feat(frontend): enhance UI components with animations and accessibility improvements

### Changes 🏗️
- Integrated `FadeIn` animations in `AgentsSection`, `FeaturedCreators`, `FeaturedSection`, `HeroSection`, and `BecomeACreator` components for improved visual appeal.
- Replaced static elements with `StaggeredList` in `FeaturedCreators` and `AgentsSection` for a more dynamic layout.
- Updated `SearchBar` to use `type="search"` and added `aria-label` for better accessibility.
- Enhanced `StoreCard` with focus-visible styles and keyboard navigation support.
- Refactored `FilterChips` to utilize `FilterChip` component for a more consistent design.

### Checklist 📋
- [x] Verified animations function correctly across components.
- [x] Ensured accessibility improvements are in place and tested.
- [x] Confirmed UI consistency with design specifications.

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

@@ -4,14 +4,9 @@ from collections.abc import AsyncGenerator
 from typing import Any
 
 import orjson
-from langfuse import Langfuse
-from openai import (
-    APIConnectionError,
-    APIError,
-    APIStatusError,
-    AsyncOpenAI,
-    RateLimitError,
-)
+from langfuse import get_client, propagate_attributes
+from langfuse.openai import openai  # type: ignore
+from openai import APIConnectionError, APIError, APIStatusError, RateLimitError
 from openai.types.chat import ChatCompletionChunk, ChatCompletionToolParam
 
 from backend.data.understanding import (
@@ -21,7 +16,6 @@ from backend.data.understanding import (
 from backend.util.exceptions import NotFoundError
 from backend.util.settings import Settings
 
-from . import db as chat_db
 from .config import ChatConfig
 from .model import (
     ChatMessage,
@@ -50,10 +44,10 @@ logger = logging.getLogger(__name__)
 
 config = ChatConfig()
 settings = Settings()
-client = AsyncOpenAI(api_key=config.api_key, base_url=config.base_url)
+client = openai.AsyncOpenAI(api_key=config.api_key, base_url=config.base_url)
 
-# Langfuse client (lazy initialization)
-_langfuse_client: Langfuse | None = None
+
+langfuse = get_client()
 
 
 class LangfuseNotConfiguredError(Exception):
@@ -69,65 +63,6 @@ def _is_langfuse_configured() -> bool:
     )
 
 
-def _get_langfuse_client() -> Langfuse:
-    """Get or create the Langfuse client for prompt management and tracing."""
-    global _langfuse_client
-    if _langfuse_client is None:
-        if not _is_langfuse_configured():
-            raise LangfuseNotConfiguredError(
-                "Langfuse is not configured. The chat feature requires Langfuse for prompt management. "
-                "Please set the LANGFUSE_PUBLIC_KEY and LANGFUSE_SECRET_KEY environment variables."
-            )
-        _langfuse_client = Langfuse(
-            public_key=settings.secrets.langfuse_public_key,
-            secret_key=settings.secrets.langfuse_secret_key,
-            host=settings.secrets.langfuse_host or "https://cloud.langfuse.com",
-        )
-    return _langfuse_client
-
-
-def _get_environment() -> str:
-    """Get the current environment name for Langfuse tagging."""
-    return settings.config.app_env.value
-
-
-def _get_langfuse_prompt() -> str:
-    """Fetch the latest production prompt from Langfuse.
-
-    Returns:
-        The compiled prompt text from Langfuse.
-
-    Raises:
-        Exception: If Langfuse is unavailable or prompt fetch fails.
-    """
-    try:
-        langfuse = _get_langfuse_client()
-        # cache_ttl_seconds=0 disables SDK caching to always get the latest prompt
-        prompt = langfuse.get_prompt(config.langfuse_prompt_name, cache_ttl_seconds=0)
-        compiled = prompt.compile()
-        logger.info(
-            f"Fetched prompt '{config.langfuse_prompt_name}' from Langfuse "
-            f"(version: {prompt.version})"
-        )
-        return compiled
-    except Exception as e:
-        logger.error(f"Failed to fetch prompt from Langfuse: {e}")
-        raise
-
-
-async def _is_first_session(user_id: str) -> bool:
-    """Check if this is the user's first chat session.
-
-    Returns True if the user has 1 or fewer sessions (meaning this is their first).
-    """
-    try:
-        session_count = await chat_db.get_user_session_count(user_id)
-        return session_count <= 1
-    except Exception as e:
-        logger.warning(f"Failed to check session count for user {user_id}: {e}")
-        return False  # Default to non-onboarding if we can't check
-
-
 async def _build_system_prompt(user_id: str | None) -> tuple[str, Any]:
     """Build the full system prompt including business understanding if available.
 
@@ -139,8 +74,6 @@ async def _build_system_prompt(user_id: str | None) -> tuple[str, Any]:
         Tuple of (compiled prompt string, Langfuse prompt object for tracing)
     """
 
-    langfuse = _get_langfuse_client()
-
     # cache_ttl_seconds=0 disables SDK caching to always get the latest prompt
     prompt = langfuse.get_prompt(config.langfuse_prompt_name, cache_ttl_seconds=0)
 
@@ -158,7 +91,7 @@ async def _build_system_prompt(user_id: str | None) -> tuple[str, Any]:
         context = "This is the first time you are meeting the user. Greet them and introduce them to the platform"
 
     compiled = prompt.compile(users_information=context)
-    return compiled, prompt
+    return compiled, understanding
 
 
 async def _generate_session_title(message: str) -> str | None:
@@ -217,6 +150,7 @@ async def assign_user_to_session(
 async def stream_chat_completion(
     session_id: str,
     message: str | None = None,
+    tool_call_response: str | None = None,
     is_user_message: bool = True,
     user_id: str | None = None,
     retry_count: int = 0,
@@ -256,11 +190,6 @@ async def stream_chat_completion(
         yield StreamFinish()
         return
 
-    # Langfuse observations will be created after session is loaded (need messages for input)
-    # Initialize to None so finally block can safely check and end them
-    trace = None
-    generation = None
-
     # Only fetch from Redis if session not provided (initial call)
     if session is None:
         session = await get_chat_session(session_id, user_id)
@@ -336,297 +265,259 @@ async def stream_chat_completion(
             asyncio.create_task(_update_title())
 
     # Build system prompt with business understanding
-    system_prompt, langfuse_prompt = await _build_system_prompt(user_id)
-
-    # Build input messages including system prompt for complete Langfuse logging
-    trace_input_messages = [{"role": "system", "content": system_prompt}] + [
-        m.model_dump() for m in session.messages
-    ]
+    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)
     # Using v3 SDK: start_observation creates a root span, update_trace sets trace-level attributes
-    try:
-        langfuse = _get_langfuse_client()
-        env = _get_environment()
-        trace = langfuse.start_observation(
-            name="chat_completion",
-            input={"messages": trace_input_messages},
-            metadata={
-                "environment": env,
-                "model": config.model,
-                "message_count": len(session.messages),
-                "prompt_name": langfuse_prompt.name if langfuse_prompt else None,
-                "prompt_version": langfuse_prompt.version if langfuse_prompt else None,
-            },
-        )
-        # Set trace-level attributes (session_id, user_id, tags)
-        trace.update_trace(
+    input = message
+    if not message and tool_call_response:
+        input = tool_call_response
+
+    langfuse = get_client()
+    with langfuse.start_as_current_observation(
+        as_type="span",
+        name="user-copilot-request",
+        input=input,
+    ) as span:
+        with propagate_attributes(
             session_id=session_id,
             user_id=user_id,
-            tags=[env, "copilot"],
-        )
-    except Exception as e:
-        logger.warning(f"Failed to create Langfuse trace: {e}")
+            tags=["copilot"],
+            metadata={
+                "users_information": format_understanding_for_prompt(understanding)[
+                    :200
+                ]  # langfuse only accepts upto to 200 chars
+            },
+        ):
 
-    # Initialize variables that will be used in finally block (must be defined before try)
-    assistant_response = ChatMessage(
-        role="assistant",
-        content="",
-    )
-    accumulated_tool_calls: list[dict[str, Any]] = []
-
-    # Wrap main logic in try/finally to ensure Langfuse observations are always ended
-    try:
-        has_yielded_end = False
-        has_yielded_error = False
-        has_done_tool_call = False
-        has_received_text = False
-        text_streaming_ended = False
-        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)
-
-        # Create Langfuse generation for each LLM call, linked to the prompt
-        # Using v3 SDK: start_observation with as_type="generation"
-        generation = (
-            trace.start_observation(
-                as_type="generation",
-                name="llm_call",
-                model=config.model,
-                input={"messages": trace_input_messages},
-                prompt=langfuse_prompt,
+            # Initialize variables that will be used in finally block (must be defined before try)
+            assistant_response = ChatMessage(
+                role="assistant",
+                content="",
             )
-            if trace
-            else None
-        )
+            accumulated_tool_calls: list[dict[str, Any]] = []
 
-        try:
-            async for chunk in _stream_chat_chunks(
-                session=session,
-                tools=tools,
-                system_prompt=system_prompt,
-                text_block_id=text_block_id,
-            ):
+            # Wrap main logic in try/finally to ensure Langfuse observations are always ended
+            has_yielded_end = False
+            has_yielded_error = False
+            has_done_tool_call = False
+            has_received_text = False
+            text_streaming_ended = False
+            tool_response_messages: list[ChatMessage] = []
+            should_retry = False
 
-                if isinstance(chunk, StreamTextStart):
-                    # Emit text-start before first text delta
-                    if not has_received_text:
+            # 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
                         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
-                    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
-                        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
+                    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
-                        has_yielded_end = True
                         yield chunk
-                elif isinstance(chunk, StreamError):
-                    has_yielded_error = True
-                elif isinstance(chunk, StreamUsage):
-                    session.usage.append(
-                        Usage(
-                            prompt_tokens=chunk.promptTokens,
-                            completion_tokens=chunk.completionTokens,
-                            total_tokens=chunk.totalTokens,
+                    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
+                            has_yielded_end = True
+                            yield chunk
+                    elif isinstance(chunk, StreamError):
+                        has_yielded_error = True
+                    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 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:
-                    logger.error(f"Unknown chunk type: {type(chunk)}", exc_info=True)
-        except Exception as e:
-            logger.error(f"Error during stream: {e!s}", exc_info=True)
+                    # Non-retryable error or max retries exceeded
+                    # Save any partial progress before reporting error
+                    messages_to_save: list[ChatMessage] = []
 
-            # Check if this is a retryable error (JSON parsing, incomplete tool calls, etc.)
-            is_retryable = isinstance(e, (orjson.JSONDecodeError, KeyError, TypeError))
+                    # Add assistant message if it has content or tool calls
+                    if accumulated_tool_calls:
+                        assistant_response.tool_calls = accumulated_tool_calls
+                    if assistant_response.content or assistant_response.tool_calls:
+                        messages_to_save.append(assistant_response)
 
-            if is_retryable and retry_count < config.max_retries:
+                    # Add tool response messages after assistant message
+                    messages_to_save.extend(tool_response_messages)
+
+                    session.messages.extend(messages_to_save)
+                    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"Retryable error encountered. Attempt {retry_count + 1}/{config.max_retries}"
+                    f"Retrying stream_chat_completion for session {session_id}, attempt {retry_count + 1}"
                 )
-                should_retry = True
-            else:
-                # Non-retryable error or max retries exceeded
-                # Save any partial progress before reporting error
-                messages_to_save: list[ChatMessage] = []
+                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
 
-                # Add assistant message if it has content or tool calls
-                if accumulated_tool_calls:
-                    assistant_response.tool_calls = accumulated_tool_calls
-                if 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)
-
-                session.messages.extend(messages_to_save)
-                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:
+            # Normal completion path - save session and handle tool call continuation
             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
-        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 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 [])}"
+                f"Normal completion path: session={session.session_id}, "
+                f"current message_count={len(session.messages)}"
             )
 
-        # 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)}"
-        )
+            # Build the messages list in the correct order
+            messages_to_save: list[ChatMessage] = []
 
-        session.messages.extend(messages_to_save)
-        logger.info(
-            f"Extended session messages, new message_count={len(session.messages)}"
-        )
-        await upsert_chat_session(session)
-
-        # 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,
-            ):
-                yield chunk
-
-    finally:
-        # Always end Langfuse observations to prevent resource leaks
-        # Guard against None and catch errors to avoid masking original exceptions
-        if generation is not None:
-            try:
-                latest_usage = session.usage[-1] if session.usage else None
-                generation.update(
-                    model=config.model,
-                    output={
-                        "content": assistant_response.content,
-                        "tool_calls": accumulated_tool_calls or None,
-                    },
-                    usage_details=(
-                        {
-                            "input": latest_usage.prompt_tokens,
-                            "output": latest_usage.completion_tokens,
-                            "total": latest_usage.total_tokens,
-                        }
-                        if latest_usage
-                        else None
-                    ),
+            # 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 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 [])}"
                 )
-                generation.end()
-            except Exception as e:
-                logger.warning(f"Failed to end Langfuse generation: {e}")
 
-        if trace is not None:
-            try:
-                if accumulated_tool_calls:
-                    trace.update_trace(output={"tool_calls": accumulated_tool_calls})
-                else:
-                    trace.update_trace(output={"response": assistant_response.content})
-                trace.end()
-            except Exception as e:
-                logger.warning(f"Failed to end Langfuse trace: {e}")
+            # 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)}"
+            )
+
+            session.messages.extend(messages_to_save)
+            logger.info(
+                f"Extended session messages, new message_count={len(session.messages)}"
+            )
+            await upsert_chat_session(session)
+
+            # 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
@@ -900,5 +791,4 @@ async def _yield_tool_call(
         session=session,
     )
 
-    logger.info(f"Yielding Tool execution response: {tool_execution_response}")
     yield tool_execution_response

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

@@ -30,7 +30,7 @@ TOOL_REGISTRY: dict[str, BaseTool] = {
     "find_library_agent": FindLibraryAgentTool(),
     "run_agent": RunAgentTool(),
     "run_block": RunBlockTool(),
-    "agent_output": AgentOutputTool(),
+    "view_agent_output": AgentOutputTool(),
     "search_docs": SearchDocsTool(),
     "get_doc_page": GetDocPageTool(),
 }

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

@@ -3,6 +3,8 @@
 import logging
 from typing import Any
 
+from langfuse import observe
+
 from backend.api.features.chat.model import ChatSession
 from backend.data.understanding import (
     BusinessUnderstandingInput,
@@ -59,6 +61,7 @@ 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

@@ -5,6 +5,7 @@ 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
@@ -103,7 +104,7 @@ class AgentOutputTool(BaseTool):
 
     @property
     def name(self) -> str:
-        return "agent_output"
+        return "view_agent_output"
 
     @property
     def description(self) -> str:
@@ -328,6 +329,7 @@ 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

@@ -3,6 +3,8 @@
 import logging
 from typing import Any
 
+from langfuse import observe
+
 from backend.api.features.chat.model import ChatSession
 
 from .agent_generator import (
@@ -78,6 +80,7 @@ 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

@@ -3,6 +3,8 @@
 import logging
 from typing import Any
 
+from langfuse import observe
+
 from backend.api.features.chat.model import ChatSession
 
 from .agent_generator import (
@@ -85,6 +87,7 @@ 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

@@ -2,6 +2,8 @@
 
 from typing import Any
 
+from langfuse import observe
+
 from backend.api.features.chat.model import ChatSession
 
 from .agent_search import search_agents
@@ -35,6 +37,7 @@ 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

@@ -1,6 +1,7 @@
 import logging
 from typing import Any
 
+from langfuse import observe
 from prisma.enums import ContentType
 
 from backend.api.features.chat.model import ChatSession
@@ -55,6 +56,7 @@ 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

@@ -2,6 +2,8 @@
 
 from typing import Any
 
+from langfuse import observe
+
 from backend.api.features.chat.model import ChatSession
 
 from .agent_search import search_agents
@@ -41,6 +43,7 @@ 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

@@ -4,6 +4,8 @@ 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 (
@@ -71,6 +73,7 @@ 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

@@ -3,6 +3,7 @@
 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
@@ -154,6 +155,7 @@ class RunAgentTool(BaseTool):
         """All operations require authentication."""
         return True
 
+    @observe(as_type="tool", name="run_agent")
     async def _execute(
         self,
         user_id: str | None,

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

@@ -4,6 +4,8 @@ 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
@@ -127,6 +129,7 @@ class RunBlockTool(BaseTool):
 
         return matched_credentials, missing_credentials
 
+    @observe(as_type="tool", name="run_block")
     async def _execute(
         self,
         user_id: str | None,

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

@@ -3,6 +3,7 @@
 import logging
 from typing import Any
 
+from langfuse import observe
 from prisma.enums import ContentType
 
 from backend.api.features.chat.model import ChatSession
@@ -87,6 +88,7 @@ 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/data/understanding.py

@@ -328,6 +328,8 @@ async def clear_business_understanding(user_id: str) -> bool:
 
 def format_understanding_for_prompt(understanding: BusinessUnderstanding) -> str:
     """Format business understanding as text for system prompt injection."""
+    if not understanding:
+        return ""
     sections = []
 
     # User info section

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

@@ -10,6 +10,7 @@ import { useRunInputDialog } from "./useRunInputDialog";
 import { CronSchedulerDialog } from "../CronSchedulerDialog/CronSchedulerDialog";
 import { useTutorialStore } from "@/app/(platform)/build/stores/tutorialStore";
 import { useEffect } from "react";
+import { CredentialsGroupedView } from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/CredentialsGroupedView";
 
 export const RunInputDialog = ({
   isOpen,
@@ -23,19 +24,17 @@ export const RunInputDialog = ({
   const hasInputs = useGraphStore((state) => state.hasInputs);
   const hasCredentials = useGraphStore((state) => state.hasCredentials);
   const inputSchema = useGraphStore((state) => state.inputSchema);
-  const credentialsSchema = useGraphStore(
-    (state) => state.credentialsInputSchema,
-  );
 
   const {
-    credentialsUiSchema,
+    credentialFields,
+    requiredCredentials,
     handleManualRun,
     handleInputChange,
     openCronSchedulerDialog,
     setOpenCronSchedulerDialog,
     inputValues,
     credentialValues,
-    handleCredentialChange,
+    handleCredentialFieldChange,
     isExecutingGraph,
   } = useRunInputDialog({ setIsOpen });
 
@@ -67,7 +66,7 @@ export const RunInputDialog = ({
         <Dialog.Content>
           <div className="space-y-6 p-1" data-id="run-input-dialog-content">
             {/* Credentials Section */}
-            {hasCredentials() && (
+            {hasCredentials() && credentialFields.length > 0 && (
               <div data-id="run-input-credentials-section">
                 <div className="mb-4">
                   <Text variant="h4" className="text-gray-900">
@@ -75,16 +74,12 @@ export const RunInputDialog = ({
                   </Text>
                 </div>
                 <div className="px-2" data-id="run-input-credentials-form">
-                  <FormRenderer
-                    jsonSchema={credentialsSchema as RJSFSchema}
-                    handleChange={(v) => handleCredentialChange(v.formData)}
-                    uiSchema={credentialsUiSchema}
-                    initialValues={{}}
-                    formContext={{
-                      showHandles: false,
-                      size: "large",
-                      showOptionalToggle: false,
-                    }}
+                  <CredentialsGroupedView
+                    credentialFields={credentialFields}
+                    requiredCredentials={requiredCredentials}
+                    inputCredentials={credentialValues}
+                    inputValues={inputValues}
+                    onCredentialChange={handleCredentialFieldChange}
                   />
                 </div>
               </div>

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

@@ -7,12 +7,11 @@ import {
   GraphExecutionMeta,
 } from "@/lib/autogpt-server-api";
 import { parseAsInteger, parseAsString, useQueryStates } from "nuqs";
-import { useMemo, useState } from "react";
-import { uiSchema } from "../../../FlowEditor/nodes/uiSchema";
-import { isCredentialFieldSchema } from "@/components/renderers/InputRenderer/custom/CredentialField/helpers";
+import { useCallback, useMemo, useState } from "react";
 import { useNodeStore } from "@/app/(platform)/build/stores/nodeStore";
 import { useToast } from "@/components/molecules/Toast/use-toast";
 import { useReactFlow } from "@xyflow/react";
+import type { CredentialField } from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/helpers";
 
 export const useRunInputDialog = ({
   setIsOpen,
@@ -120,27 +119,32 @@ export const useRunInputDialog = ({
       },
     });
 
-  // We are rendering the credentials field differently compared to other fields.
-  // In the node, we have the field name as "credential" - so our library catches it and renders it differently.
-  // But here we have a different name, something like `Firecrawl credentials`, so here we are telling the library that this field is a credential field type.
+  // Convert credentials schema to credential fields array for CredentialsGroupedView
+  const credentialFields: CredentialField[] = useMemo(() => {
+    if (!credentialsSchema?.properties) return [];
+    return Object.entries(credentialsSchema.properties);
+  }, [credentialsSchema]);
 
-  const credentialsUiSchema = useMemo(() => {
-    const dynamicUiSchema: any = { ...uiSchema };
+  // Get required credentials as a Set
+  const requiredCredentials = useMemo(() => {
+    return new Set<string>(credentialsSchema?.required || []);
+  }, [credentialsSchema]);
 
-    if (credentialsSchema?.properties) {
-      Object.keys(credentialsSchema.properties).forEach((fieldName) => {
-        const fieldSchema = credentialsSchema.properties[fieldName];
-        if (isCredentialFieldSchema(fieldSchema)) {
-          dynamicUiSchema[fieldName] = {
-            ...dynamicUiSchema[fieldName],
-            "ui:field": "custom/credential_field",
-          };
+  // Handler for individual credential changes
+  const handleCredentialFieldChange = useCallback(
+    (key: string, value?: CredentialsMetaInput) => {
+      setCredentialValues((prev) => {
+        if (value) {
+          return { ...prev, [key]: value };
+        } else {
+          const next = { ...prev };
+          delete next[key];
+          return next;
         }
       });
-    }
-
-    return dynamicUiSchema;
-  }, [credentialsSchema]);
+    },
+    [],
+  );
 
   const handleManualRun = async () => {
     // Filter out incomplete credentials (those without a valid id)
@@ -173,12 +177,14 @@ export const useRunInputDialog = ({
   };
 
   return {
-    credentialsUiSchema,
+    credentialFields,
+    requiredCredentials,
     inputValues,
     credentialValues,
     isExecutingGraph,
     handleInputChange,
     handleCredentialChange,
+    handleCredentialFieldChange,
     handleManualRun,
     openCronSchedulerDialog,
     setOpenCronSchedulerDialog,

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/Flow/useFlow.ts

@@ -139,14 +139,6 @@ export const useFlow = () => {
       useNodeStore.getState().setNodes([]);
       useNodeStore.getState().clearResolutionState();
       addNodes(customNodes);
-
-      // Sync hardcoded values with handle IDs.
-      // If a key–value field has a key without a value, the backend omits it from hardcoded values.
-      // But if a handleId exists for that key, it causes inconsistency.
-      // This ensures hardcoded values stay in sync with handle IDs.
-      customNodes.forEach((node) => {
-        useNodeStore.getState().syncHardcodedValuesWithHandleIds(node.id);
-      });
     }
   }, [customNodes, addNodes]);
 
@@ -158,6 +150,14 @@ export const useFlow = () => {
     }
   }, [graph?.links, addLinks]);
 
+  useEffect(() => {
+    if (customNodes.length > 0 && graph?.links) {
+      customNodes.forEach((node) => {
+        useNodeStore.getState().syncHardcodedValuesWithHandleIds(node.id);
+      });
+    }
+  }, [customNodes, graph?.links]);
+
   // update node execution status in nodes
   useEffect(() => {
     if (

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

@@ -1,22 +1,21 @@
 import { Button } from "@/components/atoms/Button/Button";
 import { Text } from "@/components/atoms/Text/Text";
+import {
+  Accordion,
+  AccordionContent,
+  AccordionItem,
+  AccordionTrigger,
+} from "@/components/molecules/Accordion/Accordion";
 import { beautifyString, cn } from "@/lib/utils";
-import { CaretDownIcon, CopyIcon, CheckIcon } from "@phosphor-icons/react";
+import { CopyIcon, CheckIcon } from "@phosphor-icons/react";
 import { NodeDataViewer } from "./components/NodeDataViewer/NodeDataViewer";
 import { ContentRenderer } from "./components/ContentRenderer";
 import { useNodeOutput } from "./useNodeOutput";
 import { ViewMoreData } from "./components/ViewMoreData";
 
 export const NodeDataRenderer = ({ nodeId }: { nodeId: string }) => {
-  const {
-    outputData,
-    isExpanded,
-    setIsExpanded,
-    copiedKey,
-    handleCopy,
-    executionResultId,
-    inputData,
-  } = useNodeOutput(nodeId);
+  const { outputData, copiedKey, handleCopy, executionResultId, inputData } =
+    useNodeOutput(nodeId);
 
   if (Object.keys(outputData).length === 0) {
     return null;
@@ -25,122 +24,117 @@ export const NodeDataRenderer = ({ nodeId }: { nodeId: string }) => {
   return (
     <div
       data-tutorial-id={`node-output`}
-      className="flex flex-col gap-3 rounded-b-xl border-t border-zinc-200 px-4 py-4"
+      className="rounded-b-xl border-t border-zinc-200 px-4 py-2"
     >
-      <div className="flex items-center justify-between">
-        <Text variant="body-medium" className="!font-semibold text-slate-700">
-          Node Output
-        </Text>
-        <Button
-          variant="ghost"
-          size="small"
-          onClick={() => setIsExpanded(!isExpanded)}
-          className="h-fit min-w-0 p-1 text-slate-600 hover:text-slate-900"
-        >
-          <CaretDownIcon
-            size={16}
-            weight="bold"
-            className={`transition-transform ${isExpanded ? "rotate-180" : ""}`}
-          />
-        </Button>
-      </div>
+      <Accordion type="single" collapsible defaultValue="node-output">
+        <AccordionItem value="node-output" className="border-none">
+          <AccordionTrigger className="py-2 hover:no-underline">
+            <Text
+              variant="body-medium"
+              className="!font-semibold text-slate-700"
+            >
+              Node Output
+            </Text>
+          </AccordionTrigger>
+          <AccordionContent className="pt-2">
+            <div className="flex max-w-[350px] flex-col gap-4">
+              <div className="space-y-2">
+                <Text variant="small-medium">Input</Text>
 
-      {isExpanded && (
-        <>
-          <div className="flex max-w-[350px] flex-col gap-4">
-            <div className="space-y-2">
-              <Text variant="small-medium">Input</Text>
+                <ContentRenderer value={inputData} shortContent={false} />
 
-              <ContentRenderer value={inputData} shortContent={false} />
-
-              <div className="mt-1 flex justify-end gap-1">
-                <NodeDataViewer
-                  data={inputData}
-                  pinName="Input"
-                  execId={executionResultId}
-                />
-                <Button
-                  variant="secondary"
-                  size="small"
-                  onClick={() => handleCopy("input", inputData)}
-                  className={cn(
-                    "h-fit min-w-0 gap-1.5 border border-zinc-200 p-2 text-black hover:text-slate-900",
-                    copiedKey === "input" &&
-                      "border-green-400 bg-green-100 hover:border-green-400 hover:bg-green-200",
-                  )}
-                >
-                  {copiedKey === "input" ? (
-                    <CheckIcon size={12} className="text-green-600" />
-                  ) : (
-                    <CopyIcon size={12} />
-                  )}
-                </Button>
+                <div className="mt-1 flex justify-end gap-1">
+                  <NodeDataViewer
+                    data={inputData}
+                    pinName="Input"
+                    execId={executionResultId}
+                  />
+                  <Button
+                    variant="secondary"
+                    size="small"
+                    onClick={() => handleCopy("input", inputData)}
+                    className={cn(
+                      "h-fit min-w-0 gap-1.5 border border-zinc-200 p-2 text-black hover:text-slate-900",
+                      copiedKey === "input" &&
+                        "border-green-400 bg-green-100 hover:border-green-400 hover:bg-green-200",
+                    )}
+                  >
+                    {copiedKey === "input" ? (
+                      <CheckIcon size={12} className="text-green-600" />
+                    ) : (
+                      <CopyIcon size={12} />
+                    )}
+                  </Button>
+                </div>
               </div>
-            </div>
 
-            {Object.entries(outputData)
-              .slice(0, 2)
-              .map(([key, value]) => (
-                <div key={key} className="flex flex-col gap-2">
-                  <div className="flex items-center gap-2">
-                    <Text
-                      variant="small-medium"
-                      className="!font-semibold text-slate-600"
-                    >
-                      Pin:
-                    </Text>
-                    <Text variant="small" className="text-slate-700">
-                      {beautifyString(key)}
-                    </Text>
-                  </div>
-                  <div className="w-full space-y-2">
-                    <Text
-                      variant="small"
-                      className="!font-semibold text-slate-600"
-                    >
-                      Data:
-                    </Text>
-                    <div className="relative space-y-2">
-                      {value.map((item, index) => (
-                        <div key={index}>
-                          <ContentRenderer value={item} shortContent={true} />
+              {Object.entries(outputData)
+                .slice(0, 2)
+                .map(([key, value]) => (
+                  <div key={key} className="flex flex-col gap-2">
+                    <div className="flex items-center gap-2">
+                      <Text
+                        variant="small-medium"
+                        className="!font-semibold text-slate-600"
+                      >
+                        Pin:
+                      </Text>
+                      <Text variant="small" className="text-slate-700">
+                        {beautifyString(key)}
+                      </Text>
+                    </div>
+                    <div className="w-full space-y-2">
+                      <Text
+                        variant="small"
+                        className="!font-semibold text-slate-600"
+                      >
+                        Data:
+                      </Text>
+                      <div className="relative space-y-2">
+                        {value.map((item, index) => (
+                          <div key={index}>
+                            <ContentRenderer value={item} shortContent={true} />
+                          </div>
+                        ))}
+
+                        <div className="mt-1 flex justify-end gap-1">
+                          <NodeDataViewer
+                            data={value}
+                            pinName={key}
+                            execId={executionResultId}
+                          />
+                          <Button
+                            variant="secondary"
+                            size="small"
+                            onClick={() => handleCopy(key, value)}
+                            className={cn(
+                              "h-fit min-w-0 gap-1.5 border border-zinc-200 p-2 text-black hover:text-slate-900",
+                              copiedKey === key &&
+                                "border-green-400 bg-green-100 hover:border-green-400 hover:bg-green-200",
+                            )}
+                          >
+                            {copiedKey === key ? (
+                              <CheckIcon size={12} className="text-green-600" />
+                            ) : (
+                              <CopyIcon size={12} />
+                            )}
+                          </Button>
                         </div>
-                      ))}
-
-                      <div className="mt-1 flex justify-end gap-1">
-                        <NodeDataViewer
-                          data={value}
-                          pinName={key}
-                          execId={executionResultId}
-                        />
-                        <Button
-                          variant="secondary"
-                          size="small"
-                          onClick={() => handleCopy(key, value)}
-                          className={cn(
-                            "h-fit min-w-0 gap-1.5 border border-zinc-200 p-2 text-black hover:text-slate-900",
-                            copiedKey === key &&
-                              "border-green-400 bg-green-100 hover:border-green-400 hover:bg-green-200",
-                          )}
-                        >
-                          {copiedKey === key ? (
-                            <CheckIcon size={12} className="text-green-600" />
-                          ) : (
-                            <CopyIcon size={12} />
-                          )}
-                        </Button>
                       </div>
                     </div>
                   </div>
-                </div>
-              ))}
-          </div>
+                ))}
+            </div>
 
-          {Object.keys(outputData).length > 2 && (
-            <ViewMoreData outputData={outputData} execId={executionResultId} />
-          )}
-        </>
-      )}
+            {Object.keys(outputData).length > 2 && (
+              <ViewMoreData
+                outputData={outputData}
+                execId={executionResultId}
+              />
+            )}
+          </AccordionContent>
+        </AccordionItem>
+      </Accordion>
     </div>
   );
 };

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

@@ -4,7 +4,6 @@ import { useShallow } from "zustand/react/shallow";
 import { useState } from "react";
 
 export const useNodeOutput = (nodeId: string) => {
-  const [isExpanded, setIsExpanded] = useState(true);
   const [copiedKey, setCopiedKey] = useState<string | null>(null);
   const { toast } = useToast();
 
@@ -37,13 +36,10 @@ export const useNodeOutput = (nodeId: string) => {
     }
   };
   return {
-    outputData: outputData,
-    inputData: inputData,
-    isExpanded: isExpanded,
-    setIsExpanded: setIsExpanded,
-    copiedKey: copiedKey,
-    setCopiedKey: setCopiedKey,
-    handleCopy: handleCopy,
+    outputData,
+    inputData,
+    copiedKey,
+    handleCopy,
     executionResultId: nodeExecutionResult?.node_exec_id,
   };
 };

autogpt_platform/frontend/src/app/(platform)/build/components/helper.ts

@@ -61,12 +61,18 @@ export const convertNodesPlusBlockInfoIntoCustomNodes = (
   return customNode;
 };
 
+const isToolSourceName = (sourceName: string): boolean =>
+  sourceName.startsWith("tools_^_");
+
+const cleanupSourceName = (sourceName: string): string =>
+  isToolSourceName(sourceName) ? "tools" : sourceName;
+
 export const linkToCustomEdge = (link: Link): CustomEdge => ({
   id: link.id ?? "",
   type: "custom" as const,
   source: link.source_id,
   target: link.sink_id,
-  sourceHandle: link.source_name,
+  sourceHandle: cleanupSourceName(link.source_name),
   targetHandle: link.sink_name,
   data: {
     isStatic: link.is_static,

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentModal/components/ModalRunSection/ModalRunSection.tsx

@@ -1,9 +1,9 @@
 import { Input } from "@/components/atoms/Input/Input";
+import { CredentialsGroupedView } from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/CredentialsGroupedView";
 import { InformationTooltip } from "@/components/molecules/InformationTooltip/InformationTooltip";
 import { useMemo } from "react";
 import { RunAgentInputs } from "../../../RunAgentInputs/RunAgentInputs";
 import { useRunAgentModalContext } from "../../context";
-import { CredentialsGroupedView } from "../CredentialsGroupedView/CredentialsGroupedView";
 import { ModalSection } from "../ModalSection/ModalSection";
 import { WebhookTriggerBanner } from "../WebhookTriggerBanner/WebhookTriggerBanner";
 
@@ -19,6 +19,8 @@ export function ModalRunSection() {
     setInputValue,
     agentInputFields,
     agentCredentialsInputFields,
+    inputCredentials,
+    setInputCredentialsValue,
   } = useRunAgentModalContext();
 
   const inputFields = Object.entries(agentInputFields || {});
@@ -102,6 +104,9 @@ export function ModalRunSection() {
           <CredentialsGroupedView
             credentialFields={credentialFields}
             requiredCredentials={requiredCredentials}
+            inputCredentials={inputCredentials}
+            inputValues={inputValues}
+            onCredentialChange={setInputCredentialsValue}
           />
         </ModalSection>
       ) : null}

autogpt_platform/frontend/src/app/(platform)/marketplace/components/AgentsSection/AgentsSection.tsx

@@ -5,6 +5,8 @@ import {
   CarouselContent,
   CarouselItem,
 } from "@/components/__legacy__/ui/carousel";
+import { FadeIn } from "@/components/molecules/FadeIn/FadeIn";
+import { StaggeredList } from "@/components/molecules/StaggeredList/StaggeredList";
 import { useAgentsSection } from "./useAgentsSection";
 import { StoreAgent } from "@/app/api/__generated__/models/storeAgent";
 import { StoreCard } from "../StoreCard/StoreCard";
@@ -41,12 +43,14 @@ export const AgentsSection = ({
   return (
     <div className="flex flex-col items-center justify-center">
       <div className="w-full max-w-[1360px]">
-        <h2
-          style={{ marginBottom: margin }}
-          className="font-poppins text-lg font-semibold text-[#282828] dark:text-neutral-200"
-        >
-          {sectionTitle}
-        </h2>
+        <FadeIn direction="left" duration={0.5}>
+          <h2
+            style={{ marginBottom: margin }}
+            className="font-poppins text-lg font-semibold text-neutral-800 dark:text-neutral-200"
+          >
+            {sectionTitle}
+          </h2>
+        </FadeIn>
         {!displayedAgents || displayedAgents.length === 0 ? (
           <div className="text-center text-gray-500 dark:text-gray-400">
             No agents found
@@ -54,32 +58,38 @@ export const AgentsSection = ({
         ) : (
           <>
             {/* Mobile Carousel View */}
-            <Carousel
-              className="md:hidden"
-              opts={{
-                loop: true,
-              }}
-            >
-              <CarouselContent>
-                {displayedAgents.map((agent, index) => (
-                  <CarouselItem key={index} className="min-w-64 max-w-71">
-                    <StoreCard
-                      agentName={agent.agent_name}
-                      agentImage={agent.agent_image}
-                      description={agent.description}
-                      runs={agent.runs}
-                      rating={agent.rating}
-                      avatarSrc={agent.creator_avatar}
-                      creatorName={agent.creator}
-                      hideAvatar={hideAvatars}
-                      onClick={() => handleCardClick(agent.creator, agent.slug)}
-                    />
-                  </CarouselItem>
-                ))}
-              </CarouselContent>
-            </Carousel>
+            <FadeIn direction="up" className="md:hidden">
+              <Carousel
+                opts={{
+                  loop: true,
+                }}
+              >
+                <CarouselContent>
+                  {displayedAgents.map((agent, index) => (
+                    <CarouselItem key={index} className="min-w-64 max-w-71">
+                      <StoreCard
+                        agentName={agent.agent_name}
+                        agentImage={agent.agent_image}
+                        description={agent.description}
+                        runs={agent.runs}
+                        rating={agent.rating}
+                        avatarSrc={agent.creator_avatar}
+                        creatorName={agent.creator}
+                        hideAvatar={hideAvatars}
+                        onClick={() => handleCardClick(agent.creator, agent.slug)}
+                      />
+                    </CarouselItem>
+                  ))}
+                </CarouselContent>
+              </Carousel>
+            </FadeIn>
 
-            <div className="hidden grid-cols-1 place-items-center gap-6 md:grid md:grid-cols-2 lg:grid-cols-3 2xl:grid-cols-4">
+            {/* Desktop Grid View with Staggered Animation */}
+            <StaggeredList
+              direction="up"
+              staggerDelay={0.08}
+              className="hidden grid-cols-1 place-items-center gap-6 md:grid md:grid-cols-2 lg:grid-cols-3 2xl:grid-cols-4"
+            >
               {displayedAgents.map((agent, index) => (
                 <StoreCard
                   key={index}
@@ -94,7 +104,7 @@ export const AgentsSection = ({
                   onClick={() => handleCardClick(agent.creator, agent.slug)}
                 />
               ))}
-            </div>
+            </StaggeredList>
           </>
         )}
       </div>

autogpt_platform/frontend/src/app/(platform)/marketplace/components/BecomeACreator/BecomeACreator.tsx

@@ -38,7 +38,7 @@ export function BecomeACreator({
 
         <PublishAgentModal
           trigger={
-            <button className="inline-flex h-[48px] cursor-pointer items-center justify-center rounded-[38px] bg-neutral-800 px-8 py-3 transition-colors hover:bg-neutral-700 dark:bg-neutral-700 dark:hover:bg-neutral-600 md:h-[56px] md:px-10 md:py-4 lg:h-[68px] lg:px-12 lg:py-5">
+            <button className="inline-flex h-[48px] cursor-pointer items-center justify-center rounded-[38px] bg-neutral-800 px-8 py-3 transition-colors hover:bg-neutral-700 focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-neutral-950 focus-visible:ring-offset-2 dark:bg-neutral-700 dark:hover:bg-neutral-600 dark:focus-visible:ring-neutral-50 md:h-[56px] md:px-10 md:py-4 lg:h-[68px] lg:px-12 lg:py-5">
               <span className="whitespace-nowrap font-poppins text-base font-medium leading-normal text-neutral-50 md:text-lg md:leading-relaxed lg:text-xl lg:leading-7">
                 {buttonText}
               </span>

autogpt_platform/frontend/src/app/(platform)/marketplace/components/CreatorCard/CreatorCard.tsx

@@ -20,9 +20,18 @@ export const CreatorCard = ({
 }: CreatorCardProps) => {
   return (
     <div
-      className={`h-[264px] w-full px-[18px] pb-5 pt-6 ${backgroundColor(index)} inline-flex cursor-pointer flex-col items-start justify-start gap-3.5 rounded-[26px] transition-all duration-200 hover:brightness-95`}
+      className={`h-[264px] w-full px-[18px] pb-5 pt-6 ${backgroundColor(index)} inline-flex cursor-pointer flex-col items-start justify-start gap-3.5 rounded-[26px] transition-[filter] duration-200 hover:brightness-95 focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-neutral-950 focus-visible:ring-offset-2 dark:focus-visible:ring-neutral-50`}
       onClick={onClick}
+      onKeyDown={(e) => {
+        if (e.key === "Enter" || e.key === " ") {
+          e.preventDefault();
+          onClick();
+        }
+      }}
       data-testid="creator-card"
+      role="button"
+      tabIndex={0}
+      aria-label={`View ${creatorName}'s profile - ${agentsUploaded} agents`}
     >
       <div className="relative h-[64px] w-[64px]">
         <div className="absolute inset-0 overflow-hidden rounded-full">

autogpt_platform/frontend/src/app/(platform)/marketplace/components/FeaturedCreators/FeaturedCreators.tsx

@@ -1,5 +1,7 @@
 "use client";
 
+import { FadeIn } from "@/components/molecules/FadeIn/FadeIn";
+import { StaggeredList } from "@/components/molecules/StaggeredList/StaggeredList";
 import { CreatorCard } from "../CreatorCard/CreatorCard";
 import { useFeaturedCreators } from "./useFeaturedCreators";
 import { Creator } from "@/app/api/__generated__/models/creator";
@@ -19,11 +21,17 @@ export const FeaturedCreators = ({
   return (
     <div className="flex w-full flex-col items-center justify-center">
       <div className="w-full max-w-[1360px]">
-        <h2 className="mb-9 font-poppins text-lg font-semibold text-neutral-800 dark:text-neutral-200">
-          {title}
-        </h2>
+        <FadeIn direction="left" duration={0.5}>
+          <h2 className="mb-9 font-poppins text-lg font-semibold text-neutral-800 dark:text-neutral-200">
+            {title}
+          </h2>
+        </FadeIn>
 
-        <div className="grid grid-cols-1 gap-6 md:grid-cols-2 lg:grid-cols-4">
+        <StaggeredList
+          direction="up"
+          staggerDelay={0.1}
+          className="grid grid-cols-1 gap-6 md:grid-cols-2 lg:grid-cols-4"
+        >
           {displayedCreators.map((creator, index) => (
             <CreatorCard
               key={index}
@@ -35,7 +43,7 @@ export const FeaturedCreators = ({
               index={index}
             />
           ))}
-        </div>
+        </StaggeredList>
       </div>
     </div>
   );

autogpt_platform/frontend/src/app/(platform)/marketplace/components/FeaturedSection/FeaturedSection.tsx

@@ -8,6 +8,7 @@ import {
   CarouselNext,
   CarouselIndicator,
 } from "@/components/__legacy__/ui/carousel";
+import { FadeIn } from "@/components/molecules/FadeIn/FadeIn";
 import Link from "next/link";
 import { useFeaturedSection } from "./useFeaturedSection";
 import { StoreAgent } from "@/app/api/__generated__/models/storeAgent";
@@ -25,40 +26,44 @@ export const FeaturedSection = ({ featuredAgents }: FeaturedSectionProps) => {
 
   return (
     <section className="w-full">
-      <h2 className="mb-8 font-poppins text-2xl font-semibold leading-7 text-neutral-800 dark:text-neutral-200">
-        Featured agents
-      </h2>
+      <FadeIn direction="left" duration={0.5}>
+        <h2 className="mb-8 font-poppins text-2xl font-semibold leading-7 text-neutral-800 dark:text-neutral-200">
+          Featured agents
+        </h2>
+      </FadeIn>
 
-      <Carousel
-        opts={{
-          align: "center",
-          containScroll: "trimSnaps",
-        }}
-      >
-        <CarouselContent>
-          {featuredAgents.map((agent, index) => (
-            <CarouselItem
-              key={index}
-              className="h-[480px] md:basis-1/2 lg:basis-1/3"
-            >
-              <Link
-                href={`/marketplace/agent/${encodeURIComponent(agent.creator)}/${encodeURIComponent(agent.slug)}`}
-                className="block h-full"
+      <FadeIn direction="up" duration={0.6} delay={0.1}>
+        <Carousel
+          opts={{
+            align: "center",
+            containScroll: "trimSnaps",
+          }}
+        >
+          <CarouselContent>
+            {featuredAgents.map((agent, index) => (
+              <CarouselItem
+                key={index}
+                className="h-[480px] md:basis-1/2 lg:basis-1/3"
               >
-                <FeaturedAgentCard
-                  agent={agent}
-                  backgroundColor={getBackgroundColor(index)}
-                />
-              </Link>
-            </CarouselItem>
-          ))}
-        </CarouselContent>
-        <div className="relative mt-4">
-          <CarouselIndicator />
-          <CarouselPrevious afterClick={handlePrevSlide} />
-          <CarouselNext afterClick={handleNextSlide} />
-        </div>
-      </Carousel>
+                <Link
+                  href={`/marketplace/agent/${encodeURIComponent(agent.creator)}/${encodeURIComponent(agent.slug)}`}
+                  className="block h-full"
+                >
+                  <FeaturedAgentCard
+                    agent={agent}
+                    backgroundColor={getBackgroundColor(index)}
+                  />
+                </Link>
+              </CarouselItem>
+            ))}
+          </CarouselContent>
+          <div className="relative mt-4">
+            <CarouselIndicator />
+            <CarouselPrevious afterClick={handlePrevSlide} />
+            <CarouselNext afterClick={handleNextSlide} />
+          </div>
+        </Carousel>
+      </FadeIn>
     </section>
   );
 };

autogpt_platform/frontend/src/app/(platform)/marketplace/components/FilterChips/FilterChips.tsx

@@ -1,6 +1,6 @@
 "use client";
 
-import { Badge } from "@/components/__legacy__/ui/badge";
+import { FilterChip } from "@/components/atoms/FilterChip/FilterChip";
 import { useFilterChips } from "./useFilterChips";
 
 interface FilterChipsProps {
@@ -9,8 +9,6 @@ interface FilterChipsProps {
   multiSelect?: boolean;
 }
 
-// Some flaws in its logic
-// FRONTEND-TODO : This needs to be fixed
 export const FilterChips = ({
   badges,
   onFilterChange,
@@ -22,18 +20,20 @@ export const FilterChips = ({
   });
 
   return (
-    <div className="flex h-auto min-h-8 flex-wrap items-center justify-center gap-3 lg:min-h-14 lg:justify-start lg:gap-5">
+    <div
+      className="flex h-auto min-h-8 flex-wrap items-center justify-center gap-3 lg:min-h-14 lg:justify-start lg:gap-5"
+      role="group"
+      aria-label="Filter options"
+    >
       {badges.map((badge) => (
-        <Badge
+        <FilterChip
           key={badge}
-          variant={selectedFilters.includes(badge) ? "secondary" : "outline"}
-          className="mb-2 flex cursor-pointer items-center justify-center gap-2 rounded-full border border-black/50 px-3 py-1 dark:border-white/50 lg:mb-3 lg:gap-2.5 lg:px-6 lg:py-2"
+          label={badge}
+          selected={selectedFilters.includes(badge)}
           onClick={() => handleBadgeClick(badge)}
-        >
-          <div className="text-sm font-light tracking-tight text-[#474747] dark:text-[#e0e0e0] lg:text-xl lg:font-medium lg:leading-9">
-            {badge}
-          </div>
-        </Badge>
+          size="lg"
+          className="mb-2 lg:mb-3"
+        />
       ))}
     </div>
   );

autogpt_platform/frontend/src/app/(platform)/marketplace/components/HeroSection/HeroSection.tsx

@@ -1,5 +1,6 @@
 "use client";
 
+import { FadeIn } from "@/components/molecules/FadeIn/FadeIn";
 import { FilterChips } from "../FilterChips/FilterChips";
 import { SearchBar } from "../SearchBar/SearchBar";
 import { useHeroSection } from "./useHeroSection";
@@ -9,30 +10,36 @@ export const HeroSection = () => {
   return (
     <div className="mb-2 mt-8 flex flex-col items-center justify-center px-4 sm:mb-4 sm:mt-12 sm:px-6 md:mb-6 md:mt-16 lg:my-24 lg:px-8 xl:my-16">
       <div className="w-full max-w-3xl lg:max-w-4xl xl:max-w-5xl">
-        <div className="mb-4 text-center md:mb-8">
-          <h1 className="text-center">
-            <span className="font-poppins text-[48px] font-semibold leading-[54px] text-neutral-950 dark:text-neutral-50">
-              Explore AI agents built for{" "}
-            </span>
-            <span className="font-poppins text-[48px] font-semibold leading-[54px] text-violet-600">
-              you
-            </span>
-            <br />
-            <span className="font-poppins text-[48px] font-semibold leading-[54px] text-neutral-950 dark:text-neutral-50">
-              by the{" "}
-            </span>
-            <span className="font-poppins text-[48px] font-semibold leading-[54px] text-blue-500">
-              community
-            </span>
-          </h1>
-        </div>
-        <h3 className="mb:text-2xl mb-6 text-center font-sans text-xl font-normal leading-loose text-neutral-700 dark:text-neutral-300 md:mb-12">
-          Bringing you AI agents designed by thinkers from around the world
-        </h3>
-        <div className="mb-4 flex justify-center sm:mb-5">
-          <SearchBar height="h-[74px]" />
-        </div>
-        <div>
+        <FadeIn direction="down" duration={0.6} delay={0}>
+          <div className="mb-4 text-center md:mb-8">
+            <h1 className="text-center">
+              <span className="font-poppins text-[48px] font-semibold leading-[54px] text-neutral-950 dark:text-neutral-50">
+                Explore AI agents built for{" "}
+              </span>
+              <span className="font-poppins text-[48px] font-semibold leading-[54px] text-violet-600">
+                you
+              </span>
+              <br />
+              <span className="font-poppins text-[48px] font-semibold leading-[54px] text-neutral-950 dark:text-neutral-50">
+                by the{" "}
+              </span>
+              <span className="font-poppins text-[48px] font-semibold leading-[54px] text-blue-500">
+                community
+              </span>
+            </h1>
+          </div>
+        </FadeIn>
+        <FadeIn direction="up" duration={0.6} delay={0.15}>
+          <h3 className="mb:text-2xl mb-6 text-center font-sans text-xl font-normal leading-loose text-neutral-700 dark:text-neutral-300 md:mb-12">
+            Bringing you AI agents designed by thinkers from around the world
+          </h3>
+        </FadeIn>
+        <FadeIn direction="up" duration={0.5} delay={0.3}>
+          <div className="mb-4 flex justify-center sm:mb-5">
+            <SearchBar height="h-[74px]" />
+          </div>
+        </FadeIn>
+        <FadeIn direction="up" duration={0.5} delay={0.4}>
           <div className="flex justify-center">
             <FilterChips
               badges={searchTerms}
@@ -40,7 +47,7 @@ export const HeroSection = () => {
               multiSelect={false}
             />
           </div>
-        </div>
+        </FadeIn>
       </div>
     </div>
   );

autogpt_platform/frontend/src/app/(platform)/marketplace/components/MainMarketplacePage/MainMarketplacePage.tsx

@@ -1,5 +1,6 @@
 "use client";
-import { Separator } from "@/components/__legacy__/ui/separator";
+import { Separator } from "@/components/atoms/Separator/Separator";
+import { FadeIn } from "@/components/molecules/FadeIn/FadeIn";
 import { FeaturedSection } from "../FeaturedSection/FeaturedSection";
 import { BecomeACreator } from "../BecomeACreator/BecomeACreator";
 import { HeroSection } from "../HeroSection/HeroSection";
@@ -54,11 +55,13 @@ export const MainMarkeplacePage = () => {
           <FeaturedCreators featuredCreators={featuredCreators.creators} />
         )}
         <Separator className="mb-[25px] mt-[60px]" />
-        <BecomeACreator
-          title="Become a Creator"
-          description="Join our ever-growing community of hackers and tinkerers"
-          buttonText="Become a Creator"
-        />
+        <FadeIn direction="up" duration={0.6}>
+          <BecomeACreator
+            title="Become a Creator"
+            description="Join our ever-growing community of hackers and tinkerers"
+            buttonText="Become a Creator"
+          />
+        </FadeIn>
       </main>
     </div>
   );

autogpt_platform/frontend/src/app/(platform)/marketplace/components/SearchBar/SearchBar.tsx

@@ -16,9 +16,9 @@ interface SearchBarProps {
 export const SearchBar = ({
   placeholder = 'Search for tasks like "optimise SEO"',
   backgroundColor = "bg-neutral-100 dark:bg-neutral-800",
-  iconColor = "text-[#646464] dark:text-neutral-400",
-  textColor = "text-[#707070] dark:text-neutral-200",
-  placeholderColor = "text-[#707070] dark:text-neutral-400",
+  iconColor = "text-neutral-500 dark:text-neutral-400",
+  textColor = "text-neutral-500 dark:text-neutral-200",
+  placeholderColor = "text-neutral-500 dark:text-neutral-400",
   width = "w-9/10 lg:w-[56.25rem]",
   height = "h-[60px]",
 }: SearchBarProps) => {
@@ -32,10 +32,13 @@ export const SearchBar = ({
     >
       <MagnifyingGlassIcon className={`h-5 w-5 md:h-7 md:w-7 ${iconColor}`} />
       <input
-        type="text"
+        type="search"
+        name="search"
+        autoComplete="off"
         value={searchQuery}
         onChange={(e) => setSearchQuery(e.target.value)}
         placeholder={placeholder}
+        aria-label="Search for AI agents"
         className={`flex-grow border-none bg-transparent ${textColor} font-sans text-lg font-normal leading-[2.25rem] tracking-tight md:text-xl placeholder:${placeholderColor} focus:outline-none`}
         data-testid="store-search-input"
       />

autogpt_platform/frontend/src/app/(platform)/marketplace/components/StoreCard/StoreCard.tsx

@@ -1,10 +1,25 @@
 import Image from "next/image";
-import { StarRatingIcons } from "@/components/__legacy__/ui/icons";
+import { Star } from "@phosphor-icons/react";
 import Avatar, {
   AvatarFallback,
   AvatarImage,
 } from "@/components/atoms/Avatar/Avatar";
 
+function StarRating({ rating }: { rating: number }) {
+  const stars = [];
+  const clampedRating = Math.max(0, Math.min(5, rating));
+  for (let i = 1; i <= 5; i++) {
+    stars.push(
+      <Star
+        key={i}
+        weight={i <= clampedRating ? "fill" : "regular"}
+        className="h-4 w-4 text-neutral-900 dark:text-yellow-500"
+      />,
+    );
+  }
+  return <>{stars}</>;
+}
+
 interface StoreCardProps {
   agentName: string;
   agentImage: string;
@@ -34,7 +49,7 @@ export const StoreCard: React.FC<StoreCardProps> = ({
 
   return (
     <div
-      className="flex h-[27rem] w-full max-w-md cursor-pointer flex-col items-start rounded-3xl bg-background transition-all duration-300 hover:shadow-lg dark:hover:shadow-gray-700"
+      className="flex h-[27rem] w-full max-w-md cursor-pointer flex-col items-start rounded-3xl bg-background transition-shadow duration-300 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-neutral-950 focus-visible:ring-offset-2 dark:hover:shadow-gray-700 dark:focus-visible:ring-neutral-50"
       onClick={handleClick}
       data-testid="store-card"
       role="button"
@@ -76,7 +91,7 @@ export const StoreCard: React.FC<StoreCardProps> = ({
       <div className="mt-3 flex w-full flex-1 flex-col px-4">
         {/* Second Section: Agent Name and Creator Name */}
         <div className="flex w-full flex-col">
-          <h3 className="line-clamp-2 font-poppins text-2xl font-semibold text-[#272727] dark:text-neutral-100">
+          <h3 className="line-clamp-2 font-poppins text-2xl font-semibold text-neutral-800 dark:text-neutral-100">
             {agentName}
           </h3>
           {!hideAvatar && creatorName && (
@@ -107,11 +122,11 @@ export const StoreCard: React.FC<StoreCardProps> = ({
                 {rating.toFixed(1)}
               </span>
               <div
-                className="inline-flex items-center"
+                className="inline-flex items-center gap-0.5"
                 role="img"
                 aria-label={`Rating: ${rating.toFixed(1)} out of 5 stars`}
               >
-                {StarRatingIcons(rating)}
+                <StarRating rating={rating} />
               </div>
             </div>
           </div>

autogpt_platform/frontend/src/components/atoms/FilterChip/FilterChip.stories.tsx

@@ -0,0 +1,151 @@
+import type { Meta, StoryObj } from "@storybook/react";
+import { useState } from "react";
+import { FilterChip } from "./FilterChip";
+
+const meta: Meta<typeof FilterChip> = {
+  title: "Atoms/FilterChip",
+  component: FilterChip,
+  tags: ["autodocs"],
+  parameters: {
+    layout: "centered",
+  },
+  argTypes: {
+    size: {
+      control: "select",
+      options: ["sm", "md", "lg"],
+    },
+  },
+};
+
+export default meta;
+type Story = StoryObj<typeof FilterChip>;
+
+export const Default: Story = {
+  args: {
+    label: "Marketing",
+  },
+};
+
+export const Selected: Story = {
+  args: {
+    label: "Marketing",
+    selected: true,
+  },
+};
+
+export const Dismissible: Story = {
+  args: {
+    label: "Marketing",
+    selected: true,
+    dismissible: true,
+  },
+};
+
+export const Sizes: Story = {
+  render: () => (
+    <div className="flex items-center gap-4">
+      <FilterChip label="Small" size="sm" />
+      <FilterChip label="Medium" size="md" />
+      <FilterChip label="Large" size="lg" />
+    </div>
+  ),
+};
+
+export const Disabled: Story = {
+  args: {
+    label: "Disabled",
+    disabled: true,
+  },
+};
+
+function FilterChipGroupDemo() {
+  const filters = [
+    "Marketing",
+    "Sales",
+    "Development",
+    "Design",
+    "Research",
+    "Analytics",
+  ];
+  const [selected, setSelected] = useState<string[]>(["Marketing"]);
+
+  function handleToggle(filter: string) {
+    setSelected((prev) =>
+      prev.includes(filter)
+        ? prev.filter((f) => f !== filter)
+        : [...prev, filter],
+    );
+  }
+
+  return (
+    <div className="flex flex-wrap gap-3">
+      {filters.map((filter) => (
+        <FilterChip
+          key={filter}
+          label={filter}
+          selected={selected.includes(filter)}
+          onClick={() => handleToggle(filter)}
+        />
+      ))}
+    </div>
+  );
+}
+
+export const FilterGroup: Story = {
+  render: () => <FilterChipGroupDemo />,
+};
+
+function SingleSelectDemo() {
+  const filters = ["All", "Featured", "Popular", "New"];
+  const [selected, setSelected] = useState("All");
+
+  return (
+    <div className="flex flex-wrap gap-3">
+      {filters.map((filter) => (
+        <FilterChip
+          key={filter}
+          label={filter}
+          selected={selected === filter}
+          onClick={() => setSelected(filter)}
+        />
+      ))}
+    </div>
+  );
+}
+
+export const SingleSelect: Story = {
+  render: () => <SingleSelectDemo />,
+};
+
+function DismissibleDemo() {
+  const [filters, setFilters] = useState([
+    "Marketing",
+    "Sales",
+    "Development",
+  ]);
+
+  function handleDismiss(filter: string) {
+    setFilters((prev) => prev.filter((f) => f !== filter));
+  }
+
+  return (
+    <div className="flex flex-wrap gap-3">
+      {filters.map((filter) => (
+        <FilterChip
+          key={filter}
+          label={filter}
+          selected
+          dismissible
+          onDismiss={() => handleDismiss(filter)}
+        />
+      ))}
+      {filters.length === 0 && (
+        <span className="text-neutral-500">No filters selected</span>
+      )}
+    </div>
+  );
+}
+
+export const DismissibleGroup: Story = {
+  render: () => <DismissibleDemo />,
+};

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

@@ -0,0 +1,100 @@
+"use client";
+
+import { cn } from "@/lib/utils";
+import { X } from "@phosphor-icons/react";
+
+type FilterChipSize = "sm" | "md" | "lg";
+
+interface FilterChipProps {
+  /** The label text displayed in the chip */
+  label: string;
+  /** Whether the chip is currently selected */
+  selected?: boolean;
+  /** Callback when the chip is clicked */
+  onClick?: () => void;
+  /** Whether to show a dismiss/remove button */
+  dismissible?: boolean;
+  /** Callback when the dismiss button is clicked */
+  onDismiss?: () => void;
+  /** Size variant of the chip */
+  size?: FilterChipSize;
+  /** Whether the chip is disabled */
+  disabled?: boolean;
+  /** Additional CSS classes */
+  className?: string;
+}
+
+const sizeStyles: Record<FilterChipSize, string> = {
+  sm: "px-3 py-1 text-sm gap-1.5",
+  md: "px-4 py-1.5 text-base gap-2",
+  lg: "px-6 py-2 text-lg gap-2.5 lg:text-xl lg:leading-9",
+};
+
+const iconSizes: Record<FilterChipSize, string> = {
+  sm: "h-3 w-3",
+  md: "h-4 w-4",
+  lg: "h-5 w-5",
+};
+
+/**
+ * A filter chip component for selecting/deselecting filter options.
+ * Supports single and multi-select patterns with proper accessibility.
+ */
+export function FilterChip({
+  label,
+  selected = false,
+  onClick,
+  dismissible = false,
+  onDismiss,
+  size = "md",
+  disabled = false,
+  className,
+}: FilterChipProps) {
+  function handleDismiss(e: React.MouseEvent) {
+    e.stopPropagation();
+    onDismiss?.();
+  }
+
+  return (
+    <button
+      type="button"
+      onClick={onClick}
+      disabled={disabled}
+      aria-pressed={selected}
+      className={cn(
+        // Base styles
+        "inline-flex items-center justify-center rounded-full border font-medium transition-colors",
+        // Focus styles
+        "focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-neutral-950 focus-visible:ring-offset-2 dark:focus-visible:ring-neutral-50",
+        // Size styles
+        sizeStyles[size],
+        // State styles
+        selected
+          ? "border-neutral-900 bg-neutral-100 text-neutral-800 dark:border-neutral-100 dark:bg-neutral-800 dark:text-neutral-200"
+          : "border-neutral-400 bg-transparent text-neutral-600 hover:bg-neutral-50 dark:border-neutral-500 dark:text-neutral-300 dark:hover:bg-neutral-800",
+        // Disabled styles
+        disabled && "pointer-events-none opacity-50",
+        className,
+      )}
+    >
+      <span>{label}</span>
+      {dismissible && selected && (
+        <span
+          role="button"
+          tabIndex={0}
+          onClick={handleDismiss}
+          onKeyDown={(e) => {
+            if (e.key === "Enter" || e.key === " ") {
+              e.preventDefault();
+              handleDismiss(e as unknown as React.MouseEvent);
+            }
+          }}
+          className="rounded-full p-0.5 hover:bg-neutral-200 dark:hover:bg-neutral-700"
+          aria-label={`Remove ${label} filter`}
+        >
+          <X className={iconSizes[size]} weight="bold" />
+        </span>
+      )}
+    </button>
+  );
+}

autogpt_platform/frontend/src/components/atoms/Separator/Separator.stories.tsx

@@ -0,0 +1,72 @@
+import type { Meta, StoryObj } from "@storybook/react";
+import { Separator } from "./Separator";
+
+const meta: Meta<typeof Separator> = {
+  title: "Atoms/Separator",
+  component: Separator,
+  tags: ["autodocs"],
+  parameters: {
+    layout: "padded",
+  },
+};
+
+export default meta;
+type Story = StoryObj<typeof Separator>;
+
+export const Horizontal: Story = {
+  render: () => (
+    <div className="w-full max-w-md">
+      <p className="mb-4 text-neutral-700 dark:text-neutral-300">
+        Content above the separator
+      </p>
+      <Separator />
+      <p className="mt-4 text-neutral-700 dark:text-neutral-300">
+        Content below the separator
+      </p>
+    </div>
+  ),
+};
+
+export const Vertical: Story = {
+  render: () => (
+    <div className="flex h-16 items-center gap-4">
+      <span className="text-neutral-700 dark:text-neutral-300">Left</span>
+      <Separator orientation="vertical" />
+      <span className="text-neutral-700 dark:text-neutral-300">Right</span>
+    </div>
+  ),
+};
+
+export const WithCustomStyles: Story = {
+  render: () => (
+    <div className="w-full max-w-md space-y-4">
+      <Separator className="bg-violet-500" />
+      <Separator className="h-0.5 bg-gradient-to-r from-violet-500 to-blue-500" />
+      <Separator className="bg-neutral-400 dark:bg-neutral-600" />
+    </div>
+  ),
+};
+
+export const InSection: Story = {
+  render: () => (
+    <div className="w-full max-w-md space-y-6">
+      <section>
+        <h2 className="mb-2 text-lg font-semibold text-neutral-900 dark:text-neutral-100">
+          Featured Agents
+        </h2>
+        <p className="text-neutral-600 dark:text-neutral-400">
+          Browse our collection of featured AI agents.
+        </p>
+      </section>
+      <Separator className="my-6" />
+      <section>
+        <h2 className="mb-2 text-lg font-semibold text-neutral-900 dark:text-neutral-100">
+          Top Creators
+        </h2>
+        <p className="text-neutral-600 dark:text-neutral-400">
+          Meet the creators behind the most popular agents.
+        </p>
+      </section>
+    </div>
+  ),
+};

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

@@ -0,0 +1,43 @@
+import { cn } from "@/lib/utils";
+
+type SeparatorOrientation = "horizontal" | "vertical";
+
+interface SeparatorProps {
+  /** The orientation of the separator */
+  orientation?: SeparatorOrientation;
+  /** Whether the separator is purely decorative (true) or represents a semantic boundary (false) */
+  decorative?: boolean;
+  /** Additional CSS classes */
+  className?: string;
+}
+
+/**
+ * A visual separator that divides content.
+ * Uses semantic `<hr>` for horizontal separators and a styled `<div>` for vertical.
+ */
+export function Separator({
+  orientation = "horizontal",
+  decorative = true,
+  className,
+}: SeparatorProps) {
+  const baseStyles = "shrink-0 bg-neutral-200 dark:bg-neutral-800";
+
+  if (orientation === "horizontal") {
+    return (
+      <hr
+        className={cn(baseStyles, "h-px w-full border-0", className)}
+        aria-hidden={decorative}
+        role={decorative ? "none" : "separator"}
+      />
+    );
+  }
+
+  return (
+    <div
+      className={cn(baseStyles, "h-full w-px", className)}
+      aria-hidden={decorative}
+      role={decorative ? "none" : "separator"}
+      aria-orientation="vertical"
+    />
+  );
+}

autogpt_platform/frontend/src/components/contextual/CredentialsInput/components/CredentialsGroupedView/CredentialsGroupedView.tsx

@@ -5,30 +5,37 @@ import {
   AccordionItem,
   AccordionTrigger,
 } from "@/components/molecules/Accordion/Accordion";
+import {
+  CredentialsMetaInput,
+  CredentialsType,
+} from "@/lib/autogpt-server-api/types";
 import { CredentialsProvidersContext } from "@/providers/agent-credentials/credentials-provider";
-import { SlidersHorizontal } from "@phosphor-icons/react";
+import { SlidersHorizontalIcon } from "@phosphor-icons/react";
 import { useContext, useEffect, useMemo, useRef } from "react";
-import { useRunAgentModalContext } from "../../context";
 import {
   areSystemCredentialProvidersLoading,
   CredentialField,
   findSavedCredentialByProviderAndType,
   hasMissingRequiredSystemCredentials,
   splitCredentialFieldsBySystem,
-} from "../helpers";
+} from "./helpers";
 
 type Props = {
   credentialFields: CredentialField[];
   requiredCredentials: Set<string>;
+  inputCredentials: Record<string, CredentialsMetaInput | undefined>;
+  inputValues: Record<string, any>;
+  onCredentialChange: (key: string, value?: CredentialsMetaInput) => void;
 };
 
 export function CredentialsGroupedView({
   credentialFields,
   requiredCredentials,
+  inputCredentials,
+  inputValues,
+  onCredentialChange,
 }: Props) {
   const allProviders = useContext(CredentialsProvidersContext);
-  const { inputCredentials, setInputCredentialsValue, inputValues } =
-    useRunAgentModalContext();
 
   const { userCredentialFields, systemCredentialFields } = useMemo(
     () =>
@@ -87,11 +94,11 @@ export function CredentialsGroupedView({
       );
 
       if (savedCredential) {
-        setInputCredentialsValue(key, {
+        onCredentialChange(key, {
           id: savedCredential.id,
           provider: savedCredential.provider,
-          type: savedCredential.type,
-          title: (savedCredential as { title?: string }).title,
+          type: savedCredential.type as CredentialsType,
+          title: savedCredential.title,
         });
       }
     }
@@ -103,7 +110,7 @@ export function CredentialsGroupedView({
     systemCredentialFields,
     requiredCredentials,
     inputCredentials,
-    setInputCredentialsValue,
+    onCredentialChange,
     isLoadingProviders,
   ]);
 
@@ -123,7 +130,7 @@ export function CredentialsGroupedView({
                   }
                   selectedCredentials={selectedCred}
                   onSelectCredentials={(value) => {
-                    setInputCredentialsValue(key, value);
+                    onCredentialChange(key, value);
                   }}
                   siblingInputs={inputValues}
                   isOptional={!requiredCredentials.has(key)}
@@ -143,7 +150,8 @@ export function CredentialsGroupedView({
           <AccordionItem value="system-credentials" className="border-none">
             <AccordionTrigger className="py-2 text-sm text-muted-foreground hover:no-underline">
               <div className="flex items-center gap-1">
-                <SlidersHorizontal size={16} weight="bold" /> System credentials
+                <SlidersHorizontalIcon size={16} weight="bold" /> System
+                credentials
                 {hasMissingSystemCredentials && (
                   <span className="text-destructive">(missing)</span>
                 )}
@@ -163,7 +171,7 @@ export function CredentialsGroupedView({
                         }
                         selectedCredentials={selectedCred}
                         onSelectCredentials={(value) => {
-                          setInputCredentialsValue(key, value);
+                          onCredentialChange(key, value);
                         }}
                         siblingInputs={inputValues}
                         isOptional={!requiredCredentials.has(key)}

autogpt_platform/frontend/src/components/contextual/CredentialsInput/components/CredentialsGroupedView/helpers.ts

@@ -1,5 +1,5 @@
 import { CredentialsProvidersContextType } from "@/providers/agent-credentials/credentials-provider";
-import { getSystemCredentials } from "../../../../../../../../../../../components/contextual/CredentialsInput/helpers";
+import { getSystemCredentials } from "../../helpers";
 
 export type CredentialField = [string, any];
 

autogpt_platform/frontend/src/components/molecules/FadeIn/FadeIn.stories.tsx

@@ -0,0 +1,128 @@
+import type { Meta, StoryObj } from "@storybook/react";
+import { FadeIn } from "./FadeIn";
+
+const meta: Meta<typeof FadeIn> = {
+  title: "Molecules/FadeIn",
+  component: FadeIn,
+  tags: ["autodocs"],
+  parameters: {
+    layout: "padded",
+  },
+  argTypes: {
+    direction: {
+      control: "select",
+      options: ["up", "down", "left", "right", "none"],
+    },
+  },
+};
+
+export default meta;
+type Story = StoryObj<typeof FadeIn>;
+
+const DemoCard = ({ title }: { title: string }) => (
+  <div className="rounded-xl bg-neutral-100 p-6 dark:bg-neutral-800">
+    <h3 className="mb-2 text-lg font-semibold text-neutral-900 dark:text-neutral-100">
+      {title}
+    </h3>
+    <p className="text-neutral-600 dark:text-neutral-400">
+      This card fades in with a smooth animation.
+    </p>
+  </div>
+);
+
+export const Default: Story = {
+  args: {
+    direction: "up",
+    children: <DemoCard title="Fade Up" />,
+  },
+};
+
+export const FadeDown: Story = {
+  args: {
+    direction: "down",
+    children: <DemoCard title="Fade Down" />,
+  },
+};
+
+export const FadeLeft: Story = {
+  args: {
+    direction: "left",
+    children: <DemoCard title="Fade Left" />,
+  },
+};
+
+export const FadeRight: Story = {
+  args: {
+    direction: "right",
+    children: <DemoCard title="Fade Right" />,
+  },
+};
+
+export const FadeOnly: Story = {
+  args: {
+    direction: "none",
+    children: <DemoCard title="Fade Only (No Direction)" />,
+  },
+};
+
+export const WithDelay: Story = {
+  args: {
+    direction: "up",
+    delay: 0.5,
+    children: <DemoCard title="Delayed Fade (0.5s)" />,
+  },
+};
+
+export const SlowAnimation: Story = {
+  args: {
+    direction: "up",
+    duration: 1.5,
+    children: <DemoCard title="Slow Animation (1.5s)" />,
+  },
+};
+
+export const LargeDistance: Story = {
+  args: {
+    direction: "up",
+    distance: 60,
+    children: <DemoCard title="Large Distance (60px)" />,
+  },
+};
+
+export const MultipleElements: Story = {
+  render: () => (
+    <div className="space-y-4">
+      <FadeIn direction="up" delay={0}>
+        <DemoCard title="First Card" />
+      </FadeIn>
+      <FadeIn direction="up" delay={0.1}>
+        <DemoCard title="Second Card" />
+      </FadeIn>
+      <FadeIn direction="up" delay={0.2}>
+        <DemoCard title="Third Card" />
+      </FadeIn>
+    </div>
+  ),
+};
+
+export const HeroExample: Story = {
+  render: () => (
+    <div className="text-center">
+      <FadeIn direction="down" delay={0}>
+        <h1 className="mb-4 text-4xl font-bold text-neutral-900 dark:text-neutral-100">
+          Welcome to the Marketplace
+        </h1>
+      </FadeIn>
+      <FadeIn direction="up" delay={0.2}>
+        <p className="mb-8 text-xl text-neutral-600 dark:text-neutral-400">
+          Discover AI agents built by the community
+        </p>
+      </FadeIn>
+      <FadeIn direction="up" delay={0.4}>
+        <button className="rounded-full bg-violet-600 px-8 py-3 text-white hover:bg-violet-700">
+          Get Started
+        </button>
+      </FadeIn>
+    </div>
+  ),
+};

autogpt_platform/frontend/src/components/molecules/FadeIn/FadeIn.tsx

@@ -0,0 +1,109 @@
+"use client";
+
+import { cn } from "@/lib/utils";
+import { motion, useReducedMotion, type Variants } from "framer-motion";
+import { ReactNode } from "react";
+
+type FadeDirection = "up" | "down" | "left" | "right" | "none";
+
+interface FadeInProps {
+  /** Content to animate */
+  children: ReactNode;
+  /** Direction the content fades in from */
+  direction?: FadeDirection;
+  /** Distance to travel in pixels (only applies when direction is not "none") */
+  distance?: number;
+  /** Animation duration in seconds */
+  duration?: number;
+  /** Delay before animation starts in seconds */
+  delay?: number;
+  /** Whether to trigger animation when element enters viewport */
+  viewport?: boolean;
+  /** How much of element must be visible to trigger (0-1) */
+  viewportAmount?: number;
+  /** Whether animation should only trigger once */
+  once?: boolean;
+  /** Additional CSS classes */
+  className?: string;
+  /** HTML element to render as */
+  as?: keyof JSX.IntrinsicElements;
+}
+
+function getDirectionOffset(
+  direction: FadeDirection,
+  distance: number,
+): { x: number; y: number } {
+  switch (direction) {
+    case "up":
+      return { x: 0, y: distance };
+    case "down":
+      return { x: 0, y: -distance };
+    case "left":
+      return { x: distance, y: 0 };
+    case "right":
+      return { x: -distance, y: 0 };
+    case "none":
+    default:
+      return { x: 0, y: 0 };
+  }
+}
+
+/**
+ * A fade-in animation wrapper component.
+ * Animates children with a fade effect and optional directional slide.
+ * Respects user's reduced motion preferences.
+ */
+export function FadeIn({
+  children,
+  direction = "up",
+  distance = 24,
+  duration = 0.5,
+  delay = 0,
+  viewport = true,
+  viewportAmount = 0.2,
+  once = true,
+  className,
+  as = "div",
+}: FadeInProps) {
+  const shouldReduceMotion = useReducedMotion();
+  const offset = getDirectionOffset(direction, distance);
+
+  // If user prefers reduced motion, render without animation
+  if (shouldReduceMotion) {
+    const Component = as as keyof JSX.IntrinsicElements;
+    return <Component className={className}>{children}</Component>;
+  }
+
+  const variants: Variants = {
+    hidden: {
+      opacity: 0,
+      x: offset.x,
+      y: offset.y,
+    },
+    visible: {
+      opacity: 1,
+      x: 0,
+      y: 0,
+      transition: {
+        duration,
+        delay,
+        ease: [0.25, 0.1, 0.25, 1], // Custom easing for smooth feel
+      },
+    },
+  };
+
+  const MotionComponent = motion[as as keyof typeof motion] as typeof motion.div;
+
+  return (
+    <MotionComponent
+      className={cn(className)}
+      initial="hidden"
+      animate={viewport ? undefined : "visible"}
+      whileInView={viewport ? "visible" : undefined}
+      viewport={viewport ? { once, amount: viewportAmount } : undefined}
+      variants={variants}
+    >
+      {children}
+    </MotionComponent>
+  );
+}

autogpt_platform/frontend/src/components/molecules/StaggeredList/StaggeredList.stories.tsx

@@ -0,0 +1,180 @@
+import type { Meta, StoryObj } from "@storybook/react";
+import { StaggeredList } from "./StaggeredList";
+
+const meta: Meta<typeof StaggeredList> = {
+  title: "Molecules/StaggeredList",
+  component: StaggeredList,
+  tags: ["autodocs"],
+  parameters: {
+    layout: "padded",
+  },
+  argTypes: {
+    direction: {
+      control: "select",
+      options: ["up", "down", "left", "right", "none"],
+    },
+  },
+};
+
+export default meta;
+type Story = StoryObj<typeof StaggeredList>;
+
+const DemoCard = ({ title, index }: { title: string; index: number }) => (
+  <div className="rounded-xl bg-neutral-100 p-4 dark:bg-neutral-800">
+    <h3 className="mb-1 font-semibold text-neutral-900 dark:text-neutral-100">
+      {title}
+    </h3>
+    <p className="text-sm text-neutral-600 dark:text-neutral-400">
+      Card #{index + 1} with staggered animation
+    </p>
+  </div>
+);
+
+const items = ["First Item", "Second Item", "Third Item", "Fourth Item"];
+
+export const Default: Story = {
+  args: {
+    direction: "up",
+    className: "space-y-4",
+    children: items.map((item, i) => <DemoCard key={i} title={item} index={i} />),
+  },
+};
+
+export const FadeDown: Story = {
+  args: {
+    direction: "down",
+    className: "space-y-4",
+    children: items.map((item, i) => <DemoCard key={i} title={item} index={i} />),
+  },
+};
+
+export const FadeLeft: Story = {
+  args: {
+    direction: "left",
+    className: "flex gap-4",
+    children: items.map((item, i) => <DemoCard key={i} title={item} index={i} />),
+  },
+};
+
+export const FadeRight: Story = {
+  args: {
+    direction: "right",
+    className: "flex gap-4",
+    children: items.map((item, i) => <DemoCard key={i} title={item} index={i} />),
+  },
+};
+
+export const FastStagger: Story = {
+  args: {
+    direction: "up",
+    staggerDelay: 0.05,
+    className: "space-y-4",
+    children: items.map((item, i) => <DemoCard key={i} title={item} index={i} />),
+  },
+};
+
+export const SlowStagger: Story = {
+  args: {
+    direction: "up",
+    staggerDelay: 0.3,
+    className: "space-y-4",
+    children: items.map((item, i) => <DemoCard key={i} title={item} index={i} />),
+  },
+};
+
+export const WithInitialDelay: Story = {
+  args: {
+    direction: "up",
+    initialDelay: 0.5,
+    className: "space-y-4",
+    children: items.map((item, i) => <DemoCard key={i} title={item} index={i} />),
+  },
+};
+
+export const GridLayout: Story = {
+  args: {
+    direction: "up",
+    staggerDelay: 0.08,
+    className: "grid grid-cols-2 gap-4 md:grid-cols-4",
+    children: [
+      ...items,
+      "Fifth Item",
+      "Sixth Item",
+      "Seventh Item",
+      "Eighth Item",
+    ].map((item, i) => <DemoCard key={i} title={item} index={i} />),
+  },
+};
+
+export const AgentCardsExample: Story = {
+  render: () => {
+    const agents = [
+      { name: "SEO Optimizer", runs: 1234 },
+      { name: "Content Writer", runs: 987 },
+      { name: "Data Analyzer", runs: 756 },
+      { name: "Code Reviewer", runs: 543 },
+    ];
+
+    return (
+      <StaggeredList
+        direction="up"
+        staggerDelay={0.1}
+        className="grid grid-cols-2 gap-6 md:grid-cols-4"
+      >
+        {agents.map((agent, i) => (
+          <div
+            key={i}
+            className="rounded-2xl bg-white p-4 shadow-md dark:bg-neutral-900"
+          >
+            <div className="mb-3 aspect-video rounded-xl bg-gradient-to-br from-violet-500 to-blue-500" />
+            <h3 className="mb-1 font-semibold text-neutral-900 dark:text-neutral-100">
+              {agent.name}
+            </h3>
+            <p className="text-sm text-neutral-500">{agent.runs} runs</p>
+          </div>
+        ))}
+      </StaggeredList>
+    );
+  },
+};
+
+export const CreatorCardsExample: Story = {
+  render: () => {
+    const creators = [
+      { name: "Alice", agents: 12 },
+      { name: "Bob", agents: 8 },
+      { name: "Charlie", agents: 15 },
+      { name: "Diana", agents: 6 },
+    ];
+
+    const colors = [
+      "bg-violet-100 dark:bg-violet-900/30",
+      "bg-blue-100 dark:bg-blue-900/30",
+      "bg-green-100 dark:bg-green-900/30",
+      "bg-orange-100 dark:bg-orange-900/30",
+    ];
+
+    return (
+      <StaggeredList
+        direction="up"
+        staggerDelay={0.12}
+        className="grid grid-cols-2 gap-6 md:grid-cols-4"
+      >
+        {creators.map((creator, i) => (
+          <div
+            key={i}
+            className={`rounded-2xl p-5 ${colors[i % colors.length]}`}
+          >
+            <div className="mb-3 h-12 w-12 rounded-full bg-neutral-300 dark:bg-neutral-700" />
+            <h3 className="mb-1 font-semibold text-neutral-900 dark:text-neutral-100">
+              {creator.name}
+            </h3>
+            <p className="text-sm text-neutral-600 dark:text-neutral-400">
+              {creator.agents} agents
+            </p>
+          </div>
+        ))}
+      </StaggeredList>
+    );
+  },
+};

autogpt_platform/frontend/src/components/molecules/StaggeredList/StaggeredList.tsx

@@ -0,0 +1,130 @@
+"use client";
+
+import { cn } from "@/lib/utils";
+import { motion, useReducedMotion, type Variants } from "framer-motion";
+import { ReactNode } from "react";
+
+type StaggerDirection = "up" | "down" | "left" | "right" | "none";
+
+interface StaggeredListProps {
+  /** Array of items to render with staggered animation */
+  children: ReactNode[];
+  /** Direction items animate from */
+  direction?: StaggerDirection;
+  /** Distance to travel in pixels */
+  distance?: number;
+  /** Base duration for each item's animation */
+  duration?: number;
+  /** Delay between each item's animation start */
+  staggerDelay?: number;
+  /** Initial delay before first item animates */
+  initialDelay?: number;
+  /** Whether to trigger animation when element enters viewport */
+  viewport?: boolean;
+  /** How much of container must be visible to trigger */
+  viewportAmount?: number;
+  /** Whether animation should only trigger once */
+  once?: boolean;
+  /** Additional CSS classes for the container */
+  className?: string;
+  /** Additional CSS classes for each item wrapper */
+  itemClassName?: string;
+}
+
+function getDirectionOffset(
+  direction: StaggerDirection,
+  distance: number,
+): { x: number; y: number } {
+  switch (direction) {
+    case "up":
+      return { x: 0, y: distance };
+    case "down":
+      return { x: 0, y: -distance };
+    case "left":
+      return { x: distance, y: 0 };
+    case "right":
+      return { x: -distance, y: 0 };
+    case "none":
+    default:
+      return { x: 0, y: 0 };
+  }
+}
+
+/**
+ * Animates a list of children with staggered fade-in effects.
+ * Each child appears sequentially with a configurable delay.
+ * Respects user's reduced motion preferences.
+ */
+export function StaggeredList({
+  children,
+  direction = "up",
+  distance = 20,
+  duration = 0.4,
+  staggerDelay = 0.1,
+  initialDelay = 0,
+  viewport = true,
+  viewportAmount = 0.1,
+  once = true,
+  className,
+  itemClassName,
+}: StaggeredListProps) {
+  const shouldReduceMotion = useReducedMotion();
+  const offset = getDirectionOffset(direction, distance);
+
+  // If user prefers reduced motion, render without animation
+  if (shouldReduceMotion) {
+    return (
+      <div className={className}>
+        {children.map((child, index) => (
+          <div key={index} className={itemClassName}>
+            {child}
+          </div>
+        ))}
+      </div>
+    );
+  }
+
+  const containerVariants: Variants = {
+    hidden: {},
+    visible: {
+      transition: {
+        staggerChildren: staggerDelay,
+        delayChildren: initialDelay,
+      },
+    },
+  };
+
+  const itemVariants: Variants = {
+    hidden: {
+      opacity: 0,
+      x: offset.x,
+      y: offset.y,
+    },
+    visible: {
+      opacity: 1,
+      x: 0,
+      y: 0,
+      transition: {
+        duration,
+        ease: [0.25, 0.1, 0.25, 1],
+      },
+    },
+  };
+
+  return (
+    <motion.div
+      className={cn(className)}
+      initial="hidden"
+      animate={viewport ? undefined : "visible"}
+      whileInView={viewport ? "visible" : undefined}
+      viewport={viewport ? { once, amount: viewportAmount } : undefined}
+      variants={containerVariants}
+    >
+      {children.map((child, index) => (
+        <motion.div key={index} className={itemClassName} variants={itemVariants}>
+          {child}
+        </motion.div>
+      ))}
+    </motion.div>
+  );
+}