fix(platform): evaluate chat flag after auth for correct redirect (#11873)

Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>

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 import execute_tool, get_tool, tools
-from .tools.models import ErrorResponse
+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):
+# Default system prompt used when Langfuse is not configured
-    """Raised when Langfuse is required but 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:
@@ -394,6 +528,27 @@ async def stream_chat_completion(
                     if isinstance(chunk.output, str)
                     else orjson.dumps(chunk.output).decode("utf-8")
                 )
+                # 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",
@@ -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
+    For tools marked with `is_long_running=True` (like agent generation), spawns a
-    the SSE connection alive through proxies and load balancers.
+    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/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/library/db.py

@@ -21,7 +21,7 @@ from backend.data.model import CredentialsMetaInput
 from backend.integrations.creds_manager import IntegrationCredentialsManager
 from backend.integrations.webhooks.graph_lifecycle_hooks import on_graph_activate
 from backend.util.clients import get_scheduler_client
-from backend.util.exceptions import DatabaseError, NotFoundError
+from backend.util.exceptions import DatabaseError, InvalidInputError, NotFoundError
 from backend.util.json import SafeJson
 from backend.util.models import Pagination
 from backend.util.settings import Config
@@ -64,11 +64,11 @@ async def list_library_agents(
 
     if page < 1 or page_size < 1:
         logger.warning(f"Invalid pagination: page={page}, page_size={page_size}")
-        raise DatabaseError("Invalid pagination input")
+        raise InvalidInputError("Invalid pagination input")
 
     if search_term and len(search_term.strip()) > 100:
         logger.warning(f"Search term too long: {repr(search_term)}")
-        raise DatabaseError("Search term is too long")
+        raise InvalidInputError("Search term is too long")
 
     where_clause: prisma.types.LibraryAgentWhereInput = {
         "userId": user_id,
@@ -175,7 +175,7 @@ async def list_favorite_library_agents(
 
     if page < 1 or page_size < 1:
         logger.warning(f"Invalid pagination: page={page}, page_size={page_size}")
-        raise DatabaseError("Invalid pagination input")
+        raise InvalidInputError("Invalid pagination input")
 
     where_clause: prisma.types.LibraryAgentWhereInput = {
         "userId": user_id,

autogpt_platform/backend/backend/api/features/library/routes/agents.py

@@ -1,4 +1,3 @@
-import logging
 from typing import Literal, Optional
 
 import autogpt_libs.auth as autogpt_auth_lib
@@ -6,15 +5,11 @@ from fastapi import APIRouter, Body, HTTPException, Query, Security, status
 from fastapi.responses import Response
 from prisma.enums import OnboardingStep
 
-import backend.api.features.store.exceptions as store_exceptions
 from backend.data.onboarding import complete_onboarding_step
-from backend.util.exceptions import DatabaseError, NotFoundError
 
 from .. import db as library_db
 from .. import model as library_model
 
-logger = logging.getLogger(__name__)
-
 router = APIRouter(
     prefix="/agents",
     tags=["library", "private"],
@@ -26,10 +21,6 @@ router = APIRouter(
     "",
     summary="List Library Agents",
     response_model=library_model.LibraryAgentResponse,
-    responses={
-        200: {"description": "List of library agents"},
-        500: {"description": "Server error", "content": {"application/json": {}}},
-    },
 )
 async def list_library_agents(
     user_id: str = Security(autogpt_auth_lib.get_user_id),
@@ -53,22 +44,7 @@ async def list_library_agents(
 ) -> library_model.LibraryAgentResponse:
     """
     Get all agents in the user's library (both created and saved).
-
-    Args:
-        user_id: ID of the authenticated user.
-        search_term: Optional search term to filter agents by name/description.
-        filter_by: List of filters to apply (favorites, created by user).
-        sort_by: List of sorting criteria (created date, updated date).
-        page: Page number to retrieve.
-        page_size: Number of agents per page.
-
-    Returns:
-        A LibraryAgentResponse containing agents and pagination metadata.
-
-    Raises:
-        HTTPException: If a server/database error occurs.
     """
-    try:
     return await library_db.list_library_agents(
         user_id=user_id,
         search_term=search_term,
@@ -76,20 +52,11 @@ async def list_library_agents(
         page=page,
         page_size=page_size,
     )
-    except Exception as e:
-        logger.error(f"Could not list library agents for user #{user_id}: {e}")
-        raise HTTPException(
-            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
-            detail=str(e),
-        ) from e
 
 
 @router.get(
     "/favorites",
     summary="List Favorite Library Agents",
-    responses={
-        500: {"description": "Server error", "content": {"application/json": {}}},
-    },
 )
 async def list_favorite_library_agents(
     user_id: str = Security(autogpt_auth_lib.get_user_id),
@@ -106,30 +73,12 @@ async def list_favorite_library_agents(
 ) -> library_model.LibraryAgentResponse:
     """
     Get all favorite agents in the user's library.
-
-    Args:
-        user_id: ID of the authenticated user.
-        page: Page number to retrieve.
-        page_size: Number of agents per page.
-
-    Returns:
-        A LibraryAgentResponse containing favorite agents and pagination metadata.
-
-    Raises:
-        HTTPException: If a server/database error occurs.
     """
-    try:
     return await library_db.list_favorite_library_agents(
         user_id=user_id,
         page=page,
         page_size=page_size,
     )
-    except Exception as e:
-        logger.error(f"Could not list favorite library agents for user #{user_id}: {e}")
-        raise HTTPException(
-            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
-            detail=str(e),
-        ) from e
 
 
 @router.get("/{library_agent_id}", summary="Get Library Agent")
@@ -162,10 +111,6 @@ async def get_library_agent_by_graph_id(
     summary="Get Agent By Store ID",
     tags=["store", "library"],
     response_model=library_model.LibraryAgent | None,
-    responses={
-        200: {"description": "Library agent found"},
-        404: {"description": "Agent not found"},
-    },
 )
 async def get_library_agent_by_store_listing_version_id(
     store_listing_version_id: str,
@@ -174,32 +119,15 @@ async def get_library_agent_by_store_listing_version_id(
     """
     Get Library Agent from Store Listing Version ID.
     """
-    try:
     return await library_db.get_library_agent_by_store_version_id(
         store_listing_version_id, user_id
     )
-    except NotFoundError as e:
-        raise HTTPException(
-            status_code=status.HTTP_404_NOT_FOUND,
-            detail=str(e),
-        )
-    except Exception as e:
-        logger.error(f"Could not fetch library agent from store version ID: {e}")
-        raise HTTPException(
-            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
-            detail=str(e),
-        ) from e
 
 
 @router.post(
     "",
     summary="Add Marketplace Agent",
     status_code=status.HTTP_201_CREATED,
-    responses={
-        201: {"description": "Agent added successfully"},
-        404: {"description": "Store listing version not found"},
-        500: {"description": "Server error"},
-    },
 )
 async def add_marketplace_agent_to_library(
     store_listing_version_id: str = Body(embed=True),
@@ -210,59 +138,19 @@ async def add_marketplace_agent_to_library(
 ) -> library_model.LibraryAgent:
     """
     Add an agent from the marketplace to the user's library.
-
-    Args:
-        store_listing_version_id: ID of the store listing version to add.
-        user_id: ID of the authenticated user.
-
-    Returns:
-        library_model.LibraryAgent: Agent added to the library
-
-    Raises:
-        HTTPException(404): If the listing version is not found.
-        HTTPException(500): If a server/database error occurs.
     """
-    try:
     agent = await library_db.add_store_agent_to_library(
         store_listing_version_id=store_listing_version_id,
         user_id=user_id,
     )
     if source != "onboarding":
-            await complete_onboarding_step(
+        await complete_onboarding_step(user_id, OnboardingStep.MARKETPLACE_ADD_AGENT)
-                user_id, OnboardingStep.MARKETPLACE_ADD_AGENT
-            )
     return agent
 
-    except store_exceptions.AgentNotFoundError as e:
-        logger.warning(
-            f"Could not find store listing version {store_listing_version_id} "
-            "to add to library"
-        )
-        raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=str(e))
-    except DatabaseError as e:
-        logger.error(f"Database error while adding agent to library: {e}", e)
-        raise HTTPException(
-            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
-            detail={"message": str(e), "hint": "Inspect DB logs for details."},
-        ) from e
-    except Exception as e:
-        logger.error(f"Unexpected error while adding agent to library: {e}")
-        raise HTTPException(
-            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
-            detail={
-                "message": str(e),
-                "hint": "Check server logs for more information.",
-            },
-        ) from e
-
 
 @router.patch(
     "/{library_agent_id}",
     summary="Update Library Agent",
-    responses={
-        200: {"description": "Agent updated successfully"},
-        500: {"description": "Server error"},
-    },
 )
 async def update_library_agent(
     library_agent_id: str,
@@ -271,16 +159,7 @@ async def update_library_agent(
 ) -> library_model.LibraryAgent:
     """
     Update the library agent with the given fields.
-
-    Args:
-        library_agent_id: ID of the library agent to update.
-        payload: Fields to update (auto_update_version, is_favorite, etc.).
-        user_id: ID of the authenticated user.
-
-    Raises:
-        HTTPException(500): If a server/database error occurs.
     """
-    try:
     return await library_db.update_library_agent(
         library_agent_id=library_agent_id,
         user_id=user_id,
@@ -290,33 +169,11 @@ async def update_library_agent(
         is_archived=payload.is_archived,
         settings=payload.settings,
     )
-    except NotFoundError as e:
-        raise HTTPException(
-            status_code=status.HTTP_404_NOT_FOUND,
-            detail=str(e),
-        ) from e
-    except DatabaseError as e:
-        logger.error(f"Database error while updating library agent: {e}")
-        raise HTTPException(
-            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
-            detail={"message": str(e), "hint": "Verify DB connection."},
-        ) from e
-    except Exception as e:
-        logger.error(f"Unexpected error while updating library agent: {e}")
-        raise HTTPException(
-            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
-            detail={"message": str(e), "hint": "Check server logs."},
-        ) from e
 
 
 @router.delete(
     "/{library_agent_id}",
     summary="Delete Library Agent",
-    responses={
-        204: {"description": "Agent deleted successfully"},
-        404: {"description": "Agent not found"},
-        500: {"description": "Server error"},
-    },
 )
 async def delete_library_agent(
     library_agent_id: str,
@@ -324,28 +181,11 @@ async def delete_library_agent(
 ) -> Response:
     """
     Soft-delete the specified library agent.
-
-    Args:
-        library_agent_id: ID of the library agent to delete.
-        user_id: ID of the authenticated user.
-
-    Returns:
-        204 No Content if successful.
-
-    Raises:
-        HTTPException(404): If the agent does not exist.
-        HTTPException(500): If a server/database error occurs.
     """
-    try:
     await library_db.delete_library_agent(
         library_agent_id=library_agent_id, user_id=user_id
     )
     return Response(status_code=status.HTTP_204_NO_CONTENT)
-    except NotFoundError as e:
-        raise HTTPException(
-            status_code=status.HTTP_404_NOT_FOUND,
-            detail=str(e),
-        ) from e
 
 
 @router.post("/{library_agent_id}/fork", summary="Fork Library Agent")

autogpt_platform/backend/backend/api/features/library/routes_test.py

@@ -118,21 +118,6 @@ async def test_get_library_agents_success(
     )
 
 
-def test_get_library_agents_error(mocker: pytest_mock.MockFixture, test_user_id: str):
-    mock_db_call = mocker.patch("backend.api.features.library.db.list_library_agents")
-    mock_db_call.side_effect = Exception("Test error")
-
-    response = client.get("/agents?search_term=test")
-    assert response.status_code == 500
-    mock_db_call.assert_called_once_with(
-        user_id=test_user_id,
-        search_term="test",
-        sort_by=library_model.LibraryAgentSort.UPDATED_AT,
-        page=1,
-        page_size=15,
-    )
-
-
 @pytest.mark.asyncio
 async def test_get_favorite_library_agents_success(
     mocker: pytest_mock.MockFixture,
@@ -190,23 +175,6 @@ async def test_get_favorite_library_agents_success(
     )
 
 
-def test_get_favorite_library_agents_error(
-    mocker: pytest_mock.MockFixture, test_user_id: str
-):
-    mock_db_call = mocker.patch(
-        "backend.api.features.library.db.list_favorite_library_agents"
-    )
-    mock_db_call.side_effect = Exception("Test error")
-
-    response = client.get("/agents/favorites")
-    assert response.status_code == 500
-    mock_db_call.assert_called_once_with(
-        user_id=test_user_id,
-        page=1,
-        page_size=15,
-    )
-
-
 def test_add_agent_to_library_success(
     mocker: pytest_mock.MockFixture, test_user_id: str
 ):
@@ -258,19 +226,3 @@ def test_add_agent_to_library_success(
         store_listing_version_id="test-version-id", user_id=test_user_id
     )
     mock_complete_onboarding.assert_awaited_once()
-
-
-def test_add_agent_to_library_error(mocker: pytest_mock.MockFixture, test_user_id: str):
-    mock_db_call = mocker.patch(
-        "backend.api.features.library.db.add_store_agent_to_library"
-    )
-    mock_db_call.side_effect = Exception("Test error")
-
-    response = client.post(
-        "/agents", json={"store_listing_version_id": "test-version-id"}
-    )
-    assert response.status_code == 500
-    assert "detail" in response.json()  # Verify error response structure
-    mock_db_call.assert_called_once_with(
-        store_listing_version_id="test-version-id", user_id=test_user_id
-    )

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

@@ -454,6 +454,7 @@ async def backfill_all_content_types(batch_size: int = 10) -> dict[str, Any]:
     total_processed = 0
     total_success = 0
     total_failed = 0
+    all_errors: dict[str, int] = {}  # Aggregate errors across all content types
 
     # Process content types in explicit order
     processing_order = [
@@ -499,23 +500,12 @@ async def backfill_all_content_types(batch_size: int = 10) -> dict[str, Any]:
             success = sum(1 for result in results if result is True)
             failed = len(results) - success
 
-            # Aggregate unique errors to avoid Sentry spam
+            # Aggregate errors across all content types
             if failed > 0:
-                # Group errors by type and message
-                error_summary: dict[str, int] = {}
                 for result in results:
                     if isinstance(result, Exception):
                         error_key = f"{type(result).__name__}: {str(result)}"
-                        error_summary[error_key] = error_summary.get(error_key, 0) + 1
+                        all_errors[error_key] = all_errors.get(error_key, 0) + 1
-
-                # Log aggregated error summary
-                error_details = ", ".join(
-                    f"{error} ({count}x)" for error, count in error_summary.items()
-                )
-                logger.error(
-                    f"{content_type.value}: {failed}/{len(results)} embeddings failed. "
-                    f"Errors: {error_details}"
-                )
 
             results_by_type[content_type.value] = {
                 "processed": len(missing_items),
@@ -542,6 +532,13 @@ async def backfill_all_content_types(batch_size: int = 10) -> dict[str, Any]:
                 "error": str(e),
             }
 
+    # Log aggregated errors once at the end
+    if all_errors:
+        error_details = ", ".join(
+            f"{error} ({count}x)" for error, count in all_errors.items()
+        )
+        logger.error(f"Embedding backfill errors: {error_details}")
+
     return {
         "by_type": results_by_type,
         "totals": {

autogpt_platform/backend/backend/api/features/v1.py

@@ -261,14 +261,36 @@ async def get_onboarding_agents(
     return await get_recommended_agents(user_id)
 
 
+class OnboardingStatusResponse(pydantic.BaseModel):
+    """Response for onboarding status check."""
+
+    is_onboarding_enabled: bool
+    is_chat_enabled: bool
+
+
 @v1_router.get(
     "/onboarding/enabled",
     summary="Is onboarding enabled",
     tags=["onboarding", "public"],
-    dependencies=[Security(requires_user)],
+    response_model=OnboardingStatusResponse,
 )
-async def is_onboarding_enabled() -> bool:
+async def is_onboarding_enabled(
-    return await onboarding_enabled()
+    user_id: Annotated[str, Security(get_user_id)],
+) -> OnboardingStatusResponse:
+    # Check if chat is enabled for user
+    is_chat_enabled = await is_feature_enabled(Flag.CHAT, user_id, False)
+
+    # If chat is enabled, skip legacy onboarding
+    if is_chat_enabled:
+        return OnboardingStatusResponse(
+            is_onboarding_enabled=False,
+            is_chat_enabled=True,
+        )
+
+    return OnboardingStatusResponse(
+        is_onboarding_enabled=await onboarding_enabled(),
+        is_chat_enabled=False,
+    )
 
 
 @v1_router.post(

autogpt_platform/backend/backend/data/onboarding.py

@@ -41,6 +41,7 @@ FrontendOnboardingStep = Literal[
     OnboardingStep.AGENT_NEW_RUN,
     OnboardingStep.AGENT_INPUT,
     OnboardingStep.CONGRATS,
+    OnboardingStep.VISIT_COPILOT,
     OnboardingStep.MARKETPLACE_VISIT,
     OnboardingStep.BUILDER_OPEN,
 ]
@@ -122,6 +123,9 @@ async def update_user_onboarding(user_id: str, data: UserOnboardingUpdate):
 async def _reward_user(user_id: str, onboarding: UserOnboarding, step: OnboardingStep):
     reward = 0
     match step:
+        # Welcome bonus for visiting copilot ($5 = 500 credits)
+        case OnboardingStep.VISIT_COPILOT:
+            reward = 500
         # Reward user when they clicked New Run during onboarding
         # This is because they need credits before scheduling a run (next step)
         # This is seen as a reward for the GET_RESULTS step in the wallet

autogpt_platform/backend/backend/util/exceptions.py

@@ -135,6 +135,12 @@ class GraphValidationError(ValueError):
         )
 
 
+class InvalidInputError(ValueError):
+    """Raised when user input validation fails (e.g., search term too long)"""
+
+    pass
+
+
 class DatabaseError(Exception):
     """Raised when there is an error interacting with the database"""
 

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,
+        default=600,
-        description="The timeout in seconds for Agent Generator service requests",
+        description="The timeout in seconds for Agent Generator service requests (includes retries for rate limits)",
     )
 
     enable_example_blocks: bool = Field(

autogpt_platform/backend/migrations/20260127211502_add_visit_copilot_onboarding_step/migration.sql

@@ -0,0 +1,2 @@
+-- AlterEnum
+ALTER TYPE "OnboardingStep" ADD VALUE 'VISIT_COPILOT';

autogpt_platform/backend/schema.prisma

@@ -81,6 +81,7 @@ enum OnboardingStep {
   AGENT_INPUT
   CONGRATS
   // First Wins
+  VISIT_COPILOT
   GET_RESULTS
   MARKETPLACE_VISIT
   MARKETPLACE_ADD_AGENT

autogpt_platform/frontend/src/app/(no-navbar)/onboarding/page.tsx

@@ -2,8 +2,9 @@
 import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
 import { useRouter } from "next/navigation";
 import { useEffect } from "react";
-import { resolveResponse, shouldShowOnboarding } from "@/app/api/helpers";
+import { resolveResponse, getOnboardingStatus } from "@/app/api/helpers";
 import { getV1OnboardingState } from "@/app/api/__generated__/endpoints/onboarding/onboarding";
+import { getHomepageRoute } from "@/lib/constants";
 
 export default function OnboardingPage() {
   const router = useRouter();
@@ -11,10 +12,13 @@ export default function OnboardingPage() {
   useEffect(() => {
     async function redirectToStep() {
       try {
-        // Check if onboarding is enabled
+        // Check if onboarding is enabled (also gets chat flag for redirect)
-        const isEnabled = await shouldShowOnboarding();
+        const { shouldShowOnboarding, isChatEnabled } =
-        if (!isEnabled) {
+          await getOnboardingStatus();
-          router.replace("/");
+        const homepageRoute = getHomepageRoute(isChatEnabled);
+
+        if (!shouldShowOnboarding) {
+          router.replace(homepageRoute);
           return;
         }
 
@@ -22,7 +26,7 @@ export default function OnboardingPage() {
 
         // Handle completed onboarding
         if (onboarding.completedSteps.includes("GET_RESULTS")) {
-          router.replace("/");
+          router.replace(homepageRoute);
           return;
         }
 

autogpt_platform/frontend/src/app/(platform)/auth/callback/route.ts

@@ -1,8 +1,9 @@
 import { getServerSupabase } from "@/lib/supabase/server/getServerSupabase";
+import { getHomepageRoute } from "@/lib/constants";
 import BackendAPI from "@/lib/autogpt-server-api";
 import { NextResponse } from "next/server";
 import { revalidatePath } from "next/cache";
-import { shouldShowOnboarding } from "@/app/api/helpers";
+import { getOnboardingStatus } from "@/app/api/helpers";
 
 // Handle the callback to complete the user session login
 export async function GET(request: Request) {
@@ -25,11 +26,15 @@ export async function GET(request: Request) {
         const api = new BackendAPI();
         await api.createUser();
 
-        if (await shouldShowOnboarding()) {
+        // Get onboarding status from backend (includes chat flag evaluated for this user)
+        const { shouldShowOnboarding, isChatEnabled } =
+          await getOnboardingStatus();
+        if (shouldShowOnboarding) {
           next = "/onboarding";
           revalidatePath("/onboarding", "layout");
         } else {
-          revalidatePath("/", "layout");
+          next = getHomepageRoute(isChatEnabled);
+          revalidatePath(next, "layout");
         }
       } catch (createUserError) {
         console.error("Error creating user:", createUserError);

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 { useCopilotStore } from "../../copilot-page-store";
 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";
@@ -20,38 +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 setNewChatHandler = useCopilotStore((s) => s.setNewChatHandler);
-  const requestNewChat = useCopilotStore((s) => s.requestNewChat);
-
-  useEffect(
-    function registerNewChatHandler() {
-      setNewChatHandler(handleNewChat);
-      return function cleanup() {
-        setNewChatHandler(null);
-      };
-    },
-    [handleNewChat],
-  );
-
-  function handleNewChatClick() {
-    requestNewChat();
-  }
-
   if (!isLoggedIn) {
     return (
       <div className="flex h-full items-center justify-center">
@@ -72,7 +53,7 @@ export function CopilotShell({ children }: Props) {
           isLoading={isLoading}
           hasNextPage={hasNextPage}
           isFetchingNextPage={isFetchingNextPage}
-          onSelectSession={handleSelectSession}
+          onSelectSession={handleSessionClick}
           onFetchNextPage={fetchNextPage}
           onNewChat={handleNewChatClick}
           hasActiveSession={Boolean(hasActiveSession)}
@@ -82,7 +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>
 
@@ -94,7 +86,7 @@ export function CopilotShell({ children }: Props) {
           isLoading={isLoading}
           hasNextPage={hasNextPage}
           isFetchingNextPage={isFetchingNextPage}
-          onSelectSession={handleSelectSession}
+          onSelectSession={handleSessionClick}
           onFetchNextPage={fetchNextPage}
           onNewChat={handleNewChatClick}
           onClose={handleCloseDrawer}

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

@@ -1,11 +1,6 @@
-import {
+import { useGetV2ListSessions } from "@/app/api/__generated__/endpoints/chat/chat";
-  getGetV2ListSessionsQueryKey,
-  useGetV2ListSessions,
-} from "@/app/api/__generated__/endpoints/chat/chat";
 import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
 import { okData } from "@/app/api/helpers";
-import { useChatStore } from "@/components/contextual/Chat/chat-store";
-import { useQueryClient } from "@tanstack/react-query";
 import { useEffect, useState } from "react";
 
 const PAGE_SIZE = 50;
@@ -16,12 +11,12 @@ 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 queryClient = useQueryClient();
-  const onStreamComplete = useChatStore((state) => state.onStreamComplete);
 
   const { data, isLoading, isFetching, isError } = useGetV2ListSessions(
     { limit: PAGE_SIZE, offset },
@@ -32,20 +27,7 @@ export function useSessionsPagination({ enabled }: UseSessionsPaginationArgs) {
     },
   );
 
-  useEffect(function refreshOnStreamComplete() {
+  useEffect(() => {
-    const unsubscribe = onStreamComplete(function handleStreamComplete() {
-      setOffset(0);
-      setAccumulatedSessions([]);
-      setTotalCount(null);
-      queryClient.invalidateQueries({
-        queryKey: getGetV2ListSessionsQueryKey(),
-      });
-    });
-    return unsubscribe;
-  }, []);
-
-  useEffect(
-    function updateSessionsFromResponse() {
     const responseData = okData(data);
     if (responseData) {
       const newSessions = responseData.sessions;
@@ -61,9 +43,7 @@ export function useSessionsPagination({ enabled }: UseSessionsPaginationArgs) {
       setAccumulatedSessions([]);
       setTotalCount(null);
     }
-    },
+  }, [data, offset, enabled]);
-    [data, offset, enabled],
-  );
 
   const hasNextPage =
     totalCount !== null && accumulatedSessions.length < totalCount;
@@ -86,17 +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

@@ -104,76 +104,3 @@ export function mergeCurrentSessionIntoList(
 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,
-) {
-  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,
-) {
-  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 +1,22 @@
 "use client";
 
 import {
+  getGetV2GetSessionQueryKey,
   getGetV2ListSessionsQueryKey,
   useGetV2GetSession,
 } from "@/app/api/__generated__/endpoints/chat/chat";
-import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
 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 { parseAsString, useQueryState } from "nuqs";
 import { usePathname, useSearchParams } from "next/navigation";
-import { useEffect, useRef, useState } from "react";
+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 { getCurrentSessionId } from "./helpers";
-import {
+import { useShellSessionList } from "./useShellSessionList";
-  checkReadyToShowContent,
-  convertSessionDetailToSummary,
-  filterVisibleSessions,
-  getCurrentSessionId,
-  mergeCurrentSessionIntoList,
-} from "./helpers";
 
 export function useCopilotShell() {
   const pathname = usePathname();
@@ -31,7 +27,7 @@ export function useCopilotShell() {
   const isMobile =
     breakpoint === "base" || breakpoint === "sm" || breakpoint === "md";
 
-  const [, setUrlSessionId] = useQueryState("sessionId", parseAsString);
+  const { urlSessionId, setUrlSessionId } = useCopilotSessionId();
 
   const isOnHomepage = pathname === "/copilot";
   const paramSessionId = searchParams.get("sessionId");
@@ -45,123 +41,80 @@ 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 } =
+  const { data: currentSessionData } = useGetV2GetSession(
-    useGetV2GetSession(currentSessionId || "", {
+    currentSessionId || "",
+    {
       query: {
         enabled: !!currentSessionId,
         select: okData,
       },
-    });
+    },
-
-  const [hasAutoSelectedSession, setHasAutoSelectedSession] = useState(false);
-  const hasAutoSelectedRef = useRef(false);
-  const recentlyCreatedSessionsRef = useRef<
-    Map<string, SessionSummaryResponse>
-  >(new Map());
-
-  // 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]);
-
-  // Track newly created sessions to ensure they stay visible even when switching away
-  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]);
 
-  // Clean up recently created sessions that are now in the accumulated list
+  const {
-  useEffect(() => {
+    sessions,
-    for (const sessionId of recentlyCreatedSessionsRef.current.keys()) {
+    isLoading,
-      if (accumulatedSessions.some((s) => s.id === sessionId)) {
+    isSessionsFetching,
-        recentlyCreatedSessionsRef.current.delete(sessionId);
+    hasNextPage,
-      }
+    fetchNextPage,
-    }
+    resetPagination,
-  }, [accumulatedSessions]);
+    recentlyCreatedSessionsRef,
-
+  } = useShellSessionList({
-  // Reset pagination when query becomes disabled
+    paginationEnabled,
-  const prevPaginationEnabledRef = useRef(paginationEnabled);
-  useEffect(() => {
-    if (prevPaginationEnabledRef.current && !paginationEnabled) {
-      resetPagination();
-      resetAutoSelect();
-    }
-    prevPaginationEnabledRef.current = paginationEnabled;
-  }, [paginationEnabled, resetPagination]);
-
-  const sessions = mergeCurrentSessionIntoList(
-    accumulatedSessions,
     currentSessionId,
     currentSessionData,
-    recentlyCreatedSessionsRef.current,
+    isOnHomepage,
-  );
-
-  const visibleSessions = filterVisibleSessions(sessions);
-
-  const sidebarSelectedSessionId =
-    isOnHomepage && !paramSessionId ? null : currentSessionId;
-
-  const isReadyToShowContent = isOnHomepage
-    ? true
-    : checkReadyToShowContent(
-        areAllSessionsLoaded,
     paramSessionId,
-        accumulatedSessions,
+  });
-        isCurrentSessionLoading,
-        currentSessionData,
-        hasAutoSelectedSession,
-      );
 
-  function handleSelectSession(sessionId: string) {
+  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 pendingActionRef = useRef<(() => void) | null>(null);
+
+  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() {
+  function startNewChat() {
-    resetAutoSelect();
     resetPagination();
     queryClient.invalidateQueries({
       queryKey: getGetV2ListSessionsQueryKey(),
@@ -170,12 +123,31 @@ export function useCopilotShell() {
     if (isMobile) handleCloseDrawer();
   }
 
-  function resetAutoSelect() {
+  function handleSessionClick(sessionId: string) {
-    hasAutoSelectedRef.current = false;
+    if (sessionId === currentSessionId) return;
-    setHasAutoSelectedSession(false);
+
+    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,
@@ -183,17 +155,17 @@ export function useCopilotShell() {
     isLoggedIn,
     hasActiveSession:
       Boolean(currentSessionId) && (!isOnHomepage || Boolean(paramSessionId)),
-    isLoading,
+    isLoading: isLoading || isCreatingSession,
-    sessions: visibleSessions,
+    isCreatingSession,
-    currentSessionId: sidebarSelectedSessionId,
+    sessions,
-    handleSelectSession,
+    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

@@ -4,51 +4,53 @@ import { create } from "zustand";
 
 interface CopilotStoreState {
   isStreaming: boolean;
-  isNewChatModalOpen: boolean;
+  isSwitchingSession: boolean;
-  newChatHandler: (() => void) | null;
+  isCreatingSession: boolean;
+  isInterruptModalOpen: boolean;
+  pendingAction: (() => void) | null;
 }
 
 interface CopilotStoreActions {
   setIsStreaming: (isStreaming: boolean) => void;
-  setNewChatHandler: (handler: (() => void) | null) => void;
+  setIsSwitchingSession: (isSwitchingSession: boolean) => void;
-  requestNewChat: () => void;
+  setIsCreatingSession: (isCreating: boolean) => void;
-  confirmNewChat: () => void;
+  openInterruptModal: (onConfirm: () => void) => void;
-  cancelNewChat: () => void;
+  confirmInterrupt: () => void;
+  cancelInterrupt: () => void;
 }
 
 type CopilotStore = CopilotStoreState & CopilotStoreActions;
 
 export const useCopilotStore = create<CopilotStore>((set, get) => ({
   isStreaming: false,
-  isNewChatModalOpen: false,
+  isSwitchingSession: false,
-  newChatHandler: null,
+  isCreatingSession: false,
+  isInterruptModalOpen: false,
+  pendingAction: null,
 
   setIsStreaming(isStreaming) {
     set({ isStreaming });
   },
 
-  setNewChatHandler(handler) {
+  setIsSwitchingSession(isSwitchingSession) {
-    set({ newChatHandler: handler });
+    set({ isSwitchingSession });
   },
 
-  requestNewChat() {
+  setIsCreatingSession(isCreatingSession) {
-    const { isStreaming, newChatHandler } = get();
+    set({ isCreatingSession });
-    if (isStreaming) {
-      set({ isNewChatModalOpen: true });
-    } else if (newChatHandler) {
-      newChatHandler();
-    }
   },
 
-  confirmNewChat() {
+  openInterruptModal(onConfirm) {
-    const { newChatHandler } = get();
+    set({ isInterruptModalOpen: true, pendingAction: onConfirm });
-    set({ isNewChatModalOpen: false });
-    if (newChatHandler) {
-      newChatHandler();
-    }
   },
 
-  cancelNewChat() {
+  confirmInterrupt() {
-    set({ isNewChatModalOpen: false });
+    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/page.tsx

@@ -1,25 +1,25 @@
 "use client";
 
 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 confirmNewChat = useCopilotStore((s) => s.confirmNewChat);
+  const isInterruptModalOpen = useCopilotStore((s) => s.isInterruptModalOpen);
+  const confirmInterrupt = useCopilotStore((s) => s.confirmInterrupt);
+  const cancelInterrupt = useCopilotStore((s) => s.cancelInterrupt);
   const {
     greetingName,
     quickActions,
     isLoading,
-    pageState,
+    hasSession,
-    isNewChatModalOpen,
+    initialPrompt,
     isReady,
   } = state;
   const {
@@ -27,20 +27,16 @@ export default function CopilotPage() {
     startChatWithPrompt,
     handleSessionNotFound,
     handleStreamingChange,
-    handleCancelNewChat,
-    handleNewChatModalOpen,
   } = handlers;
 
   if (!isReady) return null;
 
-  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={initialPrompt}
-          initialPrompt={pageState.initialPrompt}
           onSessionNotFound={handleSessionNotFound}
           onStreamingChange={handleStreamingChange}
         />
@@ -48,31 +44,33 @@ export default function CopilotPage() {
           title="Interrupt current chat?"
           styling={{ maxWidth: 300, width: "100%" }}
           controlled={{
-            isOpen: isNewChatModalOpen,
+            isOpen: isInterruptModalOpen,
-            set: handleNewChatModalOpen,
+            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={confirmNewChat}
+                  onClick={confirmInterrupt}
                 >
-                  Start new chat
+                  Continue
                 </Button>
               </Dialog.Footer>
             </div>
@@ -82,19 +80,6 @@ export default function CopilotPage() {
     );
   }
 
-  if (pageState.type === "newChat" || 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>
-    );
-  }
-
   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

@@ -5,79 +5,40 @@ import {
 import { useToast } from "@/components/molecules/Toast/use-toast";
 import { getHomepageRoute } from "@/lib/constants";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
+import { useOnboarding } from "@/providers/onboarding/onboarding-provider";
 import {
   Flag,
   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 { useEffect } from "react";
 import { useCopilotStore } from "./copilot-page-store";
-import { getGreetingName, getQuickActions, type PageState } from "./helpers";
+import { getGreetingName, getQuickActions } from "./helpers";
-import { useCopilotURLState } from "./useCopilotURLState";
+import { useCopilotSessionId } from "./useCopilotSessionId";
-
-type CopilotState = {
-  pageState: PageState;
-  initialPrompts: Record<string, string>;
-  previousSessionId: string | null;
-};
-
-type CopilotAction =
-  | { type: "setPageState"; pageState: PageState }
-  | { 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 === "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;
-}
 
 export function useCopilotPage() {
   const router = useRouter();
   const queryClient = useQueryClient();
   const { user, isLoggedIn, isUserLoading } = useSupabase();
   const { toast } = useToast();
+  const { completeStep } = useOnboarding();
 
-  const isNewChatModalOpen = useCopilotStore((s) => s.isNewChatModalOpen);
+  const { urlSessionId, setUrlSessionId } = useCopilotSessionId();
   const setIsStreaming = useCopilotStore((s) => s.setIsStreaming);
-  const cancelNewChat = useCopilotStore((s) => s.cancelNewChat);
+  const isCreating = useCopilotStore((s) => s.isCreatingSession);
+  const setIsCreating = useCopilotStore((s) => s.setIsCreatingSession);
+
+  // Complete VISIT_COPILOT onboarding step to grant $5 welcome bonus
+  useEffect(() => {
+    if (isLoggedIn) {
+      completeStep("VISIT_COPILOT");
+    }
+  }, [completeStep, isLoggedIn]);
 
   const isChatEnabled = useGetFlag(Flag.CHAT);
   const flags = useFlags<FlagValues>();
@@ -88,72 +49,27 @@ export function useCopilotPage() {
   const isFlagReady =
     !isLaunchDarklyConfigured || flags[Flag.CHAT] !== undefined;
 
-  const [state, dispatch] = useReducer(copilotReducer, {
-    pageState: { type: "welcome" },
-    initialPrompts: {},
-    previousSessionId: null,
-  });
-
   const greetingName = getGreetingName(user);
   const quickActions = getQuickActions();
 
-  function setPageState(pageState: PageState) {
+  const hasSession = Boolean(urlSessionId);
-    dispatch({ type: "setPageState", pageState });
+  const initialPrompt = urlSessionId
-  }
+    ? getInitialPrompt(urlSessionId)
+    : undefined;
 
-  function setInitialPrompt(sessionId: string, prompt: string) {
+  useEffect(() => {
-    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 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]);
-    [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({
+    setIsCreating(true);
-      type: "setPageState",
-      pageState: { type: "creating", prompt: trimmedPrompt },
-    });
 
     try {
       const sessionResponse = await postV2CreateSession({
@@ -165,27 +81,19 @@ 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 });
+      await setUrlSessionId(sessionId, { shallow: true });
-      dispatch({
-        type: "setPageState",
-        pageState: { type: "chat", sessionId, initialPrompt: trimmedPrompt },
-      });
     } 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);
     }
   }
 
@@ -201,21 +109,13 @@ export function useCopilotPage() {
     setIsStreaming(isStreamingValue);
   }
 
-  function handleCancelNewChat() {
-    cancelNewChat();
-  }
-
-  function handleNewChatModalOpen(isOpen: boolean) {
-    if (!isOpen) cancelNewChat();
-  }
-
   return {
     state: {
       greetingName,
       quickActions,
       isLoading: isUserLoading,
-      pageState: state.pageState,
+      hasSession,
-      isNewChatModalOpen,
+      initialPrompt,
       isReady: isFlagReady && isChatEnabled !== false && isLoggedIn,
     },
     handlers: {
@@ -223,8 +123,32 @@ export function useCopilotPage() {
       startChatWithPrompt,
       handleSessionNotFound,
       handleStreamingChange,
-      handleCancelNewChat,
-      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)/login/actions.ts

@@ -1,10 +1,11 @@
 "use server";
 
+import { getHomepageRoute } from "@/lib/constants";
 import BackendAPI from "@/lib/autogpt-server-api";
 import { getServerSupabase } from "@/lib/supabase/server/getServerSupabase";
 import { loginFormSchema } from "@/types/auth";
 import * as Sentry from "@sentry/nextjs";
-import { shouldShowOnboarding } from "../../api/helpers";
+import { getOnboardingStatus } from "../../api/helpers";
 
 export async function login(email: string, password: string) {
   try {
@@ -36,11 +37,15 @@ export async function login(email: string, password: string) {
     const api = new BackendAPI();
     await api.createUser();
 
-    const onboarding = await shouldShowOnboarding();
+    // Get onboarding status from backend (includes chat flag evaluated for this user)
+    const { shouldShowOnboarding, isChatEnabled } = await getOnboardingStatus();
+    const next = shouldShowOnboarding
+      ? "/onboarding"
+      : getHomepageRoute(isChatEnabled);
 
     return {
       success: true,
-      onboarding,
+      next,
     };
   } catch (err) {
     Sentry.captureException(err);

autogpt_platform/frontend/src/app/(platform)/login/useLoginPage.ts

@@ -97,13 +97,8 @@ export function useLoginPage() {
         throw new Error(result.error || "Login failed");
       }
 
-      if (nextUrl) {
+      // Prefer URL's next parameter, then use backend-determined route
-        router.replace(nextUrl);
+      router.replace(nextUrl || result.next || homepageRoute);
-      } else if (result.onboarding) {
-        router.replace("/onboarding");
-      } else {
-        router.replace(homepageRoute);
-      }
     } catch (error) {
       toast({
         title:

autogpt_platform/frontend/src/app/(platform)/signup/actions.ts

@@ -5,14 +5,13 @@ import { getServerSupabase } from "@/lib/supabase/server/getServerSupabase";
 import { signupFormSchema } from "@/types/auth";
 import * as Sentry from "@sentry/nextjs";
 import { isWaitlistError, logWaitlistError } from "../../api/auth/utils";
-import { shouldShowOnboarding } from "../../api/helpers";
+import { getOnboardingStatus } from "../../api/helpers";
 
 export async function signup(
   email: string,
   password: string,
   confirmPassword: string,
   agreeToTerms: boolean,
-  isChatEnabled: boolean,
 ) {
   try {
     const parsed = signupFormSchema.safeParse({
@@ -59,8 +58,9 @@ export async function signup(
       await supabase.auth.setSession(data.session);
     }
 
-    const isOnboardingEnabled = await shouldShowOnboarding();
+    // Get onboarding status from backend (includes chat flag evaluated for this user)
-    const next = isOnboardingEnabled
+    const { shouldShowOnboarding, isChatEnabled } = await getOnboardingStatus();
+    const next = shouldShowOnboarding
       ? "/onboarding"
       : getHomepageRoute(isChatEnabled);
 

autogpt_platform/frontend/src/app/(platform)/signup/useSignupPage.ts

@@ -108,7 +108,6 @@ export function useSignupPage() {
         data.password,
         data.confirmPassword,
         data.agreeToTerms,
-        isChatEnabled === true,
       );
 
       setIsLoading(false);

autogpt_platform/frontend/src/app/api/helpers.ts

@@ -175,9 +175,12 @@ export async function resolveResponse<
   return res.data;
 }
 
-export async function shouldShowOnboarding() {
+export async function getOnboardingStatus() {
-  const isEnabled = await resolveResponse(getV1IsOnboardingEnabled());
+  const status = await resolveResponse(getV1IsOnboardingEnabled());
   const onboarding = await resolveResponse(getV1OnboardingState());
   const isCompleted = onboarding.completedSteps.includes("CONGRATS");
-  return isEnabled && !isCompleted;
+  return {
+    shouldShowOnboarding: status.is_onboarding_enabled && !isCompleted,
+    isChatEnabled: status.is_chat_enabled,
+  };
 }

autogpt_platform/frontend/src/app/api/openapi.json

@@ -3339,7 +3339,7 @@
       "get": {
         "tags": ["v2", "library", "private"],
         "summary": "List Library Agents",
-        "description": "Get all agents in the user's library (both created and saved).\n\nArgs:\n    user_id: ID of the authenticated user.\n    search_term: Optional search term to filter agents by name/description.\n    filter_by: List of filters to apply (favorites, created by user).\n    sort_by: List of sorting criteria (created date, updated date).\n    page: Page number to retrieve.\n    page_size: Number of agents per page.\n\nReturns:\n    A LibraryAgentResponse containing agents and pagination metadata.\n\nRaises:\n    HTTPException: If a server/database error occurs.",
+        "description": "Get all agents in the user's library (both created and saved).",
         "operationId": "getV2List library agents",
         "security": [{ "HTTPBearerJWT": [] }],
         "parameters": [
@@ -3394,7 +3394,7 @@
         ],
         "responses": {
           "200": {
-            "description": "List of library agents",
+            "description": "Successful Response",
             "content": {
               "application/json": {
                 "schema": {
@@ -3413,17 +3413,13 @@
                 "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
               }
             }
-          },
-          "500": {
-            "description": "Server error",
-            "content": { "application/json": {} }
           }
         }
       },
       "post": {
         "tags": ["v2", "library", "private"],
         "summary": "Add Marketplace Agent",
-        "description": "Add an agent from the marketplace to the user's library.\n\nArgs:\n    store_listing_version_id: ID of the store listing version to add.\n    user_id: ID of the authenticated user.\n\nReturns:\n    library_model.LibraryAgent: Agent added to the library\n\nRaises:\n    HTTPException(404): If the listing version is not found.\n    HTTPException(500): If a server/database error occurs.",
+        "description": "Add an agent from the marketplace to the user's library.",
         "operationId": "postV2Add marketplace agent",
         "security": [{ "HTTPBearerJWT": [] }],
         "requestBody": {
@@ -3438,7 +3434,7 @@
         },
         "responses": {
           "201": {
-            "description": "Agent added successfully",
+            "description": "Successful Response",
             "content": {
               "application/json": {
                 "schema": { "$ref": "#/components/schemas/LibraryAgent" }
@@ -3448,7 +3444,6 @@
           "401": {
             "$ref": "#/components/responses/HTTP401NotAuthenticatedError"
           },
-          "404": { "description": "Store listing version not found" },
           "422": {
             "description": "Validation Error",
             "content": {
@@ -3456,8 +3451,7 @@
                 "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
               }
             }
-          },
+          }
-          "500": { "description": "Server error" }
         }
       }
     },
@@ -3511,7 +3505,7 @@
       "get": {
         "tags": ["v2", "library", "private"],
         "summary": "List Favorite Library Agents",
-        "description": "Get all favorite agents in the user's library.\n\nArgs:\n    user_id: ID of the authenticated user.\n    page: Page number to retrieve.\n    page_size: Number of agents per page.\n\nReturns:\n    A LibraryAgentResponse containing favorite agents and pagination metadata.\n\nRaises:\n    HTTPException: If a server/database error occurs.",
+        "description": "Get all favorite agents in the user's library.",
         "operationId": "getV2List favorite library agents",
         "security": [{ "HTTPBearerJWT": [] }],
         "parameters": [
@@ -3563,10 +3557,6 @@
                 "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
               }
             }
-          },
-          "500": {
-            "description": "Server error",
-            "content": { "application/json": {} }
           }
         }
       }
@@ -3588,7 +3578,7 @@
         ],
         "responses": {
           "200": {
-            "description": "Library agent found",
+            "description": "Successful Response",
             "content": {
               "application/json": {
                 "schema": {
@@ -3604,7 +3594,6 @@
           "401": {
             "$ref": "#/components/responses/HTTP401NotAuthenticatedError"
           },
-          "404": { "description": "Agent not found" },
           "422": {
             "description": "Validation Error",
             "content": {
@@ -3620,7 +3609,7 @@
       "delete": {
         "tags": ["v2", "library", "private"],
         "summary": "Delete Library Agent",
-        "description": "Soft-delete the specified library agent.\n\nArgs:\n    library_agent_id: ID of the library agent to delete.\n    user_id: ID of the authenticated user.\n\nReturns:\n    204 No Content if successful.\n\nRaises:\n    HTTPException(404): If the agent does not exist.\n    HTTPException(500): If a server/database error occurs.",
+        "description": "Soft-delete the specified library agent.",
         "operationId": "deleteV2Delete library agent",
         "security": [{ "HTTPBearerJWT": [] }],
         "parameters": [
@@ -3636,11 +3625,9 @@
             "description": "Successful Response",
             "content": { "application/json": { "schema": {} } }
           },
-          "204": { "description": "Agent deleted successfully" },
           "401": {
             "$ref": "#/components/responses/HTTP401NotAuthenticatedError"
           },
-          "404": { "description": "Agent not found" },
           "422": {
             "description": "Validation Error",
             "content": {
@@ -3648,8 +3635,7 @@
                 "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
               }
             }
-          },
+          }
-          "500": { "description": "Server error" }
         }
       },
       "get": {
@@ -3690,7 +3676,7 @@
       "patch": {
         "tags": ["v2", "library", "private"],
         "summary": "Update Library Agent",
-        "description": "Update the library agent with the given fields.\n\nArgs:\n    library_agent_id: ID of the library agent to update.\n    payload: Fields to update (auto_update_version, is_favorite, etc.).\n    user_id: ID of the authenticated user.\n\nRaises:\n    HTTPException(500): If a server/database error occurs.",
+        "description": "Update the library agent with the given fields.",
         "operationId": "patchV2Update library agent",
         "security": [{ "HTTPBearerJWT": [] }],
         "parameters": [
@@ -3713,7 +3699,7 @@
         },
         "responses": {
           "200": {
-            "description": "Agent updated successfully",
+            "description": "Successful Response",
             "content": {
               "application/json": {
                 "schema": { "$ref": "#/components/schemas/LibraryAgent" }
@@ -3730,8 +3716,7 @@
                 "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
               }
             }
-          },
+          }
-          "500": { "description": "Server error" }
         }
       }
     },
@@ -4540,8 +4525,7 @@
             "content": {
               "application/json": {
                 "schema": {
-                  "type": "boolean",
+                  "$ref": "#/components/schemas/OnboardingStatusResponse"
-                  "title": "Response Getv1Is Onboarding Enabled"
                 }
               }
             }
@@ -4594,6 +4578,7 @@
                 "AGENT_NEW_RUN",
                 "AGENT_INPUT",
                 "CONGRATS",
+                "VISIT_COPILOT",
                 "MARKETPLACE_VISIT",
                 "BUILDER_OPEN"
               ],
@@ -8744,6 +8729,19 @@
         "title": "OAuthApplicationPublicInfo",
         "description": "Public information about an OAuth application (for consent screen)"
       },
+      "OnboardingStatusResponse": {
+        "properties": {
+          "is_onboarding_enabled": {
+            "type": "boolean",
+            "title": "Is Onboarding Enabled"
+          },
+          "is_chat_enabled": { "type": "boolean", "title": "Is Chat Enabled" }
+        },
+        "type": "object",
+        "required": ["is_onboarding_enabled", "is_chat_enabled"],
+        "title": "OnboardingStatusResponse",
+        "description": "Response for onboarding status check."
+      },
       "OnboardingStep": {
         "type": "string",
         "enum": [
@@ -8754,6 +8752,7 @@
           "AGENT_NEW_RUN",
           "AGENT_INPUT",
           "CONGRATS",
+          "VISIT_COPILOT",
           "GET_RESULTS",
           "MARKETPLACE_VISIT",
           "MARKETPLACE_ADD_AGENT",

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(
+  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],
+    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">
+            <div className="flex flex-col items-center gap-3">
-              <ChatLoader />
+              <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

@@ -58,39 +58,17 @@ function notifyStreamComplete(
   }
 }
 
-function cleanupCompletedStreams(completedStreams: Map<string, StreamResult>) {
+function cleanupExpiredStreams(
-  const now = Date.now();
-  for (const [sessionId, result] of completedStreams) {
-    if (now - result.completedAt > COMPLETED_STREAM_TTL) {
-      completedStreams.delete(sessionId);
-    }
-  }
-}
-
-function moveToCompleted(
-  activeStreams: Map<string, ActiveStream>,
   completedStreams: Map<string, StreamResult>,
-  streamCompleteCallbacks: Set<StreamCompleteCallback>,
+): Map<string, StreamResult> {
-  sessionId: string,
+  const now = Date.now();
-) {
+  const cleaned = new Map(completedStreams);
-  const stream = activeStreams.get(sessionId);
+  for (const [sessionId, result] of cleaned) {
-  if (!stream) return;
+    if (now - result.completedAt > COMPLETED_STREAM_TTL) {
-
+      cleaned.delete(sessionId);
-  const result: StreamResult = {
-    sessionId,
-    status: stream.status,
-    chunks: stream.chunks,
-    completedAt: Date.now(),
-    error: stream.error,
-  };
-
-  completedStreams.set(sessionId, result);
-  activeStreams.delete(sessionId);
-  cleanupCompletedStreams(completedStreams);
-
-  if (stream.status === "completed" || stream.status === "error") {
-    notifyStreamComplete(streamCompleteCallbacks, sessionId);
     }
+  }
+  return cleaned;
 }
 
 export const useChatStore = create<ChatStore>((set, get) => ({
@@ -106,17 +84,31 @@ export const useChatStore = create<ChatStore>((set, get) => ({
     context,
     onChunk,
   ) {
-    const { activeStreams, completedStreams, streamCompleteCallbacks } = get();
+    const state = get();
+    const newActiveStreams = new Map(state.activeStreams);
+    let newCompletedStreams = new Map(state.completedStreams);
+    const callbacks = state.streamCompleteCallbacks;
 
-    const existingStream = activeStreams.get(sessionId);
+    const existingStream = newActiveStreams.get(sessionId);
     if (existingStream) {
       existingStream.abortController.abort();
-      moveToCompleted(
+      const normalizedStatus =
-        activeStreams,
+        existingStream.status === "streaming"
-        completedStreams,
+          ? "completed"
-        streamCompleteCallbacks,
+          : 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();
@@ -132,36 +124,76 @@ export const useChatStore = create<ChatStore>((set, get) => ({
       onChunkCallbacks: initialCallbacks,
     };
 
-    activeStreams.set(sessionId, stream);
+    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") {
-        moveToCompleted(
+        const currentState = get();
-          activeStreams,
+        const finalActiveStreams = new Map(currentState.activeStreams);
-          completedStreams,
+        let finalCompletedStreams = new Map(currentState.completedStreams);
-          streamCompleteCallbacks,
+
+        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 { activeStreams, completedStreams, streamCompleteCallbacks } = get();
+    const state = get();
-    const stream = activeStreams.get(sessionId);
+    const stream = state.activeStreams.get(sessionId);
-    if (stream) {
+    if (!stream) return;
+
     stream.abortController.abort();
     stream.status = "completed";
-      moveToCompleted(
+
-        activeStreams,
+    const newActiveStreams = new Map(state.activeStreams);
-        completedStreams,
+    let newCompletedStreams = new Map(state.completedStreams);
-        streamCompleteCallbacks,
+
+    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(
@@ -169,16 +201,18 @@ export const useChatStore = create<ChatStore>((set, get) => ({
     onChunk,
     skipReplay = false,
   ) {
-    const { activeStreams } = get();
+    const state = get();
+    const stream = state.activeStreams.get(sessionId);
 
-    const stream = 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);
       };
@@ -204,7 +238,12 @@ export const useChatStore = create<ChatStore>((set, get) => ({
   },
 
   clearCompletedStream: function clearCompletedStream(sessionId) {
-    get().completedStreams.delete(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) {
@@ -213,11 +252,21 @@ export const useChatStore = create<ChatStore>((set, get) => ({
   },
 
   registerActiveSession: function registerActiveSession(sessionId) {
-    get().activeSessions.add(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) {
-    get().activeSessions.delete(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) {
@@ -225,10 +274,16 @@ export const useChatStore = create<ChatStore>((set, get) => ({
   },
 
   onStreamComplete: function onStreamComplete(callback) {
-    const { streamCompleteCallbacks } = get();
+    const state = get();
-    streamCompleteCallbacks.add(callback);
+    const newCallbacks = new Set(state.streamCompleteCallbacks);
+    newCallbacks.add(callback);
+    set({ streamCompleteCallbacks: newCallbacks });
+
     return function unsubscribe() {
-      streamCompleteCallbacks.delete(callback);
+      const currentState = get();
+      const cleanedCallbacks = new Set(currentState.streamCompleteCallbacks);
+      cleanedCallbacks.delete(callback);
+      set({ streamCompleteCallbacks: cleanedCallbacks });
     };
   },
 }));

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

@@ -16,6 +16,7 @@ export interface ChatContainerProps {
   initialPrompt?: string;
   className?: string;
   onStreamingChange?: (isStreaming: boolean) => void;
+  onOperationStarted?: () => void;
 }
 
 export function ChatContainer({
@@ -24,6 +25,7 @@ export function ChatContainer({
   initialPrompt,
   className,
   onStreamingChange,
+  onOperationStarted,
 }: ChatContainerProps) {
   const {
     messages,
@@ -38,6 +40,7 @@ export function ChatContainer({
     sessionId,
     initialMessages,
     initialPrompt,
+    onOperationStarted,
   });
 
   useEffect(() => {

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()) {
+    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(),
       };
-    deps.setMessages((prev) => [...prev, assistantMessage]);
+      return [...prev, assistantMessage];
+    });
   }
   deps.setStreamingChunks([]);
   deps.streamingChunksRef.current = [];

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

@@ -304,6 +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,
@@ -316,6 +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,
@@ -341,6 +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

@@ -14,16 +14,40 @@ import {
   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[]>([]);
@@ -73,20 +97,102 @@ export function useChatContainer({
         setIsRegionBlockedModalOpen,
         sessionId,
         setIsStreamingInitiated,
+        onOperationStarted,
       });
 
       setIsStreamingInitiated(true);
       const skipReplay = initialMessages.length > 0;
       return subscribeToStream(sessionId, dispatcher, skipReplay);
     },
-    [sessionId, stopStreaming, activeStreams, subscribeToStream],
+    [
+      sessionId,
+      stopStreaming,
+      activeStreams,
+      subscribeToStream,
+      onOperationStarted,
+    ],
   );
 
-  const allMessages = useMemo(
+  // Collect toolIds from completed tool results in initialMessages
-    () => [...processInitialMessages(initialMessages), ...messages],
+  // Used to filter out operation messages when their results arrive
-    [initialMessages, messages],
+  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,
@@ -118,6 +224,7 @@ export function useChatContainer({
       setIsRegionBlockedModalOpen,
       sessionId,
       setIsStreamingInitiated,
+      onOperationStarted,
     });
 
     try {

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/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/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/useChat.ts

@@ -26,6 +26,7 @@ export function useChat({ urlSessionId }: UseChatArgs = {}) {
     claimSession,
     clearSession: clearSessionBase,
     loadSession,
+    startPollingForOperation,
   } = useChatSession({
     urlSessionId,
     autoCreate: false,
@@ -94,5 +95,6 @@ export function useChat({ urlSessionId }: UseChatArgs = {}) {
     loadSession,
     sessionId: sessionIdFromHook,
     showLoader,
+    startPollingForOperation,
   };
 }

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

@@ -59,6 +59,7 @@ export function useChatSession({
     query: {
       enabled: !!sessionId,
       select: okData,
+      staleTime: 0,
       retry: shouldRetrySessionLoad,
       retryDelay: getSessionRetryDelay,
     },
@@ -102,15 +103,123 @@ 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 refreshSessionsListOnLoad() {
+    function refreshSessionsListOnOperationComplete() {
-      if (sessionId && sessionData && !isLoadingSession) {
+      const wasHasPending = prevHasPendingOperationsRef.current;
+      prevHasPendingOperationsRef.current = hasPendingOperations;
+
+      // Only invalidate when transitioning from pending to not pending
+      if (wasHasPending && !hasPendingOperations && sessionId) {
         queryClient.invalidateQueries({
           queryKey: getGetV2ListSessionsQueryKey(),
         });
       }
     },
-    [sessionId, sessionData, isLoadingSession, queryClient],
+    [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() {
@@ -239,11 +348,13 @@ export function useChatSession({
     isCreating,
     error,
     isSessionNotFound: isNotFoundError(loadError),
+    hasPendingOperations,
     createSession,
     loadSession,
     refreshSession,
     claimSession,
     clearSession,
+    startPollingForOperation,
   };
 }
 

autogpt_platform/frontend/src/components/layout/Navbar/components/Wallet/Wallet.tsx

@@ -255,13 +255,18 @@ export function Wallet() {
     (notification: WebSocketNotification) => {
       if (
         notification.type !== "onboarding" ||
-        notification.event !== "step_completed" ||
+        notification.event !== "step_completed"
-        !walletRef.current
       ) {
         return;
       }
 
-      // Only trigger confetti for tasks that are in groups
+      // Always refresh credits when any onboarding step completes
+      fetchCredits();
+
+      // Only trigger confetti for tasks that are in displayed groups
+      if (!walletRef.current) {
+        return;
+      }
       const taskIds = groups
         .flatMap((group) => group.tasks)
         .map((task) => task.id);
@@ -274,7 +279,6 @@ export function Wallet() {
         return;
       }
 
-      fetchCredits();
       party.confetti(walletRef.current, {
         count: 30,
         spread: 120,
@@ -284,7 +288,7 @@ export function Wallet() {
         modules: [fadeOut],
       });
     },
-    [fetchCredits, fadeOut],
+    [fetchCredits, fadeOut, groups],
   );
 
   // WebSocket setup for onboarding notifications

autogpt_platform/frontend/src/lib/autogpt-server-api/types.ts

@@ -1003,6 +1003,7 @@ export type OnboardingStep =
   | "AGENT_INPUT"
   | "CONGRATS"
   // First Wins
+  | "VISIT_COPILOT"
   | "GET_RESULTS"
   | "MARKETPLACE_VISIT"
   | "MARKETPLACE_ADD_AGENT"

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) {

autogpt_platform/frontend/src/tests/pages/login.page.ts

@@ -37,9 +37,13 @@ export class LoginPage {
     this.page.on("load", (page) => console.log(`ℹ️ Now at URL: ${page.url()}`));
 
     // Start waiting for navigation before clicking
+    // Wait for redirect to marketplace, onboarding, library, or copilot (new landing pages)
     const leaveLoginPage = this.page
       .waitForURL(
-        (url) => /^\/(marketplace|onboarding(\/.*)?)?$/.test(url.pathname),
+        (url: URL) =>
+          /^\/(marketplace|onboarding(\/.*)?|library|copilot)?$/.test(
+            url.pathname,
+          ),
         { timeout: 10_000 },
       )
       .catch((reason) => {

autogpt_platform/frontend/src/tests/utils/signup.ts

@@ -36,14 +36,16 @@ export async function signupTestUser(
     const signupButton = getButton("Sign up");
     await signupButton.click();
 
-    // Wait for successful signup - could redirect to onboarding or marketplace
+    // Wait for successful signup - could redirect to various pages depending on onboarding state
 
     try {
-      // Wait for either onboarding or marketplace redirect
+      // Wait for redirect to onboarding, marketplace, copilot, or library
-      await Promise.race([
+      // Use a single waitForURL with a callback to avoid Promise.race race conditions
-        page.waitForURL(/\/onboarding/, { timeout: 15000 }),
+      await page.waitForURL(
-        page.waitForURL(/\/marketplace/, { timeout: 15000 }),
+        (url: URL) =>
-      ]);
+          /\/(onboarding|marketplace|copilot|library)/.test(url.pathname),
+        { timeout: 15000 },
+      );
     } catch (error) {
       console.error(
         "❌ Timeout waiting for redirect, current URL:",
@@ -54,14 +56,19 @@ export async function signupTestUser(
 
     const currentUrl = page.url();
 
-    // Handle onboarding or marketplace redirect
+    // Handle onboarding redirect if needed
     if (currentUrl.includes("/onboarding") && ignoreOnboarding) {
       await page.goto("http://localhost:3000/marketplace");
       await page.waitForLoadState("domcontentloaded", { timeout: 10000 });
     }
 
-    // Verify we're on the expected final page
+    // Verify we're on an expected final page and user is authenticated
-    if (ignoreOnboarding || currentUrl.includes("/marketplace")) {
+    if (currentUrl.includes("/copilot") || currentUrl.includes("/library")) {
+      // For copilot/library landing pages, just verify user is authenticated
+      await page
+        .getByTestId("profile-popout-menu-trigger")
+        .waitFor({ state: "visible", timeout: 10000 });
+    } else if (ignoreOnboarding || currentUrl.includes("/marketplace")) {
       // Verify we're on marketplace
       await page
         .getByText(

backend/blocks/video/__init__.py

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