentials_needed"
+    | "error"
+    | "usage"
+    | "stream_end";
+  timestamp?: string;
+  content?: string;
+  message?: string;
+  code?: string;
+  details?: Record<string, unknown>;
+  tool_id?: string;
+  tool_name?: string;
+  arguments?: ToolArguments;
+  result?: ToolResult;
+  success?: boolean;
+  idx?: number;
+  session_id?: string;
+  agent_info?: {
+    graph_id: string;
+    name: string;
+    trigger_type: string;
+  };
+  provider?: string;
+  provider_name?: string;
+  credential_type?: string;
+  scopes?: string[];
+  title?: string;
+  [key: string]: unknown;
+}
+
+export type VercelStreamChunk =
+  | { type: "start"; messageId: string }
+  | { type: "finish" }
+  | { type: "text-start"; id: string }
+  | { type: "text-delta"; id: string; delta: string }
+  | { type: "text-end"; id: string }
+  | { type: "tool-input-start"; toolCallId: string; toolName: string }
+  | {
+      type: "tool-input-available";
+      toolCallId: string;
+      toolName: string;
+      input: Record<string, unknown>;
+    }
+  | {
+      type: "tool-output-available";
+      toolCallId: string;
+      toolName?: string;
+      output: unknown;
+      success?: boolean;
+    }
+  | {
+      type: "usage";
+      promptTokens: number;
+      completionTokens: number;
+      totalTokens: number;
+    }
+  | {
+      type: "error";
+      errorText: string;
+      code?: string;
+      details?: Record<string, unknown>;
+    };
+
+export interface ActiveStream {
+  sessionId: string;
+  abortController: AbortController;
+  status: StreamStatus;
+  startedAt: number;
+  chunks: StreamChunk[];
+  error?: Error;
+  onChunkCallbacks: Set<(chunk: StreamChunk) => void>;
+}
+
+export interface StreamResult {
+  sessionId: string;
+  status: StreamStatus;
+  chunks: StreamChunk[];
+  completedAt: number;
+  error?: Error;
+}
+
+export type StreamCompleteCallback = (sessionId: string) => void;

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/ChatContainer.tsx

@@ -4,6 +4,7 @@ import { Text } from "@/components/atoms/Text/Text";
 import { Dialog } from "@/components/molecules/Dialog/Dialog";
 import { useBreakpoint } from "@/lib/hooks/useBreakpoint";
 import { cn } from "@/lib/utils";
+import { GlobeHemisphereEastIcon } from "@phosphor-icons/react";
 import { useEffect } from "react";
 import { ChatInput } from "../ChatInput/ChatInput";
 import { MessageList } from "../MessageList/MessageList";
@@ -15,6 +16,7 @@ export interface ChatContainerProps {
   initialPrompt?: string;
   className?: string;
   onStreamingChange?: (isStreaming: boolean) => void;
+  onOperationStarted?: () => void;
 }
 
 export function ChatContainer({
@@ -23,6 +25,7 @@ export function ChatContainer({
   initialPrompt,
   className,
   onStreamingChange,
+  onOperationStarted,
 }: ChatContainerProps) {
   const {
     messages,
@@ -37,6 +40,7 @@ export function ChatContainer({
     sessionId,
     initialMessages,
     initialPrompt,
+    onOperationStarted,
   });
 
   useEffect(() => {
@@ -55,24 +59,37 @@ export function ChatContainer({
       )}
     >
       <Dialog
-        title="Service unavailable"
+        title={
+          <div className="flex items-center gap-2">
+            <GlobeHemisphereEastIcon className="size-6" />
+            <Text
+              variant="body"
+              className="text-md font-poppins leading-none md:text-lg"
+            >
+              Service unavailable
+            </Text>
+          </div>
+        }
         controlled={{
           isOpen: isRegionBlockedModalOpen,
           set: handleRegionModalOpenChange,
         }}
         onClose={handleRegionModalClose}
+        styling={{ maxWidth: 550, width: "100%", minWidth: "auto" }}
       >
         <Dialog.Content>
-          <div className="flex flex-col gap-4">
+          <div className="flex flex-col gap-8">
             <Text variant="body">
-              This model is not available in your region. Please connect via VPN
-              and try again.
+              The Autogpt AI model is not available in your region or your
+              connection is blocking it. Please try again with a different
+              connection.
             </Text>
-            <div className="flex justify-end">
+            <div className="flex justify-center">
               <Button
                 type="button"
                 variant="primary"
                 onClick={handleRegionModalClose}
+                className="w-full"
               >
                 Got it
               </Button>

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/createStreamEventDispatcher.ts

@@ -1,5 +1,5 @@
 import { toast } from "sonner";
-import { StreamChunk } from "../../useChatStream";
+import type { StreamChunk } from "../../chat-types";
 import type { HandlerDependencies } from "./handlers";
 import {
   handleError,

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/handlers.ts

@@ -22,6 +22,7 @@ export interface HandlerDependencies {
   setIsStreamingInitiated: Dispatch<SetStateAction<boolean>>;
   setIsRegionBlockedModalOpen: Dispatch<SetStateAction<boolean>>;
   sessionId: string;
+  onOperationStarted?: () => void;
 }
 
 export function isRegionBlockedError(chunk: StreamChunk): boolean {
@@ -48,6 +49,15 @@ export function handleTextEnded(
   const completedText = deps.streamingChunksRef.current.join("");
   if (completedText.trim()) {
     deps.setMessages((prev) => {
+      // Check if this exact message already exists to prevent duplicates
+      const exists = prev.some(
+        (msg) =>
+          msg.type === "message" &&
+          msg.role === "assistant" &&
+          msg.content === completedText,
+      );
+      if (exists) return prev;
+
       const assistantMessage: ChatMessageData = {
         type: "message",
         role: "assistant",
@@ -154,6 +164,11 @@ export function handleToolResponse(
     }
     return;
   }
+  // Trigger polling when operation_started is received
+  if (responseMessage.type === "operation_started") {
+    deps.onOperationStarted?.();
+  }
+
   deps.setMessages((prev) => {
     const toolCallIndex = prev.findIndex(
       (msg) => msg.type === "tool_call" && msg.toolId === chunk.tool_id,
@@ -203,13 +218,24 @@ export function handleStreamEnd(
     ]);
   }
   if (completedContent.trim()) {
-    const assistantMessage: ChatMessageData = {
-      type: "message",
-      role: "assistant",
-      content: completedContent,
-      timestamp: new Date(),
-    };
-    deps.setMessages((prev) => [...prev, assistantMessage]);
+    deps.setMessages((prev) => {
+      // Check if this exact message already exists to prevent duplicates
+      const exists = prev.some(
+        (msg) =>
+          msg.type === "message" &&
+          msg.role === "assistant" &&
+          msg.content === completedContent,
+      );
+      if (exists) return prev;
+
+      const assistantMessage: ChatMessageData = {
+        type: "message",
+        role: "assistant",
+        content: completedContent,
+        timestamp: new Date(),
+      };
+      return [...prev, assistantMessage];
+    });
   }
   deps.setStreamingChunks([]);
   deps.streamingChunksRef.current = [];

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/helpers.ts

@@ -1,7 +1,118 @@
+import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
 import { SessionKey, sessionStorage } from "@/services/storage/session-storage";
 import type { ToolResult } from "@/types/chat";
 import type { ChatMessageData } from "../ChatMessage/useChatMessage";
 
+export function processInitialMessages(
+  initialMessages: SessionDetailResponse["messages"],
+): ChatMessageData[] {
+  const processedMessages: ChatMessageData[] = [];
+  const toolCallMap = new Map<string, string>();
+
+  for (const msg of initialMessages) {
+    if (!isValidMessage(msg)) {
+      console.warn("Invalid message structure from backend:", msg);
+      continue;
+    }
+
+    let content = String(msg.content || "");
+    const role = String(msg.role || "assistant").toLowerCase();
+    const toolCalls = msg.tool_calls;
+    const timestamp = msg.timestamp
+      ? new Date(msg.timestamp as string)
+      : undefined;
+
+    if (role === "user") {
+      content = removePageContext(content);
+      if (!content.trim()) continue;
+      processedMessages.push({
+        type: "message",
+        role: "user",
+        content,
+        timestamp,
+      });
+      continue;
+    }
+
+    if (role === "assistant") {
+      content = content
+        .replace(/<thinking>[\s\S]*?<\/thinking>/gi, "")
+        .replace(/<internal_reasoning>[\s\S]*?<\/internal_reasoning>/gi, "")
+        .trim();
+
+      if (toolCalls && isToolCallArray(toolCalls) && toolCalls.length > 0) {
+        for (const toolCall of toolCalls) {
+          const toolName = toolCall.function.name;
+          const toolId = toolCall.id;
+          toolCallMap.set(toolId, toolName);
+
+          try {
+            const args = JSON.parse(toolCall.function.arguments || "{}");
+            processedMessages.push({
+              type: "tool_call",
+              toolId,
+              toolName,
+              arguments: args,
+              timestamp,
+            });
+          } catch (err) {
+            console.warn("Failed to parse tool call arguments:", err);
+            processedMessages.push({
+              type: "tool_call",
+              toolId,
+              toolName,
+              arguments: {},
+              timestamp,
+            });
+          }
+        }
+        if (content.trim()) {
+          processedMessages.push({
+            type: "message",
+            role: "assistant",
+            content,
+            timestamp,
+          });
+        }
+      } else if (content.trim()) {
+        processedMessages.push({
+          type: "message",
+          role: "assistant",
+          content,
+          timestamp,
+        });
+      }
+      continue;
+    }
+
+    if (role === "tool") {
+      const toolCallId = (msg.tool_call_id as string) || "";
+      const toolName = toolCallMap.get(toolCallId) || "unknown";
+      const toolResponse = parseToolResponse(
+        content,
+        toolCallId,
+        toolName,
+        timestamp,
+      );
+      if (toolResponse) {
+        processedMessages.push(toolResponse);
+      }
+      continue;
+    }
+
+    if (content.trim()) {
+      processedMessages.push({
+        type: "message",
+        role: role as "user" | "assistant" | "system",
+        content,
+        timestamp,
+      });
+    }
+  }
+
+  return processedMessages;
+}
+
 export function hasSentInitialPrompt(sessionId: string): boolean {
   try {
     const sent = JSON.parse(
@@ -193,6 +304,7 @@ export function parseToolResponse(
       if (isAgentArray(agentsData)) {
         return {
           type: "agent_carousel",
+          toolId,
           toolName: "agent_carousel",
           agents: agentsData,
           totalCount: parsedResult.total_count as number | undefined,
@@ -205,6 +317,7 @@ export function parseToolResponse(
     if (responseType === "execution_started") {
       return {
         type: "execution_started",
+        toolId,
         toolName: "execution_started",
         executionId: (parsedResult.execution_id as string) || "",
         agentName: (parsedResult.graph_name as string) || undefined,
@@ -230,6 +343,41 @@ export function parseToolResponse(
         timestamp: timestamp || new Date(),
       };
     }
+    if (responseType === "operation_started") {
+      return {
+        type: "operation_started",
+        toolName: (parsedResult.tool_name as string) || toolName,
+        toolId,
+        operationId: (parsedResult.operation_id as string) || "",
+        message:
+          (parsedResult.message as string) ||
+          "Operation started. You can close this tab.",
+        timestamp: timestamp || new Date(),
+      };
+    }
+    if (responseType === "operation_pending") {
+      return {
+        type: "operation_pending",
+        toolName: (parsedResult.tool_name as string) || toolName,
+        toolId,
+        operationId: (parsedResult.operation_id as string) || "",
+        message:
+          (parsedResult.message as string) ||
+          "Operation in progress. Please wait...",
+        timestamp: timestamp || new Date(),
+      };
+    }
+    if (responseType === "operation_in_progress") {
+      return {
+        type: "operation_in_progress",
+        toolName: (parsedResult.tool_name as string) || toolName,
+        toolCallId: (parsedResult.tool_call_id as string) || toolId,
+        message:
+          (parsedResult.message as string) ||
+          "Operation already in progress. Please wait...",
+        timestamp: timestamp || new Date(),
+      };
+    }
     if (responseType === "need_login") {
       return {
         type: "login_needed",

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/useChatContainer.ts

@@ -1,5 +1,6 @@
 import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
-import { useCallback, useEffect, useMemo, useRef, useState } from "react";
+import { useEffect, useMemo, useRef, useState } from "react";
+import { useChatStore } from "../../chat-store";
 import { toast } from "sonner";
 import { useChatStream } from "../../useChatStream";
 import { usePageContext } from "../../usePageContext";
@@ -9,23 +10,44 @@ import {
   createUserMessage,
   filterAuthMessages,
   hasSentInitialPrompt,
-  isToolCallArray,
-  isValidMessage,
   markInitialPromptSent,
-  parseToolResponse,
-  removePageContext,
+  processInitialMessages,
 } from "./helpers";
 
+// Helper to generate deduplication key for a message
+function getMessageKey(msg: ChatMessageData): string {
+  if (msg.type === "message") {
+    // Don't include timestamp - dedupe by role + content only
+    // This handles the case where local and server timestamps differ
+    // Server messages are authoritative, so duplicates from local state are filtered
+    return `msg:${msg.role}:${msg.content}`;
+  } else if (msg.type === "tool_call") {
+    return `toolcall:${msg.toolId}`;
+  } else if (msg.type === "tool_response") {
+    return `toolresponse:${(msg as any).toolId}`;
+  } else if (
+    msg.type === "operation_started" ||
+    msg.type === "operation_pending" ||
+    msg.type === "operation_in_progress"
+  ) {
+    return `op:${(msg as any).toolId || (msg as any).operationId || (msg as any).toolCallId || ""}:${msg.toolName}`;
+  } else {
+    return `${msg.type}:${JSON.stringify(msg).slice(0, 100)}`;
+  }
+}
+
 interface Args {
   sessionId: string | null;
   initialMessages: SessionDetailResponse["messages"];
   initialPrompt?: string;
+  onOperationStarted?: () => void;
 }
 
 export function useChatContainer({
   sessionId,
   initialMessages,
   initialPrompt,
+  onOperationStarted,
 }: Args) {
   const [messages, setMessages] = useState<ChatMessageData[]>([]);
   const [streamingChunks, setStreamingChunks] = useState<string[]>([]);
@@ -41,11 +63,18 @@ export function useChatContainer({
     sendMessage: sendStreamMessage,
     stopStreaming,
   } = useChatStream();
+  const activeStreams = useChatStore((s) => s.activeStreams);
+  const subscribeToStream = useChatStore((s) => s.subscribeToStream);
   const isStreaming = isStreamingInitiated || hasTextChunks;
 
-  useEffect(() => {
-    if (sessionId !== previousSessionIdRef.current) {
-      stopStreaming(previousSessionIdRef.current ?? undefined, true);
+  useEffect(
+    function handleSessionChange() {
+      if (sessionId === previousSessionIdRef.current) return;
+
+      const prevSession = previousSessionIdRef.current;
+      if (prevSession) {
+        stopStreaming(prevSession);
+      }
       previousSessionIdRef.current = sessionId;
       setMessages([]);
       setStreamingChunks([]);
@@ -53,138 +82,11 @@ export function useChatContainer({
       setHasTextChunks(false);
       setIsStreamingInitiated(false);
       hasResponseRef.current = false;
-    }
-  }, [sessionId, stopStreaming]);
 
-  const allMessages = useMemo(() => {
-    const processedInitialMessages: ChatMessageData[] = [];
-    const toolCallMap = new Map<string, string>();
+      if (!sessionId) return;
 
-    for (const msg of initialMessages) {
-      if (!isValidMessage(msg)) {
-        console.warn("Invalid message structure from backend:", msg);
-        continue;
-      }
-
-      let content = String(msg.content || "");
-      const role = String(msg.role || "assistant").toLowerCase();
-      const toolCalls = msg.tool_calls;
-      const timestamp = msg.timestamp
-        ? new Date(msg.timestamp as string)
-        : undefined;
-
-      if (role === "user") {
-        content = removePageContext(content);
-        if (!content.trim()) continue;
-        processedInitialMessages.push({
-          type: "message",
-          role: "user",
-          content,
-          timestamp,
-        });
-        continue;
-      }
-
-      if (role === "assistant") {
-        content = content
-          .replace(/<thinking>[\s\S]*?<\/thinking>/gi, "")
-          .trim();
-
-        if (toolCalls && isToolCallArray(toolCalls) && toolCalls.length > 0) {
-          for (const toolCall of toolCalls) {
-            const toolName = toolCall.function.name;
-            const toolId = toolCall.id;
-            toolCallMap.set(toolId, toolName);
-
-            try {
-              const args = JSON.parse(toolCall.function.arguments || "{}");
-              processedInitialMessages.push({
-                type: "tool_call",
-                toolId,
-                toolName,
-                arguments: args,
-                timestamp,
-              });
-            } catch (err) {
-              console.warn("Failed to parse tool call arguments:", err);
-              processedInitialMessages.push({
-                type: "tool_call",
-                toolId,
-                toolName,
-                arguments: {},
-                timestamp,
-              });
-            }
-          }
-          if (content.trim()) {
-            processedInitialMessages.push({
-              type: "message",
-              role: "assistant",
-              content,
-              timestamp,
-            });
-          }
-        } else if (content.trim()) {
-          processedInitialMessages.push({
-            type: "message",
-            role: "assistant",
-            content,
-            timestamp,
-          });
-        }
-        continue;
-      }
-
-      if (role === "tool") {
-        const toolCallId = (msg.tool_call_id as string) || "";
-        const toolName = toolCallMap.get(toolCallId) || "unknown";
-        const toolResponse = parseToolResponse(
-          content,
-          toolCallId,
-          toolName,
-          timestamp,
-        );
-        if (toolResponse) {
-          processedInitialMessages.push(toolResponse);
-        }
-        continue;
-      }
-
-      if (content.trim()) {
-        processedInitialMessages.push({
-          type: "message",
-          role: role as "user" | "assistant" | "system",
-          content,
-          timestamp,
-        });
-      }
-    }
-
-    return [...processedInitialMessages, ...messages];
-  }, [initialMessages, messages]);
-
-  const sendMessage = useCallback(
-    async function sendMessage(
-      content: string,
-      isUserMessage: boolean = true,
-      context?: { url: string; content: string },
-    ) {
-      if (!sessionId) {
-        console.error("[useChatContainer] Cannot send message: no session ID");
-        return;
-      }
-      setIsRegionBlockedModalOpen(false);
-      if (isUserMessage) {
-        const userMessage = createUserMessage(content);
-        setMessages((prev) => [...filterAuthMessages(prev), userMessage]);
-      } else {
-        setMessages((prev) => filterAuthMessages(prev));
-      }
-      setStreamingChunks([]);
-      streamingChunksRef.current = [];
-      setHasTextChunks(false);
-      setIsStreamingInitiated(true);
-      hasResponseRef.current = false;
+      const activeStream = activeStreams.get(sessionId);
+      if (!activeStream || activeStream.status !== "streaming") return;
 
       const dispatcher = createStreamEventDispatcher({
         setHasTextChunks,
@@ -195,44 +97,170 @@ export function useChatContainer({
         setIsRegionBlockedModalOpen,
         sessionId,
         setIsStreamingInitiated,
+        onOperationStarted,
       });
 
-      try {
-        await sendStreamMessage(
-          sessionId,
-          content,
-          dispatcher,
-          isUserMessage,
-          context,
-        );
-      } catch (err) {
-        console.error("[useChatContainer] Failed to send message:", err);
-        setIsStreamingInitiated(false);
-
-        // Don't show error toast for AbortError (expected during cleanup)
-        if (err instanceof Error && err.name === "AbortError") return;
-
-        const errorMessage =
-          err instanceof Error ? err.message : "Failed to send message";
-        toast.error("Failed to send message", {
-          description: errorMessage,
-        });
-      }
+      setIsStreamingInitiated(true);
+      const skipReplay = initialMessages.length > 0;
+      return subscribeToStream(sessionId, dispatcher, skipReplay);
     },
-    [sessionId, sendStreamMessage],
+    [
+      sessionId,
+      stopStreaming,
+      activeStreams,
+      subscribeToStream,
+      onOperationStarted,
+    ],
   );
 
-  const handleStopStreaming = useCallback(() => {
+  // Collect toolIds from completed tool results in initialMessages
+  // Used to filter out operation messages when their results arrive
+  const completedToolIds = useMemo(() => {
+    const processedInitial = processInitialMessages(initialMessages);
+    const ids = new Set<string>();
+    for (const msg of processedInitial) {
+      if (
+        msg.type === "tool_response" ||
+        msg.type === "agent_carousel" ||
+        msg.type === "execution_started"
+      ) {
+        const toolId = (msg as any).toolId;
+        if (toolId) {
+          ids.add(toolId);
+        }
+      }
+    }
+    return ids;
+  }, [initialMessages]);
+
+  // Clean up local operation messages when their completed results arrive from polling
+  // This effect runs when completedToolIds changes (i.e., when polling brings new results)
+  useEffect(
+    function cleanupCompletedOperations() {
+      if (completedToolIds.size === 0) return;
+
+      setMessages((prev) => {
+        const filtered = prev.filter((msg) => {
+          if (
+            msg.type === "operation_started" ||
+            msg.type === "operation_pending" ||
+            msg.type === "operation_in_progress"
+          ) {
+            const toolId = (msg as any).toolId || (msg as any).toolCallId;
+            if (toolId && completedToolIds.has(toolId)) {
+              return false; // Remove - operation completed
+            }
+          }
+          return true;
+        });
+        // Only update state if something was actually filtered
+        return filtered.length === prev.length ? prev : filtered;
+      });
+    },
+    [completedToolIds],
+  );
+
+  // Combine initial messages from backend with local streaming messages,
+  // Server messages maintain correct order; only append truly new local messages
+  const allMessages = useMemo(() => {
+    const processedInitial = processInitialMessages(initialMessages);
+
+    // Build a set of keys from server messages for deduplication
+    const serverKeys = new Set<string>();
+    for (const msg of processedInitial) {
+      serverKeys.add(getMessageKey(msg));
+    }
+
+    // Filter local messages: remove duplicates and completed operation messages
+    const newLocalMessages = messages.filter((msg) => {
+      // Remove operation messages for completed tools
+      if (
+        msg.type === "operation_started" ||
+        msg.type === "operation_pending" ||
+        msg.type === "operation_in_progress"
+      ) {
+        const toolId = (msg as any).toolId || (msg as any).toolCallId;
+        if (toolId && completedToolIds.has(toolId)) {
+          return false;
+        }
+      }
+      // Remove messages that already exist in server data
+      const key = getMessageKey(msg);
+      return !serverKeys.has(key);
+    });
+
+    // Server messages first (correct order), then new local messages
+    return [...processedInitial, ...newLocalMessages];
+  }, [initialMessages, messages, completedToolIds]);
+
+  async function sendMessage(
+    content: string,
+    isUserMessage: boolean = true,
+    context?: { url: string; content: string },
+  ) {
+    if (!sessionId) {
+      console.error("[useChatContainer] Cannot send message: no session ID");
+      return;
+    }
+    setIsRegionBlockedModalOpen(false);
+    if (isUserMessage) {
+      const userMessage = createUserMessage(content);
+      setMessages((prev) => [...filterAuthMessages(prev), userMessage]);
+    } else {
+      setMessages((prev) => filterAuthMessages(prev));
+    }
+    setStreamingChunks([]);
+    streamingChunksRef.current = [];
+    setHasTextChunks(false);
+    setIsStreamingInitiated(true);
+    hasResponseRef.current = false;
+
+    const dispatcher = createStreamEventDispatcher({
+      setHasTextChunks,
+      setStreamingChunks,
+      streamingChunksRef,
+      hasResponseRef,
+      setMessages,
+      setIsRegionBlockedModalOpen,
+      sessionId,
+      setIsStreamingInitiated,
+      onOperationStarted,
+    });
+
+    try {
+      await sendStreamMessage(
+        sessionId,
+        content,
+        dispatcher,
+        isUserMessage,
+        context,
+      );
+    } catch (err) {
+      console.error("[useChatContainer] Failed to send message:", err);
+      setIsStreamingInitiated(false);
+
+      if (err instanceof Error && err.name === "AbortError") return;
+
+      const errorMessage =
+        err instanceof Error ? err.message : "Failed to send message";
+      toast.error("Failed to send message", {
+        description: errorMessage,
+      });
+    }
+  }
+
+  function handleStopStreaming() {
     stopStreaming();
     setStreamingChunks([]);
     streamingChunksRef.current = [];
     setHasTextChunks(false);
     setIsStreamingInitiated(false);
-  }, [stopStreaming]);
+  }
 
   const { capturePageContext } = usePageContext();
+  const sendMessageRef = useRef(sendMessage);
+  sendMessageRef.current = sendMessage;
 
-  // Send initial prompt if provided (for new sessions from homepage)
   useEffect(
     function handleInitialPrompt() {
       if (!initialPrompt || !sessionId) return;
@@ -241,15 +269,9 @@ export function useChatContainer({
 
       markInitialPromptSent(sessionId);
       const context = capturePageContext();
-      sendMessage(initialPrompt, true, context);
+      sendMessageRef.current(initialPrompt, true, context);
     },
-    [
-      initialPrompt,
-      sessionId,
-      initialMessages.length,
-      sendMessage,
-      capturePageContext,
-    ],
+    [initialPrompt, sessionId, initialMessages.length, capturePageContext],
   );
 
   async function sendMessageWithContext(

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/ChatInput.tsx

@@ -21,7 +21,7 @@ export function ChatInput({
   className,
 }: Props) {
   const inputId = "chat-input";
-  const { value, setValue, handleKeyDown, handleSend, hasMultipleLines } =
+  const { value, handleKeyDown, handleSubmit, handleChange, hasMultipleLines } =
     useChatInput({
       onSend,
       disabled: disabled || isStreaming,
@@ -29,15 +29,6 @@ export function ChatInput({
       inputId,
     });
 
-  function handleSubmit(e: React.FormEvent<HTMLFormElement>) {
-    e.preventDefault();
-    handleSend();
-  }
-
-  function handleChange(e: React.ChangeEvent<HTMLTextAreaElement>) {
-    setValue(e.target.value);
-  }
-
   return (
     <form onSubmit={handleSubmit} className={cn("relative flex-1", className)}>
       <div className="relative">

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/useChatInput.ts

@@ -1,4 +1,10 @@
-import { KeyboardEvent, useCallback, useEffect, useState } from "react";
+import {
+  ChangeEvent,
+  FormEvent,
+  KeyboardEvent,
+  useEffect,
+  useState,
+} from "react";
 
 interface UseChatInputArgs {
   onSend: (message: string) => void;
@@ -16,6 +22,23 @@ export function useChatInput({
   const [value, setValue] = useState("");
   const [hasMultipleLines, setHasMultipleLines] = useState(false);
 
+  useEffect(
+    function focusOnMount() {
+      const textarea = document.getElementById(inputId) as HTMLTextAreaElement;
+      if (textarea) textarea.focus();
+    },
+    [inputId],
+  );
+
+  useEffect(
+    function focusWhenEnabled() {
+      if (disabled) return;
+      const textarea = document.getElementById(inputId) as HTMLTextAreaElement;
+      if (textarea) textarea.focus();
+    },
+    [disabled, inputId],
+  );
+
   useEffect(() => {
     const textarea = document.getElementById(inputId) as HTMLTextAreaElement;
     const wrapper = document.getElementById(
@@ -77,7 +100,7 @@ export function useChatInput({
     }
   }, [value, maxRows, inputId]);
 
-  const handleSend = useCallback(() => {
+  const handleSend = () => {
     if (disabled || !value.trim()) return;
     onSend(value.trim());
     setValue("");
@@ -93,23 +116,31 @@ export function useChatInput({
       wrapper.style.height = "";
       wrapper.style.maxHeight = "";
     }
-  }, [value, onSend, disabled, inputId]);
+  };
 
-  const handleKeyDown = useCallback(
-    (event: KeyboardEvent<HTMLTextAreaElement>) => {
-      if (event.key === "Enter" && !event.shiftKey) {
-        event.preventDefault();
-        handleSend();
-      }
-    },
-    [handleSend],
-  );
+  function handleKeyDown(event: KeyboardEvent<HTMLTextAreaElement>) {
+    if (event.key === "Enter" && !event.shiftKey) {
+      event.preventDefault();
+      handleSend();
+    }
+  }
+
+  function handleSubmit(e: FormEvent<HTMLFormElement>) {
+    e.preventDefault();
+    handleSend();
+  }
+
+  function handleChange(e: ChangeEvent<HTMLTextAreaElement>) {
+    setValue(e.target.value);
+  }
 
   return {
     value,
     setValue,
     handleKeyDown,
     handleSend,
+    handleSubmit,
+    handleChange,
     hasMultipleLines,
   };
 }

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatMessage/ChatMessage.tsx

@@ -16,6 +16,7 @@ import { AuthPromptWidget } from "../AuthPromptWidget/AuthPromptWidget";
 import { ChatCredentialsSetup } from "../ChatCredentialsSetup/ChatCredentialsSetup";
 import { ClarificationQuestionsWidget } from "../ClarificationQuestionsWidget/ClarificationQuestionsWidget";
 import { ExecutionStartedMessage } from "../ExecutionStartedMessage/ExecutionStartedMessage";
+import { PendingOperationWidget } from "../PendingOperationWidget/PendingOperationWidget";
 import { MarkdownContent } from "../MarkdownContent/MarkdownContent";
 import { NoResultsMessage } from "../NoResultsMessage/NoResultsMessage";
 import { ToolCallMessage } from "../ToolCallMessage/ToolCallMessage";
@@ -71,6 +72,9 @@ export function ChatMessage({
     isLoginNeeded,
     isCredentialsNeeded,
     isClarificationNeeded,
+    isOperationStarted,
+    isOperationPending,
+    isOperationInProgress,
   } = useChatMessage(message);
   const displayContent = getDisplayContent(message, isUser);
 
@@ -126,10 +130,6 @@ export function ChatMessage({
     [displayContent, message],
   );
 
-  function isLongResponse(content: string): boolean {
-    return content.split("\n").length > 5;
-  }
-
   const handleTryAgain = useCallback(() => {
     if (message.type !== "message" || !onSendMessage) return;
     onSendMessage(message.content, message.role === "user");
@@ -294,6 +294,42 @@ export function ChatMessage({
     );
   }
 
+  // Render operation_started messages (long-running background operations)
+  if (isOperationStarted && message.type === "operation_started") {
+    return (
+      <PendingOperationWidget
+        status="started"
+        message={message.message}
+        toolName={message.toolName}
+        className={className}
+      />
+    );
+  }
+
+  // Render operation_pending messages (operations in progress when refreshing)
+  if (isOperationPending && message.type === "operation_pending") {
+    return (
+      <PendingOperationWidget
+        status="pending"
+        message={message.message}
+        toolName={message.toolName}
+        className={className}
+      />
+    );
+  }
+
+  // Render operation_in_progress messages (duplicate request while operation running)
+  if (isOperationInProgress && message.type === "operation_in_progress") {
+    return (
+      <PendingOperationWidget
+        status="in_progress"
+        message={message.message}
+        toolName={message.toolName}
+        className={className}
+      />
+    );
+  }
+
   // Render tool response messages (but skip agent_output if it's being rendered inside assistant message)
   if (isToolResponse && message.type === "tool_response") {
     return (
@@ -358,7 +394,7 @@ export function ChatMessage({
                   <ArrowsClockwiseIcon className="size-4 text-zinc-600" />
                 </Button>
               )}
-              {!isUser && isFinalMessage && isLongResponse(displayContent) && (
+              {!isUser && isFinalMessage && !isStreaming && (
                 <Button
                   variant="ghost"
                   size="icon"

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatMessage/useChatMessage.ts

@@ -61,6 +61,7 @@ export type ChatMessageData =
     }
   | {
       type: "agent_carousel";
+      toolId: string;
       toolName: string;
       agents: Array<{
         id: string;
@@ -74,6 +75,7 @@ export type ChatMessageData =
     }
   | {
       type: "execution_started";
+      toolId: string;
       toolName: string;
       executionId: string;
       agentName?: string;
@@ -103,6 +105,29 @@ export type ChatMessageData =
       message: string;
       sessionId: string;
       timestamp?: string | Date;
+    }
+  | {
+      type: "operation_started";
+      toolName: string;
+      toolId: string;
+      operationId: string;
+      message: string;
+      timestamp?: string | Date;
+    }
+  | {
+      type: "operation_pending";
+      toolName: string;
+      toolId: string;
+      operationId: string;
+      message: string;
+      timestamp?: string | Date;
+    }
+  | {
+      type: "operation_in_progress";
+      toolName: string;
+      toolCallId: string;
+      message: string;
+      timestamp?: string | Date;
     };
 
 export function useChatMessage(message: ChatMessageData) {
@@ -124,5 +149,8 @@ export function useChatMessage(message: ChatMessageData) {
     isExecutionStarted: message.type === "execution_started",
     isInputsNeeded: message.type === "inputs_needed",
     isClarificationNeeded: message.type === "clarification_needed",
+    isOperationStarted: message.type === "operation_started",
+    isOperationPending: message.type === "operation_pending",
+    isOperationInProgress: message.type === "operation_in_progress",
   };
 }

autogpt_platform/frontend/src/components/contextual/Chat/components/ClarificationQuestionsWidget/ClarificationQuestionsWidget.tsx

@@ -30,6 +30,7 @@ export function ClarificationQuestionsWidget({
   className,
 }: Props) {
   const [answers, setAnswers] = useState<Record<string, string>>({});
+  const [isSubmitted, setIsSubmitted] = useState(false);
 
   function handleAnswerChange(keyword: string, value: string) {
     setAnswers((prev) => ({ ...prev, [keyword]: value }));
@@ -41,11 +42,42 @@ export function ClarificationQuestionsWidget({
     if (!allAnswered) {
       return;
     }
+    setIsSubmitted(true);
     onSubmitAnswers(answers);
   }
 
   const allAnswered = questions.every((q) => answers[q.keyword]?.trim());
 
+  // Show submitted state after answers are submitted
+  if (isSubmitted) {
+    return (
+      <div
+        className={cn(
+          "group relative flex w-full justify-start gap-3 px-4 py-3",
+          className,
+        )}
+      >
+        <div className="flex w-full max-w-3xl gap-3">
+          <div className="flex-shrink-0">
+            <div className="flex h-7 w-7 items-center justify-center rounded-lg bg-green-500">
+              <CheckCircleIcon className="h-4 w-4 text-white" weight="bold" />
+            </div>
+          </div>
+          <div className="flex min-w-0 flex-1 flex-col">
+            <Card className="p-4">
+              <Text variant="h4" className="mb-1 text-slate-900">
+                Answers submitted
+              </Text>
+              <Text variant="small" className="text-slate-600">
+                Processing your responses...
+              </Text>
+            </Card>
+          </div>
+        </div>
+      </div>
+    );
+  }
+
   return (
     <div
       className={cn(

autogpt_platform/frontend/src/components/contextual/Chat/components/MessageList/components/LastToolResponse/LastToolResponse.tsx

@@ -1,7 +1,5 @@
-import { AIChatBubble } from "../../../AIChatBubble/AIChatBubble";
 import type { ChatMessageData } from "../../../ChatMessage/useChatMessage";
-import { MarkdownContent } from "../../../MarkdownContent/MarkdownContent";
-import { formatToolResponse } from "../../../ToolResponseMessage/helpers";
+import { ToolResponseMessage } from "../../../ToolResponseMessage/ToolResponseMessage";
 import { shouldSkipAgentOutput } from "../../helpers";
 
 export interface LastToolResponseProps {
@@ -15,16 +13,15 @@ export function LastToolResponse({
 }: LastToolResponseProps) {
   if (message.type !== "tool_response") return null;
 
-  // Skip if this is an agent_output that should be rendered inside assistant message
   if (shouldSkipAgentOutput(message, prevMessage)) return null;
 
-  const formattedText = formatToolResponse(message.result, message.toolName);
-
   return (
     <div className="min-w-0 overflow-x-hidden hyphens-auto break-words px-4 py-2">
-      <AIChatBubble>
-        <MarkdownContent content={formattedText} />
-      </AIChatBubble>
+      <ToolResponseMessage
+        toolId={message.toolId}
+        toolName={message.toolName}
+        result={message.result}
+      />
     </div>
   );
 }

autogpt_platform/frontend/src/components/contextual/Chat/components/PendingOperationWidget/PendingOperationWidget.tsx

@@ -0,0 +1,109 @@
+"use client";
+
+import { Card } from "@/components/atoms/Card/Card";
+import { Text } from "@/components/atoms/Text/Text";
+import { cn } from "@/lib/utils";
+import { CircleNotch, CheckCircle, XCircle } from "@phosphor-icons/react";
+
+type OperationStatus =
+  | "pending"
+  | "started"
+  | "in_progress"
+  | "completed"
+  | "error";
+
+interface Props {
+  status: OperationStatus;
+  message: string;
+  toolName?: string;
+  className?: string;
+}
+
+function getOperationTitle(toolName?: string): string {
+  if (!toolName) return "Operation";
+  // Convert tool name to human-readable format
+  // e.g., "create_agent" -> "Creating Agent", "edit_agent" -> "Editing Agent"
+  if (toolName === "create_agent") return "Creating Agent";
+  if (toolName === "edit_agent") return "Editing Agent";
+  // Default: capitalize and format tool name
+  return toolName
+    .split("_")
+    .map((word) => word.charAt(0).toUpperCase() + word.slice(1))
+    .join(" ");
+}
+
+export function PendingOperationWidget({
+  status,
+  message,
+  toolName,
+  className,
+}: Props) {
+  const isPending =
+    status === "pending" || status === "started" || status === "in_progress";
+  const isCompleted = status === "completed";
+  const isError = status === "error";
+
+  const operationTitle = getOperationTitle(toolName);
+
+  return (
+    <div
+      className={cn(
+        "group relative flex w-full justify-start gap-3 px-4 py-3",
+        className,
+      )}
+    >
+      <div className="flex w-full max-w-3xl gap-3">
+        <div className="flex-shrink-0">
+          <div
+            className={cn(
+              "flex h-7 w-7 items-center justify-center rounded-lg",
+              isPending && "bg-blue-500",
+              isCompleted && "bg-green-500",
+              isError && "bg-red-500",
+            )}
+          >
+            {isPending && (
+              <CircleNotch
+                className="h-4 w-4 animate-spin text-white"
+                weight="bold"
+              />
+            )}
+            {isCompleted && (
+              <CheckCircle className="h-4 w-4 text-white" weight="bold" />
+            )}
+            {isError && (
+              <XCircle className="h-4 w-4 text-white" weight="bold" />
+            )}
+          </div>
+        </div>
+
+        <div className="flex min-w-0 flex-1 flex-col">
+          <Card className="space-y-2 p-4">
+            <div>
+              <Text variant="h4" className="mb-1 text-slate-900">
+                {isPending && operationTitle}
+                {isCompleted && `${operationTitle} Complete`}
+                {isError && `${operationTitle} Failed`}
+              </Text>
+              <Text variant="small" className="text-slate-600">
+                {message}
+              </Text>
+            </div>
+
+            {isPending && (
+              <Text variant="small" className="italic text-slate-500">
+                Check your library in a few minutes.
+              </Text>
+            )}
+
+            {toolName && (
+              <Text variant="small" className="text-slate-400">
+                Tool: {toolName}
+              </Text>
+            )}
+          </Card>
+        </div>
+      </div>
+    </div>
+  );
+}

autogpt_platform/frontend/src/components/contextual/Chat/components/ToolResponseMessage/ToolResponseMessage.tsx

@@ -1,7 +1,14 @@
+import { Text } from "@/components/atoms/Text/Text";
+import { cn } from "@/lib/utils";
 import type { ToolResult } from "@/types/chat";
+import { WarningCircleIcon } from "@phosphor-icons/react";
 import { AIChatBubble } from "../AIChatBubble/AIChatBubble";
 import { MarkdownContent } from "../MarkdownContent/MarkdownContent";
-import { formatToolResponse } from "./helpers";
+import {
+  formatToolResponse,
+  getErrorMessage,
+  isErrorResponse,
+} from "./helpers";
 
 export interface ToolResponseMessageProps {
   toolId?: string;
@@ -18,6 +25,24 @@ export function ToolResponseMessage({
   success: _success,
   className,
 }: ToolResponseMessageProps) {
+  if (isErrorResponse(result)) {
+    const errorMessage = getErrorMessage(result);
+    return (
+      <AIChatBubble className={className}>
+        <div className="flex items-center gap-2">
+          <WarningCircleIcon
+            size={14}
+            weight="regular"
+            className="shrink-0 text-neutral-400"
+          />
+          <Text variant="small" className={cn("text-xs text-neutral-500")}>
+            {errorMessage}
+          </Text>
+        </div>
+      </AIChatBubble>
+    );
+  }
+
   const formattedText = formatToolResponse(result, toolName);
 
   return (

autogpt_platform/frontend/src/components/contextual/Chat/components/ToolResponseMessage/helpers.ts

@@ -1,3 +1,42 @@
+function stripInternalReasoning(content: string): string {
+  return content
+    .replace(/<internal_reasoning>[\s\S]*?<\/internal_reasoning>/gi, "")
+    .replace(/<thinking>[\s\S]*?<\/thinking>/gi, "")
+    .replace(/\n{3,}/g, "\n\n")
+    .trim();
+}
+
+export function isErrorResponse(result: unknown): boolean {
+  if (typeof result === "string") {
+    const lower = result.toLowerCase();
+    return (
+      lower.startsWith("error:") ||
+      lower.includes("not found") ||
+      lower.includes("does not exist") ||
+      lower.includes("failed to") ||
+      lower.includes("unable to")
+    );
+  }
+  if (typeof result === "object" && result !== null) {
+    const response = result as Record<string, unknown>;
+    return response.type === "error" || response.error !== undefined;
+  }
+  return false;
+}
+
+export function getErrorMessage(result: unknown): string {
+  if (typeof result === "string") {
+    return stripInternalReasoning(result.replace(/^error:\s*/i, ""));
+  }
+  if (typeof result === "object" && result !== null) {
+    const response = result as Record<string, unknown>;
+    if (response.error) return stripInternalReasoning(String(response.error));
+    if (response.message)
+      return stripInternalReasoning(String(response.message));
+  }
+  return "An error occurred";
+}
+
 function getToolCompletionPhrase(toolName: string): string {
   const toolCompletionPhrases: Record<string, string> = {
     add_understanding: "Updated your business information",
@@ -28,10 +67,10 @@ export function formatToolResponse(result: unknown, toolName: string): string {
         const parsed = JSON.parse(trimmed);
         return formatToolResponse(parsed, toolName);
       } catch {
-        return trimmed;
+        return stripInternalReasoning(trimmed);
       }
     }
-    return result;
+    return stripInternalReasoning(result);
   }
 
   if (typeof result !== "object" || result === null) {

autogpt_platform/frontend/src/components/contextual/Chat/components/UserChatBubble/UserChatBubble.tsx

@@ -10,7 +10,7 @@ export function UserChatBubble({ children, className }: UserChatBubbleProps) {
   return (
     <div
       className={cn(
-        "group relative min-w-20 overflow-hidden rounded-xl bg-purple-100 px-3 text-right text-[1rem] leading-relaxed transition-all duration-500 ease-in-out",
+        "group relative min-w-20 overflow-hidden rounded-xl bg-purple-100 px-3 text-left text-[1rem] leading-relaxed transition-all duration-500 ease-in-out",
         className,
       )}
       style={{

autogpt_platform/frontend/src/components/contextual/Chat/stream-executor.ts

@@ -0,0 +1,142 @@
+import type {
+  ActiveStream,
+  StreamChunk,
+  VercelStreamChunk,
+} from "./chat-types";
+import {
+  INITIAL_RETRY_DELAY,
+  MAX_RETRIES,
+  normalizeStreamChunk,
+  parseSSELine,
+} from "./stream-utils";
+
+function notifySubscribers(stream: ActiveStream, chunk: StreamChunk) {
+  stream.chunks.push(chunk);
+  for (const callback of stream.onChunkCallbacks) {
+    try {
+      callback(chunk);
+    } catch (err) {
+      console.warn("[StreamExecutor] Subscriber callback error:", err);
+    }
+  }
+}
+
+export async function executeStream(
+  stream: ActiveStream,
+  message: string,
+  isUserMessage: boolean,
+  context?: { url: string; content: string },
+  retryCount: number = 0,
+): Promise<void> {
+  const { sessionId, abortController } = stream;
+
+  try {
+    const url = `/api/chat/sessions/${sessionId}/stream`;
+    const body = JSON.stringify({
+      message,
+      is_user_message: isUserMessage,
+      context: context || null,
+    });
+
+    const response = await fetch(url, {
+      method: "POST",
+      headers: {
+        "Content-Type": "application/json",
+        Accept: "text/event-stream",
+      },
+      body,
+      signal: abortController.signal,
+    });
+
+    if (!response.ok) {
+      const errorText = await response.text();
+      throw new Error(errorText || `HTTP ${response.status}`);
+    }
+
+    if (!response.body) {
+      throw new Error("Response body is null");
+    }
+
+    const reader = response.body.getReader();
+    const decoder = new TextDecoder();
+    let buffer = "";
+
+    while (true) {
+      const { done, value } = await reader.read();
+
+      if (done) {
+        notifySubscribers(stream, { type: "stream_end" });
+        stream.status = "completed";
+        return;
+      }
+
+      buffer += decoder.decode(value, { stream: true });
+      const lines = buffer.split("\n");
+      buffer = lines.pop() || "";
+
+      for (const line of lines) {
+        const data = parseSSELine(line);
+        if (data !== null) {
+          if (data === "[DONE]") {
+            notifySubscribers(stream, { type: "stream_end" });
+            stream.status = "completed";
+            return;
+          }
+
+          try {
+            const rawChunk = JSON.parse(data) as
+              | StreamChunk
+              | VercelStreamChunk;
+            const chunk = normalizeStreamChunk(rawChunk);
+            if (!chunk) continue;
+
+            notifySubscribers(stream, chunk);
+
+            if (chunk.type === "stream_end") {
+              stream.status = "completed";
+              return;
+            }
+
+            if (chunk.type === "error") {
+              stream.status = "error";
+              stream.error = new Error(
+                chunk.message || chunk.content || "Stream error",
+              );
+              return;
+            }
+          } catch (err) {
+            console.warn("[StreamExecutor] Failed to parse SSE chunk:", err);
+          }
+        }
+      }
+    }
+  } catch (err) {
+    if (err instanceof Error && err.name === "AbortError") {
+      notifySubscribers(stream, { type: "stream_end" });
+      stream.status = "completed";
+      return;
+    }
+
+    if (retryCount < MAX_RETRIES) {
+      const retryDelay = INITIAL_RETRY_DELAY * Math.pow(2, retryCount);
+      console.log(
+        `[StreamExecutor] Retrying in ${retryDelay}ms (attempt ${retryCount + 1}/${MAX_RETRIES})`,
+      );
+      await new Promise((resolve) => setTimeout(resolve, retryDelay));
+      return executeStream(
+        stream,
+        message,
+        isUserMessage,
+        context,
+        retryCount + 1,
+      );
+    }
+
+    stream.status = "error";
+    stream.error = err instanceof Error ? err : new Error("Stream failed");
+    notifySubscribers(stream, {
+      type: "error",
+      message: stream.error.message,
+    });
+  }
+}

autogpt_platform/frontend/src/components/contextual/Chat/stream-utils.ts

@@ -0,0 +1,84 @@
+import type { ToolArguments, ToolResult } from "@/types/chat";
+import type { StreamChunk, VercelStreamChunk } from "./chat-types";
+
+const LEGACY_STREAM_TYPES = new Set<StreamChunk["type"]>([
+  "text_chunk",
+  "text_ended",
+  "tool_call",
+  "tool_call_start",
+  "tool_response",
+  "login_needed",
+  "need_login",
+  "credentials_needed",
+  "error",
+  "usage",
+  "stream_end",
+]);
+
+export function isLegacyStreamChunk(
+  chunk: StreamChunk | VercelStreamChunk,
+): chunk is StreamChunk {
+  return LEGACY_STREAM_TYPES.has(chunk.type as StreamChunk["type"]);
+}
+
+export function normalizeStreamChunk(
+  chunk: StreamChunk | VercelStreamChunk,
+): StreamChunk | null {
+  if (isLegacyStreamChunk(chunk)) return chunk;
+
+  switch (chunk.type) {
+    case "text-delta":
+      return { type: "text_chunk", content: chunk.delta };
+    case "text-end":
+      return { type: "text_ended" };
+    case "tool-input-available":
+      return {
+        type: "tool_call_start",
+        tool_id: chunk.toolCallId,
+        tool_name: chunk.toolName,
+        arguments: chunk.input as ToolArguments,
+      };
+    case "tool-output-available":
+      return {
+        type: "tool_response",
+        tool_id: chunk.toolCallId,
+        tool_name: chunk.toolName,
+        result: chunk.output as ToolResult,
+        success: chunk.success ?? true,
+      };
+    case "usage":
+      return {
+        type: "usage",
+        promptTokens: chunk.promptTokens,
+        completionTokens: chunk.completionTokens,
+        totalTokens: chunk.totalTokens,
+      };
+    case "error":
+      return {
+        type: "error",
+        message: chunk.errorText,
+        code: chunk.code,
+        details: chunk.details,
+      };
+    case "finish":
+      return { type: "stream_end" };
+    case "start":
+    case "text-start":
+      return null;
+    case "tool-input-start":
+      return {
+        type: "tool_call_start",
+        tool_id: chunk.toolCallId,
+        tool_name: chunk.toolName,
+        arguments: {},
+      };
+  }
+}
+
+export const MAX_RETRIES = 3;
+export const INITIAL_RETRY_DELAY = 1000;
+
+export function parseSSELine(line: string): string | null {
+  if (line.startsWith("data: ")) return line.slice(6);
+  return null;
+}

autogpt_platform/frontend/src/components/contextual/Chat/useChat.ts

@@ -2,7 +2,6 @@
 
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
 import { useEffect, useRef, useState } from "react";
-import { toast } from "sonner";
 import { useChatSession } from "./useChatSession";
 import { useChatStream } from "./useChatStream";
 
@@ -27,6 +26,7 @@ export function useChat({ urlSessionId }: UseChatArgs = {}) {
     claimSession,
     clearSession: clearSessionBase,
     loadSession,
+    startPollingForOperation,
   } = useChatSession({
     urlSessionId,
     autoCreate: false,
@@ -67,38 +67,16 @@ export function useChat({ urlSessionId }: UseChatArgs = {}) {
     ],
   );
 
-  useEffect(() => {
-    if (isLoading || isCreating) {
-      const timer = setTimeout(() => {
-        setShowLoader(true);
-      }, 300);
-      return () => clearTimeout(timer);
-    } else {
+  useEffect(
+    function showLoaderWithDelay() {
+      if (isLoading || isCreating) {
+        const timer = setTimeout(() => setShowLoader(true), 300);
+        return () => clearTimeout(timer);
+      }
       setShowLoader(false);
-    }
-  }, [isLoading, isCreating]);
-
-  useEffect(function monitorNetworkStatus() {
-    function handleOnline() {
-      toast.success("Connection restored", {
-        description: "You're back online",
-      });
-    }
-
-    function handleOffline() {
-      toast.error("You're offline", {
-        description: "Check your internet connection",
-      });
-    }
-
-    window.addEventListener("online", handleOnline);
-    window.addEventListener("offline", handleOffline);
-
-    return () => {
-      window.removeEventListener("online", handleOnline);
-      window.removeEventListener("offline", handleOffline);
-    };
-  }, []);
+    },
+    [isLoading, isCreating],
+  );
 
   function clearSession() {
     clearSessionBase();
@@ -117,5 +95,6 @@ export function useChat({ urlSessionId }: UseChatArgs = {}) {
     loadSession,
     sessionId: sessionIdFromHook,
     showLoader,
+    startPollingForOperation,
   };
 }

autogpt_platform/frontend/src/components/contextual/Chat/useChatDrawer.ts

@@ -1,17 +0,0 @@
-"use client";
-
-import { create } from "zustand";
-
-interface ChatDrawerState {
-  isOpen: boolean;
-  open: () => void;
-  close: () => void;
-  toggle: () => void;
-}
-
-export const useChatDrawer = create<ChatDrawerState>((set) => ({
-  isOpen: false,
-  open: () => set({ isOpen: true }),
-  close: () => set({ isOpen: false }),
-  toggle: () => set((state) => ({ isOpen: !state.isOpen })),
-}));

autogpt_platform/frontend/src/components/contextual/Chat/useChatSession.ts

@@ -1,6 +1,7 @@
 import {
   getGetV2GetSessionQueryKey,
   getGetV2GetSessionQueryOptions,
+  getGetV2ListSessionsQueryKey,
   postV2CreateSession,
   useGetV2GetSession,
   usePatchV2SessionAssignUser,
@@ -58,6 +59,7 @@ export function useChatSession({
     query: {
       enabled: !!sessionId,
       select: okData,
+      staleTime: 0,
       retry: shouldRetrySessionLoad,
       retryDelay: getSessionRetryDelay,
     },
@@ -101,6 +103,125 @@ export function useChatSession({
     }
   }, [createError, loadError]);
 
+  // Track if we should be polling (set by external callers when they receive operation_started via SSE)
+  const [forcePolling, setForcePolling] = useState(false);
+  // Track if we've seen server acknowledge the pending operation (to avoid clearing forcePolling prematurely)
+  const hasSeenServerPendingRef = useRef(false);
+
+  // Check if there are any pending operations in the messages
+  // Must check all operation types: operation_pending, operation_started, operation_in_progress
+  const hasPendingOperationsFromServer = useMemo(() => {
+    if (!messages || messages.length === 0) return false;
+    const pendingTypes = new Set([
+      "operation_pending",
+      "operation_in_progress",
+      "operation_started",
+    ]);
+    return messages.some((msg) => {
+      if (msg.role !== "tool" || !msg.content) return false;
+      try {
+        const content =
+          typeof msg.content === "string"
+            ? JSON.parse(msg.content)
+            : msg.content;
+        return pendingTypes.has(content?.type);
+      } catch {
+        return false;
+      }
+    });
+  }, [messages]);
+
+  // Track when server has acknowledged the pending operation
+  useEffect(() => {
+    if (hasPendingOperationsFromServer) {
+      hasSeenServerPendingRef.current = true;
+    }
+  }, [hasPendingOperationsFromServer]);
+
+  // Combined: poll if server has pending ops OR if we received operation_started via SSE
+  const hasPendingOperations = hasPendingOperationsFromServer || forcePolling;
+
+  // Clear forcePolling only after server has acknowledged AND completed the operation
+  useEffect(() => {
+    if (
+      forcePolling &&
+      !hasPendingOperationsFromServer &&
+      hasSeenServerPendingRef.current
+    ) {
+      // Server acknowledged the operation and it's now complete
+      setForcePolling(false);
+      hasSeenServerPendingRef.current = false;
+    }
+  }, [forcePolling, hasPendingOperationsFromServer]);
+
+  // Function to trigger polling (called when operation_started is received via SSE)
+  function startPollingForOperation() {
+    setForcePolling(true);
+    hasSeenServerPendingRef.current = false; // Reset for new operation
+  }
+
+  // Refresh sessions list when a pending operation completes
+  // (hasPendingOperations transitions from true to false)
+  const prevHasPendingOperationsRef = useRef(hasPendingOperations);
+  useEffect(
+    function refreshSessionsListOnOperationComplete() {
+      const wasHasPending = prevHasPendingOperationsRef.current;
+      prevHasPendingOperationsRef.current = hasPendingOperations;
+
+      // Only invalidate when transitioning from pending to not pending
+      if (wasHasPending && !hasPendingOperations && sessionId) {
+        queryClient.invalidateQueries({
+          queryKey: getGetV2ListSessionsQueryKey(),
+        });
+      }
+    },
+    [hasPendingOperations, sessionId, queryClient],
+  );
+
+  // Poll for updates when there are pending operations
+  // Backoff: 2s, 4s, 6s, 8s, 10s, ... up to 30s max
+  const pollAttemptRef = useRef(0);
+  const hasPendingOperationsRef = useRef(hasPendingOperations);
+  hasPendingOperationsRef.current = hasPendingOperations;
+
+  useEffect(
+    function pollForPendingOperations() {
+      if (!sessionId || !hasPendingOperations) {
+        pollAttemptRef.current = 0;
+        return;
+      }
+
+      let cancelled = false;
+      let timeoutId: ReturnType<typeof setTimeout> | null = null;
+
+      function schedule() {
+        // 2s, 4s, 6s, 8s, 10s, ... 30s (max)
+        const delay = Math.min((pollAttemptRef.current + 1) * 2000, 30000);
+        timeoutId = setTimeout(async () => {
+          if (cancelled) return;
+          pollAttemptRef.current += 1;
+          try {
+            await refetch();
+          } catch (err) {
+            console.error("[useChatSession] Poll failed:", err);
+          } finally {
+            if (!cancelled && hasPendingOperationsRef.current) {
+              schedule();
+            }
+          }
+        }, delay);
+      }
+
+      schedule();
+
+      return () => {
+        cancelled = true;
+        if (timeoutId) clearTimeout(timeoutId);
+      };
+    },
+    [sessionId, hasPendingOperations, refetch],
+  );
+
   async function createSession() {
     try {
       setError(null);
@@ -227,11 +348,13 @@ export function useChatSession({
     isCreating,
     error,
     isSessionNotFound: isNotFoundError(loadError),
+    hasPendingOperations,
     createSession,
     loadSession,
     refreshSession,
     claimSession,
     clearSession,
+    startPollingForOperation,
   };
 }
 

autogpt_platform/frontend/src/components/contextual/Chat/useChatStream.ts

@@ -1,543 +1,110 @@
-import type { ToolArguments, ToolResult } from "@/types/chat";
-import { useCallback, useEffect, useRef, useState } from "react";
+"use client";
+
+import { useEffect, useRef, useState } from "react";
 import { toast } from "sonner";
+import { useChatStore } from "./chat-store";
+import type { StreamChunk } from "./chat-types";
 
-const MAX_RETRIES = 3;
-const INITIAL_RETRY_DELAY = 1000;
-
-export interface StreamChunk {
-  type:
-    | "text_chunk"
-    | "text_ended"
-    | "tool_call"
-    | "tool_call_start"
-    | "tool_response"
-    | "login_needed"
-    | "need_login"
-    | "credentials_needed"
-    | "error"
-    | "usage"
-    | "stream_end";
-  timestamp?: string;
-  content?: string;
-  message?: string;
-  code?: string;
-  details?: Record<string, unknown>;
-  tool_id?: string;
-  tool_name?: string;
-  arguments?: ToolArguments;
-  result?: ToolResult;
-  success?: boolean;
-  idx?: number;
-  session_id?: string;
-  agent_info?: {
-    graph_id: string;
-    name: string;
-    trigger_type: string;
-  };
-  provider?: string;
-  provider_name?: string;
-  credential_type?: string;
-  scopes?: string[];
-  title?: string;
-  [key: string]: unknown;
-}
-
-type VercelStreamChunk =
-  | { type: "start"; messageId: string }
-  | { type: "finish" }
-  | { type: "text-start"; id: string }
-  | { type: "text-delta"; id: string; delta: string }
-  | { type: "text-end"; id: string }
-  | { type: "tool-input-start"; toolCallId: string; toolName: string }
-  | {
-      type: "tool-input-available";
-      toolCallId: string;
-      toolName: string;
-      input: ToolArguments;
-    }
-  | {
-      type: "tool-output-available";
-      toolCallId: string;
-      toolName?: string;
-      output: ToolResult;
-      success?: boolean;
-    }
-  | {
-      type: "usage";
-      promptTokens: number;
-      completionTokens: number;
-      totalTokens: number;
-    }
-  | {
-      type: "error";
-      errorText: string;
-      code?: string;
-      details?: Record<string, unknown>;
-    };
-
-const LEGACY_STREAM_TYPES = new Set<StreamChunk["type"]>([
-  "text_chunk",
-  "text_ended",
-  "tool_call",
-  "tool_call_start",
-  "tool_response",
-  "login_needed",
-  "need_login",
-  "credentials_needed",
-  "error",
-  "usage",
-  "stream_end",
-]);
-
-function isLegacyStreamChunk(
-  chunk: StreamChunk | VercelStreamChunk,
-): chunk is StreamChunk {
-  return LEGACY_STREAM_TYPES.has(chunk.type as StreamChunk["type"]);
-}
-
-function normalizeStreamChunk(
-  chunk: StreamChunk | VercelStreamChunk,
-): StreamChunk | null {
-  if (isLegacyStreamChunk(chunk)) {
-    return chunk;
-  }
-  switch (chunk.type) {
-    case "text-delta":
-      return { type: "text_chunk", content: chunk.delta };
-    case "text-end":
-      return { type: "text_ended" };
-    case "tool-input-available":
-      return {
-        type: "tool_call_start",
-        tool_id: chunk.toolCallId,
-        tool_name: chunk.toolName,
-        arguments: chunk.input,
-      };
-    case "tool-output-available":
-      return {
-        type: "tool_response",
-        tool_id: chunk.toolCallId,
-        tool_name: chunk.toolName,
-        result: chunk.output,
-        success: chunk.success ?? true,
-      };
-    case "usage":
-      return {
-        type: "usage",
-        promptTokens: chunk.promptTokens,
-        completionTokens: chunk.completionTokens,
-        totalTokens: chunk.totalTokens,
-      };
-    case "error":
-      return {
-        type: "error",
-        message: chunk.errorText,
-        code: chunk.code,
-        details: chunk.details,
-      };
-    case "finish":
-      return { type: "stream_end" };
-    case "start":
-    case "text-start":
-      return null;
-    case "tool-input-start":
-      const toolInputStart = chunk as Extract<
-        VercelStreamChunk,
-        { type: "tool-input-start" }
-      >;
-      return {
-        type: "tool_call_start",
-        tool_id: toolInputStart.toolCallId,
-        tool_name: toolInputStart.toolName,
-        arguments: {},
-      };
-  }
-}
+export type { StreamChunk } from "./chat-types";
 
 export function useChatStream() {
   const [isStreaming, setIsStreaming] = useState(false);
   const [error, setError] = useState<Error | null>(null);
-  const retryCountRef = useRef<number>(0);
-  const retryTimeoutRef = useRef<NodeJS.Timeout | null>(null);
-  const abortControllerRef = useRef<AbortController | null>(null);
   const currentSessionIdRef = useRef<string | null>(null);
-  const requestStartTimeRef = useRef<number | null>(null);
-
-  const stopStreaming = useCallback(
-    (sessionId?: string, force: boolean = false) => {
-      console.log("[useChatStream] stopStreaming called", {
-        hasAbortController: !!abortControllerRef.current,
-        isAborted: abortControllerRef.current?.signal.aborted,
-        currentSessionId: currentSessionIdRef.current,
-        requestedSessionId: sessionId,
-        requestStartTime: requestStartTimeRef.current,
-        timeSinceStart: requestStartTimeRef.current
-          ? Date.now() - requestStartTimeRef.current
-          : null,
-        force,
-        stack: new Error().stack,
-      });
-
-      if (
-        sessionId &&
-        currentSessionIdRef.current &&
-        currentSessionIdRef.current !== sessionId
-      ) {
-        console.log(
-          "[useChatStream] Session changed, aborting previous stream",
-          {
-            oldSessionId: currentSessionIdRef.current,
-            newSessionId: sessionId,
-          },
-        );
-      }
-
-      const controller = abortControllerRef.current;
-      if (controller) {
-        const timeSinceStart = requestStartTimeRef.current
-          ? Date.now() - requestStartTimeRef.current
-          : null;
-
-        if (!force && timeSinceStart !== null && timeSinceStart < 100) {
-          console.log(
-            "[useChatStream] Request just started (<100ms), skipping abort to prevent race condition",
-            {
-              timeSinceStart,
-            },
-          );
-          return;
-        }
-
-        try {
-          const signal = controller.signal;
-
-          if (
-            signal &&
-            typeof signal.aborted === "boolean" &&
-            !signal.aborted
-          ) {
-            console.log("[useChatStream] Aborting stream");
-            controller.abort();
-          } else {
-            console.log(
-              "[useChatStream] Stream already aborted or signal invalid",
-            );
-          }
-        } catch (error) {
-          if (error instanceof Error && error.name === "AbortError") {
-            console.log(
-              "[useChatStream] AbortError caught (expected during cleanup)",
-            );
-          } else {
-            console.warn("[useChatStream] Error aborting stream:", error);
-          }
-        } finally {
-          abortControllerRef.current = null;
-          requestStartTimeRef.current = null;
-        }
-      }
-      if (retryTimeoutRef.current) {
-        clearTimeout(retryTimeoutRef.current);
-        retryTimeoutRef.current = null;
-      }
-      setIsStreaming(false);
-    },
-    [],
+  const onChunkCallbackRef = useRef<((chunk: StreamChunk) => void) | null>(
+    null,
   );
 
+  const stopStream = useChatStore((s) => s.stopStream);
+  const unregisterActiveSession = useChatStore(
+    (s) => s.unregisterActiveSession,
+  );
+  const isSessionActive = useChatStore((s) => s.isSessionActive);
+  const onStreamComplete = useChatStore((s) => s.onStreamComplete);
+  const getCompletedStream = useChatStore((s) => s.getCompletedStream);
+  const registerActiveSession = useChatStore((s) => s.registerActiveSession);
+  const startStream = useChatStore((s) => s.startStream);
+  const getStreamStatus = useChatStore((s) => s.getStreamStatus);
+
+  function stopStreaming(sessionId?: string) {
+    const targetSession = sessionId || currentSessionIdRef.current;
+    if (targetSession) {
+      stopStream(targetSession);
+      unregisterActiveSession(targetSession);
+    }
+    setIsStreaming(false);
+  }
+
   useEffect(() => {
-    console.log("[useChatStream] Component mounted");
-    return () => {
-      const sessionIdAtUnmount = currentSessionIdRef.current;
-      console.log(
-        "[useChatStream] Component unmounting, calling stopStreaming",
-        {
-          sessionIdAtUnmount,
-        },
-      );
-      stopStreaming(undefined, false);
+    return function cleanup() {
+      const sessionId = currentSessionIdRef.current;
+      if (sessionId && !isSessionActive(sessionId)) {
+        stopStream(sessionId);
+      }
       currentSessionIdRef.current = null;
+      onChunkCallbackRef.current = null;
     };
-  }, [stopStreaming]);
+  }, []);
 
-  const sendMessage = useCallback(
-    async (
-      sessionId: string,
-      message: string,
-      onChunk: (chunk: StreamChunk) => void,
-      isUserMessage: boolean = true,
-      context?: { url: string; content: string },
-      isRetry: boolean = false,
-    ) => {
-      console.log("[useChatStream] sendMessage called", {
-        sessionId,
-        message: message.substring(0, 50),
-        isUserMessage,
-        isRetry,
-        stack: new Error().stack,
-      });
+  useEffect(() => {
+    const unsubscribe = onStreamComplete(
+      function handleStreamComplete(completedSessionId) {
+        if (completedSessionId !== currentSessionIdRef.current) return;
 
-      const previousSessionId = currentSessionIdRef.current;
-      stopStreaming(sessionId, true);
-      currentSessionIdRef.current = sessionId;
-
-      const abortController = new AbortController();
-      abortControllerRef.current = abortController;
-      requestStartTimeRef.current = Date.now();
-      console.log("[useChatStream] Created new AbortController", {
-        sessionId,
-        previousSessionId,
-        requestStartTime: requestStartTimeRef.current,
-      });
-
-      if (abortController.signal.aborted) {
-        console.warn(
-          "[useChatStream] AbortController was aborted before request started",
-        );
-        requestStartTimeRef.current = null;
-        return Promise.reject(new Error("Request aborted"));
-      }
-
-      if (!isRetry) {
-        retryCountRef.current = 0;
-      }
-      setIsStreaming(true);
-      setError(null);
-
-      try {
-        const url = `/api/chat/sessions/${sessionId}/stream`;
-        const body = JSON.stringify({
-          message,
-          is_user_message: isUserMessage,
-          context: context || null,
-        });
-
-        const response = await fetch(url, {
-          method: "POST",
-          headers: {
-            "Content-Type": "application/json",
-            Accept: "text/event-stream",
-          },
-          body,
-          signal: abortController.signal,
-        });
-
-        console.info("[useChatStream] Stream response", {
-          sessionId,
-          status: response.status,
-          ok: response.ok,
-          contentType: response.headers.get("content-type"),
-        });
-
-        if (!response.ok) {
-          const errorText = await response.text();
-          console.warn("[useChatStream] Stream response error", {
-            sessionId,
-            status: response.status,
-            errorText,
-          });
-          throw new Error(errorText || `HTTP ${response.status}`);
-        }
-
-        if (!response.body) {
-          console.warn("[useChatStream] Response body is null", { sessionId });
-          throw new Error("Response body is null");
-        }
-
-        const reader = response.body.getReader();
-        const decoder = new TextDecoder();
-        let buffer = "";
-        let receivedChunkCount = 0;
-        let firstChunkAt: number | null = null;
-        let loggedLineCount = 0;
-
-        return new Promise<void>((resolve, reject) => {
-          let didDispatchStreamEnd = false;
-
-          function dispatchStreamEnd() {
-            if (didDispatchStreamEnd) return;
-            didDispatchStreamEnd = true;
-            onChunk({ type: "stream_end" });
-          }
-
-          const cleanup = () => {
-            reader.cancel().catch(() => {
-              // Ignore cancel errors
-            });
-          };
-
-          async function readStream() {
-            try {
-              while (true) {
-                const { done, value } = await reader.read();
-
-                if (done) {
-                  cleanup();
-                  console.info("[useChatStream] Stream closed", {
-                    sessionId,
-                    receivedChunkCount,
-                    timeSinceStart: requestStartTimeRef.current
-                      ? Date.now() - requestStartTimeRef.current
-                      : null,
-                  });
-                  dispatchStreamEnd();
-                  retryCountRef.current = 0;
-                  stopStreaming();
-                  resolve();
-                  return;
-                }
-
-                buffer += decoder.decode(value, { stream: true });
-                const lines = buffer.split("\n");
-                buffer = lines.pop() || "";
-
-                for (const line of lines) {
-                  if (line.startsWith("data: ")) {
-                    const data = line.slice(6);
-                    if (loggedLineCount < 3) {
-                      console.info("[useChatStream] Raw stream line", {
-                        sessionId,
-                        data:
-                          data.length > 300 ? `${data.slice(0, 300)}...` : data,
-                      });
-                      loggedLineCount += 1;
-                    }
-                    if (data === "[DONE]") {
-                      cleanup();
-                      console.info("[useChatStream] Stream done marker", {
-                        sessionId,
-                        receivedChunkCount,
-                        timeSinceStart: requestStartTimeRef.current
-                          ? Date.now() - requestStartTimeRef.current
-                          : null,
-                      });
-                      dispatchStreamEnd();
-                      retryCountRef.current = 0;
-                      stopStreaming();
-                      resolve();
-                      return;
-                    }
-
-                    try {
-                      const rawChunk = JSON.parse(data) as
-                        | StreamChunk
-                        | VercelStreamChunk;
-                      const chunk = normalizeStreamChunk(rawChunk);
-                      if (!chunk) {
-                        continue;
-                      }
-
-                      if (!firstChunkAt) {
-                        firstChunkAt = Date.now();
-                        console.info("[useChatStream] First stream chunk", {
-                          sessionId,
-                          chunkType: chunk.type,
-                          timeSinceStart: requestStartTimeRef.current
-                            ? firstChunkAt - requestStartTimeRef.current
-                            : null,
-                        });
-                      }
-                      receivedChunkCount += 1;
-
-                      // Call the chunk handler
-                      onChunk(chunk);
-
-                      // Handle stream lifecycle
-                      if (chunk.type === "stream_end") {
-                        didDispatchStreamEnd = true;
-                        cleanup();
-                        console.info("[useChatStream] Stream end chunk", {
-                          sessionId,
-                          receivedChunkCount,
-                          timeSinceStart: requestStartTimeRef.current
-                            ? Date.now() - requestStartTimeRef.current
-                            : null,
-                        });
-                        retryCountRef.current = 0;
-                        stopStreaming();
-                        resolve();
-                        return;
-                      } else if (chunk.type === "error") {
-                        cleanup();
-                        reject(
-                          new Error(
-                            chunk.message || chunk.content || "Stream error",
-                          ),
-                        );
-                        return;
-                      }
-                    } catch (err) {
-                      // Skip invalid JSON lines
-                      console.warn("Failed to parse SSE chunk:", err, data);
-                    }
-                  }
-                }
-              }
-            } catch (err) {
-              if (err instanceof Error && err.name === "AbortError") {
-                cleanup();
-                dispatchStreamEnd();
-                stopStreaming();
-                resolve();
-                return;
-              }
-
-              const streamError =
-                err instanceof Error ? err : new Error("Failed to read stream");
-
-              if (retryCountRef.current < MAX_RETRIES) {
-                retryCountRef.current += 1;
-                const retryDelay =
-                  INITIAL_RETRY_DELAY * Math.pow(2, retryCountRef.current - 1);
-
-                toast.info("Connection interrupted", {
-                  description: `Retrying in ${retryDelay / 1000} seconds...`,
-                });
-
-                retryTimeoutRef.current = setTimeout(() => {
-                  sendMessage(
-                    sessionId,
-                    message,
-                    onChunk,
-                    isUserMessage,
-                    context,
-                    true,
-                  ).catch((_err) => {
-                    // Retry failed
-                  });
-                }, retryDelay);
-              } else {
-                setError(streamError);
-                toast.error("Connection Failed", {
-                  description:
-                    "Unable to connect to chat service. Please try again.",
-                });
-                cleanup();
-                dispatchStreamEnd();
-                retryCountRef.current = 0;
-                stopStreaming();
-                reject(streamError);
-              }
-            }
-          }
-
-          readStream();
-        });
-      } catch (err) {
-        if (err instanceof Error && err.name === "AbortError") {
-          setIsStreaming(false);
-          return Promise.resolve();
-        }
-        const streamError =
-          err instanceof Error ? err : new Error("Failed to start stream");
-        setError(streamError);
         setIsStreaming(false);
-        throw streamError;
+        const completed = getCompletedStream(completedSessionId);
+        if (completed?.error) {
+          setError(completed.error);
+        }
+        unregisterActiveSession(completedSessionId);
+      },
+    );
+
+    return unsubscribe;
+  }, []);
+
+  async function sendMessage(
+    sessionId: string,
+    message: string,
+    onChunk: (chunk: StreamChunk) => void,
+    isUserMessage: boolean = true,
+    context?: { url: string; content: string },
+  ) {
+    const previousSessionId = currentSessionIdRef.current;
+    if (previousSessionId && previousSessionId !== sessionId) {
+      stopStreaming(previousSessionId);
+    }
+
+    currentSessionIdRef.current = sessionId;
+    onChunkCallbackRef.current = onChunk;
+    setIsStreaming(true);
+    setError(null);
+
+    registerActiveSession(sessionId);
+
+    try {
+      await startStream(sessionId, message, isUserMessage, context, onChunk);
+
+      const status = getStreamStatus(sessionId);
+      if (status === "error") {
+        const completed = getCompletedStream(sessionId);
+        if (completed?.error) {
+          setError(completed.error);
+          toast.error("Connection Failed", {
+            description: "Unable to connect to chat service. Please try again.",
+          });
+          throw completed.error;
+        }
       }
-    },
-    [stopStreaming],
-  );
+    } catch (err) {
+      const streamError =
+        err instanceof Error ? err : new Error("Failed to start stream");
+      setError(streamError);
+      throw streamError;
+    } finally {
+      setIsStreaming(false);
+    }
+  }
 
   return {
     isStreaming,

autogpt_platform/frontend/src/providers/posthog/posthog-provider.tsx

@@ -9,11 +9,12 @@ import { ReactNode, useEffect, useRef } from "react";
 
 export function PostHogProvider({ children }: { children: ReactNode }) {
   const isPostHogEnabled = environment.isPostHogEnabled();
+  const postHogCredentials = environment.getPostHogCredentials();
 
   useEffect(() => {
-    if (process.env.NEXT_PUBLIC_POSTHOG_KEY) {
-      posthog.init(process.env.NEXT_PUBLIC_POSTHOG_KEY, {
-        api_host: process.env.NEXT_PUBLIC_POSTHOG_HOST,
+    if (postHogCredentials.key) {
+      posthog.init(postHogCredentials.key, {
+        api_host: postHogCredentials.host,
         defaults: "2025-11-30",
         capture_pageview: false,
         capture_pageleave: true,

autogpt_platform/frontend/src/services/network-status/NetworkStatusMonitor.tsx

@@ -0,0 +1,8 @@
+"use client";
+
+import { useNetworkStatus } from "./useNetworkStatus";
+
+export function NetworkStatusMonitor() {
+  useNetworkStatus();
+  return null;
+}

autogpt_platform/frontend/src/services/network-status/useNetworkStatus.ts

@@ -0,0 +1,28 @@
+"use client";
+
+import { useEffect } from "react";
+import { toast } from "sonner";
+
+export function useNetworkStatus() {
+  useEffect(function monitorNetworkStatus() {
+    function handleOnline() {
+      toast.success("Connection restored", {
+        description: "You're back online",
+      });
+    }
+
+    function handleOffline() {
+      toast.error("You're offline", {
+        description: "Check your internet connection",
+      });
+    }
+
+    window.addEventListener("online", handleOnline);
+    window.addEventListener("offline", handleOffline);
+
+    return function cleanup() {
+      window.removeEventListener("online", handleOnline);
+      window.removeEventListener("offline", handleOffline);
+    };
+  }, []);
+}

autogpt_platform/frontend/src/services/storage/session-storage.ts

@@ -3,6 +3,7 @@ import { environment } from "../environment";
 
 export enum SessionKey {
   CHAT_SENT_INITIAL_PROMPTS = "chat_sent_initial_prompts",
+  CHAT_INITIAL_PROMPTS = "chat_initial_prompts",
 }
 
 function get(key: SessionKey) {

backend/blocks/video/__init__.py

@@ -1 +0,0 @@
-# Video editing blocks