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/.env.default

@@ -178,5 +178,10 @@ AYRSHARE_JWT_KEY=
 SMARTLEAD_API_KEY=
 ZEROBOUNCE_API_KEY=
 
+# PostHog Analytics
+# Get API key from https://posthog.com - Project Settings > Project API Key
+POSTHOG_API_KEY=
+POSTHOG_HOST=https://eu.i.posthog.com
+
 # Other Services
 AUTOMOD_API_KEY=

autogpt_platform/backend/backend/api/external/v1/routes.py

@@ -86,6 +86,8 @@ async def execute_graph_block(
     obj = backend.data.block.get_block(block_id)
     if not obj:
         raise HTTPException(status_code=404, detail=f"Block #{block_id} not found.")
+    if obj.disabled:
+        raise HTTPException(status_code=403, detail=f"Block #{block_id} is disabled.")
 
     output = defaultdict(list)
     async for name, data in obj.execute(data):

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/response_model.py

@@ -31,6 +31,7 @@ class ResponseType(str, Enum):
     # Other
     ERROR = "error"
     USAGE = "usage"
+    HEARTBEAT = "heartbeat"
 
 
 class StreamBaseResponse(BaseModel):
@@ -142,3 +143,20 @@ class StreamError(StreamBaseResponse):
     details: dict[str, Any] | None = Field(
         default=None, description="Additional error details"
     )
+
+
+class StreamHeartbeat(StreamBaseResponse):
+    """Heartbeat to keep SSE connection alive during long-running operations.
+
+    Uses SSE comment format (: comment) which is ignored by clients but keeps
+    the connection alive through proxies and load balancers.
+    """
+
+    type: ResponseType = ResponseType.HEARTBEAT
+    toolCallId: str | None = Field(
+        default=None, description="Tool call ID if heartbeat is for a specific tool"
+    )
+
+    def to_sse(self) -> str:
+        """Convert to SSE comment format to keep connection alive."""
+        return ": heartbeat\n\n"

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

@@ -1,8 +1,10 @@
+import logging
 from typing import TYPE_CHECKING, Any
 
 from openai.types.chat import ChatCompletionToolParam
 
 from backend.api.features.chat.model import ChatSession
+from backend.api.features.chat.tracking import track_tool_called
 
 from .add_understanding import AddUnderstandingTool
 from .agent_output import AgentOutputTool
@@ -16,10 +18,18 @@ 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
 
+logger = logging.getLogger(__name__)
+
 # Single source of truth for all tools
 TOOL_REGISTRY: dict[str, BaseTool] = {
     "add_understanding": AddUnderstandingTool(),
@@ -33,6 +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
@@ -45,6 +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],
@@ -53,7 +73,20 @@ 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")
+
+    # Track tool call in PostHog
+    logger.info(
+        f"Tracking tool call: tool={tool_name}, user={user_id}, "
+        f"session={session.session_id}, call_id={tool_call_id}"
+    )
+    track_tool_called(
+        user_id=user_id,
+        session_id=session.session_id,
+        tool_name=tool_name,
+        tool_call_id=tool_call_id,
+    )
+
     return await tool.execute(user_id, session, tool_call_id, **parameters)

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

@@ -3,8 +3,6 @@
 import logging
 from typing import Any
 
-from langfuse import observe
-
 from backend.api.features.chat.model import ChatSession
 from backend.data.understanding import (
     BusinessUnderstandingInput,
@@ -61,7 +59,6 @@ and automations for the user's specific needs."""
         """Requires authentication to store user-specific data."""
         return True
 
-    @observe(as_type="tool", name="add_understanding")
     async def _execute(
         self,
         user_id: str | None,

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

@@ -5,7 +5,6 @@ import re
 from datetime import datetime, timedelta, timezone
 from typing import Any
 
-from langfuse import observe
 from pydantic import BaseModel, field_validator
 
 from backend.api.features.chat.model import ChatSession
@@ -329,7 +328,6 @@ class AgentOutputTool(BaseTool):
             total_executions=len(available_executions) if available_executions else 1,
         )
 
-    @observe(as_type="tool", name="view_agent_output")
     async def _execute(
         self,
         user_id: str | None,

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

@@ -3,8 +3,6 @@
 import logging
 from typing import Any
 
-from langfuse import observe
-
 from backend.api.features.chat.model import ChatSession
 
 from .agent_generator import (
@@ -44,6 +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 {
@@ -75,7 +77,6 @@ class CreateAgentTool(BaseTool):
             "required": ["description"],
         }
 
-    @observe(as_type="tool", name="create_agent")
     async def _execute(
         self,
         user_id: str | None,
@@ -116,8 +117,11 @@ class CreateAgentTool(BaseTool):
 
         if decomposition_result is None:
             return ErrorResponse(
-                message="Failed to analyze the goal. Please try rephrasing.",
-                error="Decomposition failed",
+                message="Failed to analyze the goal. The agent generation service may be unavailable or timed out. Please try again.",
+                error="decomposition_failed",
+                details={
+                    "description": description[:100]
+                },  # Include context for debugging
                 session_id=session_id,
             )
 
@@ -182,8 +186,11 @@ class CreateAgentTool(BaseTool):
 
         if agent_json is None:
             return ErrorResponse(
-                message="Failed to generate the agent. Please try again.",
-                error="Generation failed",
+                message="Failed to generate the agent. The agent generation service may be unavailable or timed out. Please try again.",
+                error="generation_failed",
+                details={
+                    "description": description[:100]
+                },  # Include context for debugging
                 session_id=session_id,
             )
 

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

@@ -3,8 +3,6 @@
 import logging
 from typing import Any
 
-from langfuse import observe
-
 from backend.api.features.chat.model import ChatSession
 
 from .agent_generator import (
@@ -44,6 +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 {
@@ -81,7 +83,6 @@ class EditAgentTool(BaseTool):
             "required": ["agent_id", "changes"],
         }
 
-    @observe(as_type="tool", name="edit_agent")
     async def _execute(
         self,
         user_id: str | None,
@@ -145,8 +146,9 @@ class EditAgentTool(BaseTool):
 
         if result is None:
             return ErrorResponse(
-                message="Failed to generate changes. Please try rephrasing.",
-                error="Update generation failed",
+                message="Failed to generate changes. The agent generation service may be unavailable or timed out. Please try again.",
+                error="update_generation_failed",
+                details={"agent_id": agent_id, "changes": changes[:100]},
                 session_id=session_id,
             )
 

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

@@ -2,8 +2,6 @@
 
 from typing import Any
 
-from langfuse import observe
-
 from backend.api.features.chat.model import ChatSession
 
 from .agent_search import search_agents
@@ -37,7 +35,6 @@ class FindAgentTool(BaseTool):
             "required": ["query"],
         }
 
-    @observe(as_type="tool", name="find_agent")
     async def _execute(
         self, user_id: str | None, session: ChatSession, **kwargs
     ) -> ToolResponseBase:

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

@@ -1,7 +1,6 @@
 import logging
 from typing import Any
 
-from langfuse import observe
 from prisma.enums import ContentType
 
 from backend.api.features.chat.model import ChatSession
@@ -56,7 +55,6 @@ class FindBlockTool(BaseTool):
     def requires_auth(self) -> bool:
         return True
 
-    @observe(as_type="tool", name="find_block")
     async def _execute(
         self,
         user_id: str | None,
@@ -109,7 +107,8 @@ class FindBlockTool(BaseTool):
                 block_id = result["content_id"]
                 block = get_block(block_id)
 
-                if block:
+                # Skip disabled blocks
+                if block and not block.disabled:
                     # Get input/output schemas
                     input_schema = {}
                     output_schema = {}

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

@@ -2,8 +2,6 @@
 
 from typing import Any
 
-from langfuse import observe
-
 from backend.api.features.chat.model import ChatSession
 
 from .agent_search import search_agents
@@ -43,7 +41,6 @@ class FindLibraryAgentTool(BaseTool):
     def requires_auth(self) -> bool:
         return True
 
-    @observe(as_type="tool", name="find_library_agent")
     async def _execute(
         self, user_id: str | None, session: ChatSession, **kwargs
     ) -> ToolResponseBase:

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

@@ -4,8 +4,6 @@ import logging
 from pathlib import Path
 from typing import Any
 
-from langfuse import observe
-
 from backend.api.features.chat.model import ChatSession
 from backend.api.features.chat.tools.base import BaseTool
 from backend.api.features.chat.tools.models import (
@@ -73,7 +71,6 @@ class GetDocPageTool(BaseTool):
         url_path = path.rsplit(".", 1)[0] if "." in path else path
         return f"{DOCS_BASE_URL}/{url_path}"
 
-    @observe(as_type="tool", name="get_doc_page")
     async def _execute(
         self,
         user_id: str | None,

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_agent.py

@@ -3,11 +3,14 @@
 import logging
 from typing import Any
 
-from langfuse import observe
 from pydantic import BaseModel, Field, field_validator
 
 from backend.api.features.chat.config import ChatConfig
 from backend.api.features.chat.model import ChatSession
+from backend.api.features.chat.tracking import (
+    track_agent_run_success,
+    track_agent_scheduled,
+)
 from backend.api.features.library import db as library_db
 from backend.data.graph import GraphModel
 from backend.data.model import CredentialsMetaInput
@@ -155,7 +158,6 @@ class RunAgentTool(BaseTool):
         """All operations require authentication."""
         return True
 
-    @observe(as_type="tool", name="run_agent")
     async def _execute(
         self,
         user_id: str | None,
@@ -453,6 +455,16 @@ class RunAgentTool(BaseTool):
             session.successful_agent_runs.get(library_agent.graph_id, 0) + 1
         )
 
+        # Track in PostHog
+        track_agent_run_success(
+            user_id=user_id,
+            session_id=session_id,
+            graph_id=library_agent.graph_id,
+            graph_name=library_agent.name,
+            execution_id=execution.id,
+            library_agent_id=library_agent.id,
+        )
+
         library_agent_link = f"/library/agents/{library_agent.id}"
         return ExecutionStartedResponse(
             message=(
@@ -534,6 +546,18 @@ class RunAgentTool(BaseTool):
             session.successful_agent_schedules.get(library_agent.graph_id, 0) + 1
         )
 
+        # Track in PostHog
+        track_agent_scheduled(
+            user_id=user_id,
+            session_id=session_id,
+            graph_id=library_agent.graph_id,
+            graph_name=library_agent.name,
+            schedule_id=result.id,
+            schedule_name=schedule_name,
+            cron=cron,
+            library_agent_id=library_agent.id,
+        )
+
         library_agent_link = f"/library/agents/{library_agent.id}"
         return ExecutionStartedResponse(
             message=(

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

@@ -1,15 +1,15 @@
 """Tool for executing blocks directly."""
 
 import logging
+import uuid
 from collections import defaultdict
 from typing import Any
 
-from langfuse import observe
-
 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
 
@@ -130,7 +130,6 @@ class RunBlockTool(BaseTool):
 
         return matched_credentials, missing_credentials
 
-    @observe(as_type="tool", name="run_block")
     async def _execute(
         self,
         user_id: str | None,
@@ -179,6 +178,11 @@ class RunBlockTool(BaseTool):
                 message=f"Block '{block_id}' not found",
                 session_id=session_id,
             )
+        if block.disabled:
+            return ErrorResponse(
+                message=f"Block '{block_id}' is disabled",
+                session_id=session_id,
+            )
 
         logger.info(f"Executing block {block.name} ({block_id}) for user {user_id}")
 
@@ -221,11 +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/search_docs.py

@@ -3,7 +3,6 @@
 import logging
 from typing import Any
 
-from langfuse import observe
 from prisma.enums import ContentType
 
 from backend.api.features.chat.model import ChatSession
@@ -88,7 +87,6 @@ class SearchDocsTool(BaseTool):
         url_path = path.rsplit(".", 1)[0] if "." in path else path
         return f"{DOCS_BASE_URL}/{url_path}"
 
-    @observe(as_type="tool", name="search_docs")
     async def _execute(
         self,
         user_id: str | None,

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/chat/tracking.py

@@ -0,0 +1,250 @@
+"""PostHog analytics tracking for the chat system."""
+
+import atexit
+import logging
+from typing import Any
+
+from posthog import Posthog
+
+from backend.util.settings import Settings
+
+logger = logging.getLogger(__name__)
+settings = Settings()
+
+# PostHog client instance (lazily initialized)
+_posthog_client: Posthog | None = None
+
+
+def _shutdown_posthog() -> None:
+    """Flush and shutdown PostHog client on process exit."""
+    if _posthog_client is not None:
+        _posthog_client.flush()
+        _posthog_client.shutdown()
+
+
+atexit.register(_shutdown_posthog)
+
+
+def _get_posthog_client() -> Posthog | None:
+    """Get or create the PostHog client instance."""
+    global _posthog_client
+    if _posthog_client is not None:
+        return _posthog_client
+
+    if not settings.secrets.posthog_api_key:
+        logger.debug("PostHog API key not configured, analytics disabled")
+        return None
+
+    _posthog_client = Posthog(
+        settings.secrets.posthog_api_key,
+        host=settings.secrets.posthog_host,
+    )
+    logger.info(
+        f"PostHog client initialized with host: {settings.secrets.posthog_host}"
+    )
+    return _posthog_client
+
+
+def _get_base_properties() -> dict[str, Any]:
+    """Get base properties included in all events."""
+    return {
+        "environment": settings.config.app_env.value,
+        "source": "chat_copilot",
+    }
+
+
+def track_user_message(
+    user_id: str | None,
+    session_id: str,
+    message_length: int,
+) -> None:
+    """Track when a user sends a message in chat.
+
+    Args:
+        user_id: The user's ID (or None for anonymous)
+        session_id: The chat session ID
+        message_length: Length of the user's message
+    """
+    client = _get_posthog_client()
+    if not client:
+        return
+
+    try:
+        properties = {
+            **_get_base_properties(),
+            "session_id": session_id,
+            "message_length": message_length,
+        }
+        client.capture(
+            distinct_id=user_id or f"anonymous_{session_id}",
+            event="copilot_message_sent",
+            properties=properties,
+        )
+    except Exception as e:
+        logger.warning(f"Failed to track user message: {e}")
+
+
+def track_tool_called(
+    user_id: str | None,
+    session_id: str,
+    tool_name: str,
+    tool_call_id: str,
+) -> None:
+    """Track when a tool is called in chat.
+
+    Args:
+        user_id: The user's ID (or None for anonymous)
+        session_id: The chat session ID
+        tool_name: Name of the tool being called
+        tool_call_id: Unique ID of the tool call
+    """
+    client = _get_posthog_client()
+    if not client:
+        logger.info("PostHog client not available for tool tracking")
+        return
+
+    try:
+        properties = {
+            **_get_base_properties(),
+            "session_id": session_id,
+            "tool_name": tool_name,
+            "tool_call_id": tool_call_id,
+        }
+        distinct_id = user_id or f"anonymous_{session_id}"
+        logger.info(
+            f"Sending copilot_tool_called event to PostHog: distinct_id={distinct_id}, "
+            f"tool_name={tool_name}"
+        )
+        client.capture(
+            distinct_id=distinct_id,
+            event="copilot_tool_called",
+            properties=properties,
+        )
+    except Exception as e:
+        logger.warning(f"Failed to track tool call: {e}")
+
+
+def track_agent_run_success(
+    user_id: str,
+    session_id: str,
+    graph_id: str,
+    graph_name: str,
+    execution_id: str,
+    library_agent_id: str,
+) -> None:
+    """Track when an agent is successfully run.
+
+    Args:
+        user_id: The user's ID
+        session_id: The chat session ID
+        graph_id: ID of the agent graph
+        graph_name: Name of the agent
+        execution_id: ID of the execution
+        library_agent_id: ID of the library agent
+    """
+    client = _get_posthog_client()
+    if not client:
+        return
+
+    try:
+        properties = {
+            **_get_base_properties(),
+            "session_id": session_id,
+            "graph_id": graph_id,
+            "graph_name": graph_name,
+            "execution_id": execution_id,
+            "library_agent_id": library_agent_id,
+        }
+        client.capture(
+            distinct_id=user_id,
+            event="copilot_agent_run_success",
+            properties=properties,
+        )
+    except Exception as e:
+        logger.warning(f"Failed to track agent run: {e}")
+
+
+def track_agent_scheduled(
+    user_id: str,
+    session_id: str,
+    graph_id: str,
+    graph_name: str,
+    schedule_id: str,
+    schedule_name: str,
+    cron: str,
+    library_agent_id: str,
+) -> None:
+    """Track when an agent is successfully scheduled.
+
+    Args:
+        user_id: The user's ID
+        session_id: The chat session ID
+        graph_id: ID of the agent graph
+        graph_name: Name of the agent
+        schedule_id: ID of the schedule
+        schedule_name: Name of the schedule
+        cron: Cron expression for the schedule
+        library_agent_id: ID of the library agent
+    """
+    client = _get_posthog_client()
+    if not client:
+        return
+
+    try:
+        properties = {
+            **_get_base_properties(),
+            "session_id": session_id,
+            "graph_id": graph_id,
+            "graph_name": graph_name,
+            "schedule_id": schedule_id,
+            "schedule_name": schedule_name,
+            "cron": cron,
+            "library_agent_id": library_agent_id,
+        }
+        client.capture(
+            distinct_id=user_id,
+            event="copilot_agent_scheduled",
+            properties=properties,
+        )
+    except Exception as e:
+        logger.warning(f"Failed to track agent schedule: {e}")
+
+
+def track_trigger_setup(
+    user_id: str,
+    session_id: str,
+    graph_id: str,
+    graph_name: str,
+    trigger_type: str,
+    library_agent_id: str,
+) -> None:
+    """Track when a trigger is set up for an agent.
+
+    Args:
+        user_id: The user's ID
+        session_id: The chat session ID
+        graph_id: ID of the agent graph
+        graph_name: Name of the agent
+        trigger_type: Type of trigger (e.g., 'webhook')
+        library_agent_id: ID of the library agent
+    """
+    client = _get_posthog_client()
+    if not client:
+        return
+
+    try:
+        properties = {
+            **_get_base_properties(),
+            "session_id": session_id,
+            "graph_id": graph_id,
+            "graph_name": graph_name,
+            "trigger_type": trigger_type,
+            "library_agent_id": library_agent_id,
+        }
+        client.capture(
+            distinct_id=user_id,
+            event="copilot_trigger_setup",
+            properties=properties,
+        )
+    except Exception as e:
+        logger.warning(f"Failed to track trigger setup: {e}")

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

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

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

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

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

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

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

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

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

@@ -364,6 +364,8 @@ async def execute_graph_block(
     obj = get_block(block_id)
     if not obj:
         raise HTTPException(status_code=404, detail=f"Block #{block_id} not found.")
+    if obj.disabled:
+        raise HTTPException(status_code=403, detail=f"Block #{block_id} is disabled.")
 
     user = await get_user_by_id(user_id)
     if not user:

autogpt_platform/backend/backend/api/features/v1_test.py

@@ -138,6 +138,7 @@ def test_execute_graph_block(
     """Test execute block endpoint"""
     # Mock block
     mock_block = Mock()
+    mock_block.disabled = False
 
     async def mock_execute(*args, **kwargs):
         yield "output1", {"data": "result1"}

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/human_review.py

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

autogpt_platform/backend/backend/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(
@@ -679,6 +685,12 @@ class Secrets(UpdateTrackingModel["Secrets"], BaseSettings):
         default="https://cloud.langfuse.com", description="Langfuse host URL"
     )
 
+    # PostHog analytics
+    posthog_api_key: str = Field(default="", description="PostHog API key")
+    posthog_host: str = Field(
+        default="https://eu.i.posthog.com", description="PostHog host URL"
+    )
+
     # Add more secret fields as needed
     model_config = SettingsConfigDict(
         env_file=".env",

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/poetry.lock

@@ -4204,14 +4204,14 @@ strenum = {version = ">=0.4.9,<0.5.0", markers = "python_version < \"3.11\""}
 
 [[package]]
 name = "posthog"
-version = "6.1.1"
+version = "7.6.0"
 description = "Integrate PostHog into any python application."
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "posthog-6.1.1-py3-none-any.whl", hash = "sha256:329fd3d06b4d54cec925f47235bd8e327c91403c2f9ec38f1deb849535934dba"},
-    {file = "posthog-6.1.1.tar.gz", hash = "sha256:b453f54c4a2589da859fd575dd3bf86fcb40580727ec399535f268b1b9f318b8"},
+    {file = "posthog-7.6.0-py3-none-any.whl", hash = "sha256:c4dd78cf77c4fecceb965f86066e5ac37886ef867d68ffe75a1db5d681d7d9ad"},
+    {file = "posthog-7.6.0.tar.gz", hash = "sha256:941dfd278ee427c9b14640f09b35b5bb52a71bdf028d7dbb7307e1838fd3002e"},
 ]
 
 [package.dependencies]
@@ -4225,7 +4225,7 @@ typing-extensions = ">=4.2.0"
 [package.extras]
 dev = ["django-stubs", "lxml", "mypy", "mypy-baseline", "packaging", "pre-commit", "pydantic", "ruff", "setuptools", "tomli", "tomli_w", "twine", "types-mock", "types-python-dateutil", "types-requests", "types-setuptools", "types-six", "wheel"]
 langchain = ["langchain (>=0.2.0)"]
-test = ["anthropic", "coverage", "django", "freezegun (==1.5.1)", "google-genai", "langchain-anthropic (>=0.3.15)", "langchain-community (>=0.3.25)", "langchain-core (>=0.3.65)", "langchain-openai (>=0.3.22)", "langgraph (>=0.4.8)", "mock (>=2.0.0)", "openai", "parameterized (>=0.8.1)", "pydantic", "pytest", "pytest-asyncio", "pytest-timeout"]
+test = ["anthropic (>=0.72)", "coverage", "django", "freezegun (==1.5.1)", "google-genai", "langchain-anthropic (>=1.0)", "langchain-community (>=0.4)", "langchain-core (>=1.0)", "langchain-openai (>=1.0)", "langgraph (>=1.0)", "mock (>=2.0.0)", "openai (>=2.0)", "parameterized (>=0.8.1)", "pydantic", "pytest", "pytest-asyncio", "pytest-timeout"]
 
 [[package]]
 name = "postmarker"
@@ -7512,4 +7512,4 @@ cffi = ["cffi (>=1.11)"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<3.14"
-content-hash = "18b92e09596298c82432e4d0a85cb6d80a40b4229bee0a0c15f0529fd6cb21a4"
+content-hash = "ee5742dc1a9df50dfc06d4b26a1682cbb2b25cab6b79ce5625ec272f93e4f4bf"

autogpt_platform/backend/pyproject.toml

@@ -85,6 +85,7 @@ exa-py = "^1.14.20"
 croniter = "^6.0.0"
 stagehand = "^0.5.1"
 gravitas-md2gdocs = "^0.1.0"
+posthog = "^7.6.0"
 
 [tool.poetry.group.dev.dependencies]
 aiohappyeyeballs = "^2.6.1"

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/.env.default

@@ -30,3 +30,7 @@ NEXT_PUBLIC_TURNSTILE=disabled
 
 # PR previews
 NEXT_PUBLIC_PREVIEW_STEALING_DEV=
+
+# PostHog Analytics
+NEXT_PUBLIC_POSTHOG_KEY=
+NEXT_PUBLIC_POSTHOG_HOST=https://eu.i.posthog.com

autogpt_platform/frontend/package.json

@@ -34,6 +34,7 @@
     "@hookform/resolvers": "5.2.2",
     "@next/third-parties": "15.4.6",
     "@phosphor-icons/react": "2.1.10",
+    "@posthog/react": "1.7.0",
     "@radix-ui/react-accordion": "1.2.12",
     "@radix-ui/react-alert-dialog": "1.1.15",
     "@radix-ui/react-avatar": "1.1.10",
@@ -91,6 +92,7 @@
     "next-themes": "0.4.6",
     "nuqs": "2.7.2",
     "party-js": "2.2.0",
+    "posthog-js": "1.334.1",
     "react": "18.3.1",
     "react-currency-input-field": "4.0.3",
     "react-day-picker": "9.11.1",
@@ -120,7 +122,6 @@
   },
   "devDependencies": {
     "@chromatic-com/storybook": "4.1.2",
-    "happy-dom": "20.3.4",
     "@opentelemetry/instrumentation": "0.209.0",
     "@playwright/test": "1.56.1",
     "@storybook/addon-a11y": "9.1.5",
@@ -148,6 +149,7 @@
     "eslint": "8.57.1",
     "eslint-config-next": "15.5.7",
     "eslint-plugin-storybook": "9.1.5",
+    "happy-dom": "20.3.4",
     "import-in-the-middle": "2.0.2",
     "msw": "2.11.6",
     "msw-storybook-addon": "2.0.6",

autogpt_platform/frontend/pnpm-lock.yaml

@@ -23,6 +23,9 @@ importers:
       '@phosphor-icons/react':
         specifier: 2.1.10
         version: 2.1.10(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
+      '@posthog/react':
+        specifier: 1.7.0
+        version: 1.7.0(@types/react@18.3.17)(posthog-js@1.334.1)(react@18.3.1)
       '@radix-ui/react-accordion':
         specifier: 1.2.12
         version: 1.2.12(@types/react-dom@18.3.5(@types/react@18.3.17))(@types/react@18.3.17)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
@@ -194,6 +197,9 @@ importers:
       party-js:
         specifier: 2.2.0
         version: 2.2.0
+      posthog-js:
+        specifier: 1.334.1
+        version: 1.334.1
       react:
         specifier: 18.3.1
         version: 18.3.1
@@ -1794,6 +1800,10 @@ packages:
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+  '@opentelemetry/api-logs@0.208.0':
+    resolution: {integrity: sha512-CjruKY9V6NMssL/T1kAFgzosF1v9o6oeN+aX5JB/C/xPNtmgIJqcXHG7fA82Ou1zCpWGl4lROQUKwUNE1pMCyg==}
+    engines: {node: '>=8.0.0'}
+
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     resolution: {integrity: sha512-xomnUNi7TiAGtOgs0tb54LyrjRZLu9shJGGwkcN7NgtiPYOpNnKLkRJtzZvTjD/w6knSZH9sFZcUSUovYOPg6A==}
     engines: {node: '>=8.0.0'}
@@ -1814,6 +1824,12 @@ packages:
     peerDependencies:
       '@opentelemetry/api': '>=1.0.0 <1.10.0'
 
+  '@opentelemetry/exporter-logs-otlp-http@0.208.0':
+    resolution: {integrity: sha512-jOv40Bs9jy9bZVLo/i8FwUiuCvbjWDI+ZW13wimJm4LjnlwJxGgB+N/VWOZUTpM+ah/awXeQqKdNlpLf2EjvYg==}
+    engines: {node: ^18.19.0 || >=20.6.0}
+    peerDependencies:
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+
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     resolution: {integrity: sha512-5ULoU8p+tWcQw5PDYZn8rySptGSLZHNX/7srqo2TioPnAAcvTy6sQFQXsNPrAnyRRtYGMetXVyZUy5OaX1+IfA==}
     engines: {node: ^18.19.0 || >=20.6.0}
@@ -1952,6 +1968,18 @@ packages:
     peerDependencies:
       '@opentelemetry/api': ^1.3.0
 
+  '@opentelemetry/otlp-exporter-base@0.208.0':
+    resolution: {integrity: sha512-gMd39gIfVb2OgxldxUtOwGJYSH8P1kVFFlJLuut32L6KgUC4gl1dMhn+YC2mGn0bDOiQYSk/uHOdSjuKp58vvA==}
+    engines: {node: ^18.19.0 || >=20.6.0}
+    peerDependencies:
+      '@opentelemetry/api': ^1.3.0
+
+  '@opentelemetry/otlp-transformer@0.208.0':
+    resolution: {integrity: sha512-DCFPY8C6lAQHUNkzcNT9R+qYExvsk6C5Bto2pbNxgicpcSWbe2WHShLxkOxIdNcBiYPdVHv/e7vH7K6TI+C+fQ==}
+    engines: {node: ^18.19.0 || >=20.6.0}
+    peerDependencies:
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+
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@@ -1962,6 +1990,18 @@ packages:
     peerDependencies:
       '@opentelemetry/api': '>=1.3.0 <1.10.0'
 
+  '@opentelemetry/sdk-logs@0.208.0':
+    resolution: {integrity: sha512-QlAyL1jRpOeaqx7/leG1vJMp84g0xKP6gJmfELBpnI4O/9xPX+Hu5m1POk9Kl+veNkyth5t19hRlN6tNY1sjbA==}
+    engines: {node: ^18.19.0 || >=20.6.0}
+    peerDependencies:
+      '@opentelemetry/api': '>=1.4.0 <1.10.0'
+
+  '@opentelemetry/sdk-metrics@2.2.0':
+    resolution: {integrity: sha512-G5KYP6+VJMZzpGipQw7Giif48h6SGQ2PFKEYCybeXJsOCB4fp8azqMAAzE5lnnHK3ZVwYQrgmFbsUJO/zOnwGw==}
+    engines: {node: ^18.19.0 || >=20.6.0}
+    peerDependencies:
+      '@opentelemetry/api': '>=1.9.0 <1.10.0'
+
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     resolution: {integrity: sha512-xWQgL0Bmctsalg6PaXExmzdedSp3gyKV8mQBwK/j9VGdCDu2fmXIb2gAehBKbkXCpJ4HPkgv3QfoJWRT4dHWbw==}
     engines: {node: ^18.19.0 || >=20.6.0}
@@ -2050,11 +2090,57 @@ packages:
       webpack-plugin-serve:
         optional: true
 
+  '@posthog/core@1.13.0':
+    resolution: {integrity: sha512-knjncrk7qRmssFRbGzBl1Tunt21GRpe0Wv+uVelyL0Rh7PdQUsgguulzXFTps8hA6wPwTU4kq85qnbAJ3eH6Wg==}
+
+  '@posthog/react@1.7.0':
+    resolution: {integrity: sha512-pM7GL7z/rKjiIwosbRiQA3buhLI6vUo+wg+T/ZrVZC7O5bVU07TfgNZTcuOj8E9dx7vDbfNrc1kjDN7PKMM8ug==}
+    peerDependencies:
+      '@types/react': '>=16.8.0'
+      posthog-js: '>=1.257.2'
+      react: '>=16.8.0'
+    peerDependenciesMeta:
+      '@types/react':
+        optional: true
+
+  '@posthog/types@1.334.1':
+    resolution: {integrity: sha512-ypFnwTO7qbV7icylLbujbamPdQXbJq0a61GUUBnJAeTbBw/qYPIss5IRYICcbCj0uunQrwD7/CGxVb5TOYKWgA==}
+
   '@prisma/instrumentation@6.19.0':
     resolution: {integrity: sha512-QcuYy25pkXM8BJ37wVFBO7Zh34nyRV1GOb2n3lPkkbRYfl4hWl3PTcImP41P0KrzVXfa/45p6eVCos27x3exIg==}
     peerDependencies:
       '@opentelemetry/api': ^1.8
 
+  '@protobufjs/aspromise@1.1.2':
+    resolution: {integrity: sha512-j+gKExEuLmKwvz3OgROXtrJ2UG2x8Ch2YZUxahh+s1F2HZ+wAceUNLkvy6zKCPVRkU++ZWQrdxsUeQXmcg4uoQ==}
+
+  '@protobufjs/base64@1.1.2':
+    resolution: {integrity: sha512-AZkcAA5vnN/v4PDqKyMR5lx7hZttPDgClv83E//FMNhR2TMcLUhfRUBHCmSl0oi9zMgDDqRUJkSxO3wm85+XLg==}
+
+  '@protobufjs/codegen@2.0.4':
+    resolution: {integrity: sha512-YyFaikqM5sH0ziFZCN3xDC7zeGaB/d0IUb9CATugHWbd1FRFwWwt4ld4OYMPWu5a3Xe01mGAULCdqhMlPl29Jg==}
+
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+
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+  '@protobufjs/inquire@1.1.0':
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+
+  '@protobufjs/path@1.1.2':
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+
+  '@protobufjs/pool@1.1.0':
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+
+  '@protobufjs/utf8@1.1.0':
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+
   '@radix-ui/number@1.1.1':
     resolution: {integrity: sha512-MkKCwxlXTgz6CFoJx3pCwn07GKp36+aZyu/u2Ln2VrA5DcdyCZkASEDBTd8x5whTQQL5CiYf4prXKLcgQdv29g==}
 
@@ -3401,6 +3487,9 @@ packages:
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+  '@types/trusted-types@2.0.7':
+    resolution: {integrity: sha512-ScaPdn1dQczgbl0QFTeTOmVHFULt394XJgOQNoyVhZ6r2vLnMLJfBPd53SB52T/3G36VI1/g2MZaX0cwDuXsfw==}
+
   '@types/unist@2.0.11':
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@@ -4278,6 +4367,9 @@ packages:
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+  core-js@3.48.0:
+    resolution: {integrity: sha512-zpEHTy1fjTMZCKLHUZoVeylt9XrzaIN2rbPXEt0k+q7JE5CkCZdo6bNq55bn24a69CH7ErAVLKijxJja4fw+UQ==}
+
   core-util-is@1.0.3:
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@@ -4569,6 +4661,9 @@ packages:
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     engines: {node: '>= 4'}
 
+  dompurify@3.3.1:
+    resolution: {integrity: sha512-qkdCKzLNtrgPFP1Vo+98FRzJnBRGe4ffyCea9IwHB1fyxPOeNTHpLKYGd4Uk9xvNoH0ZoOjwZxNptyMwqrId1Q==}
+
   domutils@2.8.0:
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@@ -4939,6 +5034,9 @@ packages:
       picomatch:
         optional: true
 
+  fflate@0.4.8:
+    resolution: {integrity: sha512-FJqqoDBR00Mdj9ppamLa/Y7vxm+PRmNWA67N846RvsoYVMKB4q3y/de5PA7gUmRMYK/8CMz2GDZQmCRN1wBcWA==}
+
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     engines: {node: '>= 0.6.0'}
 
+  long@5.3.2:
+    resolution: {integrity: sha512-mNAgZ1GmyNhD7AuqnTG3/VQ26o760+ZYBPKjPvugO8+nLbYfX6TVpJPseBvopbdY+qpZ/lKUnmEc1LeZYS3QAA==}
+
   longest-streak@3.1.0:
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@@ -6534,6 +6635,12 @@ packages:
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     engines: {node: '>=0.10.0'}
 
+  posthog-js@1.334.1:
+    resolution: {integrity: sha512-5cDzLICr2afnwX/cR9fwoLC0vN0Nb5gP5HiCigzHkgHdO+E3WsYefla3EFMQz7U4r01CBPZ+nZ9/srkzeACxtQ==}
+
+  preact@10.28.2:
+    resolution: {integrity: sha512-lbteaWGzGHdlIuiJ0l2Jq454m6kcpI1zNje6d8MlGAFlYvP2GO4ibnat7P74Esfz4sPTdM6UxtTwh/d3pwM9JA==}
+
   prelude-ls@1.2.1:
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@@ -6622,6 +6729,10 @@ packages:
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+  protobufjs@7.5.4:
+    resolution: {integrity: sha512-CvexbZtbov6jW2eXAvLukXjXUW1TzFaivC46BpWc/3BpcCysb5Vffu+B3XHMm8lVEuy2Mm4XGex8hBSg1yapPg==}
+    engines: {node: '>=12.0.0'}
+
   proxy-from-env@1.1.0:
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@@ -6643,6 +6754,9 @@ packages:
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     engines: {node: '>=0.6'}
 
+  query-selector-shadow-dom@1.0.1:
+    resolution: {integrity: sha512-lT5yCqEBgfoMYpf3F2xQRK7zEr1rhIIZuceDK6+xRkJQ4NMbHTwXqk4NkwDwQMNqXgG9r9fyHnzwNVs6zV5KRw==}
+
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@@ -7821,6 +7935,9 @@ packages:
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+  web-vitals@5.1.0:
+    resolution: {integrity: sha512-ArI3kx5jI0atlTtmV0fWU3fjpLmq/nD3Zr1iFFlJLaqa5wLBkUSzINwBPySCX/8jRyjlmy1Volw1kz1g9XE4Jg==}
+
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@@ -9420,6 +9537,10 @@ snapshots:
 
   '@open-draft/until@2.1.0': {}
 
+  '@opentelemetry/api-logs@0.208.0':
+    dependencies:
+      '@opentelemetry/api': 1.9.0
+
   '@opentelemetry/api-logs@0.209.0':
     dependencies:
       '@opentelemetry/api': 1.9.0
@@ -9435,6 +9556,15 @@ snapshots:
       '@opentelemetry/api': 1.9.0
       '@opentelemetry/semantic-conventions': 1.38.0
 
+  '@opentelemetry/exporter-logs-otlp-http@0.208.0(@opentelemetry/api@1.9.0)':
+    dependencies:
+      '@opentelemetry/api': 1.9.0
+      '@opentelemetry/api-logs': 0.208.0
+      '@opentelemetry/core': 2.2.0(@opentelemetry/api@1.9.0)
+      '@opentelemetry/otlp-exporter-base': 0.208.0(@opentelemetry/api@1.9.0)
+      '@opentelemetry/otlp-transformer': 0.208.0(@opentelemetry/api@1.9.0)
+      '@opentelemetry/sdk-logs': 0.208.0(@opentelemetry/api@1.9.0)
+
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     dependencies:
       '@opentelemetry/api': 1.9.0
@@ -9629,6 +9759,23 @@ snapshots:
     transitivePeerDependencies:
       - supports-color
 
+  '@opentelemetry/otlp-exporter-base@0.208.0(@opentelemetry/api@1.9.0)':
+    dependencies:
+      '@opentelemetry/api': 1.9.0
+      '@opentelemetry/core': 2.2.0(@opentelemetry/api@1.9.0)
+      '@opentelemetry/otlp-transformer': 0.208.0(@opentelemetry/api@1.9.0)
+
+  '@opentelemetry/otlp-transformer@0.208.0(@opentelemetry/api@1.9.0)':
+    dependencies:
+      '@opentelemetry/api': 1.9.0
+      '@opentelemetry/api-logs': 0.208.0
+      '@opentelemetry/core': 2.2.0(@opentelemetry/api@1.9.0)
+      '@opentelemetry/resources': 2.2.0(@opentelemetry/api@1.9.0)
+      '@opentelemetry/sdk-logs': 0.208.0(@opentelemetry/api@1.9.0)
+      '@opentelemetry/sdk-metrics': 2.2.0(@opentelemetry/api@1.9.0)
+      '@opentelemetry/sdk-trace-base': 2.2.0(@opentelemetry/api@1.9.0)
+      protobufjs: 7.5.4
+
   '@opentelemetry/redis-common@0.38.2': {}
 
   '@opentelemetry/resources@2.2.0(@opentelemetry/api@1.9.0)':
@@ -9637,6 +9784,19 @@ snapshots:
       '@opentelemetry/core': 2.2.0(@opentelemetry/api@1.9.0)
       '@opentelemetry/semantic-conventions': 1.38.0
 
+  '@opentelemetry/sdk-logs@0.208.0(@opentelemetry/api@1.9.0)':
+    dependencies:
+      '@opentelemetry/api': 1.9.0
+      '@opentelemetry/api-logs': 0.208.0
+      '@opentelemetry/core': 2.2.0(@opentelemetry/api@1.9.0)
+      '@opentelemetry/resources': 2.2.0(@opentelemetry/api@1.9.0)
+
+  '@opentelemetry/sdk-metrics@2.2.0(@opentelemetry/api@1.9.0)':
+    dependencies:
+      '@opentelemetry/api': 1.9.0
+      '@opentelemetry/core': 2.2.0(@opentelemetry/api@1.9.0)
+      '@opentelemetry/resources': 2.2.0(@opentelemetry/api@1.9.0)
+
   '@opentelemetry/sdk-trace-base@2.2.0(@opentelemetry/api@1.9.0)':
     dependencies:
       '@opentelemetry/api': 1.9.0
@@ -9801,6 +9961,19 @@ snapshots:
       type-fest: 4.41.0
       webpack-hot-middleware: 2.26.1
 
+  '@posthog/core@1.13.0':
+    dependencies:
+      cross-spawn: 7.0.6
+
+  '@posthog/react@1.7.0(@types/react@18.3.17)(posthog-js@1.334.1)(react@18.3.1)':
+    dependencies:
+      posthog-js: 1.334.1
+      react: 18.3.1
+    optionalDependencies:
+      '@types/react': 18.3.17
+
+  '@posthog/types@1.334.1': {}
+
   '@prisma/instrumentation@6.19.0(@opentelemetry/api@1.9.0)':
     dependencies:
       '@opentelemetry/api': 1.9.0
@@ -9808,6 +9981,29 @@ snapshots:
     transitivePeerDependencies:
       - supports-color
 
+  '@protobufjs/aspromise@1.1.2': {}
+
+  '@protobufjs/base64@1.1.2': {}
+
+  '@protobufjs/codegen@2.0.4': {}
+
+  '@protobufjs/eventemitter@1.1.0': {}
+
+  '@protobufjs/fetch@1.1.0':
+    dependencies:
+      '@protobufjs/aspromise': 1.1.2
+      '@protobufjs/inquire': 1.1.0
+
+  '@protobufjs/float@1.0.2': {}
+
+  '@protobufjs/inquire@1.1.0': {}
+
+  '@protobufjs/path@1.1.2': {}
+
+  '@protobufjs/pool@1.1.0': {}
+
+  '@protobufjs/utf8@1.1.0': {}
+
   '@radix-ui/number@1.1.1': {}
 
   '@radix-ui/primitive@1.1.3': {}
@@ -11426,6 +11622,9 @@ snapshots:
     dependencies:
       '@types/node': 24.10.0
 
+  '@types/trusted-types@2.0.7':
+    optional: true
+
   '@types/unist@2.0.11': {}
 
   '@types/unist@3.0.3': {}
@@ -12327,6 +12526,8 @@ snapshots:
 
   core-js-pure@3.47.0: {}
 
+  core-js@3.48.0: {}
+
   core-util-is@1.0.3: {}
 
   cosmiconfig@7.1.0:
@@ -12636,6 +12837,10 @@ snapshots:
     dependencies:
       domelementtype: 2.3.0
 
+  dompurify@3.3.1:
+    optionalDependencies:
+      '@types/trusted-types': 2.0.7
+
   domutils@2.8.0:
     dependencies:
       dom-serializer: 1.4.1
@@ -13205,6 +13410,8 @@ snapshots:
     optionalDependencies:
       picomatch: 4.0.3
 
+  fflate@0.4.8: {}
+
   file-entry-cache@6.0.1:
     dependencies:
       flat-cache: 3.2.0
@@ -14092,6 +14299,8 @@ snapshots:
 
   loglevel@1.9.2: {}
 
+  long@5.3.2: {}
+
   longest-streak@3.1.0: {}
 
   loose-envify@1.4.0:
@@ -15154,6 +15363,24 @@ snapshots:
     dependencies:
       xtend: 4.0.2
 
+  posthog-js@1.334.1:
+    dependencies:
+      '@opentelemetry/api': 1.9.0
+      '@opentelemetry/api-logs': 0.208.0
+      '@opentelemetry/exporter-logs-otlp-http': 0.208.0(@opentelemetry/api@1.9.0)
+      '@opentelemetry/resources': 2.2.0(@opentelemetry/api@1.9.0)
+      '@opentelemetry/sdk-logs': 0.208.0(@opentelemetry/api@1.9.0)
+      '@posthog/core': 1.13.0
+      '@posthog/types': 1.334.1
+      core-js: 3.48.0
+      dompurify: 3.3.1
+      fflate: 0.4.8
+      preact: 10.28.2
+      query-selector-shadow-dom: 1.0.1
+      web-vitals: 5.1.0
+
+  preact@10.28.2: {}
+
   prelude-ls@1.2.1: {}
 
   prettier-plugin-tailwindcss@0.7.1(prettier@3.6.2):
@@ -15187,6 +15414,21 @@ snapshots:
 
   property-information@7.1.0: {}
 
+  protobufjs@7.5.4:
+    dependencies:
+      '@protobufjs/aspromise': 1.1.2
+      '@protobufjs/base64': 1.1.2
+      '@protobufjs/codegen': 2.0.4
+      '@protobufjs/eventemitter': 1.1.0
+      '@protobufjs/fetch': 1.1.0
+      '@protobufjs/float': 1.0.2
+      '@protobufjs/inquire': 1.1.0
+      '@protobufjs/path': 1.1.2
+      '@protobufjs/pool': 1.1.0
+      '@protobufjs/utf8': 1.1.0
+      '@types/node': 24.10.0
+      long: 5.3.2
+
   proxy-from-env@1.1.0: {}
 
   public-encrypt@4.0.3:
@@ -15208,6 +15450,8 @@ snapshots:
     dependencies:
       side-channel: 1.1.0
 
+  query-selector-shadow-dom@1.0.1: {}
+
   querystring-es3@0.2.1: {}
 
   queue-microtask@1.2.3: {}
@@ -16619,6 +16863,8 @@ snapshots:
 
   web-namespaces@2.0.1: {}
 
+  web-vitals@5.1.0: {}
+
   webidl-conversions@3.0.1: {}
 
   webidl-conversions@8.0.1:

autogpt_platform/frontend/src/app/(platform)/build/components/BuilderActions/components/AgentOutputs/AgentOutputs.tsx

@@ -38,8 +38,12 @@ export const AgentOutputs = ({ flowID }: { flowID: string | null }) => {
 
     return outputNodes
       .map((node) => {
-        const executionResult = node.data.nodeExecutionResult;
-        const outputData = executionResult?.output_data?.output;
+        const executionResults = node.data.nodeExecutionResults || [];
+        const latestResult =
+          executionResults.length > 0
+            ? executionResults[executionResults.length - 1]
+            : undefined;
+        const outputData = latestResult?.output_data?.output;
 
         const renderer = globalRegistry.getRenderer(outputData);
 

autogpt_platform/frontend/src/app/(platform)/build/components/BuilderActions/components/RunInputDialog/useRunInputDialog.ts

@@ -153,6 +153,9 @@ export const useRunInputDialog = ({
       Object.entries(credentialValues).filter(([_, cred]) => cred && cred.id),
     );
 
+    useNodeStore.getState().clearAllNodeExecutionResults();
+    useNodeStore.getState().cleanNodesStatuses();
+
     await executeGraph({
       graphId: flowID ?? "",
       graphVersion: flowVersion || null,

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/CustomNode.tsx

@@ -34,7 +34,7 @@ export type CustomNodeData = {
   uiType: BlockUIType;
   block_id: string;
   status?: AgentExecutionStatus;
-  nodeExecutionResult?: NodeExecutionResult;
+  nodeExecutionResults?: NodeExecutionResult[];
   staticOutput?: boolean;
   // TODO : We need better type safety for the following backend fields.
   costs: BlockCost[];
@@ -75,7 +75,11 @@ export const CustomNode: React.FC<NodeProps<CustomNode>> = React.memo(
         (value) => value !== null && value !== undefined && value !== "",
       );
 
-    const outputData = data.nodeExecutionResult?.output_data;
+    const latestResult =
+      data.nodeExecutionResults && data.nodeExecutionResults.length > 0
+        ? data.nodeExecutionResults[data.nodeExecutionResults.length - 1]
+        : undefined;
+    const outputData = latestResult?.output_data;
     const hasOutputError =
       typeof outputData === "object" &&
       outputData !== null &&

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/NodeOutput/NodeOutput.tsx

@@ -14,10 +14,15 @@ import { useNodeOutput } from "./useNodeOutput";
 import { ViewMoreData } from "./components/ViewMoreData";
 
 export const NodeDataRenderer = ({ nodeId }: { nodeId: string }) => {
-  const { outputData, copiedKey, handleCopy, executionResultId, inputData } =
-    useNodeOutput(nodeId);
+  const {
+    latestOutputData,
+    copiedKey,
+    handleCopy,
+    executionResultId,
+    latestInputData,
+  } = useNodeOutput(nodeId);
 
-  if (Object.keys(outputData).length === 0) {
+  if (Object.keys(latestOutputData).length === 0) {
     return null;
   }
 
@@ -41,18 +46,19 @@ export const NodeDataRenderer = ({ nodeId }: { nodeId: string }) => {
               <div className="space-y-2">
                 <Text variant="small-medium">Input</Text>
 
-                <ContentRenderer value={inputData} shortContent={false} />
+                <ContentRenderer value={latestInputData} shortContent={false} />
 
                 <div className="mt-1 flex justify-end gap-1">
                   <NodeDataViewer
-                    data={inputData}
                     pinName="Input"
+                    nodeId={nodeId}
                     execId={executionResultId}
+                    dataType="input"
                   />
                   <Button
                     variant="secondary"
                     size="small"
-                    onClick={() => handleCopy("input", inputData)}
+                    onClick={() => handleCopy("input", latestInputData)}
                     className={cn(
                       "h-fit min-w-0 gap-1.5 border border-zinc-200 p-2 text-black hover:text-slate-900",
                       copiedKey === "input" &&
@@ -68,70 +74,72 @@ export const NodeDataRenderer = ({ nodeId }: { nodeId: string }) => {
                 </div>
               </div>
 
-              {Object.entries(outputData)
+              {Object.entries(latestOutputData)
                 .slice(0, 2)
-                .map(([key, value]) => (
-                  <div key={key} className="flex flex-col gap-2">
-                    <div className="flex items-center gap-2">
-                      <Text
-                        variant="small-medium"
-                        className="!font-semibold text-slate-600"
-                      >
-                        Pin:
-                      </Text>
-                      <Text variant="small" className="text-slate-700">
-                        {beautifyString(key)}
-                      </Text>
-                    </div>
-                    <div className="w-full space-y-2">
-                      <Text
-                        variant="small"
-                        className="!font-semibold text-slate-600"
-                      >
-                        Data:
-                      </Text>
-                      <div className="relative space-y-2">
-                        {value.map((item, index) => (
-                          <div key={index}>
-                            <ContentRenderer value={item} shortContent={true} />
-                          </div>
-                        ))}
+                .map(([key, value]) => {
+                  return (
+                    <div key={key} className="flex flex-col gap-2">
+                      <div className="flex items-center gap-2">
+                        <Text
+                          variant="small-medium"
+                          className="!font-semibold text-slate-600"
+                        >
+                          Pin:
+                        </Text>
+                        <Text variant="small" className="text-slate-700">
+                          {beautifyString(key)}
+                        </Text>
+                      </div>
+                      <div className="w-full space-y-2">
+                        <Text
+                          variant="small"
+                          className="!font-semibold text-slate-600"
+                        >
+                          Data:
+                        </Text>
+                        <div className="relative space-y-2">
+                          {value.map((item, index) => (
+                            <div key={index}>
+                              <ContentRenderer
+                                value={item}
+                                shortContent={true}
+                              />
+                            </div>
+                          ))}
 
-                        <div className="mt-1 flex justify-end gap-1">
-                          <NodeDataViewer
-                            data={value}
-                            pinName={key}
-                            execId={executionResultId}
-                          />
-                          <Button
-                            variant="secondary"
-                            size="small"
-                            onClick={() => handleCopy(key, value)}
-                            className={cn(
-                              "h-fit min-w-0 gap-1.5 border border-zinc-200 p-2 text-black hover:text-slate-900",
-                              copiedKey === key &&
-                                "border-green-400 bg-green-100 hover:border-green-400 hover:bg-green-200",
-                            )}
-                          >
-                            {copiedKey === key ? (
-                              <CheckIcon size={12} className="text-green-600" />
-                            ) : (
-                              <CopyIcon size={12} />
-                            )}
-                          </Button>
+                          <div className="mt-1 flex justify-end gap-1">
+                            <NodeDataViewer
+                              pinName={key}
+                              nodeId={nodeId}
+                              execId={executionResultId}
+                            />
+                            <Button
+                              variant="secondary"
+                              size="small"
+                              onClick={() => handleCopy(key, value)}
+                              className={cn(
+                                "h-fit min-w-0 gap-1.5 border border-zinc-200 p-2 text-black hover:text-slate-900",
+                                copiedKey === key &&
+                                  "border-green-400 bg-green-100 hover:border-green-400 hover:bg-green-200",
+                              )}
+                            >
+                              {copiedKey === key ? (
+                                <CheckIcon
+                                  size={12}
+                                  className="text-green-600"
+                                />
+                              ) : (
+                                <CopyIcon size={12} />
+                              )}
+                            </Button>
+                          </div>
                         </div>
                       </div>
                     </div>
-                  </div>
-                ))}
+                  );
+                })}
             </div>
-
-            {Object.keys(outputData).length > 2 && (
-              <ViewMoreData
-                outputData={outputData}
-                execId={executionResultId}
-              />
-            )}
+            <ViewMoreData nodeId={nodeId} />
           </AccordionContent>
         </AccordionItem>
       </Accordion>

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/NodeOutput/components/NodeDataViewer/NodeDataViewer.tsx

@@ -19,22 +19,51 @@ import {
   CopyIcon,
   DownloadIcon,
 } from "@phosphor-icons/react";
-import { FC } from "react";
+import React, { FC } from "react";
 import { useNodeDataViewer } from "./useNodeDataViewer";
+import { useNodeStore } from "@/app/(platform)/build/stores/nodeStore";
+import { useShallow } from "zustand/react/shallow";
+import { NodeDataType } from "../../helpers";
 
-interface NodeDataViewerProps {
-  data: any;
+export interface NodeDataViewerProps {
+  data?: any;
   pinName: string;
+  nodeId?: string;
   execId?: string;
   isViewMoreData?: boolean;
+  dataType?: NodeDataType;
 }
 
 export const NodeDataViewer: FC<NodeDataViewerProps> = ({
   data,
   pinName,
+  nodeId,
   execId = "N/A",
   isViewMoreData = false,
+  dataType = "output",
 }) => {
+  const executionResults = useNodeStore(
+    useShallow((state) =>
+      nodeId ? state.getNodeExecutionResults(nodeId) : [],
+    ),
+  );
+  const latestInputData = useNodeStore(
+    useShallow((state) =>
+      nodeId ? state.getLatestNodeInputData(nodeId) : undefined,
+    ),
+  );
+  const accumulatedOutputData = useNodeStore(
+    useShallow((state) =>
+      nodeId ? state.getAccumulatedNodeOutputData(nodeId) : {},
+    ),
+  );
+
+  const resolvedData =
+    data ??
+    (dataType === "input"
+      ? (latestInputData ?? {})
+      : (accumulatedOutputData[pinName] ?? []));
+
   const {
     outputItems,
     copyExecutionId,
@@ -42,7 +71,20 @@ export const NodeDataViewer: FC<NodeDataViewerProps> = ({
     handleDownloadItem,
     dataArray,
     copiedIndex,
-  } = useNodeDataViewer(data, pinName, execId);
+    groupedExecutions,
+    totalGroupedItems,
+    handleCopyGroupedItem,
+    handleDownloadGroupedItem,
+    copiedKey,
+  } = useNodeDataViewer(
+    resolvedData,
+    pinName,
+    execId,
+    executionResults,
+    dataType,
+  );
+
+  const shouldGroupExecutions = groupedExecutions.length > 0;
   return (
     <Dialog styling={{ width: "600px" }}>
       <TooltipProvider>
@@ -68,44 +110,141 @@ export const NodeDataViewer: FC<NodeDataViewerProps> = ({
           <div className="flex items-center gap-4">
             <div className="flex items-center gap-2">
               <Text variant="large-medium" className="text-slate-900">
-                Full Output Preview
+                Full {dataType === "input" ? "Input" : "Output"} Preview
               </Text>
             </div>
             <div className="rounded-full border border-slate-300 bg-slate-100 px-3 py-1.5 text-xs font-medium text-black">
-              {dataArray.length} item{dataArray.length !== 1 ? "s" : ""} total
+              {shouldGroupExecutions ? totalGroupedItems : dataArray.length}{" "}
+              item
+              {shouldGroupExecutions
+                ? totalGroupedItems !== 1
+                  ? "s"
+                  : ""
+                : dataArray.length !== 1
+                  ? "s"
+                  : ""}{" "}
+              total
             </div>
           </div>
           <div className="text-sm text-gray-600">
-            <div className="flex items-center gap-2">
-              <Text variant="body" className="text-slate-600">
-                Execution ID:
-              </Text>
-              <Text
-                variant="body-medium"
-                className="rounded-full border border-gray-300 bg-gray-50 px-2 py-1 font-mono text-xs"
-              >
-                {execId}
-              </Text>
-              <Button
-                variant="ghost"
-                size="small"
-                onClick={copyExecutionId}
-                className="h-6 w-6 min-w-0 p-0"
-              >
-                <CopyIcon size={14} />
-              </Button>
-            </div>
-            <div className="mt-2">
-              Pin:{" "}
-              <span className="font-semibold">{beautifyString(pinName)}</span>
-            </div>
+            {shouldGroupExecutions ? (
+              <div>
+                Pin:{" "}
+                <span className="font-semibold">{beautifyString(pinName)}</span>
+              </div>
+            ) : (
+              <>
+                <div className="flex items-center gap-2">
+                  <Text variant="body" className="text-slate-600">
+                    Execution ID:
+                  </Text>
+                  <Text
+                    variant="body-medium"
+                    className="rounded-full border border-gray-300 bg-gray-50 px-2 py-1 font-mono text-xs"
+                  >
+                    {execId}
+                  </Text>
+                  <Button
+                    variant="ghost"
+                    size="small"
+                    onClick={copyExecutionId}
+                    className="h-6 w-6 min-w-0 p-0"
+                  >
+                    <CopyIcon size={14} />
+                  </Button>
+                </div>
+                <div className="mt-2">
+                  Pin:{" "}
+                  <span className="font-semibold">
+                    {beautifyString(pinName)}
+                  </span>
+                </div>
+              </>
+            )}
           </div>
         </div>
 
         <div className="flex-1 overflow-hidden">
           <ScrollArea className="h-full">
             <div className="my-4">
-              {dataArray.length > 0 ? (
+              {shouldGroupExecutions ? (
+                <div className="space-y-4">
+                  {groupedExecutions.map((execution) => (
+                    <div
+                      key={execution.execId}
+                      className="rounded-3xl border border-slate-200 bg-white p-4 shadow-sm"
+                    >
+                      <div className="flex items-center gap-2">
+                        <Text variant="body" className="text-slate-600">
+                          Execution ID:
+                        </Text>
+                        <Text
+                          variant="body-medium"
+                          className="rounded-full border border-gray-300 bg-gray-50 px-2 py-1 font-mono text-xs"
+                        >
+                          {execution.execId}
+                        </Text>
+                      </div>
+                      <div className="mt-2 space-y-4">
+                        {execution.outputItems.length > 0 ? (
+                          execution.outputItems.map((item, index) => (
+                            <div
+                              key={item.key}
+                              className="group flex items-start gap-4"
+                            >
+                              <div className="w-full flex-1">
+                                <OutputItem
+                                  value={item.value}
+                                  metadata={item.metadata}
+                                  renderer={item.renderer}
+                                />
+                              </div>
+
+                              <div className="flex w-fit gap-3">
+                                <Button
+                                  variant="secondary"
+                                  className="min-w-0 p-1"
+                                  size="icon"
+                                  onClick={() =>
+                                    handleCopyGroupedItem(
+                                      execution.execId,
+                                      index,
+                                      item,
+                                    )
+                                  }
+                                  aria-label="Copy item"
+                                >
+                                  {copiedKey ===
+                                  `${execution.execId}-${index}` ? (
+                                    <CheckIcon className="size-4 text-green-600" />
+                                  ) : (
+                                    <CopyIcon className="size-4 text-black" />
+                                  )}
+                                </Button>
+                                <Button
+                                  variant="secondary"
+                                  size="icon"
+                                  className="min-w-0 p-1"
+                                  onClick={() =>
+                                    handleDownloadGroupedItem(item)
+                                  }
+                                  aria-label="Download item"
+                                >
+                                  <DownloadIcon className="size-4 text-black" />
+                                </Button>
+                              </div>
+                            </div>
+                          ))
+                        ) : (
+                          <div className="py-4 text-center text-gray-500">
+                            No data available
+                          </div>
+                        )}
+                      </div>
+                    </div>
+                  ))}
+                </div>
+              ) : dataArray.length > 0 ? (
                 <div className="space-y-4">
                   {outputItems.map((item, index) => (
                     <div key={item.key} className="group relative">

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/NodeOutput/components/NodeDataViewer/useNodeDataViewer.ts

@@ -1,82 +1,70 @@
-import type { OutputMetadata } from "@/components/contextual/OutputRenderers";
-import { globalRegistry } from "@/components/contextual/OutputRenderers";
 import { downloadOutputs } from "@/components/contextual/OutputRenderers/utils/download";
 import { useToast } from "@/components/molecules/Toast/use-toast";
 import { beautifyString } from "@/lib/utils";
-import React, { useMemo, useState } from "react";
+import { useState } from "react";
+import type { NodeExecutionResult } from "@/app/api/__generated__/models/nodeExecutionResult";
+import {
+  NodeDataType,
+  createOutputItems,
+  getExecutionData,
+  normalizeToArray,
+  type OutputItem,
+} from "../../helpers";
+
+export type GroupedExecution = {
+  execId: string;
+  outputItems: Array<OutputItem>;
+};
 
 export const useNodeDataViewer = (
   data: any,
   pinName: string,
   execId: string,
+  executionResults?: NodeExecutionResult[],
+  dataType?: NodeDataType,
 ) => {
   const { toast } = useToast();
   const [copiedIndex, setCopiedIndex] = useState<number | null>(null);
+  const [copiedKey, setCopiedKey] = useState<string | null>(null);
 
-  // Normalize data to array format
-  const dataArray = useMemo(() => {
-    return Array.isArray(data) ? data : [data];
-  }, [data]);
+  const dataArray = Array.isArray(data) ? data : [data];
 
-  // Prepare items for the enhanced renderer system
-  const outputItems = useMemo(() => {
-    if (!dataArray) return [];
-
-    const items: Array<{
-      key: string;
-      label: string;
-      value: unknown;
-      metadata?: OutputMetadata;
-      renderer: any;
-    }> = [];
-
-    dataArray.forEach((value, index) => {
-      const metadata: OutputMetadata = {};
-
-      // Extract metadata from the value if it's an object
-      if (
-        typeof value === "object" &&
-        value !== null &&
-        !React.isValidElement(value)
-      ) {
-        const objValue = value as any;
-        if (objValue.type) metadata.type = objValue.type;
-        if (objValue.mimeType) metadata.mimeType = objValue.mimeType;
-        if (objValue.filename) metadata.filename = objValue.filename;
-        if (objValue.language) metadata.language = objValue.language;
-      }
-
-      const renderer = globalRegistry.getRenderer(value, metadata);
-      if (renderer) {
-        items.push({
-          key: `item-${index}`,
+  const outputItems =
+    !dataArray || dataArray.length === 0
+      ? []
+      : createOutputItems(dataArray).map((item, index) => ({
+          ...item,
           label: index === 0 ? beautifyString(pinName) : "",
-          value,
-          metadata,
-          renderer,
-        });
-      } else {
-        // Fallback to text renderer
-        const textRenderer = globalRegistry
-          .getAllRenderers()
-          .find((r) => r.name === "TextRenderer");
-        if (textRenderer) {
-          items.push({
-            key: `item-${index}`,
-            label: index === 0 ? beautifyString(pinName) : "",
-            value:
-              typeof value === "string"
-                ? value
-                : JSON.stringify(value, null, 2),
-            metadata,
-            renderer: textRenderer,
-          });
-        }
-      }
-    });
+        }));
 
-    return items;
-  }, [dataArray, pinName]);
+  const groupedExecutions =
+    !executionResults || executionResults.length === 0
+      ? []
+      : [...executionResults].reverse().map((result) => {
+          const rawData = getExecutionData(
+            result,
+            dataType || "output",
+            pinName,
+          );
+          let dataArray: unknown[];
+          if (dataType === "input") {
+            dataArray =
+              rawData !== undefined && rawData !== null ? [rawData] : [];
+          } else {
+            dataArray = normalizeToArray(rawData);
+          }
+
+          const outputItems = createOutputItems(dataArray);
+          return {
+            execId: result.node_exec_id,
+            outputItems,
+          };
+        });
+
+  const totalGroupedItems = groupedExecutions.reduce(
+    (total, execution) => total + execution.outputItems.length,
+    0,
+  );
 
   const copyExecutionId = () => {
     navigator.clipboard.writeText(execId).then(() => {
@@ -122,6 +110,45 @@ export const useNodeDataViewer = (
     ]);
   };
 
+  const handleCopyGroupedItem = async (
+    execId: string,
+    index: number,
+    item: OutputItem,
+  ) => {
+    const copyContent = item.renderer.getCopyContent(item.value, item.metadata);
+
+    if (!copyContent) {
+      return;
+    }
+
+    try {
+      let text: string;
+      if (typeof copyContent.data === "string") {
+        text = copyContent.data;
+      } else if (copyContent.fallbackText) {
+        text = copyContent.fallbackText;
+      } else {
+        return;
+      }
+
+      await navigator.clipboard.writeText(text);
+      setCopiedKey(`${execId}-${index}`);
+      setTimeout(() => setCopiedKey(null), 2000);
+    } catch (error) {
+      console.error("Failed to copy:", error);
+    }
+  };
+
+  const handleDownloadGroupedItem = (item: OutputItem) => {
+    downloadOutputs([
+      {
+        value: item.value,
+        metadata: item.metadata,
+        renderer: item.renderer,
+      },
+    ]);
+  };
+
   return {
     outputItems,
     dataArray,
@@ -129,5 +156,10 @@ export const useNodeDataViewer = (
     handleCopyItem,
     handleDownloadItem,
     copiedIndex,
+    groupedExecutions,
+    totalGroupedItems,
+    handleCopyGroupedItem,
+    handleDownloadGroupedItem,
+    copiedKey,
   };
 };

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/NodeOutput/components/ViewMoreData.tsx

@@ -8,16 +8,28 @@ import { useState } from "react";
 import { NodeDataViewer } from "./NodeDataViewer/NodeDataViewer";
 import { useToast } from "@/components/molecules/Toast/use-toast";
 import { CheckIcon, CopyIcon } from "@phosphor-icons/react";
+import { useNodeStore } from "@/app/(platform)/build/stores/nodeStore";
+import { useShallow } from "zustand/react/shallow";
+import {
+  NodeDataType,
+  getExecutionEntries,
+  normalizeToArray,
+} from "../helpers";
 
 export const ViewMoreData = ({
-  outputData,
-  execId,
+  nodeId,
+  dataType = "output",
 }: {
-  outputData: Record<string, Array<any>>;
-  execId?: string;
+  nodeId: string;
+  dataType?: NodeDataType;
 }) => {
   const [copiedKey, setCopiedKey] = useState<string | null>(null);
   const { toast } = useToast();
+  const executionResults = useNodeStore(
+    useShallow((state) => state.getNodeExecutionResults(nodeId)),
+  );
+
+  const reversedExecutionResults = [...executionResults].reverse();
 
   const handleCopy = (key: string, value: any) => {
     const textToCopy =
@@ -29,8 +41,8 @@ export const ViewMoreData = ({
     setTimeout(() => setCopiedKey(null), 2000);
   };
 
-  const copyExecutionId = () => {
-    navigator.clipboard.writeText(execId || "N/A").then(() => {
+  const copyExecutionId = (executionId: string) => {
+    navigator.clipboard.writeText(executionId || "N/A").then(() => {
       toast({
         title: "Execution ID copied to clipboard!",
         duration: 2000,
@@ -42,7 +54,7 @@ export const ViewMoreData = ({
     <Dialog styling={{ width: "600px", paddingRight: "16px" }}>
       <Dialog.Trigger>
         <Button
-          variant="primary"
+          variant="secondary"
           size="small"
           className="h-fit w-fit min-w-0 !text-xs"
         >
@@ -52,83 +64,114 @@ export const ViewMoreData = ({
       <Dialog.Content>
         <div className="flex flex-col gap-4">
           <Text variant="h4" className="text-slate-900">
-            Complete Output Data
+            Complete {dataType === "input" ? "Input" : "Output"} Data
           </Text>
 
-          <div className="flex items-center gap-2">
-            <Text variant="body" className="text-slate-600">
-              Execution ID:
-            </Text>
-            <Text
-              variant="body-medium"
-              className="rounded-full border border-gray-300 bg-gray-50 px-2 py-1 font-mono text-xs"
-            >
-              {execId}
-            </Text>
-            <Button
-              variant="ghost"
-              size="small"
-              onClick={copyExecutionId}
-              className="h-6 w-6 min-w-0 p-0"
-            >
-              <CopyIcon size={14} />
-            </Button>
-          </div>
-
           <ScrollArea className="h-full">
             <div className="flex flex-col gap-4">
-              {Object.entries(outputData).map(([key, value]) => (
-                <div key={key} className="flex flex-col gap-2">
+              {reversedExecutionResults.map((result) => (
+                <div
+                  key={result.node_exec_id}
+                  className="rounded-3xl border border-slate-200 bg-white p-4 shadow-sm"
+                >
                   <div className="flex items-center gap-2">
+                    <Text variant="body" className="text-slate-600">
+                      Execution ID:
+                    </Text>
                     <Text
                       variant="body-medium"
-                      className="!font-semibold text-slate-600"
+                      className="rounded-full border border-gray-300 bg-gray-50 px-2 py-1 font-mono text-xs"
                     >
-                      Pin:
-                    </Text>
-                    <Text variant="body-medium" className="text-slate-700">
-                      {beautifyString(key)}
+                      {result.node_exec_id}
                     </Text>
+                    <Button
+                      variant="ghost"
+                      size="small"
+                      onClick={() => copyExecutionId(result.node_exec_id)}
+                      className="h-6 w-6 min-w-0 p-0"
+                    >
+                      <CopyIcon size={14} />
+                    </Button>
                   </div>
-                  <div className="w-full space-y-2">
-                    <Text
-                      variant="body-medium"
-                      className="!font-semibold text-slate-600"
-                    >
-                      Data:
-                    </Text>
-                    <div className="relative space-y-2">
-                      {value.map((item, index) => (
-                        <div key={index}>
-                          <ContentRenderer value={item} shortContent={false} />
-                        </div>
-                      ))}
 
-                      <div className="mt-1 flex justify-end gap-1">
-                        <NodeDataViewer
-                          data={value}
-                          pinName={key}
-                          execId={execId}
-                          isViewMoreData={true}
-                        />
-                        <Button
-                          variant="secondary"
-                          size="small"
-                          onClick={() => handleCopy(key, value)}
-                          className={cn(
-                            "h-fit min-w-0 gap-1.5 border border-zinc-200 p-2 text-black hover:text-slate-900",
-                            copiedKey === key &&
-                              "border-green-400 bg-green-100 hover:border-green-400 hover:bg-green-200",
-                          )}
-                        >
-                          {copiedKey === key ? (
-                            <CheckIcon size={16} className="text-green-600" />
-                          ) : (
-                            <CopyIcon size={16} />
-                          )}
-                        </Button>
-                      </div>
-                    </div>
+                  <div className="mt-4 flex flex-col gap-4">
+                    {getExecutionEntries(result, dataType).map(
+                      ([key, value]) => {
+                        const normalizedValue = normalizeToArray(value);
+                        return (
+                          <div key={key} className="flex flex-col gap-2">
+                            <div className="flex items-center gap-2">
+                              <Text
+                                variant="body-medium"
+                                className="!font-semibold text-slate-600"
+                              >
+                                Pin:
+                              </Text>
+                              <Text
+                                variant="body-medium"
+                                className="text-slate-700"
+                              >
+                                {beautifyString(key)}
+                              </Text>
+                            </div>
+                            <div className="w-full space-y-2">
+                              <Text
+                                variant="body-medium"
+                                className="!font-semibold text-slate-600"
+                              >
+                                Data:
+                              </Text>
+                              <div className="relative space-y-2">
+                                {normalizedValue.map((item, index) => (
+                                  <div key={index}>
+                                    <ContentRenderer
+                                      value={item}
+                                      shortContent={false}
+                                    />
+                                  </div>
+                                ))}
+
+                                <div className="mt-1 flex justify-end gap-1">
+                                  <NodeDataViewer
+                                    data={normalizedValue}
+                                    pinName={key}
+                                    execId={result.node_exec_id}
+                                    isViewMoreData={true}
+                                    dataType={dataType}
+                                  />
+                                  <Button
+                                    variant="secondary"
+                                    size="small"
+                                    onClick={() =>
+                                      handleCopy(
+                                        `${result.node_exec_id}-${key}`,
+                                        normalizedValue,
+                                      )
+                                    }
+                                    className={cn(
+                                      "h-fit min-w-0 gap-1.5 border border-zinc-200 p-2 text-black hover:text-slate-900",
+                                      copiedKey ===
+                                        `${result.node_exec_id}-${key}` &&
+                                        "border-green-400 bg-green-100 hover:border-green-400 hover:bg-green-200",
+                                    )}
+                                  >
+                                    {copiedKey ===
+                                    `${result.node_exec_id}-${key}` ? (
+                                      <CheckIcon
+                                        size={16}
+                                        className="text-green-600"
+                                      />
+                                    ) : (
+                                      <CopyIcon size={16} />
+                                    )}
+                                  </Button>
+                                </div>
+                              </div>
+                            </div>
+                          </div>
+                        );
+                      },
+                    )}
                   </div>
                 </div>
               ))}

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/NodeOutput/helpers.ts

@@ -0,0 +1,83 @@
+import type { NodeExecutionResult } from "@/app/api/__generated__/models/nodeExecutionResult";
+import type { OutputMetadata } from "@/components/contextual/OutputRenderers";
+import { globalRegistry } from "@/components/contextual/OutputRenderers";
+import React from "react";
+
+export type NodeDataType = "input" | "output";
+
+export type OutputItem = {
+  key: string;
+  value: unknown;
+  metadata?: OutputMetadata;
+  renderer: any;
+};
+
+export const normalizeToArray = (value: unknown) => {
+  if (value === undefined) return [];
+  return Array.isArray(value) ? value : [value];
+};
+
+export const getExecutionData = (
+  result: NodeExecutionResult,
+  dataType: NodeDataType,
+  pinName: string,
+) => {
+  if (dataType === "input") {
+    return result.input_data;
+  }
+
+  return result.output_data?.[pinName];
+};
+
+export const createOutputItems = (dataArray: unknown[]): Array<OutputItem> => {
+  const items: Array<OutputItem> = [];
+
+  dataArray.forEach((value, index) => {
+    const metadata: OutputMetadata = {};
+
+    if (
+      typeof value === "object" &&
+      value !== null &&
+      !React.isValidElement(value)
+    ) {
+      const objValue = value as any;
+      if (objValue.type) metadata.type = objValue.type;
+      if (objValue.mimeType) metadata.mimeType = objValue.mimeType;
+      if (objValue.filename) metadata.filename = objValue.filename;
+      if (objValue.language) metadata.language = objValue.language;
+    }
+
+    const renderer = globalRegistry.getRenderer(value, metadata);
+    if (renderer) {
+      items.push({
+        key: `item-${index}`,
+        value,
+        metadata,
+        renderer,
+      });
+    } else {
+      const textRenderer = globalRegistry
+        .getAllRenderers()
+        .find((r) => r.name === "TextRenderer");
+      if (textRenderer) {
+        items.push({
+          key: `item-${index}`,
+          value:
+            typeof value === "string" ? value : JSON.stringify(value, null, 2),
+          metadata,
+          renderer: textRenderer,
+        });
+      }
+    }
+  });
+
+  return items;
+};
+
+export const getExecutionEntries = (
+  result: NodeExecutionResult,
+  dataType: NodeDataType,
+) => {
+  const data = dataType === "input" ? result.input_data : result.output_data;
+  return Object.entries(data || {});
+};

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/NodeOutput/useNodeOutput.tsx

@@ -7,15 +7,18 @@ export const useNodeOutput = (nodeId: string) => {
   const [copiedKey, setCopiedKey] = useState<string | null>(null);
   const { toast } = useToast();
 
-  const nodeExecutionResult = useNodeStore(
-    useShallow((state) => state.getNodeExecutionResult(nodeId)),
+  const latestResult = useNodeStore(
+    useShallow((state) => state.getLatestNodeExecutionResult(nodeId)),
   );
 
-  const inputData = nodeExecutionResult?.input_data;
+  const latestInputData = useNodeStore(
+    useShallow((state) => state.getLatestNodeInputData(nodeId)),
+  );
+
+  const latestOutputData: Record<string, Array<any>> = useNodeStore(
+    useShallow((state) => state.getLatestNodeOutputData(nodeId) || {}),
+  );
 
-  const outputData: Record<string, Array<any>> = {
-    ...nodeExecutionResult?.output_data,
-  };
   const handleCopy = async (key: string, value: any) => {
     try {
       const text = JSON.stringify(value, null, 2);
@@ -35,11 +38,12 @@ export const useNodeOutput = (nodeId: string) => {
       });
     }
   };
+
   return {
-    outputData,
-    inputData,
+    latestOutputData,
+    latestInputData,
     copiedKey,
     handleCopy,
-    executionResultId: nodeExecutionResult?.node_exec_id,
+    executionResultId: latestResult?.node_exec_id,
   };
 };

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/SubAgentUpdate/useSubAgentUpdateState.ts

@@ -1,10 +1,7 @@
 import { useState, useCallback, useEffect } from "react";
 import { useShallow } from "zustand/react/shallow";
 import { useGraphStore } from "@/app/(platform)/build/stores/graphStore";
-import {
-  useNodeStore,
-  NodeResolutionData,
-} from "@/app/(platform)/build/stores/nodeStore";
+import { useNodeStore } from "@/app/(platform)/build/stores/nodeStore";
 import { useEdgeStore } from "@/app/(platform)/build/stores/edgeStore";
 import {
   useSubAgentUpdate,
@@ -13,6 +10,7 @@ import {
 } from "@/app/(platform)/build/hooks/useSubAgentUpdate";
 import { GraphInputSchema, GraphOutputSchema } from "@/lib/autogpt-server-api";
 import { CustomNodeData } from "../../CustomNode";
+import { NodeResolutionData } from "@/app/(platform)/build/stores/types";
 
 // Stable empty set to avoid creating new references in selectors
 const EMPTY_SET: Set<string> = new Set();

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/helpers.ts

@@ -1,5 +1,5 @@
 import { AgentExecutionStatus } from "@/app/api/__generated__/models/agentExecutionStatus";
-import { NodeResolutionData } from "@/app/(platform)/build/stores/nodeStore";
+import { NodeResolutionData } from "@/app/(platform)/build/stores/types";
 import { RJSFSchema } from "@rjsf/utils";
 
 export const nodeStyleBasedOnStatus: Record<AgentExecutionStatus, string> = {

autogpt_platform/frontend/src/app/(platform)/build/stores/helpers.ts

@@ -0,0 +1,16 @@
+export const accumulateExecutionData = (
+  accumulated: Record<string, unknown[]>,
+  data: Record<string, unknown> | undefined,
+) => {
+  if (!data) return { ...accumulated };
+  const next = { ...accumulated };
+  Object.entries(data).forEach(([key, values]) => {
+    const nextValues = Array.isArray(values) ? values : [values];
+    if (next[key]) {
+      next[key] = [...next[key], ...nextValues];
+    } else {
+      next[key] = [...nextValues];
+    }
+  });
+  return next;
+};

autogpt_platform/frontend/src/app/(platform)/build/stores/nodeStore.ts

@@ -10,6 +10,8 @@ import {
 import { Node } from "@/app/api/__generated__/models/node";
 import { AgentExecutionStatus } from "@/app/api/__generated__/models/agentExecutionStatus";
 import { NodeExecutionResult } from "@/app/api/__generated__/models/nodeExecutionResult";
+import { NodeExecutionResultInputData } from "@/app/api/__generated__/models/nodeExecutionResultInputData";
+import { NodeExecutionResultOutputData } from "@/app/api/__generated__/models/nodeExecutionResultOutputData";
 import { useHistoryStore } from "./historyStore";
 import { useEdgeStore } from "./edgeStore";
 import { BlockUIType } from "../components/types";
@@ -18,31 +20,10 @@ import {
   ensurePathExists,
   parseHandleIdToPath,
 } from "@/components/renderers/InputRenderer/helpers";
-import { IncompatibilityInfo } from "../hooks/useSubAgentUpdate/types";
+import { accumulateExecutionData } from "./helpers";
+import { NodeResolutionData } from "./types";
 
-// Resolution mode data stored per node
-export type NodeResolutionData = {
-  incompatibilities: IncompatibilityInfo;
-  // The NEW schema from the update (what we're updating TO)
-  pendingUpdate: {
-    input_schema: Record<string, unknown>;
-    output_schema: Record<string, unknown>;
-  };
-  // The OLD schema before the update (what we're updating FROM)
-  // Needed to merge and show removed inputs during resolution
-  currentSchema: {
-    input_schema: Record<string, unknown>;
-    output_schema: Record<string, unknown>;
-  };
-  // The full updated hardcoded values to apply when resolution completes
-  pendingHardcodedValues: Record<string, unknown>;
-};
-
-// Minimum movement (in pixels) required before logging position change to history
-// Prevents spamming history with small movements when clicking on inputs inside blocks
 const MINIMUM_MOVE_BEFORE_LOG = 50;
-
-// Track initial positions when drag starts (outside store to avoid re-renders)
 const dragStartPositions: Record<string, XYPosition> = {};
 
 let dragStartState: { nodes: CustomNode[]; edges: CustomEdge[] } | null = null;
@@ -52,6 +33,15 @@ type NodeStore = {
   nodeCounter: number;
   setNodeCounter: (nodeCounter: number) => void;
   nodeAdvancedStates: Record<string, boolean>;
+
+  latestNodeInputData: Record<string, NodeExecutionResultInputData | undefined>;
+  latestNodeOutputData: Record<
+    string,
+    NodeExecutionResultOutputData | undefined
+  >;
+  accumulatedNodeInputData: Record<string, Record<string, unknown[]>>;
+  accumulatedNodeOutputData: Record<string, Record<string, unknown[]>>;
+
   setNodes: (nodes: CustomNode[]) => void;
   onNodesChange: (changes: NodeChange<CustomNode>[]) => void;
   addNode: (node: CustomNode) => void;
@@ -72,12 +62,26 @@ type NodeStore = {
 
   updateNodeStatus: (nodeId: string, status: AgentExecutionStatus) => void;
   getNodeStatus: (nodeId: string) => AgentExecutionStatus | undefined;
+  cleanNodesStatuses: () => void;
 
   updateNodeExecutionResult: (
     nodeId: string,
     result: NodeExecutionResult,
   ) => void;
-  getNodeExecutionResult: (nodeId: string) => NodeExecutionResult | undefined;
+  getNodeExecutionResults: (nodeId: string) => NodeExecutionResult[];
+  getLatestNodeInputData: (
+    nodeId: string,
+  ) => NodeExecutionResultInputData | undefined;
+  getLatestNodeOutputData: (
+    nodeId: string,
+  ) => NodeExecutionResultOutputData | undefined;
+  getAccumulatedNodeInputData: (nodeId: string) => Record<string, unknown[]>;
+  getAccumulatedNodeOutputData: (nodeId: string) => Record<string, unknown[]>;
+  getLatestNodeExecutionResult: (
+    nodeId: string,
+  ) => NodeExecutionResult | undefined;
+  clearAllNodeExecutionResults: () => void;
+
   getNodeBlockUIType: (nodeId: string) => BlockUIType;
   hasWebhookNodes: () => boolean;
 
@@ -122,6 +126,10 @@ export const useNodeStore = create<NodeStore>((set, get) => ({
   nodeCounter: 0,
   setNodeCounter: (nodeCounter) => set({ nodeCounter }),
   nodeAdvancedStates: {},
+  latestNodeInputData: {},
+  latestNodeOutputData: {},
+  accumulatedNodeInputData: {},
+  accumulatedNodeOutputData: {},
   incrementNodeCounter: () =>
     set((state) => ({
       nodeCounter: state.nodeCounter + 1,
@@ -317,17 +325,162 @@ export const useNodeStore = create<NodeStore>((set, get) => ({
     return get().nodes.find((n) => n.id === nodeId)?.data?.status;
   },
 
-  updateNodeExecutionResult: (nodeId: string, result: NodeExecutionResult) => {
+  cleanNodesStatuses: () => {
     set((state) => ({
-      nodes: state.nodes.map((n) =>
-        n.id === nodeId
-          ? { ...n, data: { ...n.data, nodeExecutionResult: result } }
-          : n,
-      ),
+      nodes: state.nodes.map((n) => ({
+        ...n,
+        data: { ...n.data, status: undefined },
+      })),
     }));
   },
-  getNodeExecutionResult: (nodeId: string) => {
-    return get().nodes.find((n) => n.id === nodeId)?.data?.nodeExecutionResult;
+
+  updateNodeExecutionResult: (nodeId: string, result: NodeExecutionResult) => {
+    set((state) => {
+      let latestNodeInputData = state.latestNodeInputData;
+      let latestNodeOutputData = state.latestNodeOutputData;
+      let accumulatedNodeInputData = state.accumulatedNodeInputData;
+      let accumulatedNodeOutputData = state.accumulatedNodeOutputData;
+
+      const nodes = state.nodes.map((n) => {
+        if (n.id !== nodeId) return n;
+
+        const existingResults = n.data.nodeExecutionResults || [];
+        const duplicateIndex = existingResults.findIndex(
+          (r) => r.node_exec_id === result.node_exec_id,
+        );
+
+        if (duplicateIndex !== -1) {
+          const oldResult = existingResults[duplicateIndex];
+          const inputDataChanged =
+            JSON.stringify(oldResult.input_data) !==
+            JSON.stringify(result.input_data);
+          const outputDataChanged =
+            JSON.stringify(oldResult.output_data) !==
+            JSON.stringify(result.output_data);
+
+          if (!inputDataChanged && !outputDataChanged) {
+            return n;
+          }
+
+          const updatedResults = [...existingResults];
+          updatedResults[duplicateIndex] = result;
+
+          const recomputedAccumulatedInput = updatedResults.reduce(
+            (acc, r) => accumulateExecutionData(acc, r.input_data),
+            {} as Record<string, unknown[]>,
+          );
+          const recomputedAccumulatedOutput = updatedResults.reduce(
+            (acc, r) => accumulateExecutionData(acc, r.output_data),
+            {} as Record<string, unknown[]>,
+          );
+
+          const mostRecentResult = updatedResults[updatedResults.length - 1];
+          latestNodeInputData = {
+            ...latestNodeInputData,
+            [nodeId]: mostRecentResult.input_data,
+          };
+          latestNodeOutputData = {
+            ...latestNodeOutputData,
+            [nodeId]: mostRecentResult.output_data,
+          };
+
+          accumulatedNodeInputData = {
+            ...accumulatedNodeInputData,
+            [nodeId]: recomputedAccumulatedInput,
+          };
+          accumulatedNodeOutputData = {
+            ...accumulatedNodeOutputData,
+            [nodeId]: recomputedAccumulatedOutput,
+          };
+
+          return {
+            ...n,
+            data: {
+              ...n.data,
+              nodeExecutionResults: updatedResults,
+            },
+          };
+        }
+
+        accumulatedNodeInputData = {
+          ...accumulatedNodeInputData,
+          [nodeId]: accumulateExecutionData(
+            accumulatedNodeInputData[nodeId] || {},
+            result.input_data,
+          ),
+        };
+        accumulatedNodeOutputData = {
+          ...accumulatedNodeOutputData,
+          [nodeId]: accumulateExecutionData(
+            accumulatedNodeOutputData[nodeId] || {},
+            result.output_data,
+          ),
+        };
+
+        latestNodeInputData = {
+          ...latestNodeInputData,
+          [nodeId]: result.input_data,
+        };
+        latestNodeOutputData = {
+          ...latestNodeOutputData,
+          [nodeId]: result.output_data,
+        };
+
+        return {
+          ...n,
+          data: {
+            ...n.data,
+            nodeExecutionResults: [...existingResults, result],
+          },
+        };
+      });
+
+      return {
+        nodes,
+        latestNodeInputData,
+        latestNodeOutputData,
+        accumulatedNodeInputData,
+        accumulatedNodeOutputData,
+      };
+    });
+  },
+  getNodeExecutionResults: (nodeId: string) => {
+    return (
+      get().nodes.find((n) => n.id === nodeId)?.data?.nodeExecutionResults || []
+    );
+  },
+  getLatestNodeInputData: (nodeId: string) => {
+    return get().latestNodeInputData[nodeId];
+  },
+  getLatestNodeOutputData: (nodeId: string) => {
+    return get().latestNodeOutputData[nodeId];
+  },
+  getAccumulatedNodeInputData: (nodeId: string) => {
+    return get().accumulatedNodeInputData[nodeId] || {};
+  },
+  getAccumulatedNodeOutputData: (nodeId: string) => {
+    return get().accumulatedNodeOutputData[nodeId] || {};
+  },
+  getLatestNodeExecutionResult: (nodeId: string) => {
+    const results =
+      get().nodes.find((n) => n.id === nodeId)?.data?.nodeExecutionResults ||
+      [];
+    return results.length > 0 ? results[results.length - 1] : undefined;
+  },
+  clearAllNodeExecutionResults: () => {
+    set((state) => ({
+      nodes: state.nodes.map((n) => ({
+        ...n,
+        data: {
+          ...n.data,
+          nodeExecutionResults: [],
+        },
+      })),
+      latestNodeInputData: {},
+      latestNodeOutputData: {},
+      accumulatedNodeInputData: {},
+      accumulatedNodeOutputData: {},
+    }));
   },
   getNodeBlockUIType: (nodeId: string) => {
     return (

autogpt_platform/frontend/src/app/(platform)/build/stores/types.ts

@@ -0,0 +1,14 @@
+import { IncompatibilityInfo } from "../hooks/useSubAgentUpdate/types";
+
+export type NodeResolutionData = {
+  incompatibilities: IncompatibilityInfo;
+  pendingUpdate: {
+    input_schema: Record<string, unknown>;
+    output_schema: Record<string, unknown>;
+  };
+  currentSchema: {
+    input_schema: Record<string, unknown>;
+    output_schema: Record<string, unknown>;
+  };
+  pendingHardcodedValues: Record<string, unknown>;
+};

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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