Update migration to retain 'search' column

Removed the dropping of the 'search' column and its associated index from the migration script.

autogpt_platform/CLAUDE.md

@@ -194,6 +194,50 @@ ex: do the inputs and outputs tie well together?
 
 If you get any pushback or hit complex block conditions check the new_blocks guide in the docs.
 
+**Handling files in blocks with `store_media_file()`:**
+
+When blocks need to work with files (images, videos, documents), use `store_media_file()` from `backend.util.file`. The `return_format` parameter determines what you get back:
+
+| Format | Use When | Returns |
+|--------|----------|---------|
+| `"for_local_processing"` | Processing with local tools (ffmpeg, MoviePy, PIL) | Local file path (e.g., `"image.png"`) |
+| `"for_external_api"` | Sending content to external APIs (Replicate, OpenAI) | Data URI (e.g., `"data:image/png;base64,..."`) |
+| `"for_block_output"` | Returning output from your block | Smart: `workspace://` in CoPilot, data URI in graphs |
+
+**Examples:**
+```python
+# INPUT: Need to process file locally with ffmpeg
+local_path = await store_media_file(
+    file=input_data.video,
+    execution_context=execution_context,
+    return_format="for_local_processing",
+)
+# local_path = "video.mp4" - use with Path/ffmpeg/etc
+
+# INPUT: Need to send to external API like Replicate
+image_b64 = await store_media_file(
+    file=input_data.image,
+    execution_context=execution_context,
+    return_format="for_external_api",
+)
+# image_b64 = "data:image/png;base64,iVBORw0..." - send to API
+
+# OUTPUT: Returning result from block
+result_url = await store_media_file(
+    file=generated_image_url,
+    execution_context=execution_context,
+    return_format="for_block_output",
+)
+yield "image_url", result_url
+# In CoPilot: result_url = "workspace://abc123"
+# In graphs:  result_url = "data:image/png;base64,..."
+```
+
+**Key points:**
+- `for_block_output` is the ONLY format that auto-adapts to execution context
+- Always use `for_block_output` for block outputs unless you have a specific reason not to
+- Never hardcode workspace checks - let `for_block_output` handle it
+
 **Modifying the API:**
 
 1. Update route in `/backend/backend/server/routers/`

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

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

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

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

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

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

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

@@ -17,6 +17,7 @@ from openai import (
 )
 from openai.types.chat import ChatCompletionChunk, ChatCompletionToolParam
 
+from backend.data.redis_client import get_redis_async
 from backend.data.understanding import (
     format_understanding_for_prompt,
     get_business_understanding,
@@ -24,6 +25,7 @@ from backend.data.understanding import (
 from backend.util.exceptions import NotFoundError
 from backend.util.settings import Settings
 
+from . import db as chat_db
 from .config import ChatConfig
 from .model import (
     ChatMessage,
@@ -31,6 +33,7 @@ from .model import (
     Usage,
     cache_chat_session,
     get_chat_session,
+    invalidate_session_cache,
     update_session_title,
     upsert_chat_session,
 )
@@ -48,8 +51,13 @@ from .response_model import (
     StreamToolOutputAvailable,
     StreamUsage,
 )
-from .tools import execute_tool, tools
-from .tools.models import ErrorResponse
+from .tools import execute_tool, get_tool, tools
+from .tools.models import (
+    ErrorResponse,
+    OperationInProgressResponse,
+    OperationPendingResponse,
+    OperationStartedResponse,
+)
 from .tracking import track_user_message
 
 logger = logging.getLogger(__name__)
@@ -61,6 +69,43 @@ 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:"
+
+# 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}")
+
 
 class LangfuseNotConfiguredError(Exception):
     """Raised when Langfuse is required but not configured."""
@@ -315,6 +360,7 @@ 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 +382,6 @@ async def stream_chat_completion(
             system_prompt=system_prompt,
             text_block_id=text_block_id,
         ):
-
             if isinstance(chunk, StreamTextStart):
                 # Emit text-start before first text delta
                 if not has_received_text:
@@ -394,13 +439,34 @@ async def stream_chat_completion(
                     if isinstance(chunk.output, str)
                     else orjson.dumps(chunk.output).decode("utf-8")
                 )
-                tool_response_messages.append(
-                    ChatMessage(
-                        role="tool",
-                        content=result_content,
-                        tool_call_id=chunk.toolCallId,
+                # Skip saving long-running operation responses - messages already saved in _yield_tool_call
+                # Use JSON parsing instead of substring matching to avoid false positives
+                is_long_running_response = False
+                try:
+                    parsed = orjson.loads(result_content)
+                    if isinstance(parsed, dict) and parsed.get("type") in (
+                        "operation_started",
+                        "operation_in_progress",
+                    ):
+                        is_long_running_response = True
+                except (orjson.JSONDecodeError, TypeError):
+                    pass  # Not JSON or not a dict - treat as regular response
+                if is_long_running_response:
+                    # Remove from accumulated_tool_calls since assistant message was already saved
+                    accumulated_tool_calls[:] = [
+                        tc
+                        for tc in accumulated_tool_calls
+                        if tc["id"] != chunk.toolCallId
+                    ]
+                    has_long_running_tool_call = True
+                else:
+                    tool_response_messages.append(
+                        ChatMessage(
+                            role="tool",
+                            content=result_content,
+                            tool_call_id=chunk.toolCallId,
+                        )
                     )
-                )
                 has_done_tool_call = True
                 # Track if any tool execution failed
                 if not chunk.success:
@@ -576,7 +642,14 @@ 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 +658,9 @@ 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 +800,114 @@ 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 +999,15 @@ 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 +1094,13 @@ 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 +1159,10 @@ 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 +1185,12 @@ 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:
@@ -1260,14 +1467,17 @@ async def _yield_tool_call(
     """
     Yield a tool call and its execution result.
 
-    For long-running tools, yields heartbeat events every 15 seconds to keep
-    the SSE connection alive through proxies and load balancers.
+    For tools marked with `is_long_running=True` (like agent generation), spawns a
+    background task so the operation survives SSE disconnections. For other tools,
+    yields heartbeat events every 15 seconds to keep the SSE connection alive.
 
     Raises:
         orjson.JSONDecodeError: If tool call arguments cannot be parsed as JSON
         KeyError: If expected tool call fields are missing
         TypeError: If tool call structure is invalid
     """
+    import uuid as uuid_module
+
     tool_name = tool_calls[yield_idx]["function"]["name"]
     tool_call_id = tool_calls[yield_idx]["id"]
     logger.info(f"Yielding tool call: {tool_calls[yield_idx]}")
@@ -1285,7 +1495,151 @@ 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 +1689,190 @@ 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

@@ -18,6 +18,12 @@ from .get_doc_page import GetDocPageTool
 from .run_agent import RunAgentTool
 from .run_block import RunBlockTool
 from .search_docs import SearchDocsTool
+from .workspace_tools import (
+    DeleteWorkspaceFileTool,
+    ListWorkspaceFilesTool,
+    ReadWorkspaceFileTool,
+    WriteWorkspaceFileTool,
+)
 
 if TYPE_CHECKING:
     from backend.api.features.chat.response_model import StreamToolOutputAvailable
@@ -37,6 +43,11 @@ TOOL_REGISTRY: dict[str, BaseTool] = {
     "view_agent_output": AgentOutputTool(),
     "search_docs": SearchDocsTool(),
     "get_doc_page": GetDocPageTool(),
+    # Workspace tools for CoPilot file operations
+    "list_workspace_files": ListWorkspaceFilesTool(),
+    "read_workspace_file": ReadWorkspaceFileTool(),
+    "write_workspace_file": WriteWorkspaceFileTool(),
+    "delete_workspace_file": DeleteWorkspaceFileTool(),
 }
 
 # Export individual tool instances for backwards compatibility
@@ -49,6 +60,11 @@ 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 +73,7 @@ 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 +28,17 @@ class ResponseType(str, Enum):
     BLOCK_OUTPUT = "block_output"
     DOC_SEARCH_RESULTS = "doc_search_results"
     DOC_PAGE = "doc_page"
+    # Workspace response types
+    WORKSPACE_FILE_LIST = "workspace_file_list"
+    WORKSPACE_FILE_CONTENT = "workspace_file_content"
+    WORKSPACE_FILE_METADATA = "workspace_file_metadata"
+    WORKSPACE_FILE_WRITTEN = "workspace_file_written"
+    WORKSPACE_FILE_DELETED = "workspace_file_deleted"
+    WORKSPACE_FILE_INFO = "workspace_file_info"
+    # Long-running operation types
+    OPERATION_STARTED = "operation_started"
+    OPERATION_PENDING = "operation_pending"
+    OPERATION_IN_PROGRESS = "operation_in_progress"
 
 
 # Base response model
@@ -334,3 +345,39 @@ 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/chat/tools/run_block.py

@@ -1,6 +1,7 @@
 """Tool for executing blocks directly."""
 
 import logging
+import uuid
 from collections import defaultdict
 from typing import Any
 
@@ -8,6 +9,7 @@ from backend.api.features.chat.model import ChatSession
 from backend.data.block import get_block
 from backend.data.execution import ExecutionContext
 from backend.data.model import CredentialsMetaInput
+from backend.data.workspace import get_or_create_workspace
 from backend.integrations.creds_manager import IntegrationCredentialsManager
 from backend.util.exceptions import BlockError
 
@@ -223,11 +225,48 @@ class RunBlockTool(BaseTool):
             )
 
         try:
-            # Fetch actual credentials and prepare kwargs for block execution
-            # Create execution context with defaults (blocks may require it)
+            # Get or create user's workspace for CoPilot file operations
+            workspace = await get_or_create_workspace(user_id)
+
+            # Generate synthetic IDs for CoPilot context
+            # Each chat session is treated as its own agent with one continuous run
+            # This means:
+            # - graph_id (agent) = session (memories scoped to session when limit_to_agent=True)
+            # - graph_exec_id (run) = session (memories scoped to session when limit_to_run=True)
+            # - node_exec_id = unique per block execution
+            synthetic_graph_id = f"copilot-session-{session.session_id}"
+            synthetic_graph_exec_id = f"copilot-session-{session.session_id}"
+            synthetic_node_id = f"copilot-node-{block_id}"
+            synthetic_node_exec_id = (
+                f"copilot-{session.session_id}-{uuid.uuid4().hex[:8]}"
+            )
+
+            # Create unified execution context with all required fields
+            execution_context = ExecutionContext(
+                # Execution identity
+                user_id=user_id,
+                graph_id=synthetic_graph_id,
+                graph_exec_id=synthetic_graph_exec_id,
+                graph_version=1,  # Versions are 1-indexed
+                node_id=synthetic_node_id,
+                node_exec_id=synthetic_node_exec_id,
+                # Workspace with session scoping
+                workspace_id=workspace.id,
+                session_id=session.session_id,
+            )
+
+            # Prepare kwargs for block execution
+            # Keep individual kwargs for backwards compatibility with existing blocks
             exec_kwargs: dict[str, Any] = {
                 "user_id": user_id,
-                "execution_context": ExecutionContext(),
+                "execution_context": execution_context,
+                # Legacy: individual kwargs for blocks not yet using execution_context
+                "workspace_id": workspace.id,
+                "graph_exec_id": synthetic_graph_exec_id,
+                "node_exec_id": synthetic_node_exec_id,
+                "node_id": synthetic_node_id,
+                "graph_version": 1,  # Versions are 1-indexed
+                "graph_id": synthetic_graph_id,
             }
 
             for field_name, cred_meta in matched_credentials.items():

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

@@ -0,0 +1,619 @@
+"""CoPilot tools for workspace file operations."""
+
+import base64
+import logging
+from typing import Any, Optional
+
+from prisma.enums import WorkspaceFileSource
+from pydantic import BaseModel
+
+from backend.api.features.chat.model import ChatSession
+from backend.data.workspace import get_or_create_workspace
+from backend.util.virus_scanner import scan_content_safe
+from backend.util.workspace import MAX_FILE_SIZE_BYTES, WorkspaceManager
+
+from .base import BaseTool
+from .models import ErrorResponse, ResponseType, ToolResponseBase
+
+logger = logging.getLogger(__name__)
+
+
+class WorkspaceFileInfoData(BaseModel):
+    """Data model for workspace file information (not a response itself)."""
+
+    file_id: str
+    name: str
+    path: str
+    mime_type: str
+    size_bytes: int
+    source: str
+
+
+class WorkspaceFileListResponse(ToolResponseBase):
+    """Response containing list of workspace files."""
+
+    type: ResponseType = ResponseType.WORKSPACE_FILE_LIST
+    files: list[WorkspaceFileInfoData]
+    total_count: int
+
+
+class WorkspaceFileContentResponse(ToolResponseBase):
+    """Response containing workspace file content (legacy, for small text files)."""
+
+    type: ResponseType = ResponseType.WORKSPACE_FILE_CONTENT
+    file_id: str
+    name: str
+    path: str
+    mime_type: str
+    content_base64: str
+
+
+class WorkspaceFileMetadataResponse(ToolResponseBase):
+    """Response containing workspace file metadata and download URL (prevents context bloat)."""
+
+    type: ResponseType = ResponseType.WORKSPACE_FILE_METADATA
+    file_id: str
+    name: str
+    path: str
+    mime_type: str
+    size_bytes: int
+    download_url: str
+    preview: str | None = None  # First 500 chars for text files
+
+
+class WorkspaceWriteResponse(ToolResponseBase):
+    """Response after writing a file to workspace."""
+
+    type: ResponseType = ResponseType.WORKSPACE_FILE_WRITTEN
+    file_id: str
+    name: str
+    path: str
+    size_bytes: int
+
+
+class WorkspaceDeleteResponse(ToolResponseBase):
+    """Response after deleting a file from workspace."""
+
+    type: ResponseType = ResponseType.WORKSPACE_FILE_DELETED
+    file_id: str
+    success: bool
+
+
+class ListWorkspaceFilesTool(BaseTool):
+    """Tool for listing files in user's workspace."""
+
+    @property
+    def name(self) -> str:
+        return "list_workspace_files"
+
+    @property
+    def description(self) -> str:
+        return (
+            "List files in the user's workspace. "
+            "Returns file names, paths, sizes, and metadata. "
+            "Optionally filter by path prefix."
+        )
+
+    @property
+    def parameters(self) -> dict[str, Any]:
+        return {
+            "type": "object",
+            "properties": {
+                "path_prefix": {
+                    "type": "string",
+                    "description": (
+                        "Optional path prefix to filter files "
+                        "(e.g., '/documents/' to list only files in documents folder). "
+                        "By default, only files from the current session are listed."
+                    ),
+                },
+                "limit": {
+                    "type": "integer",
+                    "description": "Maximum number of files to return (default 50, max 100)",
+                    "minimum": 1,
+                    "maximum": 100,
+                },
+                "include_all_sessions": {
+                    "type": "boolean",
+                    "description": (
+                        "If true, list files from all sessions. "
+                        "Default is false (only current session's files)."
+                    ),
+                },
+            },
+            "required": [],
+        }
+
+    @property
+    def requires_auth(self) -> bool:
+        return True
+
+    async def _execute(
+        self,
+        user_id: str | None,
+        session: ChatSession,
+        **kwargs,
+    ) -> ToolResponseBase:
+        session_id = session.session_id
+
+        if not user_id:
+            return ErrorResponse(
+                message="Authentication required",
+                session_id=session_id,
+            )
+
+        path_prefix: Optional[str] = kwargs.get("path_prefix")
+        limit = min(kwargs.get("limit", 50), 100)
+        include_all_sessions: bool = kwargs.get("include_all_sessions", False)
+
+        try:
+            workspace = await get_or_create_workspace(user_id)
+            # Pass session_id for session-scoped file access
+            manager = WorkspaceManager(user_id, workspace.id, session_id)
+
+            files = await manager.list_files(
+                path=path_prefix,
+                limit=limit,
+                include_all_sessions=include_all_sessions,
+            )
+            total = await manager.get_file_count()
+
+            file_infos = [
+                WorkspaceFileInfoData(
+                    file_id=f.id,
+                    name=f.name,
+                    path=f.path,
+                    mime_type=f.mimeType,
+                    size_bytes=f.sizeBytes,
+                    source=f.source,
+                )
+                for f in files
+            ]
+
+            scope_msg = "all sessions" if include_all_sessions else "current session"
+            return WorkspaceFileListResponse(
+                files=file_infos,
+                total_count=total,
+                message=f"Found {len(files)} files in workspace ({scope_msg})",
+                session_id=session_id,
+            )
+
+        except Exception as e:
+            logger.error(f"Error listing workspace files: {e}", exc_info=True)
+            return ErrorResponse(
+                message=f"Failed to list workspace files: {str(e)}",
+                error=str(e),
+                session_id=session_id,
+            )
+
+
+class ReadWorkspaceFileTool(BaseTool):
+    """Tool for reading file content from workspace."""
+
+    # Size threshold for returning full content vs metadata+URL
+    # Files larger than this return metadata with download URL to prevent context bloat
+    MAX_INLINE_SIZE_BYTES = 32 * 1024  # 32KB
+    # Preview size for text files
+    PREVIEW_SIZE = 500
+
+    @property
+    def name(self) -> str:
+        return "read_workspace_file"
+
+    @property
+    def description(self) -> str:
+        return (
+            "Read a file from the user's workspace. "
+            "Specify either file_id or path to identify the file. "
+            "For small text files, returns content directly. "
+            "For large or binary files, returns metadata and a download URL. "
+            "Paths are scoped to the current session by default. "
+            "Use /sessions/<session_id>/... for cross-session access."
+        )
+
+    @property
+    def parameters(self) -> dict[str, Any]:
+        return {
+            "type": "object",
+            "properties": {
+                "file_id": {
+                    "type": "string",
+                    "description": "The file's unique ID (from list_workspace_files)",
+                },
+                "path": {
+                    "type": "string",
+                    "description": (
+                        "The virtual file path (e.g., '/documents/report.pdf'). "
+                        "Scoped to current session by default."
+                    ),
+                },
+                "force_download_url": {
+                    "type": "boolean",
+                    "description": (
+                        "If true, always return metadata+URL instead of inline content. "
+                        "Default is false (auto-selects based on file size/type)."
+                    ),
+                },
+            },
+            "required": [],  # At least one must be provided
+        }
+
+    @property
+    def requires_auth(self) -> bool:
+        return True
+
+    def _is_text_mime_type(self, mime_type: str) -> bool:
+        """Check if the MIME type is a text-based type."""
+        text_types = [
+            "text/",
+            "application/json",
+            "application/xml",
+            "application/javascript",
+            "application/x-python",
+            "application/x-sh",
+        ]
+        return any(mime_type.startswith(t) for t in text_types)
+
+    async def _execute(
+        self,
+        user_id: str | None,
+        session: ChatSession,
+        **kwargs,
+    ) -> ToolResponseBase:
+        session_id = session.session_id
+
+        if not user_id:
+            return ErrorResponse(
+                message="Authentication required",
+                session_id=session_id,
+            )
+
+        file_id: Optional[str] = kwargs.get("file_id")
+        path: Optional[str] = kwargs.get("path")
+        force_download_url: bool = kwargs.get("force_download_url", False)
+
+        if not file_id and not path:
+            return ErrorResponse(
+                message="Please provide either file_id or path",
+                session_id=session_id,
+            )
+
+        try:
+            workspace = await get_or_create_workspace(user_id)
+            # Pass session_id for session-scoped file access
+            manager = WorkspaceManager(user_id, workspace.id, session_id)
+
+            # Get file info
+            if file_id:
+                file_info = await manager.get_file_info(file_id)
+                if file_info is None:
+                    return ErrorResponse(
+                        message=f"File not found: {file_id}",
+                        session_id=session_id,
+                    )
+                target_file_id = file_id
+            else:
+                # path is guaranteed to be non-None here due to the check above
+                assert path is not None
+                file_info = await manager.get_file_info_by_path(path)
+                if file_info is None:
+                    return ErrorResponse(
+                        message=f"File not found at path: {path}",
+                        session_id=session_id,
+                    )
+                target_file_id = file_info.id
+
+            # Decide whether to return inline content or metadata+URL
+            is_small_file = file_info.sizeBytes <= self.MAX_INLINE_SIZE_BYTES
+            is_text_file = self._is_text_mime_type(file_info.mimeType)
+
+            # Return inline content for small text files (unless force_download_url)
+            if is_small_file and is_text_file and not force_download_url:
+                content = await manager.read_file_by_id(target_file_id)
+                content_b64 = base64.b64encode(content).decode("utf-8")
+
+                return WorkspaceFileContentResponse(
+                    file_id=file_info.id,
+                    name=file_info.name,
+                    path=file_info.path,
+                    mime_type=file_info.mimeType,
+                    content_base64=content_b64,
+                    message=f"Successfully read file: {file_info.name}",
+                    session_id=session_id,
+                )
+
+            # Return metadata + URL for large or binary files
+            # This prevents context bloat (100KB file = ~133KB as base64)
+            download_url = await manager.get_download_url(target_file_id)
+
+            # Generate preview for text files
+            preview: str | None = None
+            if is_text_file:
+                try:
+                    content = await manager.read_file_by_id(target_file_id)
+                    preview_text = content[: self.PREVIEW_SIZE].decode(
+                        "utf-8", errors="replace"
+                    )
+                    if len(content) > self.PREVIEW_SIZE:
+                        preview_text += "..."
+                    preview = preview_text
+                except Exception:
+                    pass  # Preview is optional
+
+            return WorkspaceFileMetadataResponse(
+                file_id=file_info.id,
+                name=file_info.name,
+                path=file_info.path,
+                mime_type=file_info.mimeType,
+                size_bytes=file_info.sizeBytes,
+                download_url=download_url,
+                preview=preview,
+                message=f"File: {file_info.name} ({file_info.sizeBytes} bytes). Use download_url to retrieve content.",
+                session_id=session_id,
+            )
+
+        except FileNotFoundError as e:
+            return ErrorResponse(
+                message=str(e),
+                session_id=session_id,
+            )
+        except Exception as e:
+            logger.error(f"Error reading workspace file: {e}", exc_info=True)
+            return ErrorResponse(
+                message=f"Failed to read workspace file: {str(e)}",
+                error=str(e),
+                session_id=session_id,
+            )
+
+
+class WriteWorkspaceFileTool(BaseTool):
+    """Tool for writing files to workspace."""
+
+    @property
+    def name(self) -> str:
+        return "write_workspace_file"
+
+    @property
+    def description(self) -> str:
+        return (
+            "Write or create a file in the user's workspace. "
+            "Provide the content as a base64-encoded string. "
+            "Maximum file size is 100MB. "
+            "Files are saved to the current session's folder by default. "
+            "Use /sessions/<session_id>/... for cross-session access."
+        )
+
+    @property
+    def parameters(self) -> dict[str, Any]:
+        return {
+            "type": "object",
+            "properties": {
+                "filename": {
+                    "type": "string",
+                    "description": "Name for the file (e.g., 'report.pdf')",
+                },
+                "content_base64": {
+                    "type": "string",
+                    "description": "Base64-encoded file content",
+                },
+                "path": {
+                    "type": "string",
+                    "description": (
+                        "Optional virtual path where to save the file "
+                        "(e.g., '/documents/report.pdf'). "
+                        "Defaults to '/{filename}'. Scoped to current session."
+                    ),
+                },
+                "mime_type": {
+                    "type": "string",
+                    "description": (
+                        "Optional MIME type of the file. "
+                        "Auto-detected from filename if not provided."
+                    ),
+                },
+                "overwrite": {
+                    "type": "boolean",
+                    "description": "Whether to overwrite if file exists at path (default: false)",
+                },
+            },
+            "required": ["filename", "content_base64"],
+        }
+
+    @property
+    def requires_auth(self) -> bool:
+        return True
+
+    async def _execute(
+        self,
+        user_id: str | None,
+        session: ChatSession,
+        **kwargs,
+    ) -> ToolResponseBase:
+        session_id = session.session_id
+
+        if not user_id:
+            return ErrorResponse(
+                message="Authentication required",
+                session_id=session_id,
+            )
+
+        filename: str = kwargs.get("filename", "")
+        content_b64: str = kwargs.get("content_base64", "")
+        path: Optional[str] = kwargs.get("path")
+        mime_type: Optional[str] = kwargs.get("mime_type")
+        overwrite: bool = kwargs.get("overwrite", False)
+
+        if not filename:
+            return ErrorResponse(
+                message="Please provide a filename",
+                session_id=session_id,
+            )
+
+        if not content_b64:
+            return ErrorResponse(
+                message="Please provide content_base64",
+                session_id=session_id,
+            )
+
+        # Decode content
+        try:
+            content = base64.b64decode(content_b64)
+        except Exception:
+            return ErrorResponse(
+                message="Invalid base64-encoded content",
+                session_id=session_id,
+            )
+
+        # Check size
+        if len(content) > MAX_FILE_SIZE_BYTES:
+            return ErrorResponse(
+                message=f"File too large. Maximum size is {MAX_FILE_SIZE_BYTES // (1024*1024)}MB",
+                session_id=session_id,
+            )
+
+        try:
+            # Virus scan
+            await scan_content_safe(content, filename=filename)
+
+            workspace = await get_or_create_workspace(user_id)
+            # Pass session_id for session-scoped file access
+            manager = WorkspaceManager(user_id, workspace.id, session_id)
+
+            file_record = await manager.write_file(
+                content=content,
+                filename=filename,
+                path=path,
+                mime_type=mime_type,
+                source=WorkspaceFileSource.COPILOT,
+                source_session_id=session.session_id,
+                overwrite=overwrite,
+            )
+
+            return WorkspaceWriteResponse(
+                file_id=file_record.id,
+                name=file_record.name,
+                path=file_record.path,
+                size_bytes=file_record.sizeBytes,
+                message=f"Successfully wrote file: {file_record.name}",
+                session_id=session_id,
+            )
+
+        except ValueError as e:
+            return ErrorResponse(
+                message=str(e),
+                session_id=session_id,
+            )
+        except Exception as e:
+            logger.error(f"Error writing workspace file: {e}", exc_info=True)
+            return ErrorResponse(
+                message=f"Failed to write workspace file: {str(e)}",
+                error=str(e),
+                session_id=session_id,
+            )
+
+
+class DeleteWorkspaceFileTool(BaseTool):
+    """Tool for deleting files from workspace."""
+
+    @property
+    def name(self) -> str:
+        return "delete_workspace_file"
+
+    @property
+    def description(self) -> str:
+        return (
+            "Delete a file from the user's workspace. "
+            "Specify either file_id or path to identify the file. "
+            "Paths are scoped to the current session by default. "
+            "Use /sessions/<session_id>/... for cross-session access."
+        )
+
+    @property
+    def parameters(self) -> dict[str, Any]:
+        return {
+            "type": "object",
+            "properties": {
+                "file_id": {
+                    "type": "string",
+                    "description": "The file's unique ID (from list_workspace_files)",
+                },
+                "path": {
+                    "type": "string",
+                    "description": (
+                        "The virtual file path (e.g., '/documents/report.pdf'). "
+                        "Scoped to current session by default."
+                    ),
+                },
+            },
+            "required": [],  # At least one must be provided
+        }
+
+    @property
+    def requires_auth(self) -> bool:
+        return True
+
+    async def _execute(
+        self,
+        user_id: str | None,
+        session: ChatSession,
+        **kwargs,
+    ) -> ToolResponseBase:
+        session_id = session.session_id
+
+        if not user_id:
+            return ErrorResponse(
+                message="Authentication required",
+                session_id=session_id,
+            )
+
+        file_id: Optional[str] = kwargs.get("file_id")
+        path: Optional[str] = kwargs.get("path")
+
+        if not file_id and not path:
+            return ErrorResponse(
+                message="Please provide either file_id or path",
+                session_id=session_id,
+            )
+
+        try:
+            workspace = await get_or_create_workspace(user_id)
+            # Pass session_id for session-scoped file access
+            manager = WorkspaceManager(user_id, workspace.id, session_id)
+
+            # Determine the file_id to delete
+            target_file_id: str
+            if file_id:
+                target_file_id = file_id
+            else:
+                # path is guaranteed to be non-None here due to the check above
+                assert path is not None
+                file_info = await manager.get_file_info_by_path(path)
+                if file_info is None:
+                    return ErrorResponse(
+                        message=f"File not found at path: {path}",
+                        session_id=session_id,
+                    )
+                target_file_id = file_info.id
+
+            success = await manager.delete_file(target_file_id)
+
+            if not success:
+                return ErrorResponse(
+                    message=f"File not found: {target_file_id}",
+                    session_id=session_id,
+                )
+
+            return WorkspaceDeleteResponse(
+                file_id=target_file_id,
+                success=True,
+                message="File deleted successfully",
+                session_id=session_id,
+            )
+
+        except Exception as e:
+            logger.error(f"Error deleting workspace file: {e}", exc_info=True)
+            return ErrorResponse(
+                message=f"Failed to delete workspace file: {str(e)}",
+                error=str(e),
+                session_id=session_id,
+            )

autogpt_platform/backend/backend/api/features/workspace/__init__.py

@@ -0,0 +1 @@
+# Workspace API feature module

autogpt_platform/backend/backend/api/features/workspace/models.py

@@ -0,0 +1,85 @@
+"""
+Pydantic models for the Workspace API.
+"""
+
+from datetime import datetime
+from typing import Any, Optional
+
+from prisma.enums import WorkspaceFileSource
+from pydantic import BaseModel, Field
+
+
+class WorkspaceInfo(BaseModel):
+    """Response model for workspace information."""
+
+    id: str
+    user_id: str
+    created_at: datetime
+    updated_at: datetime
+    file_count: int = 0
+
+
+class WorkspaceFileInfo(BaseModel):
+    """Response model for workspace file information."""
+
+    id: str
+    name: str
+    path: str
+    mime_type: str
+    size_bytes: int
+    checksum: Optional[str] = None
+    source: WorkspaceFileSource
+    source_exec_id: Optional[str] = None
+    source_session_id: Optional[str] = None
+    created_at: datetime
+    updated_at: datetime
+    metadata: dict[str, Any] = Field(default_factory=dict)
+
+
+class WorkspaceFileListResponse(BaseModel):
+    """Response model for listing workspace files."""
+
+    files: list[WorkspaceFileInfo]
+    total_count: int
+    path_filter: Optional[str] = None
+
+
+class UploadFileRequest(BaseModel):
+    """Request model for file upload metadata."""
+
+    filename: str
+    path: Optional[str] = None
+    mime_type: Optional[str] = None
+    overwrite: bool = False
+
+
+class WriteFileRequest(BaseModel):
+    """Request model for writing file content directly (for CoPilot tools)."""
+
+    filename: str
+    content_base64: str = Field(description="Base64-encoded file content")
+    path: Optional[str] = None
+    mime_type: Optional[str] = None
+    overwrite: bool = False
+
+
+class UploadFileResponse(BaseModel):
+    """Response model for file upload."""
+
+    file: WorkspaceFileInfo
+    message: str
+
+
+class DeleteFileResponse(BaseModel):
+    """Response model for file deletion."""
+
+    success: bool
+    file_id: str
+    message: str
+
+
+class DownloadUrlResponse(BaseModel):
+    """Response model for download URL."""
+
+    url: str
+    expires_in_seconds: int

autogpt_platform/backend/backend/api/features/workspace/routes.py

@@ -0,0 +1,495 @@
+"""
+Workspace API routes for managing user file storage.
+"""
+
+import base64
+import logging
+from typing import Annotated, Optional
+
+import fastapi
+from autogpt_libs.auth.dependencies import get_user_id, requires_user
+from fastapi import File, Query, UploadFile
+from fastapi.responses import Response
+from prisma.enums import WorkspaceFileSource
+
+from backend.data.workspace import (
+    count_workspace_files,
+    get_or_create_workspace,
+    get_workspace,
+    get_workspace_file,
+    get_workspace_file_by_path,
+)
+from backend.util.virus_scanner import scan_content_safe
+from backend.util.workspace import MAX_FILE_SIZE_BYTES, WorkspaceManager
+from backend.util.workspace_storage import get_workspace_storage
+
+from .models import (
+    DeleteFileResponse,
+    DownloadUrlResponse,
+    UploadFileResponse,
+    WorkspaceFileInfo,
+    WorkspaceFileListResponse,
+    WorkspaceInfo,
+    WriteFileRequest,
+)
+
+logger = logging.getLogger(__name__)
+
+router = fastapi.APIRouter(
+    dependencies=[fastapi.Security(requires_user)],
+)
+
+
+def _file_to_info(file) -> WorkspaceFileInfo:
+    """Convert database file record to API response model."""
+    return WorkspaceFileInfo(
+        id=file.id,
+        name=file.name,
+        path=file.path,
+        mime_type=file.mimeType,
+        size_bytes=file.sizeBytes,
+        checksum=file.checksum,
+        source=file.source,
+        source_exec_id=file.sourceExecId,
+        source_session_id=file.sourceSessionId,
+        created_at=file.createdAt,
+        updated_at=file.updatedAt,
+        metadata=file.metadata if file.metadata else {},
+    )
+
+
+@router.get(
+    "",
+    summary="Get workspace info",
+    response_model=WorkspaceInfo,
+)
+async def get_workspace_info(
+    user_id: Annotated[str, fastapi.Security(get_user_id)],
+) -> WorkspaceInfo:
+    """
+    Get the current user's workspace information.
+    Creates workspace if it doesn't exist.
+    """
+    workspace = await get_or_create_workspace(user_id)
+    file_count = await count_workspace_files(workspace.id)
+
+    return WorkspaceInfo(
+        id=workspace.id,
+        user_id=workspace.userId,
+        created_at=workspace.createdAt,
+        updated_at=workspace.updatedAt,
+        file_count=file_count,
+    )
+
+
+@router.post(
+    "/files",
+    summary="Upload file to workspace",
+    response_model=UploadFileResponse,
+)
+async def upload_file(
+    user_id: Annotated[str, fastapi.Security(get_user_id)],
+    file: UploadFile = File(...),
+    path: Annotated[Optional[str], Query()] = None,
+    overwrite: Annotated[bool, Query()] = False,
+) -> UploadFileResponse:
+    """
+    Upload a file to the user's workspace.
+
+    - **file**: The file to upload (max 100MB)
+    - **path**: Optional virtual path (defaults to "/{filename}")
+    - **overwrite**: Whether to overwrite existing file at path
+    """
+    workspace = await get_or_create_workspace(user_id)
+    manager = WorkspaceManager(user_id, workspace.id)
+
+    # Read file content
+    content = await file.read()
+
+    # Check file size
+    if len(content) > MAX_FILE_SIZE_BYTES:
+        raise fastapi.HTTPException(
+            status_code=413,
+            detail=f"File too large. Maximum size is {MAX_FILE_SIZE_BYTES // (1024*1024)}MB",
+        )
+
+    # Virus scan
+    filename = file.filename or "uploaded_file"
+    await scan_content_safe(content, filename=filename)
+
+    # Write file to workspace
+    try:
+        workspace_file = await manager.write_file(
+            content=content,
+            filename=filename,
+            path=path,
+            mime_type=file.content_type,
+            source=WorkspaceFileSource.UPLOAD,
+            overwrite=overwrite,
+        )
+    except ValueError as e:
+        raise fastapi.HTTPException(status_code=400, detail=str(e))
+
+    return UploadFileResponse(
+        file=_file_to_info(workspace_file),
+        message="File uploaded successfully",
+    )
+
+
+@router.post(
+    "/files/write",
+    summary="Write file content directly",
+    response_model=UploadFileResponse,
+)
+async def write_file_content(
+    user_id: Annotated[str, fastapi.Security(get_user_id)],
+    request: WriteFileRequest,
+) -> UploadFileResponse:
+    """
+    Write file content directly to workspace (for programmatic access).
+
+    - **filename**: Name for the file
+    - **content_base64**: Base64-encoded file content
+    - **path**: Optional virtual path (defaults to "/{filename}")
+    - **mime_type**: Optional MIME type (auto-detected if not provided)
+    - **overwrite**: Whether to overwrite existing file at path
+    """
+    workspace = await get_or_create_workspace(user_id)
+    manager = WorkspaceManager(user_id, workspace.id)
+
+    # Decode content
+    try:
+        content = base64.b64decode(request.content_base64)
+    except Exception:
+        raise fastapi.HTTPException(
+            status_code=400, detail="Invalid base64-encoded content"
+        )
+
+    # Check file size
+    if len(content) > MAX_FILE_SIZE_BYTES:
+        raise fastapi.HTTPException(
+            status_code=413,
+            detail=f"File too large. Maximum size is {MAX_FILE_SIZE_BYTES // (1024*1024)}MB",
+        )
+
+    # Virus scan
+    await scan_content_safe(content, filename=request.filename)
+
+    # Write file to workspace
+    try:
+        workspace_file = await manager.write_file(
+            content=content,
+            filename=request.filename,
+            path=request.path,
+            mime_type=request.mime_type,
+            source=WorkspaceFileSource.UPLOAD,
+            overwrite=request.overwrite,
+        )
+    except ValueError as e:
+        raise fastapi.HTTPException(status_code=400, detail=str(e))
+
+    return UploadFileResponse(
+        file=_file_to_info(workspace_file),
+        message="File written successfully",
+    )
+
+
+@router.get(
+    "/files",
+    summary="List workspace files",
+    response_model=WorkspaceFileListResponse,
+)
+async def list_files(
+    user_id: Annotated[str, fastapi.Security(get_user_id)],
+    path: Annotated[Optional[str], Query(description="Path prefix filter")] = None,
+    limit: Annotated[int, Query(ge=1, le=100)] = 50,
+    offset: Annotated[int, Query(ge=0)] = 0,
+) -> WorkspaceFileListResponse:
+    """
+    List files in the user's workspace.
+
+    - **path**: Optional path prefix to filter results
+    - **limit**: Maximum number of files to return (1-100)
+    - **offset**: Number of files to skip
+    """
+    workspace = await get_workspace(user_id)
+    if workspace is None:
+        return WorkspaceFileListResponse(
+            files=[],
+            total_count=0,
+            path_filter=path,
+        )
+
+    manager = WorkspaceManager(user_id, workspace.id)
+    files = await manager.list_files(path=path, limit=limit, offset=offset)
+    total = await manager.get_file_count()
+
+    return WorkspaceFileListResponse(
+        files=[_file_to_info(f) for f in files],
+        total_count=total,
+        path_filter=path,
+    )
+
+
+@router.get(
+    "/files/{file_id}",
+    summary="Get file info by ID",
+    response_model=WorkspaceFileInfo,
+)
+async def get_file_info(
+    user_id: Annotated[str, fastapi.Security(get_user_id)],
+    file_id: str,
+) -> WorkspaceFileInfo:
+    """
+    Get file metadata by file ID.
+    """
+    workspace = await get_workspace(user_id)
+    if workspace is None:
+        raise fastapi.HTTPException(status_code=404, detail="Workspace not found")
+
+    file = await get_workspace_file(file_id, workspace.id)
+    if file is None:
+        raise fastapi.HTTPException(status_code=404, detail="File not found")
+
+    return _file_to_info(file)
+
+
+@router.get(
+    "/files/{file_id}/download",
+    summary="Download file by ID",
+)
+async def download_file(
+    user_id: Annotated[str, fastapi.Security(get_user_id)],
+    file_id: str,
+) -> Response:
+    """
+    Download a file by its ID.
+
+    Returns the file content directly or redirects to a signed URL for GCS.
+    """
+    workspace = await get_workspace(user_id)
+    if workspace is None:
+        raise fastapi.HTTPException(status_code=404, detail="Workspace not found")
+
+    file = await get_workspace_file(file_id, workspace.id)
+    if file is None:
+        raise fastapi.HTTPException(status_code=404, detail="File not found")
+
+    storage = await get_workspace_storage()
+
+    # For local storage, stream the file directly
+    if file.storagePath.startswith("local://"):
+        content = await storage.retrieve(file.storagePath)
+        return Response(
+            content=content,
+            media_type=file.mimeType,
+            headers={
+                "Content-Disposition": f'attachment; filename="{file.name}"',
+                "Content-Length": str(len(content)),
+            },
+        )
+
+    # For GCS, try to redirect to signed URL, fall back to streaming
+    try:
+        url = await storage.get_download_url(file.storagePath, expires_in=300)
+        # If we got back an API path (fallback), stream directly instead
+        if url.startswith("/api/"):
+            content = await storage.retrieve(file.storagePath)
+            return Response(
+                content=content,
+                media_type=file.mimeType,
+                headers={
+                    "Content-Disposition": f'attachment; filename="{file.name}"',
+                    "Content-Length": str(len(content)),
+                },
+            )
+        return fastapi.responses.RedirectResponse(url=url, status_code=302)
+    except Exception:
+        # Fall back to streaming directly from GCS
+        content = await storage.retrieve(file.storagePath)
+        return Response(
+            content=content,
+            media_type=file.mimeType,
+            headers={
+                "Content-Disposition": f'attachment; filename="{file.name}"',
+                "Content-Length": str(len(content)),
+            },
+        )
+
+
+@router.get(
+    "/files/{file_id}/url",
+    summary="Get download URL",
+    response_model=DownloadUrlResponse,
+)
+async def get_download_url(
+    user_id: Annotated[str, fastapi.Security(get_user_id)],
+    file_id: str,
+    expires_in: Annotated[int, Query(ge=60, le=86400)] = 3600,
+) -> DownloadUrlResponse:
+    """
+    Get a download URL for a file.
+
+    - **expires_in**: URL expiration time in seconds (60-86400, default 3600)
+    """
+    workspace = await get_workspace(user_id)
+    if workspace is None:
+        raise fastapi.HTTPException(status_code=404, detail="Workspace not found")
+
+    manager = WorkspaceManager(user_id, workspace.id)
+
+    try:
+        url = await manager.get_download_url(file_id, expires_in)
+    except FileNotFoundError:
+        raise fastapi.HTTPException(status_code=404, detail="File not found")
+
+    return DownloadUrlResponse(
+        url=url,
+        expires_in_seconds=expires_in,
+    )
+
+
+@router.delete(
+    "/files/{file_id}",
+    summary="Delete file by ID",
+    response_model=DeleteFileResponse,
+)
+async def delete_file(
+    user_id: Annotated[str, fastapi.Security(get_user_id)],
+    file_id: str,
+) -> DeleteFileResponse:
+    """
+    Delete a file from the workspace (soft-delete).
+    """
+    workspace = await get_workspace(user_id)
+    if workspace is None:
+        raise fastapi.HTTPException(status_code=404, detail="Workspace not found")
+
+    manager = WorkspaceManager(user_id, workspace.id)
+    success = await manager.delete_file(file_id)
+
+    if not success:
+        raise fastapi.HTTPException(status_code=404, detail="File not found")
+
+    return DeleteFileResponse(
+        success=True,
+        file_id=file_id,
+        message="File deleted successfully",
+    )
+
+
+# By-path endpoints
+
+
+@router.get(
+    "/files/by-path",
+    summary="Get file info by path",
+    response_model=WorkspaceFileInfo,
+)
+async def get_file_by_path(
+    user_id: Annotated[str, fastapi.Security(get_user_id)],
+    path: Annotated[str, Query(description="Virtual file path")],
+) -> WorkspaceFileInfo:
+    """
+    Get file metadata by virtual path.
+    """
+    workspace = await get_workspace(user_id)
+    if workspace is None:
+        raise fastapi.HTTPException(status_code=404, detail="Workspace not found")
+
+    file = await get_workspace_file_by_path(workspace.id, path)
+    if file is None:
+        raise fastapi.HTTPException(status_code=404, detail="File not found")
+
+    return _file_to_info(file)
+
+
+@router.get(
+    "/files/by-path/download",
+    summary="Download file by path",
+)
+async def download_file_by_path(
+    user_id: Annotated[str, fastapi.Security(get_user_id)],
+    path: Annotated[str, Query(description="Virtual file path")],
+) -> Response:
+    """
+    Download a file by its virtual path.
+    """
+    workspace = await get_workspace(user_id)
+    if workspace is None:
+        raise fastapi.HTTPException(status_code=404, detail="Workspace not found")
+
+    file = await get_workspace_file_by_path(workspace.id, path)
+    if file is None:
+        raise fastapi.HTTPException(status_code=404, detail="File not found")
+
+    storage = await get_workspace_storage()
+
+    # For local storage, stream the file directly
+    if file.storagePath.startswith("local://"):
+        content = await storage.retrieve(file.storagePath)
+        return Response(
+            content=content,
+            media_type=file.mimeType,
+            headers={
+                "Content-Disposition": f'attachment; filename="{file.name}"',
+                "Content-Length": str(len(content)),
+            },
+        )
+
+    # For GCS, try to redirect to signed URL, fall back to streaming
+    try:
+        url = await storage.get_download_url(file.storagePath, expires_in=300)
+        # If we got back an API path (fallback), stream directly instead
+        if url.startswith("/api/"):
+            content = await storage.retrieve(file.storagePath)
+            return Response(
+                content=content,
+                media_type=file.mimeType,
+                headers={
+                    "Content-Disposition": f'attachment; filename="{file.name}"',
+                    "Content-Length": str(len(content)),
+                },
+            )
+        return fastapi.responses.RedirectResponse(url=url, status_code=302)
+    except Exception:
+        # Fall back to streaming directly from GCS
+        content = await storage.retrieve(file.storagePath)
+        return Response(
+            content=content,
+            media_type=file.mimeType,
+            headers={
+                "Content-Disposition": f'attachment; filename="{file.name}"',
+                "Content-Length": str(len(content)),
+            },
+        )
+
+
+@router.delete(
+    "/files/by-path",
+    summary="Delete file by path",
+    response_model=DeleteFileResponse,
+)
+async def delete_file_by_path(
+    user_id: Annotated[str, fastapi.Security(get_user_id)],
+    path: Annotated[str, Query(description="Virtual file path")],
+) -> DeleteFileResponse:
+    """
+    Delete a file by its virtual path (soft-delete).
+    """
+    workspace = await get_workspace(user_id)
+    if workspace is None:
+        raise fastapi.HTTPException(status_code=404, detail="Workspace not found")
+
+    file = await get_workspace_file_by_path(workspace.id, path)
+    if file is None:
+        raise fastapi.HTTPException(status_code=404, detail="File not found")
+
+    manager = WorkspaceManager(user_id, workspace.id)
+    success = await manager.delete_file(file.id)
+
+    return DeleteFileResponse(
+        success=success,
+        file_id=file.id,
+        message="File deleted successfully" if success else "Failed to delete file",
+    )

autogpt_platform/backend/backend/api/rest_api.py

@@ -32,6 +32,7 @@ import backend.api.features.postmark.postmark
 import backend.api.features.store.model
 import backend.api.features.store.routes
 import backend.api.features.v1
+import backend.api.features.workspace.routes as workspace_routes
 import backend.data.block
 import backend.data.db
 import backend.data.graph
@@ -315,6 +316,11 @@ app.include_router(
     tags=["v2", "chat"],
     prefix="/api/chat",
 )
+app.include_router(
+    workspace_routes.router,
+    tags=["v2", "workspace"],
+    prefix="/api/workspace",
+)
 app.include_router(
     backend.api.features.oauth.router,
     tags=["oauth"],

autogpt_platform/backend/backend/blocks/ai_image_customizer.py

@@ -13,6 +13,7 @@ from backend.data.block import (
     BlockSchemaInput,
     BlockSchemaOutput,
 )
+from backend.data.execution import ExecutionContext
 from backend.data.model import (
     APIKeyCredentials,
     CredentialsField,
@@ -132,8 +133,7 @@ class AIImageCustomizerBlock(Block):
         input_data: Input,
         *,
         credentials: APIKeyCredentials,
-        graph_exec_id: str,
-        user_id: str,
+        execution_context: ExecutionContext,
         **kwargs,
     ) -> BlockOutput:
         try:
@@ -141,10 +141,9 @@ class AIImageCustomizerBlock(Block):
             processed_images = await asyncio.gather(
                 *(
                     store_media_file(
-                        graph_exec_id=graph_exec_id,
                         file=img,
-                        user_id=user_id,
-                        return_content=True,
+                        execution_context=execution_context,
+                        return_format="for_external_api",  # Get content for Replicate API
                     )
                     for img in input_data.images
                 )
@@ -158,7 +157,14 @@ class AIImageCustomizerBlock(Block):
                 aspect_ratio=input_data.aspect_ratio.value,
                 output_format=input_data.output_format.value,
             )
-            yield "image_url", result
+
+            # Store the generated image to the user's workspace for persistence
+            stored_url = await store_media_file(
+                file=result,
+                execution_context=execution_context,
+                return_format="for_block_output",
+            )
+            yield "image_url", stored_url
         except Exception as e:
             yield "error", str(e)
 

autogpt_platform/backend/backend/blocks/ai_image_generator_block.py

@@ -6,6 +6,7 @@ from replicate.client import Client as ReplicateClient
 from replicate.helpers import FileOutput
 
 from backend.data.block import Block, BlockCategory, BlockSchemaInput, BlockSchemaOutput
+from backend.data.execution import ExecutionContext
 from backend.data.model import (
     APIKeyCredentials,
     CredentialsField,
@@ -13,6 +14,8 @@ from backend.data.model import (
     SchemaField,
 )
 from backend.integrations.providers import ProviderName
+from backend.util.file import store_media_file
+from backend.util.type import MediaFileType
 
 
 class ImageSize(str, Enum):
@@ -165,11 +168,13 @@ class AIImageGeneratorBlock(Block):
             test_output=[
                 (
                     "image_url",
-                    "https://replicate.delivery/generated-image.webp",
+                    # Test output is a data URI since we now store images
+                    lambda x: x.startswith("data:image/"),
                 ),
             ],
             test_mock={
-                "_run_client": lambda *args, **kwargs: "https://replicate.delivery/generated-image.webp"
+                # Return a data URI directly so store_media_file doesn't need to download
+                "_run_client": lambda *args, **kwargs: "data:image/webp;base64,UklGRiQAAABXRUJQVlA4IBgAAAAwAQCdASoBAAEAAQAcJYgCdAEO"
             },
         )
 
@@ -318,11 +323,24 @@ class AIImageGeneratorBlock(Block):
         style_text = style_map.get(style, "")
         return f"{style_text} of" if style_text else ""
 
-    async def run(self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs):
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: APIKeyCredentials,
+        execution_context: ExecutionContext,
+        **kwargs,
+    ):
         try:
             url = await self.generate_image(input_data, credentials)
             if url:
-                yield "image_url", url
+                # Store the generated image to the user's workspace/execution folder
+                stored_url = await store_media_file(
+                    file=MediaFileType(url),
+                    execution_context=execution_context,
+                    return_format="for_block_output",
+                )
+                yield "image_url", stored_url
             else:
                 yield "error", "Image generation returned an empty result."
         except Exception as e:

autogpt_platform/backend/backend/blocks/ai_shortform_video_block.py

@@ -13,6 +13,7 @@ from backend.data.block import (
     BlockSchemaInput,
     BlockSchemaOutput,
 )
+from backend.data.execution import ExecutionContext
 from backend.data.model import (
     APIKeyCredentials,
     CredentialsField,
@@ -21,7 +22,9 @@ from backend.data.model import (
 )
 from backend.integrations.providers import ProviderName
 from backend.util.exceptions import BlockExecutionError
+from backend.util.file import store_media_file
 from backend.util.request import Requests
+from backend.util.type import MediaFileType
 
 TEST_CREDENTIALS = APIKeyCredentials(
     id="01234567-89ab-cdef-0123-456789abcdef",
@@ -288,7 +291,12 @@ class AIShortformVideoCreatorBlock(Block):
         )
 
     async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+        self,
+        input_data: Input,
+        *,
+        credentials: APIKeyCredentials,
+        execution_context: ExecutionContext,
+        **kwargs,
     ) -> BlockOutput:
         # Create a new Webhook.site URL
         webhook_token, webhook_url = await self.create_webhook()
@@ -340,7 +348,13 @@ class AIShortformVideoCreatorBlock(Block):
             )
             video_url = await self.wait_for_video(credentials.api_key, pid)
             logger.debug(f"Video ready: {video_url}")
-            yield "video_url", video_url
+            # Store the generated video to the user's workspace for persistence
+            stored_url = await store_media_file(
+                file=MediaFileType(video_url),
+                execution_context=execution_context,
+                return_format="for_block_output",
+            )
+            yield "video_url", stored_url
 
 
 class AIAdMakerVideoCreatorBlock(Block):
@@ -463,7 +477,14 @@ class AIAdMakerVideoCreatorBlock(Block):
             test_credentials=TEST_CREDENTIALS,
         )
 
-    async def run(self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs):
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: APIKeyCredentials,
+        execution_context: ExecutionContext,
+        **kwargs,
+    ):
         webhook_token, webhook_url = await self.create_webhook()
 
         payload = {
@@ -531,7 +552,13 @@ class AIAdMakerVideoCreatorBlock(Block):
             raise RuntimeError("Failed to create video: No project ID returned")
 
         video_url = await self.wait_for_video(credentials.api_key, pid)
-        yield "video_url", video_url
+        # Store the generated video to the user's workspace for persistence
+        stored_url = await store_media_file(
+            file=MediaFileType(video_url),
+            execution_context=execution_context,
+            return_format="for_block_output",
+        )
+        yield "video_url", stored_url
 
 
 class AIScreenshotToVideoAdBlock(Block):
@@ -642,7 +669,14 @@ class AIScreenshotToVideoAdBlock(Block):
             test_credentials=TEST_CREDENTIALS,
         )
 
-    async def run(self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs):
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: APIKeyCredentials,
+        execution_context: ExecutionContext,
+        **kwargs,
+    ):
         webhook_token, webhook_url = await self.create_webhook()
 
         payload = {
@@ -710,4 +744,10 @@ class AIScreenshotToVideoAdBlock(Block):
             raise RuntimeError("Failed to create video: No project ID returned")
 
         video_url = await self.wait_for_video(credentials.api_key, pid)
-        yield "video_url", video_url
+        # Store the generated video to the user's workspace for persistence
+        stored_url = await store_media_file(
+            file=MediaFileType(video_url),
+            execution_context=execution_context,
+            return_format="for_block_output",
+        )
+        yield "video_url", stored_url

autogpt_platform/backend/backend/blocks/bannerbear/text_overlay.py

@@ -6,6 +6,7 @@ if TYPE_CHECKING:
 
 from pydantic import SecretStr
 
+from backend.data.execution import ExecutionContext
 from backend.sdk import (
     APIKeyCredentials,
     Block,
@@ -17,6 +18,8 @@ from backend.sdk import (
     Requests,
     SchemaField,
 )
+from backend.util.file import store_media_file
+from backend.util.type import MediaFileType
 
 from ._config import bannerbear
 
@@ -177,7 +180,12 @@ class BannerbearTextOverlayBlock(Block):
             raise Exception(error_msg)
 
     async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+        self,
+        input_data: Input,
+        *,
+        credentials: APIKeyCredentials,
+        execution_context: ExecutionContext,
+        **kwargs,
     ) -> BlockOutput:
         # Build the modifications array
         modifications = []
@@ -234,6 +242,18 @@ class BannerbearTextOverlayBlock(Block):
 
         # Synchronous request - image should be ready
         yield "success", True
-        yield "image_url", data.get("image_url", "")
+
+        # Store the generated image to workspace for persistence
+        image_url = data.get("image_url", "")
+        if image_url:
+            stored_url = await store_media_file(
+                file=MediaFileType(image_url),
+                execution_context=execution_context,
+                return_format="for_block_output",
+            )
+            yield "image_url", stored_url
+        else:
+            yield "image_url", ""
+
         yield "uid", data.get("uid", "")
         yield "status", data.get("status", "completed")

autogpt_platform/backend/backend/blocks/basic.py

@@ -9,6 +9,7 @@ from backend.data.block import (
     BlockSchemaOutput,
     BlockType,
 )
+from backend.data.execution import ExecutionContext
 from backend.data.model import SchemaField
 from backend.util.file import store_media_file
 from backend.util.type import MediaFileType, convert
@@ -45,15 +46,20 @@ class FileStoreBlock(Block):
         self,
         input_data: Input,
         *,
-        graph_exec_id: str,
-        user_id: str,
+        execution_context: ExecutionContext,
         **kwargs,
     ) -> BlockOutput:
+        # Determine return format based on user preference
+        # for_block_output: returns workspace:// if available, else data URI
+        # for_local_processing: returns local file path
+        return_format = (
+            "for_block_output" if input_data.base_64 else "for_local_processing"
+        )
+
         yield "file_out", await store_media_file(
-            graph_exec_id=graph_exec_id,
             file=input_data.file_in,
-            user_id=user_id,
-            return_content=input_data.base_64,
+            execution_context=execution_context,
+            return_format=return_format,
         )
 
 

autogpt_platform/backend/backend/blocks/discord/bot_blocks.py

@@ -15,6 +15,7 @@ from backend.data.block import (
     BlockSchemaInput,
     BlockSchemaOutput,
 )
+from backend.data.execution import ExecutionContext
 from backend.data.model import APIKeyCredentials, SchemaField
 from backend.util.file import store_media_file
 from backend.util.request import Requests
@@ -666,8 +667,7 @@ class SendDiscordFileBlock(Block):
         file: MediaFileType,
         filename: str,
         message_content: str,
-        graph_exec_id: str,
-        user_id: str,
+        execution_context: ExecutionContext,
     ) -> dict:
         intents = discord.Intents.default()
         intents.guilds = True
@@ -731,10 +731,9 @@ class SendDiscordFileBlock(Block):
                     # Local file path - read from stored media file
                     # This would be a path from a previous block's output
                     stored_file = await store_media_file(
-                        graph_exec_id=graph_exec_id,
                         file=file,
-                        user_id=user_id,
-                        return_content=True,  # Get as data URI
+                        execution_context=execution_context,
+                        return_format="for_external_api",  # Get content to send to Discord
                     )
                     # Now process as data URI
                     header, encoded = stored_file.split(",", 1)
@@ -781,8 +780,7 @@ class SendDiscordFileBlock(Block):
         input_data: Input,
         *,
         credentials: APIKeyCredentials,
-        graph_exec_id: str,
-        user_id: str,
+        execution_context: ExecutionContext,
         **kwargs,
     ) -> BlockOutput:
         try:
@@ -793,8 +791,7 @@ class SendDiscordFileBlock(Block):
                 file=input_data.file,
                 filename=input_data.filename,
                 message_content=input_data.message_content,
-                graph_exec_id=graph_exec_id,
-                user_id=user_id,
+                execution_context=execution_context,
             )
 
             yield "status", result.get("status", "Unknown error")

autogpt_platform/backend/backend/blocks/fal/ai_video_generator.py

@@ -17,8 +17,11 @@ from backend.data.block import (
     BlockSchemaInput,
     BlockSchemaOutput,
 )
+from backend.data.execution import ExecutionContext
 from backend.data.model import SchemaField
+from backend.util.file import store_media_file
 from backend.util.request import ClientResponseError, Requests
+from backend.util.type import MediaFileType
 
 logger = logging.getLogger(__name__)
 
@@ -208,11 +211,22 @@ class AIVideoGeneratorBlock(Block):
             raise RuntimeError(f"API request failed: {str(e)}")
 
     async def run(
-        self, input_data: Input, *, credentials: FalCredentials, **kwargs
+        self,
+        input_data: Input,
+        *,
+        credentials: FalCredentials,
+        execution_context: ExecutionContext,
+        **kwargs,
     ) -> BlockOutput:
         try:
             video_url = await self.generate_video(input_data, credentials)
-            yield "video_url", video_url
+            # Store the generated video to the user's workspace for persistence
+            stored_url = await store_media_file(
+                file=MediaFileType(video_url),
+                execution_context=execution_context,
+                return_format="for_block_output",
+            )
+            yield "video_url", stored_url
         except Exception as e:
             error_message = str(e)
             yield "error", error_message

autogpt_platform/backend/backend/blocks/flux_kontext.py

@@ -12,6 +12,7 @@ from backend.data.block import (
     BlockSchemaInput,
     BlockSchemaOutput,
 )
+from backend.data.execution import ExecutionContext
 from backend.data.model import (
     APIKeyCredentials,
     CredentialsField,
@@ -134,8 +135,7 @@ class AIImageEditorBlock(Block):
         input_data: Input,
         *,
         credentials: APIKeyCredentials,
-        graph_exec_id: str,
-        user_id: str,
+        execution_context: ExecutionContext,
         **kwargs,
     ) -> BlockOutput:
         result = await self.run_model(
@@ -144,20 +144,25 @@ class AIImageEditorBlock(Block):
             prompt=input_data.prompt,
             input_image_b64=(
                 await store_media_file(
-                    graph_exec_id=graph_exec_id,
                     file=input_data.input_image,
-                    user_id=user_id,
-                    return_content=True,
+                    execution_context=execution_context,
+                    return_format="for_external_api",  # Get content for Replicate API
                 )
                 if input_data.input_image
                 else None
             ),
             aspect_ratio=input_data.aspect_ratio.value,
             seed=input_data.seed,
-            user_id=user_id,
-            graph_exec_id=graph_exec_id,
+            user_id=execution_context.user_id or "",
+            graph_exec_id=execution_context.graph_exec_id or "",
         )
-        yield "output_image", result
+        # Store the generated image to the user's workspace for persistence
+        stored_url = await store_media_file(
+            file=result,
+            execution_context=execution_context,
+            return_format="for_block_output",
+        )
+        yield "output_image", stored_url
 
     async def run_model(
         self,

autogpt_platform/backend/backend/blocks/google/gmail.py

@@ -21,6 +21,7 @@ from backend.data.block import (
     BlockSchemaInput,
     BlockSchemaOutput,
 )
+from backend.data.execution import ExecutionContext
 from backend.data.model import SchemaField
 from backend.util.file import MediaFileType, get_exec_file_path, store_media_file
 from backend.util.settings import Settings
@@ -95,8 +96,7 @@ def _make_mime_text(
 
 async def create_mime_message(
     input_data,
-    graph_exec_id: str,
-    user_id: str,
+    execution_context: ExecutionContext,
 ) -> str:
     """Create a MIME message with attachments and return base64-encoded raw message."""
 
@@ -117,12 +117,13 @@ async def create_mime_message(
     if input_data.attachments:
         for attach in input_data.attachments:
             local_path = await store_media_file(
-                user_id=user_id,
-                graph_exec_id=graph_exec_id,
                 file=attach,
-                return_content=False,
+                execution_context=execution_context,
+                return_format="for_local_processing",
+            )
+            abs_path = get_exec_file_path(
+                execution_context.graph_exec_id or "", local_path
             )
-            abs_path = get_exec_file_path(graph_exec_id, local_path)
             part = MIMEBase("application", "octet-stream")
             with open(abs_path, "rb") as f:
                 part.set_payload(f.read())
@@ -582,27 +583,25 @@ class GmailSendBlock(GmailBase):
         input_data: Input,
         *,
         credentials: GoogleCredentials,
-        graph_exec_id: str,
-        user_id: str,
+        execution_context: ExecutionContext,
         **kwargs,
     ) -> BlockOutput:
         service = self._build_service(credentials, **kwargs)
         result = await self._send_email(
             service,
             input_data,
-            graph_exec_id,
-            user_id,
+            execution_context,
         )
         yield "result", result
 
     async def _send_email(
-        self, service, input_data: Input, graph_exec_id: str, user_id: str
+        self, service, input_data: Input, execution_context: ExecutionContext
     ) -> dict:
         if not input_data.to or not input_data.subject or not input_data.body:
             raise ValueError(
                 "At least one recipient, subject, and body are required for sending an email"
             )
-        raw_message = await create_mime_message(input_data, graph_exec_id, user_id)
+        raw_message = await create_mime_message(input_data, execution_context)
         sent_message = await asyncio.to_thread(
             lambda: service.users()
             .messages()
@@ -692,30 +691,28 @@ class GmailCreateDraftBlock(GmailBase):
         input_data: Input,
         *,
         credentials: GoogleCredentials,
-        graph_exec_id: str,
-        user_id: str,
+        execution_context: ExecutionContext,
         **kwargs,
     ) -> BlockOutput:
         service = self._build_service(credentials, **kwargs)
         result = await self._create_draft(
             service,
             input_data,
-            graph_exec_id,
-            user_id,
+            execution_context,
         )
         yield "result", GmailDraftResult(
             id=result["id"], message_id=result["message"]["id"], status="draft_created"
         )
 
     async def _create_draft(
-        self, service, input_data: Input, graph_exec_id: str, user_id: str
+        self, service, input_data: Input, execution_context: ExecutionContext
     ) -> dict:
         if not input_data.to or not input_data.subject:
             raise ValueError(
                 "At least one recipient and subject are required for creating a draft"
             )
 
-        raw_message = await create_mime_message(input_data, graph_exec_id, user_id)
+        raw_message = await create_mime_message(input_data, execution_context)
         draft = await asyncio.to_thread(
             lambda: service.users()
             .drafts()
@@ -1100,7 +1097,7 @@ class GmailGetThreadBlock(GmailBase):
 
 
 async def _build_reply_message(
-    service, input_data, graph_exec_id: str, user_id: str
+    service, input_data, execution_context: ExecutionContext
 ) -> tuple[str, str]:
     """
     Builds a reply MIME message for Gmail threads.
@@ -1190,12 +1187,11 @@ async def _build_reply_message(
     # Handle attachments
     for attach in input_data.attachments:
         local_path = await store_media_file(
-            user_id=user_id,
-            graph_exec_id=graph_exec_id,
             file=attach,
-            return_content=False,
+            execution_context=execution_context,
+            return_format="for_local_processing",
         )
-        abs_path = get_exec_file_path(graph_exec_id, local_path)
+        abs_path = get_exec_file_path(execution_context.graph_exec_id or "", local_path)
         part = MIMEBase("application", "octet-stream")
         with open(abs_path, "rb") as f:
             part.set_payload(f.read())
@@ -1311,16 +1307,14 @@ class GmailReplyBlock(GmailBase):
         input_data: Input,
         *,
         credentials: GoogleCredentials,
-        graph_exec_id: str,
-        user_id: str,
+        execution_context: ExecutionContext,
         **kwargs,
     ) -> BlockOutput:
         service = self._build_service(credentials, **kwargs)
         message = await self._reply(
             service,
             input_data,
-            graph_exec_id,
-            user_id,
+            execution_context,
         )
         yield "messageId", message["id"]
         yield "threadId", message.get("threadId", input_data.threadId)
@@ -1343,11 +1337,11 @@ class GmailReplyBlock(GmailBase):
         yield "email", email
 
     async def _reply(
-        self, service, input_data: Input, graph_exec_id: str, user_id: str
+        self, service, input_data: Input, execution_context: ExecutionContext
     ) -> dict:
         # Build the reply message using the shared helper
         raw, thread_id = await _build_reply_message(
-            service, input_data, graph_exec_id, user_id
+            service, input_data, execution_context
         )
 
         # Send the message
@@ -1441,16 +1435,14 @@ class GmailDraftReplyBlock(GmailBase):
         input_data: Input,
         *,
         credentials: GoogleCredentials,
-        graph_exec_id: str,
-        user_id: str,
+        execution_context: ExecutionContext,
         **kwargs,
     ) -> BlockOutput:
         service = self._build_service(credentials, **kwargs)
         draft = await self._create_draft_reply(
             service,
             input_data,
-            graph_exec_id,
-            user_id,
+            execution_context,
         )
         yield "draftId", draft["id"]
         yield "messageId", draft["message"]["id"]
@@ -1458,11 +1450,11 @@ class GmailDraftReplyBlock(GmailBase):
         yield "status", "draft_created"
 
     async def _create_draft_reply(
-        self, service, input_data: Input, graph_exec_id: str, user_id: str
+        self, service, input_data: Input, execution_context: ExecutionContext
     ) -> dict:
         # Build the reply message using the shared helper
         raw, thread_id = await _build_reply_message(
-            service, input_data, graph_exec_id, user_id
+            service, input_data, execution_context
         )
 
         # Create draft with proper thread association
@@ -1629,23 +1621,21 @@ class GmailForwardBlock(GmailBase):
         input_data: Input,
         *,
         credentials: GoogleCredentials,
-        graph_exec_id: str,
-        user_id: str,
+        execution_context: ExecutionContext,
         **kwargs,
     ) -> BlockOutput:
         service = self._build_service(credentials, **kwargs)
         result = await self._forward_message(
             service,
             input_data,
-            graph_exec_id,
-            user_id,
+            execution_context,
         )
         yield "messageId", result["id"]
         yield "threadId", result.get("threadId", "")
         yield "status", "forwarded"
 
     async def _forward_message(
-        self, service, input_data: Input, graph_exec_id: str, user_id: str
+        self, service, input_data: Input, execution_context: ExecutionContext
     ) -> dict:
         if not input_data.to:
             raise ValueError("At least one recipient is required for forwarding")
@@ -1727,12 +1717,13 @@ To: {original_to}
         # Add any additional attachments
         for attach in input_data.additionalAttachments:
             local_path = await store_media_file(
-                user_id=user_id,
-                graph_exec_id=graph_exec_id,
                 file=attach,
-                return_content=False,
+                execution_context=execution_context,
+                return_format="for_local_processing",
+            )
+            abs_path = get_exec_file_path(
+                execution_context.graph_exec_id or "", local_path
             )
-            abs_path = get_exec_file_path(graph_exec_id, local_path)
             part = MIMEBase("application", "octet-stream")
             with open(abs_path, "rb") as f:
                 part.set_payload(f.read())

autogpt_platform/backend/backend/blocks/http.py

@@ -15,6 +15,7 @@ from backend.data.block import (
     BlockSchemaInput,
     BlockSchemaOutput,
 )
+from backend.data.execution import ExecutionContext
 from backend.data.model import (
     CredentialsField,
     CredentialsMetaInput,
@@ -116,10 +117,9 @@ class SendWebRequestBlock(Block):
 
     @staticmethod
     async def _prepare_files(
-        graph_exec_id: str,
+        execution_context: ExecutionContext,
         files_name: str,
         files: list[MediaFileType],
-        user_id: str,
     ) -> list[tuple[str, tuple[str, BytesIO, str]]]:
         """
         Prepare files for the request by storing them and reading their content.
@@ -127,11 +127,15 @@ class SendWebRequestBlock(Block):
         (files_name, (filename, BytesIO, mime_type))
         """
         files_payload: list[tuple[str, tuple[str, BytesIO, str]]] = []
+        graph_exec_id = execution_context.graph_exec_id
+        assert graph_exec_id is not None
 
         for media in files:
             # Normalise to a list so we can repeat the same key
             rel_path = await store_media_file(
-                graph_exec_id, media, user_id, return_content=False
+                file=media,
+                execution_context=execution_context,
+                return_format="for_local_processing",
             )
             abs_path = get_exec_file_path(graph_exec_id, rel_path)
             async with aiofiles.open(abs_path, "rb") as f:
@@ -143,7 +147,7 @@ class SendWebRequestBlock(Block):
         return files_payload
 
     async def run(
-        self, input_data: Input, *, graph_exec_id: str, user_id: str, **kwargs
+        self, input_data: Input, *, execution_context: ExecutionContext, **kwargs
     ) -> BlockOutput:
         # ─── Parse/normalise body ────────────────────────────────────
         body = input_data.body
@@ -174,7 +178,7 @@ class SendWebRequestBlock(Block):
         files_payload: list[tuple[str, tuple[str, BytesIO, str]]] = []
         if use_files:
             files_payload = await self._prepare_files(
-                graph_exec_id, input_data.files_name, input_data.files, user_id
+                execution_context, input_data.files_name, input_data.files
             )
 
         # Enforce body format rules
@@ -238,9 +242,8 @@ class SendAuthenticatedWebRequestBlock(SendWebRequestBlock):
         self,
         input_data: Input,
         *,
-        graph_exec_id: str,
+        execution_context: ExecutionContext,
         credentials: HostScopedCredentials,
-        user_id: str,
         **kwargs,
     ) -> BlockOutput:
         # Create SendWebRequestBlock.Input from our input (removing credentials field)
@@ -271,6 +274,6 @@ class SendAuthenticatedWebRequestBlock(SendWebRequestBlock):
 
         # Use parent class run method
         async for output_name, output_data in super().run(
-            base_input, graph_exec_id=graph_exec_id, user_id=user_id, **kwargs
+            base_input, execution_context=execution_context, **kwargs
         ):
             yield output_name, output_data

autogpt_platform/backend/backend/blocks/io.py

@@ -12,6 +12,7 @@ from backend.data.block import (
     BlockSchemaInput,
     BlockType,
 )
+from backend.data.execution import ExecutionContext
 from backend.data.model import SchemaField
 from backend.util.file import store_media_file
 from backend.util.mock import MockObject
@@ -462,18 +463,23 @@ class AgentFileInputBlock(AgentInputBlock):
         self,
         input_data: Input,
         *,
-        graph_exec_id: str,
-        user_id: str,
+        execution_context: ExecutionContext,
         **kwargs,
     ) -> BlockOutput:
         if not input_data.value:
             return
 
+        # Determine return format based on user preference
+        # for_block_output: returns workspace:// if available, else data URI
+        # for_local_processing: returns local file path
+        return_format = (
+            "for_block_output" if input_data.base_64 else "for_local_processing"
+        )
+
         yield "result", await store_media_file(
-            graph_exec_id=graph_exec_id,
             file=input_data.value,
-            user_id=user_id,
-            return_content=input_data.base_64,
+            execution_context=execution_context,
+            return_format=return_format,
         )
 
 

autogpt_platform/backend/backend/blocks/media.py

@@ -13,6 +13,7 @@ from backend.data.block import (
     BlockSchemaInput,
     BlockSchemaOutput,
 )
+from backend.data.execution import ExecutionContext
 from backend.data.model import SchemaField
 from backend.util.file import MediaFileType, get_exec_file_path, store_media_file
 
@@ -46,18 +47,19 @@ class MediaDurationBlock(Block):
         self,
         input_data: Input,
         *,
-        graph_exec_id: str,
-        user_id: str,
+        execution_context: ExecutionContext,
         **kwargs,
     ) -> BlockOutput:
         # 1) Store the input media locally
         local_media_path = await store_media_file(
-            graph_exec_id=graph_exec_id,
             file=input_data.media_in,
-            user_id=user_id,
-            return_content=False,
+            execution_context=execution_context,
+            return_format="for_local_processing",
+        )
+        assert execution_context.graph_exec_id is not None
+        media_abspath = get_exec_file_path(
+            execution_context.graph_exec_id, local_media_path
         )
-        media_abspath = get_exec_file_path(graph_exec_id, local_media_path)
 
         # 2) Load the clip
         if input_data.is_video:
@@ -111,17 +113,19 @@ class LoopVideoBlock(Block):
         self,
         input_data: Input,
         *,
-        node_exec_id: str,
-        graph_exec_id: str,
-        user_id: str,
+        execution_context: ExecutionContext,
         **kwargs,
     ) -> BlockOutput:
+        assert execution_context.graph_exec_id is not None
+        assert execution_context.node_exec_id is not None
+        graph_exec_id = execution_context.graph_exec_id
+        node_exec_id = execution_context.node_exec_id
+
         # 1) Store the input video locally
         local_video_path = await store_media_file(
-            graph_exec_id=graph_exec_id,
             file=input_data.video_in,
-            user_id=user_id,
-            return_content=False,
+            execution_context=execution_context,
+            return_format="for_local_processing",
         )
         input_abspath = get_exec_file_path(graph_exec_id, local_video_path)
 
@@ -149,12 +153,11 @@ class LoopVideoBlock(Block):
         looped_clip = looped_clip.with_audio(clip.audio)
         looped_clip.write_videofile(output_abspath, codec="libx264", audio_codec="aac")
 
-        # Return as data URI
+        # Return output - for_block_output returns workspace:// if available, else data URI
         video_out = await store_media_file(
-            graph_exec_id=graph_exec_id,
             file=output_filename,
-            user_id=user_id,
-            return_content=input_data.output_return_type == "data_uri",
+            execution_context=execution_context,
+            return_format="for_block_output",
         )
 
         yield "video_out", video_out
@@ -200,23 +203,24 @@ class AddAudioToVideoBlock(Block):
         self,
         input_data: Input,
         *,
-        node_exec_id: str,
-        graph_exec_id: str,
-        user_id: str,
+        execution_context: ExecutionContext,
         **kwargs,
     ) -> BlockOutput:
+        assert execution_context.graph_exec_id is not None
+        assert execution_context.node_exec_id is not None
+        graph_exec_id = execution_context.graph_exec_id
+        node_exec_id = execution_context.node_exec_id
+
         # 1) Store the inputs locally
         local_video_path = await store_media_file(
-            graph_exec_id=graph_exec_id,
             file=input_data.video_in,
-            user_id=user_id,
-            return_content=False,
+            execution_context=execution_context,
+            return_format="for_local_processing",
         )
         local_audio_path = await store_media_file(
-            graph_exec_id=graph_exec_id,
             file=input_data.audio_in,
-            user_id=user_id,
-            return_content=False,
+            execution_context=execution_context,
+            return_format="for_local_processing",
         )
 
         abs_temp_dir = os.path.join(tempfile.gettempdir(), "exec_file", graph_exec_id)
@@ -240,12 +244,11 @@ class AddAudioToVideoBlock(Block):
         output_abspath = os.path.join(abs_temp_dir, output_filename)
         final_clip.write_videofile(output_abspath, codec="libx264", audio_codec="aac")
 
-        # 5) Return either path or data URI
+        # 5) Return output - for_block_output returns workspace:// if available, else data URI
         video_out = await store_media_file(
-            graph_exec_id=graph_exec_id,
             file=output_filename,
-            user_id=user_id,
-            return_content=input_data.output_return_type == "data_uri",
+            execution_context=execution_context,
+            return_format="for_block_output",
         )
 
         yield "video_out", video_out

autogpt_platform/backend/backend/blocks/screenshotone.py

@@ -11,6 +11,7 @@ from backend.data.block import (
     BlockSchemaInput,
     BlockSchemaOutput,
 )
+from backend.data.execution import ExecutionContext
 from backend.data.model import (
     APIKeyCredentials,
     CredentialsField,
@@ -112,8 +113,7 @@ class ScreenshotWebPageBlock(Block):
     @staticmethod
     async def take_screenshot(
         credentials: APIKeyCredentials,
-        graph_exec_id: str,
-        user_id: str,
+        execution_context: ExecutionContext,
         url: str,
         viewport_width: int,
         viewport_height: int,
@@ -155,12 +155,11 @@ class ScreenshotWebPageBlock(Block):
 
         return {
             "image": await store_media_file(
-                graph_exec_id=graph_exec_id,
                 file=MediaFileType(
                     f"data:image/{format.value};base64,{b64encode(content).decode('utf-8')}"
                 ),
-                user_id=user_id,
-                return_content=True,
+                execution_context=execution_context,
+                return_format="for_block_output",
             )
         }
 
@@ -169,15 +168,13 @@ class ScreenshotWebPageBlock(Block):
         input_data: Input,
         *,
         credentials: APIKeyCredentials,
-        graph_exec_id: str,
-        user_id: str,
+        execution_context: ExecutionContext,
         **kwargs,
     ) -> BlockOutput:
         try:
             screenshot_data = await self.take_screenshot(
                 credentials=credentials,
-                graph_exec_id=graph_exec_id,
-                user_id=user_id,
+                execution_context=execution_context,
                 url=input_data.url,
                 viewport_width=input_data.viewport_width,
                 viewport_height=input_data.viewport_height,

autogpt_platform/backend/backend/blocks/spreadsheet.py

@@ -7,6 +7,7 @@ from backend.data.block import (
     BlockSchemaInput,
     BlockSchemaOutput,
 )
+from backend.data.execution import ExecutionContext
 from backend.data.model import ContributorDetails, SchemaField
 from backend.util.file import get_exec_file_path, store_media_file
 from backend.util.type import MediaFileType
@@ -98,7 +99,7 @@ class ReadSpreadsheetBlock(Block):
         )
 
     async def run(
-        self, input_data: Input, *, graph_exec_id: str, user_id: str, **_kwargs
+        self, input_data: Input, *, execution_context: ExecutionContext, **_kwargs
     ) -> BlockOutput:
         import csv
         from io import StringIO
@@ -106,14 +107,15 @@ class ReadSpreadsheetBlock(Block):
         # Determine data source - prefer file_input if provided, otherwise use contents
         if input_data.file_input:
             stored_file_path = await store_media_file(
-                user_id=user_id,
-                graph_exec_id=graph_exec_id,
                 file=input_data.file_input,
-                return_content=False,
+                execution_context=execution_context,
+                return_format="for_local_processing",
             )
 
             # Get full file path
-            file_path = get_exec_file_path(graph_exec_id, stored_file_path)
+            file_path = get_exec_file_path(
+                execution_context.graph_exec_id or "", stored_file_path
+            )
             if not Path(file_path).exists():
                 raise ValueError(f"File does not exist: {file_path}")
 

autogpt_platform/backend/backend/blocks/talking_head.py

@@ -10,6 +10,7 @@ from backend.data.block import (
     BlockSchemaInput,
     BlockSchemaOutput,
 )
+from backend.data.execution import ExecutionContext
 from backend.data.model import (
     APIKeyCredentials,
     CredentialsField,
@@ -17,7 +18,9 @@ from backend.data.model import (
     SchemaField,
 )
 from backend.integrations.providers import ProviderName
+from backend.util.file import store_media_file
 from backend.util.request import Requests
+from backend.util.type import MediaFileType
 
 TEST_CREDENTIALS = APIKeyCredentials(
     id="01234567-89ab-cdef-0123-456789abcdef",
@@ -138,7 +141,12 @@ class CreateTalkingAvatarVideoBlock(Block):
         return response.json()
 
     async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+        self,
+        input_data: Input,
+        *,
+        credentials: APIKeyCredentials,
+        execution_context: ExecutionContext,
+        **kwargs,
     ) -> BlockOutput:
         # Create the clip
         payload = {
@@ -165,7 +173,14 @@ class CreateTalkingAvatarVideoBlock(Block):
         for _ in range(input_data.max_polling_attempts):
             status_response = await self.get_clip_status(credentials.api_key, clip_id)
             if status_response["status"] == "done":
-                yield "video_url", status_response["result_url"]
+                # Store the generated video to the user's workspace for persistence
+                video_url = status_response["result_url"]
+                stored_url = await store_media_file(
+                    file=MediaFileType(video_url),
+                    execution_context=execution_context,
+                    return_format="for_block_output",
+                )
+                yield "video_url", stored_url
                 return
             elif status_response["status"] == "error":
                 raise RuntimeError(

autogpt_platform/backend/backend/blocks/test/test_blocks_dos_vulnerability.py

@@ -12,6 +12,7 @@ from backend.blocks.iteration import StepThroughItemsBlock
 from backend.blocks.llm import AITextSummarizerBlock
 from backend.blocks.text import ExtractTextInformationBlock
 from backend.blocks.xml_parser import XMLParserBlock
+from backend.data.execution import ExecutionContext
 from backend.util.file import store_media_file
 from backend.util.type import MediaFileType
 
@@ -233,9 +234,11 @@ class TestStoreMediaFileSecurity:
 
         with pytest.raises(ValueError, match="File too large"):
             await store_media_file(
-                graph_exec_id="test",
                 file=MediaFileType(large_data_uri),
-                user_id="test_user",
+                execution_context=ExecutionContext(
+                    user_id="test_user",
+                    graph_exec_id="test",
+                ),
             )
 
     @patch("backend.util.file.Path")
@@ -270,9 +273,11 @@ class TestStoreMediaFileSecurity:
         # Should raise an error when directory size exceeds limit
         with pytest.raises(ValueError, match="Disk usage limit exceeded"):
             await store_media_file(
-                graph_exec_id="test",
                 file=MediaFileType(
                     "data:text/plain;base64,dGVzdA=="
                 ),  # Small test file
-                user_id="test_user",
+                execution_context=ExecutionContext(
+                    user_id="test_user",
+                    graph_exec_id="test",
+                ),
             )

autogpt_platform/backend/backend/blocks/test/test_http.py

@@ -11,10 +11,22 @@ from backend.blocks.http import (
     HttpMethod,
     SendAuthenticatedWebRequestBlock,
 )
+from backend.data.execution import ExecutionContext
 from backend.data.model import HostScopedCredentials
 from backend.util.request import Response
 
 
+def make_test_context(
+    graph_exec_id: str = "test-exec-id",
+    user_id: str = "test-user-id",
+) -> ExecutionContext:
+    """Helper to create test ExecutionContext."""
+    return ExecutionContext(
+        user_id=user_id,
+        graph_exec_id=graph_exec_id,
+    )
+
+
 class TestHttpBlockWithHostScopedCredentials:
     """Test suite for HTTP block integration with HostScopedCredentials."""
 
@@ -105,8 +117,7 @@ class TestHttpBlockWithHostScopedCredentials:
         async for output_name, output_data in http_block.run(
             input_data,
             credentials=exact_match_credentials,
-            graph_exec_id="test-exec-id",
-            user_id="test-user-id",
+            execution_context=make_test_context(),
         ):
             result.append((output_name, output_data))
 
@@ -161,8 +172,7 @@ class TestHttpBlockWithHostScopedCredentials:
         async for output_name, output_data in http_block.run(
             input_data,
             credentials=wildcard_credentials,
-            graph_exec_id="test-exec-id",
-            user_id="test-user-id",
+            execution_context=make_test_context(),
         ):
             result.append((output_name, output_data))
 
@@ -208,8 +218,7 @@ class TestHttpBlockWithHostScopedCredentials:
         async for output_name, output_data in http_block.run(
             input_data,
             credentials=non_matching_credentials,
-            graph_exec_id="test-exec-id",
-            user_id="test-user-id",
+            execution_context=make_test_context(),
         ):
             result.append((output_name, output_data))
 
@@ -258,8 +267,7 @@ class TestHttpBlockWithHostScopedCredentials:
         async for output_name, output_data in http_block.run(
             input_data,
             credentials=exact_match_credentials,
-            graph_exec_id="test-exec-id",
-            user_id="test-user-id",
+            execution_context=make_test_context(),
         ):
             result.append((output_name, output_data))
 
@@ -318,8 +326,7 @@ class TestHttpBlockWithHostScopedCredentials:
         async for output_name, output_data in http_block.run(
             input_data,
             credentials=auto_discovered_creds,  # Execution manager found these
-            graph_exec_id="test-exec-id",
-            user_id="test-user-id",
+            execution_context=make_test_context(),
         ):
             result.append((output_name, output_data))
 
@@ -382,8 +389,7 @@ class TestHttpBlockWithHostScopedCredentials:
         async for output_name, output_data in http_block.run(
             input_data,
             credentials=multi_header_creds,
-            graph_exec_id="test-exec-id",
-            user_id="test-user-id",
+            execution_context=make_test_context(),
         ):
             result.append((output_name, output_data))
 
@@ -471,8 +477,7 @@ class TestHttpBlockWithHostScopedCredentials:
             async for output_name, output_data in http_block.run(
                 input_data,
                 credentials=test_creds,
-                graph_exec_id="test-exec-id",
-                user_id="test-user-id",
+                execution_context=make_test_context(),
             ):
                 result.append((output_name, output_data))
 

autogpt_platform/backend/backend/blocks/text.py

@@ -11,6 +11,7 @@ from backend.data.block import (
     BlockSchemaInput,
     BlockSchemaOutput,
 )
+from backend.data.execution import ExecutionContext
 from backend.data.model import SchemaField
 from backend.util import json, text
 from backend.util.file import get_exec_file_path, store_media_file
@@ -444,18 +445,19 @@ class FileReadBlock(Block):
         )
 
     async def run(
-        self, input_data: Input, *, graph_exec_id: str, user_id: str, **_kwargs
+        self, input_data: Input, *, execution_context: ExecutionContext, **_kwargs
     ) -> BlockOutput:
         # Store the media file properly (handles URLs, data URIs, etc.)
         stored_file_path = await store_media_file(
-            user_id=user_id,
-            graph_exec_id=graph_exec_id,
             file=input_data.file_input,
-            return_content=False,
+            execution_context=execution_context,
+            return_format="for_local_processing",
         )
 
         # Get full file path
-        file_path = get_exec_file_path(graph_exec_id, stored_file_path)
+        file_path = get_exec_file_path(
+            execution_context.graph_exec_id or "", stored_file_path
+        )
 
         if not Path(file_path).exists():
             raise ValueError(f"File does not exist: {file_path}")

autogpt_platform/backend/backend/data/execution.py

@@ -83,12 +83,29 @@ class ExecutionContext(BaseModel):
 
     model_config = {"extra": "ignore"}
 
+    # Execution identity
+    user_id: Optional[str] = None
+    graph_id: Optional[str] = None
+    graph_exec_id: Optional[str] = None
+    graph_version: Optional[int] = None
+    node_id: Optional[str] = None
+    node_exec_id: Optional[str] = None
+
+    # Safety settings
     human_in_the_loop_safe_mode: bool = True
     sensitive_action_safe_mode: bool = False
+
+    # User settings
     user_timezone: str = "UTC"
+
+    # Execution hierarchy
     root_execution_id: Optional[str] = None
     parent_execution_id: Optional[str] = None
 
+    # Workspace
+    workspace_id: Optional[str] = None
+    session_id: Optional[str] = None
+
 
 # -------------------------- Models -------------------------- #
 

autogpt_platform/backend/backend/data/workspace.py

@@ -0,0 +1,365 @@
+"""
+Database CRUD operations for User Workspace.
+
+This module provides functions for managing user workspaces and workspace files.
+"""
+
+import logging
+from datetime import datetime, timezone
+from typing import Optional
+
+from prisma.enums import WorkspaceFileSource
+from prisma.models import UserWorkspace, UserWorkspaceFile
+
+from backend.util.json import SafeJson
+
+logger = logging.getLogger(__name__)
+
+
+async def get_or_create_workspace(user_id: str) -> UserWorkspace:
+    """
+    Get user's workspace, creating one if it doesn't exist.
+
+    Args:
+        user_id: The user's ID
+
+    Returns:
+        UserWorkspace instance
+    """
+    workspace = await UserWorkspace.prisma().find_unique(where={"userId": user_id})
+
+    if workspace is None:
+        workspace = await UserWorkspace.prisma().create(
+            data={
+                "userId": user_id,
+            }
+        )
+        logger.info(f"Created new workspace {workspace.id} for user {user_id}")
+
+    return workspace
+
+
+async def get_workspace(user_id: str) -> Optional[UserWorkspace]:
+    """
+    Get user's workspace if it exists.
+
+    Args:
+        user_id: The user's ID
+
+    Returns:
+        UserWorkspace instance or None
+    """
+    return await UserWorkspace.prisma().find_unique(where={"userId": user_id})
+
+
+async def get_workspace_by_id(workspace_id: str) -> Optional[UserWorkspace]:
+    """
+    Get workspace by its ID.
+
+    Args:
+        workspace_id: The workspace ID
+
+    Returns:
+        UserWorkspace instance or None
+    """
+    return await UserWorkspace.prisma().find_unique(where={"id": workspace_id})
+
+
+async def create_workspace_file(
+    workspace_id: str,
+    name: str,
+    path: str,
+    storage_path: str,
+    mime_type: str,
+    size_bytes: int,
+    checksum: Optional[str] = None,
+    source: WorkspaceFileSource = WorkspaceFileSource.UPLOAD,
+    source_exec_id: Optional[str] = None,
+    source_session_id: Optional[str] = None,
+    metadata: Optional[dict] = None,
+) -> UserWorkspaceFile:
+    """
+    Create a new workspace file record.
+
+    Args:
+        workspace_id: The workspace ID
+        name: User-visible filename
+        path: Virtual path (e.g., "/documents/report.pdf")
+        storage_path: Actual storage path (GCS or local)
+        mime_type: MIME type of the file
+        size_bytes: File size in bytes
+        checksum: Optional SHA256 checksum
+        source: How the file was created
+        source_exec_id: Graph execution ID if from execution
+        source_session_id: Chat session ID if from CoPilot
+        metadata: Optional additional metadata
+
+    Returns:
+        Created UserWorkspaceFile instance
+    """
+    # Normalize path to start with /
+    if not path.startswith("/"):
+        path = f"/{path}"
+
+    file = await UserWorkspaceFile.prisma().create(
+        data={
+            "workspaceId": workspace_id,
+            "name": name,
+            "path": path,
+            "storagePath": storage_path,
+            "mimeType": mime_type,
+            "sizeBytes": size_bytes,
+            "checksum": checksum,
+            "source": source,
+            "sourceExecId": source_exec_id,
+            "sourceSessionId": source_session_id,
+            "metadata": SafeJson(metadata or {}),
+        }
+    )
+
+    logger.info(
+        f"Created workspace file {file.id} at path {path} "
+        f"in workspace {workspace_id}"
+    )
+    return file
+
+
+async def get_workspace_file(
+    file_id: str,
+    workspace_id: Optional[str] = None,
+) -> Optional[UserWorkspaceFile]:
+    """
+    Get a workspace file by ID.
+
+    Args:
+        file_id: The file ID
+        workspace_id: Optional workspace ID for validation
+
+    Returns:
+        UserWorkspaceFile instance or None
+    """
+    where_clause: dict = {"id": file_id, "isDeleted": False}
+    if workspace_id:
+        where_clause["workspaceId"] = workspace_id
+
+    return await UserWorkspaceFile.prisma().find_first(where=where_clause)
+
+
+async def get_workspace_file_by_path(
+    workspace_id: str,
+    path: str,
+) -> Optional[UserWorkspaceFile]:
+    """
+    Get a workspace file by its virtual path.
+
+    Args:
+        workspace_id: The workspace ID
+        path: Virtual path
+
+    Returns:
+        UserWorkspaceFile instance or None
+    """
+    # Normalize path
+    if not path.startswith("/"):
+        path = f"/{path}"
+
+    return await UserWorkspaceFile.prisma().find_first(
+        where={
+            "workspaceId": workspace_id,
+            "path": path,
+            "isDeleted": False,
+        }
+    )
+
+
+async def list_workspace_files(
+    workspace_id: str,
+    path_prefix: Optional[str] = None,
+    include_deleted: bool = False,
+    limit: Optional[int] = None,
+    offset: int = 0,
+) -> list[UserWorkspaceFile]:
+    """
+    List files in a workspace.
+
+    Args:
+        workspace_id: The workspace ID
+        path_prefix: Optional path prefix to filter (e.g., "/documents/")
+        include_deleted: Whether to include soft-deleted files
+        limit: Maximum number of files to return
+        offset: Number of files to skip
+
+    Returns:
+        List of UserWorkspaceFile instances
+    """
+    where_clause: dict = {"workspaceId": workspace_id}
+
+    if not include_deleted:
+        where_clause["isDeleted"] = False
+
+    if path_prefix:
+        # Normalize prefix
+        if not path_prefix.startswith("/"):
+            path_prefix = f"/{path_prefix}"
+        where_clause["path"] = {"startswith": path_prefix}
+
+    return await UserWorkspaceFile.prisma().find_many(
+        where=where_clause,
+        order={"createdAt": "desc"},
+        take=limit,
+        skip=offset,
+    )
+
+
+async def count_workspace_files(
+    workspace_id: str,
+    include_deleted: bool = False,
+) -> int:
+    """
+    Count files in a workspace.
+
+    Args:
+        workspace_id: The workspace ID
+        include_deleted: Whether to include soft-deleted files
+
+    Returns:
+        Number of files
+    """
+    where_clause: dict = {"workspaceId": workspace_id}
+    if not include_deleted:
+        where_clause["isDeleted"] = False
+
+    return await UserWorkspaceFile.prisma().count(where=where_clause)
+
+
+async def soft_delete_workspace_file(
+    file_id: str,
+    workspace_id: Optional[str] = None,
+) -> Optional[UserWorkspaceFile]:
+    """
+    Soft-delete a workspace file.
+
+    Args:
+        file_id: The file ID
+        workspace_id: Optional workspace ID for validation
+
+    Returns:
+        Updated UserWorkspaceFile instance or None if not found
+    """
+    # First verify the file exists and belongs to workspace
+    file = await get_workspace_file(file_id, workspace_id)
+    if file is None:
+        return None
+
+    updated = await UserWorkspaceFile.prisma().update(
+        where={"id": file_id},
+        data={
+            "isDeleted": True,
+            "deletedAt": datetime.now(timezone.utc),
+        },
+    )
+
+    logger.info(f"Soft-deleted workspace file {file_id}")
+    return updated
+
+
+async def hard_delete_workspace_file(file_id: str) -> bool:
+    """
+    Permanently delete a workspace file record.
+
+    Note: This only deletes the database record. The actual file should be
+    deleted from storage separately using the storage backend.
+
+    Args:
+        file_id: The file ID
+
+    Returns:
+        True if deleted, False if not found
+    """
+    try:
+        await UserWorkspaceFile.prisma().delete(where={"id": file_id})
+        logger.info(f"Hard-deleted workspace file {file_id}")
+        return True
+    except Exception:
+        return False
+
+
+async def update_workspace_file(
+    file_id: str,
+    name: Optional[str] = None,
+    path: Optional[str] = None,
+    metadata: Optional[dict] = None,
+) -> Optional[UserWorkspaceFile]:
+    """
+    Update workspace file metadata.
+
+    Args:
+        file_id: The file ID
+        name: New filename
+        path: New virtual path
+        metadata: New metadata (merged with existing)
+
+    Returns:
+        Updated UserWorkspaceFile instance or None if not found
+    """
+    update_data: dict = {}
+
+    if name is not None:
+        update_data["name"] = name
+
+    if path is not None:
+        if not path.startswith("/"):
+            path = f"/{path}"
+        update_data["path"] = path
+
+    if metadata is not None:
+        # Get existing metadata and merge
+        file = await get_workspace_file(file_id)
+        if file is None:
+            return None
+        existing_metadata = file.metadata if file.metadata else {}
+        merged_metadata = {**existing_metadata, **metadata}
+        update_data["metadata"] = SafeJson(merged_metadata)
+
+    if not update_data:
+        return await get_workspace_file(file_id)
+
+    try:
+        return await UserWorkspaceFile.prisma().update(
+            where={"id": file_id},
+            data=update_data,
+        )
+    except Exception:
+        return None
+
+
+async def workspace_file_exists(
+    workspace_id: str,
+    path: str,
+) -> bool:
+    """
+    Check if a file exists at the given path in the workspace.
+
+    Args:
+        workspace_id: The workspace ID
+        path: Virtual path to check
+
+    Returns:
+        True if file exists, False otherwise
+    """
+    file = await get_workspace_file_by_path(workspace_id, path)
+    return file is not None
+
+
+async def get_workspace_total_size(workspace_id: str) -> int:
+    """
+    Get the total size of all files in a workspace.
+
+    Args:
+        workspace_id: The workspace ID
+
+    Returns:
+        Total size in bytes
+    """
+    files = await list_workspace_files(workspace_id)
+    return sum(file.sizeBytes for file in files)

autogpt_platform/backend/backend/executor/manager.py

@@ -236,7 +236,12 @@ async def execute_node(
     input_size = len(input_data_str)
     log_metadata.debug("Executed node with input", input=input_data_str)
 
+    # Update execution_context with node-level info
+    execution_context.node_id = node_id
+    execution_context.node_exec_id = node_exec_id
+
     # Inject extra execution arguments for the blocks via kwargs
+    # Keep individual kwargs for backwards compatibility with existing blocks
     extra_exec_kwargs: dict = {
         "graph_id": graph_id,
         "graph_version": graph_version,

autogpt_platform/backend/backend/executor/utils.py

@@ -892,11 +892,19 @@ async def add_graph_execution(
         settings = await gdb.get_graph_settings(user_id=user_id, graph_id=graph_id)
 
         execution_context = ExecutionContext(
+            # Execution identity
+            user_id=user_id,
+            graph_id=graph_id,
+            graph_exec_id=graph_exec.id,
+            graph_version=graph_version,
+            # Safety settings
             human_in_the_loop_safe_mode=settings.human_in_the_loop_safe_mode,
             sensitive_action_safe_mode=settings.sensitive_action_safe_mode,
+            # User settings
             user_timezone=(
                 user.timezone if user.timezone != USER_TIMEZONE_NOT_SET else "UTC"
             ),
+            # Execution hierarchy
             root_execution_id=graph_exec.id,
         )
 

autogpt_platform/backend/backend/util/file.py

@@ -4,13 +4,29 @@ import re
 import shutil
 import tempfile
 import uuid
+import warnings
 from pathlib import Path
+from typing import TYPE_CHECKING, Literal
 from urllib.parse import urlparse
 
+from prisma.enums import WorkspaceFileSource
+
 from backend.util.cloud_storage import get_cloud_storage_handler
 from backend.util.request import Requests
 from backend.util.type import MediaFileType
 from backend.util.virus_scanner import scan_content_safe
+from backend.util.workspace import WorkspaceManager
+
+if TYPE_CHECKING:
+    from backend.data.execution import ExecutionContext
+
+# Return format options for store_media_file
+# - "for_local_processing": Returns local file path - use with ffmpeg, MoviePy, PIL, etc.
+# - "for_external_api": Returns data URI (base64) - use when sending content to external APIs
+# - "for_block_output": Returns best format for output - workspace:// in CoPilot, data URI in graphs
+MediaReturnFormat = Literal[
+    "for_local_processing", "for_external_api", "for_block_output"
+]
 
 TEMP_DIR = Path(tempfile.gettempdir()).resolve()
 
@@ -67,36 +83,73 @@ def clean_exec_files(graph_exec_id: str, file: str = "") -> None:
 
 
 async def store_media_file(
-    graph_exec_id: str,
     file: MediaFileType,
-    user_id: str,
-    return_content: bool = False,
+    execution_context: "ExecutionContext",
+    *,
+    return_format: MediaReturnFormat | None = None,
+    # Deprecated parameters - use return_format instead
+    return_content: bool | None = None,
+    save_to_workspace: bool | None = None,
 ) -> MediaFileType:
     """
-    Safely handle 'file' (a data URI, a URL, or a local path relative to {temp}/exec_file/{exec_id}),
-    placing or verifying it under:
+    Safely handle 'file' (a data URI, a URL, a workspace:// reference, or a local path
+    relative to {temp}/exec_file/{exec_id}), placing or verifying it under:
         {tempdir}/exec_file/{exec_id}/...
 
-    If 'return_content=True', return a data URI (data:<mime>;base64,<content>).
-    Otherwise, returns the file media path relative to the exec_id folder.
+    For each MediaFileType input:
+    - Data URI: decode and store locally
+    - URL: download and store locally
+    - workspace:// reference: read from workspace, store locally
+    - Local path: verify it exists in exec_file directory
 
-    For each MediaFileType type:
-    - Data URI:
-      -> decode and store in a new random file in that folder
-    - URL:
-      -> download and store in that folder
-    - Local path:
-      -> interpret as relative to that folder; verify it exists
-         (no copying, as it's presumably already there).
-         We realpath-check so no symlink or '..' can escape the folder.
+    Return format options:
+    - "for_local_processing": Returns local file path - use with ffmpeg, MoviePy, PIL, etc.
+    - "for_external_api": Returns data URI (base64) - use when sending to external APIs
+    - "for_block_output": Returns best format for output - workspace:// in CoPilot, data URI in graphs
 
-
-    :param graph_exec_id:  The unique ID of the graph execution.
-    :param file:           Data URI, URL, or local (relative) path.
-    :param return_content: If True, return a data URI of the file content.
-                           If False, return the *relative* path inside the exec_id folder.
-    :return:               The requested result: data URI or relative path of the media.
+    :param file:               Data URI, URL, workspace://, or local (relative) path.
+    :param execution_context:  ExecutionContext with user_id, graph_exec_id, workspace_id.
+    :param return_format:      What to return: "for_local_processing", "for_external_api", or "for_block_output".
+    :param return_content:     DEPRECATED. Use return_format instead.
+    :param save_to_workspace:  DEPRECATED. Use return_format instead.
+    :return:                   The requested result based on return_format.
     """
+    # Handle deprecated parameters
+    if return_format is None:
+        if return_content is not None or save_to_workspace is not None:
+            warnings.warn(
+                "return_content and save_to_workspace are deprecated. "
+                "Use return_format='for_local_processing', 'for_external_api', or 'for_block_output' instead.",
+                DeprecationWarning,
+                stacklevel=2,
+            )
+        # Map old parameters to new return_format
+        if return_content is False or (
+            return_content is None and save_to_workspace is None
+        ):
+            # Default or explicit return_content=False -> for_local_processing
+            return_format = "for_local_processing"
+        elif save_to_workspace is False:
+            # return_content=True, save_to_workspace=False -> for_external_api
+            return_format = "for_external_api"
+        else:
+            # return_content=True, save_to_workspace=True (or default) -> for_block_output
+            return_format = "for_block_output"
+    # Extract values from execution_context
+    graph_exec_id = execution_context.graph_exec_id
+    user_id = execution_context.user_id
+
+    if not graph_exec_id:
+        raise ValueError("execution_context.graph_exec_id is required")
+    if not user_id:
+        raise ValueError("execution_context.user_id is required")
+
+    # Create workspace_manager if we have workspace_id (with session scoping)
+    workspace_manager: WorkspaceManager | None = None
+    if execution_context.workspace_id:
+        workspace_manager = WorkspaceManager(
+            user_id, execution_context.workspace_id, execution_context.session_id
+        )
     # Build base path
     base_path = Path(get_exec_file_path(graph_exec_id, ""))
     base_path.mkdir(parents=True, exist_ok=True)
@@ -142,9 +195,57 @@ async def store_media_file(
         """
         return str(absolute_path.relative_to(base))
 
-    # Check if this is a cloud storage path
+    # Get cloud storage handler for checking cloud paths
     cloud_storage = await get_cloud_storage_handler()
-    if cloud_storage.is_cloud_path(file):
+
+    # Track if the input came from workspace (don't re-save it)
+    is_from_workspace = file.startswith("workspace://")
+
+    # Check if this is a workspace file reference
+    if is_from_workspace:
+        if workspace_manager is None:
+            raise ValueError(
+                "Workspace file reference requires workspace context. "
+                "This file type is only available in CoPilot sessions."
+            )
+
+        # Parse workspace reference
+        # workspace://abc123 - by file ID
+        # workspace:///path/to/file.txt - by virtual path
+        file_ref = file[12:]  # Remove "workspace://"
+
+        if file_ref.startswith("/"):
+            # Path reference
+            workspace_content = await workspace_manager.read_file(file_ref)
+            file_info = await workspace_manager.get_file_info_by_path(file_ref)
+            filename = sanitize_filename(
+                file_info.name if file_info else f"{uuid.uuid4()}.bin"
+            )
+        else:
+            # ID reference
+            workspace_content = await workspace_manager.read_file_by_id(file_ref)
+            file_info = await workspace_manager.get_file_info(file_ref)
+            filename = sanitize_filename(
+                file_info.name if file_info else f"{uuid.uuid4()}.bin"
+            )
+
+        try:
+            target_path = _ensure_inside_base(base_path / filename, base_path)
+        except OSError as e:
+            raise ValueError(f"Invalid file path '{filename}': {e}") from e
+
+        # Check file size limit
+        if len(workspace_content) > MAX_FILE_SIZE:
+            raise ValueError(
+                f"File too large: {len(workspace_content)} bytes > {MAX_FILE_SIZE} bytes"
+            )
+
+        # Virus scan the workspace content before writing locally
+        await scan_content_safe(workspace_content, filename=filename)
+        target_path.write_bytes(workspace_content)
+
+    # Check if this is a cloud storage path
+    elif cloud_storage.is_cloud_path(file):
         # Download from cloud storage and store locally
         cloud_content = await cloud_storage.retrieve_file(
             file, user_id=user_id, graph_exec_id=graph_exec_id
@@ -230,12 +331,45 @@ async def store_media_file(
         if not target_path.is_file():
             raise ValueError(f"Local file does not exist: {target_path}")
 
-    # Return result
-    if return_content:
-        return MediaFileType(_file_to_data_uri(target_path))
-    else:
+    # Return based on requested format
+    if return_format == "for_local_processing":
+        # Use when processing files locally with tools like ffmpeg, MoviePy, PIL
+        # Returns: relative path in exec_file directory (e.g., "image.png")
         return MediaFileType(_strip_base_prefix(target_path, base_path))
 
+    elif return_format == "for_external_api":
+        # Use when sending content to external APIs that need base64
+        # Returns: data URI (e.g., "data:image/png;base64,iVBORw0...")
+        return MediaFileType(_file_to_data_uri(target_path))
+
+    elif return_format == "for_block_output":
+        # Use when returning output from a block to user/next block
+        # Returns: workspace:// ref (CoPilot) or data URI (graph execution)
+        if workspace_manager is None:
+            # No workspace available (graph execution without CoPilot)
+            # Fallback to data URI so the content can still be used/displayed
+            return MediaFileType(_file_to_data_uri(target_path))
+
+        # Don't re-save if input was already from workspace
+        if is_from_workspace:
+            # Return original workspace reference
+            return MediaFileType(file)
+
+        # Save new content to workspace
+        content = target_path.read_bytes()
+        filename = target_path.name
+
+        file_record = await workspace_manager.write_file(
+            content=content,
+            filename=filename,
+            source=WorkspaceFileSource.COPILOT,
+            overwrite=True,
+        )
+        return MediaFileType(f"workspace://{file_record.id}")
+
+    else:
+        raise ValueError(f"Invalid return_format: {return_format}")
+
 
 def get_dir_size(path: Path) -> int:
     """Get total size of directory."""

autogpt_platform/backend/backend/util/file_test.py

@@ -7,10 +7,22 @@ from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 
+from backend.data.execution import ExecutionContext
 from backend.util.file import store_media_file
 from backend.util.type import MediaFileType
 
 
+def make_test_context(
+    graph_exec_id: str = "test-exec-123",
+    user_id: str = "test-user-123",
+) -> ExecutionContext:
+    """Helper to create test ExecutionContext."""
+    return ExecutionContext(
+        user_id=user_id,
+        graph_exec_id=graph_exec_id,
+    )
+
+
 class TestFileCloudIntegration:
     """Test cases for cloud storage integration in file utilities."""
 
@@ -70,10 +82,9 @@ class TestFileCloudIntegration:
             mock_path_class.side_effect = path_constructor
 
             result = await store_media_file(
-                graph_exec_id,
-                MediaFileType(cloud_path),
-                "test-user-123",
-                return_content=False,
+                file=MediaFileType(cloud_path),
+                execution_context=make_test_context(graph_exec_id=graph_exec_id),
+                return_format="for_local_processing",
             )
 
             # Verify cloud storage operations
@@ -144,10 +155,9 @@ class TestFileCloudIntegration:
             mock_path_obj.name = "image.png"
             with patch("backend.util.file.Path", return_value=mock_path_obj):
                 result = await store_media_file(
-                    graph_exec_id,
-                    MediaFileType(cloud_path),
-                    "test-user-123",
-                    return_content=True,
+                    file=MediaFileType(cloud_path),
+                    execution_context=make_test_context(graph_exec_id=graph_exec_id),
+                    return_format="for_external_api",
                 )
 
             # Verify result is a data URI
@@ -198,10 +208,9 @@ class TestFileCloudIntegration:
             mock_resolved_path.relative_to.return_value = Path("test-uuid-789.txt")
 
             await store_media_file(
-                graph_exec_id,
-                MediaFileType(data_uri),
-                "test-user-123",
-                return_content=False,
+                file=MediaFileType(data_uri),
+                execution_context=make_test_context(graph_exec_id=graph_exec_id),
+                return_format="for_local_processing",
             )
 
             # Verify cloud handler was checked but not used for retrieval
@@ -234,5 +243,6 @@ class TestFileCloudIntegration:
                 FileNotFoundError, match="File not found in cloud storage"
             ):
                 await store_media_file(
-                    graph_exec_id, MediaFileType(cloud_path), "test-user-123"
+                    file=MediaFileType(cloud_path),
+                    execution_context=make_test_context(graph_exec_id=graph_exec_id),
                 )

autogpt_platform/backend/backend/util/settings.py

@@ -263,6 +263,12 @@ class Config(UpdateTrackingModel["Config"], BaseSettings):
         description="The name of the Google Cloud Storage bucket for media files",
     )
 
+    workspace_storage_dir: str = Field(
+        default="",
+        description="Local directory for workspace file storage when GCS is not configured. "
+        "If empty, defaults to {app_data}/workspaces. Used for self-hosted deployments.",
+    )
+
     reddit_user_agent: str = Field(
         default="web:AutoGPT:v0.6.0 (by /u/autogpt)",
         description="The user agent for the Reddit API",
@@ -359,8 +365,8 @@ class Config(UpdateTrackingModel["Config"], BaseSettings):
         description="The port for the Agent Generator service",
     )
     agentgenerator_timeout: int = Field(
-        default=120,
-        description="The timeout in seconds for Agent Generator service requests",
+        default=600,
+        description="The timeout in seconds for Agent Generator service requests (includes retries for rate limits)",
     )
 
     enable_example_blocks: bool = Field(

autogpt_platform/backend/backend/util/test.py

@@ -140,14 +140,29 @@ async def execute_block_test(block: Block):
             setattr(block, mock_name, mock_obj)
 
     # Populate credentials argument(s)
+    # Generate IDs for execution context
+    graph_id = str(uuid.uuid4())
+    node_id = str(uuid.uuid4())
+    graph_exec_id = str(uuid.uuid4())
+    node_exec_id = str(uuid.uuid4())
+    user_id = str(uuid.uuid4())
+    graph_version = 1  # Default version for tests
+
     extra_exec_kwargs: dict = {
-        "graph_id": str(uuid.uuid4()),
-        "node_id": str(uuid.uuid4()),
-        "graph_exec_id": str(uuid.uuid4()),
-        "node_exec_id": str(uuid.uuid4()),
-        "user_id": str(uuid.uuid4()),
-        "graph_version": 1,  # Default version for tests
-        "execution_context": ExecutionContext(),
+        "graph_id": graph_id,
+        "node_id": node_id,
+        "graph_exec_id": graph_exec_id,
+        "node_exec_id": node_exec_id,
+        "user_id": user_id,
+        "graph_version": graph_version,
+        "execution_context": ExecutionContext(
+            user_id=user_id,
+            graph_id=graph_id,
+            graph_exec_id=graph_exec_id,
+            graph_version=graph_version,
+            node_id=node_id,
+            node_exec_id=node_exec_id,
+        ),
     }
     input_model = cast(type[BlockSchema], block.input_schema)
 

autogpt_platform/backend/backend/util/workspace.py

@@ -0,0 +1,370 @@
+"""
+WorkspaceManager for managing user workspace file operations.
+
+This module provides a high-level interface for workspace file operations,
+combining the storage backend and database layer.
+"""
+
+import logging
+import mimetypes
+import uuid
+from typing import Optional
+
+from prisma.enums import WorkspaceFileSource
+from prisma.models import UserWorkspaceFile
+
+from backend.data.workspace import (
+    count_workspace_files,
+    create_workspace_file,
+    get_workspace_file,
+    get_workspace_file_by_path,
+    list_workspace_files,
+    soft_delete_workspace_file,
+    workspace_file_exists,
+)
+from backend.util.workspace_storage import compute_file_checksum, get_workspace_storage
+
+logger = logging.getLogger(__name__)
+
+# Maximum file size: 100MB per file
+MAX_FILE_SIZE_BYTES = 100 * 1024 * 1024
+
+
+class WorkspaceManager:
+    """
+    Manages workspace file operations.
+
+    Combines storage backend operations with database record management.
+    Supports session-scoped file segmentation where files are stored in
+    session-specific virtual paths: /sessions/{session_id}/{filename}
+    """
+
+    def __init__(
+        self, user_id: str, workspace_id: str, session_id: Optional[str] = None
+    ):
+        """
+        Initialize WorkspaceManager.
+
+        Args:
+            user_id: The user's ID
+            workspace_id: The workspace ID
+            session_id: Optional session ID for session-scoped file access
+        """
+        self.user_id = user_id
+        self.workspace_id = workspace_id
+        self.session_id = session_id
+        # Session path prefix for file isolation
+        self.session_path = f"/sessions/{session_id}" if session_id else ""
+
+    def _resolve_path(self, path: str) -> str:
+        """
+        Resolve a path, defaulting to session folder if session_id is set.
+
+        Cross-session access is allowed by explicitly using /sessions/other-session-id/...
+
+        Args:
+            path: Virtual path (e.g., "/file.txt" or "/sessions/abc123/file.txt")
+
+        Returns:
+            Resolved path with session prefix if applicable
+        """
+        # If path explicitly references a session folder, use it as-is
+        if path.startswith("/sessions/"):
+            return path
+
+        # If we have a session context, prepend session path
+        if self.session_path:
+            # Normalize the path
+            if not path.startswith("/"):
+                path = f"/{path}"
+            return f"{self.session_path}{path}"
+
+        # No session context, use path as-is
+        return path if path.startswith("/") else f"/{path}"
+
+    async def read_file(self, path: str) -> bytes:
+        """
+        Read file from workspace by virtual path.
+
+        When session_id is set, paths are resolved relative to the session folder
+        unless they explicitly reference /sessions/...
+
+        Args:
+            path: Virtual path (e.g., "/documents/report.pdf")
+
+        Returns:
+            File content as bytes
+
+        Raises:
+            FileNotFoundError: If file doesn't exist
+        """
+        resolved_path = self._resolve_path(path)
+        file = await get_workspace_file_by_path(self.workspace_id, resolved_path)
+        if file is None:
+            raise FileNotFoundError(f"File not found at path: {resolved_path}")
+
+        storage = await get_workspace_storage()
+        return await storage.retrieve(file.storagePath)
+
+    async def read_file_by_id(self, file_id: str) -> bytes:
+        """
+        Read file from workspace by file ID.
+
+        Args:
+            file_id: The file's ID
+
+        Returns:
+            File content as bytes
+
+        Raises:
+            FileNotFoundError: If file doesn't exist
+        """
+        file = await get_workspace_file(file_id, self.workspace_id)
+        if file is None:
+            raise FileNotFoundError(f"File not found: {file_id}")
+
+        storage = await get_workspace_storage()
+        return await storage.retrieve(file.storagePath)
+
+    async def write_file(
+        self,
+        content: bytes,
+        filename: str,
+        path: Optional[str] = None,
+        mime_type: Optional[str] = None,
+        source: WorkspaceFileSource = WorkspaceFileSource.UPLOAD,
+        source_exec_id: Optional[str] = None,
+        source_session_id: Optional[str] = None,
+        overwrite: bool = False,
+    ) -> UserWorkspaceFile:
+        """
+        Write file to workspace.
+
+        When session_id is set, files are written to /sessions/{session_id}/...
+        by default. Use explicit /sessions/... paths for cross-session access.
+
+        Args:
+            content: File content as bytes
+            filename: Filename for the file
+            path: Virtual path (defaults to "/{filename}", session-scoped if session_id set)
+            mime_type: MIME type (auto-detected if not provided)
+            source: How the file was created
+            source_exec_id: Graph execution ID if from execution
+            source_session_id: Chat session ID if from CoPilot
+            overwrite: Whether to overwrite existing file at path
+
+        Returns:
+            Created UserWorkspaceFile instance
+
+        Raises:
+            ValueError: If file exceeds size limit or path already exists
+        """
+        # Enforce file size limit
+        if len(content) > MAX_FILE_SIZE_BYTES:
+            raise ValueError(
+                f"File too large: {len(content)} bytes exceeds "
+                f"{MAX_FILE_SIZE_BYTES // (1024*1024)}MB limit"
+            )
+
+        # Determine path with session scoping
+        if path is None:
+            path = f"/{filename}"
+        elif not path.startswith("/"):
+            path = f"/{path}"
+
+        # Resolve path with session prefix
+        path = self._resolve_path(path)
+
+        # Check if file exists at path
+        existing = await get_workspace_file_by_path(self.workspace_id, path)
+        if existing is not None:
+            if overwrite:
+                # Delete existing file first
+                await self.delete_file(existing.id)
+            else:
+                raise ValueError(f"File already exists at path: {path}")
+
+        # Auto-detect MIME type if not provided
+        if mime_type is None:
+            mime_type, _ = mimetypes.guess_type(filename)
+            mime_type = mime_type or "application/octet-stream"
+
+        # Compute checksum
+        checksum = compute_file_checksum(content)
+
+        # Generate unique file ID for storage
+        file_id = str(uuid.uuid4())
+
+        # Store file in storage backend
+        storage = await get_workspace_storage()
+        storage_path = await storage.store(
+            workspace_id=self.workspace_id,
+            file_id=file_id,
+            filename=filename,
+            content=content,
+        )
+
+        # Create database record
+        file = await create_workspace_file(
+            workspace_id=self.workspace_id,
+            name=filename,
+            path=path,
+            storage_path=storage_path,
+            mime_type=mime_type,
+            size_bytes=len(content),
+            checksum=checksum,
+            source=source,
+            source_exec_id=source_exec_id,
+            source_session_id=source_session_id,
+        )
+
+        logger.info(
+            f"Wrote file {file.id} ({filename}) to workspace {self.workspace_id} "
+            f"at path {path}, size={len(content)} bytes"
+        )
+
+        return file
+
+    async def list_files(
+        self,
+        path: Optional[str] = None,
+        limit: Optional[int] = None,
+        offset: int = 0,
+        include_all_sessions: bool = False,
+    ) -> list[UserWorkspaceFile]:
+        """
+        List files in workspace.
+
+        When session_id is set and include_all_sessions is False (default),
+        only files in the current session's folder are listed.
+
+        Args:
+            path: Optional path prefix to filter (e.g., "/documents/")
+            limit: Maximum number of files to return
+            offset: Number of files to skip
+            include_all_sessions: If True, list files from all sessions.
+                                  If False (default), only list current session's files.
+
+        Returns:
+            List of UserWorkspaceFile instances
+        """
+        # Determine the effective path prefix
+        if include_all_sessions:
+            # Use provided path as-is (or None for all files)
+            effective_path = path
+        elif path is not None:
+            # Resolve the provided path with session scoping
+            effective_path = self._resolve_path(path)
+        elif self.session_path:
+            # Default to session folder
+            effective_path = self.session_path
+        else:
+            # No session context, list all
+            effective_path = path
+
+        return await list_workspace_files(
+            workspace_id=self.workspace_id,
+            path_prefix=effective_path,
+            limit=limit,
+            offset=offset,
+        )
+
+    async def delete_file(self, file_id: str) -> bool:
+        """
+        Delete a file (soft-delete).
+
+        Args:
+            file_id: The file's ID
+
+        Returns:
+            True if deleted, False if not found
+        """
+        file = await get_workspace_file(file_id, self.workspace_id)
+        if file is None:
+            return False
+
+        # Delete from storage
+        storage = await get_workspace_storage()
+        try:
+            await storage.delete(file.storagePath)
+        except Exception as e:
+            logger.warning(f"Failed to delete file from storage: {e}")
+            # Continue with database soft-delete even if storage delete fails
+
+        # Soft-delete database record
+        result = await soft_delete_workspace_file(file_id, self.workspace_id)
+        return result is not None
+
+    async def get_download_url(self, file_id: str, expires_in: int = 3600) -> str:
+        """
+        Get download URL for a file.
+
+        Args:
+            file_id: The file's ID
+            expires_in: URL expiration in seconds (default 1 hour)
+
+        Returns:
+            Download URL (signed URL for GCS, API endpoint for local)
+
+        Raises:
+            FileNotFoundError: If file doesn't exist
+        """
+        file = await get_workspace_file(file_id, self.workspace_id)
+        if file is None:
+            raise FileNotFoundError(f"File not found: {file_id}")
+
+        storage = await get_workspace_storage()
+        return await storage.get_download_url(file.storagePath, expires_in)
+
+    async def get_file_info(self, file_id: str) -> Optional[UserWorkspaceFile]:
+        """
+        Get file metadata.
+
+        Args:
+            file_id: The file's ID
+
+        Returns:
+            UserWorkspaceFile instance or None
+        """
+        return await get_workspace_file(file_id, self.workspace_id)
+
+    async def get_file_info_by_path(self, path: str) -> Optional[UserWorkspaceFile]:
+        """
+        Get file metadata by path.
+
+        When session_id is set, paths are resolved relative to the session folder
+        unless they explicitly reference /sessions/...
+
+        Args:
+            path: Virtual path
+
+        Returns:
+            UserWorkspaceFile instance or None
+        """
+        resolved_path = self._resolve_path(path)
+        return await get_workspace_file_by_path(self.workspace_id, resolved_path)
+
+    async def file_exists(self, path: str) -> bool:
+        """
+        Check if a file exists at the given path.
+
+        When session_id is set, paths are resolved relative to the session folder
+        unless they explicitly reference /sessions/...
+
+        Args:
+            path: Virtual path
+
+        Returns:
+            True if file exists
+        """
+        resolved_path = self._resolve_path(path)
+        return await workspace_file_exists(self.workspace_id, resolved_path)
+
+    async def get_file_count(self) -> int:
+        """
+        Get number of files in workspace.
+
+        Returns:
+            Number of files
+        """
+        return await count_workspace_files(self.workspace_id)

autogpt_platform/backend/backend/util/workspace_storage.py

@@ -0,0 +1,449 @@
+"""
+Workspace storage backend abstraction for supporting both cloud and local deployments.
+
+This module provides a unified interface for storing workspace files, with implementations
+for Google Cloud Storage (cloud deployments) and local filesystem (self-hosted deployments).
+"""
+
+import asyncio
+import hashlib
+import logging
+from abc import ABC, abstractmethod
+from datetime import datetime, timedelta, timezone
+from pathlib import Path
+from typing import Optional
+
+import aiofiles
+import aiohttp
+from gcloud.aio import storage as async_gcs_storage
+from google.cloud import storage as gcs_storage
+
+from backend.util.data import get_data_path
+from backend.util.settings import Config
+
+logger = logging.getLogger(__name__)
+
+
+class WorkspaceStorageBackend(ABC):
+    """Abstract interface for workspace file storage."""
+
+    @abstractmethod
+    async def store(
+        self,
+        workspace_id: str,
+        file_id: str,
+        filename: str,
+        content: bytes,
+    ) -> str:
+        """
+        Store file content, return storage path.
+
+        Args:
+            workspace_id: The workspace ID
+            file_id: Unique file ID for storage
+            filename: Original filename
+            content: File content as bytes
+
+        Returns:
+            Storage path string (cloud path or local path)
+        """
+        pass
+
+    @abstractmethod
+    async def retrieve(self, storage_path: str) -> bytes:
+        """
+        Retrieve file content from storage.
+
+        Args:
+            storage_path: The storage path returned from store()
+
+        Returns:
+            File content as bytes
+        """
+        pass
+
+    @abstractmethod
+    async def delete(self, storage_path: str) -> None:
+        """
+        Delete file from storage.
+
+        Args:
+            storage_path: The storage path to delete
+        """
+        pass
+
+    @abstractmethod
+    async def get_download_url(self, storage_path: str, expires_in: int = 3600) -> str:
+        """
+        Get URL for downloading the file.
+
+        Args:
+            storage_path: The storage path
+            expires_in: URL expiration time in seconds (default 1 hour)
+
+        Returns:
+            Download URL (signed URL for GCS, direct API path for local)
+        """
+        pass
+
+    @abstractmethod
+    async def exists(self, storage_path: str) -> bool:
+        """
+        Check if a file exists at the storage path.
+
+        Args:
+            storage_path: The storage path to check
+
+        Returns:
+            True if file exists, False otherwise
+        """
+        pass
+
+
+class GCSWorkspaceStorage(WorkspaceStorageBackend):
+    """Google Cloud Storage implementation for workspace storage."""
+
+    def __init__(self, bucket_name: str):
+        self.bucket_name = bucket_name
+        self._async_client: Optional[async_gcs_storage.Storage] = None
+        self._sync_client: Optional[gcs_storage.Client] = None
+        self._session: Optional[aiohttp.ClientSession] = None
+
+    async def _get_async_client(self) -> async_gcs_storage.Storage:
+        """Get or create async GCS client."""
+        if self._async_client is None:
+            self._session = aiohttp.ClientSession(
+                connector=aiohttp.TCPConnector(limit=100, force_close=False)
+            )
+            self._async_client = async_gcs_storage.Storage(session=self._session)
+        return self._async_client
+
+    def _get_sync_client(self) -> gcs_storage.Client:
+        """Get or create sync GCS client (for signed URLs)."""
+        if self._sync_client is None:
+            self._sync_client = gcs_storage.Client()
+        return self._sync_client
+
+    async def close(self) -> None:
+        """Close all client connections."""
+        if self._async_client is not None:
+            try:
+                await self._async_client.close()
+            except Exception as e:
+                logger.warning(f"Error closing GCS client: {e}")
+            self._async_client = None
+
+        if self._session is not None:
+            try:
+                await self._session.close()
+            except Exception as e:
+                logger.warning(f"Error closing session: {e}")
+            self._session = None
+
+    def _build_blob_name(self, workspace_id: str, file_id: str, filename: str) -> str:
+        """Build the blob path for workspace files."""
+        return f"workspaces/{workspace_id}/{file_id}/{filename}"
+
+    async def store(
+        self,
+        workspace_id: str,
+        file_id: str,
+        filename: str,
+        content: bytes,
+    ) -> str:
+        """Store file in GCS."""
+        client = await self._get_async_client()
+        blob_name = self._build_blob_name(workspace_id, file_id, filename)
+
+        # Upload with metadata
+        upload_time = datetime.now(timezone.utc)
+        await client.upload(
+            self.bucket_name,
+            blob_name,
+            content,
+            metadata={
+                "uploaded_at": upload_time.isoformat(),
+                "workspace_id": workspace_id,
+                "file_id": file_id,
+            },
+        )
+
+        return f"gcs://{self.bucket_name}/{blob_name}"
+
+    async def retrieve(self, storage_path: str) -> bytes:
+        """Retrieve file from GCS."""
+        if not storage_path.startswith("gcs://"):
+            raise ValueError(f"Invalid GCS path: {storage_path}")
+
+        # Parse bucket and blob name
+        path = storage_path[6:]  # Remove "gcs://"
+        parts = path.split("/", 1)
+        if len(parts) != 2:
+            raise ValueError(f"Invalid GCS path format: {storage_path}")
+
+        bucket_name, blob_name = parts
+
+        # Create fresh session for download
+        session = aiohttp.ClientSession(
+            connector=aiohttp.TCPConnector(limit=10, force_close=True)
+        )
+        try:
+            client = async_gcs_storage.Storage(session=session)
+            content = await client.download(bucket_name, blob_name)
+            await client.close()
+            return content
+        except Exception as e:
+            if "404" in str(e) or "Not Found" in str(e):
+                raise FileNotFoundError(f"File not found: {storage_path}")
+            raise
+        finally:
+            await session.close()
+
+    async def delete(self, storage_path: str) -> None:
+        """Delete file from GCS."""
+        if not storage_path.startswith("gcs://"):
+            raise ValueError(f"Invalid GCS path: {storage_path}")
+
+        path = storage_path[6:]
+        parts = path.split("/", 1)
+        if len(parts) != 2:
+            raise ValueError(f"Invalid GCS path format: {storage_path}")
+
+        bucket_name, blob_name = parts
+        client = await self._get_async_client()
+
+        try:
+            await client.delete(bucket_name, blob_name)
+        except Exception as e:
+            if "404" not in str(e) and "Not Found" not in str(e):
+                raise
+            # File already deleted, that's fine
+
+    async def get_download_url(self, storage_path: str, expires_in: int = 3600) -> str:
+        """
+        Generate download URL for GCS file.
+
+        Attempts to generate a signed URL if running with service account credentials.
+        Falls back to an API proxy endpoint if signed URL generation fails
+        (e.g., when running locally with user OAuth credentials).
+        """
+        if not storage_path.startswith("gcs://"):
+            raise ValueError(f"Invalid GCS path: {storage_path}")
+
+        path = storage_path[6:]
+        parts = path.split("/", 1)
+        if len(parts) != 2:
+            raise ValueError(f"Invalid GCS path format: {storage_path}")
+
+        bucket_name, blob_name = parts
+
+        # Extract file_id from blob_name for fallback: workspaces/{workspace_id}/{file_id}/{filename}
+        blob_parts = blob_name.split("/")
+        file_id = blob_parts[2] if len(blob_parts) >= 3 else None
+
+        # Try to generate signed URL (requires service account credentials)
+        try:
+            sync_client = self._get_sync_client()
+            bucket = sync_client.bucket(bucket_name)
+            blob = bucket.blob(blob_name)
+
+            url = await asyncio.to_thread(
+                blob.generate_signed_url,
+                version="v4",
+                expiration=datetime.now(timezone.utc) + timedelta(seconds=expires_in),
+                method="GET",
+            )
+            return url
+        except AttributeError as e:
+            # Signed URL generation requires service account with private key.
+            # When running with user OAuth credentials, fall back to API proxy.
+            if "private key" in str(e) and file_id:
+                logger.debug(
+                    "Cannot generate signed URL (no service account credentials), "
+                    "falling back to API proxy endpoint"
+                )
+                return f"/api/workspace/files/{file_id}/download"
+            raise
+
+    async def exists(self, storage_path: str) -> bool:
+        """Check if file exists in GCS."""
+        if not storage_path.startswith("gcs://"):
+            return False
+
+        path = storage_path[6:]
+        parts = path.split("/", 1)
+        if len(parts) != 2:
+            return False
+
+        bucket_name, blob_name = parts
+
+        try:
+            client = await self._get_async_client()
+            await client.download_metadata(bucket_name, blob_name)
+            return True
+        except Exception:
+            return False
+
+
+class LocalWorkspaceStorage(WorkspaceStorageBackend):
+    """Local filesystem implementation for workspace storage (self-hosted deployments)."""
+
+    def __init__(self, base_dir: Optional[str] = None):
+        """
+        Initialize local storage backend.
+
+        Args:
+            base_dir: Base directory for workspace storage.
+                     If None, defaults to {app_data}/workspaces
+        """
+        if base_dir:
+            self.base_dir = Path(base_dir)
+        else:
+            self.base_dir = Path(get_data_path()) / "workspaces"
+
+        # Ensure base directory exists
+        self.base_dir.mkdir(parents=True, exist_ok=True)
+
+    def _build_file_path(self, workspace_id: str, file_id: str, filename: str) -> Path:
+        """Build the local file path."""
+        return self.base_dir / workspace_id / file_id / filename
+
+    def _parse_storage_path(self, storage_path: str) -> Path:
+        """Parse local storage path to filesystem path."""
+        if storage_path.startswith("local://"):
+            relative_path = storage_path[8:]  # Remove "local://"
+        else:
+            relative_path = storage_path
+
+        full_path = (self.base_dir / relative_path).resolve()
+
+        # Security check: ensure path is under base_dir
+        if not str(full_path).startswith(str(self.base_dir.resolve())):
+            raise ValueError("Invalid storage path: path traversal detected")
+
+        return full_path
+
+    async def store(
+        self,
+        workspace_id: str,
+        file_id: str,
+        filename: str,
+        content: bytes,
+    ) -> str:
+        """Store file locally."""
+        file_path = self._build_file_path(workspace_id, file_id, filename)
+
+        # Create parent directories
+        file_path.parent.mkdir(parents=True, exist_ok=True)
+
+        # Write file asynchronously
+        async with aiofiles.open(file_path, "wb") as f:
+            await f.write(content)
+
+        # Return relative path as storage path
+        relative_path = file_path.relative_to(self.base_dir)
+        return f"local://{relative_path}"
+
+    async def retrieve(self, storage_path: str) -> bytes:
+        """Retrieve file from local storage."""
+        file_path = self._parse_storage_path(storage_path)
+
+        if not file_path.exists():
+            raise FileNotFoundError(f"File not found: {storage_path}")
+
+        async with aiofiles.open(file_path, "rb") as f:
+            return await f.read()
+
+    async def delete(self, storage_path: str) -> None:
+        """Delete file from local storage."""
+        file_path = self._parse_storage_path(storage_path)
+
+        if file_path.exists():
+            # Remove file
+            file_path.unlink()
+
+            # Clean up empty parent directories
+            parent = file_path.parent
+            while parent != self.base_dir:
+                try:
+                    if parent.exists() and not any(parent.iterdir()):
+                        parent.rmdir()
+                    else:
+                        break
+                except OSError:
+                    break
+                parent = parent.parent
+
+    async def get_download_url(self, storage_path: str, expires_in: int = 3600) -> str:
+        """
+        Get download URL for local file.
+
+        For local storage, this returns an API endpoint path.
+        The actual serving is handled by the API layer.
+        """
+        # Parse the storage path to get the components
+        if storage_path.startswith("local://"):
+            relative_path = storage_path[8:]
+        else:
+            relative_path = storage_path
+
+        # Return the API endpoint for downloading
+        # The file_id is extracted from the path: {workspace_id}/{file_id}/{filename}
+        parts = relative_path.split("/")
+        if len(parts) >= 2:
+            file_id = parts[1]  # Second component is file_id
+            return f"/api/workspace/files/{file_id}/download"
+        else:
+            raise ValueError(f"Invalid storage path format: {storage_path}")
+
+    async def exists(self, storage_path: str) -> bool:
+        """Check if file exists locally."""
+        try:
+            file_path = self._parse_storage_path(storage_path)
+            return file_path.exists()
+        except ValueError:
+            return False
+
+
+# Global storage backend instance
+_workspace_storage: Optional[WorkspaceStorageBackend] = None
+_storage_lock = asyncio.Lock()
+
+
+async def get_workspace_storage() -> WorkspaceStorageBackend:
+    """
+    Get the workspace storage backend instance.
+
+    Uses GCS if media_gcs_bucket_name is configured, otherwise uses local storage.
+    """
+    global _workspace_storage
+
+    if _workspace_storage is None:
+        async with _storage_lock:
+            if _workspace_storage is None:
+                config = Config()
+
+                if config.media_gcs_bucket_name:
+                    logger.info(
+                        f"Using GCS workspace storage: {config.media_gcs_bucket_name}"
+                    )
+                    _workspace_storage = GCSWorkspaceStorage(
+                        config.media_gcs_bucket_name
+                    )
+                else:
+                    storage_dir = (
+                        config.workspace_storage_dir
+                        if config.workspace_storage_dir
+                        else None
+                    )
+                    logger.info(
+                        f"Using local workspace storage: {storage_dir or 'default'}"
+                    )
+                    _workspace_storage = LocalWorkspaceStorage(storage_dir)
+
+    return _workspace_storage
+
+
+def compute_file_checksum(content: bytes) -> str:
+    """Compute SHA256 checksum of file content."""
+    return hashlib.sha256(content).hexdigest()

autogpt_platform/backend/migrations/20260127230419_add_user_workspace/migration.sql

@@ -0,0 +1,52 @@
+-- CreateEnum
+CREATE TYPE "WorkspaceFileSource" AS ENUM ('UPLOAD', 'EXECUTION', 'COPILOT', 'IMPORT');
+
+-- CreateTable
+CREATE TABLE "UserWorkspace" (
+    "id" TEXT NOT NULL,
+    "createdAt" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
+    "updatedAt" TIMESTAMP(3) NOT NULL,
+    "userId" TEXT NOT NULL,
+
+    CONSTRAINT "UserWorkspace_pkey" PRIMARY KEY ("id")
+);
+
+-- CreateTable
+CREATE TABLE "UserWorkspaceFile" (
+    "id" TEXT NOT NULL,
+    "createdAt" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
+    "updatedAt" TIMESTAMP(3) NOT NULL,
+    "workspaceId" TEXT NOT NULL,
+    "name" TEXT NOT NULL,
+    "path" TEXT NOT NULL,
+    "storagePath" TEXT NOT NULL,
+    "mimeType" TEXT NOT NULL,
+    "sizeBytes" BIGINT NOT NULL,
+    "checksum" TEXT,
+    "isDeleted" BOOLEAN NOT NULL DEFAULT false,
+    "deletedAt" TIMESTAMP(3),
+    "source" "WorkspaceFileSource" NOT NULL DEFAULT 'UPLOAD',
+    "sourceExecId" TEXT,
+    "sourceSessionId" TEXT,
+    "metadata" JSONB NOT NULL DEFAULT '{}',
+
+    CONSTRAINT "UserWorkspaceFile_pkey" PRIMARY KEY ("id")
+);
+
+-- CreateIndex
+CREATE UNIQUE INDEX "UserWorkspace_userId_key" ON "UserWorkspace"("userId");
+
+-- CreateIndex
+CREATE INDEX "UserWorkspace_userId_idx" ON "UserWorkspace"("userId");
+
+-- CreateIndex
+CREATE INDEX "UserWorkspaceFile_workspaceId_isDeleted_idx" ON "UserWorkspaceFile"("workspaceId", "isDeleted");
+
+-- CreateIndex
+CREATE UNIQUE INDEX "UserWorkspaceFile_workspaceId_path_key" ON "UserWorkspaceFile"("workspaceId", "path");
+
+-- AddForeignKey
+ALTER TABLE "UserWorkspace" ADD CONSTRAINT "UserWorkspace_userId_fkey" FOREIGN KEY ("userId") REFERENCES "User"("id") ON DELETE CASCADE ON UPDATE CASCADE;
+
+-- AddForeignKey
+ALTER TABLE "UserWorkspaceFile" ADD CONSTRAINT "UserWorkspaceFile_workspaceId_fkey" FOREIGN KEY ("workspaceId") REFERENCES "UserWorkspace"("id") ON DELETE CASCADE ON UPDATE CASCADE;

autogpt_platform/backend/schema.prisma

@@ -63,6 +63,7 @@ model User {
   IntegrationWebhooks   IntegrationWebhook[]
   NotificationBatches   UserNotificationBatch[]
   PendingHumanReviews   PendingHumanReview[]
+  Workspace             UserWorkspace?
 
   // OAuth Provider relations
   OAuthApplications       OAuthApplication[]
@@ -136,6 +137,66 @@ model CoPilotUnderstanding {
   @@index([userId])
 }
 
+////////////////////////////////////////////////////////////
+////////////////////////////////////////////////////////////
+////////////////   USER WORKSPACE TABLES   /////////////////
+////////////////////////////////////////////////////////////
+////////////////////////////////////////////////////////////
+
+// User's persistent file storage workspace
+model UserWorkspace {
+  id        String   @id @default(uuid())
+  createdAt DateTime @default(now())
+  updatedAt DateTime @updatedAt
+
+  userId String @unique
+  User   User   @relation(fields: [userId], references: [id], onDelete: Cascade)
+
+  Files UserWorkspaceFile[]
+
+  @@index([userId])
+}
+
+// Source of workspace file creation
+enum WorkspaceFileSource {
+  UPLOAD // Direct user upload
+  EXECUTION // Created by graph execution
+  COPILOT // Created by CoPilot session
+  IMPORT // Imported from external source
+}
+
+// Individual files in a user's workspace
+model UserWorkspaceFile {
+  id        String   @id @default(uuid())
+  createdAt DateTime @default(now())
+  updatedAt DateTime @updatedAt
+
+  workspaceId String
+  Workspace   UserWorkspace @relation(fields: [workspaceId], references: [id], onDelete: Cascade)
+
+  // File metadata
+  name        String // User-visible filename
+  path        String // Virtual path (e.g., "/documents/report.pdf")
+  storagePath String // Actual GCS or local storage path
+  mimeType    String
+  sizeBytes   BigInt
+  checksum    String? // SHA256 for integrity
+
+  // File state
+  isDeleted Boolean   @default(false)
+  deletedAt DateTime?
+
+  // Source tracking
+  source          WorkspaceFileSource @default(UPLOAD)
+  sourceExecId    String? // graph_exec_id if from execution
+  sourceSessionId String? // chat_session_id if from CoPilot
+
+  metadata Json @default("{}")
+
+  @@unique([workspaceId, path])
+  @@index([workspaceId, isDeleted])
+}
+
 model BuilderSearchHistory {
   id        String   @id @default(uuid())
   createdAt DateTime @default(now())

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 {
-  getGetV2ListSessionsQueryKey,
-  useGetV2ListSessions,
-} from "@/app/api/__generated__/endpoints/chat/chat";
+import { useGetV2ListSessions } from "@/app/api/__generated__/endpoints/chat/chat";
 import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
 import { okData } from "@/app/api/helpers";
-import { 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 },
@@ -32,38 +27,23 @@ export function useSessionsPagination({ enabled }: UseSessionsPaginationArgs) {
     },
   );
 
-  useEffect(function refreshOnStreamComplete() {
-    const unsubscribe = onStreamComplete(function handleStreamComplete() {
-      setOffset(0);
+  useEffect(() => {
+    const responseData = okData(data);
+    if (responseData) {
+      const newSessions = responseData.sessions;
+      const total = responseData.total;
+      setTotalCount(total);
+
+      if (offset === 0) {
+        setAccumulatedSessions(newSessions);
+      } else {
+        setAccumulatedSessions((prev) => [...prev, ...newSessions]);
+      }
+    } else if (!enabled) {
       setAccumulatedSessions([]);
       setTotalCount(null);
-      queryClient.invalidateQueries({
-        queryKey: getGetV2ListSessionsQueryKey(),
-      });
-    });
-    return unsubscribe;
-  }, []);
-
-  useEffect(
-    function updateSessionsFromResponse() {
-      const responseData = okData(data);
-      if (responseData) {
-        const newSessions = responseData.sessions;
-        const total = responseData.total;
-        setTotalCount(total);
-
-        if (offset === 0) {
-          setAccumulatedSessions(newSessions);
-        } else {
-          setAccumulatedSessions((prev) => [...prev, ...newSessions]);
-        }
-      } else if (!enabled) {
-        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 {
-  checkReadyToShowContent,
-  convertSessionDetailToSummary,
-  filterVisibleSessions,
-  getCurrentSessionId,
-  mergeCurrentSessionIntoList,
-} from "./helpers";
+import { getCurrentSessionId } from "./helpers";
+import { useShellSessionList } from "./useShellSessionList";
 
 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 } =
-    useGetV2GetSession(currentSessionId || "", {
+  const { data: currentSessionData } = useGetV2GetSession(
+    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
-  useEffect(() => {
-    for (const sessionId of recentlyCreatedSessionsRef.current.keys()) {
-      if (accumulatedSessions.some((s) => s.id === sessionId)) {
-        recentlyCreatedSessionsRef.current.delete(sessionId);
-      }
-    }
-  }, [accumulatedSessions]);
-
-  // Reset pagination when query becomes disabled
-  const prevPaginationEnabledRef = useRef(paginationEnabled);
-  useEffect(() => {
-    if (prevPaginationEnabledRef.current && !paginationEnabled) {
-      resetPagination();
-      resetAutoSelect();
-    }
-    prevPaginationEnabledRef.current = paginationEnabled;
-  }, [paginationEnabled, resetPagination]);
-
-  const sessions = mergeCurrentSessionIntoList(
-    accumulatedSessions,
-    currentSessionId,
-    currentSessionData,
-    recentlyCreatedSessionsRef.current,
+    },
   );
 
-  const visibleSessions = filterVisibleSessions(sessions);
+  const {
+    sessions,
+    isLoading,
+    isSessionsFetching,
+    hasNextPage,
+    fetchNextPage,
+    resetPagination,
+    recentlyCreatedSessionsRef,
+  } = useShellSessionList({
+    paginationEnabled,
+    currentSessionId,
+    currentSessionData,
+    isOnHomepage,
+    paramSessionId,
+  });
 
-  const sidebarSelectedSessionId =
-    isOnHomepage && !paramSessionId ? null : currentSessionId;
+  const stopStream = useChatStore((s) => s.stopStream);
+  const onStreamComplete = useChatStore((s) => s.onStreamComplete);
+  const isStreaming = useCopilotStore((s) => s.isStreaming);
+  const isCreatingSession = useCopilotStore((s) => s.isCreatingSession);
+  const setIsSwitchingSession = useCopilotStore((s) => s.setIsSwitchingSession);
+  const openInterruptModal = useCopilotStore((s) => s.openInterruptModal);
 
-  const isReadyToShowContent = isOnHomepage
-    ? true
-    : checkReadyToShowContent(
-        areAllSessionsLoaded,
-        paramSessionId,
-        accumulatedSessions,
-        isCurrentSessionLoading,
-        currentSessionData,
-        hasAutoSelectedSession,
-      );
+  const pendingActionRef = useRef<(() => void) | null>(null);
 
-  function handleSelectSession(sessionId: string) {
+  async function stopCurrentStream() {
+    if (!currentSessionId) return;
+
+    setIsSwitchingSession(true);
+    await new Promise<void>((resolve) => {
+      const unsubscribe = onStreamComplete((completedId) => {
+        if (completedId === currentSessionId) {
+          clearTimeout(timeout);
+          unsubscribe();
+          resolve();
+        }
+      });
+      const timeout = setTimeout(() => {
+        unsubscribe();
+        resolve();
+      }, 3000);
+      stopStream(currentSessionId);
+    });
+
+    queryClient.invalidateQueries({
+      queryKey: getGetV2GetSessionQueryKey(currentSessionId),
+    });
+    setIsSwitchingSession(false);
+  }
+
+  function selectSession(sessionId: string) {
+    if (sessionId === currentSessionId) return;
+    if (recentlyCreatedSessionsRef.current.has(sessionId)) {
+      queryClient.invalidateQueries({
+        queryKey: getGetV2GetSessionQueryKey(sessionId),
+      });
+    }
     setUrlSessionId(sessionId, { shallow: false });
     if (isMobile) handleCloseDrawer();
   }
 
-  function handleNewChat() {
-    resetAutoSelect();
+  function startNewChat() {
     resetPagination();
     queryClient.invalidateQueries({
       queryKey: getGetV2ListSessionsQueryKey(),
@@ -170,12 +123,31 @@ export function useCopilotShell() {
     if (isMobile) handleCloseDrawer();
   }
 
-  function resetAutoSelect() {
-    hasAutoSelectedRef.current = false;
-    setHasAutoSelectedSession(false);
+  function handleSessionClick(sessionId: string) {
+    if (sessionId === currentSessionId) return;
+
+    if (isStreaming) {
+      pendingActionRef.current = async () => {
+        await stopCurrentStream();
+        selectSession(sessionId);
+      };
+      openInterruptModal(pendingActionRef.current);
+    } else {
+      selectSession(sessionId);
+    }
   }
 
-  const isLoading = isSessionsLoading && accumulatedSessions.length === 0;
+  function handleNewChatClick() {
+    if (isStreaming) {
+      pendingActionRef.current = async () => {
+        await stopCurrentStream();
+        startNewChat();
+      };
+      openInterruptModal(pendingActionRef.current);
+    } else {
+      startNewChat();
+    }
+  }
 
   return {
     isMobile,
@@ -183,17 +155,17 @@ export function useCopilotShell() {
     isLoggedIn,
     hasActiveSession:
       Boolean(currentSessionId) && (!isOnHomepage || Boolean(paramSessionId)),
-    isLoading,
-    sessions: visibleSessions,
-    currentSessionId: sidebarSelectedSessionId,
-    handleSelectSession,
+    isLoading: isLoading || isCreatingSession,
+    isCreatingSession,
+    sessions,
+    currentSessionId: urlSessionId,
     handleOpenDrawer,
     handleCloseDrawer,
     handleDrawerOpenChange,
-    handleNewChat,
+    handleNewChatClick,
+    handleSessionClick,
     hasNextPage,
     isFetchingNextPage: isSessionsFetching,
     fetchNextPage,
-    isReadyToShowContent,
   };
 }

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

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

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

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

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

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

autogpt_platform/frontend/src/app/(platform)/copilot/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,
-    isNewChatModalOpen,
+    hasSession,
+    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={pageState.initialPrompt}
+          initialPrompt={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,
-            set: handleNewChatModalOpen,
+            isOpen: isInterruptModalOpen,
+            set: (open) => {
+              if (!open) cancelInterrupt();
+            },
           }}
-          onClose={handleCancelNewChat}
+          onClose={cancelInterrupt}
         >
           <Dialog.Content>
             <div className="flex flex-col gap-4">
               <Text variant="body">
                 The current chat response will be interrupted. Are you sure you
-                want to start a new chat?
+                want to continue?
               </Text>
               <Dialog.Footer>
                 <Button
                   type="button"
                   variant="outline"
-                  onClick={handleCancelNewChat}
+                  onClick={cancelInterrupt}
                 >
                   Cancel
                 </Button>
                 <Button
                   type="button"
                   variant="primary"
-                  onClick={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

@@ -10,64 +10,15 @@ import {
   type FlagValues,
   useGetFlag,
 } from "@/services/feature-flags/use-get-flag";
+import { SessionKey, sessionStorage } from "@/services/storage/session-storage";
 import * as Sentry from "@sentry/nextjs";
 import { useQueryClient } from "@tanstack/react-query";
 import { useFlags } from "launchdarkly-react-client-sdk";
 import { useRouter } from "next/navigation";
-import { useEffect, useReducer } from "react";
+import { useEffect } from "react";
 import { useCopilotStore } from "./copilot-page-store";
-import { getGreetingName, getQuickActions, type PageState } from "./helpers";
-import { useCopilotURLState } from "./useCopilotURLState";
-
-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;
-}
+import { getGreetingName, getQuickActions } from "./helpers";
+import { useCopilotSessionId } from "./useCopilotSessionId";
 
 export function useCopilotPage() {
   const router = useRouter();
@@ -75,9 +26,10 @@ export function useCopilotPage() {
   const { user, isLoggedIn, isUserLoading } = useSupabase();
   const { toast } = useToast();
 
-  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);
 
   const isChatEnabled = useGetFlag(Flag.CHAT);
   const flags = useFlags<FlagValues>();
@@ -88,72 +40,27 @@ 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) {
-    dispatch({ type: "setPageState", pageState });
-  }
+  const hasSession = Boolean(urlSessionId);
+  const initialPrompt = urlSessionId
+    ? getInitialPrompt(urlSessionId)
+    : undefined;
 
-  function setInitialPrompt(sessionId: string, prompt: string) {
-    dispatch({ type: "setInitialPrompt", sessionId, prompt });
-  }
-
-  function setPreviousSessionId(sessionId: string | null) {
-    dispatch({ type: "setPreviousSessionId", sessionId });
-  }
-
-  const { setUrlSessionId } = useCopilotURLState({
-    pageState: state.pageState,
-    initialPrompts: state.initialPrompts,
-    previousSessionId: state.previousSessionId,
-    setPageState,
-    setInitialPrompt,
-    setPreviousSessionId,
-  });
-
-  useEffect(
-    function transitionNewChatToWelcome() {
-      if (state.pageState.type === "newChat") {
-        function setWelcomeState() {
-          dispatch({ type: "setPageState", pageState: { type: "welcome" } });
-        }
-
-        const timer = setTimeout(setWelcomeState, 300);
-
-        return function cleanup() {
-          clearTimeout(timer);
-        };
-      }
-    },
-    [state.pageState.type],
-  );
-
-  useEffect(
-    function ensureAccess() {
-      if (!isFlagReady) return;
-      if (isChatEnabled === false) {
-        router.replace(homepageRoute);
-      }
-    },
-    [homepageRoute, isChatEnabled, isFlagReady, router],
-  );
+  useEffect(() => {
+    if (!isFlagReady) return;
+    if (isChatEnabled === false) {
+      router.replace(homepageRoute);
+    }
+  }, [homepageRoute, isChatEnabled, isFlagReady, router]);
 
   async function startChatWithPrompt(prompt: string) {
     if (!prompt?.trim()) return;
-    if (state.pageState.type === "creating") return;
+    if (isCreating) return;
 
     const trimmedPrompt = prompt.trim();
-    dispatch({
-      type: "setPageState",
-      pageState: { type: "creating", prompt: trimmedPrompt },
-    });
+    setIsCreating(true);
 
     try {
       const sessionResponse = await postV2CreateSession({
@@ -165,27 +72,19 @@ export function useCopilotPage() {
       }
 
       const sessionId = sessionResponse.data.id;
-
-      dispatch({
-        type: "setInitialPrompt",
-        sessionId,
-        prompt: trimmedPrompt,
-      });
+      setInitialPrompt(sessionId, trimmedPrompt);
 
       await queryClient.invalidateQueries({
         queryKey: getGetV2ListSessionsQueryKey(),
       });
 
-      await setUrlSessionId(sessionId, { shallow: false });
-      dispatch({
-        type: "setPageState",
-        pageState: { type: "chat", sessionId, initialPrompt: trimmedPrompt },
-      });
+      await setUrlSessionId(sessionId, { shallow: true });
     } catch (error) {
       console.error("[CopilotPage] Failed to start chat:", error);
       toast({ title: "Failed to start chat", variant: "destructive" });
       Sentry.captureException(error);
-      dispatch({ type: "setPageState", pageState: { type: "welcome" } });
+    } finally {
+      setIsCreating(false);
     }
   }
 
@@ -201,21 +100,13 @@ export function useCopilotPage() {
     setIsStreaming(isStreamingValue);
   }
 
-  function handleCancelNewChat() {
-    cancelNewChat();
-  }
-
-  function handleNewChatModalOpen(isOpen: boolean) {
-    if (!isOpen) cancelNewChat();
-  }
-
   return {
     state: {
       greetingName,
       quickActions,
       isLoading: isUserLoading,
-      pageState: state.pageState,
-      isNewChatModalOpen,
+      hasSession,
+      initialPrompt,
       isReady: isFlagReady && isChatEnabled !== false && isLoggedIn,
     },
     handlers: {
@@ -223,8 +114,32 @@ 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/api/openapi.json

@@ -1933,7 +1933,9 @@
             "description": "Successful Response",
             "content": {
               "application/json": {
-                "schema": { "$ref": "#/components/schemas/UploadFileResponse" }
+                "schema": {
+                  "$ref": "#/components/schemas/backend__api__model__UploadFileResponse"
+                }
               }
             }
           },
@@ -5927,6 +5929,478 @@
         }
       }
     },
+    "/api/workspace": {
+      "get": {
+        "tags": ["v2", "workspace"],
+        "summary": "Get workspace info",
+        "description": "Get the current user's workspace information.\nCreates workspace if it doesn't exist.",
+        "operationId": "getV2Get workspace info",
+        "responses": {
+          "200": {
+            "description": "Successful Response",
+            "content": {
+              "application/json": {
+                "schema": { "$ref": "#/components/schemas/WorkspaceInfo" }
+              }
+            }
+          },
+          "401": {
+            "$ref": "#/components/responses/HTTP401NotAuthenticatedError"
+          }
+        },
+        "security": [{ "HTTPBearerJWT": [] }]
+      }
+    },
+    "/api/workspace/files": {
+      "get": {
+        "tags": ["v2", "workspace"],
+        "summary": "List workspace files",
+        "description": "List files in the user's workspace.\n\n- **path**: Optional path prefix to filter results\n- **limit**: Maximum number of files to return (1-100)\n- **offset**: Number of files to skip",
+        "operationId": "getV2List workspace files",
+        "security": [{ "HTTPBearerJWT": [] }],
+        "parameters": [
+          {
+            "name": "path",
+            "in": "query",
+            "required": false,
+            "schema": {
+              "anyOf": [{ "type": "string" }, { "type": "null" }],
+              "description": "Path prefix filter",
+              "title": "Path"
+            },
+            "description": "Path prefix filter"
+          },
+          {
+            "name": "limit",
+            "in": "query",
+            "required": false,
+            "schema": {
+              "type": "integer",
+              "maximum": 100,
+              "minimum": 1,
+              "default": 50,
+              "title": "Limit"
+            }
+          },
+          {
+            "name": "offset",
+            "in": "query",
+            "required": false,
+            "schema": {
+              "type": "integer",
+              "minimum": 0,
+              "default": 0,
+              "title": "Offset"
+            }
+          }
+        ],
+        "responses": {
+          "200": {
+            "description": "Successful Response",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/WorkspaceFileListResponse"
+                }
+              }
+            }
+          },
+          "401": {
+            "$ref": "#/components/responses/HTTP401NotAuthenticatedError"
+          },
+          "422": {
+            "description": "Validation Error",
+            "content": {
+              "application/json": {
+                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
+              }
+            }
+          }
+        }
+      },
+      "post": {
+        "tags": ["v2", "workspace"],
+        "summary": "Upload file to workspace",
+        "description": "Upload a file to the user's workspace.\n\n- **file**: The file to upload (max 100MB)\n- **path**: Optional virtual path (defaults to \"/{filename}\")\n- **overwrite**: Whether to overwrite existing file at path",
+        "operationId": "postV2Upload file to workspace",
+        "security": [{ "HTTPBearerJWT": [] }],
+        "parameters": [
+          {
+            "name": "path",
+            "in": "query",
+            "required": false,
+            "schema": {
+              "anyOf": [{ "type": "string" }, { "type": "null" }],
+              "title": "Path"
+            }
+          },
+          {
+            "name": "overwrite",
+            "in": "query",
+            "required": false,
+            "schema": {
+              "type": "boolean",
+              "default": false,
+              "title": "Overwrite"
+            }
+          }
+        ],
+        "requestBody": {
+          "required": true,
+          "content": {
+            "multipart/form-data": {
+              "schema": {
+                "$ref": "#/components/schemas/Body_postV2Upload_file_to_workspace"
+              }
+            }
+          }
+        },
+        "responses": {
+          "200": {
+            "description": "Successful Response",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/backend__api__features__workspace__models__UploadFileResponse"
+                }
+              }
+            }
+          },
+          "401": {
+            "$ref": "#/components/responses/HTTP401NotAuthenticatedError"
+          },
+          "422": {
+            "description": "Validation Error",
+            "content": {
+              "application/json": {
+                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
+              }
+            }
+          }
+        }
+      }
+    },
+    "/api/workspace/files/by-path": {
+      "delete": {
+        "tags": ["v2", "workspace"],
+        "summary": "Delete file by path",
+        "description": "Delete a file by its virtual path (soft-delete).",
+        "operationId": "deleteV2Delete file by path",
+        "security": [{ "HTTPBearerJWT": [] }],
+        "parameters": [
+          {
+            "name": "path",
+            "in": "query",
+            "required": true,
+            "schema": {
+              "type": "string",
+              "description": "Virtual file path",
+              "title": "Path"
+            },
+            "description": "Virtual file path"
+          }
+        ],
+        "responses": {
+          "200": {
+            "description": "Successful Response",
+            "content": {
+              "application/json": {
+                "schema": { "$ref": "#/components/schemas/DeleteFileResponse" }
+              }
+            }
+          },
+          "401": {
+            "$ref": "#/components/responses/HTTP401NotAuthenticatedError"
+          },
+          "422": {
+            "description": "Validation Error",
+            "content": {
+              "application/json": {
+                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
+              }
+            }
+          }
+        }
+      },
+      "get": {
+        "tags": ["v2", "workspace"],
+        "summary": "Get file info by path",
+        "description": "Get file metadata by virtual path.",
+        "operationId": "getV2Get file info by path",
+        "security": [{ "HTTPBearerJWT": [] }],
+        "parameters": [
+          {
+            "name": "path",
+            "in": "query",
+            "required": true,
+            "schema": {
+              "type": "string",
+              "description": "Virtual file path",
+              "title": "Path"
+            },
+            "description": "Virtual file path"
+          }
+        ],
+        "responses": {
+          "200": {
+            "description": "Successful Response",
+            "content": {
+              "application/json": {
+                "schema": { "$ref": "#/components/schemas/WorkspaceFileInfo" }
+              }
+            }
+          },
+          "401": {
+            "$ref": "#/components/responses/HTTP401NotAuthenticatedError"
+          },
+          "422": {
+            "description": "Validation Error",
+            "content": {
+              "application/json": {
+                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
+              }
+            }
+          }
+        }
+      }
+    },
+    "/api/workspace/files/by-path/download": {
+      "get": {
+        "tags": ["v2", "workspace"],
+        "summary": "Download file by path",
+        "description": "Download a file by its virtual path.",
+        "operationId": "getV2Download file by path",
+        "security": [{ "HTTPBearerJWT": [] }],
+        "parameters": [
+          {
+            "name": "path",
+            "in": "query",
+            "required": true,
+            "schema": {
+              "type": "string",
+              "description": "Virtual file path",
+              "title": "Path"
+            },
+            "description": "Virtual file path"
+          }
+        ],
+        "responses": {
+          "200": {
+            "description": "Successful Response",
+            "content": { "application/json": { "schema": {} } }
+          },
+          "401": {
+            "$ref": "#/components/responses/HTTP401NotAuthenticatedError"
+          },
+          "422": {
+            "description": "Validation Error",
+            "content": {
+              "application/json": {
+                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
+              }
+            }
+          }
+        }
+      }
+    },
+    "/api/workspace/files/write": {
+      "post": {
+        "tags": ["v2", "workspace"],
+        "summary": "Write file content directly",
+        "description": "Write file content directly to workspace (for programmatic access).\n\n- **filename**: Name for the file\n- **content_base64**: Base64-encoded file content\n- **path**: Optional virtual path (defaults to \"/{filename}\")\n- **mime_type**: Optional MIME type (auto-detected if not provided)\n- **overwrite**: Whether to overwrite existing file at path",
+        "operationId": "postV2Write file content directly",
+        "requestBody": {
+          "content": {
+            "application/json": {
+              "schema": { "$ref": "#/components/schemas/WriteFileRequest" }
+            }
+          },
+          "required": true
+        },
+        "responses": {
+          "200": {
+            "description": "Successful Response",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/backend__api__features__workspace__models__UploadFileResponse"
+                }
+              }
+            }
+          },
+          "401": {
+            "$ref": "#/components/responses/HTTP401NotAuthenticatedError"
+          },
+          "422": {
+            "description": "Validation Error",
+            "content": {
+              "application/json": {
+                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
+              }
+            }
+          }
+        },
+        "security": [{ "HTTPBearerJWT": [] }]
+      }
+    },
+    "/api/workspace/files/{file_id}": {
+      "delete": {
+        "tags": ["v2", "workspace"],
+        "summary": "Delete file by ID",
+        "description": "Delete a file from the workspace (soft-delete).",
+        "operationId": "deleteV2Delete file by id",
+        "security": [{ "HTTPBearerJWT": [] }],
+        "parameters": [
+          {
+            "name": "file_id",
+            "in": "path",
+            "required": true,
+            "schema": { "type": "string", "title": "File Id" }
+          }
+        ],
+        "responses": {
+          "200": {
+            "description": "Successful Response",
+            "content": {
+              "application/json": {
+                "schema": { "$ref": "#/components/schemas/DeleteFileResponse" }
+              }
+            }
+          },
+          "401": {
+            "$ref": "#/components/responses/HTTP401NotAuthenticatedError"
+          },
+          "422": {
+            "description": "Validation Error",
+            "content": {
+              "application/json": {
+                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
+              }
+            }
+          }
+        }
+      },
+      "get": {
+        "tags": ["v2", "workspace"],
+        "summary": "Get file info by ID",
+        "description": "Get file metadata by file ID.",
+        "operationId": "getV2Get file info by id",
+        "security": [{ "HTTPBearerJWT": [] }],
+        "parameters": [
+          {
+            "name": "file_id",
+            "in": "path",
+            "required": true,
+            "schema": { "type": "string", "title": "File Id" }
+          }
+        ],
+        "responses": {
+          "200": {
+            "description": "Successful Response",
+            "content": {
+              "application/json": {
+                "schema": { "$ref": "#/components/schemas/WorkspaceFileInfo" }
+              }
+            }
+          },
+          "401": {
+            "$ref": "#/components/responses/HTTP401NotAuthenticatedError"
+          },
+          "422": {
+            "description": "Validation Error",
+            "content": {
+              "application/json": {
+                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
+              }
+            }
+          }
+        }
+      }
+    },
+    "/api/workspace/files/{file_id}/download": {
+      "get": {
+        "tags": ["v2", "workspace"],
+        "summary": "Download file by ID",
+        "description": "Download a file by its ID.\n\nReturns the file content directly or redirects to a signed URL for GCS.",
+        "operationId": "getV2Download file by id",
+        "security": [{ "HTTPBearerJWT": [] }],
+        "parameters": [
+          {
+            "name": "file_id",
+            "in": "path",
+            "required": true,
+            "schema": { "type": "string", "title": "File Id" }
+          }
+        ],
+        "responses": {
+          "200": {
+            "description": "Successful Response",
+            "content": { "application/json": { "schema": {} } }
+          },
+          "401": {
+            "$ref": "#/components/responses/HTTP401NotAuthenticatedError"
+          },
+          "422": {
+            "description": "Validation Error",
+            "content": {
+              "application/json": {
+                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
+              }
+            }
+          }
+        }
+      }
+    },
+    "/api/workspace/files/{file_id}/url": {
+      "get": {
+        "tags": ["v2", "workspace"],
+        "summary": "Get download URL",
+        "description": "Get a download URL for a file.\n\n- **expires_in**: URL expiration time in seconds (60-86400, default 3600)",
+        "operationId": "getV2Get download url",
+        "security": [{ "HTTPBearerJWT": [] }],
+        "parameters": [
+          {
+            "name": "file_id",
+            "in": "path",
+            "required": true,
+            "schema": { "type": "string", "title": "File Id" }
+          },
+          {
+            "name": "expires_in",
+            "in": "query",
+            "required": false,
+            "schema": {
+              "type": "integer",
+              "maximum": 86400,
+              "minimum": 60,
+              "default": 3600,
+              "title": "Expires In"
+            }
+          }
+        ],
+        "responses": {
+          "200": {
+            "description": "Successful Response",
+            "content": {
+              "application/json": {
+                "schema": { "$ref": "#/components/schemas/DownloadUrlResponse" }
+              }
+            }
+          },
+          "401": {
+            "$ref": "#/components/responses/HTTP401NotAuthenticatedError"
+          },
+          "422": {
+            "description": "Validation Error",
+            "content": {
+              "application/json": {
+                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
+              }
+            }
+          }
+        }
+      }
+    },
     "/health": {
       "get": {
         "tags": ["health"],
@@ -6698,6 +7172,14 @@
         "type": "object",
         "title": "Body_postV2Execute a preset"
       },
+      "Body_postV2Upload_file_to_workspace": {
+        "properties": {
+          "file": { "type": "string", "format": "binary", "title": "File" }
+        },
+        "type": "object",
+        "required": ["file"],
+        "title": "Body_postV2Upload file to workspace"
+      },
       "Body_postV2Upload_submission_media": {
         "properties": {
           "file": { "type": "string", "format": "binary", "title": "File" }
@@ -6989,6 +7471,17 @@
         "enum": ["TOP_UP", "USAGE", "GRANT", "REFUND", "CARD_CHECK"],
         "title": "CreditTransactionType"
       },
+      "DeleteFileResponse": {
+        "properties": {
+          "success": { "type": "boolean", "title": "Success" },
+          "file_id": { "type": "string", "title": "File Id" },
+          "message": { "type": "string", "title": "Message" }
+        },
+        "type": "object",
+        "required": ["success", "file_id", "message"],
+        "title": "DeleteFileResponse",
+        "description": "Response model for file deletion."
+      },
       "DeleteGraphResponse": {
         "properties": {
           "version_counts": { "type": "integer", "title": "Version Counts" }
@@ -7006,6 +7499,19 @@
         "required": ["url", "relevance_score"],
         "title": "Document"
       },
+      "DownloadUrlResponse": {
+        "properties": {
+          "url": { "type": "string", "title": "Url" },
+          "expires_in_seconds": {
+            "type": "integer",
+            "title": "Expires In Seconds"
+          }
+        },
+        "type": "object",
+        "required": ["url", "expires_in_seconds"],
+        "title": "DownloadUrlResponse",
+        "description": "Response model for download URL."
+      },
       "ExecutionAnalyticsConfig": {
         "properties": {
           "available_models": {
@@ -11722,24 +12228,6 @@
         "required": ["timezone"],
         "title": "UpdateTimezoneRequest"
       },
-      "UploadFileResponse": {
-        "properties": {
-          "file_uri": { "type": "string", "title": "File Uri" },
-          "file_name": { "type": "string", "title": "File Name" },
-          "size": { "type": "integer", "title": "Size" },
-          "content_type": { "type": "string", "title": "Content Type" },
-          "expires_in_hours": { "type": "integer", "title": "Expires In Hours" }
-        },
-        "type": "object",
-        "required": [
-          "file_uri",
-          "file_name",
-          "size",
-          "content_type",
-          "expires_in_hours"
-        ],
-        "title": "UploadFileResponse"
-      },
       "UserHistoryResponse": {
         "properties": {
           "history": {
@@ -12043,6 +12531,159 @@
           "url"
         ],
         "title": "Webhook"
+      },
+      "WorkspaceFileInfo": {
+        "properties": {
+          "id": { "type": "string", "title": "Id" },
+          "name": { "type": "string", "title": "Name" },
+          "path": { "type": "string", "title": "Path" },
+          "mime_type": { "type": "string", "title": "Mime Type" },
+          "size_bytes": { "type": "integer", "title": "Size Bytes" },
+          "checksum": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Checksum"
+          },
+          "source": { "$ref": "#/components/schemas/WorkspaceFileSource" },
+          "source_exec_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Source Exec Id"
+          },
+          "source_session_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Source Session Id"
+          },
+          "created_at": {
+            "type": "string",
+            "format": "date-time",
+            "title": "Created At"
+          },
+          "updated_at": {
+            "type": "string",
+            "format": "date-time",
+            "title": "Updated At"
+          },
+          "metadata": {
+            "additionalProperties": true,
+            "type": "object",
+            "title": "Metadata"
+          }
+        },
+        "type": "object",
+        "required": [
+          "id",
+          "name",
+          "path",
+          "mime_type",
+          "size_bytes",
+          "source",
+          "created_at",
+          "updated_at"
+        ],
+        "title": "WorkspaceFileInfo",
+        "description": "Response model for workspace file information."
+      },
+      "WorkspaceFileListResponse": {
+        "properties": {
+          "files": {
+            "items": { "$ref": "#/components/schemas/WorkspaceFileInfo" },
+            "type": "array",
+            "title": "Files"
+          },
+          "total_count": { "type": "integer", "title": "Total Count" },
+          "path_filter": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Path Filter"
+          }
+        },
+        "type": "object",
+        "required": ["files", "total_count"],
+        "title": "WorkspaceFileListResponse",
+        "description": "Response model for listing workspace files."
+      },
+      "WorkspaceFileSource": {
+        "type": "string",
+        "enum": ["UPLOAD", "EXECUTION", "COPILOT", "IMPORT"],
+        "title": "WorkspaceFileSource"
+      },
+      "WorkspaceInfo": {
+        "properties": {
+          "id": { "type": "string", "title": "Id" },
+          "user_id": { "type": "string", "title": "User Id" },
+          "created_at": {
+            "type": "string",
+            "format": "date-time",
+            "title": "Created At"
+          },
+          "updated_at": {
+            "type": "string",
+            "format": "date-time",
+            "title": "Updated At"
+          },
+          "file_count": {
+            "type": "integer",
+            "title": "File Count",
+            "default": 0
+          }
+        },
+        "type": "object",
+        "required": ["id", "user_id", "created_at", "updated_at"],
+        "title": "WorkspaceInfo",
+        "description": "Response model for workspace information."
+      },
+      "WriteFileRequest": {
+        "properties": {
+          "filename": { "type": "string", "title": "Filename" },
+          "content_base64": {
+            "type": "string",
+            "title": "Content Base64",
+            "description": "Base64-encoded file content"
+          },
+          "path": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Path"
+          },
+          "mime_type": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Mime Type"
+          },
+          "overwrite": {
+            "type": "boolean",
+            "title": "Overwrite",
+            "default": false
+          }
+        },
+        "type": "object",
+        "required": ["filename", "content_base64"],
+        "title": "WriteFileRequest",
+        "description": "Request model for writing file content directly (for CoPilot tools)."
+      },
+      "backend__api__features__workspace__models__UploadFileResponse": {
+        "properties": {
+          "file": { "$ref": "#/components/schemas/WorkspaceFileInfo" },
+          "message": { "type": "string", "title": "Message" }
+        },
+        "type": "object",
+        "required": ["file", "message"],
+        "title": "UploadFileResponse",
+        "description": "Response model for file upload."
+      },
+      "backend__api__model__UploadFileResponse": {
+        "properties": {
+          "file_uri": { "type": "string", "title": "File Uri" },
+          "file_name": { "type": "string", "title": "File Name" },
+          "size": { "type": "integer", "title": "Size" },
+          "content_type": { "type": "string", "title": "Content Type" },
+          "expires_in_hours": { "type": "integer", "title": "Expires In Hours" }
+        },
+        "type": "object",
+        "required": [
+          "file_uri",
+          "file_name",
+          "size",
+          "content_type",
+          "expires_in_hours"
+        ],
+        "title": "UploadFileResponse"
       }
     },
     "securitySchemes": {

autogpt_platform/frontend/src/app/api/proxy/[...path]/route.ts

@@ -1,5 +1,6 @@
 import {
   ApiError,
+  getServerAuthToken,
   makeAuthenticatedFileUpload,
   makeAuthenticatedRequest,
 } from "@/lib/autogpt-server-api/helpers";
@@ -15,6 +16,69 @@ function buildBackendUrl(path: string[], queryString: string): string {
   return `${environment.getAGPTServerBaseUrl()}/${backendPath}${queryString}`;
 }
 
+/**
+ * Check if this is a workspace file download request that needs binary response handling.
+ */
+function isWorkspaceDownloadRequest(path: string[]): boolean {
+  // Match pattern: api/workspace/files/{id}/download
+  return (
+    path.length >= 4 &&
+    path[0] === "api" &&
+    path[1] === "workspace" &&
+    path[2] === "files" &&
+    path[path.length - 1] === "download"
+  );
+}
+
+/**
+ * Handle workspace file download requests with proper binary response streaming.
+ */
+async function handleWorkspaceDownload(
+  req: NextRequest,
+  backendUrl: string,
+): Promise<NextResponse> {
+  const token = await getServerAuthToken();
+
+  const headers: Record<string, string> = {};
+  if (token && token !== "no-token-found") {
+    headers["Authorization"] = `Bearer ${token}`;
+  }
+
+  const response = await fetch(backendUrl, {
+    method: "GET",
+    headers,
+    redirect: "follow", // Follow redirects to signed URLs
+  });
+
+  if (!response.ok) {
+    return NextResponse.json(
+      { error: `Failed to download file: ${response.statusText}` },
+      { status: response.status },
+    );
+  }
+
+  // Get the content type from the backend response
+  const contentType =
+    response.headers.get("Content-Type") || "application/octet-stream";
+  const contentDisposition = response.headers.get("Content-Disposition");
+
+  // Stream the response body
+  const responseHeaders: Record<string, string> = {
+    "Content-Type": contentType,
+  };
+
+  if (contentDisposition) {
+    responseHeaders["Content-Disposition"] = contentDisposition;
+  }
+
+  // Return the binary content
+  const arrayBuffer = await response.arrayBuffer();
+  return new NextResponse(arrayBuffer, {
+    status: 200,
+    headers: responseHeaders,
+  });
+}
+
 async function handleJsonRequest(
   req: NextRequest,
   method: string,
@@ -180,6 +244,11 @@ async function handler(
   };
 
   try {
+    // Handle workspace file downloads separately (binary response)
+    if (method === "GET" && isWorkspaceDownloadRequest(path)) {
+      return await handleWorkspaceDownload(req, backendUrl);
+    }
+
     if (method === "GET" || method === "DELETE") {
       responseBody = await handleGetDeleteRequest(method, backendUrl, req);
     } else if (contentType?.includes("application/json")) {

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,
@@ -35,41 +37,49 @@ export function Chat({
     showLoader,
   } = useChat({ urlSessionId });
 
-  useEffect(
-    function handleMissingSession() {
-      if (!onSessionNotFound) return;
-      if (!urlSessionId) return;
-      if (!isSessionNotFound || isLoading || isCreating) return;
-      if (hasHandledNotFoundRef.current) return;
-      hasHandledNotFoundRef.current = true;
-      onSessionNotFound();
-    },
-    [onSessionNotFound, urlSessionId, isSessionNotFound, isLoading, isCreating],
-  );
+  useEffect(() => {
+    if (!onSessionNotFound) return;
+    if (!urlSessionId) return;
+    if (!isSessionNotFound || isLoading || isCreating) return;
+    if (hasHandledNotFoundRef.current) return;
+    hasHandledNotFoundRef.current = true;
+    onSessionNotFound();
+  }, [
+    onSessionNotFound,
+    urlSessionId,
+    isSessionNotFound,
+    isLoading,
+    isCreating,
+  ]);
+
+  const shouldShowLoader =
+    (showLoader && (isLoading || isCreating)) || isSwitchingSession;
 
   return (
     <div className={cn("flex h-full flex-col", className)}>
       {/* Main Content */}
       <main className="flex min-h-0 w-full flex-1 flex-col overflow-hidden bg-[#f8f8f9]">
         {/* Loading State */}
-        {showLoader && (isLoading || isCreating) && (
+        {shouldShowLoader && (
           <div className="flex flex-1 items-center justify-center">
-            <div className="flex flex-col items-center gap-4">
-              <ChatLoader />
+            <div className="flex flex-col items-center gap-3">
+              <LoadingSpinner size="large" className="text-neutral-400" />
               <Text variant="body" className="text-zinc-500">
-                Loading your chats...
+                {isSwitchingSession
+                  ? "Switching chat..."
+                  : "Loading your chat..."}
               </Text>
             </div>
           </div>
         )}
 
         {/* Error State */}
-        {error && !isLoading && (
+        {error && !isLoading && !isSwitchingSession && (
           <ChatErrorState error={error} onRetry={createSession} />
         )}
 
         {/* Session Content */}
-        {sessionId && !isLoading && !error && (
+        {sessionId && !isLoading && !error && !isSwitchingSession && (
           <ChatContainer
             sessionId={sessionId}
             initialMessages={messages}

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

@@ -58,39 +58,17 @@ function notifyStreamComplete(
   }
 }
 
-function cleanupCompletedStreams(completedStreams: Map<string, StreamResult>) {
+function cleanupExpiredStreams(
+  completedStreams: Map<string, StreamResult>,
+): Map<string, StreamResult> {
   const now = Date.now();
-  for (const [sessionId, result] of completedStreams) {
+  const cleaned = new Map(completedStreams);
+  for (const [sessionId, result] of cleaned) {
     if (now - result.completedAt > COMPLETED_STREAM_TTL) {
-      completedStreams.delete(sessionId);
+      cleaned.delete(sessionId);
     }
   }
-}
-
-function moveToCompleted(
-  activeStreams: Map<string, ActiveStream>,
-  completedStreams: Map<string, StreamResult>,
-  streamCompleteCallbacks: Set<StreamCompleteCallback>,
-  sessionId: string,
-) {
-  const stream = activeStreams.get(sessionId);
-  if (!stream) return;
-
-  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(
-        activeStreams,
-        completedStreams,
-        streamCompleteCallbacks,
+      const normalizedStatus =
+        existingStream.status === "streaming"
+          ? "completed"
+          : existingStream.status;
+      const result: StreamResult = {
         sessionId,
-      );
+        status: normalizedStatus,
+        chunks: existingStream.chunks,
+        completedAt: Date.now(),
+        error: existingStream.error,
+      };
+      newCompletedStreams.set(sessionId, result);
+      newActiveStreams.delete(sessionId);
+      newCompletedStreams = cleanupExpiredStreams(newCompletedStreams);
+      if (normalizedStatus === "completed" || normalizedStatus === "error") {
+        notifyStreamComplete(callbacks, sessionId);
+      }
     }
 
     const abortController = new AbortController();
@@ -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(
-          activeStreams,
-          completedStreams,
-          streamCompleteCallbacks,
-          sessionId,
-        );
+        const currentState = get();
+        const finalActiveStreams = new Map(currentState.activeStreams);
+        let finalCompletedStreams = new Map(currentState.completedStreams);
+
+        const storedStream = finalActiveStreams.get(sessionId);
+        if (storedStream === stream) {
+          const result: StreamResult = {
+            sessionId,
+            status: stream.status,
+            chunks: stream.chunks,
+            completedAt: Date.now(),
+            error: stream.error,
+          };
+          finalCompletedStreams.set(sessionId, result);
+          finalActiveStreams.delete(sessionId);
+          finalCompletedStreams = cleanupExpiredStreams(finalCompletedStreams);
+          set({
+            activeStreams: finalActiveStreams,
+            completedStreams: finalCompletedStreams,
+          });
+          if (stream.status === "completed" || stream.status === "error") {
+            notifyStreamComplete(
+              currentState.streamCompleteCallbacks,
+              sessionId,
+            );
+          }
+        }
       }
     }
   },
 
   stopStream: function stopStream(sessionId) {
-    const { activeStreams, completedStreams, streamCompleteCallbacks } = get();
-    const stream = activeStreams.get(sessionId);
-    if (stream) {
-      stream.abortController.abort();
-      stream.status = "completed";
-      moveToCompleted(
-        activeStreams,
-        completedStreams,
-        streamCompleteCallbacks,
-        sessionId,
-      );
-    }
+    const state = get();
+    const stream = state.activeStreams.get(sessionId);
+    if (!stream) return;
+
+    stream.abortController.abort();
+    stream.status = "completed";
+
+    const newActiveStreams = new Map(state.activeStreams);
+    let newCompletedStreams = new Map(state.completedStreams);
+
+    const result: StreamResult = {
+      sessionId,
+      status: stream.status,
+      chunks: stream.chunks,
+      completedAt: Date.now(),
+      error: stream.error,
+    };
+    newCompletedStreams.set(sessionId, result);
+    newActiveStreams.delete(sessionId);
+    newCompletedStreams = cleanupExpiredStreams(newCompletedStreams);
+
+    set({
+      activeStreams: newActiveStreams,
+      completedStreams: newCompletedStreams,
+    });
+
+    notifyStreamComplete(state.streamCompleteCallbacks, sessionId);
   },
 
   subscribeToStream: function subscribeToStream(
@@ -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();
-    streamCompleteCallbacks.add(callback);
+    const state = get();
+    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/handlers.ts

@@ -48,6 +48,15 @@ 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",
@@ -203,13 +212,24 @@ export function handleStreamEnd(
     ]);
   }
   if (completedContent.trim()) {
-    const assistantMessage: ChatMessageData = {
-      type: "message",
-      role: "assistant",
-      content: completedContent,
-      timestamp: new Date(),
-    };
-    deps.setMessages((prev) => [...prev, assistantMessage]);
+    deps.setMessages((prev) => {
+      // Check if this exact message already exists to prevent duplicates
+      const exists = prev.some(
+        (msg) =>
+          msg.type === "message" &&
+          msg.role === "assistant" &&
+          msg.content === completedContent,
+      );
+      if (exists) return prev;
+
+      const assistantMessage: ChatMessageData = {
+        type: "message",
+        role: "assistant",
+        content: completedContent,
+        timestamp: new Date(),
+      };
+      return [...prev, assistantMessage];
+    });
   }
   deps.setStreamingChunks([]);
   deps.streamingChunksRef.current = [];

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

@@ -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

@@ -82,11 +82,110 @@ export function useChatContainer({
     [sessionId, stopStreaming, activeStreams, subscribeToStream],
   );
 
-  const allMessages = useMemo(
-    () => [...processInitialMessages(initialMessages), ...messages],
-    [initialMessages, messages],
+  // Collect toolIds from completed tool results in initialMessages
+  // Used to filter out operation messages when their results arrive
+  const completedToolIds = useMemo(() => {
+    const processedInitial = processInitialMessages(initialMessages);
+    const ids = new Set<string>();
+    for (const msg of processedInitial) {
+      if (
+        msg.type === "tool_response" ||
+        msg.type === "agent_carousel" ||
+        msg.type === "execution_started"
+      ) {
+        const toolId = (msg as any).toolId;
+        if (toolId) {
+          ids.add(toolId);
+        }
+      }
+    }
+    return ids;
+  }, [initialMessages]);
+
+  // Clean up local operation messages when their completed results arrive from polling
+  // This effect runs when completedToolIds changes (i.e., when polling brings new results)
+  useEffect(
+    function cleanupCompletedOperations() {
+      if (completedToolIds.size === 0) return;
+
+      setMessages((prev) => {
+        const filtered = prev.filter((msg) => {
+          if (
+            msg.type === "operation_started" ||
+            msg.type === "operation_pending" ||
+            msg.type === "operation_in_progress"
+          ) {
+            const toolId = (msg as any).toolId || (msg as any).toolCallId;
+            if (toolId && completedToolIds.has(toolId)) {
+              return false; // Remove - operation completed
+            }
+          }
+          return true;
+        });
+        // Only update state if something was actually filtered
+        return filtered.length === prev.length ? prev : filtered;
+      });
+    },
+    [completedToolIds],
   );
 
+  // Combine initial messages from backend with local streaming messages,
+  // then deduplicate to prevent duplicates when polling refreshes initialMessages
+  const allMessages = useMemo(() => {
+    const processedInitial = processInitialMessages(initialMessages);
+
+    // Filter local messages to remove operation messages for completed tools
+    const filteredLocalMessages = messages.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; // Filter out - operation completed
+        }
+      }
+      return true;
+    });
+
+    const combined = [...processedInitial, ...filteredLocalMessages];
+
+    // Deduplicate by content+role+timestamp. When initialMessages is refreshed via polling,
+    // it may contain messages that are also in the local `messages` state.
+    // Including timestamp prevents dropping legitimate repeated messages (e.g., user sends "yes" twice)
+    const seen = new Set<string>();
+    return combined.filter((msg) => {
+      // Create a key based on type, role, content, and timestamp for deduplication
+      let key: string;
+      if (msg.type === "message") {
+        // Use timestamp (rounded to nearest second) to allow slight variations
+        // while still catching true duplicates from SSE/polling overlap
+        const ts = msg.timestamp
+          ? Math.floor(new Date(msg.timestamp).getTime() / 1000)
+          : "";
+        key = `msg:${msg.role}:${ts}:${msg.content}`;
+      } else if (msg.type === "tool_call") {
+        key = `toolcall:${msg.toolId}`;
+      } else if (
+        msg.type === "operation_started" ||
+        msg.type === "operation_pending" ||
+        msg.type === "operation_in_progress"
+      ) {
+        // Dedupe operation messages by toolId or operationId
+        key = `op:${(msg as any).toolId || (msg as any).operationId || (msg as any).toolCallId || ""}:${msg.toolName}`;
+      } else {
+        // For other types, use a combination of type and first few fields
+        key = `${msg.type}:${JSON.stringify(msg).slice(0, 100)}`;
+      }
+      if (seen.has(key)) {
+        return false;
+      }
+      seen.add(key);
+      return true;
+    });
+  }, [initialMessages, messages]);
+
   async function sendMessage(
     content: string,
     isUserMessage: boolean = true,

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/MarkdownContent/MarkdownContent.tsx

@@ -1,6 +1,8 @@
 "use client";
 
+import { getGetV2DownloadFileByIdUrl } from "@/app/api/__generated__/endpoints/workspace/workspace";
 import { cn } from "@/lib/utils";
+import { EyeSlash } from "@phosphor-icons/react";
 import React from "react";
 import ReactMarkdown from "react-markdown";
 import remarkGfm from "remark-gfm";
@@ -29,12 +31,90 @@ interface InputProps extends React.InputHTMLAttributes<HTMLInputElement> {
   type?: string;
 }
 
+/**
+ * Converts a workspace:// URL to a proxy URL that routes through Next.js to the backend.
+ * workspace://abc123 -> /api/proxy/api/workspace/files/abc123/download
+ *
+ * Uses the generated API URL helper and routes through the Next.js proxy
+ * which handles authentication and proper backend routing.
+ */
+function resolveWorkspaceUrl(src: string): string {
+  if (src.startsWith("workspace://")) {
+    const fileId = src.replace("workspace://", "");
+    // Use the generated API URL helper to get the correct path
+    const apiPath = getGetV2DownloadFileByIdUrl(fileId);
+    // Route through the Next.js proxy (same pattern as customMutator for client-side)
+    return `/api/proxy${apiPath}`;
+  }
+  return src;
+}
+
+/**
+ * URL transformer for ReactMarkdown.
+ * Transforms workspace:// URLs to backend API download URLs before rendering.
+ * This is needed because ReactMarkdown sanitizes URLs and only allows
+ * http, https, mailto, and tel protocols by default.
+ */
+function transformUrl(url: string): string {
+  return resolveWorkspaceUrl(url);
+}
+
+/**
+ * Check if the image URL is a workspace file (AI cannot see these yet).
+ * After URL transformation, workspace files have URLs like /api/proxy/api/workspace/files/...
+ */
+function isWorkspaceImage(src: string | undefined): boolean {
+  return src?.includes("/workspace/files/") ?? false;
+}
+
+/**
+ * Custom image component that shows an indicator when the AI cannot see the image.
+ * Note: src is already transformed by urlTransform, so workspace:// is now /api/workspace/...
+ */
+function MarkdownImage(props: Record<string, unknown>) {
+  const src = props.src as string | undefined;
+  const alt = props.alt as string | undefined;
+
+  const aiCannotSee = isWorkspaceImage(src);
+
+  // If no src, show a placeholder
+  if (!src) {
+    return (
+      <span className="my-2 inline-block rounded border border-amber-200 bg-amber-50 px-2 py-1 text-sm text-amber-700">
+        [Image: {alt || "missing src"}]
+      </span>
+    );
+  }
+
+  return (
+    <span className="relative my-2 inline-block">
+      {/* eslint-disable-next-line @next/next/no-img-element */}
+      <img
+        src={src}
+        alt={alt || "Image"}
+        className="h-auto max-w-full rounded-md border border-zinc-200"
+        loading="lazy"
+      />
+      {aiCannotSee && (
+        <span
+          className="absolute bottom-2 right-2 flex items-center gap-1 rounded bg-black/70 px-2 py-1 text-xs text-white"
+          title="The AI cannot see this image"
+        >
+          <EyeSlash size={14} />
+          <span>AI cannot see this image</span>
+        </span>
+      )}
+    </span>
+  );
+}
+
 export function MarkdownContent({ content, className }: MarkdownContentProps) {
   return (
     <div className={cn("markdown-content", className)}>
       <ReactMarkdown
         skipHtml={true}
         remarkPlugins={[remarkGfm]}
+        urlTransform={transformUrl}
         components={{
           code: ({ children, className, ...props }: CodeProps) => {
             const isInline = !className?.includes("language-");
@@ -206,6 +286,9 @@ export function MarkdownContent({ content, className }: MarkdownContentProps) {
               {children}
             </td>
           ),
+          img: ({ src, alt, ...props }) => (
+            <MarkdownImage src={src} alt={alt} {...props} />
+          ),
         }}
       >
         {content}

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

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

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

@@ -37,6 +37,77 @@ export function getErrorMessage(result: unknown): string {
   return "An error occurred";
 }
 
+/**
+ * Check if a value is a workspace file reference.
+ */
+function isWorkspaceRef(value: unknown): value is string {
+  return typeof value === "string" && value.startsWith("workspace://");
+}
+
+/**
+ * Check if a workspace reference appears to be an image based on common patterns.
+ * Since workspace refs don't have extensions, we check the context or assume image
+ * for certain block types.
+ */
+function isLikelyImageRef(value: string, outputKey?: string): boolean {
+  if (!isWorkspaceRef(value)) return false;
+
+  // Check output key name for image-related hints
+  const imageKeywords = [
+    "image",
+    "img",
+    "photo",
+    "picture",
+    "thumbnail",
+    "avatar",
+    "icon",
+    "screenshot",
+    "output",
+    "result",
+    "generated",
+  ];
+  if (outputKey) {
+    const lowerKey = outputKey.toLowerCase();
+    if (imageKeywords.some((kw) => lowerKey.includes(kw))) {
+      return true;
+    }
+  }
+
+  // Default to treating workspace refs as potential images
+  // since that's the most common case for generated content
+  return true;
+}
+
+/**
+ * Format a single output value, converting workspace refs to markdown images.
+ */
+function formatOutputValue(value: unknown, outputKey?: string): string {
+  if (isWorkspaceRef(value) && isLikelyImageRef(value, outputKey)) {
+    // Format as markdown image
+    return `![${outputKey || "Generated image"}](${value})`;
+  }
+
+  if (typeof value === "string") {
+    // Check for data URIs (images)
+    if (value.startsWith("data:image/")) {
+      return `![${outputKey || "Generated image"}](${value})`;
+    }
+    return value;
+  }
+
+  if (Array.isArray(value)) {
+    return value
+      .map((item, idx) => formatOutputValue(item, `${outputKey}_${idx}`))
+      .join("\n\n");
+  }
+
+  if (typeof value === "object" && value !== null) {
+    return JSON.stringify(value, null, 2);
+  }
+
+  return String(value);
+}
+
 function getToolCompletionPhrase(toolName: string): string {
   const toolCompletionPhrases: Record<string, string> = {
     add_understanding: "Updated your business information",
@@ -127,10 +198,26 @@ export function formatToolResponse(result: unknown, toolName: string): string {
 
     case "block_output":
       const blockName = (response.block_name as string) || "Block";
-      const outputs = response.outputs as Record<string, unknown> | undefined;
+      const outputs = response.outputs as Record<string, unknown[]> | undefined;
       if (outputs && Object.keys(outputs).length > 0) {
-        const outputKeys = Object.keys(outputs);
-        return `${blockName} executed successfully. Outputs: ${outputKeys.join(", ")}`;
+        const formattedOutputs: string[] = [];
+
+        for (const [key, values] of Object.entries(outputs)) {
+          if (!Array.isArray(values) || values.length === 0) continue;
+
+          // Format each value in the output array
+          for (const value of values) {
+            const formatted = formatOutputValue(value, key);
+            if (formatted) {
+              formattedOutputs.push(formatted);
+            }
+          }
+        }
+
+        if (formattedOutputs.length > 0) {
+          return `${blockName} executed successfully.\n\n${formattedOutputs.join("\n\n")}`;
+        }
+        return `${blockName} executed successfully.`;
       }
       return `${blockName} executed successfully.`;
 

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/useChatSession.ts

@@ -59,6 +59,7 @@ export function useChatSession({
     query: {
       enabled: !!sessionId,
       select: okData,
+      staleTime: 0,
       retry: shouldRetrySessionLoad,
       retryDelay: getSessionRetryDelay,
     },
@@ -102,15 +103,98 @@ export function useChatSession({
     }
   }, [createError, loadError]);
 
+  // Check if there are any pending operations in the messages
+  // Must check all operation types: operation_pending, operation_started, operation_in_progress
+  const hasPendingOperations = 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]);
+
+  // Refresh sessions list when a pending operation completes
+  // (hasPendingOperations transitions from true to false)
+  const prevHasPendingOperationsRef = useRef(hasPendingOperations);
   useEffect(
-    function refreshSessionsListOnLoad() {
-      if (sessionId && sessionData && !isLoadingSession) {
+    function refreshSessionsListOnOperationComplete() {
+      const wasHasPending = prevHasPendingOperationsRef.current;
+      prevHasPendingOperationsRef.current = hasPendingOperations;
+
+      // Only invalidate when transitioning from pending to not pending
+      if (wasHasPending && !hasPendingOperations && sessionId) {
         queryClient.invalidateQueries({
           queryKey: getGetV2ListSessionsQueryKey(),
         });
       }
     },
-    [sessionId, sessionData, isLoadingSession, queryClient],
+    [hasPendingOperations, sessionId, queryClient],
+  );
+
+  // Poll for updates when there are pending operations (long poll - 10s intervals with backoff)
+  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;
+
+      // Calculate delay with exponential backoff: 10s, 15s, 20s, 25s, 30s (max)
+      const baseDelay = 10000;
+      const maxDelay = 30000;
+
+      function schedule() {
+        const delay = Math.min(
+          baseDelay + pollAttemptRef.current * 5000,
+          maxDelay,
+        );
+        timeoutId = setTimeout(async () => {
+          if (cancelled) return;
+          console.info(
+            `[useChatSession] Polling for pending operation updates (attempt ${pollAttemptRef.current + 1})`,
+          );
+          pollAttemptRef.current += 1;
+          try {
+            await refetch();
+          } catch (err) {
+            console.error("[useChatSession] Poll failed:", err);
+          } finally {
+            // Continue polling if still pending and not cancelled
+            if (!cancelled && hasPendingOperationsRef.current) {
+              schedule();
+            }
+          }
+        }, delay);
+      }
+
+      schedule();
+
+      return () => {
+        cancelled = true;
+        if (timeoutId) clearTimeout(timeoutId);
+      };
+    },
+    [sessionId, hasPendingOperations, refetch],
   );
 
   async function createSession() {
@@ -239,6 +323,7 @@ export function useChatSession({
     isCreating,
     error,
     isSessionNotFound: isNotFoundError(loadError),
+    hasPendingOperations,
     createSession,
     loadSession,
     refreshSession,

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

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

backend/blocks/video/__init__.py

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

docs/platform/block-sdk-guide.md

@@ -277,6 +277,50 @@ async def run(
         token = credentials.api_key.get_secret_value()
 ```
 
+### Handling Files
+
+When your block works with files (images, videos, documents), use `store_media_file()`:
+
+```python
+from backend.data.execution import ExecutionContext
+from backend.util.file import store_media_file
+from backend.util.type import MediaFileType
+
+async def run(
+    self,
+    input_data: Input,
+    *,
+    execution_context: ExecutionContext,
+    **kwargs,
+):
+    # PROCESSING: Need local file path for tools like ffmpeg, MoviePy, PIL
+    local_path = await store_media_file(
+        file=input_data.video,
+        execution_context=execution_context,
+        return_format="for_local_processing",
+    )
+
+    # EXTERNAL API: Need base64 content for APIs like Replicate, OpenAI
+    image_b64 = await store_media_file(
+        file=input_data.image,
+        execution_context=execution_context,
+        return_format="for_external_api",
+    )
+
+    # OUTPUT: Return to user/next block (auto-adapts to context)
+    result = await store_media_file(
+        file=generated_url,
+        execution_context=execution_context,
+        return_format="for_block_output",  # workspace:// in CoPilot, data URI in graphs
+    )
+    yield "image_url", result
+```
+
+**Return format options:**
+- `"for_local_processing"` - Local file path for processing tools
+- `"for_external_api"` - Data URI for external APIs needing base64
+- `"for_block_output"` - **Always use for outputs** - automatically picks best format
+
 ## Testing Your Block
 
 ```bash

docs/platform/new_blocks.md

@@ -111,6 +111,71 @@ Follow these steps to create and test a new block:
      - `graph_exec_id`: The ID of the execution of the agent. This changes every time the agent has a new "run"
      - `node_exec_id`: The ID of the execution of the node. This changes every time the node is executed
      - `node_id`: The ID of the node that is being executed. It changes every version of the graph, but not every time the node is executed.
+     - `execution_context`: An `ExecutionContext` object containing user_id, graph_exec_id, workspace_id, and session_id. Required for file handling.
+
+### Handling Files in Blocks
+
+When your block needs to work with files (images, videos, documents), use `store_media_file()` from `backend.util.file`. This function handles downloading, validation, virus scanning, and storage.
+
+**Import:**
+```python
+from backend.data.execution import ExecutionContext
+from backend.util.file import store_media_file
+from backend.util.type import MediaFileType
+```
+
+**The `return_format` parameter determines what you get back:**
+
+| Format | Use When | Returns |
+|--------|----------|---------|
+| `"for_local_processing"` | Processing with local tools (ffmpeg, MoviePy, PIL) | Local file path (e.g., `"image.png"`) |
+| `"for_external_api"` | Sending content to external APIs (Replicate, OpenAI) | Data URI (e.g., `"data:image/png;base64,..."`) |
+| `"for_block_output"` | Returning output from your block | Smart: `workspace://` in CoPilot, data URI in graphs |
+
+**Examples:**
+
+```python
+async def run(
+    self,
+    input_data: Input,
+    *,
+    execution_context: ExecutionContext,
+    **kwargs,
+) -> BlockOutput:
+    # PROCESSING: Need to work with file locally (ffmpeg, MoviePy, PIL)
+    local_path = await store_media_file(
+        file=input_data.video,
+        execution_context=execution_context,
+        return_format="for_local_processing",
+    )
+    # local_path = "video.mp4" - use with Path, ffmpeg, subprocess, etc.
+    full_path = get_exec_file_path(execution_context.graph_exec_id, local_path)
+
+    # EXTERNAL API: Need to send content to an API like Replicate
+    image_b64 = await store_media_file(
+        file=input_data.image,
+        execution_context=execution_context,
+        return_format="for_external_api",
+    )
+    # image_b64 = "data:image/png;base64,iVBORw0..." - send to external API
+
+    # OUTPUT: Returning result from block to user/next block
+    result_url = await store_media_file(
+        file=generated_image_url,
+        execution_context=execution_context,
+        return_format="for_block_output",
+    )
+    yield "image_url", result_url
+    # In CoPilot: result_url = "workspace://abc123" (persistent, context-efficient)
+    # In graphs:  result_url = "data:image/png;base64,..." (for next block/display)
+```
+
+**Key points:**
+
+- `for_block_output` is the **only** format that auto-adapts to execution context
+- Always use `for_block_output` for block outputs unless you have a specific reason not to
+- Never manually check for `workspace_id` - let `for_block_output` handle the logic
+- The function handles URLs, data URIs, `workspace://` references, and local paths as input
 
 ### Field Types