refactor(backend): remove Langfuse tracing from chat system (#11829)

We are removing Langfuse tracing from the chat/copilot system in favor
of using OpenRouter's broadcast feature, which keeps our codebase
simpler. Langfuse prompt management is retained for fetching system
prompts.

### Changes 🏗️

**Removed Langfuse tracing:**
- Removed `@observe` decorators from all 11 chat tool files
- Removed `langfuse.openai` wrapper (now using standard `openai` client)
- Removed `start_as_current_observation` and `propagate_attributes`
context managers from `service.py`
- Removed `update_current_trace()`, `update_current_span()`,
`span.update()` calls

**Retained Langfuse prompt management:**
- `langfuse.get_prompt()` for fetching system prompts
- `_is_langfuse_configured()` check for prompt availability
- Configuration for `langfuse_prompt_name`

**Files modified:**
- `backend/api/features/chat/service.py`
- `backend/api/features/chat/tools/*.py` (11 tool files)

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  - [x] Verified `poetry run format` passes
  - [x] Verified no `@observe` decorators remain in chat tools
- [x] Verified Langfuse prompt fetching is still functional (code
preserved)

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/service.py

@@ -5,9 +5,9 @@ from asyncio import CancelledError
 from collections.abc import AsyncGenerator
 from typing import Any
 
+import openai
 import orjson
-from langfuse import get_client, propagate_attributes
+from langfuse import get_client
-from langfuse.openai import openai  # type: ignore
 from openai import (
     APIConnectionError,
     APIError,
@@ -48,6 +48,7 @@ from .response_model import (
     StreamUsage,
 )
 from .tools import execute_tool, tools
+from .tracking import track_user_message
 
 logger = logging.getLogger(__name__)
 
@@ -103,16 +104,33 @@ async def _build_system_prompt(user_id: str | None) -> tuple[str, Any]:
     return compiled, understanding
 
 
-async def _generate_session_title(message: str) -> str | None:
+async def _generate_session_title(
+    message: str,
+    user_id: str | None = None,
+    session_id: str | None = None,
+) -> str | None:
     """Generate a concise title for a chat session based on the first message.
 
     Args:
         message: The first user message in the session
+        user_id: User ID for OpenRouter tracing (optional)
+        session_id: Session ID for OpenRouter tracing (optional)
 
     Returns:
         A short title (3-6 words) or None if generation fails
     """
     try:
+        # Build extra_body for OpenRouter tracing and PostHog analytics
+        extra_body: dict[str, Any] = {}
+        if user_id:
+            extra_body["user"] = user_id[:128]  # OpenRouter limit
+            extra_body["posthogDistinctId"] = user_id
+        if session_id:
+            extra_body["session_id"] = session_id[:128]  # OpenRouter limit
+        extra_body["posthogProperties"] = {
+            "environment": settings.config.app_env.value,
+        }
+
         response = await client.chat.completions.create(
             model=config.title_model,
             messages=[
@@ -127,6 +145,7 @@ async def _generate_session_title(message: str) -> str | None:
                 {"role": "user", "content": message[:500]},  # Limit input length
             ],
             max_tokens=20,
+            extra_body=extra_body,
         )
         title = response.choices[0].message.content
         if title:
@@ -218,18 +237,9 @@ async def stream_chat_completion(
         )
 
     if message:
-        # Build message content with context if provided
-        message_content = message
-        if context and context.get("url") and context.get("content"):
-            context_text = f"Page URL: {context['url']}\n\nPage Content:\n{context['content']}\n\n---\n\nUser Message: {message}"
-            message_content = context_text
-            logger.info(
-                f"Including page context: URL={context['url']}, content_length={len(context['content'])}"
-            )
-
         session.messages.append(
             ChatMessage(
-                role="user" if is_user_message else "assistant", content=message_content
+                role="user" if is_user_message else "assistant", content=message
             )
         )
         logger.info(
@@ -237,6 +247,14 @@ async def stream_chat_completion(
             f"new message_count={len(session.messages)}"
         )
 
+        # Track user message in PostHog
+        if is_user_message:
+            track_user_message(
+                user_id=user_id,
+                session_id=session_id,
+                message_length=len(message),
+            )
+
     logger.info(
         f"Upserting session: {session.session_id} with user id {session.user_id}, "
         f"message_count={len(session.messages)}"
@@ -256,10 +274,15 @@ async def stream_chat_completion(
             # stale data issues when the main flow modifies the session
             captured_session_id = session_id
             captured_message = message
+            captured_user_id = user_id
 
             async def _update_title():
                 try:
-                    title = await _generate_session_title(captured_message)
+                    title = await _generate_session_title(
+                        captured_message,
+                        user_id=captured_user_id,
+                        session_id=captured_session_id,
+                    )
                     if title:
                         # Use dedicated title update function that doesn't
                         # touch messages, avoiding race conditions
@@ -276,347 +299,302 @@ async def stream_chat_completion(
     # Build system prompt with business understanding
     system_prompt, understanding = await _build_system_prompt(user_id)
 
-    # Create Langfuse trace for this LLM call (each call gets its own trace, grouped by session_id)
+    # Initialize variables for streaming
-    # Using v3 SDK: start_observation creates a root span, update_trace sets trace-level attributes
+    assistant_response = ChatMessage(
-    input = message
+        role="assistant",
-    if not message and tool_call_response:
+        content="",
-        input = tool_call_response
+    )
+    accumulated_tool_calls: list[dict[str, Any]] = []
+    has_saved_assistant_message = False
+    has_appended_streaming_message = False
+    last_cache_time = 0.0
+    last_cache_content_len = 0
 
-    langfuse = get_client()
+    has_yielded_end = False
-    with langfuse.start_as_current_observation(
+    has_yielded_error = False
-        as_type="span",
+    has_done_tool_call = False
-        name="user-copilot-request",
+    has_received_text = False
-        input=input,
+    text_streaming_ended = False
-    ) as span:
+    tool_response_messages: list[ChatMessage] = []
-        with propagate_attributes(
+    should_retry = False
-            session_id=session_id,
+
-            user_id=user_id,
+    # Generate unique IDs for AI SDK protocol
-            tags=["copilot"],
+    import uuid as uuid_module
-            metadata={
+
-                "users_information": format_understanding_for_prompt(understanding)[
+    message_id = str(uuid_module.uuid4())
-                    :200
+    text_block_id = str(uuid_module.uuid4())
-                ]  # langfuse only accepts upto to 200 chars
+
-            },
+    # Yield message start
+    yield StreamStart(messageId=message_id)
+
+    try:
+        async for chunk in _stream_chat_chunks(
+            session=session,
+            tools=tools,
+            system_prompt=system_prompt,
+            text_block_id=text_block_id,
         ):
 
-            # Initialize variables that will be used in finally block (must be defined before try)
+            if isinstance(chunk, StreamTextStart):
-            assistant_response = ChatMessage(
+                # Emit text-start before first text delta
-                role="assistant",
+                if not has_received_text:
-                content="",
+                    yield chunk
-            )
+            elif isinstance(chunk, StreamTextDelta):
-            accumulated_tool_calls: list[dict[str, Any]] = []
+                delta = chunk.delta or ""
-            has_saved_assistant_message = False
+                assert assistant_response.content is not None
-            has_appended_streaming_message = False
+                assistant_response.content += delta
-            last_cache_time = 0.0
+                has_received_text = True
-            last_cache_content_len = 0
+                if not has_appended_streaming_message:
-
+                    session.messages.append(assistant_response)
-            # Wrap main logic in try/finally to ensure Langfuse observations are always ended
+                    has_appended_streaming_message = True
-            has_yielded_end = False
+                current_time = time.monotonic()
-            has_yielded_error = False
+                content_len = len(assistant_response.content)
-            has_done_tool_call = False
+                if (
-            has_received_text = False
+                    current_time - last_cache_time >= 1.0
-            text_streaming_ended = False
+                    and content_len > last_cache_content_len
-            tool_response_messages: list[ChatMessage] = []
-            should_retry = False
-
-            # Generate unique IDs for AI SDK protocol
-            import uuid as uuid_module
-
-            message_id = str(uuid_module.uuid4())
-            text_block_id = str(uuid_module.uuid4())
-
-            # Yield message start
-            yield StreamStart(messageId=message_id)
-
-            try:
-                async for chunk in _stream_chat_chunks(
-                    session=session,
-                    tools=tools,
-                    system_prompt=system_prompt,
-                    text_block_id=text_block_id,
                 ):
-
-                    if isinstance(chunk, StreamTextStart):
-                        # Emit text-start before first text delta
-                        if not has_received_text:
-                            yield chunk
-                    elif isinstance(chunk, StreamTextDelta):
-                        delta = chunk.delta or ""
-                        assert assistant_response.content is not None
-                        assistant_response.content += delta
-                        has_received_text = True
-                        if not has_appended_streaming_message:
-                            session.messages.append(assistant_response)
-                            has_appended_streaming_message = True
-                        current_time = time.monotonic()
-                        content_len = len(assistant_response.content)
-                        if (
-                            current_time - last_cache_time >= 1.0
-                            and content_len > last_cache_content_len
-                        ):
-                            try:
-                                await cache_chat_session(session)
-                            except Exception as e:
-                                logger.warning(
-                                    f"Failed to cache partial session {session.session_id}: {e}"
-                                )
-                            last_cache_time = current_time
-                            last_cache_content_len = content_len
-                        yield chunk
-                    elif isinstance(chunk, StreamTextEnd):
-                        # Emit text-end after text completes
-                        if has_received_text and not text_streaming_ended:
-                            text_streaming_ended = True
-                            if assistant_response.content:
-                                logger.warn(
-                                    f"StreamTextEnd: Attempting to set output {assistant_response.content}"
-                                )
-                                span.update_trace(output=assistant_response.content)
-                                span.update(output=assistant_response.content)
-                            yield chunk
-                    elif isinstance(chunk, StreamToolInputStart):
-                        # Emit text-end before first tool call, but only if we've received text
-                        if has_received_text and not text_streaming_ended:
-                            yield StreamTextEnd(id=text_block_id)
-                            text_streaming_ended = True
-                        yield chunk
-                    elif isinstance(chunk, StreamToolInputAvailable):
-                        # Accumulate tool calls in OpenAI format
-                        accumulated_tool_calls.append(
-                            {
-                                "id": chunk.toolCallId,
-                                "type": "function",
-                                "function": {
-                                    "name": chunk.toolName,
-                                    "arguments": orjson.dumps(chunk.input).decode(
-                                        "utf-8"
-                                    ),
-                                },
-                            }
-                        )
-                    elif isinstance(chunk, StreamToolOutputAvailable):
-                        result_content = (
-                            chunk.output
-                            if isinstance(chunk.output, str)
-                            else orjson.dumps(chunk.output).decode("utf-8")
-                        )
-                        tool_response_messages.append(
-                            ChatMessage(
-                                role="tool",
-                                content=result_content,
-                                tool_call_id=chunk.toolCallId,
-                            )
-                        )
-                        has_done_tool_call = True
-                        # Track if any tool execution failed
-                        if not chunk.success:
-                            logger.warning(
-                                f"Tool {chunk.toolName} (ID: {chunk.toolCallId}) execution failed"
-                            )
-                        yield chunk
-                    elif isinstance(chunk, StreamFinish):
-                        if not has_done_tool_call:
-                            # Emit text-end before finish if we received text but haven't closed it
-                            if has_received_text and not text_streaming_ended:
-                                yield StreamTextEnd(id=text_block_id)
-                                text_streaming_ended = True
-
-                            # Save assistant message before yielding finish to ensure it's persisted
-                            # even if client disconnects immediately after receiving StreamFinish
-                            if not has_saved_assistant_message:
-                                messages_to_save_early: list[ChatMessage] = []
-                                if accumulated_tool_calls:
-                                    assistant_response.tool_calls = (
-                                        accumulated_tool_calls
-                                    )
-                                if not has_appended_streaming_message and (
-                                    assistant_response.content
-                                    or assistant_response.tool_calls
-                                ):
-                                    messages_to_save_early.append(assistant_response)
-                                messages_to_save_early.extend(tool_response_messages)
-
-                                if messages_to_save_early:
-                                    session.messages.extend(messages_to_save_early)
-                                    logger.info(
-                                        f"Saving assistant message before StreamFinish: "
-                                        f"content_len={len(assistant_response.content or '')}, "
-                                        f"tool_calls={len(assistant_response.tool_calls or [])}, "
-                                        f"tool_responses={len(tool_response_messages)}"
-                                    )
-                                if (
-                                    messages_to_save_early
-                                    or has_appended_streaming_message
-                                ):
-                                    await upsert_chat_session(session)
-                                    has_saved_assistant_message = True
-
-                            has_yielded_end = True
-                            yield chunk
-                    elif isinstance(chunk, StreamError):
-                        has_yielded_error = True
-                        yield chunk
-                    elif isinstance(chunk, StreamUsage):
-                        session.usage.append(
-                            Usage(
-                                prompt_tokens=chunk.promptTokens,
-                                completion_tokens=chunk.completionTokens,
-                                total_tokens=chunk.totalTokens,
-                            )
-                        )
-                    else:
-                        logger.error(
-                            f"Unknown chunk type: {type(chunk)}", exc_info=True
-                        )
-                if assistant_response.content:
-                    langfuse.update_current_trace(output=assistant_response.content)
-                    langfuse.update_current_span(output=assistant_response.content)
-                elif tool_response_messages:
-                    langfuse.update_current_trace(output=str(tool_response_messages))
-                    langfuse.update_current_span(output=str(tool_response_messages))
-
-            except CancelledError:
-                if not has_saved_assistant_message:
-                    if accumulated_tool_calls:
-                        assistant_response.tool_calls = accumulated_tool_calls
-                    if assistant_response.content:
-                        assistant_response.content = (
-                            f"{assistant_response.content}\n\n[interrupted]"
-                        )
-                    else:
-                        assistant_response.content = "[interrupted]"
-                    if not has_appended_streaming_message:
-                        session.messages.append(assistant_response)
-                    if tool_response_messages:
-                        session.messages.extend(tool_response_messages)
                     try:
-                        await upsert_chat_session(session)
+                        await cache_chat_session(session)
                     except Exception as e:
                         logger.warning(
-                            f"Failed to save interrupted session {session.session_id}: {e}"
+                            f"Failed to cache partial session {session.session_id}: {e}"
                         )
-                raise
+                    last_cache_time = current_time
-            except Exception as e:
+                    last_cache_content_len = content_len
-                logger.error(f"Error during stream: {e!s}", exc_info=True)
+                yield chunk
-
+            elif isinstance(chunk, StreamTextEnd):
-                # Check if this is a retryable error (JSON parsing, incomplete tool calls, etc.)
+                # Emit text-end after text completes
-                is_retryable = isinstance(
+                if has_received_text and not text_streaming_ended:
-                    e, (orjson.JSONDecodeError, KeyError, TypeError)
+                    text_streaming_ended = True
-                )
-
-                if is_retryable and retry_count < config.max_retries:
-                    logger.info(
-                        f"Retryable error encountered. Attempt {retry_count + 1}/{config.max_retries}"
-                    )
-                    should_retry = True
-                else:
-                    # Non-retryable error or max retries exceeded
-                    # Save any partial progress before reporting error
-                    messages_to_save: list[ChatMessage] = []
-
-                    # Add assistant message if it has content or tool calls
-                    if accumulated_tool_calls:
-                        assistant_response.tool_calls = accumulated_tool_calls
-                    if not has_appended_streaming_message and (
-                        assistant_response.content or assistant_response.tool_calls
-                    ):
-                        messages_to_save.append(assistant_response)
-
-                    # Add tool response messages after assistant message
-                    messages_to_save.extend(tool_response_messages)
-
-                    if not has_saved_assistant_message:
-                        if messages_to_save:
-                            session.messages.extend(messages_to_save)
-                        if messages_to_save or has_appended_streaming_message:
-                            await upsert_chat_session(session)
-
-                    if not has_yielded_error:
-                        error_message = str(e)
-                        if not is_retryable:
-                            error_message = f"Non-retryable error: {error_message}"
-                        elif retry_count >= config.max_retries:
-                            error_message = f"Max retries ({config.max_retries}) exceeded: {error_message}"
-
-                        error_response = StreamError(errorText=error_message)
-                        yield error_response
-                    if not has_yielded_end:
-                        yield StreamFinish()
-                    return
-
-            # Handle retry outside of exception handler to avoid nesting
-            if should_retry and retry_count < config.max_retries:
-                logger.info(
-                    f"Retrying stream_chat_completion for session {session_id}, attempt {retry_count + 1}"
-                )
-                async for chunk in stream_chat_completion(
-                    session_id=session.session_id,
-                    user_id=user_id,
-                    retry_count=retry_count + 1,
-                    session=session,
-                    context=context,
-                ):
                     yield chunk
-                return  # Exit after retry to avoid double-saving in finally block
+            elif isinstance(chunk, StreamToolInputStart):
+                # Emit text-end before first tool call, but only if we've received text
+                if has_received_text and not text_streaming_ended:
+                    yield StreamTextEnd(id=text_block_id)
+                    text_streaming_ended = True
+                yield chunk
+            elif isinstance(chunk, StreamToolInputAvailable):
+                # Accumulate tool calls in OpenAI format
+                accumulated_tool_calls.append(
+                    {
+                        "id": chunk.toolCallId,
+                        "type": "function",
+                        "function": {
+                            "name": chunk.toolName,
+                            "arguments": orjson.dumps(chunk.input).decode("utf-8"),
+                        },
+                    }
+                )
+                yield chunk
+            elif isinstance(chunk, StreamToolOutputAvailable):
+                result_content = (
+                    chunk.output
+                    if isinstance(chunk.output, str)
+                    else orjson.dumps(chunk.output).decode("utf-8")
+                )
+                tool_response_messages.append(
+                    ChatMessage(
+                        role="tool",
+                        content=result_content,
+                        tool_call_id=chunk.toolCallId,
+                    )
+                )
+                has_done_tool_call = True
+                # Track if any tool execution failed
+                if not chunk.success:
+                    logger.warning(
+                        f"Tool {chunk.toolName} (ID: {chunk.toolCallId}) execution failed"
+                    )
+                yield chunk
+            elif isinstance(chunk, StreamFinish):
+                if not has_done_tool_call:
+                    # Emit text-end before finish if we received text but haven't closed it
+                    if has_received_text and not text_streaming_ended:
+                        yield StreamTextEnd(id=text_block_id)
+                        text_streaming_ended = True
+
+                    # Save assistant message before yielding finish to ensure it's persisted
+                    # even if client disconnects immediately after receiving StreamFinish
+                    if not has_saved_assistant_message:
+                        messages_to_save_early: list[ChatMessage] = []
+                        if accumulated_tool_calls:
+                            assistant_response.tool_calls = accumulated_tool_calls
+                        if not has_appended_streaming_message and (
+                            assistant_response.content or assistant_response.tool_calls
+                        ):
+                            messages_to_save_early.append(assistant_response)
+                        messages_to_save_early.extend(tool_response_messages)
+
+                        if messages_to_save_early:
+                            session.messages.extend(messages_to_save_early)
+                            logger.info(
+                                f"Saving assistant message before StreamFinish: "
+                                f"content_len={len(assistant_response.content or '')}, "
+                                f"tool_calls={len(assistant_response.tool_calls or [])}, "
+                                f"tool_responses={len(tool_response_messages)}"
+                            )
+                        if messages_to_save_early or has_appended_streaming_message:
+                            await upsert_chat_session(session)
+                            has_saved_assistant_message = True
+
+                    has_yielded_end = True
+                    yield chunk
+            elif isinstance(chunk, StreamError):
+                has_yielded_error = True
+                yield chunk
+            elif isinstance(chunk, StreamUsage):
+                session.usage.append(
+                    Usage(
+                        prompt_tokens=chunk.promptTokens,
+                        completion_tokens=chunk.completionTokens,
+                        total_tokens=chunk.totalTokens,
+                    )
+                )
+            else:
+                logger.error(f"Unknown chunk type: {type(chunk)}", exc_info=True)
+
+    except CancelledError:
+        if not has_saved_assistant_message:
+            if accumulated_tool_calls:
+                assistant_response.tool_calls = accumulated_tool_calls
+            if assistant_response.content:
+                assistant_response.content = (
+                    f"{assistant_response.content}\n\n[interrupted]"
+                )
+            else:
+                assistant_response.content = "[interrupted]"
+            if not has_appended_streaming_message:
+                session.messages.append(assistant_response)
+            if tool_response_messages:
+                session.messages.extend(tool_response_messages)
+            try:
+                await upsert_chat_session(session)
+            except Exception as e:
+                logger.warning(
+                    f"Failed to save interrupted session {session.session_id}: {e}"
+                )
+        raise
+    except Exception as e:
+        logger.error(f"Error during stream: {e!s}", exc_info=True)
+
+        # Check if this is a retryable error (JSON parsing, incomplete tool calls, etc.)
+        is_retryable = isinstance(e, (orjson.JSONDecodeError, KeyError, TypeError))
+
+        if is_retryable and retry_count < config.max_retries:
+            logger.info(
+                f"Retryable error encountered. Attempt {retry_count + 1}/{config.max_retries}"
+            )
+            should_retry = True
+        else:
+            # Non-retryable error or max retries exceeded
+            # Save any partial progress before reporting error
+            messages_to_save: list[ChatMessage] = []
+
+            # Add assistant message if it has content or tool calls
+            if accumulated_tool_calls:
+                assistant_response.tool_calls = accumulated_tool_calls
+            if not has_appended_streaming_message and (
+                assistant_response.content or assistant_response.tool_calls
+            ):
+                messages_to_save.append(assistant_response)
+
+            # Add tool response messages after assistant message
+            messages_to_save.extend(tool_response_messages)
 
-            # Normal completion path - save session and handle tool call continuation
-            # Only save if we haven't already saved when StreamFinish was received
             if not has_saved_assistant_message:
-                logger.info(
-                    f"Normal completion path: session={session.session_id}, "
-                    f"current message_count={len(session.messages)}"
-                )
-
-                # Build the messages list in the correct order
-                messages_to_save: list[ChatMessage] = []
-
-                # Add assistant message with tool_calls if any
-                if accumulated_tool_calls:
-                    assistant_response.tool_calls = accumulated_tool_calls
-                    logger.info(
-                        f"Added {len(accumulated_tool_calls)} tool calls to assistant message"
-                    )
-                if not has_appended_streaming_message and (
-                    assistant_response.content or assistant_response.tool_calls
-                ):
-                    messages_to_save.append(assistant_response)
-                    logger.info(
-                        f"Saving assistant message with content_len={len(assistant_response.content or '')}, tool_calls={len(assistant_response.tool_calls or [])}"
-                    )
-
-                # Add tool response messages after assistant message
-                messages_to_save.extend(tool_response_messages)
-                logger.info(
-                    f"Saving {len(tool_response_messages)} tool response messages, "
-                    f"total_to_save={len(messages_to_save)}"
-                )
-
                 if messages_to_save:
                     session.messages.extend(messages_to_save)
-                    logger.info(
-                        f"Extended session messages, new message_count={len(session.messages)}"
-                    )
                 if messages_to_save or has_appended_streaming_message:
                     await upsert_chat_session(session)
-            else:
-                logger.info(
-                    "Assistant message already saved when StreamFinish was received, "
-                    "skipping duplicate save"
-                )
 
-            # If we did a tool call, stream the chat completion again to get the next response
+            if not has_yielded_error:
-            if has_done_tool_call:
+                error_message = str(e)
-                logger.info(
+                if not is_retryable:
-                    "Tool call executed, streaming chat completion again to get assistant response"
+                    error_message = f"Non-retryable error: {error_message}"
-                )
+                elif retry_count >= config.max_retries:
-                async for chunk in stream_chat_completion(
+                    error_message = (
-                    session_id=session.session_id,
+                        f"Max retries ({config.max_retries}) exceeded: {error_message}"
-                    user_id=user_id,
+                    )
-                    session=session,  # Pass session object to avoid Redis refetch
+
-                    context=context,
+                error_response = StreamError(errorText=error_message)
-                    tool_call_response=str(tool_response_messages),
+                yield error_response
-                ):
+            if not has_yielded_end:
-                    yield chunk
+                yield StreamFinish()
+            return
+
+    # Handle retry outside of exception handler to avoid nesting
+    if should_retry and retry_count < config.max_retries:
+        logger.info(
+            f"Retrying stream_chat_completion for session {session_id}, attempt {retry_count + 1}"
+        )
+        async for chunk in stream_chat_completion(
+            session_id=session.session_id,
+            user_id=user_id,
+            retry_count=retry_count + 1,
+            session=session,
+            context=context,
+        ):
+            yield chunk
+        return  # Exit after retry to avoid double-saving in finally block
+
+    # Normal completion path - save session and handle tool call continuation
+    # Only save if we haven't already saved when StreamFinish was received
+    if not has_saved_assistant_message:
+        logger.info(
+            f"Normal completion path: session={session.session_id}, "
+            f"current message_count={len(session.messages)}"
+        )
+
+        # Build the messages list in the correct order
+        messages_to_save: list[ChatMessage] = []
+
+        # Add assistant message with tool_calls if any
+        if accumulated_tool_calls:
+            assistant_response.tool_calls = accumulated_tool_calls
+            logger.info(
+                f"Added {len(accumulated_tool_calls)} tool calls to assistant message"
+            )
+        if not has_appended_streaming_message and (
+            assistant_response.content or assistant_response.tool_calls
+        ):
+            messages_to_save.append(assistant_response)
+            logger.info(
+                f"Saving assistant message with content_len={len(assistant_response.content or '')}, tool_calls={len(assistant_response.tool_calls or [])}"
+            )
+
+        # Add tool response messages after assistant message
+        messages_to_save.extend(tool_response_messages)
+        logger.info(
+            f"Saving {len(tool_response_messages)} tool response messages, "
+            f"total_to_save={len(messages_to_save)}"
+        )
+
+        if messages_to_save:
+            session.messages.extend(messages_to_save)
+            logger.info(
+                f"Extended session messages, new message_count={len(session.messages)}"
+            )
+        if messages_to_save or has_appended_streaming_message:
+            await upsert_chat_session(session)
+    else:
+        logger.info(
+            "Assistant message already saved when StreamFinish was received, "
+            "skipping duplicate save"
+        )
+
+    # If we did a tool call, stream the chat completion again to get the next response
+    if has_done_tool_call:
+        logger.info(
+            "Tool call executed, streaming chat completion again to get assistant response"
+        )
+        async for chunk in stream_chat_completion(
+            session_id=session.session_id,
+            user_id=user_id,
+            session=session,  # Pass session object to avoid Redis refetch
+            context=context,
+            tool_call_response=str(tool_response_messages),
+        ):
+            yield chunk
 
 
 # Retry configuration for OpenAI API calls
@@ -698,6 +676,20 @@ async def _stream_chat_chunks(
                     f"{f' (retry {retry_count}/{MAX_RETRIES})' if retry_count > 0 else ''}"
                 )
 
+                # Build extra_body for OpenRouter tracing and PostHog analytics
+                extra_body: dict[str, Any] = {
+                    "posthogProperties": {
+                        "environment": settings.config.app_env.value,
+                    },
+                }
+                if session.user_id:
+                    extra_body["user"] = session.user_id[:128]  # OpenRouter limit
+                    extra_body["posthogDistinctId"] = session.user_id
+                if session.session_id:
+                    extra_body["session_id"] = session.session_id[
+                        :128
+                    ]  # OpenRouter limit
+
                 # Create the stream with proper types
                 stream = await client.chat.completions.create(
                     model=model,
@@ -706,6 +698,7 @@ async def _stream_chat_chunks(
                     tool_choice="auto",
                     stream=True,
                     stream_options={"include_usage": True},
+                    extra_body=extra_body,
                 )
 
                 # Variables to accumulate tool calls

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
@@ -20,6 +22,8 @@ from .search_docs import SearchDocsTool
 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(),
@@ -56,4 +60,17 @@ async def execute_tool(
     tool = TOOL_REGISTRY.get(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/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 (
@@ -75,7 +73,6 @@ class CreateAgentTool(BaseTool):
             "required": ["description"],
         }
 
-    @observe(as_type="tool", name="create_agent")
     async def _execute(
         self,
         user_id: str | None,

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 (
@@ -81,7 +79,6 @@ class EditAgentTool(BaseTool):
             "required": ["agent_id", "changes"],
         }
 
-    @observe(as_type="tool", name="edit_agent")
     async def _execute(
         self,
         user_id: str | None,

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,

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/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

@@ -4,8 +4,6 @@ import logging
 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
@@ -130,7 +128,6 @@ 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 +176,11 @@ 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}")
 

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/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/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/util/settings.py

@@ -679,6 +679,12 @@ 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/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-7.6.0-py3-none-any.whl", hash = "sha256:c4dd78cf77c4fecceb965f86066e5ac37886ef867d68ffe75a1db5d681d7d9ad"},
-    {file = "posthog-6.1.1.tar.gz", hash = "sha256:b453f54c4a2589da859fd575dd3bf86fcb40580727ec399535f268b1b9f318b8"},
+    {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/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:
   '@open-draft/until@2.1.0':
     resolution: {integrity: sha512-U69T3ItWHvLwGg5eJ0n3I62nWuE6ilHlmz7zM0npLBRvPRd7e6NYmg54vvRtP5mZG7kZqZCFVdsTWo7BPtBujg==}
 
+  '@opentelemetry/api-logs@0.208.0':
+    resolution: {integrity: sha512-CjruKY9V6NMssL/T1kAFgzosF1v9o6oeN+aX5JB/C/xPNtmgIJqcXHG7fA82Ou1zCpWGl4lROQUKwUNE1pMCyg==}
+    engines: {node: '>=8.0.0'}
+
   '@opentelemetry/api-logs@0.209.0':
     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:
+      '@opentelemetry/api': ^1.3.0
+
   '@opentelemetry/instrumentation-amqplib@0.55.0':
     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:
+      '@opentelemetry/api': ^1.3.0
+
   '@opentelemetry/redis-common@0.38.2':
     resolution: {integrity: sha512-1BCcU93iwSRZvDAgwUxC/DV4T/406SkMfxGqu5ojc3AvNI+I9GhV7v0J1HljsczuuhcnFLYqD5VmwVXfCGHzxA==}
     engines: {node: ^18.19.0 || >=20.6.0}
@@ -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'
+
   '@opentelemetry/sdk-trace-base@2.2.0':
     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==}
+
+  '@protobufjs/eventemitter@1.1.0':
+    resolution: {integrity: sha512-j9ednRT81vYJ9OfVuXG6ERSTdEL1xVsNgqpkxMsbIabzSo3goCjDIveeGv5d03om39ML71RdmrGNjG5SReBP/Q==}
+
+  '@protobufjs/fetch@1.1.0':
+    resolution: {integrity: sha512-lljVXpqXebpsijW71PZaCYeIcE5on1w5DlQy5WH6GLbFryLUrBD4932W/E2BSpfRJWseIL4v/KPgBFxDOIdKpQ==}
+
+  '@protobufjs/float@1.0.2':
+    resolution: {integrity: sha512-Ddb+kVXlXst9d+R9PfTIxh1EdNkgoRe5tOX6t01f1lYWOvJnSPDBlG241QLzcyPdoNTsblLUdujGSE4RzrTZGQ==}
+
+  '@protobufjs/inquire@1.1.0':
+    resolution: {integrity: sha512-kdSefcPdruJiFMVSbn801t4vFK7KB/5gd2fYvrxhuJYg8ILrmn9SKSX2tZdV6V+ksulWqS7aXjBcRXl3wHoD9Q==}
+
+  '@protobufjs/path@1.1.2':
+    resolution: {integrity: sha512-6JOcJ5Tm08dOHAbdR3GrvP+yUUfkjG5ePsHYczMFLq3ZmMkAD98cDgcT2iA1lJ9NVwFd4tH/iSSoe44YWkltEA==}
+
+  '@protobufjs/pool@1.1.0':
+    resolution: {integrity: sha512-0kELaGSIDBKvcgS4zkjz1PeddatrjYcmMWOlAuAPwAeccUrPHdUqo/J6LiymHHEiJT5NrF1UVwxY14f+fy4WQw==}
+
+  '@protobufjs/utf8@1.1.0':
+    resolution: {integrity: sha512-Vvn3zZrhQZkkBE8LSuW3em98c0FwgO4nxzv6OdSxPKJIEKY2bGbHn+mhGIPerzI4twdxaP8/0+06HBpwf345Lw==}
+
   '@radix-ui/number@1.1.1':
     resolution: {integrity: sha512-MkKCwxlXTgz6CFoJx3pCwn07GKp36+aZyu/u2Ln2VrA5DcdyCZkASEDBTd8x5whTQQL5CiYf4prXKLcgQdv29g==}
 
@@ -3401,6 +3487,9 @@ packages:
   '@types/tedious@4.0.14':
     resolution: {integrity: sha512-KHPsfX/FoVbUGbyYvk1q9MMQHLPeRZhRJZdO45Q4YjvFkv4hMNghCWTvy7rdKessBsmtz4euWCWAB6/tVpI1Iw==}
 
+  '@types/trusted-types@2.0.7':
+    resolution: {integrity: sha512-ScaPdn1dQczgbl0QFTeTOmVHFULt394XJgOQNoyVhZ6r2vLnMLJfBPd53SB52T/3G36VI1/g2MZaX0cwDuXsfw==}
+
   '@types/unist@2.0.11':
     resolution: {integrity: sha512-CmBKiL6NNo/OqgmMn95Fk9Whlp2mtvIv+KNpQKN2F4SjvrEesubTRWGYSg+BnWZOnlCaSTU1sMpsBOzgbYhnsA==}
 
@@ -4278,6 +4367,9 @@ packages:
   core-js-pure@3.47.0:
     resolution: {integrity: sha512-BcxeDbzUrRnXGYIVAGFtcGQVNpFcUhVjr6W7F8XktvQW2iJP9e66GP6xdKotCRFlrxBvNIBrhwKteRXqMV86Nw==}
 
+  core-js@3.48.0:
+    resolution: {integrity: sha512-zpEHTy1fjTMZCKLHUZoVeylt9XrzaIN2rbPXEt0k+q7JE5CkCZdo6bNq55bn24a69CH7ErAVLKijxJja4fw+UQ==}
+
   core-util-is@1.0.3:
     resolution: {integrity: sha512-ZQBvi1DcpJ4GDqanjucZ2Hj3wEO5pZDS89BWbkcrvdxksJorwUDDZamX9ldFkp9aw2lmBDLgkObEA4DWNJ9FYQ==}
 
@@ -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:
     resolution: {integrity: sha512-w96Cjofp72M5IIhpjgobBimYEfoPjx1Vx0BSX9P30WBdZW2WIKU0T1Bd0kz2eNZ9ikjKgHbEyKx8BB6H1L3h3A==}
 
@@ -4939,6 +5034,9 @@ packages:
       picomatch:
         optional: true
 
+  fflate@0.4.8:
+    resolution: {integrity: sha512-FJqqoDBR00Mdj9ppamLa/Y7vxm+PRmNWA67N846RvsoYVMKB4q3y/de5PA7gUmRMYK/8CMz2GDZQmCRN1wBcWA==}
+
   file-entry-cache@6.0.1:
     resolution: {integrity: sha512-7Gps/XWymbLk2QLYK4NzpMOrYjMhdIxXuIvy2QBsLE6ljuodKvdkWs/cpyJJ3CVIVpH0Oi1Hvg1ovbMzLdFBBg==}
     engines: {node: ^10.12.0 || >=12.0.0}
@@ -5745,6 +5843,9 @@ packages:
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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:
     resolution: {integrity: sha512-9Ri+o0JYgehTaVBBDoMqIl8GXtbWg711O3srftcHhZ0dqnETqLaoIK0x17fUw9rFSlK/0NlsKe0Ahhyl5pXE2g==}
 
@@ -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:
     resolution: {integrity: sha512-vkcDPrRZo1QZLbn5RLGPpg/WmIQ65qoWWhcGKf/b5eplkkarX0m9z8ppCat4mlOqUsWpyNuYgO3VRyrYHSzX5g==}
     engines: {node: '>= 0.8.0'}
@@ -6622,6 +6729,10 @@ packages:
   property-information@7.1.0:
     resolution: {integrity: sha512-TwEZ+X+yCJmYfL7TPUOcvBZ4QfoT5YenQiJuX//0th53DE6w0xxLEtfK3iyryQFddXuvkIk51EEgrJQ0WJkOmQ==}
 
+  protobufjs@7.5.4:
+    resolution: {integrity: sha512-CvexbZtbov6jW2eXAvLukXjXUW1TzFaivC46BpWc/3BpcCysb5Vffu+B3XHMm8lVEuy2Mm4XGex8hBSg1yapPg==}
+    engines: {node: '>=12.0.0'}
+
   proxy-from-env@1.1.0:
     resolution: {integrity: sha512-D+zkORCbA9f1tdWRK0RaCR3GPv50cMxcrz4X8k5LTSUD1Dkw47mKJEZQNunItRTkWwgtaUSo1RVFRIG9ZXiFYg==}
 
@@ -6643,6 +6754,9 @@ packages:
     resolution: {integrity: sha512-4EK3+xJl8Ts67nLYNwqw/dsFVnCf+qR7RgXSK9jEEm9unao3njwMDdmsdvoKBKHzxd7tCYz5e5M+SnMjdtXGQQ==}
     engines: {node: '>=0.6'}
 
+  query-selector-shadow-dom@1.0.1:
+    resolution: {integrity: sha512-lT5yCqEBgfoMYpf3F2xQRK7zEr1rhIIZuceDK6+xRkJQ4NMbHTwXqk4NkwDwQMNqXgG9r9fyHnzwNVs6zV5KRw==}
+
   querystring-es3@0.2.1:
     resolution: {integrity: sha512-773xhDQnZBMFobEiztv8LIl70ch5MSF/jUQVlhwFyBILqq96anmoctVIYz+ZRp0qbCKATTn6ev02M3r7Ga5vqA==}
     engines: {node: '>=0.4.x'}
@@ -7821,6 +7935,9 @@ packages:
   web-namespaces@2.0.1:
     resolution: {integrity: sha512-bKr1DkiNa2krS7qxNtdrtHAmzuYGFQLiQ13TsorsdT6ULTkPLKuu5+GsFpDlg6JFjUTwX2DyhMPG2be8uPrqsQ==}
 
+  web-vitals@5.1.0:
+    resolution: {integrity: sha512-ArI3kx5jI0atlTtmV0fWU3fjpLmq/nD3Zr1iFFlJLaqa5wLBkUSzINwBPySCX/8jRyjlmy1Volw1kz1g9XE4Jg==}
+
   webidl-conversions@3.0.1:
     resolution: {integrity: sha512-2JAn3z8AR6rjK8Sm8orRC0h/bcl/DqL7tRPdGZ4I1CjdF+EaMLmYxBHyXuKL849eucPFhvBoxMsflfOb8kxaeQ==}
 
@@ -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)
+
   '@opentelemetry/instrumentation-amqplib@0.55.0(@opentelemetry/api@1.9.0)':
     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 executionResults = node.data.nodeExecutionResults || [];
-        const outputData = executionResult?.output_data?.output;
+        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 } =
+  const {
-    useNodeOutput(nodeId);
+    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]) => (
+                .map(([key, value]) => {
-                  <div key={key} className="flex flex-col gap-2">
+                  return (
-                    <div className="flex items-center gap-2">
+                    <div key={key} className="flex flex-col gap-2">
-                      <Text
+                      <div className="flex items-center gap-2">
-                        variant="small-medium"
+                        <Text
-                        className="!font-semibold text-slate-600"
+                          variant="small-medium"
-                      >
+                          className="!font-semibold text-slate-600"
-                        Pin:
+                        >
-                      </Text>
+                          Pin:
-                      <Text variant="small" className="text-slate-700">
+                        </Text>
-                        {beautifyString(key)}
+                        <Text variant="small" className="text-slate-700">
-                      </Text>
+                          {beautifyString(key)}
-                    </div>
+                        </Text>
-                    <div className="w-full space-y-2">
+                      </div>
-                      <Text
+                      <div className="w-full space-y-2">
-                        variant="small"
+                        <Text
-                        className="!font-semibold text-slate-600"
+                          variant="small"
-                      >
+                          className="!font-semibold text-slate-600"
-                        Data:
+                        >
-                      </Text>
+                          Data:
-                      <div className="relative space-y-2">
+                        </Text>
-                        {value.map((item, index) => (
+                        <div className="relative space-y-2">
-                          <div key={index}>
+                          {value.map((item, index) => (
-                            <ContentRenderer value={item} shortContent={true} />
+                            <div key={index}>
-                          </div>
+                              <ContentRenderer
-                        ))}
+                                value={item}
+                                shortContent={true}
+                              />
+                            </div>
+                          ))}
 
-                        <div className="mt-1 flex justify-end gap-1">
+                          <div className="mt-1 flex justify-end gap-1">
-                          <NodeDataViewer
+                            <NodeDataViewer
-                            data={value}
+                              pinName={key}
-                            pinName={key}
+                              nodeId={nodeId}
-                            execId={executionResultId}
+                              execId={executionResultId}
-                          />
+                            />
-                          <Button
+                            <Button
-                            variant="secondary"
+                              variant="secondary"
-                            size="small"
+                              size="small"
-                            onClick={() => handleCopy(key, value)}
+                              onClick={() => handleCopy(key, value)}
-                            className={cn(
+                              className={cn(
-                              "h-fit min-w-0 gap-1.5 border border-zinc-200 p-2 text-black hover:text-slate-900",
+                                "h-fit min-w-0 gap-1.5 border border-zinc-200 p-2 text-black hover:text-slate-900",
-                              copiedKey === key &&
+                                copiedKey === key &&
-                                "border-green-400 bg-green-100 hover:border-green-400 hover:bg-green-200",
+                                  "border-green-400 bg-green-100 hover:border-green-400 hover:bg-green-200",
-                            )}
+                              )}
-                          >
+                            >
-                            {copiedKey === key ? (
+                              {copiedKey === key ? (
-                              <CheckIcon size={12} className="text-green-600" />
+                                <CheckIcon
-                            ) : (
+                                  size={12}
-                              <CopyIcon size={12} />
+                                  className="text-green-600"
-                            )}
+                                />
-                          </Button>
+                              ) : (
+                                <CopyIcon size={12} />
+                              )}
+                            </Button>
+                          </div>
                         </div>
                       </div>
                     </div>
-                  </div>
+                  );
-                ))}
+                })}
             </div>
-
+            <ViewMoreData nodeId={nodeId} />
-            {Object.keys(outputData).length > 2 && (
-              <ViewMoreData
-                outputData={outputData}
-                execId={executionResultId}
-              />
-            )}
           </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 {
+export interface NodeDataViewerProps {
-  data: any;
+  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">
+            {shouldGroupExecutions ? (
-              <Text variant="body" className="text-slate-600">
+              <div>
-                Execution ID:
+                Pin:{" "}
-              </Text>
+                <span className="font-semibold">{beautifyString(pinName)}</span>
-              <Text
+              </div>
-                variant="body-medium"
+            ) : (
-                className="rounded-full border border-gray-300 bg-gray-50 px-2 py-1 font-mono text-xs"
+              <>
-              >
+                <div className="flex items-center gap-2">
-                {execId}
+                  <Text variant="body" className="text-slate-600">
-              </Text>
+                    Execution ID:
-              <Button
+                  </Text>
-                variant="ghost"
+                  <Text
-                size="small"
+                    variant="body-medium"
-                onClick={copyExecutionId}
+                    className="rounded-full border border-gray-300 bg-gray-50 px-2 py-1 font-mono text-xs"
-                className="h-6 w-6 min-w-0 p-0"
+                  >
-              >
+                    {execId}
-                <CopyIcon size={14} />
+                  </Text>
-              </Button>
+                  <Button
-            </div>
+                    variant="ghost"
-            <div className="mt-2">
+                    size="small"
-              Pin:{" "}
+                    onClick={copyExecutionId}
-              <span className="font-semibold">{beautifyString(pinName)}</span>
+                    className="h-6 w-6 min-w-0 p-0"
-            </div>
+                  >
+                    <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 = Array.isArray(data) ? data : [data];
-  const dataArray = useMemo(() => {
-    return Array.isArray(data) ? data : [data];
-  }, [data]);
 
-  // Prepare items for the enhanced renderer system
+  const outputItems =
-  const outputItems = useMemo(() => {
+    !dataArray || dataArray.length === 0
-    if (!dataArray) return [];
+      ? []
-
+      : createOutputItems(dataArray).map((item, index) => ({
-    const items: Array<{
+          ...item,
-      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-${index}`,
           label: index === 0 ? beautifyString(pinName) : "",
-          value,
+        }));
-          metadata,
-          renderer,
-        });
-      } else {
-        // Fallback to text renderer
-        const textRenderer = globalRegistry
-          .getAllRenderers()
-          .find((r) => r.name === "TextRenderer");
-        if (textRenderer) {
-          items.push({
-            key: `item-${index}`,
-            label: index === 0 ? beautifyString(pinName) : "",
-            value:
-              typeof value === "string"
-                ? value
-                : JSON.stringify(value, null, 2),
-            metadata,
-            renderer: textRenderer,
-          });
-        }
-      }
-    });
 
-    return items;
+  const groupedExecutions =
-  }, [dataArray, pinName]);
+    !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,
+  nodeId,
-  execId,
+  dataType = "output",
 }: {
-  outputData: Record<string, Array<any>>;
+  nodeId: string;
-  execId?: 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 = () => {
+  const copyExecutionId = (executionId: string) => {
-    navigator.clipboard.writeText(execId || "N/A").then(() => {
+    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]) => (
+              {reversedExecutionResults.map((result) => (
-                <div key={key} className="flex flex-col gap-2">
+                <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:
+                      {result.node_exec_id}
-                    </Text>
-                    <Text variant="body-medium" className="text-slate-700">
-                      {beautifyString(key)}
                     </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">
+                  <div className="mt-4 flex flex-col gap-4">
-                        <NodeDataViewer
+                    {getExecutionEntries(result, dataType).map(
-                          data={value}
+                      ([key, value]) => {
-                          pinName={key}
+                        const normalizedValue = normalizeToArray(value);
-                          execId={execId}
+                        return (
-                          isViewMoreData={true}
+                          <div key={key} className="flex flex-col gap-2">
-                        />
+                            <div className="flex items-center gap-2">
-                        <Button
+                              <Text
-                          variant="secondary"
+                                variant="body-medium"
-                          size="small"
+                                className="!font-semibold text-slate-600"
-                          onClick={() => handleCopy(key, value)}
+                              >
-                          className={cn(
+                                Pin:
-                            "h-fit min-w-0 gap-1.5 border border-zinc-200 p-2 text-black hover:text-slate-900",
+                              </Text>
-                            copiedKey === key &&
+                              <Text
-                              "border-green-400 bg-green-100 hover:border-green-400 hover:bg-green-200",
+                                variant="body-medium"
-                          )}
+                                className="text-slate-700"
-                        >
+                              >
-                          {copiedKey === key ? (
+                                {beautifyString(key)}
-                            <CheckIcon size={16} className="text-green-600" />
+                              </Text>
-                          ) : (
+                            </div>
-                            <CopyIcon size={16} />
+                            <div className="w-full space-y-2">
-                          )}
+                              <Text
-                        </Button>
+                                variant="body-medium"
-                      </div>
+                                className="!font-semibold text-slate-600"
-                    </div>
+                              >
+                                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(
+  const latestResult = useNodeStore(
-    useShallow((state) => state.getNodeExecutionResult(nodeId)),
+    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,
+    latestOutputData,
-    inputData,
+    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 {
+import { useNodeStore } from "@/app/(platform)/build/stores/nodeStore";
-  useNodeStore,
-  NodeResolutionData,
-} 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) =>
+      nodes: state.nodes.map((n) => ({
-        n.id === nodeId
+        ...n,
-          ? { ...n, data: { ...n.data, nodeExecutionResult: result } }
+        data: { ...n.data, status: undefined },
-          : n,
+      })),
-      ),
     }));
   },
-  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/providers.tsx

@@ -6,28 +6,40 @@ import { BackendAPIProvider } from "@/lib/autogpt-server-api/context";
 import { getQueryClient } from "@/lib/react-query/queryClient";
 import CredentialsProvider from "@/providers/agent-credentials/credentials-provider";
 import OnboardingProvider from "@/providers/onboarding/onboarding-provider";
+import {
+  PostHogPageViewTracker,
+  PostHogProvider,
+  PostHogUserTracker,
+} from "@/providers/posthog/posthog-provider";
 import { LaunchDarklyProvider } from "@/services/feature-flags/feature-flag-provider";
 import { QueryClientProvider } from "@tanstack/react-query";
 import { ThemeProvider, ThemeProviderProps } from "next-themes";
 import { NuqsAdapter } from "nuqs/adapters/next/app";
+import { Suspense } from "react";
 
 export function Providers({ children, ...props }: ThemeProviderProps) {
   const queryClient = getQueryClient();
   return (
     <QueryClientProvider client={queryClient}>
       <NuqsAdapter>
-        <BackendAPIProvider>
+        <PostHogProvider>
-          <SentryUserTracker />
+          <BackendAPIProvider>
-          <CredentialsProvider>
+            <SentryUserTracker />
-            <LaunchDarklyProvider>
+            <PostHogUserTracker />
-              <OnboardingProvider>
+            <Suspense fallback={null}>
-                <ThemeProvider forcedTheme="light" {...props}>
+              <PostHogPageViewTracker />
-                  <TooltipProvider>{children}</TooltipProvider>
+            </Suspense>
-                </ThemeProvider>
+            <CredentialsProvider>
-              </OnboardingProvider>
+              <LaunchDarklyProvider>
-            </LaunchDarklyProvider>
+                <OnboardingProvider>
-          </CredentialsProvider>
+                  <ThemeProvider forcedTheme="light" {...props}>
-        </BackendAPIProvider>
+                    <TooltipProvider>{children}</TooltipProvider>
+                  </ThemeProvider>
+                </OnboardingProvider>
+              </LaunchDarklyProvider>
+            </CredentialsProvider>
+          </BackendAPIProvider>
+        </PostHogProvider>
       </NuqsAdapter>
     </QueryClientProvider>
   );

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

@@ -213,6 +213,23 @@ export function parseToolResponse(
         timestamp: timestamp || new Date(),
       };
     }
+    if (responseType === "clarification_needed") {
+      return {
+        type: "clarification_needed",
+        toolName,
+        questions:
+          (parsedResult.questions as Array<{
+            question: string;
+            keyword: string;
+            example?: string;
+          }>) || [],
+        message:
+          (parsedResult.message as string) ||
+          "I need more information to proceed.",
+        sessionId: (parsedResult.session_id as string) || "",
+        timestamp: timestamp || new Date(),
+      };
+    }
     if (responseType === "need_login") {
       return {
         type: "login_needed",

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

@@ -14,6 +14,7 @@ import { AgentCarouselMessage } from "../AgentCarouselMessage/AgentCarouselMessa
 import { AIChatBubble } from "../AIChatBubble/AIChatBubble";
 import { AuthPromptWidget } from "../AuthPromptWidget/AuthPromptWidget";
 import { ChatCredentialsSetup } from "../ChatCredentialsSetup/ChatCredentialsSetup";
+import { ClarificationQuestionsWidget } from "../ClarificationQuestionsWidget/ClarificationQuestionsWidget";
 import { ExecutionStartedMessage } from "../ExecutionStartedMessage/ExecutionStartedMessage";
 import { MarkdownContent } from "../MarkdownContent/MarkdownContent";
 import { NoResultsMessage } from "../NoResultsMessage/NoResultsMessage";
@@ -69,6 +70,7 @@ export function ChatMessage({
     isToolResponse,
     isLoginNeeded,
     isCredentialsNeeded,
+    isClarificationNeeded,
   } = useChatMessage(message);
   const displayContent = getDisplayContent(message, isUser);
 
@@ -96,6 +98,18 @@ export function ChatMessage({
     }
   }
 
+  function handleClarificationAnswers(answers: Record<string, string>) {
+    if (onSendMessage) {
+      const contextMessage = Object.entries(answers)
+        .map(([keyword, answer]) => `${keyword}: ${answer}`)
+        .join("\n");
+
+      onSendMessage(
+        `I have the answers to your questions:\n\n${contextMessage}\n\nPlease proceed with creating the agent.`,
+      );
+    }
+  }
+
   const handleCopy = useCallback(
     async function handleCopy() {
       if (message.type !== "message") return;
@@ -141,6 +155,17 @@ export function ChatMessage({
     );
   }
 
+  if (isClarificationNeeded && message.type === "clarification_needed") {
+    return (
+      <ClarificationQuestionsWidget
+        questions={message.questions}
+        message={message.message}
+        onSubmitAnswers={handleClarificationAnswers}
+        className={className}
+      />
+    );
+  }
+
   // Render login needed messages
   if (isLoginNeeded && message.type === "login_needed") {
     // If user is already logged in, show success message instead of auth prompt

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

@@ -91,6 +91,18 @@ export type ChatMessageData =
       credentialsSchema?: Record<string, any>;
       message: string;
       timestamp?: string | Date;
+    }
+  | {
+      type: "clarification_needed";
+      toolName: string;
+      questions: Array<{
+        question: string;
+        keyword: string;
+        example?: string;
+      }>;
+      message: string;
+      sessionId: string;
+      timestamp?: string | Date;
     };
 
 export function useChatMessage(message: ChatMessageData) {
@@ -111,5 +123,6 @@ export function useChatMessage(message: ChatMessageData) {
     isAgentCarousel: message.type === "agent_carousel",
     isExecutionStarted: message.type === "execution_started",
     isInputsNeeded: message.type === "inputs_needed",
+    isClarificationNeeded: message.type === "clarification_needed",
   };
 }

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

@@ -0,0 +1,154 @@
+"use client";
+
+import { Button } from "@/components/atoms/Button/Button";
+import { Card } from "@/components/atoms/Card/Card";
+import { Input } from "@/components/atoms/Input/Input";
+import { Text } from "@/components/atoms/Text/Text";
+import { cn } from "@/lib/utils";
+import { CheckCircleIcon, QuestionIcon } from "@phosphor-icons/react";
+import { useState } from "react";
+
+export interface ClarifyingQuestion {
+  question: string;
+  keyword: string;
+  example?: string;
+}
+
+interface Props {
+  questions: ClarifyingQuestion[];
+  message: string;
+  onSubmitAnswers: (answers: Record<string, string>) => void;
+  onCancel?: () => void;
+  className?: string;
+}
+
+export function ClarificationQuestionsWidget({
+  questions,
+  message,
+  onSubmitAnswers,
+  onCancel,
+  className,
+}: Props) {
+  const [answers, setAnswers] = useState<Record<string, string>>({});
+
+  function handleAnswerChange(keyword: string, value: string) {
+    setAnswers((prev) => ({ ...prev, [keyword]: value }));
+  }
+
+  function handleSubmit() {
+    // Check if all questions are answered
+    const allAnswered = questions.every((q) => answers[q.keyword]?.trim());
+    if (!allAnswered) {
+      return;
+    }
+    onSubmitAnswers(answers);
+  }
+
+  const allAnswered = questions.every((q) => answers[q.keyword]?.trim());
+
+  return (
+    <div
+      className={cn(
+        "group relative flex w-full justify-start gap-3 px-4 py-3",
+        className,
+      )}
+    >
+      <div className="flex w-full max-w-3xl gap-3">
+        <div className="flex-shrink-0">
+          <div className="flex h-7 w-7 items-center justify-center rounded-lg bg-indigo-500">
+            <QuestionIcon className="h-4 w-4 text-indigo-50" weight="bold" />
+          </div>
+        </div>
+
+        <div className="flex min-w-0 flex-1 flex-col">
+          <Card className="space-y-4 p-4">
+            <div>
+              <Text variant="h4" className="mb-1 text-slate-900">
+                I need more information
+              </Text>
+              <Text variant="small" className="text-slate-600">
+                {message}
+              </Text>
+            </div>
+
+            <div className="space-y-3">
+              {questions.map((q, index) => {
+                const isAnswered = !!answers[q.keyword]?.trim();
+
+                return (
+                  <div
+                    key={`${q.keyword}-${index}`}
+                    className={cn(
+                      "relative rounded-lg border p-3",
+                      isAnswered
+                        ? "border-green-500 bg-green-50/50"
+                        : "border-slate-200 bg-white/50",
+                    )}
+                  >
+                    <div className="mb-2 flex items-start gap-2">
+                      {isAnswered ? (
+                        <CheckCircleIcon
+                          size={16}
+                          className="mt-0.5 text-green-500"
+                          weight="bold"
+                        />
+                      ) : (
+                        <div className="mt-0.5 flex h-4 w-4 items-center justify-center rounded-full border border-slate-300 bg-white text-xs text-slate-500">
+                          {index + 1}
+                        </div>
+                      )}
+                      <div className="flex-1">
+                        <Text
+                          variant="small"
+                          className="mb-2 font-semibold text-slate-900"
+                        >
+                          {q.question}
+                        </Text>
+                        {q.example && (
+                          <Text
+                            variant="small"
+                            className="mb-2 italic text-slate-500"
+                          >
+                            Example: {q.example}
+                          </Text>
+                        )}
+                        <Input
+                          type="textarea"
+                          id={`clarification-${q.keyword}-${index}`}
+                          label={q.question}
+                          hideLabel
+                          placeholder="Your answer..."
+                          rows={2}
+                          value={answers[q.keyword] || ""}
+                          onChange={(e) =>
+                            handleAnswerChange(q.keyword, e.target.value)
+                          }
+                        />
+                      </div>
+                    </div>
+                  </div>
+                );
+              })}
+            </div>
+
+            <div className="flex gap-2">
+              <Button
+                onClick={handleSubmit}
+                disabled={!allAnswered}
+                className="flex-1"
+                variant="primary"
+              >
+                Submit Answers
+              </Button>
+              {onCancel && (
+                <Button onClick={onCancel} variant="outline">
+                  Cancel
+                </Button>
+              )}
+            </div>
+          </Card>
+        </div>
+      </div>
+    </div>
+  );
+}

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

@@ -0,0 +1,71 @@
+"use client";
+
+import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
+import { environment } from "@/services/environment";
+import { PostHogProvider as PHProvider } from "@posthog/react";
+import { usePathname, useSearchParams } from "next/navigation";
+import posthog from "posthog-js";
+import { ReactNode, useEffect, useRef } from "react";
+
+export function PostHogProvider({ children }: { children: ReactNode }) {
+  const isPostHogEnabled = environment.isPostHogEnabled();
+
+  useEffect(() => {
+    if (process.env.NEXT_PUBLIC_POSTHOG_KEY) {
+      posthog.init(process.env.NEXT_PUBLIC_POSTHOG_KEY, {
+        api_host: process.env.NEXT_PUBLIC_POSTHOG_HOST,
+        defaults: "2025-11-30",
+        capture_pageview: false,
+        capture_pageleave: true,
+        autocapture: true,
+      });
+    }
+  }, []);
+
+  if (!isPostHogEnabled) return <>{children}</>;
+
+  return <PHProvider client={posthog}>{children}</PHProvider>;
+}
+
+export function PostHogUserTracker() {
+  const { user, isUserLoading } = useSupabase();
+  const previousUserIdRef = useRef<string | null>(null);
+  const isPostHogEnabled = environment.isPostHogEnabled();
+
+  useEffect(() => {
+    if (isUserLoading || !isPostHogEnabled) return;
+
+    if (user) {
+      if (previousUserIdRef.current !== user.id) {
+        posthog.identify(user.id, {
+          email: user.email,
+          ...(user.user_metadata?.name && { name: user.user_metadata.name }),
+        });
+        previousUserIdRef.current = user.id;
+      }
+    } else if (previousUserIdRef.current !== null) {
+      posthog.reset();
+      previousUserIdRef.current = null;
+    }
+  }, [user, isUserLoading, isPostHogEnabled]);
+
+  return null;
+}
+
+export function PostHogPageViewTracker() {
+  const pathname = usePathname();
+  const searchParams = useSearchParams();
+  const isPostHogEnabled = environment.isPostHogEnabled();
+
+  useEffect(() => {
+    if (pathname && isPostHogEnabled) {
+      let url = window.origin + pathname;
+      if (searchParams && searchParams.toString()) {
+        url = url + `?${searchParams.toString()}`;
+      }
+      posthog.capture("$pageview", { $current_url: url });
+    }
+  }, [pathname, searchParams, isPostHogEnabled]);
+
+  return null;
+}

autogpt_platform/frontend/src/services/environment/index.ts

@@ -76,6 +76,13 @@ function getPreviewStealingDev() {
   return branch;
 }
 
+function getPostHogCredentials() {
+  return {
+    key: process.env.NEXT_PUBLIC_POSTHOG_KEY,
+    host: process.env.NEXT_PUBLIC_POSTHOG_HOST,
+  };
+}
+
 function isProductionBuild() {
   return process.env.NODE_ENV === "production";
 }
@@ -116,6 +123,13 @@ function areFeatureFlagsEnabled() {
   return process.env.NEXT_PUBLIC_LAUNCHDARKLY_ENABLED === "enabled";
 }
 
+function isPostHogEnabled() {
+  const inCloud = isCloud();
+  const key = process.env.NEXT_PUBLIC_POSTHOG_KEY;
+  const host = process.env.NEXT_PUBLIC_POSTHOG_HOST;
+  return inCloud && key && host;
+}
+
 export const environment = {
   // Generic
   getEnvironmentStr,
@@ -128,6 +142,7 @@ export const environment = {
   getSupabaseUrl,
   getSupabaseAnonKey,
   getPreviewStealingDev,
+  getPostHogCredentials,
   // Assertions
   isServerSide,
   isClientSide,
@@ -138,5 +153,6 @@ export const environment = {
   isCloud,
   isLocal,
   isVercelPreview,
+  isPostHogEnabled,
   areFeatureFlagsEnabled,
 };