fix(db): Remove redundant migration and fix pgvector schema handling (#11822)

### Changes 🏗️

This PR includes two database migration fixes:

#### 1. Remove redundant Supabase extensions migration

Removes the `20260112173500_add_supabase_extensions_to_platform_schema`
migration which was attempting to manage Supabase-provided extensions
and schemas.

**What was removed:**
- Migration that created extensions (pgcrypto, uuid-ossp,
pg_stat_statements, pg_net, pgjwt, pg_graphql, pgsodium, supabase_vault)
- Schema creation for these extensions

**Why it was removed:**
- These extensions and schemas are pre-installed and managed by Supabase
automatically
- The migration was redundant and could cause schema drift warnings
- Attempting to manage Supabase-owned resources in our migrations is an
anti-pattern

#### 2. Fix pgvector extension schema handling

Improves the `20260109181714_add_docs_embedding` migration to handle
cases where pgvector exists in the wrong schema.

**Problem:**
- If pgvector was previously installed in `public` schema, `CREATE
EXTENSION IF NOT EXISTS` would succeed but not actually install it in
the `platform` schema
- This causes `type "vector" does not exist` errors because the type
isn't in the search_path

**Solution:**
- Detect if vector extension exists in a different schema than the
current one
- Drop it with CASCADE and reinstall in the correct schema (platform)
- Use dynamic SQL with `EXECUTE format()` to explicitly specify the
target schema
- Split exception handling: catch errors during removal, but let
installation fail naturally with clear PostgreSQL errors

**Impact:**
- No functional changes - Supabase continues to provide extensions as
before
- pgvector now correctly installs in the platform schema
- Cleaner migration history
- Prevents schema-related errors

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  - [x] Verified migrations run successfully without the redundant file
  - [x] Confirmed Supabase extensions are still available
  - [x] Tested pgvector migration handles wrong-schema scenario
  - [x] No schema drift warnings

#### For configuration changes:
- [x] .env.default is updated or already compatible with my changes
- [x] docker-compose.yml is updated or already compatible with my
changes
- [x] I have included a list of my configuration changes in the PR
description (under **Changes**)
  - N/A - No configuration changes required

.github/workflows/platform-frontend-ci.yml

@@ -128,7 +128,7 @@ jobs:
           token: ${{ secrets.GITHUB_TOKEN }}
           exitOnceUploaded: true
 
-  test:
+  e2e_test:
     runs-on: big-boi
     needs: setup
     strategy:
@@ -258,3 +258,39 @@ jobs:
       - name: Print Final Docker Compose logs
         if: always()
         run: docker compose -f ../docker-compose.yml logs
+
+  integration_test:
+    runs-on: ubuntu-latest
+    needs: setup
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+        with:
+          submodules: recursive
+
+      - name: Set up Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: "22.18.0"
+
+      - name: Enable corepack
+        run: corepack enable
+
+      - name: Restore dependencies cache
+        uses: actions/cache@v4
+        with:
+          path: ~/.pnpm-store
+          key: ${{ needs.setup.outputs.cache-key }}
+          restore-keys: |
+            ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
+            ${{ runner.os }}-pnpm-
+
+      - name: Install dependencies
+        run: pnpm install --frozen-lockfile
+
+      - name: Generate API client
+        run: pnpm generate:api
+
+      - name: Run Integration Tests
+        run: pnpm test:unit

AGENTS.md

@@ -16,6 +16,32 @@ See `docs/content/platform/getting-started.md` for setup instructions.
 - Format Python code with `poetry run format`.
 - Format frontend code using `pnpm format`.
 
+
+## Frontend guidelines:
+
+See `/frontend/CONTRIBUTING.md` for complete patterns. Quick reference:
+
+1. **Pages**: Create in `src/app/(platform)/feature-name/page.tsx`
+   - Add `usePageName.ts` hook for logic
+   - Put sub-components in local `components/` folder
+2. **Components**: Structure as `ComponentName/ComponentName.tsx` + `useComponentName.ts` + `helpers.ts`
+   - Use design system components from `src/components/` (atoms, molecules, organisms)
+   - Never use `src/components/__legacy__/*`
+3. **Data fetching**: Use generated API hooks from `@/app/api/__generated__/endpoints/`
+   - Regenerate with `pnpm generate:api`
+   - Pattern: `use{Method}{Version}{OperationName}`
+4. **Styling**: Tailwind CSS only, use design tokens, Phosphor Icons only
+5. **Testing**: Add Storybook stories for new components, Playwright for E2E
+6. **Code conventions**: Function declarations (not arrow functions) for components/handlers
+- Component props should be `interface Props { ... }` (not exported) unless the interface needs to be used outside the component
+- Separate render logic from business logic (component.tsx + useComponent.ts + helpers.ts)
+- Colocate state when possible and avoid creating large components, use sub-components ( local `/components` folder next to the parent component ) when sensible
+- Avoid large hooks, abstract logic into `helpers.ts` files when sensible
+- Use function declarations for components, arrow functions only for callbacks
+- No barrel files or `index.ts` re-exports
+- Do not use `useCallback` or `useMemo` unless strictly needed
+- Avoid comments at all times unless the code is very complex
+
 ## Testing
 
 - Backend: `poetry run test` (runs pytest with a docker based postgres + prisma).

autogpt_platform/CLAUDE.md

@@ -201,7 +201,7 @@ If you get any pushback or hit complex block conditions check the new_blocks gui
 3. Write tests alongside the route file
 4. Run `poetry run test` to verify
 
-**Frontend feature development:**
+### Frontend guidelines:
 
 See `/frontend/CONTRIBUTING.md` for complete patterns. Quick reference:
 
@@ -217,6 +217,14 @@ See `/frontend/CONTRIBUTING.md` for complete patterns. Quick reference:
 4. **Styling**: Tailwind CSS only, use design tokens, Phosphor Icons only
 5. **Testing**: Add Storybook stories for new components, Playwright for E2E
 6. **Code conventions**: Function declarations (not arrow functions) for components/handlers
+- Component props should be `interface Props { ... }` (not exported) unless the interface needs to be used outside the component
+- Separate render logic from business logic (component.tsx + useComponent.ts + helpers.ts)
+- Colocate state when possible and avoid creating large components, use sub-components ( local `/components` folder next to the parent component ) when sensible
+- Avoid large hooks, abstract logic into `helpers.ts` files when sensible
+- Use function declarations for components, arrow functions only for callbacks
+- No barrel files or `index.ts` re-exports
+- Do not use `useCallback` or `useMemo` unless strictly needed
+- Avoid comments at all times unless the code is very complex
 
 ### Security Implementation
 

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

@@ -290,6 +290,11 @@ async def _cache_session(session: ChatSession) -> None:
     await async_redis.setex(redis_key, config.session_ttl, session.model_dump_json())
 
 
+async def cache_chat_session(session: ChatSession) -> None:
+    """Cache a chat session without persisting to the database."""
+    await _cache_session(session)
+
+
 async def _get_session_from_db(session_id: str) -> ChatSession | None:
     """Get a chat session from the database."""
     prisma_session = await chat_db.get_chat_session(session_id)

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

@@ -172,12 +172,12 @@ async def get_session(
         user_id: The optional authenticated user ID, or None for anonymous access.
 
     Returns:
-        SessionDetailResponse: Details for the requested session; raises NotFoundError if not found.
+        SessionDetailResponse: Details for the requested session, or None if not found.
 
     """
     session = await get_chat_session(session_id, user_id)
     if not session:
-        raise NotFoundError(f"Session {session_id} not found")
+        raise NotFoundError(f"Session {session_id} not found.")
 
     messages = [message.model_dump() for message in session.messages]
     logger.info(
@@ -222,6 +222,8 @@ async def stream_chat_post(
     session = await _validate_and_get_session(session_id, user_id)
 
     async def event_generator() -> AsyncGenerator[str, None]:
+        chunk_count = 0
+        first_chunk_type: str | None = None
         async for chunk in chat_service.stream_chat_completion(
             session_id,
             request.message,
@@ -230,7 +232,26 @@ async def stream_chat_post(
             session=session,  # Pass pre-fetched session to avoid double-fetch
             context=request.context,
         ):
+            if chunk_count < 3:
+                logger.info(
+                    "Chat stream chunk",
+                    extra={
+                        "session_id": session_id,
+                        "chunk_type": str(chunk.type),
+                    },
+                )
+            if not first_chunk_type:
+                first_chunk_type = str(chunk.type)
+            chunk_count += 1
             yield chunk.to_sse()
+        logger.info(
+            "Chat stream completed",
+            extra={
+                "session_id": session_id,
+                "chunk_count": chunk_count,
+                "first_chunk_type": first_chunk_type,
+            },
+        )
         # AI SDK protocol termination
         yield "data: [DONE]\n\n"
 
@@ -275,6 +296,8 @@ async def stream_chat_get(
     session = await _validate_and_get_session(session_id, user_id)
 
     async def event_generator() -> AsyncGenerator[str, None]:
+        chunk_count = 0
+        first_chunk_type: str | None = None
         async for chunk in chat_service.stream_chat_completion(
             session_id,
             message,
@@ -282,7 +305,26 @@ async def stream_chat_get(
             user_id=user_id,
             session=session,  # Pass pre-fetched session to avoid double-fetch
         ):
+            if chunk_count < 3:
+                logger.info(
+                    "Chat stream chunk",
+                    extra={
+                        "session_id": session_id,
+                        "chunk_type": str(chunk.type),
+                    },
+                )
+            if not first_chunk_type:
+                first_chunk_type = str(chunk.type)
+            chunk_count += 1
             yield chunk.to_sse()
+        logger.info(
+            "Chat stream completed",
+            extra={
+                "session_id": session_id,
+                "chunk_count": chunk_count,
+                "first_chunk_type": first_chunk_type,
+            },
+        )
         # AI SDK protocol termination
         yield "data: [DONE]\n\n"
 

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

@@ -1,12 +1,20 @@
 import asyncio
 import logging
+import time
+from asyncio import CancelledError
 from collections.abc import AsyncGenerator
 from typing import Any
 
 import orjson
 from langfuse import get_client, propagate_attributes
 from langfuse.openai import openai  # type: ignore
-from openai import APIConnectionError, APIError, APIStatusError, RateLimitError
+from openai import (
+    APIConnectionError,
+    APIError,
+    APIStatusError,
+    PermissionDeniedError,
+    RateLimitError,
+)
 from openai.types.chat import ChatCompletionChunk, ChatCompletionToolParam
 
 from backend.data.understanding import (
@@ -21,6 +29,7 @@ from .model import (
     ChatMessage,
     ChatSession,
     Usage,
+    cache_chat_session,
     get_chat_session,
     update_session_title,
     upsert_chat_session,
@@ -296,6 +305,10 @@ async def stream_chat_completion(
                 content="",
             )
             accumulated_tool_calls: list[dict[str, Any]] = []
+            has_saved_assistant_message = False
+            has_appended_streaming_message = False
+            last_cache_time = 0.0
+            last_cache_content_len = 0
 
             # Wrap main logic in try/finally to ensure Langfuse observations are always ended
             has_yielded_end = False
@@ -332,6 +345,23 @@ async def stream_chat_completion(
                         assert assistant_response.content is not None
                         assistant_response.content += delta
                         has_received_text = True
+                        if not has_appended_streaming_message:
+                            session.messages.append(assistant_response)
+                            has_appended_streaming_message = True
+                        current_time = time.monotonic()
+                        content_len = len(assistant_response.content)
+                        if (
+                            current_time - last_cache_time >= 1.0
+                            and content_len > last_cache_content_len
+                        ):
+                            try:
+                                await cache_chat_session(session)
+                            except Exception as e:
+                                logger.warning(
+                                    f"Failed to cache partial session {session.session_id}: {e}"
+                                )
+                            last_cache_time = current_time
+                            last_cache_content_len = content_len
                         yield chunk
                     elif isinstance(chunk, StreamTextEnd):
                         # Emit text-end after text completes
@@ -390,10 +420,42 @@ async def stream_chat_completion(
                             if has_received_text and not text_streaming_ended:
                                 yield StreamTextEnd(id=text_block_id)
                                 text_streaming_ended = True
+
+                            # Save assistant message before yielding finish to ensure it's persisted
+                            # even if client disconnects immediately after receiving StreamFinish
+                            if not has_saved_assistant_message:
+                                messages_to_save_early: list[ChatMessage] = []
+                                if accumulated_tool_calls:
+                                    assistant_response.tool_calls = (
+                                        accumulated_tool_calls
+                                    )
+                                if not has_appended_streaming_message and (
+                                    assistant_response.content
+                                    or assistant_response.tool_calls
+                                ):
+                                    messages_to_save_early.append(assistant_response)
+                                messages_to_save_early.extend(tool_response_messages)
+
+                                if messages_to_save_early:
+                                    session.messages.extend(messages_to_save_early)
+                                    logger.info(
+                                        f"Saving assistant message before StreamFinish: "
+                                        f"content_len={len(assistant_response.content or '')}, "
+                                        f"tool_calls={len(assistant_response.tool_calls or [])}, "
+                                        f"tool_responses={len(tool_response_messages)}"
+                                    )
+                                if (
+                                    messages_to_save_early
+                                    or has_appended_streaming_message
+                                ):
+                                    await upsert_chat_session(session)
+                                    has_saved_assistant_message = True
+
                             has_yielded_end = True
                             yield chunk
                     elif isinstance(chunk, StreamError):
                         has_yielded_error = True
+                        yield chunk
                     elif isinstance(chunk, StreamUsage):
                         session.usage.append(
                             Usage(
@@ -413,6 +475,27 @@ async def stream_chat_completion(
                     langfuse.update_current_trace(output=str(tool_response_messages))
                     langfuse.update_current_span(output=str(tool_response_messages))
 
+            except CancelledError:
+                if not has_saved_assistant_message:
+                    if accumulated_tool_calls:
+                        assistant_response.tool_calls = accumulated_tool_calls
+                    if assistant_response.content:
+                        assistant_response.content = (
+                            f"{assistant_response.content}\n\n[interrupted]"
+                        )
+                    else:
+                        assistant_response.content = "[interrupted]"
+                    if not has_appended_streaming_message:
+                        session.messages.append(assistant_response)
+                    if tool_response_messages:
+                        session.messages.extend(tool_response_messages)
+                    try:
+                        await upsert_chat_session(session)
+                    except Exception as e:
+                        logger.warning(
+                            f"Failed to save interrupted session {session.session_id}: {e}"
+                        )
+                raise
             except Exception as e:
                 logger.error(f"Error during stream: {e!s}", exc_info=True)
 
@@ -434,14 +517,19 @@ async def stream_chat_completion(
                     # 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:
+                    if not has_appended_streaming_message and (
+                        assistant_response.content or assistant_response.tool_calls
+                    ):
                         messages_to_save.append(assistant_response)
 
                     # Add tool response messages after assistant message
                     messages_to_save.extend(tool_response_messages)
 
-                    session.messages.extend(messages_to_save)
+                    if not has_saved_assistant_message:
-                    await upsert_chat_session(session)
+                        if messages_to_save:
+                            session.messages.extend(messages_to_save)
+                        if messages_to_save or has_appended_streaming_message:
+                            await upsert_chat_session(session)
 
                     if not has_yielded_error:
                         error_message = str(e)
@@ -472,38 +560,49 @@ async def stream_chat_completion(
                 return  # Exit after retry to avoid double-saving in finally block
 
             # Normal completion path - save session and handle tool call continuation
-            logger.info(
+            # Only save if we haven't already saved when StreamFinish was received
-                f"Normal completion path: session={session.session_id}, "
+            if not has_saved_assistant_message:
-                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"
+                    f"Normal completion path: session={session.session_id}, "
-                )
+                    f"current message_count={len(session.messages)}"
-            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 [])}"
                 )
 
-            # Add tool response messages after assistant message
+                # Build the messages list in the correct order
-            messages_to_save.extend(tool_response_messages)
+                messages_to_save: list[ChatMessage] = []
-            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)
+                # Add assistant message with tool_calls if any
-            logger.info(
+                if accumulated_tool_calls:
-                f"Extended session messages, new message_count={len(session.messages)}"
+                    assistant_response.tool_calls = accumulated_tool_calls
-            )
+                    logger.info(
-            await upsert_chat_session(session)
+                        f"Added {len(accumulated_tool_calls)} tool calls to assistant message"
+                    )
+                if not has_appended_streaming_message and (
+                    assistant_response.content or assistant_response.tool_calls
+                ):
+                    messages_to_save.append(assistant_response)
+                    logger.info(
+                        f"Saving assistant message with content_len={len(assistant_response.content or '')}, tool_calls={len(assistant_response.tool_calls or [])}"
+                    )
+
+                # Add tool response messages after assistant message
+                messages_to_save.extend(tool_response_messages)
+                logger.info(
+                    f"Saving {len(tool_response_messages)} tool response messages, "
+                    f"total_to_save={len(messages_to_save)}"
+                )
+
+                if messages_to_save:
+                    session.messages.extend(messages_to_save)
+                    logger.info(
+                        f"Extended session messages, new message_count={len(session.messages)}"
+                    )
+                if messages_to_save or has_appended_streaming_message:
+                    await upsert_chat_session(session)
+            else:
+                logger.info(
+                    "Assistant message already saved when StreamFinish was received, "
+                    "skipping duplicate save"
+                )
 
             # If we did a tool call, stream the chat completion again to get the next response
             if has_done_tool_call:
@@ -545,6 +644,12 @@ def _is_retryable_error(error: Exception) -> bool:
     return False
 
 
+def _is_region_blocked_error(error: Exception) -> bool:
+    if isinstance(error, PermissionDeniedError):
+        return "not available in your region" in str(error).lower()
+    return "not available in your region" in str(error).lower()
+
+
 async def _stream_chat_chunks(
     session: ChatSession,
     tools: list[ChatCompletionToolParam],
@@ -737,7 +842,18 @@ async def _stream_chat_chunks(
                         f"Error in stream (not retrying): {e!s}",
                         exc_info=True,
                     )
-                    error_response = StreamError(errorText=str(e))
+                    error_code = None
+                    error_text = str(e)
+                    if _is_region_blocked_error(e):
+                        error_code = "MODEL_NOT_AVAILABLE_REGION"
+                        error_text = (
+                            "This model is not available in your region. "
+                            "Please connect via VPN and try again."
+                        )
+                    error_response = StreamError(
+                        errorText=error_text,
+                        code=error_code,
+                    )
                     yield error_response
                     yield StreamFinish()
                     return

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

@@ -154,16 +154,16 @@ async def store_content_embedding(
 
         # Upsert the embedding
         # WHERE clause in DO UPDATE prevents PostgreSQL 15 bug with NULLS NOT DISTINCT
-        # Use {pgvector_schema}.vector for explicit pgvector type qualification
+        # Use unqualified ::vector - pgvector is in search_path on all environments
         await execute_raw_with_schema(
             """
             INSERT INTO {schema_prefix}"UnifiedContentEmbedding" (
                 "id", "contentType", "contentId", "userId", "embedding", "searchableText", "metadata", "createdAt", "updatedAt"
             )
-            VALUES (gen_random_uuid()::text, $1::{schema_prefix}"ContentType", $2, $3, $4::{pgvector_schema}.vector, $5, $6::jsonb, NOW(), NOW())
+            VALUES (gen_random_uuid()::text, $1::{schema_prefix}"ContentType", $2, $3, $4::vector, $5, $6::jsonb, NOW(), NOW())
             ON CONFLICT ("contentType", "contentId", "userId")
             DO UPDATE SET
-                "embedding" = $4::{pgvector_schema}.vector,
+                "embedding" = $4::vector,
                 "searchableText" = $5,
                 "metadata" = $6::jsonb,
                 "updatedAt" = NOW()
@@ -879,8 +879,7 @@ async def semantic_search(
         min_similarity_idx = len(params) + 1
         params.append(min_similarity)
 
-        # Use regular string (not f-string) for template to preserve {schema_prefix} and {schema} placeholders
+        # Use unqualified ::vector and <=> operator - pgvector is in search_path on all environments
-        # Use OPERATOR({pgvector_schema}.<=>) for explicit operator schema qualification
         sql = (
             """
             SELECT
@@ -888,9 +887,9 @@ async def semantic_search(
                 "contentType" as content_type,
                 "searchableText" as searchable_text,
                 metadata,
-                1 - (embedding OPERATOR({pgvector_schema}.<=>) '"""
+                1 - (embedding <=> '"""
             + embedding_str
-            + """'::{pgvector_schema}.vector) as similarity
+            + """'::vector) as similarity
             FROM {schema_prefix}"UnifiedContentEmbedding"
             WHERE "contentType" IN ("""
             + content_type_placeholders
@@ -898,9 +897,9 @@ async def semantic_search(
             """
             + user_filter
             + """
-            AND 1 - (embedding OPERATOR({pgvector_schema}.<=>) '"""
+            AND 1 - (embedding <=> '"""
             + embedding_str
-            + """'::{pgvector_schema}.vector) >= $"""
+            + """'::vector) >= $"""
             + str(min_similarity_idx)
             + """
             ORDER BY similarity DESC

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

@@ -295,7 +295,7 @@ async def unified_hybrid_search(
                 FROM {{schema_prefix}}"UnifiedContentEmbedding" uce
                 WHERE uce."contentType" = ANY({content_types_param}::{{schema_prefix}}"ContentType"[])
                 {user_filter}
-                ORDER BY uce.embedding OPERATOR({{pgvector_schema}}.<=>)  {embedding_param}::{{pgvector_schema}}.vector
+                ORDER BY uce.embedding <=> {embedding_param}::vector
                 LIMIT 200
             )
         ),
@@ -307,7 +307,7 @@ async def unified_hybrid_search(
                 uce.metadata,
                 uce."updatedAt" as updated_at,
                 -- Semantic score: cosine similarity (1 - distance)
-                COALESCE(1 - (uce.embedding OPERATOR({{pgvector_schema}}.<=>)  {embedding_param}::{{pgvector_schema}}.vector), 0) as semantic_score,
+                COALESCE(1 - (uce.embedding <=> {embedding_param}::vector), 0) as semantic_score,
                 -- Lexical score: ts_rank_cd
                 COALESCE(ts_rank_cd(uce.search, plainto_tsquery('english', {query_param})), 0) as lexical_raw,
                 -- Category match from metadata
@@ -583,7 +583,7 @@ async def hybrid_search(
                 WHERE uce."contentType" = 'STORE_AGENT'::{{schema_prefix}}"ContentType"
                 AND uce."userId" IS NULL
                 AND {where_clause}
-                ORDER BY uce.embedding OPERATOR({{pgvector_schema}}.<=>)  {embedding_param}::{{pgvector_schema}}.vector
+                ORDER BY uce.embedding <=> {embedding_param}::vector
                 LIMIT 200
             ) uce
         ),
@@ -605,7 +605,7 @@ async def hybrid_search(
                 -- Searchable text for BM25 reranking
                 COALESCE(sa.agent_name, '') || ' ' || COALESCE(sa.sub_heading, '') || ' ' || COALESCE(sa.description, '') as searchable_text,
                 -- Semantic score
-                COALESCE(1 - (uce.embedding OPERATOR({{pgvector_schema}}.<=>)  {embedding_param}::{{pgvector_schema}}.vector), 0) as semantic_score,
+                COALESCE(1 - (uce.embedding <=> {embedding_param}::vector), 0) as semantic_score,
                 -- Lexical score (raw, will normalize)
                 COALESCE(ts_rank_cd(uce.search, plainto_tsquery('english', {query_param})), 0) as lexical_raw,
                 -- Category match

autogpt_platform/backend/backend/data/db.py

@@ -121,10 +121,14 @@ async def _raw_with_schema(
     Supports placeholders:
         - {schema_prefix}: Table/type prefix (e.g., "platform".)
         - {schema}: Raw schema name for application tables (e.g., platform)
-        - {pgvector_schema}: Schema where pgvector is installed (defaults to "public")
+
+    Note on pgvector types:
+        Use unqualified ::vector and <=> operator in queries. PostgreSQL resolves
+        these via search_path, which includes the schema where pgvector is installed
+        on all environments (local, CI, dev).
 
     Args:
-        query_template: SQL query with {schema_prefix}, {schema}, and/or {pgvector_schema} placeholders
+        query_template: SQL query with {schema_prefix} and/or {schema} placeholders
         *args: Query parameters
         execute: If False, executes SELECT query. If True, executes INSERT/UPDATE/DELETE.
         client: Optional Prisma client for transactions (only used when execute=True).
@@ -135,20 +139,16 @@ async def _raw_with_schema(
 
     Example with vector type:
         await execute_raw_with_schema(
-            'INSERT INTO {schema_prefix}"Embedding" (vec) VALUES ($1::{pgvector_schema}.vector)',
+            'INSERT INTO {schema_prefix}"Embedding" (vec) VALUES ($1::vector)',
             embedding_data
         )
     """
     schema = get_database_schema()
     schema_prefix = f'"{schema}".' if schema != "public" else ""
-    # pgvector extension is typically installed in "public" schema
-    # On Supabase it may be in "extensions" but "public" is the common default
-    pgvector_schema = "public"
 
     formatted_query = query_template.format(
         schema_prefix=schema_prefix,
         schema=schema,
-        pgvector_schema=pgvector_schema,
     )
 
     import prisma as prisma_module

autogpt_platform/backend/backend/data/event_bus.py

@@ -103,8 +103,18 @@ class RedisEventBus(BaseRedisEventBus[M], ABC):
         return redis.get_redis()
 
     def publish_event(self, event: M, channel_key: str):
-        message, full_channel_name = self._serialize_message(event, channel_key)
+        """
-        self.connection.publish(full_channel_name, message)
+        Publish an event to Redis. Gracefully handles connection failures
+        by logging the error instead of raising exceptions.
+        """
+        try:
+            message, full_channel_name = self._serialize_message(event, channel_key)
+            self.connection.publish(full_channel_name, message)
+        except Exception:
+            logger.exception(
+                f"Failed to publish event to Redis channel {channel_key}. "
+                "Event bus operation will continue without Redis connectivity."
+            )
 
     def listen_events(self, channel_key: str) -> Generator[M, None, None]:
         pubsub, full_channel_name = self._get_pubsub_channel(
@@ -128,9 +138,19 @@ class AsyncRedisEventBus(BaseRedisEventBus[M], ABC):
         return await redis.get_redis_async()
 
     async def publish_event(self, event: M, channel_key: str):
-        message, full_channel_name = self._serialize_message(event, channel_key)
+        """
-        connection = await self.connection
+        Publish an event to Redis. Gracefully handles connection failures
-        await connection.publish(full_channel_name, message)
+        by logging the error instead of raising exceptions.
+        """
+        try:
+            message, full_channel_name = self._serialize_message(event, channel_key)
+            connection = await self.connection
+            await connection.publish(full_channel_name, message)
+        except Exception:
+            logger.exception(
+                f"Failed to publish event to Redis channel {channel_key}. "
+                "Event bus operation will continue without Redis connectivity."
+            )
 
     async def listen_events(self, channel_key: str) -> AsyncGenerator[M, None]:
         pubsub, full_channel_name = self._get_pubsub_channel(

autogpt_platform/backend/backend/data/event_bus_test.py

@@ -0,0 +1,56 @@
+"""
+Tests for event_bus graceful degradation when Redis is unavailable.
+"""
+
+from unittest.mock import AsyncMock, patch
+
+import pytest
+from pydantic import BaseModel
+
+from backend.data.event_bus import AsyncRedisEventBus
+
+
+class TestEvent(BaseModel):
+    """Test event model."""
+
+    message: str
+
+
+class TestNotificationBus(AsyncRedisEventBus[TestEvent]):
+    """Test implementation of AsyncRedisEventBus."""
+
+    Model = TestEvent
+
+    @property
+    def event_bus_name(self) -> str:
+        return "test_event_bus"
+
+
+@pytest.mark.asyncio
+async def test_publish_event_handles_connection_failure_gracefully():
+    """Test that publish_event logs exception instead of raising when Redis is unavailable."""
+    bus = TestNotificationBus()
+    event = TestEvent(message="test message")
+
+    # Mock get_redis_async to raise connection error
+    with patch(
+        "backend.data.event_bus.redis.get_redis_async",
+        side_effect=ConnectionError("Authentication required."),
+    ):
+        # Should not raise exception
+        await bus.publish_event(event, "test_channel")
+
+
+@pytest.mark.asyncio
+async def test_publish_event_works_with_redis_available():
+    """Test that publish_event works normally when Redis is available."""
+    bus = TestNotificationBus()
+    event = TestEvent(message="test message")
+
+    # Mock successful Redis connection
+    mock_redis = AsyncMock()
+    mock_redis.publish = AsyncMock()
+
+    with patch("backend.data.event_bus.redis.get_redis_async", return_value=mock_redis):
+        await bus.publish_event(event, "test_channel")
+        mock_redis.publish.assert_called_once()

autogpt_platform/backend/backend/data/execution.py

@@ -81,6 +81,8 @@ class ExecutionContext(BaseModel):
     This includes information needed by blocks, sub-graphs, and execution management.
     """
 
+    model_config = {"extra": "ignore"}
+
     human_in_the_loop_safe_mode: bool = True
     sensitive_action_safe_mode: bool = False
     user_timezone: str = "UTC"

autogpt_platform/backend/backend/data/graph.py

@@ -64,6 +64,8 @@ logger = logging.getLogger(__name__)
 class GraphSettings(BaseModel):
     # Use Annotated with BeforeValidator to coerce None to default values.
     # This handles cases where the database has null values for these fields.
+    model_config = {"extra": "ignore"}
+
     human_in_the_loop_safe_mode: Annotated[
         bool, BeforeValidator(lambda v: v if v is not None else True)
     ] = True

autogpt_platform/backend/migrations/20260109181714_add_docs_embedding/migration.sql

@@ -1,11 +1,37 @@
 -- CreateExtension
 -- Supabase: pgvector must be enabled via Dashboard → Database → Extensions first
--- Create in public schema so vector type is available across all schemas
+-- Ensures vector extension is in the current schema (from DATABASE_URL ?schema= param)
+-- If it exists in a different schema (e.g., public), we drop and recreate it in the current schema
+-- This ensures vector type is in the same schema as tables, making ::vector work without explicit qualification
 DO $$
+DECLARE
+    current_schema_name text;
+    vector_schema text;
 BEGIN
-    CREATE EXTENSION IF NOT EXISTS "vector" WITH SCHEMA "public";
+    -- Get the current schema from search_path
-EXCEPTION WHEN OTHERS THEN
+    SELECT current_schema() INTO current_schema_name;
-    RAISE NOTICE 'vector extension not available or already exists, skipping';
+
+    -- Check if vector extension exists and which schema it's in
+    SELECT n.nspname INTO vector_schema
+    FROM pg_extension e
+    JOIN pg_namespace n ON e.extnamespace = n.oid
+    WHERE e.extname = 'vector';
+
+    -- Handle removal if in wrong schema
+    IF vector_schema IS NOT NULL AND vector_schema != current_schema_name THEN
+        BEGIN
+            -- Vector exists in a different schema, drop it first
+            RAISE WARNING 'pgvector found in schema "%" but need it in "%". Dropping and reinstalling...',
+                vector_schema, current_schema_name;
+            EXECUTE 'DROP EXTENSION IF EXISTS vector CASCADE';
+        EXCEPTION WHEN OTHERS THEN
+            RAISE EXCEPTION 'Failed to drop pgvector from schema "%": %. You may need to drop it manually.',
+                vector_schema, SQLERRM;
+        END;
+    END IF;
+
+    -- Create extension in current schema (let it fail naturally if not available)
+    EXECUTE format('CREATE EXTENSION IF NOT EXISTS vector SCHEMA %I', current_schema_name);
 END $$;
 
 -- CreateEnum
@@ -19,7 +45,7 @@ CREATE TABLE "UnifiedContentEmbedding" (
     "contentType" "ContentType" NOT NULL,
     "contentId" TEXT NOT NULL,
     "userId" TEXT,
-    "embedding" public.vector(1536) NOT NULL,
+    "embedding" vector(1536) NOT NULL,
     "searchableText" TEXT NOT NULL,
     "metadata" JSONB NOT NULL DEFAULT '{}',
 
@@ -45,4 +71,4 @@ CREATE UNIQUE INDEX "UnifiedContentEmbedding_contentType_contentId_userId_key" O
 -- Uses cosine distance operator (<=>), which matches the query in hybrid_search.py
 -- Note: Drop first in case Prisma created a btree index (Prisma doesn't support HNSW)
 DROP INDEX IF EXISTS "UnifiedContentEmbedding_embedding_idx";
-CREATE INDEX "UnifiedContentEmbedding_embedding_idx" ON "UnifiedContentEmbedding" USING hnsw ("embedding" public.vector_cosine_ops);
+CREATE INDEX "UnifiedContentEmbedding_embedding_idx" ON "UnifiedContentEmbedding" USING hnsw ("embedding" vector_cosine_ops);

autogpt_platform/backend/migrations/20260112173500_add_supabase_extensions_to_platform_schema/migration.sql

@@ -1,71 +0,0 @@
--- Acknowledge Supabase-managed extensions to prevent drift warnings
--- These extensions are pre-installed by Supabase in specific schemas
--- This migration ensures they exist where available (Supabase) or skips gracefully (CI)
-
--- Create schemas (safe in both CI and Supabase)
-CREATE SCHEMA IF NOT EXISTS "extensions";
-
--- Extensions that exist in both CI and Supabase
-DO $$
-BEGIN
-    CREATE EXTENSION IF NOT EXISTS "pgcrypto" WITH SCHEMA "extensions";
-EXCEPTION WHEN OTHERS THEN
-    RAISE NOTICE 'pgcrypto extension not available, skipping';
-END $$;
-
-DO $$
-BEGIN
-    CREATE EXTENSION IF NOT EXISTS "uuid-ossp" WITH SCHEMA "extensions";
-EXCEPTION WHEN OTHERS THEN
-    RAISE NOTICE 'uuid-ossp extension not available, skipping';
-END $$;
-
--- Supabase-specific extensions (skip gracefully in CI)
-DO $$
-BEGIN
-    CREATE EXTENSION IF NOT EXISTS "pg_stat_statements" WITH SCHEMA "extensions";
-EXCEPTION WHEN OTHERS THEN
-    RAISE NOTICE 'pg_stat_statements extension not available, skipping';
-END $$;
-
-DO $$
-BEGIN
-    CREATE EXTENSION IF NOT EXISTS "pg_net" WITH SCHEMA "extensions";
-EXCEPTION WHEN OTHERS THEN
-    RAISE NOTICE 'pg_net extension not available, skipping';
-END $$;
-
-DO $$
-BEGIN
-    CREATE EXTENSION IF NOT EXISTS "pgjwt" WITH SCHEMA "extensions";
-EXCEPTION WHEN OTHERS THEN
-    RAISE NOTICE 'pgjwt extension not available, skipping';
-END $$;
-
-DO $$
-BEGIN
-    CREATE SCHEMA IF NOT EXISTS "graphql";
-    CREATE EXTENSION IF NOT EXISTS "pg_graphql" WITH SCHEMA "graphql";
-EXCEPTION WHEN OTHERS THEN
-    RAISE NOTICE 'pg_graphql extension not available, skipping';
-END $$;
-
-DO $$
-BEGIN
-    CREATE SCHEMA IF NOT EXISTS "pgsodium";
-    CREATE EXTENSION IF NOT EXISTS "pgsodium" WITH SCHEMA "pgsodium";
-EXCEPTION WHEN OTHERS THEN
-    RAISE NOTICE 'pgsodium extension not available, skipping';
-END $$;
-
-DO $$
-BEGIN
-    CREATE SCHEMA IF NOT EXISTS "vault";
-    CREATE EXTENSION IF NOT EXISTS "supabase_vault" WITH SCHEMA "vault";
-EXCEPTION WHEN OTHERS THEN
-    RAISE NOTICE 'supabase_vault extension not available, skipping';
-END $$;
-
-
--- Return to platform
-CREATE SCHEMA IF NOT EXISTS "platform";

autogpt_platform/backend/scripts/generate_block_docs.py

@@ -366,12 +366,12 @@ def generate_block_markdown(
     lines.append("")
 
     # What it is (full description)
-    lines.append(f"### What it is")
+    lines.append("### What it is")
     lines.append(block.description or "No description available.")
     lines.append("")
 
     # How it works (manual section)
-    lines.append(f"### How it works")
+    lines.append("### How it works")
     how_it_works = manual_content.get(
         "how_it_works", "_Add technical explanation here._"
     )
@@ -383,7 +383,7 @@ def generate_block_markdown(
     # Inputs table (auto-generated)
     visible_inputs = [f for f in block.inputs if not f.hidden]
     if visible_inputs:
-        lines.append(f"### Inputs")
+        lines.append("### Inputs")
         lines.append("")
         lines.append("| Input | Description | Type | Required |")
         lines.append("|-------|-------------|------|----------|")
@@ -400,7 +400,7 @@ def generate_block_markdown(
     # Outputs table (auto-generated)
     visible_outputs = [f for f in block.outputs if not f.hidden]
     if visible_outputs:
-        lines.append(f"### Outputs")
+        lines.append("### Outputs")
         lines.append("")
         lines.append("| Output | Description | Type |")
         lines.append("|--------|-------------|------|")
@@ -414,7 +414,7 @@ def generate_block_markdown(
         lines.append("")
 
     # Possible use case (manual section)
-    lines.append(f"### Possible use case")
+    lines.append("### Possible use case")
     use_case = manual_content.get("use_case", "_Add practical use case examples here._")
     lines.append("<!-- MANUAL: use_case -->")
     lines.append(use_case)

autogpt_platform/frontend/CONTRIBUTING.md

@@ -175,6 +175,8 @@ While server components and actions are cool and cutting-edge, they introduce a
 
 - Prefer [React Query](https://tanstack.com/query/latest/docs/framework/react/overview) for server state, colocated near consumers (see [state colocation](https://kentcdodds.com/blog/state-colocation-will-make-your-react-app-faster))
 - Co-locate UI state inside components/hooks; keep global state minimal
+- Avoid `useMemo` and `useCallback` unless you have a measured performance issue
+- Do not abuse `useEffect`; prefer state colocation and derive values directly when possible
 
 ### Styling and components
 
@@ -549,9 +551,48 @@ Files:
 Types:
 
 - Prefer `interface` for object shapes
-- Component props should be `interface Props { ... }`
+- Component props should be `interface Props { ... }` (not exported)
+- Only use specific exported names (e.g., `export interface MyComponentProps`) when the interface needs to be used outside the component
+- Keep type definitions inline with the component - do not create separate `types.ts` files unless types are shared across multiple files
 - Use precise types; avoid `any` and unsafe casts
 
+**Props naming examples:**
+
+```tsx
+// ✅ Good - internal props, not exported
+interface Props {
+  title: string;
+  onClose: () => void;
+}
+
+export function Modal({ title, onClose }: Props) {
+  // ...
+}
+
+// ✅ Good - exported when needed externally
+export interface ModalProps {
+  title: string;
+  onClose: () => void;
+}
+
+export function Modal({ title, onClose }: ModalProps) {
+  // ...
+}
+
+// ❌ Bad - unnecessarily specific name for internal use
+interface ModalComponentProps {
+  title: string;
+  onClose: () => void;
+}
+
+// ❌ Bad - separate types.ts file for single component
+// types.ts
+export interface ModalProps { ... }
+
+// Modal.tsx
+import type { ModalProps } from './types';
+```
+
 Parameters:
 
 - If more than one parameter is needed, pass a single `Args` object for clarity

autogpt_platform/frontend/orval.config.ts

@@ -16,6 +16,12 @@ export default defineConfig({
       client: "react-query",
       httpClient: "fetch",
       indexFiles: false,
+      mock: {
+        type: "msw",
+        baseUrl: "http://localhost:3000/api/proxy",
+        generateEachHttpStatus: true,
+        delay: 0,
+      },
       override: {
         mutator: {
           path: "./mutators/custom-mutator.ts",

autogpt_platform/frontend/package.json

@@ -15,6 +15,8 @@
     "types": "tsc --noEmit",
     "test": "NEXT_PUBLIC_PW_TEST=true next build --turbo && playwright test",
     "test-ui": "NEXT_PUBLIC_PW_TEST=true next build --turbo && playwright test --ui",
+    "test:unit": "vitest run",
+    "test:unit:watch": "vitest",
     "test:no-build": "playwright test",
     "gentests": "playwright codegen http://localhost:3000",
     "storybook": "storybook dev -p 6006",
@@ -118,6 +120,7 @@
   },
   "devDependencies": {
     "@chromatic-com/storybook": "4.1.2",
+    "happy-dom": "20.3.4",
     "@opentelemetry/instrumentation": "0.209.0",
     "@playwright/test": "1.56.1",
     "@storybook/addon-a11y": "9.1.5",
@@ -127,6 +130,8 @@
     "@storybook/nextjs": "9.1.5",
     "@tanstack/eslint-plugin-query": "5.91.2",
     "@tanstack/react-query-devtools": "5.90.2",
+    "@testing-library/dom": "10.4.1",
+    "@testing-library/react": "16.3.2",
     "@types/canvas-confetti": "1.9.0",
     "@types/lodash": "4.17.20",
     "@types/negotiator": "0.6.4",
@@ -135,6 +140,7 @@
     "@types/react-dom": "18.3.5",
     "@types/react-modal": "3.16.3",
     "@types/react-window": "1.8.8",
+    "@vitejs/plugin-react": "5.1.2",
     "axe-playwright": "2.2.2",
     "chromatic": "13.3.3",
     "concurrently": "9.2.1",
@@ -153,7 +159,9 @@
     "require-in-the-middle": "8.0.1",
     "storybook": "9.1.5",
     "tailwindcss": "3.4.17",
-    "typescript": "5.9.3"
+    "typescript": "5.9.3",
+    "vite-tsconfig-paths": "6.0.4",
+    "vitest": "4.0.17"
   },
   "msw": {
     "workerDirectory": [

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

@@ -0,0 +1,58 @@
+"use client";
+
+import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
+import { Text } from "@/components/atoms/Text/Text";
+import { useToast } from "@/components/molecules/Toast/use-toast";
+import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
+import { useRouter } from "next/navigation";
+import { useEffect, useRef } from "react";
+
+const LOGOUT_REDIRECT_DELAY_MS = 400;
+
+function wait(ms: number): Promise<void> {
+  return new Promise(function resolveAfterDelay(resolve) {
+    setTimeout(resolve, ms);
+  });
+}
+
+export default function LogoutPage() {
+  const { logOut } = useSupabase();
+  const { toast } = useToast();
+  const router = useRouter();
+  const hasStartedRef = useRef(false);
+
+  useEffect(
+    function handleLogoutEffect() {
+      if (hasStartedRef.current) return;
+      hasStartedRef.current = true;
+
+      async function runLogout() {
+        try {
+          await logOut();
+        } catch {
+          toast({
+            title: "Failed to log out. Redirecting to login.",
+            variant: "destructive",
+          });
+        } finally {
+          await wait(LOGOUT_REDIRECT_DELAY_MS);
+          router.replace("/login");
+        }
+      }
+
+      void runLogout();
+    },
+    [logOut, router, toast],
+  );
+
+  return (
+    <div className="flex min-h-screen items-center justify-center px-4">
+      <div className="flex flex-col items-center justify-center gap-4 py-8">
+        <LoadingSpinner size="large" />
+        <Text variant="body" className="text-center">
+          Logging you out...
+        </Text>
+      </div>
+    </div>
+  );
+}

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

@@ -9,7 +9,7 @@ export async function GET(request: Request) {
   const { searchParams, origin } = new URL(request.url);
   const code = searchParams.get("code");
 
-  let next = "/marketplace";
+  let next = "/";
 
   if (code) {
     const supabase = await getServerSupabase();

autogpt_platform/frontend/src/app/(platform)/chat/components/Chat/Chat.tsx

@@ -1,134 +0,0 @@
-"use client";
-
-import { Button } from "@/components/atoms/Button/Button";
-import { Text } from "@/components/atoms/Text/Text";
-import { cn } from "@/lib/utils";
-import { List } from "@phosphor-icons/react";
-import React, { useState } from "react";
-import { ChatContainer } from "./components/ChatContainer/ChatContainer";
-import { ChatErrorState } from "./components/ChatErrorState/ChatErrorState";
-import { ChatLoadingState } from "./components/ChatLoadingState/ChatLoadingState";
-import { SessionsDrawer } from "./components/SessionsDrawer/SessionsDrawer";
-import { useChat } from "./useChat";
-
-export interface ChatProps {
-  className?: string;
-  headerTitle?: React.ReactNode;
-  showHeader?: boolean;
-  showSessionInfo?: boolean;
-  showNewChatButton?: boolean;
-  onNewChat?: () => void;
-  headerActions?: React.ReactNode;
-}
-
-export function Chat({
-  className,
-  headerTitle = "AutoGPT Copilot",
-  showHeader = true,
-  showSessionInfo = true,
-  showNewChatButton = true,
-  onNewChat,
-  headerActions,
-}: ChatProps) {
-  const {
-    messages,
-    isLoading,
-    isCreating,
-    error,
-    sessionId,
-    createSession,
-    clearSession,
-    loadSession,
-  } = useChat();
-
-  const [isSessionsDrawerOpen, setIsSessionsDrawerOpen] = useState(false);
-
-  const handleNewChat = () => {
-    clearSession();
-    onNewChat?.();
-  };
-
-  const handleSelectSession = async (sessionId: string) => {
-    try {
-      await loadSession(sessionId);
-    } catch (err) {
-      console.error("Failed to load session:", err);
-    }
-  };
-
-  return (
-    <div className={cn("flex h-full flex-col", className)}>
-      {/* Header */}
-      {showHeader && (
-        <header className="shrink-0 border-t border-zinc-200 bg-white p-3">
-          <div className="flex items-center justify-between">
-            <div className="flex items-center gap-3">
-              <button
-                aria-label="View sessions"
-                onClick={() => setIsSessionsDrawerOpen(true)}
-                className="flex size-8 items-center justify-center rounded hover:bg-zinc-100"
-              >
-                <List width="1.25rem" height="1.25rem" />
-              </button>
-              {typeof headerTitle === "string" ? (
-                <Text variant="h2" className="text-lg font-semibold">
-                  {headerTitle}
-                </Text>
-              ) : (
-                headerTitle
-              )}
-            </div>
-            <div className="flex items-center gap-3">
-              {showSessionInfo && sessionId && (
-                <>
-                  {showNewChatButton && (
-                    <Button
-                      variant="outline"
-                      size="small"
-                      onClick={handleNewChat}
-                    >
-                      New Chat
-                    </Button>
-                  )}
-                </>
-              )}
-              {headerActions}
-            </div>
-          </div>
-        </header>
-      )}
-
-      {/* Main Content */}
-      <main className="flex min-h-0 flex-1 flex-col overflow-hidden">
-        {/* Loading State - show when explicitly loading/creating OR when we don't have a session yet and no error */}
-        {(isLoading || isCreating || (!sessionId && !error)) && (
-          <ChatLoadingState
-            message={isCreating ? "Creating session..." : "Loading..."}
-          />
-        )}
-
-        {/* Error State */}
-        {error && !isLoading && (
-          <ChatErrorState error={error} onRetry={createSession} />
-        )}
-
-        {/* Session Content */}
-        {sessionId && !isLoading && !error && (
-          <ChatContainer
-            sessionId={sessionId}
-            initialMessages={messages}
-            className="flex-1"
-          />
-        )}
-      </main>
-
-      {/* Sessions Drawer */}
-      <SessionsDrawer
-        isOpen={isSessionsDrawerOpen}
-        onClose={() => setIsSessionsDrawerOpen(false)}
-        onSelectSession={handleSelectSession}
-        currentSessionId={sessionId}
-      />
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/chat/components/Chat/components/ChatContainer/ChatContainer.tsx

@@ -1,88 +0,0 @@
-import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
-import { cn } from "@/lib/utils";
-import { useCallback } from "react";
-import { usePageContext } from "../../usePageContext";
-import { ChatInput } from "../ChatInput/ChatInput";
-import { MessageList } from "../MessageList/MessageList";
-import { QuickActionsWelcome } from "../QuickActionsWelcome/QuickActionsWelcome";
-import { useChatContainer } from "./useChatContainer";
-
-export interface ChatContainerProps {
-  sessionId: string | null;
-  initialMessages: SessionDetailResponse["messages"];
-  className?: string;
-}
-
-export function ChatContainer({
-  sessionId,
-  initialMessages,
-  className,
-}: ChatContainerProps) {
-  const { messages, streamingChunks, isStreaming, sendMessage } =
-    useChatContainer({
-      sessionId,
-      initialMessages,
-    });
-  const { capturePageContext } = usePageContext();
-
-  // Wrap sendMessage to automatically capture page context
-  const sendMessageWithContext = useCallback(
-    async (content: string, isUserMessage: boolean = true) => {
-      const context = capturePageContext();
-      await sendMessage(content, isUserMessage, context);
-    },
-    [sendMessage, capturePageContext],
-  );
-
-  const quickActions = [
-    "Find agents for social media management",
-    "Show me agents for content creation",
-    "Help me automate my business",
-    "What can you help me with?",
-  ];
-
-  return (
-    <div
-      className={cn("flex h-full min-h-0 flex-col", className)}
-      style={{
-        backgroundColor: "#ffffff",
-        backgroundImage:
-          "radial-gradient(#e5e5e5 0.5px, transparent 0.5px), radial-gradient(#e5e5e5 0.5px, #ffffff 0.5px)",
-        backgroundSize: "20px 20px",
-        backgroundPosition: "0 0, 10px 10px",
-      }}
-    >
-      {/* Messages or Welcome Screen */}
-      <div className="flex min-h-0 flex-1 flex-col overflow-hidden pb-24">
-        {messages.length === 0 ? (
-          <QuickActionsWelcome
-            title="Welcome to AutoGPT Copilot"
-            description="Start a conversation to discover and run AI agents."
-            actions={quickActions}
-            onActionClick={sendMessageWithContext}
-            disabled={isStreaming || !sessionId}
-          />
-        ) : (
-          <MessageList
-            messages={messages}
-            streamingChunks={streamingChunks}
-            isStreaming={isStreaming}
-            onSendMessage={sendMessageWithContext}
-            className="flex-1"
-          />
-        )}
-      </div>
-
-      {/* Input - Always visible */}
-      <div className="fixed bottom-0 left-0 right-0 z-50 border-t border-zinc-200 bg-white p-4">
-        <ChatInput
-          onSend={sendMessageWithContext}
-          disabled={isStreaming || !sessionId}
-          placeholder={
-            sessionId ? "Type your message..." : "Creating session..."
-          }
-        />
-      </div>
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/chat/components/Chat/components/ChatInput/ChatInput.tsx

@@ -1,64 +0,0 @@
-import { Input } from "@/components/atoms/Input/Input";
-import { cn } from "@/lib/utils";
-import { ArrowUpIcon } from "@phosphor-icons/react";
-import { useChatInput } from "./useChatInput";
-
-export interface ChatInputProps {
-  onSend: (message: string) => void;
-  disabled?: boolean;
-  placeholder?: string;
-  className?: string;
-}
-
-export function ChatInput({
-  onSend,
-  disabled = false,
-  placeholder = "Type your message...",
-  className,
-}: ChatInputProps) {
-  const inputId = "chat-input";
-  const { value, setValue, handleKeyDown, handleSend } = useChatInput({
-    onSend,
-    disabled,
-    maxRows: 5,
-    inputId,
-  });
-
-  return (
-    <div className={cn("relative flex-1", className)}>
-      <Input
-        id={inputId}
-        label="Chat message input"
-        hideLabel
-        type="textarea"
-        value={value}
-        onChange={(e) => setValue(e.target.value)}
-        onKeyDown={handleKeyDown}
-        placeholder={placeholder}
-        disabled={disabled}
-        rows={1}
-        wrapperClassName="mb-0 relative"
-        className="pr-12"
-      />
-      <span id="chat-input-hint" className="sr-only">
-        Press Enter to send, Shift+Enter for new line
-      </span>
-
-      <button
-        onClick={handleSend}
-        disabled={disabled || !value.trim()}
-        className={cn(
-          "absolute right-3 top-1/2 flex h-8 w-8 -translate-y-1/2 items-center justify-center rounded-full",
-          "border border-zinc-800 bg-zinc-800 text-white",
-          "hover:border-zinc-900 hover:bg-zinc-900",
-          "disabled:border-zinc-200 disabled:bg-zinc-200 disabled:text-white disabled:opacity-50",
-          "transition-colors focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-neutral-950",
-          "disabled:pointer-events-none",
-        )}
-        aria-label="Send message"
-      >
-        <ArrowUpIcon className="h-3 w-3" weight="bold" />
-      </button>
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/chat/components/Chat/components/ChatInput/useChatInput.ts

@@ -1,60 +0,0 @@
-import { KeyboardEvent, useCallback, useEffect, useState } from "react";
-
-interface UseChatInputArgs {
-  onSend: (message: string) => void;
-  disabled?: boolean;
-  maxRows?: number;
-  inputId?: string;
-}
-
-export function useChatInput({
-  onSend,
-  disabled = false,
-  maxRows = 5,
-  inputId = "chat-input",
-}: UseChatInputArgs) {
-  const [value, setValue] = useState("");
-
-  useEffect(() => {
-    const textarea = document.getElementById(inputId) as HTMLTextAreaElement;
-    if (!textarea) return;
-    textarea.style.height = "auto";
-    const lineHeight = parseInt(
-      window.getComputedStyle(textarea).lineHeight,
-      10,
-    );
-    const maxHeight = lineHeight * maxRows;
-    const newHeight = Math.min(textarea.scrollHeight, maxHeight);
-    textarea.style.height = `${newHeight}px`;
-    textarea.style.overflowY =
-      textarea.scrollHeight > maxHeight ? "auto" : "hidden";
-  }, [value, maxRows, inputId]);
-
-  const handleSend = useCallback(() => {
-    if (disabled || !value.trim()) return;
-    onSend(value.trim());
-    setValue("");
-    const textarea = document.getElementById(inputId) as HTMLTextAreaElement;
-    if (textarea) {
-      textarea.style.height = "auto";
-    }
-  }, [value, onSend, disabled, inputId]);
-
-  const handleKeyDown = useCallback(
-    (event: KeyboardEvent<HTMLInputElement | HTMLTextAreaElement>) => {
-      if (event.key === "Enter" && !event.shiftKey) {
-        event.preventDefault();
-        handleSend();
-      }
-      // Shift+Enter allows default behavior (new line) - no need to handle explicitly
-    },
-    [handleSend],
-  );
-
-  return {
-    value,
-    setValue,
-    handleKeyDown,
-    handleSend,
-  };
-}

autogpt_platform/frontend/src/app/(platform)/chat/components/Chat/components/MessageList/MessageList.tsx

@@ -1,121 +0,0 @@
-"use client";
-
-import { cn } from "@/lib/utils";
-import { ChatMessage } from "../ChatMessage/ChatMessage";
-import type { ChatMessageData } from "../ChatMessage/useChatMessage";
-import { StreamingMessage } from "../StreamingMessage/StreamingMessage";
-import { ThinkingMessage } from "../ThinkingMessage/ThinkingMessage";
-import { useMessageList } from "./useMessageList";
-
-export interface MessageListProps {
-  messages: ChatMessageData[];
-  streamingChunks?: string[];
-  isStreaming?: boolean;
-  className?: string;
-  onStreamComplete?: () => void;
-  onSendMessage?: (content: string) => void;
-}
-
-export function MessageList({
-  messages,
-  streamingChunks = [],
-  isStreaming = false,
-  className,
-  onStreamComplete,
-  onSendMessage,
-}: MessageListProps) {
-  const { messagesEndRef, messagesContainerRef } = useMessageList({
-    messageCount: messages.length,
-    isStreaming,
-  });
-
-  return (
-    <div
-      ref={messagesContainerRef}
-      className={cn(
-        "flex-1 overflow-y-auto",
-        "scrollbar-thin scrollbar-track-transparent scrollbar-thumb-zinc-300",
-        className,
-      )}
-    >
-      <div className="mx-auto flex max-w-3xl flex-col py-4">
-        {/* Render all persisted messages */}
-        {messages.map((message, index) => {
-          // Check if current message is an agent_output tool_response
-          // and if previous message is an assistant message
-          let agentOutput: ChatMessageData | undefined;
-
-          if (message.type === "tool_response" && message.result) {
-            let parsedResult: Record<string, unknown> | null = null;
-            try {
-              parsedResult =
-                typeof message.result === "string"
-                  ? JSON.parse(message.result)
-                  : (message.result as Record<string, unknown>);
-            } catch {
-              parsedResult = null;
-            }
-            if (parsedResult?.type === "agent_output") {
-              const prevMessage = messages[index - 1];
-              if (
-                prevMessage &&
-                prevMessage.type === "message" &&
-                prevMessage.role === "assistant"
-              ) {
-                // This agent output will be rendered inside the previous assistant message
-                // Skip rendering this message separately
-                return null;
-              }
-            }
-          }
-
-          // Check if next message is an agent_output tool_response to include in current assistant message
-          if (message.type === "message" && message.role === "assistant") {
-            const nextMessage = messages[index + 1];
-            if (
-              nextMessage &&
-              nextMessage.type === "tool_response" &&
-              nextMessage.result
-            ) {
-              let parsedResult: Record<string, unknown> | null = null;
-              try {
-                parsedResult =
-                  typeof nextMessage.result === "string"
-                    ? JSON.parse(nextMessage.result)
-                    : (nextMessage.result as Record<string, unknown>);
-              } catch {
-                parsedResult = null;
-              }
-              if (parsedResult?.type === "agent_output") {
-                agentOutput = nextMessage;
-              }
-            }
-          }
-
-          return (
-            <ChatMessage
-              key={index}
-              message={message}
-              onSendMessage={onSendMessage}
-              agentOutput={agentOutput}
-            />
-          );
-        })}
-
-        {/* Render thinking message when streaming but no chunks yet */}
-        {isStreaming && streamingChunks.length === 0 && <ThinkingMessage />}
-
-        {/* Render streaming message if active */}
-        {isStreaming && streamingChunks.length > 0 && (
-          <StreamingMessage
-            chunks={streamingChunks}
-            onComplete={onStreamComplete}
-          />
-        )}
-
-        {/* Invisible div to scroll to */}
-        <div ref={messagesEndRef} />
-      </div>
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/chat/components/Chat/components/ToolCallMessage/ToolCallMessage.tsx

@@ -1,24 +0,0 @@
-import { Text } from "@/components/atoms/Text/Text";
-import { cn } from "@/lib/utils";
-import { WrenchIcon } from "@phosphor-icons/react";
-import { getToolActionPhrase } from "../../helpers";
-
-export interface ToolCallMessageProps {
-  toolName: string;
-  className?: string;
-}
-
-export function ToolCallMessage({ toolName, className }: ToolCallMessageProps) {
-  return (
-    <div className={cn("flex items-center justify-center gap-2", className)}>
-      <WrenchIcon
-        size={14}
-        weight="bold"
-        className="flex-shrink-0 text-neutral-500"
-      />
-      <Text variant="small" className="text-neutral-500">
-        {getToolActionPhrase(toolName)}...
-      </Text>
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/chat/components/Chat/components/ToolResponseMessage/ToolResponseMessage.tsx

@@ -1,260 +0,0 @@
-import { Text } from "@/components/atoms/Text/Text";
-import "@/components/contextual/OutputRenderers";
-import {
-  globalRegistry,
-  OutputItem,
-} from "@/components/contextual/OutputRenderers";
-import { cn } from "@/lib/utils";
-import type { ToolResult } from "@/types/chat";
-import { WrenchIcon } from "@phosphor-icons/react";
-import { getToolActionPhrase } from "../../helpers";
-
-export interface ToolResponseMessageProps {
-  toolName: string;
-  result?: ToolResult;
-  success?: boolean;
-  className?: string;
-}
-
-export function ToolResponseMessage({
-  toolName,
-  result,
-  success: _success = true,
-  className,
-}: ToolResponseMessageProps) {
-  if (!result) {
-    return (
-      <div className={cn("flex items-center justify-center gap-2", className)}>
-        <WrenchIcon
-          size={14}
-          weight="bold"
-          className="flex-shrink-0 text-neutral-500"
-        />
-        <Text variant="small" className="text-neutral-500">
-          {getToolActionPhrase(toolName)}...
-        </Text>
-      </div>
-    );
-  }
-
-  let parsedResult: Record<string, unknown> | null = null;
-  try {
-    parsedResult =
-      typeof result === "string"
-        ? JSON.parse(result)
-        : (result as Record<string, unknown>);
-  } catch {
-    parsedResult = null;
-  }
-
-  if (parsedResult && typeof parsedResult === "object") {
-    const responseType = parsedResult.type as string | undefined;
-
-    if (responseType === "agent_output") {
-      const execution = parsedResult.execution as
-        | {
-            outputs?: Record<string, unknown[]>;
-          }
-        | null
-        | undefined;
-      const outputs = execution?.outputs || {};
-      const message = parsedResult.message as string | undefined;
-
-      return (
-        <div className={cn("space-y-4 px-4 py-2", className)}>
-          <div className="flex items-center gap-2">
-            <WrenchIcon
-              size={14}
-              weight="bold"
-              className="flex-shrink-0 text-neutral-500"
-            />
-            <Text variant="small" className="text-neutral-500">
-              {getToolActionPhrase(toolName)}
-            </Text>
-          </div>
-          {message && (
-            <div className="rounded border p-4">
-              <Text variant="small" className="text-neutral-600">
-                {message}
-              </Text>
-            </div>
-          )}
-          {Object.keys(outputs).length > 0 && (
-            <div className="space-y-4">
-              {Object.entries(outputs).map(([outputName, values]) =>
-                values.map((value, index) => {
-                  const renderer = globalRegistry.getRenderer(value);
-                  if (renderer) {
-                    return (
-                      <OutputItem
-                        key={`${outputName}-${index}`}
-                        value={value}
-                        renderer={renderer}
-                        label={outputName}
-                      />
-                    );
-                  }
-                  return (
-                    <div
-                      key={`${outputName}-${index}`}
-                      className="rounded border p-4"
-                    >
-                      <Text variant="large-medium" className="mb-2 capitalize">
-                        {outputName}
-                      </Text>
-                      <pre className="overflow-auto text-sm">
-                        {JSON.stringify(value, null, 2)}
-                      </pre>
-                    </div>
-                  );
-                }),
-              )}
-            </div>
-          )}
-        </div>
-      );
-    }
-
-    if (responseType === "block_output" && parsedResult.outputs) {
-      const outputs = parsedResult.outputs as Record<string, unknown[]>;
-
-      return (
-        <div className={cn("space-y-4 px-4 py-2", className)}>
-          <div className="flex items-center gap-2">
-            <WrenchIcon
-              size={14}
-              weight="bold"
-              className="flex-shrink-0 text-neutral-500"
-            />
-            <Text variant="small" className="text-neutral-500">
-              {getToolActionPhrase(toolName)}
-            </Text>
-          </div>
-          <div className="space-y-4">
-            {Object.entries(outputs).map(([outputName, values]) =>
-              values.map((value, index) => {
-                const renderer = globalRegistry.getRenderer(value);
-                if (renderer) {
-                  return (
-                    <OutputItem
-                      key={`${outputName}-${index}`}
-                      value={value}
-                      renderer={renderer}
-                      label={outputName}
-                    />
-                  );
-                }
-                return (
-                  <div
-                    key={`${outputName}-${index}`}
-                    className="rounded border p-4"
-                  >
-                    <Text variant="large-medium" className="mb-2 capitalize">
-                      {outputName}
-                    </Text>
-                    <pre className="overflow-auto text-sm">
-                      {JSON.stringify(value, null, 2)}
-                    </pre>
-                  </div>
-                );
-              }),
-            )}
-          </div>
-        </div>
-      );
-    }
-
-    // Handle other response types with a message field (e.g., understanding_updated)
-    if (parsedResult.message && typeof parsedResult.message === "string") {
-      // Format tool name from snake_case to Title Case
-      const formattedToolName = toolName
-        .split("_")
-        .map((word) => word.charAt(0).toUpperCase() + word.slice(1))
-        .join(" ");
-
-      // Clean up message - remove incomplete user_name references
-      let cleanedMessage = parsedResult.message;
-      // Remove "Updated understanding with: user_name" pattern if user_name is just a placeholder
-      cleanedMessage = cleanedMessage.replace(
-        /Updated understanding with:\s*user_name\.?\s*/gi,
-        "",
-      );
-      // Remove standalone user_name references
-      cleanedMessage = cleanedMessage.replace(/\buser_name\b\.?\s*/gi, "");
-      cleanedMessage = cleanedMessage.trim();
-
-      // Only show message if it has content after cleaning
-      if (!cleanedMessage) {
-        return (
-          <div
-            className={cn(
-              "flex items-center justify-center gap-2 px-4 py-2",
-              className,
-            )}
-          >
-            <WrenchIcon
-              size={14}
-              weight="bold"
-              className="flex-shrink-0 text-neutral-500"
-            />
-            <Text variant="small" className="text-neutral-500">
-              {formattedToolName}
-            </Text>
-          </div>
-        );
-      }
-
-      return (
-        <div className={cn("space-y-2 px-4 py-2", className)}>
-          <div className="flex items-center justify-center gap-2">
-            <WrenchIcon
-              size={14}
-              weight="bold"
-              className="flex-shrink-0 text-neutral-500"
-            />
-            <Text variant="small" className="text-neutral-500">
-              {formattedToolName}
-            </Text>
-          </div>
-          <div className="rounded border p-4">
-            <Text variant="small" className="text-neutral-600">
-              {cleanedMessage}
-            </Text>
-          </div>
-        </div>
-      );
-    }
-  }
-
-  const renderer = globalRegistry.getRenderer(result);
-  if (renderer) {
-    return (
-      <div className={cn("px-4 py-2", className)}>
-        <div className="mb-2 flex items-center gap-2">
-          <WrenchIcon
-            size={14}
-            weight="bold"
-            className="flex-shrink-0 text-neutral-500"
-          />
-          <Text variant="small" className="text-neutral-500">
-            {getToolActionPhrase(toolName)}
-          </Text>
-        </div>
-        <OutputItem value={result} renderer={renderer} />
-      </div>
-    );
-  }
-
-  return (
-    <div className={cn("flex items-center justify-center gap-2", className)}>
-      <WrenchIcon
-        size={14}
-        weight="bold"
-        className="flex-shrink-0 text-neutral-500"
-      />
-      <Text variant="small" className="text-neutral-500">
-        {getToolActionPhrase(toolName)}...
-      </Text>
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/chat/components/Chat/helpers.ts

@@ -1,66 +0,0 @@
-/**
- * Maps internal tool names to user-friendly display names with emojis.
- * @deprecated Use getToolActionPhrase or getToolCompletionPhrase for status messages
- *
- * @param toolName - The internal tool name from the backend
- * @returns A user-friendly display name with an emoji prefix
- */
-export function getToolDisplayName(toolName: string): string {
-  const toolDisplayNames: Record<string, string> = {
-    find_agent: "🔍 Search Marketplace",
-    get_agent_details: "📋 Get Agent Details",
-    check_credentials: "🔑 Check Credentials",
-    setup_agent: "⚙️ Setup Agent",
-    run_agent: "▶️ Run Agent",
-    get_required_setup_info: "📝 Get Setup Requirements",
-  };
-  return toolDisplayNames[toolName] || toolName;
-}
-
-/**
- * Maps internal tool names to human-friendly action phrases (present continuous).
- * Used for tool call messages to indicate what action is currently happening.
- *
- * @param toolName - The internal tool name from the backend
- * @returns A human-friendly action phrase in present continuous tense
- */
-export function getToolActionPhrase(toolName: string): string {
-  const toolActionPhrases: Record<string, string> = {
-    find_agent: "Looking for agents in the marketplace",
-    agent_carousel: "Looking for agents in the marketplace",
-    get_agent_details: "Learning about the agent",
-    check_credentials: "Checking your credentials",
-    setup_agent: "Setting up the agent",
-    execution_started: "Running the agent",
-    run_agent: "Running the agent",
-    get_required_setup_info: "Getting setup requirements",
-    schedule_agent: "Scheduling the agent to run",
-  };
-
-  // Return mapped phrase or generate human-friendly fallback
-  return toolActionPhrases[toolName] || toolName;
-}
-
-/**
- * Maps internal tool names to human-friendly completion phrases (past tense).
- * Used for tool response messages to indicate what action was completed.
- *
- * @param toolName - The internal tool name from the backend
- * @returns A human-friendly completion phrase in past tense
- */
-export function getToolCompletionPhrase(toolName: string): string {
-  const toolCompletionPhrases: Record<string, string> = {
-    find_agent: "Finished searching the marketplace",
-    get_agent_details: "Got agent details",
-    check_credentials: "Checked credentials",
-    setup_agent: "Agent setup complete",
-    run_agent: "Agent execution started",
-    get_required_setup_info: "Got setup requirements",
-  };
-
-  // Return mapped phrase or generate human-friendly fallback
-  return (
-    toolCompletionPhrases[toolName] ||
-    `Finished ${toolName.replace(/_/g, " ").replace("...", "")}`
-  );
-}

autogpt_platform/frontend/src/app/(platform)/chat/components/Chat/useChatSession.ts

@@ -1,271 +0,0 @@
-import {
-  getGetV2GetSessionQueryKey,
-  getGetV2GetSessionQueryOptions,
-  postV2CreateSession,
-  useGetV2GetSession,
-  usePatchV2SessionAssignUser,
-  usePostV2CreateSession,
-} from "@/app/api/__generated__/endpoints/chat/chat";
-import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
-import { okData } from "@/app/api/helpers";
-import { isValidUUID } from "@/lib/utils";
-import { Key, storage } from "@/services/storage/local-storage";
-import { useQueryClient } from "@tanstack/react-query";
-import { useCallback, useEffect, useMemo, useRef, useState } from "react";
-import { toast } from "sonner";
-
-interface UseChatSessionArgs {
-  urlSessionId?: string | null;
-  autoCreate?: boolean;
-}
-
-export function useChatSession({
-  urlSessionId,
-  autoCreate = false,
-}: UseChatSessionArgs = {}) {
-  const queryClient = useQueryClient();
-  const [sessionId, setSessionId] = useState<string | null>(null);
-  const [error, setError] = useState<Error | null>(null);
-  const justCreatedSessionIdRef = useRef<string | null>(null);
-
-  useEffect(() => {
-    if (urlSessionId) {
-      if (!isValidUUID(urlSessionId)) {
-        console.error("Invalid session ID format:", urlSessionId);
-        toast.error("Invalid session ID", {
-          description:
-            "The session ID in the URL is not valid. Starting a new session...",
-        });
-        setSessionId(null);
-        storage.clean(Key.CHAT_SESSION_ID);
-        return;
-      }
-      setSessionId(urlSessionId);
-      storage.set(Key.CHAT_SESSION_ID, urlSessionId);
-    } else {
-      const storedSessionId = storage.get(Key.CHAT_SESSION_ID);
-      if (storedSessionId) {
-        if (!isValidUUID(storedSessionId)) {
-          console.error("Invalid stored session ID:", storedSessionId);
-          storage.clean(Key.CHAT_SESSION_ID);
-          setSessionId(null);
-        } else {
-          setSessionId(storedSessionId);
-        }
-      } else if (autoCreate) {
-        setSessionId(null);
-      }
-    }
-  }, [urlSessionId, autoCreate]);
-
-  const {
-    mutateAsync: createSessionMutation,
-    isPending: isCreating,
-    error: createError,
-  } = usePostV2CreateSession();
-
-  const {
-    data: sessionData,
-    isLoading: isLoadingSession,
-    error: loadError,
-    refetch,
-  } = useGetV2GetSession(sessionId || "", {
-    query: {
-      enabled: !!sessionId,
-      select: okData,
-      staleTime: Infinity, // Never mark as stale
-      refetchOnMount: false, // Don't refetch on component mount
-      refetchOnWindowFocus: false, // Don't refetch when window regains focus
-      refetchOnReconnect: false, // Don't refetch when network reconnects
-      retry: 1,
-    },
-  });
-
-  const { mutateAsync: claimSessionMutation } = usePatchV2SessionAssignUser();
-
-  const session = useMemo(() => {
-    if (sessionData) return sessionData;
-
-    if (sessionId && justCreatedSessionIdRef.current === sessionId) {
-      return {
-        id: sessionId,
-        user_id: null,
-        messages: [],
-        created_at: new Date().toISOString(),
-        updated_at: new Date().toISOString(),
-      } as SessionDetailResponse;
-    }
-    return null;
-  }, [sessionData, sessionId]);
-
-  const messages = session?.messages || [];
-  const isLoading = isCreating || isLoadingSession;
-
-  useEffect(() => {
-    if (createError) {
-      setError(
-        createError instanceof Error
-          ? createError
-          : new Error("Failed to create session"),
-      );
-    } else if (loadError) {
-      setError(
-        loadError instanceof Error
-          ? loadError
-          : new Error("Failed to load session"),
-      );
-    } else {
-      setError(null);
-    }
-  }, [createError, loadError]);
-
-  const createSession = useCallback(
-    async function createSession() {
-      try {
-        setError(null);
-        const response = await postV2CreateSession({
-          body: JSON.stringify({}),
-        });
-        if (response.status !== 200) {
-          throw new Error("Failed to create session");
-        }
-        const newSessionId = response.data.id;
-        setSessionId(newSessionId);
-        storage.set(Key.CHAT_SESSION_ID, newSessionId);
-        justCreatedSessionIdRef.current = newSessionId;
-        setTimeout(() => {
-          if (justCreatedSessionIdRef.current === newSessionId) {
-            justCreatedSessionIdRef.current = null;
-          }
-        }, 10000);
-        return newSessionId;
-      } catch (err) {
-        const error =
-          err instanceof Error ? err : new Error("Failed to create session");
-        setError(error);
-        toast.error("Failed to create chat session", {
-          description: error.message,
-        });
-        throw error;
-      }
-    },
-    [createSessionMutation],
-  );
-
-  const loadSession = useCallback(
-    async function loadSession(id: string) {
-      try {
-        setError(null);
-        // Invalidate the query cache for this session to force a fresh fetch
-        await queryClient.invalidateQueries({
-          queryKey: getGetV2GetSessionQueryKey(id),
-        });
-        // Set sessionId after invalidation to ensure the hook refetches
-        setSessionId(id);
-        storage.set(Key.CHAT_SESSION_ID, id);
-        // Force fetch with fresh data (bypass cache)
-        const queryOptions = getGetV2GetSessionQueryOptions(id, {
-          query: {
-            staleTime: 0, // Force fresh fetch
-            retry: 1,
-          },
-        });
-        const result = await queryClient.fetchQuery(queryOptions);
-        if (!result || ("status" in result && result.status !== 200)) {
-          console.warn("Session not found on server, clearing local state");
-          storage.clean(Key.CHAT_SESSION_ID);
-          setSessionId(null);
-          throw new Error("Session not found");
-        }
-      } catch (err) {
-        const error =
-          err instanceof Error ? err : new Error("Failed to load session");
-        setError(error);
-        throw error;
-      }
-    },
-    [queryClient],
-  );
-
-  const refreshSession = useCallback(
-    async function refreshSession() {
-      if (!sessionId) {
-        console.log("[refreshSession] Skipping - no session ID");
-        return;
-      }
-      try {
-        setError(null);
-        await refetch();
-      } catch (err) {
-        const error =
-          err instanceof Error ? err : new Error("Failed to refresh session");
-        setError(error);
-        throw error;
-      }
-    },
-    [sessionId, refetch],
-  );
-
-  const claimSession = useCallback(
-    async function claimSession(id: string) {
-      try {
-        setError(null);
-        await claimSessionMutation({ sessionId: id });
-        if (justCreatedSessionIdRef.current === id) {
-          justCreatedSessionIdRef.current = null;
-        }
-        await queryClient.invalidateQueries({
-          queryKey: getGetV2GetSessionQueryKey(id),
-        });
-        await refetch();
-        toast.success("Session claimed successfully", {
-          description: "Your chat history has been saved to your account",
-        });
-      } catch (err: unknown) {
-        const error =
-          err instanceof Error ? err : new Error("Failed to claim session");
-        const is404 =
-          (typeof err === "object" &&
-            err !== null &&
-            "status" in err &&
-            err.status === 404) ||
-          (typeof err === "object" &&
-            err !== null &&
-            "response" in err &&
-            typeof err.response === "object" &&
-            err.response !== null &&
-            "status" in err.response &&
-            err.response.status === 404);
-        if (!is404) {
-          setError(error);
-          toast.error("Failed to claim session", {
-            description: error.message || "Unable to claim session",
-          });
-        }
-        throw error;
-      }
-    },
-    [claimSessionMutation, queryClient, refetch],
-  );
-
-  const clearSession = useCallback(function clearSession() {
-    setSessionId(null);
-    setError(null);
-    storage.clean(Key.CHAT_SESSION_ID);
-    justCreatedSessionIdRef.current = null;
-  }, []);
-
-  return {
-    session,
-    sessionId,
-    messages,
-    isLoading,
-    isCreating,
-    error,
-    createSession,
-    loadSession,
-    refreshSession,
-    claimSession,
-    clearSession,
-  };
-}

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

@@ -1,27 +0,0 @@
-"use client";
-
-import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
-import { useRouter } from "next/navigation";
-import { useEffect } from "react";
-import { Chat } from "./components/Chat/Chat";
-
-export default function ChatPage() {
-  const isChatEnabled = useGetFlag(Flag.CHAT);
-  const router = useRouter();
-
-  useEffect(() => {
-    if (isChatEnabled === false) {
-      router.push("/marketplace");
-    }
-  }, [isChatEnabled, router]);
-
-  if (isChatEnabled === null || isChatEnabled === false) {
-    return null;
-  }
-
-  return (
-    <div className="flex h-full flex-col">
-      <Chat className="flex-1" />
-    </div>
-  );
-}

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

@@ -0,0 +1,88 @@
+"use client";
+
+import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
+import { NAVBAR_HEIGHT_PX } from "@/lib/constants";
+import type { ReactNode } from "react";
+import { DesktopSidebar } from "./components/DesktopSidebar/DesktopSidebar";
+import { LoadingState } from "./components/LoadingState/LoadingState";
+import { MobileDrawer } from "./components/MobileDrawer/MobileDrawer";
+import { MobileHeader } from "./components/MobileHeader/MobileHeader";
+import { useCopilotShell } from "./useCopilotShell";
+
+interface Props {
+  children: ReactNode;
+}
+
+export function CopilotShell({ children }: Props) {
+  const {
+    isMobile,
+    isDrawerOpen,
+    isLoading,
+    isLoggedIn,
+    hasActiveSession,
+    sessions,
+    currentSessionId,
+    handleSelectSession,
+    handleOpenDrawer,
+    handleCloseDrawer,
+    handleDrawerOpenChange,
+    handleNewChat,
+    hasNextPage,
+    isFetchingNextPage,
+    fetchNextPage,
+    isReadyToShowContent,
+  } = useCopilotShell();
+
+  if (!isLoggedIn) {
+    return (
+      <div className="flex h-full items-center justify-center">
+        <LoadingSpinner size="large" />
+      </div>
+    );
+  }
+
+  return (
+    <div
+      className="flex overflow-hidden bg-[#EFEFF0]"
+      style={{ height: `calc(100vh - ${NAVBAR_HEIGHT_PX}px)` }}
+    >
+      {!isMobile && (
+        <DesktopSidebar
+          sessions={sessions}
+          currentSessionId={currentSessionId}
+          isLoading={isLoading}
+          hasNextPage={hasNextPage}
+          isFetchingNextPage={isFetchingNextPage}
+          onSelectSession={handleSelectSession}
+          onFetchNextPage={fetchNextPage}
+          onNewChat={handleNewChat}
+          hasActiveSession={Boolean(hasActiveSession)}
+        />
+      )}
+
+      <div className="relative flex min-h-0 flex-1 flex-col">
+        {isMobile && <MobileHeader onOpenDrawer={handleOpenDrawer} />}
+        <div className="flex min-h-0 flex-1 flex-col">
+          {isReadyToShowContent ? children : <LoadingState />}
+        </div>
+      </div>
+
+      {isMobile && (
+        <MobileDrawer
+          isOpen={isDrawerOpen}
+          sessions={sessions}
+          currentSessionId={currentSessionId}
+          isLoading={isLoading}
+          hasNextPage={hasNextPage}
+          isFetchingNextPage={isFetchingNextPage}
+          onSelectSession={handleSelectSession}
+          onFetchNextPage={fetchNextPage}
+          onNewChat={handleNewChat}
+          onClose={handleCloseDrawer}
+          onOpenChange={handleDrawerOpenChange}
+          hasActiveSession={Boolean(hasActiveSession)}
+        />
+      )}
+    </div>
+  );
+}

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

@@ -0,0 +1,70 @@
+import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
+import { Button } from "@/components/atoms/Button/Button";
+import { Text } from "@/components/atoms/Text/Text";
+import { scrollbarStyles } from "@/components/styles/scrollbars";
+import { cn } from "@/lib/utils";
+import { Plus } from "@phosphor-icons/react";
+import { SessionsList } from "../SessionsList/SessionsList";
+
+interface Props {
+  sessions: SessionSummaryResponse[];
+  currentSessionId: string | null;
+  isLoading: boolean;
+  hasNextPage: boolean;
+  isFetchingNextPage: boolean;
+  onSelectSession: (sessionId: string) => void;
+  onFetchNextPage: () => void;
+  onNewChat: () => void;
+  hasActiveSession: boolean;
+}
+
+export function DesktopSidebar({
+  sessions,
+  currentSessionId,
+  isLoading,
+  hasNextPage,
+  isFetchingNextPage,
+  onSelectSession,
+  onFetchNextPage,
+  onNewChat,
+  hasActiveSession,
+}: Props) {
+  return (
+    <aside className="flex h-full w-80 flex-col border-r border-zinc-100 bg-zinc-50">
+      <div className="shrink-0 px-6 py-4">
+        <Text variant="h3" size="body-medium">
+          Your chats
+        </Text>
+      </div>
+      <div
+        className={cn(
+          "flex min-h-0 flex-1 flex-col overflow-y-auto px-3 py-3",
+          scrollbarStyles,
+        )}
+      >
+        <SessionsList
+          sessions={sessions}
+          currentSessionId={currentSessionId}
+          isLoading={isLoading}
+          hasNextPage={hasNextPage}
+          isFetchingNextPage={isFetchingNextPage}
+          onSelectSession={onSelectSession}
+          onFetchNextPage={onFetchNextPage}
+        />
+      </div>
+      {hasActiveSession && (
+        <div className="shrink-0 bg-zinc-50 p-3 shadow-[0_-4px_6px_-1px_rgba(0,0,0,0.05)]">
+          <Button
+            variant="primary"
+            size="small"
+            onClick={onNewChat}
+            className="w-full"
+            leftIcon={<Plus width="1rem" height="1rem" />}
+          >
+            New Chat
+          </Button>
+        </div>
+      )}
+    </aside>
+  );
+}

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

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

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

@@ -0,0 +1,91 @@
+import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
+import { Button } from "@/components/atoms/Button/Button";
+import { scrollbarStyles } from "@/components/styles/scrollbars";
+import { cn } from "@/lib/utils";
+import { PlusIcon, X } from "@phosphor-icons/react";
+import { Drawer } from "vaul";
+import { SessionsList } from "../SessionsList/SessionsList";
+
+interface Props {
+  isOpen: boolean;
+  sessions: SessionSummaryResponse[];
+  currentSessionId: string | null;
+  isLoading: boolean;
+  hasNextPage: boolean;
+  isFetchingNextPage: boolean;
+  onSelectSession: (sessionId: string) => void;
+  onFetchNextPage: () => void;
+  onNewChat: () => void;
+  onClose: () => void;
+  onOpenChange: (open: boolean) => void;
+  hasActiveSession: boolean;
+}
+
+export function MobileDrawer({
+  isOpen,
+  sessions,
+  currentSessionId,
+  isLoading,
+  hasNextPage,
+  isFetchingNextPage,
+  onSelectSession,
+  onFetchNextPage,
+  onNewChat,
+  onClose,
+  onOpenChange,
+  hasActiveSession,
+}: Props) {
+  return (
+    <Drawer.Root open={isOpen} onOpenChange={onOpenChange} direction="left">
+      <Drawer.Portal>
+        <Drawer.Overlay className="fixed inset-0 z-[60] bg-black/10 backdrop-blur-sm" />
+        <Drawer.Content className="fixed left-0 top-0 z-[70] flex h-full w-80 flex-col border-r border-zinc-200 bg-zinc-50">
+          <div className="shrink-0 border-b border-zinc-200 p-4">
+            <div className="flex items-center justify-between">
+              <Drawer.Title className="text-lg font-semibold text-zinc-800">
+                Your chats
+              </Drawer.Title>
+              <Button
+                variant="icon"
+                size="icon"
+                aria-label="Close sessions"
+                onClick={onClose}
+              >
+                <X width="1.25rem" height="1.25rem" />
+              </Button>
+            </div>
+          </div>
+          <div
+            className={cn(
+              "flex min-h-0 flex-1 flex-col overflow-y-auto px-3 py-3",
+              scrollbarStyles,
+            )}
+          >
+            <SessionsList
+              sessions={sessions}
+              currentSessionId={currentSessionId}
+              isLoading={isLoading}
+              hasNextPage={hasNextPage}
+              isFetchingNextPage={isFetchingNextPage}
+              onSelectSession={onSelectSession}
+              onFetchNextPage={onFetchNextPage}
+            />
+          </div>
+          {hasActiveSession && (
+            <div className="shrink-0 bg-white p-3 shadow-[0_-4px_6px_-1px_rgba(0,0,0,0.05)]">
+              <Button
+                variant="primary"
+                size="small"
+                onClick={onNewChat}
+                className="w-full"
+                leftIcon={<PlusIcon width="1rem" height="1rem" />}
+              >
+                New Chat
+              </Button>
+            </div>
+          )}
+        </Drawer.Content>
+      </Drawer.Portal>
+    </Drawer.Root>
+  );
+}

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

@@ -0,0 +1,24 @@
+import { useState } from "react";
+
+export function useMobileDrawer() {
+  const [isDrawerOpen, setIsDrawerOpen] = useState(false);
+
+  function handleOpenDrawer() {
+    setIsDrawerOpen(true);
+  }
+
+  function handleCloseDrawer() {
+    setIsDrawerOpen(false);
+  }
+
+  function handleDrawerOpenChange(open: boolean) {
+    setIsDrawerOpen(open);
+  }
+
+  return {
+    isDrawerOpen,
+    handleOpenDrawer,
+    handleCloseDrawer,
+    handleDrawerOpenChange,
+  };
+}

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

@@ -0,0 +1,22 @@
+import { Button } from "@/components/atoms/Button/Button";
+import { NAVBAR_HEIGHT_PX } from "@/lib/constants";
+import { ListIcon } from "@phosphor-icons/react";
+
+interface Props {
+  onOpenDrawer: () => void;
+}
+
+export function MobileHeader({ onOpenDrawer }: Props) {
+  return (
+    <Button
+      variant="icon"
+      size="icon"
+      aria-label="Open sessions"
+      onClick={onOpenDrawer}
+      className="fixed z-50 bg-white shadow-md"
+      style={{ left: "1rem", top: `${NAVBAR_HEIGHT_PX + 20}px` }}
+    >
+      <ListIcon width="1.25rem" height="1.25rem" />
+    </Button>
+  );
+}

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

@@ -0,0 +1,80 @@
+import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
+import { Skeleton } from "@/components/__legacy__/ui/skeleton";
+import { Text } from "@/components/atoms/Text/Text";
+import { InfiniteList } from "@/components/molecules/InfiniteList/InfiniteList";
+import { cn } from "@/lib/utils";
+import { getSessionTitle } from "../../helpers";
+
+interface Props {
+  sessions: SessionSummaryResponse[];
+  currentSessionId: string | null;
+  isLoading: boolean;
+  hasNextPage: boolean;
+  isFetchingNextPage: boolean;
+  onSelectSession: (sessionId: string) => void;
+  onFetchNextPage: () => void;
+}
+
+export function SessionsList({
+  sessions,
+  currentSessionId,
+  isLoading,
+  hasNextPage,
+  isFetchingNextPage,
+  onSelectSession,
+  onFetchNextPage,
+}: Props) {
+  if (isLoading) {
+    return (
+      <div className="space-y-1">
+        {Array.from({ length: 5 }).map((_, i) => (
+          <div key={i} className="rounded-lg px-3 py-2.5">
+            <Skeleton className="h-5 w-full" />
+          </div>
+        ))}
+      </div>
+    );
+  }
+
+  if (sessions.length === 0) {
+    return (
+      <div className="flex h-full items-center justify-center">
+        <Text variant="body" className="text-zinc-500">
+          You don&apos;t have previous chats
+        </Text>
+      </div>
+    );
+  }
+
+  return (
+    <InfiniteList
+      items={sessions}
+      hasMore={hasNextPage}
+      isFetchingMore={isFetchingNextPage}
+      onEndReached={onFetchNextPage}
+      className="space-y-1"
+      renderItem={(session) => {
+        const isActive = session.id === currentSessionId;
+        return (
+          <button
+            onClick={() => onSelectSession(session.id)}
+            className={cn(
+              "w-full rounded-lg px-3 py-2.5 text-left transition-colors",
+              isActive ? "bg-zinc-100" : "hover:bg-zinc-50",
+            )}
+          >
+            <Text
+              variant="body"
+              className={cn(
+                "font-normal",
+                isActive ? "text-zinc-600" : "text-zinc-800",
+              )}
+            >
+              {getSessionTitle(session)}
+            </Text>
+          </button>
+        );
+      }}
+    />
+  );
+}

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

@@ -0,0 +1,92 @@
+import { useGetV2ListSessions } from "@/app/api/__generated__/endpoints/chat/chat";
+import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
+import { okData } from "@/app/api/helpers";
+import { useEffect, useMemo, useState } from "react";
+
+const PAGE_SIZE = 50;
+
+export interface UseSessionsPaginationArgs {
+  enabled: boolean;
+}
+
+export function useSessionsPagination({ enabled }: UseSessionsPaginationArgs) {
+  const [offset, setOffset] = useState(0);
+  const [accumulatedSessions, setAccumulatedSessions] = useState<
+    SessionSummaryResponse[]
+  >([]);
+  const [totalCount, setTotalCount] = useState<number | null>(null);
+
+  const { data, isLoading, isFetching, isError } = useGetV2ListSessions(
+    { limit: PAGE_SIZE, offset },
+    {
+      query: {
+        enabled: enabled && offset >= 0,
+      },
+    },
+  );
+
+  useEffect(() => {
+    const responseData = okData(data);
+    if (responseData) {
+      const newSessions = responseData.sessions;
+      const total = responseData.total;
+      setTotalCount(total);
+
+      if (offset === 0) {
+        setAccumulatedSessions(newSessions);
+      } else {
+        setAccumulatedSessions((prev) => [...prev, ...newSessions]);
+      }
+    } else if (!enabled) {
+      setAccumulatedSessions([]);
+      setTotalCount(null);
+    }
+  }, [data, offset, enabled]);
+
+  const hasNextPage = useMemo(() => {
+    if (totalCount === null) return false;
+    return accumulatedSessions.length < totalCount;
+  }, [accumulatedSessions.length, totalCount]);
+
+  const areAllSessionsLoaded = useMemo(() => {
+    if (totalCount === null) return false;
+    return (
+      accumulatedSessions.length >= totalCount && !isFetching && !isLoading
+    );
+  }, [accumulatedSessions.length, totalCount, isFetching, isLoading]);
+
+  useEffect(() => {
+    if (
+      hasNextPage &&
+      !isFetching &&
+      !isLoading &&
+      !isError &&
+      totalCount !== null
+    ) {
+      setOffset((prev) => prev + PAGE_SIZE);
+    }
+  }, [hasNextPage, isFetching, isLoading, isError, totalCount]);
+
+  function fetchNextPage() {
+    if (hasNextPage && !isFetching) {
+      setOffset((prev) => prev + PAGE_SIZE);
+    }
+  }
+
+  function reset() {
+    setOffset(0);
+    setAccumulatedSessions([]);
+    setTotalCount(null);
+  }
+
+  return {
+    sessions: accumulatedSessions,
+    isLoading,
+    isFetching,
+    hasNextPage,
+    areAllSessionsLoaded,
+    totalCount,
+    fetchNextPage,
+    reset,
+  };
+}

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

@@ -0,0 +1,165 @@
+import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
+import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
+import { format, formatDistanceToNow, isToday } from "date-fns";
+
+export function convertSessionDetailToSummary(
+  session: SessionDetailResponse,
+): SessionSummaryResponse {
+  return {
+    id: session.id,
+    created_at: session.created_at,
+    updated_at: session.updated_at,
+    title: undefined,
+  };
+}
+
+export function filterVisibleSessions(
+  sessions: SessionSummaryResponse[],
+): SessionSummaryResponse[] {
+  return sessions.filter(
+    (session) => session.updated_at !== session.created_at,
+  );
+}
+
+export function getSessionTitle(session: SessionSummaryResponse): string {
+  if (session.title) return session.title;
+  const isNewSession = session.updated_at === session.created_at;
+  if (isNewSession) {
+    const createdDate = new Date(session.created_at);
+    if (isToday(createdDate)) {
+      return "Today";
+    }
+    return format(createdDate, "MMM d, yyyy");
+  }
+  return "Untitled Chat";
+}
+
+export function getSessionUpdatedLabel(
+  session: SessionSummaryResponse,
+): string {
+  if (!session.updated_at) return "";
+  return formatDistanceToNow(new Date(session.updated_at), { addSuffix: true });
+}
+
+export function mergeCurrentSessionIntoList(
+  accumulatedSessions: SessionSummaryResponse[],
+  currentSessionId: string | null,
+  currentSessionData: SessionDetailResponse | null | undefined,
+): SessionSummaryResponse[] {
+  const filteredSessions: SessionSummaryResponse[] = [];
+
+  if (accumulatedSessions.length > 0) {
+    const visibleSessions = filterVisibleSessions(accumulatedSessions);
+
+    if (currentSessionId) {
+      const currentInAll = accumulatedSessions.find(
+        (s) => s.id === currentSessionId,
+      );
+      if (currentInAll) {
+        const isInVisible = visibleSessions.some(
+          (s) => s.id === currentSessionId,
+        );
+        if (!isInVisible) {
+          filteredSessions.push(currentInAll);
+        }
+      }
+    }
+
+    filteredSessions.push(...visibleSessions);
+  }
+
+  if (currentSessionId && currentSessionData) {
+    const isCurrentInList = filteredSessions.some(
+      (s) => s.id === currentSessionId,
+    );
+    if (!isCurrentInList) {
+      const summarySession = convertSessionDetailToSummary(currentSessionData);
+      filteredSessions.unshift(summarySession);
+    }
+  }
+
+  return filteredSessions;
+}
+
+export function getCurrentSessionId(
+  searchParams: URLSearchParams,
+): string | null {
+  return searchParams.get("sessionId");
+}
+
+export function shouldAutoSelectSession(
+  areAllSessionsLoaded: boolean,
+  hasAutoSelectedSession: boolean,
+  paramSessionId: string | null,
+  visibleSessions: SessionSummaryResponse[],
+  accumulatedSessions: SessionSummaryResponse[],
+  isLoading: boolean,
+  totalCount: number | null,
+): {
+  shouldSelect: boolean;
+  sessionIdToSelect: string | null;
+  shouldCreate: boolean;
+} {
+  if (!areAllSessionsLoaded || hasAutoSelectedSession) {
+    return {
+      shouldSelect: false,
+      sessionIdToSelect: null,
+      shouldCreate: false,
+    };
+  }
+
+  if (paramSessionId) {
+    return {
+      shouldSelect: false,
+      sessionIdToSelect: null,
+      shouldCreate: false,
+    };
+  }
+
+  if (visibleSessions.length > 0) {
+    return {
+      shouldSelect: true,
+      sessionIdToSelect: visibleSessions[0].id,
+      shouldCreate: false,
+    };
+  }
+
+  if (accumulatedSessions.length === 0 && !isLoading && totalCount === 0) {
+    return { shouldSelect: false, sessionIdToSelect: null, shouldCreate: true };
+  }
+
+  if (totalCount === 0) {
+    return {
+      shouldSelect: false,
+      sessionIdToSelect: null,
+      shouldCreate: false,
+    };
+  }
+
+  return { shouldSelect: false, sessionIdToSelect: null, shouldCreate: false };
+}
+
+export function checkReadyToShowContent(
+  areAllSessionsLoaded: boolean,
+  paramSessionId: string | null,
+  accumulatedSessions: SessionSummaryResponse[],
+  isCurrentSessionLoading: boolean,
+  currentSessionData: SessionDetailResponse | null | undefined,
+  hasAutoSelectedSession: boolean,
+): boolean {
+  if (!areAllSessionsLoaded) return false;
+
+  if (paramSessionId) {
+    const sessionFound = accumulatedSessions.some(
+      (s) => s.id === paramSessionId,
+    );
+    return (
+      sessionFound ||
+      (!isCurrentSessionLoading &&
+        currentSessionData !== undefined &&
+        currentSessionData !== null)
+    );
+  }
+
+  return hasAutoSelectedSession;
+}

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

@@ -0,0 +1,170 @@
+"use client";
+
+import {
+  getGetV2ListSessionsQueryKey,
+  useGetV2GetSession,
+} from "@/app/api/__generated__/endpoints/chat/chat";
+import { okData } from "@/app/api/helpers";
+import { useBreakpoint } from "@/lib/hooks/useBreakpoint";
+import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
+import { useQueryClient } from "@tanstack/react-query";
+import { usePathname, useRouter, useSearchParams } from "next/navigation";
+import { useEffect, useRef, useState } from "react";
+import { useMobileDrawer } from "./components/MobileDrawer/useMobileDrawer";
+import { useSessionsPagination } from "./components/SessionsList/useSessionsPagination";
+import {
+  checkReadyToShowContent,
+  filterVisibleSessions,
+  getCurrentSessionId,
+  mergeCurrentSessionIntoList,
+} from "./helpers";
+
+export function useCopilotShell() {
+  const router = useRouter();
+  const pathname = usePathname();
+  const searchParams = useSearchParams();
+  const queryClient = useQueryClient();
+  const breakpoint = useBreakpoint();
+  const { isLoggedIn } = useSupabase();
+  const isMobile =
+    breakpoint === "base" || breakpoint === "sm" || breakpoint === "md";
+
+  const isOnHomepage = pathname === "/copilot";
+  const paramSessionId = searchParams.get("sessionId");
+
+  const {
+    isDrawerOpen,
+    handleOpenDrawer,
+    handleCloseDrawer,
+    handleDrawerOpenChange,
+  } = useMobileDrawer();
+
+  const paginationEnabled = !isMobile || isDrawerOpen || !!paramSessionId;
+
+  const {
+    sessions: accumulatedSessions,
+    isLoading: isSessionsLoading,
+    isFetching: isSessionsFetching,
+    hasNextPage,
+    areAllSessionsLoaded,
+    fetchNextPage,
+    reset: resetPagination,
+  } = useSessionsPagination({
+    enabled: paginationEnabled,
+  });
+
+  const currentSessionId = getCurrentSessionId(searchParams);
+
+  const { data: currentSessionData, isLoading: isCurrentSessionLoading } =
+    useGetV2GetSession(currentSessionId || "", {
+      query: {
+        enabled: !!currentSessionId,
+        select: okData,
+      },
+    });
+
+  const [hasAutoSelectedSession, setHasAutoSelectedSession] = useState(false);
+  const hasAutoSelectedRef = useRef(false);
+
+  // Mark as auto-selected when sessionId is in URL
+  useEffect(() => {
+    if (paramSessionId && !hasAutoSelectedRef.current) {
+      hasAutoSelectedRef.current = true;
+      setHasAutoSelectedSession(true);
+    }
+  }, [paramSessionId]);
+
+  // On homepage without sessionId, mark as ready immediately
+  useEffect(() => {
+    if (isOnHomepage && !paramSessionId && !hasAutoSelectedRef.current) {
+      hasAutoSelectedRef.current = true;
+      setHasAutoSelectedSession(true);
+    }
+  }, [isOnHomepage, paramSessionId]);
+
+  // Invalidate sessions list when navigating to homepage (to show newly created sessions)
+  useEffect(() => {
+    if (isOnHomepage && !paramSessionId) {
+      queryClient.invalidateQueries({
+        queryKey: getGetV2ListSessionsQueryKey(),
+      });
+    }
+  }, [isOnHomepage, paramSessionId, queryClient]);
+
+  // Reset pagination when query becomes disabled
+  const prevPaginationEnabledRef = useRef(paginationEnabled);
+  useEffect(() => {
+    if (prevPaginationEnabledRef.current && !paginationEnabled) {
+      resetPagination();
+      resetAutoSelect();
+    }
+    prevPaginationEnabledRef.current = paginationEnabled;
+  }, [paginationEnabled, resetPagination]);
+
+  const sessions = mergeCurrentSessionIntoList(
+    accumulatedSessions,
+    currentSessionId,
+    currentSessionData,
+  );
+
+  const visibleSessions = filterVisibleSessions(sessions);
+
+  const sidebarSelectedSessionId =
+    isOnHomepage && !paramSessionId ? null : currentSessionId;
+
+  const isReadyToShowContent = isOnHomepage
+    ? true
+    : checkReadyToShowContent(
+        areAllSessionsLoaded,
+        paramSessionId,
+        accumulatedSessions,
+        isCurrentSessionLoading,
+        currentSessionData,
+        hasAutoSelectedSession,
+      );
+
+  function handleSelectSession(sessionId: string) {
+    // Navigate using replaceState to avoid full page reload
+    window.history.replaceState(null, "", `/copilot?sessionId=${sessionId}`);
+    // Force a re-render by updating the URL through router
+    router.replace(`/copilot?sessionId=${sessionId}`);
+    if (isMobile) handleCloseDrawer();
+  }
+
+  function handleNewChat() {
+    resetAutoSelect();
+    resetPagination();
+    // Invalidate and refetch sessions list to ensure newly created sessions appear
+    queryClient.invalidateQueries({
+      queryKey: getGetV2ListSessionsQueryKey(),
+    });
+    window.history.replaceState(null, "", "/copilot");
+    router.replace("/copilot");
+    if (isMobile) handleCloseDrawer();
+  }
+
+  function resetAutoSelect() {
+    hasAutoSelectedRef.current = false;
+    setHasAutoSelectedSession(false);
+  }
+
+  return {
+    isMobile,
+    isDrawerOpen,
+    isLoggedIn,
+    hasActiveSession:
+      Boolean(currentSessionId) && (!isOnHomepage || Boolean(paramSessionId)),
+    isLoading: isSessionsLoading || !areAllSessionsLoaded,
+    sessions: visibleSessions,
+    currentSessionId: sidebarSelectedSessionId,
+    handleSelectSession,
+    handleOpenDrawer,
+    handleCloseDrawer,
+    handleDrawerOpenChange,
+    handleNewChat,
+    hasNextPage,
+    isFetchingNextPage: isSessionsFetching,
+    fetchNextPage,
+    isReadyToShowContent,
+  };
+}

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

@@ -0,0 +1,33 @@
+import type { User } from "@supabase/supabase-js";
+
+export function getGreetingName(user?: User | null): string {
+  if (!user) return "there";
+  const metadata = user.user_metadata as Record<string, unknown> | undefined;
+  const fullName = metadata?.full_name;
+  const name = metadata?.name;
+  if (typeof fullName === "string" && fullName.trim()) {
+    return fullName.split(" ")[0];
+  }
+  if (typeof name === "string" && name.trim()) {
+    return name.split(" ")[0];
+  }
+  if (user.email) {
+    return user.email.split("@")[0];
+  }
+  return "there";
+}
+
+export function buildCopilotChatUrl(prompt: string): string {
+  const trimmed = prompt.trim();
+  if (!trimmed) return "/copilot/chat";
+  const encoded = encodeURIComponent(trimmed);
+  return `/copilot/chat?prompt=${encoded}`;
+}
+
+export function getQuickActions(): string[] {
+  return [
+    "Show me what I can automate",
+    "Design a custom workflow",
+    "Help me with content creation",
+  ];
+}

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

@@ -0,0 +1,6 @@
+import type { ReactNode } from "react";
+import { CopilotShell } from "./components/CopilotShell/CopilotShell";
+
+export default function CopilotLayout({ children }: { children: ReactNode }) {
+  return <CopilotShell>{children}</CopilotShell>;
+}

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

@@ -0,0 +1,228 @@
+"use client";
+
+import { postV2CreateSession } from "@/app/api/__generated__/endpoints/chat/chat";
+import { Skeleton } from "@/components/__legacy__/ui/skeleton";
+import { Button } from "@/components/atoms/Button/Button";
+import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
+import { Text } from "@/components/atoms/Text/Text";
+import { Chat } from "@/components/contextual/Chat/Chat";
+import { ChatInput } from "@/components/contextual/Chat/components/ChatInput/ChatInput";
+import { getHomepageRoute } from "@/lib/constants";
+import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
+import {
+  Flag,
+  type FlagValues,
+  useGetFlag,
+} from "@/services/feature-flags/use-get-flag";
+import { useFlags } from "launchdarkly-react-client-sdk";
+import { useRouter, useSearchParams } from "next/navigation";
+import { useEffect, useMemo, useRef, useState } from "react";
+import { getGreetingName, getQuickActions } from "./helpers";
+
+type PageState =
+  | { type: "welcome" }
+  | { type: "creating"; prompt: string }
+  | { type: "chat"; sessionId: string; initialPrompt?: string };
+
+export default function CopilotPage() {
+  const router = useRouter();
+  const searchParams = useSearchParams();
+  const { user, isLoggedIn, isUserLoading } = useSupabase();
+
+  const isChatEnabled = useGetFlag(Flag.CHAT);
+  const flags = useFlags<FlagValues>();
+  const homepageRoute = getHomepageRoute(isChatEnabled);
+  const envEnabled = process.env.NEXT_PUBLIC_LAUNCHDARKLY_ENABLED === "true";
+  const clientId = process.env.NEXT_PUBLIC_LAUNCHDARKLY_CLIENT_ID;
+  const isLaunchDarklyConfigured = envEnabled && Boolean(clientId);
+  const isFlagReady =
+    !isLaunchDarklyConfigured || flags[Flag.CHAT] !== undefined;
+
+  const [pageState, setPageState] = useState<PageState>({ type: "welcome" });
+  const initialPromptRef = useRef<Map<string, string>>(new Map());
+
+  const urlSessionId = searchParams.get("sessionId");
+
+  // Sync with URL sessionId (preserve initialPrompt from ref)
+  useEffect(
+    function syncSessionFromUrl() {
+      if (urlSessionId) {
+        // If we're already in chat state with this sessionId, don't overwrite
+        if (pageState.type === "chat" && pageState.sessionId === urlSessionId) {
+          return;
+        }
+        // Get initialPrompt from ref or current state
+        const storedInitialPrompt = initialPromptRef.current.get(urlSessionId);
+        const currentInitialPrompt =
+          storedInitialPrompt ||
+          (pageState.type === "creating"
+            ? pageState.prompt
+            : pageState.type === "chat"
+              ? pageState.initialPrompt
+              : undefined);
+        if (currentInitialPrompt) {
+          initialPromptRef.current.set(urlSessionId, currentInitialPrompt);
+        }
+        setPageState({
+          type: "chat",
+          sessionId: urlSessionId,
+          initialPrompt: currentInitialPrompt,
+        });
+      } else if (pageState.type === "chat") {
+        setPageState({ type: "welcome" });
+      }
+    },
+    [urlSessionId],
+  );
+
+  useEffect(
+    function ensureAccess() {
+      if (!isFlagReady) return;
+      if (isChatEnabled === false) {
+        router.replace(homepageRoute);
+      }
+    },
+    [homepageRoute, isChatEnabled, isFlagReady, router],
+  );
+
+  const greetingName = useMemo(
+    function getName() {
+      return getGreetingName(user);
+    },
+    [user],
+  );
+
+  const quickActions = useMemo(function getActions() {
+    return getQuickActions();
+  }, []);
+
+  async function startChatWithPrompt(prompt: string) {
+    if (!prompt?.trim()) return;
+    if (pageState.type === "creating") return;
+
+    const trimmedPrompt = prompt.trim();
+    setPageState({ type: "creating", prompt: trimmedPrompt });
+
+    try {
+      // Create session
+      const sessionResponse = await postV2CreateSession({
+        body: JSON.stringify({}),
+      });
+
+      if (sessionResponse.status !== 200 || !sessionResponse.data?.id) {
+        throw new Error("Failed to create session");
+      }
+
+      const sessionId = sessionResponse.data.id;
+
+      // Store initialPrompt in ref so it persists across re-renders
+      initialPromptRef.current.set(sessionId, trimmedPrompt);
+
+      // Update URL and show Chat with initial prompt
+      // Chat will handle sending the message and streaming
+      window.history.replaceState(null, "", `/copilot?sessionId=${sessionId}`);
+      setPageState({ type: "chat", sessionId, initialPrompt: trimmedPrompt });
+    } catch (error) {
+      console.error("[CopilotPage] Failed to start chat:", error);
+      setPageState({ type: "welcome" });
+    }
+  }
+
+  function handleQuickAction(action: string) {
+    startChatWithPrompt(action);
+  }
+
+  function handleSessionNotFound() {
+    router.replace("/copilot");
+  }
+
+  if (!isFlagReady || isChatEnabled === false || !isLoggedIn) {
+    return null;
+  }
+
+  // Show Chat when we have an active session
+  if (pageState.type === "chat") {
+    return (
+      <div className="flex h-full flex-col">
+        <Chat
+          key={pageState.sessionId ?? "welcome"}
+          className="flex-1"
+          urlSessionId={pageState.sessionId}
+          initialPrompt={pageState.initialPrompt}
+          onSessionNotFound={handleSessionNotFound}
+        />
+      </div>
+    );
+  }
+
+  // Show loading state while creating session and sending first message
+  if (pageState.type === "creating") {
+    return (
+      <div className="flex h-full flex-1 flex-col items-center justify-center bg-[#f8f8f9] px-6 py-10">
+        <LoadingSpinner size="large" />
+        <Text variant="body" className="mt-4 text-zinc-500">
+          Starting your chat...
+        </Text>
+      </div>
+    );
+  }
+
+  // Show Welcome screen
+  const isLoading = isUserLoading;
+
+  return (
+    <div className="flex h-full flex-1 items-center justify-center overflow-y-auto bg-[#f8f8f9] px-6 py-10">
+      <div className="w-full text-center">
+        {isLoading ? (
+          <div className="mx-auto max-w-2xl">
+            <Skeleton className="mx-auto mb-3 h-8 w-64" />
+            <Skeleton className="mx-auto mb-8 h-6 w-80" />
+            <div className="mb-8">
+              <Skeleton className="mx-auto h-14 w-full rounded-lg" />
+            </div>
+            <div className="flex flex-wrap items-center justify-center gap-3">
+              {Array.from({ length: 4 }).map((_, i) => (
+                <Skeleton key={i} className="h-9 w-48 rounded-md" />
+              ))}
+            </div>
+          </div>
+        ) : (
+          <>
+            <div className="mx-auto max-w-2xl">
+              <Text
+                variant="h3"
+                className="mb-3 !text-[1.375rem] text-zinc-700"
+              >
+                Hey, <span className="text-violet-600">{greetingName}</span>
+              </Text>
+              <Text variant="h3" className="mb-8 !font-normal">
+                What do you want to automate?
+              </Text>
+
+              <div className="mb-6">
+                <ChatInput
+                  onSend={startChatWithPrompt}
+                  placeholder='You can search or just ask - e.g. "create a blog post outline"'
+                />
+              </div>
+            </div>
+            <div className="flex flex-nowrap items-center justify-center gap-3 overflow-x-auto [-ms-overflow-style:none] [scrollbar-width:none] [&::-webkit-scrollbar]:hidden">
+              {quickActions.map((action) => (
+                <Button
+                  key={action}
+                  type="button"
+                  variant="outline"
+                  size="small"
+                  onClick={() => handleQuickAction(action)}
+                  className="h-auto shrink-0 border-zinc-600 !px-4 !py-2 text-[1rem] text-zinc-600"
+                >
+                  {action}
+                </Button>
+              ))}
+            </div>
+          </>
+        )}
+      </div>
+    </div>
+  );
+}

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

@@ -1,6 +1,8 @@
 "use client";
 
 import { ErrorCard } from "@/components/molecules/ErrorCard/ErrorCard";
+import { getHomepageRoute } from "@/lib/constants";
+import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
 import { useSearchParams } from "next/navigation";
 import { Suspense } from "react";
 import { getErrorDetails } from "./helpers";
@@ -9,6 +11,8 @@ function ErrorPageContent() {
   const searchParams = useSearchParams();
   const errorMessage = searchParams.get("message");
   const errorDetails = getErrorDetails(errorMessage);
+  const isChatEnabled = useGetFlag(Flag.CHAT);
+  const homepageRoute = getHomepageRoute(isChatEnabled);
 
   function handleRetry() {
     // Auth-related errors should redirect to login
@@ -25,8 +29,8 @@ function ErrorPageContent() {
         window.location.reload();
       }, 2000);
     } else {
-      // For server/network errors, go to marketplace
+      // For server/network errors, go to home
-      window.location.href = "/marketplace";
+      window.location.href = homepageRoute;
     }
   }
 

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

@@ -180,7 +180,7 @@ export function RunAgentModal({
 
               {/* Content */}
               {hasAnySetupFields ? (
-                <div className="mt-10 pb-32">
+                <div className="mt-4 pb-10">
                   <RunAgentModalContextProvider
                     value={{
                       agent,

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

@@ -29,7 +29,7 @@ export function ModalHeader({ agent }: ModalHeaderProps) {
           <ShowMoreText
             previewLimit={400}
             variant="small"
-            className="mt-4 !text-zinc-700"
+            className="mb-2 mt-4 !text-zinc-700"
           >
             {agent.description}
           </ShowMoreText>
@@ -40,6 +40,8 @@ export function ModalHeader({ agent }: ModalHeaderProps) {
             <Text variant="lead-semibold" className="text-blue-600">
               Tip
             </Text>
+            <div className="h-px w-full bg-blue-100" />
+
             <Text variant="body">
               For best results, run this agent{" "}
               {humanizeCronExpression(
@@ -50,7 +52,7 @@ export function ModalHeader({ agent }: ModalHeaderProps) {
         ) : null}
 
         {agent.instructions ? (
-          <div className="flex flex-col gap-4 rounded-medium border border-purple-100 bg-[#F1EBFE/5] p-4">
+          <div className="mt-4 flex flex-col gap-4 rounded-medium border border-purple-100 bg-[#f1ebfe80] p-4">
             <Text variant="lead-semibold" className="text-purple-600">
               Instructions
             </Text>

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-draft-view.tsx

@@ -1,8 +1,15 @@
 "use client";
-import React, { useCallback, useEffect, useMemo, useState } from "react";
+import React, {
+  useCallback,
+  useContext,
+  useEffect,
+  useMemo,
+  useState,
+} from "react";
 
 import {
   CredentialsMetaInput,
+  CredentialsType,
   GraphExecutionID,
   GraphMeta,
   LibraryAgentPreset,
@@ -29,7 +36,11 @@ import {
 } from "@/components/__legacy__/ui/icons";
 import { Input } from "@/components/__legacy__/ui/input";
 import { Button } from "@/components/atoms/Button/Button";
-import { CredentialsInput } from "@/components/contextual/CredentialsInput/CredentialsInput";
+import { CredentialsGroupedView } from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/CredentialsGroupedView";
+import {
+  findSavedCredentialByProviderAndType,
+  findSavedUserCredentialByProviderAndType,
+} from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/helpers";
 import { InformationTooltip } from "@/components/molecules/InformationTooltip/InformationTooltip";
 import {
   useToast,
@@ -37,6 +48,7 @@ import {
 } from "@/components/molecules/Toast/use-toast";
 import { humanizeCronExpression } from "@/lib/cron-expression-utils";
 import { cn, isEmpty } from "@/lib/utils";
+import { CredentialsProvidersContext } from "@/providers/agent-credentials/credentials-provider";
 import { ClockIcon, CopyIcon, InfoIcon } from "@phosphor-icons/react";
 import { CalendarClockIcon, Trash2Icon } from "lucide-react";
 
@@ -90,6 +102,7 @@ export function AgentRunDraftView({
   const api = useBackendAPI();
   const { toast } = useToast();
   const toastOnFail = useToastOnFail();
+  const allProviders = useContext(CredentialsProvidersContext);
 
   const [inputValues, setInputValues] = useState<Record<string, any>>({});
   const [inputCredentials, setInputCredentials] = useState<
@@ -128,6 +141,77 @@ export function AgentRunDraftView({
     () => graph.credentials_input_schema.properties,
     [graph],
   );
+  const credentialFields = useMemo(
+    function getCredentialFields() {
+      return Object.entries(agentCredentialsInputFields);
+    },
+    [agentCredentialsInputFields],
+  );
+  const requiredCredentials = useMemo(
+    function getRequiredCredentials() {
+      return new Set(
+        (graph.credentials_input_schema?.required as string[]) || [],
+      );
+    },
+    [graph.credentials_input_schema?.required],
+  );
+
+  useEffect(
+    function initializeDefaultCredentials() {
+      if (!allProviders) return;
+      if (!graph.credentials_input_schema?.properties) return;
+      if (requiredCredentials.size === 0) return;
+
+      setInputCredentials(function updateCredentials(currentCreds) {
+        const next = { ...currentCreds };
+        let didAdd = false;
+
+        for (const key of requiredCredentials) {
+          if (next[key]) continue;
+          const schema = graph.credentials_input_schema.properties[key];
+          if (!schema) continue;
+
+          const providerNames = schema.credentials_provider || [];
+          const credentialTypes = schema.credentials_types || [];
+          const requiredScopes = schema.credentials_scopes;
+
+          const userCredential = findSavedUserCredentialByProviderAndType(
+            providerNames,
+            credentialTypes,
+            requiredScopes,
+            allProviders,
+          );
+
+          const savedCredential =
+            userCredential ||
+            findSavedCredentialByProviderAndType(
+              providerNames,
+              credentialTypes,
+              requiredScopes,
+              allProviders,
+            );
+
+          if (!savedCredential) continue;
+
+          next[key] = {
+            id: savedCredential.id,
+            provider: savedCredential.provider,
+            type: savedCredential.type as CredentialsType,
+            title: savedCredential.title,
+          };
+          didAdd = true;
+        }
+
+        if (!didAdd) return currentCreds;
+        return next;
+      });
+    },
+    [
+      allProviders,
+      graph.credentials_input_schema?.properties,
+      requiredCredentials,
+    ],
+  );
 
   const [allRequiredInputsAreSet, missingInputs] = useMemo(() => {
     const nonEmptyInputs = new Set(
@@ -145,18 +229,35 @@ export function AgentRunDraftView({
     );
     return [isSuperset, difference];
   }, [agentInputSchema.required, inputValues]);
-  const [allCredentialsAreSet, missingCredentials] = useMemo(() => {
+  const [allCredentialsAreSet, missingCredentials] = useMemo(
-    const availableCredentials = new Set(Object.keys(inputCredentials));
+    function getCredentialStatus() {
-    const allCredentials = new Set(Object.keys(agentCredentialsInputFields));
+      const missing = Array.from(requiredCredentials).filter((key) => {
-    // Backwards-compatible implementation of isSupersetOf and difference
+        const cred = inputCredentials[key];
-    const isSuperset = Array.from(allCredentials).every((item) =>
+        return !cred || !cred.id;
-      availableCredentials.has(item),
+      });
-    );
+      return [missing.length === 0, missing];
-    const difference = Array.from(allCredentials).filter(
+    },
-      (item) => !availableCredentials.has(item),
+    [requiredCredentials, inputCredentials],
-    );
+  );
-    return [isSuperset, difference];
+  function addChangedCredentials(prev: Set<keyof LibraryAgentPresetUpdatable>) {
-  }, [agentCredentialsInputFields, inputCredentials]);
+    const next = new Set(prev);
+    next.add("credentials");
+    return next;
+  }
+
+  function handleCredentialChange(key: string, value?: CredentialsMetaInput) {
+    setInputCredentials(function updateInputCredentials(currentCreds) {
+      const next = { ...currentCreds };
+      if (value === undefined) {
+        delete next[key];
+        return next;
+      }
+      next[key] = value;
+      return next;
+    });
+    setChangedPresetAttributes(addChangedCredentials);
+  }
+
   const notifyMissingInputs = useCallback(
     (needPresetName: boolean = true) => {
       const allMissingFields = (
@@ -649,35 +750,6 @@ export function AgentRunDraftView({
               </>
             )}
 
-            {/* Credentials inputs */}
-            {Object.entries(agentCredentialsInputFields).map(
-              ([key, inputSubSchema]) => (
-                <CredentialsInput
-                  key={key}
-                  schema={{ ...inputSubSchema, discriminator: undefined }}
-                  selectedCredentials={
-                    inputCredentials[key] ?? inputSubSchema.default
-                  }
-                  onSelectCredentials={(value) => {
-                    setInputCredentials((obj) => {
-                      const newObj = { ...obj };
-                      if (value === undefined) {
-                        delete newObj[key];
-                        return newObj;
-                      }
-                      return {
-                        ...obj,
-                        [key]: value,
-                      };
-                    });
-                    setChangedPresetAttributes((prev) =>
-                      prev.add("credentials"),
-                    );
-                  }}
-                />
-              ),
-            )}
-
             {/* Regular inputs */}
             {Object.entries(agentInputFields).map(([key, inputSubSchema]) => (
               <RunAgentInputs
@@ -695,6 +767,17 @@ export function AgentRunDraftView({
                 data-testid={`agent-input-${key}`}
               />
             ))}
+
+            {/* Credentials inputs */}
+            {credentialFields.length > 0 && (
+              <CredentialsGroupedView
+                credentialFields={credentialFields}
+                requiredCredentials={requiredCredentials}
+                inputCredentials={inputCredentials}
+                inputValues={inputValues}
+                onCredentialChange={handleCredentialChange}
+              />
+            )}
           </CardContent>
         </Card>
       </div>

autogpt_platform/frontend/src/app/(platform)/library/components/LibraryAgentCard/useLibraryAgentCard.ts

@@ -8,6 +8,8 @@ import { useGetV2GetUserProfile } from "@/app/api/__generated__/endpoints/store/
 import { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent";
 import { okData } from "@/app/api/helpers";
 import { useToast } from "@/components/molecules/Toast/use-toast";
+import { isLogoutInProgress } from "@/lib/autogpt-server-api/helpers";
+import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
 import { updateFavoriteInQueries } from "./helpers";
 
 interface Props {
@@ -23,10 +25,14 @@ export function useLibraryAgentCard({ agent }: Props) {
   const { toast } = useToast();
   const queryClient = getQueryClient();
   const { mutateAsync: updateLibraryAgent } = usePatchV2UpdateLibraryAgent();
+  const { user, isLoggedIn } = useSupabase();
+  const logoutInProgress = isLogoutInProgress();
 
   const { data: profile } = useGetV2GetUserProfile({
     query: {
       select: okData,
+      enabled: isLoggedIn && !!user && !logoutInProgress,
+      queryKey: ["/api/store/profile", user?.id],
     },
   });
 

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

@@ -1,6 +1,8 @@
 import { useToast } from "@/components/molecules/Toast/use-toast";
+import { getHomepageRoute } from "@/lib/constants";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
 import { environment } from "@/services/environment";
+import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
 import { loginFormSchema, LoginProvider } from "@/types/auth";
 import { zodResolver } from "@hookform/resolvers/zod";
 import { useRouter, useSearchParams } from "next/navigation";
@@ -20,15 +22,17 @@ export function useLoginPage() {
   const [isGoogleLoading, setIsGoogleLoading] = useState(false);
   const [showNotAllowedModal, setShowNotAllowedModal] = useState(false);
   const isCloudEnv = environment.isCloud();
+  const isChatEnabled = useGetFlag(Flag.CHAT);
+  const homepageRoute = getHomepageRoute(isChatEnabled);
 
   // Get redirect destination from 'next' query parameter
   const nextUrl = searchParams.get("next");
 
   useEffect(() => {
     if (isLoggedIn && !isLoggingIn) {
-      router.push(nextUrl || "/marketplace");
+      router.push(nextUrl || homepageRoute);
     }
-  }, [isLoggedIn, isLoggingIn, nextUrl, router]);
+  }, [homepageRoute, isLoggedIn, isLoggingIn, nextUrl, router]);
 
   const form = useForm<z.infer<typeof loginFormSchema>>({
     resolver: zodResolver(loginFormSchema),
@@ -98,7 +102,7 @@ export function useLoginPage() {
       } else if (result.onboarding) {
         router.replace("/onboarding");
       } else {
-        router.replace("/marketplace");
+        router.replace(homepageRoute);
       }
     } catch (error) {
       toast({

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

@@ -0,0 +1,15 @@
+import { expect, test } from "vitest";
+import { render, screen } from "@/tests/integrations/test-utils";
+import { MainMarkeplacePage } from "../MainMarketplacePage";
+import { server } from "@/mocks/mock-server";
+import { getDeleteV2DeleteStoreSubmissionMockHandler422 } from "@/app/api/__generated__/endpoints/store/store.msw";
+
+// Only for CI testing purpose, will remove it in future PR
+test("MainMarketplacePage", async () => {
+  server.use(getDeleteV2DeleteStoreSubmissionMockHandler422());
+
+  render(<MainMarkeplacePage />);
+  expect(
+    await screen.findByText("Featured agents", { exact: false }),
+  ).toBeDefined();
+});

autogpt_platform/frontend/src/app/(platform)/profile/(user)/page.tsx

@@ -3,12 +3,14 @@
 import { useGetV2GetUserProfile } from "@/app/api/__generated__/endpoints/store/store";
 import { ProfileInfoForm } from "@/components/__legacy__/ProfileInfoForm";
 import { ErrorCard } from "@/components/molecules/ErrorCard/ErrorCard";
+import { isLogoutInProgress } from "@/lib/autogpt-server-api/helpers";
 import { ProfileDetails } from "@/lib/autogpt-server-api/types";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
 import { ProfileLoading } from "./ProfileLoading";
 
 export default function UserProfilePage() {
   const { user } = useSupabase();
+  const logoutInProgress = isLogoutInProgress();
 
   const {
     data: profile,
@@ -18,7 +20,7 @@ export default function UserProfilePage() {
     refetch,
   } = useGetV2GetUserProfile<ProfileDetails | null>({
     query: {
-      enabled: !!user,
+      enabled: !!user && !logoutInProgress,
       select: (res) => {
         if (res.status === 200) {
           return {

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

@@ -1,5 +1,6 @@
 "use server";
 
+import { getHomepageRoute } from "@/lib/constants";
 import { getServerSupabase } from "@/lib/supabase/server/getServerSupabase";
 import { signupFormSchema } from "@/types/auth";
 import * as Sentry from "@sentry/nextjs";
@@ -11,6 +12,7 @@ export async function signup(
   password: string,
   confirmPassword: string,
   agreeToTerms: boolean,
+  isChatEnabled: boolean,
 ) {
   try {
     const parsed = signupFormSchema.safeParse({
@@ -58,7 +60,9 @@ export async function signup(
     }
 
     const isOnboardingEnabled = await shouldShowOnboarding();
-    const next = isOnboardingEnabled ? "/onboarding" : "/";
+    const next = isOnboardingEnabled
+      ? "/onboarding"
+      : getHomepageRoute(isChatEnabled);
 
     return { success: true, next };
   } catch (err) {

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

@@ -1,6 +1,8 @@
 import { useToast } from "@/components/molecules/Toast/use-toast";
+import { getHomepageRoute } from "@/lib/constants";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
 import { environment } from "@/services/environment";
+import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
 import { LoginProvider, signupFormSchema } from "@/types/auth";
 import { zodResolver } from "@hookform/resolvers/zod";
 import { useRouter, useSearchParams } from "next/navigation";
@@ -20,15 +22,17 @@ export function useSignupPage() {
   const [isGoogleLoading, setIsGoogleLoading] = useState(false);
   const [showNotAllowedModal, setShowNotAllowedModal] = useState(false);
   const isCloudEnv = environment.isCloud();
+  const isChatEnabled = useGetFlag(Flag.CHAT);
+  const homepageRoute = getHomepageRoute(isChatEnabled);
 
   // Get redirect destination from 'next' query parameter
   const nextUrl = searchParams.get("next");
 
   useEffect(() => {
     if (isLoggedIn && !isSigningUp) {
-      router.push(nextUrl || "/marketplace");
+      router.push(nextUrl || homepageRoute);
     }
-  }, [isLoggedIn, isSigningUp, nextUrl, router]);
+  }, [homepageRoute, isLoggedIn, isSigningUp, nextUrl, router]);
 
   const form = useForm<z.infer<typeof signupFormSchema>>({
     resolver: zodResolver(signupFormSchema),
@@ -104,6 +108,7 @@ export function useSignupPage() {
         data.password,
         data.confirmPassword,
         data.agreeToTerms,
+        isChatEnabled === true,
       );
 
       setIsLoading(false);
@@ -129,7 +134,7 @@ export function useSignupPage() {
       }
 
       // Prefer the URL's next parameter, then result.next (for onboarding), then default
-      const redirectTo = nextUrl || result.next || "/";
+      const redirectTo = nextUrl || result.next || homepageRoute;
       router.replace(redirectTo);
     } catch (error) {
       setIsLoading(false);

autogpt_platform/frontend/src/app/api/mutators/custom-mutator.ts

@@ -4,12 +4,12 @@ import {
   getServerAuthToken,
 } from "@/lib/autogpt-server-api/helpers";
 
-import { transformDates } from "./date-transformer";
-import { environment } from "@/services/environment";
 import {
   IMPERSONATION_HEADER_NAME,
   IMPERSONATION_STORAGE_KEY,
 } from "@/lib/constants";
+import { environment } from "@/services/environment";
+import { transformDates } from "./date-transformer";
 
 const FRONTEND_BASE_URL =
   process.env.NEXT_PUBLIC_FRONTEND_BASE_URL || "http://localhost:3000";

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

@@ -1022,7 +1022,7 @@
       "get": {
         "tags": ["v2", "chat", "chat"],
         "summary": "Get Session",
-        "description": "Retrieve the details of a specific chat session.\n\nLooks up a chat session by ID for the given user (if authenticated) and returns all session data including messages.\n\nArgs:\n    session_id: The unique identifier for the desired chat session.\n    user_id: The optional authenticated user ID, or None for anonymous access.\n\nReturns:\n    SessionDetailResponse: Details for the requested session; raises NotFoundError if not found.",
+        "description": "Retrieve the details of a specific chat session.\n\nLooks up a chat session by ID for the given user (if authenticated) and returns all session data including messages.\n\nArgs:\n    session_id: The unique identifier for the desired chat session.\n    user_id: The optional authenticated user ID, or None for anonymous access.\n\nReturns:\n    SessionDetailResponse: Details for the requested session, or None if not found.",
         "operationId": "getV2GetSession",
         "security": [{ "HTTPBearerJWT": [] }],
         "parameters": [

autogpt_platform/frontend/src/app/globals.css

@@ -141,52 +141,6 @@
   }
 }
 
-@keyframes shimmer {
-  0% {
-    background-position: -200% 0;
-  }
-  100% {
-    background-position: 200% 0;
-  }
-}
-
-@keyframes l3 {
-  25% {
-    background-position:
-      0 0,
-      100% 100%,
-      100% calc(100% - 5px);
-  }
-  50% {
-    background-position:
-      0 100%,
-      100% 100%,
-      0 calc(100% - 5px);
-  }
-  75% {
-    background-position:
-      0 100%,
-      100% 0,
-      100% 5px;
-  }
-}
-
-.loader {
-  width: 80px;
-  height: 70px;
-  border: 5px solid rgb(241 245 249);
-  padding: 0 8px;
-  box-sizing: border-box;
-  background:
-    linear-gradient(rgb(15 23 42) 0 0) 0 0/8px 20px,
-    linear-gradient(rgb(15 23 42) 0 0) 100% 0/8px 20px,
-    radial-gradient(farthest-side, rgb(15 23 42) 90%, #0000) 0 5px/8px 8px
-      content-box,
-    transparent;
-  background-repeat: no-repeat;
-  animation: l3 2s infinite linear;
-}
-
 input[type="number"]::-webkit-outer-spin-button,
 input[type="number"]::-webkit-inner-spin-button {
   -webkit-appearance: none;

autogpt_platform/frontend/src/app/page.tsx

@@ -1,5 +1,27 @@
-import { redirect } from "next/navigation";
+"use client";
+
+import { getHomepageRoute } from "@/lib/constants";
+import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
+import { useRouter } from "next/navigation";
+import { useEffect } from "react";
 
 export default function Page() {
-  redirect("/marketplace");
+  const isChatEnabled = useGetFlag(Flag.CHAT);
+  const router = useRouter();
+  const homepageRoute = getHomepageRoute(isChatEnabled);
+  const envEnabled = process.env.NEXT_PUBLIC_LAUNCHDARKLY_ENABLED === "true";
+  const clientId = process.env.NEXT_PUBLIC_LAUNCHDARKLY_CLIENT_ID;
+  const isLaunchDarklyConfigured = envEnabled && Boolean(clientId);
+  const isFlagReady =
+    !isLaunchDarklyConfigured || typeof isChatEnabled === "boolean";
+
+  useEffect(
+    function redirectToHomepage() {
+      if (!isFlagReady) return;
+      router.replace(homepageRoute);
+    },
+    [homepageRoute, isFlagReady, router],
+  );
+
+  return null;
 }

autogpt_platform/frontend/src/components/atoms/Badge/Badge.test.tsx

@@ -1,81 +0,0 @@
-// import { render, screen } from "@testing-library/react";
-// import { describe, expect, it } from "vitest";
-// import { Badge } from "./Badge";
-
-// describe("Badge Component", () => {
-//   it("renders badge with content", () => {
-//     render(<Badge variant="success">Success</Badge>);
-
-//     expect(screen.getByText("Success")).toBeInTheDocument();
-//   });
-
-//   it("applies correct variant styles", () => {
-//     const { rerender } = render(<Badge variant="success">Success</Badge>);
-//     let badge = screen.getByText("Success");
-//     expect(badge).toHaveClass("bg-green-100", "text-green-800");
-
-//     rerender(<Badge variant="error">Error</Badge>);
-//     badge = screen.getByText("Error");
-//     expect(badge).toHaveClass("bg-red-100", "text-red-800");
-
-//     rerender(<Badge variant="info">Info</Badge>);
-//     badge = screen.getByText("Info");
-//     expect(badge).toHaveClass("bg-slate-100", "text-slate-800");
-//   });
-
-//   it("applies custom className", () => {
-//     render(
-//       <Badge variant="success" className="custom-class">
-//         Success
-//       </Badge>,
-//     );
-
-//     const badge = screen.getByText("Success");
-//     expect(badge).toHaveClass("custom-class");
-//   });
-
-//   it("renders as span element", () => {
-//     render(<Badge variant="success">Success</Badge>);
-
-//     const badge = screen.getByText("Success");
-//     expect(badge.tagName).toBe("SPAN");
-//   });
-
-//   it("renders children correctly", () => {
-//     render(
-//       <Badge variant="success">
-//         <span>Custom</span> Content
-//       </Badge>,
-//     );
-
-//     expect(screen.getByText("Custom")).toBeInTheDocument();
-//     expect(screen.getByText("Content")).toBeInTheDocument();
-//   });
-
-//   it("supports all badge variants", () => {
-//     const variants = ["success", "error", "info"] as const;
-
-//     variants.forEach((variant) => {
-//       const { unmount } = render(
-//         <Badge variant={variant} data-testid={`badge-${variant}`}>
-//           {variant}
-//         </Badge>,
-//       );
-
-//       expect(screen.getByTestId(`badge-${variant}`)).toBeInTheDocument();
-//       unmount();
-//     });
-//   });
-
-//   it("handles long text content", () => {
-//     render(
-//       <Badge variant="info">
-//         Very long text that should be handled properly by the component
-//       </Badge>,
-//     );
-
-//     const badge = screen.getByText(/Very long text/);
-//     expect(badge).toBeInTheDocument();
-//     expect(badge).toHaveClass("overflow-hidden", "text-ellipsis");
-//   });
-// });

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

@@ -0,0 +1,81 @@
+"use client";
+
+import { Text } from "@/components/atoms/Text/Text";
+import { cn } from "@/lib/utils";
+import { useEffect, useRef } from "react";
+import { ChatContainer } from "./components/ChatContainer/ChatContainer";
+import { ChatErrorState } from "./components/ChatErrorState/ChatErrorState";
+import { ChatLoader } from "./components/ChatLoader/ChatLoader";
+import { useChat } from "./useChat";
+
+export interface ChatProps {
+  className?: string;
+  urlSessionId?: string | null;
+  initialPrompt?: string;
+  onSessionNotFound?: () => void;
+}
+
+export function Chat({
+  className,
+  urlSessionId,
+  initialPrompt,
+  onSessionNotFound,
+}: ChatProps) {
+  const hasHandledNotFoundRef = useRef(false);
+  const {
+    messages,
+    isLoading,
+    isCreating,
+    error,
+    isSessionNotFound,
+    sessionId,
+    createSession,
+    showLoader,
+  } = useChat({ urlSessionId });
+
+  useEffect(
+    function handleMissingSession() {
+      if (!onSessionNotFound) return;
+      if (!urlSessionId) return;
+      if (!isSessionNotFound || isLoading || isCreating) return;
+      if (hasHandledNotFoundRef.current) return;
+      hasHandledNotFoundRef.current = true;
+      onSessionNotFound();
+    },
+    [onSessionNotFound, urlSessionId, isSessionNotFound, isLoading, isCreating],
+  );
+
+  return (
+    <div className={cn("flex h-full flex-col", className)}>
+      {/* Main Content */}
+      <main className="flex min-h-0 w-full flex-1 flex-col overflow-hidden bg-[#f8f8f9]">
+        {/* Loading State */}
+        {showLoader && (isLoading || isCreating) && (
+          <div className="flex flex-1 items-center justify-center">
+            <div className="flex flex-col items-center gap-4">
+              <ChatLoader />
+              <Text variant="body" className="text-zinc-500">
+                Loading your chats...
+              </Text>
+            </div>
+          </div>
+        )}
+
+        {/* Error State */}
+        {error && !isLoading && (
+          <ChatErrorState error={error} onRetry={createSession} />
+        )}
+
+        {/* Session Content */}
+        {sessionId && !isLoading && !error && (
+          <ChatContainer
+            sessionId={sessionId}
+            initialMessages={messages}
+            initialPrompt={initialPrompt}
+            className="flex-1"
+          />
+        )}
+      </main>
+    </div>
+  );
+}

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

@@ -0,0 +1,15 @@
+import { cn } from "@/lib/utils";
+import { ReactNode } from "react";
+
+export interface AIChatBubbleProps {
+  children: ReactNode;
+  className?: string;
+}
+
+export function AIChatBubble({ children, className }: AIChatBubbleProps) {
+  return (
+    <div className={cn("text-left text-[1rem] leading-relaxed", className)}>
+      {children}
+    </div>
+  );
+}

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

@@ -21,7 +21,7 @@ export function AuthPromptWidget({
   message,
   sessionId,
   agentInfo,
-  returnUrl = "/chat",
+  returnUrl = "/copilot/chat",
   className,
 }: AuthPromptWidgetProps) {
   const router = useRouter();

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

@@ -0,0 +1,106 @@
+import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
+import { Button } from "@/components/atoms/Button/Button";
+import { Text } from "@/components/atoms/Text/Text";
+import { Dialog } from "@/components/molecules/Dialog/Dialog";
+import { useBreakpoint } from "@/lib/hooks/useBreakpoint";
+import { cn } from "@/lib/utils";
+import { ChatInput } from "../ChatInput/ChatInput";
+import { MessageList } from "../MessageList/MessageList";
+import { useChatContainer } from "./useChatContainer";
+
+export interface ChatContainerProps {
+  sessionId: string | null;
+  initialMessages: SessionDetailResponse["messages"];
+  initialPrompt?: string;
+  className?: string;
+}
+
+export function ChatContainer({
+  sessionId,
+  initialMessages,
+  initialPrompt,
+  className,
+}: ChatContainerProps) {
+  const {
+    messages,
+    streamingChunks,
+    isStreaming,
+    stopStreaming,
+    isRegionBlockedModalOpen,
+    sendMessageWithContext,
+    handleRegionModalOpenChange,
+    handleRegionModalClose,
+  } = useChatContainer({
+    sessionId,
+    initialMessages,
+    initialPrompt,
+  });
+
+  const breakpoint = useBreakpoint();
+  const isMobile =
+    breakpoint === "base" || breakpoint === "sm" || breakpoint === "md";
+
+  return (
+    <div
+      className={cn(
+        "mx-auto flex h-full min-h-0 w-full max-w-3xl flex-col bg-[#f8f8f9]",
+        className,
+      )}
+    >
+      <Dialog
+        title="Service unavailable"
+        controlled={{
+          isOpen: isRegionBlockedModalOpen,
+          set: handleRegionModalOpenChange,
+        }}
+        onClose={handleRegionModalClose}
+      >
+        <Dialog.Content>
+          <div className="flex flex-col gap-4">
+            <Text variant="body">
+              This model is not available in your region. Please connect via VPN
+              and try again.
+            </Text>
+            <div className="flex justify-end">
+              <Button
+                type="button"
+                variant="primary"
+                onClick={handleRegionModalClose}
+              >
+                Got it
+              </Button>
+            </div>
+          </div>
+        </Dialog.Content>
+      </Dialog>
+      {/* Messages - Scrollable */}
+      <div className="relative flex min-h-0 flex-1 flex-col">
+        <div className="flex min-h-full flex-col justify-end">
+          <MessageList
+            messages={messages}
+            streamingChunks={streamingChunks}
+            isStreaming={isStreaming}
+            onSendMessage={sendMessageWithContext}
+            className="flex-1"
+          />
+        </div>
+      </div>
+
+      {/* Input - Fixed at bottom */}
+      <div className="relative px-3 pb-6 pt-2">
+        <div className="pointer-events-none absolute top-[-18px] z-10 h-6 w-full bg-gradient-to-b from-transparent to-[#f8f8f9]" />
+        <ChatInput
+          onSend={sendMessageWithContext}
+          disabled={isStreaming || !sessionId}
+          isStreaming={isStreaming}
+          onStop={stopStreaming}
+          placeholder={
+            isMobile
+              ? "You can search or just ask"
+              : 'You can search or just ask — e.g. "create a blog post outline"'
+          }
+        />
+      </div>
+    </div>
+  );
+}

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

@@ -1,6 +1,6 @@
 import { toast } from "sonner";
 import { StreamChunk } from "../../useChatStream";
-import type { HandlerDependencies } from "./useChatContainer.handlers";
+import type { HandlerDependencies } from "./handlers";
 import {
   handleError,
   handleLoginNeeded,
@@ -9,12 +9,30 @@ import {
   handleTextEnded,
   handleToolCallStart,
   handleToolResponse,
-} from "./useChatContainer.handlers";
+  isRegionBlockedError,
+} from "./handlers";
 
 export function createStreamEventDispatcher(
   deps: HandlerDependencies,
 ): (chunk: StreamChunk) => void {
   return function dispatchStreamEvent(chunk: StreamChunk): void {
+    if (
+      chunk.type === "text_chunk" ||
+      chunk.type === "tool_call_start" ||
+      chunk.type === "tool_response" ||
+      chunk.type === "login_needed" ||
+      chunk.type === "need_login" ||
+      chunk.type === "error"
+    ) {
+      if (!deps.hasResponseRef.current) {
+        console.info("[ChatStream] First response chunk:", {
+          type: chunk.type,
+          sessionId: deps.sessionId,
+        });
+      }
+      deps.hasResponseRef.current = true;
+    }
+
     switch (chunk.type) {
       case "text_chunk":
         handleTextChunk(chunk, deps);
@@ -38,15 +56,23 @@ export function createStreamEventDispatcher(
         break;
 
       case "stream_end":
+        console.info("[ChatStream] Stream ended:", {
+          sessionId: deps.sessionId,
+          hasResponse: deps.hasResponseRef.current,
+          chunkCount: deps.streamingChunksRef.current.length,
+        });
         handleStreamEnd(chunk, deps);
         break;
 
       case "error":
+        const isRegionBlocked = isRegionBlockedError(chunk);
         handleError(chunk, deps);
         // Show toast at dispatcher level to avoid circular dependencies
-        toast.error("Chat Error", {
+        if (!isRegionBlocked) {
-          description: chunk.message || chunk.content || "An error occurred",
+          toast.error("Chat Error", {
-        });
+            description: chunk.message || chunk.content || "An error occurred",
+          });
+        }
         break;
 
       case "usage":

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

@@ -7,15 +7,30 @@ import {
   parseToolResponse,
 } from "./helpers";
 
+function isToolCallMessage(
+  message: ChatMessageData,
+): message is Extract<ChatMessageData, { type: "tool_call" }> {
+  return message.type === "tool_call";
+}
+
 export interface HandlerDependencies {
   setHasTextChunks: Dispatch<SetStateAction<boolean>>;
   setStreamingChunks: Dispatch<SetStateAction<string[]>>;
   streamingChunksRef: MutableRefObject<string[]>;
+  hasResponseRef: MutableRefObject<boolean>;
   setMessages: Dispatch<SetStateAction<ChatMessageData[]>>;
   setIsStreamingInitiated: Dispatch<SetStateAction<boolean>>;
+  setIsRegionBlockedModalOpen: Dispatch<SetStateAction<boolean>>;
   sessionId: string;
 }
 
+export function isRegionBlockedError(chunk: StreamChunk): boolean {
+  if (chunk.code === "MODEL_NOT_AVAILABLE_REGION") return true;
+  const message = chunk.message || chunk.content;
+  if (typeof message !== "string") return false;
+  return message.toLowerCase().includes("not available in your region");
+}
+
 export function handleTextChunk(chunk: StreamChunk, deps: HandlerDependencies) {
   if (!chunk.content) return;
   deps.setHasTextChunks(true);
@@ -30,16 +45,17 @@ export function handleTextEnded(
   _chunk: StreamChunk,
   deps: HandlerDependencies,
 ) {
-  console.log("[Text Ended] Saving streamed text as assistant message");
   const completedText = deps.streamingChunksRef.current.join("");
   if (completedText.trim()) {
-    const assistantMessage: ChatMessageData = {
+    deps.setMessages((prev) => {
-      type: "message",
+      const assistantMessage: ChatMessageData = {
-      role: "assistant",
+        type: "message",
-      content: completedText,
+        role: "assistant",
-      timestamp: new Date(),
+        content: completedText,
-    };
+        timestamp: new Date(),
-    deps.setMessages((prev) => [...prev, assistantMessage]);
+      };
+      return [...prev, assistantMessage];
+    });
   }
   deps.setStreamingChunks([]);
   deps.streamingChunksRef.current = [];
@@ -50,30 +66,45 @@ export function handleToolCallStart(
   chunk: StreamChunk,
   deps: HandlerDependencies,
 ) {
-  const toolCallMessage: ChatMessageData = {
+  const toolCallMessage: Extract<ChatMessageData, { type: "tool_call" }> = {
     type: "tool_call",
     toolId: chunk.tool_id || `tool-${Date.now()}-${chunk.idx || 0}`,
-    toolName: chunk.tool_name || "Executing...",
+    toolName: chunk.tool_name || "Executing",
     arguments: chunk.arguments || {},
     timestamp: new Date(),
   };
-  deps.setMessages((prev) => [...prev, toolCallMessage]);
+
-  console.log("[Tool Call Start]", {
+  function updateToolCallMessages(prev: ChatMessageData[]) {
-    toolId: toolCallMessage.toolId,
+    const existingIndex = prev.findIndex(function findToolCallIndex(msg) {
-    toolName: toolCallMessage.toolName,
+      return isToolCallMessage(msg) && msg.toolId === toolCallMessage.toolId;
-    timestamp: new Date().toISOString(),
+    });
-  });
+    if (existingIndex === -1) {
+      return [...prev, toolCallMessage];
+    }
+    const nextMessages = [...prev];
+    const existing = nextMessages[existingIndex];
+    if (!isToolCallMessage(existing)) return prev;
+    const nextArguments =
+      toolCallMessage.arguments &&
+      Object.keys(toolCallMessage.arguments).length > 0
+        ? toolCallMessage.arguments
+        : existing.arguments;
+    nextMessages[existingIndex] = {
+      ...existing,
+      toolName: toolCallMessage.toolName || existing.toolName,
+      arguments: nextArguments,
+      timestamp: toolCallMessage.timestamp,
+    };
+    return nextMessages;
+  }
+
+  deps.setMessages(updateToolCallMessages);
 }
 
 export function handleToolResponse(
   chunk: StreamChunk,
   deps: HandlerDependencies,
 ) {
-  console.log("[Tool Response] Received:", {
-    toolId: chunk.tool_id,
-    toolName: chunk.tool_name,
-    timestamp: new Date().toISOString(),
-  });
   let toolName = chunk.tool_name || "unknown";
   if (!chunk.tool_name || chunk.tool_name === "unknown") {
     deps.setMessages((prev) => {
@@ -127,22 +158,15 @@ export function handleToolResponse(
     const toolCallIndex = prev.findIndex(
       (msg) => msg.type === "tool_call" && msg.toolId === chunk.tool_id,
     );
+    const hasResponse = prev.some(
+      (msg) => msg.type === "tool_response" && msg.toolId === chunk.tool_id,
+    );
+    if (hasResponse) return prev;
     if (toolCallIndex !== -1) {
       const newMessages = [...prev];
-      newMessages[toolCallIndex] = responseMessage;
+      newMessages.splice(toolCallIndex + 1, 0, responseMessage);
-      console.log(
-        "[Tool Response] Replaced tool_call with matching tool_id:",
-        chunk.tool_id,
-        "at index:",
-        toolCallIndex,
-      );
       return newMessages;
     }
-    console.warn(
-      "[Tool Response] No tool_call found with tool_id:",
-      chunk.tool_id,
-      "appending instead",
-    );
     return [...prev, responseMessage];
   });
 }
@@ -167,55 +191,38 @@ export function handleStreamEnd(
   deps: HandlerDependencies,
 ) {
   const completedContent = deps.streamingChunksRef.current.join("");
-  // Only save message if there are uncommitted chunks
+  if (!completedContent.trim() && !deps.hasResponseRef.current) {
-  // (text_ended already saved if there were tool calls)
+    deps.setMessages((prev) => [
+      ...prev,
+      {
+        type: "message",
+        role: "assistant",
+        content: "No response received. Please try again.",
+        timestamp: new Date(),
+      },
+    ]);
+  }
   if (completedContent.trim()) {
-    console.log(
-      "[Stream End] Saving remaining streamed text as assistant message",
-    );
     const assistantMessage: ChatMessageData = {
       type: "message",
       role: "assistant",
       content: completedContent,
       timestamp: new Date(),
     };
-    deps.setMessages((prev) => {
+    deps.setMessages((prev) => [...prev, assistantMessage]);
-      const updated = [...prev, assistantMessage];
-      console.log("[Stream End] Final state:", {
-        localMessages: updated.map((m) => ({
-          type: m.type,
-          ...(m.type === "message" && {
-            role: m.role,
-            contentLength: m.content.length,
-          }),
-          ...(m.type === "tool_call" && {
-            toolId: m.toolId,
-            toolName: m.toolName,
-          }),
-          ...(m.type === "tool_response" && {
-            toolId: m.toolId,
-            toolName: m.toolName,
-            success: m.success,
-          }),
-        })),
-        streamingChunks: deps.streamingChunksRef.current,
-        timestamp: new Date().toISOString(),
-      });
-      return updated;
-    });
-  } else {
-    console.log("[Stream End] No uncommitted chunks, message already saved");
   }
   deps.setStreamingChunks([]);
   deps.streamingChunksRef.current = [];
   deps.setHasTextChunks(false);
   deps.setIsStreamingInitiated(false);
-  console.log("[Stream End] Stream complete, messages in local state");
 }
 
 export function handleError(chunk: StreamChunk, deps: HandlerDependencies) {
   const errorMessage = chunk.message || chunk.content || "An error occurred";
   console.error("Stream error:", errorMessage);
+  if (isRegionBlockedError(chunk)) {
+    deps.setIsRegionBlockedModalOpen(true);
+  }
   deps.setIsStreamingInitiated(false);
   deps.setHasTextChunks(false);
   deps.setStreamingChunks([]);

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

@@ -1,6 +1,33 @@
+import { SessionKey, sessionStorage } from "@/services/storage/session-storage";
 import type { ToolResult } from "@/types/chat";
 import type { ChatMessageData } from "../ChatMessage/useChatMessage";
 
+export function hasSentInitialPrompt(sessionId: string): boolean {
+  try {
+    const sent = JSON.parse(
+      sessionStorage.get(SessionKey.CHAT_SENT_INITIAL_PROMPTS) || "{}",
+    );
+    return sent[sessionId] === true;
+  } catch {
+    return false;
+  }
+}
+
+export function markInitialPromptSent(sessionId: string): void {
+  try {
+    const sent = JSON.parse(
+      sessionStorage.get(SessionKey.CHAT_SENT_INITIAL_PROMPTS) || "{}",
+    );
+    sent[sessionId] = true;
+    sessionStorage.set(
+      SessionKey.CHAT_SENT_INITIAL_PROMPTS,
+      JSON.stringify(sent),
+    );
+  } catch {
+    // Ignore storage errors
+  }
+}
+
 export function removePageContext(content: string): string {
   // Remove "Page URL: ..." pattern at start of line (case insensitive, handles various formats)
   let cleaned = content.replace(/^\s*Page URL:\s*[^\n\r]*/gim, "");
@@ -207,12 +234,22 @@ export function parseToolResponse(
     if (responseType === "setup_requirements") {
       return null;
     }
+    if (responseType === "understanding_updated") {
+      return {
+        type: "tool_response",
+        toolId,
+        toolName,
+        result: (parsedResult || result) as ToolResult,
+        success: true,
+        timestamp: timestamp || new Date(),
+      };
+    }
   }
   return {
     type: "tool_response",
     toolId,
     toolName,
-    result,
+    result: parsedResult ? (parsedResult as ToolResult) : result,
     success: true,
     timestamp: timestamp || new Date(),
   };

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

@@ -1,14 +1,17 @@
 import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
-import { useCallback, useMemo, useRef, useState } from "react";
+import { useCallback, useEffect, useMemo, useRef, useState } from "react";
 import { toast } from "sonner";
 import { useChatStream } from "../../useChatStream";
+import { usePageContext } from "../../usePageContext";
 import type { ChatMessageData } from "../ChatMessage/useChatMessage";
 import { createStreamEventDispatcher } from "./createStreamEventDispatcher";
 import {
   createUserMessage,
   filterAuthMessages,
+  hasSentInitialPrompt,
   isToolCallArray,
   isValidMessage,
+  markInitialPromptSent,
   parseToolResponse,
   removePageContext,
 } from "./helpers";
@@ -16,20 +19,45 @@ import {
 interface Args {
   sessionId: string | null;
   initialMessages: SessionDetailResponse["messages"];
+  initialPrompt?: string;
 }
 
-export function useChatContainer({ sessionId, initialMessages }: Args) {
+export function useChatContainer({
+  sessionId,
+  initialMessages,
+  initialPrompt,
+}: Args) {
   const [messages, setMessages] = useState<ChatMessageData[]>([]);
   const [streamingChunks, setStreamingChunks] = useState<string[]>([]);
   const [hasTextChunks, setHasTextChunks] = useState(false);
   const [isStreamingInitiated, setIsStreamingInitiated] = useState(false);
+  const [isRegionBlockedModalOpen, setIsRegionBlockedModalOpen] =
+    useState(false);
+  const hasResponseRef = useRef(false);
   const streamingChunksRef = useRef<string[]>([]);
-  const { error, sendMessage: sendStreamMessage } = useChatStream();
+  const previousSessionIdRef = useRef<string | null>(null);
+  const {
+    error,
+    sendMessage: sendStreamMessage,
+    stopStreaming,
+  } = useChatStream();
   const isStreaming = isStreamingInitiated || hasTextChunks;
 
+  useEffect(() => {
+    if (sessionId !== previousSessionIdRef.current) {
+      stopStreaming(previousSessionIdRef.current ?? undefined, true);
+      previousSessionIdRef.current = sessionId;
+      setMessages([]);
+      setStreamingChunks([]);
+      streamingChunksRef.current = [];
+      setHasTextChunks(false);
+      setIsStreamingInitiated(false);
+      hasResponseRef.current = false;
+    }
+  }, [sessionId, stopStreaming]);
+
   const allMessages = useMemo(() => {
     const processedInitialMessages: ChatMessageData[] = [];
-    // Map to track tool calls by their ID so we can look up tool names for tool responses
     const toolCallMap = new Map<string, string>();
 
     for (const msg of initialMessages) {
@@ -45,13 +73,9 @@ export function useChatContainer({ sessionId, initialMessages }: Args) {
         ? new Date(msg.timestamp as string)
         : undefined;
 
-      // Remove page context from user messages when loading existing sessions
       if (role === "user") {
         content = removePageContext(content);
-        // Skip user messages that become empty after removing page context
+        if (!content.trim()) continue;
-        if (!content.trim()) {
-          continue;
-        }
         processedInitialMessages.push({
           type: "message",
           role: "user",
@@ -61,19 +85,15 @@ export function useChatContainer({ sessionId, initialMessages }: Args) {
         continue;
       }
 
-      // Handle assistant messages first (before tool messages) to build tool call map
       if (role === "assistant") {
-        // Strip <thinking> tags from content
         content = content
           .replace(/<thinking>[\s\S]*?<\/thinking>/gi, "")
           .trim();
 
-        // If assistant has tool calls, create tool_call messages for each
         if (toolCalls && isToolCallArray(toolCalls) && toolCalls.length > 0) {
           for (const toolCall of toolCalls) {
             const toolName = toolCall.function.name;
             const toolId = toolCall.id;
-            // Store tool name for later lookup
             toolCallMap.set(toolId, toolName);
 
             try {
@@ -96,7 +116,6 @@ export function useChatContainer({ sessionId, initialMessages }: Args) {
               });
             }
           }
-          // Only add assistant message if there's content after stripping thinking tags
           if (content.trim()) {
             processedInitialMessages.push({
               type: "message",
@@ -106,7 +125,6 @@ export function useChatContainer({ sessionId, initialMessages }: Args) {
             });
           }
         } else if (content.trim()) {
-          // Assistant message without tool calls, but with content
           processedInitialMessages.push({
             type: "message",
             role: "assistant",
@@ -117,7 +135,6 @@ export function useChatContainer({ sessionId, initialMessages }: Args) {
         continue;
       }
 
-      // Handle tool messages - look up tool name from tool call map
       if (role === "tool") {
         const toolCallId = (msg.tool_call_id as string) || "";
         const toolName = toolCallMap.get(toolCallId) || "unknown";
@@ -133,7 +150,6 @@ export function useChatContainer({ sessionId, initialMessages }: Args) {
         continue;
       }
 
-      // Handle other message types (system, etc.)
       if (content.trim()) {
         processedInitialMessages.push({
           type: "message",
@@ -154,9 +170,10 @@ export function useChatContainer({ sessionId, initialMessages }: Args) {
       context?: { url: string; content: string },
     ) {
       if (!sessionId) {
-        console.error("Cannot send message: no session ID");
+        console.error("[useChatContainer] Cannot send message: no session ID");
         return;
       }
+      setIsRegionBlockedModalOpen(false);
       if (isUserMessage) {
         const userMessage = createUserMessage(content);
         setMessages((prev) => [...filterAuthMessages(prev), userMessage]);
@@ -167,14 +184,19 @@ export function useChatContainer({ sessionId, initialMessages }: Args) {
       streamingChunksRef.current = [];
       setHasTextChunks(false);
       setIsStreamingInitiated(true);
+      hasResponseRef.current = false;
+
       const dispatcher = createStreamEventDispatcher({
         setHasTextChunks,
         setStreamingChunks,
         streamingChunksRef,
+        hasResponseRef,
         setMessages,
+        setIsRegionBlockedModalOpen,
         sessionId,
         setIsStreamingInitiated,
       });
+
       try {
         await sendStreamMessage(
           sessionId,
@@ -184,8 +206,12 @@ export function useChatContainer({ sessionId, initialMessages }: Args) {
           context,
         );
       } catch (err) {
-        console.error("Failed to send message:", err);
+        console.error("[useChatContainer] Failed to send message:", err);
         setIsStreamingInitiated(false);
+
+        // Don't show error toast for AbortError (expected during cleanup)
+        if (err instanceof Error && err.name === "AbortError") return;
+
         const errorMessage =
           err instanceof Error ? err.message : "Failed to send message";
         toast.error("Failed to send message", {
@@ -196,11 +222,63 @@ export function useChatContainer({ sessionId, initialMessages }: Args) {
     [sessionId, sendStreamMessage],
   );
 
+  const handleStopStreaming = useCallback(() => {
+    stopStreaming();
+    setStreamingChunks([]);
+    streamingChunksRef.current = [];
+    setHasTextChunks(false);
+    setIsStreamingInitiated(false);
+  }, [stopStreaming]);
+
+  const { capturePageContext } = usePageContext();
+
+  // Send initial prompt if provided (for new sessions from homepage)
+  useEffect(
+    function handleInitialPrompt() {
+      if (!initialPrompt || !sessionId) return;
+      if (initialMessages.length > 0) return;
+      if (hasSentInitialPrompt(sessionId)) return;
+
+      markInitialPromptSent(sessionId);
+      const context = capturePageContext();
+      sendMessage(initialPrompt, true, context);
+    },
+    [
+      initialPrompt,
+      sessionId,
+      initialMessages.length,
+      sendMessage,
+      capturePageContext,
+    ],
+  );
+
+  async function sendMessageWithContext(
+    content: string,
+    isUserMessage: boolean = true,
+  ) {
+    const context = capturePageContext();
+    await sendMessage(content, isUserMessage, context);
+  }
+
+  function handleRegionModalOpenChange(open: boolean) {
+    setIsRegionBlockedModalOpen(open);
+  }
+
+  function handleRegionModalClose() {
+    setIsRegionBlockedModalOpen(false);
+  }
+
   return {
     messages: allMessages,
     streamingChunks,
     isStreaming,
     error,
+    isRegionBlockedModalOpen,
+    setIsRegionBlockedModalOpen,
+    sendMessageWithContext,
+    handleRegionModalOpenChange,
+    handleRegionModalClose,
     sendMessage,
+    stopStreaming: handleStopStreaming,
   };
 }

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

@@ -0,0 +1,103 @@
+import { Button } from "@/components/atoms/Button/Button";
+import { cn } from "@/lib/utils";
+import { ArrowUpIcon, StopIcon } from "@phosphor-icons/react";
+import { useChatInput } from "./useChatInput";
+
+export interface Props {
+  onSend: (message: string) => void;
+  disabled?: boolean;
+  isStreaming?: boolean;
+  onStop?: () => void;
+  placeholder?: string;
+  className?: string;
+}
+
+export function ChatInput({
+  onSend,
+  disabled = false,
+  isStreaming = false,
+  onStop,
+  placeholder = "Type your message...",
+  className,
+}: Props) {
+  const inputId = "chat-input";
+  const { value, setValue, handleKeyDown, handleSend, hasMultipleLines } =
+    useChatInput({
+      onSend,
+      disabled: disabled || isStreaming,
+      maxRows: 4,
+      inputId,
+    });
+
+  function handleSubmit(e: React.FormEvent<HTMLFormElement>) {
+    e.preventDefault();
+    handleSend();
+  }
+
+  function handleChange(e: React.ChangeEvent<HTMLTextAreaElement>) {
+    setValue(e.target.value);
+  }
+
+  return (
+    <form onSubmit={handleSubmit} className={cn("relative flex-1", className)}>
+      <div className="relative">
+        <div
+          id={`${inputId}-wrapper`}
+          className={cn(
+            "relative overflow-hidden border border-neutral-200 bg-white shadow-sm",
+            "focus-within:border-zinc-400 focus-within:ring-1 focus-within:ring-zinc-400",
+            hasMultipleLines ? "rounded-xlarge" : "rounded-full",
+          )}
+        >
+          <textarea
+            id={inputId}
+            aria-label="Chat message input"
+            value={value}
+            onChange={handleChange}
+            onKeyDown={handleKeyDown}
+            placeholder={placeholder}
+            disabled={disabled || isStreaming}
+            rows={1}
+            className={cn(
+              "w-full resize-none overflow-y-auto border-0 bg-transparent text-[1rem] leading-6 text-black",
+              "placeholder:text-zinc-400",
+              "focus:outline-none focus:ring-0",
+              "disabled:text-zinc-500",
+              hasMultipleLines ? "pb-6 pl-4 pr-4 pt-2" : "pb-4 pl-4 pr-14 pt-4",
+            )}
+          />
+        </div>
+        <span id="chat-input-hint" className="sr-only">
+          Press Enter to send, Shift+Enter for new line
+        </span>
+
+        {isStreaming ? (
+          <Button
+            type="button"
+            variant="icon"
+            size="icon"
+            aria-label="Stop generating"
+            onClick={onStop}
+            className="absolute bottom-[7px] right-2 border-red-600 bg-red-600 text-white hover:border-red-800 hover:bg-red-800"
+          >
+            <StopIcon className="h-4 w-4" weight="bold" />
+          </Button>
+        ) : (
+          <Button
+            type="submit"
+            variant="icon"
+            size="icon"
+            aria-label="Send message"
+            className={cn(
+              "absolute bottom-[7px] right-2 border-zinc-800 bg-zinc-800 text-white hover:border-zinc-900 hover:bg-zinc-900",
+              (disabled || !value.trim()) && "opacity-20",
+            )}
+            disabled={disabled || !value.trim()}
+          >
+            <ArrowUpIcon className="h-4 w-4" weight="bold" />
+          </Button>
+        )}
+      </div>
+    </form>
+  );
+}

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/useChatInput.ts

@@ -0,0 +1,115 @@
+import { KeyboardEvent, useCallback, useEffect, useState } from "react";
+
+interface UseChatInputArgs {
+  onSend: (message: string) => void;
+  disabled?: boolean;
+  maxRows?: number;
+  inputId?: string;
+}
+
+export function useChatInput({
+  onSend,
+  disabled = false,
+  maxRows = 5,
+  inputId = "chat-input",
+}: UseChatInputArgs) {
+  const [value, setValue] = useState("");
+  const [hasMultipleLines, setHasMultipleLines] = useState(false);
+
+  useEffect(() => {
+    const textarea = document.getElementById(inputId) as HTMLTextAreaElement;
+    const wrapper = document.getElementById(
+      `${inputId}-wrapper`,
+    ) as HTMLDivElement;
+    if (!textarea || !wrapper) return;
+
+    const isEmpty = !value.trim();
+    const lines = value.split("\n").length;
+    const hasExplicitNewlines = lines > 1;
+
+    const computedStyle = window.getComputedStyle(textarea);
+    const lineHeight = parseInt(computedStyle.lineHeight, 10);
+    const paddingTop = parseInt(computedStyle.paddingTop, 10);
+    const paddingBottom = parseInt(computedStyle.paddingBottom, 10);
+
+    const singleLinePadding = paddingTop + paddingBottom;
+
+    textarea.style.height = "auto";
+    const scrollHeight = textarea.scrollHeight;
+
+    const singleLineHeight = lineHeight + singleLinePadding;
+    const isMultiLine =
+      hasExplicitNewlines || scrollHeight > singleLineHeight + 2;
+    setHasMultipleLines(isMultiLine);
+
+    if (isEmpty) {
+      wrapper.style.height = `${singleLineHeight}px`;
+      wrapper.style.maxHeight = "";
+      textarea.style.height = `${singleLineHeight}px`;
+      textarea.style.maxHeight = "";
+      textarea.style.overflowY = "hidden";
+      return;
+    }
+
+    if (isMultiLine) {
+      const wrapperMaxHeight = 196;
+      const currentMultilinePadding = paddingTop + paddingBottom;
+      const contentMaxHeight = wrapperMaxHeight - currentMultilinePadding;
+      const minMultiLineHeight = lineHeight * 2 + currentMultilinePadding;
+      const contentHeight = scrollHeight;
+      const targetWrapperHeight = Math.min(
+        Math.max(contentHeight + currentMultilinePadding, minMultiLineHeight),
+        wrapperMaxHeight,
+      );
+
+      wrapper.style.height = `${targetWrapperHeight}px`;
+      wrapper.style.maxHeight = `${wrapperMaxHeight}px`;
+      textarea.style.height = `${contentHeight}px`;
+      textarea.style.maxHeight = `${contentMaxHeight}px`;
+      textarea.style.overflowY =
+        contentHeight > contentMaxHeight ? "auto" : "hidden";
+    } else {
+      wrapper.style.height = `${singleLineHeight}px`;
+      wrapper.style.maxHeight = "";
+      textarea.style.height = `${singleLineHeight}px`;
+      textarea.style.maxHeight = "";
+      textarea.style.overflowY = "hidden";
+    }
+  }, [value, maxRows, inputId]);
+
+  const handleSend = useCallback(() => {
+    if (disabled || !value.trim()) return;
+    onSend(value.trim());
+    setValue("");
+    setHasMultipleLines(false);
+    const textarea = document.getElementById(inputId) as HTMLTextAreaElement;
+    const wrapper = document.getElementById(
+      `${inputId}-wrapper`,
+    ) as HTMLDivElement;
+    if (textarea) {
+      textarea.style.height = "auto";
+    }
+    if (wrapper) {
+      wrapper.style.height = "";
+      wrapper.style.maxHeight = "";
+    }
+  }, [value, onSend, disabled, inputId]);
+
+  const handleKeyDown = useCallback(
+    (event: KeyboardEvent<HTMLTextAreaElement>) => {
+      if (event.key === "Enter" && !event.shiftKey) {
+        event.preventDefault();
+        handleSend();
+      }
+    },
+    [handleSend],
+  );
+
+  return {
+    value,
+    setValue,
+    handleKeyDown,
+    handleSend,
+    hasMultipleLines,
+  };
+}

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

@@ -0,0 +1,12 @@
+import { Text } from "@/components/atoms/Text/Text";
+
+export function ChatLoader() {
+  return (
+    <Text
+      variant="small"
+      className="bg-gradient-to-r from-neutral-600 via-neutral-500 to-neutral-600 bg-[length:200%_100%] bg-clip-text text-xs text-transparent [animation:shimmer_2s_ease-in-out_infinite]"
+    >
+      Taking a bit more time...
+    </Text>
+  );
+}

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

@@ -1,48 +1,65 @@
 "use client";
 
-import { useGetV2GetUserProfile } from "@/app/api/__generated__/endpoints/store/store";
-import Avatar, {
-  AvatarFallback,
-  AvatarImage,
-} from "@/components/atoms/Avatar/Avatar";
 import { Button } from "@/components/atoms/Button/Button";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
 import { cn } from "@/lib/utils";
 import {
-  ArrowClockwise,
+  ArrowsClockwiseIcon,
   CheckCircleIcon,
   CheckIcon,
   CopyIcon,
-  RobotIcon,
 } from "@phosphor-icons/react";
 import { useRouter } from "next/navigation";
 import { useCallback, useState } from "react";
-import { getToolActionPhrase } from "../../helpers";
 import { AgentCarouselMessage } from "../AgentCarouselMessage/AgentCarouselMessage";
+import { AIChatBubble } from "../AIChatBubble/AIChatBubble";
 import { AuthPromptWidget } from "../AuthPromptWidget/AuthPromptWidget";
 import { ChatCredentialsSetup } from "../ChatCredentialsSetup/ChatCredentialsSetup";
 import { ExecutionStartedMessage } from "../ExecutionStartedMessage/ExecutionStartedMessage";
 import { MarkdownContent } from "../MarkdownContent/MarkdownContent";
-import { MessageBubble } from "../MessageBubble/MessageBubble";
 import { NoResultsMessage } from "../NoResultsMessage/NoResultsMessage";
 import { ToolCallMessage } from "../ToolCallMessage/ToolCallMessage";
 import { ToolResponseMessage } from "../ToolResponseMessage/ToolResponseMessage";
+import { UserChatBubble } from "../UserChatBubble/UserChatBubble";
 import { useChatMessage, type ChatMessageData } from "./useChatMessage";
+
+function stripInternalReasoning(content: string): string {
+  const cleaned = content.replace(
+    /<internal_reasoning>[\s\S]*?<\/internal_reasoning>/gi,
+    "",
+  );
+  return cleaned.replace(/\n{3,}/g, "\n\n").trim();
+}
+
+function getDisplayContent(message: ChatMessageData, isUser: boolean): string {
+  if (message.type !== "message") return "";
+  if (isUser) return message.content;
+  return stripInternalReasoning(message.content);
+}
+
 export interface ChatMessageProps {
   message: ChatMessageData;
+  messages?: ChatMessageData[];
+  index?: number;
+  isStreaming?: boolean;
   className?: string;
   onDismissLogin?: () => void;
   onDismissCredentials?: () => void;
   onSendMessage?: (content: string, isUserMessage?: boolean) => void;
   agentOutput?: ChatMessageData;
+  isFinalMessage?: boolean;
 }
 
 export function ChatMessage({
   message,
+  messages = [],
+  index = -1,
+  isStreaming = false,
   className,
   onDismissCredentials,
   onSendMessage,
   agentOutput,
+  isFinalMessage = true,
 }: ChatMessageProps) {
   const { user } = useSupabase();
   const router = useRouter();
@@ -54,14 +71,7 @@ export function ChatMessage({
     isLoginNeeded,
     isCredentialsNeeded,
   } = useChatMessage(message);
-
+  const displayContent = getDisplayContent(message, isUser);
-  const { data: profile } = useGetV2GetUserProfile({
-    query: {
-      select: (res) => (res.status === 200 ? res.data : null),
-      enabled: isUser && !!user,
-      queryKey: ["/api/store/profile", user?.id],
-    },
-  });
 
   const handleAllCredentialsComplete = useCallback(
     function handleAllCredentialsComplete() {
@@ -87,17 +97,25 @@ export function ChatMessage({
     }
   }
 
-  const handleCopy = useCallback(async () => {
+  const handleCopy = useCallback(
-    if (message.type !== "message") return;
+    async function handleCopy() {
+      if (message.type !== "message") return;
+      if (!displayContent) return;
 
-    try {
+      try {
-      await navigator.clipboard.writeText(message.content);
+        await navigator.clipboard.writeText(displayContent);
-      setCopied(true);
+        setCopied(true);
-      setTimeout(() => setCopied(false), 2000);
+        setTimeout(() => setCopied(false), 2000);
-    } catch (error) {
+      } catch (error) {
-      console.error("Failed to copy:", error);
+        console.error("Failed to copy:", error);
-    }
+      }
-  }, [message]);
+    },
+    [displayContent, message],
+  );
+
+  function isLongResponse(content: string): boolean {
+    return content.split("\n").length > 5;
+  }
 
   const handleTryAgain = useCallback(() => {
     if (message.type !== "message" || !onSendMessage) return;
@@ -169,9 +187,45 @@ export function ChatMessage({
 
   // Render tool call messages
   if (isToolCall && message.type === "tool_call") {
+    // Check if this tool call is currently streaming
+    // A tool call is streaming if:
+    // 1. isStreaming is true
+    // 2. This is the last tool_call message
+    // 3. There's no tool_response for this tool call yet
+    const isToolCallStreaming =
+      isStreaming &&
+      index >= 0 &&
+      (() => {
+        // Find the last tool_call index
+        let lastToolCallIndex = -1;
+        for (let i = messages.length - 1; i >= 0; i--) {
+          if (messages[i].type === "tool_call") {
+            lastToolCallIndex = i;
+            break;
+          }
+        }
+        // Check if this is the last tool_call and there's no response yet
+        if (index === lastToolCallIndex) {
+          // Check if there's a tool_response for this tool call
+          const hasResponse = messages
+            .slice(index + 1)
+            .some(
+              (msg) =>
+                msg.type === "tool_response" && msg.toolId === message.toolId,
+            );
+          return !hasResponse;
+        }
+        return false;
+      })();
+
     return (
       <div className={cn("px-4 py-2", className)}>
-        <ToolCallMessage toolName={message.toolName} />
+        <ToolCallMessage
+          toolId={message.toolId}
+          toolName={message.toolName}
+          arguments={message.arguments}
+          isStreaming={isToolCallStreaming}
+        />
       </div>
     );
   }
@@ -218,27 +272,11 @@ export function ChatMessage({
 
   // Render tool response messages (but skip agent_output if it's being rendered inside assistant message)
   if (isToolResponse && message.type === "tool_response") {
-    // Check if this is an agent_output that should be rendered inside assistant message
-    if (message.result) {
-      let parsedResult: Record<string, unknown> | null = null;
-      try {
-        parsedResult =
-          typeof message.result === "string"
-            ? JSON.parse(message.result)
-            : (message.result as Record<string, unknown>);
-      } catch {
-        parsedResult = null;
-      }
-      if (parsedResult?.type === "agent_output") {
-        // Skip rendering - this will be rendered inside the assistant message
-        return null;
-      }
-    }
-
     return (
       <div className={cn("px-4 py-2", className)}>
         <ToolResponseMessage
-          toolName={getToolActionPhrase(message.toolName)}
+          toolId={message.toolId}
+          toolName={message.toolName}
           result={message.result}
         />
       </div>
@@ -256,40 +294,33 @@ export function ChatMessage({
         )}
       >
         <div className="flex w-full max-w-3xl gap-3">
-          {!isUser && (
-            <div className="flex-shrink-0">
-              <div className="flex h-7 w-7 items-center justify-center rounded-lg bg-indigo-500">
-                <RobotIcon className="h-4 w-4 text-indigo-50" />
-              </div>
-            </div>
-          )}
-
           <div
             className={cn(
               "flex min-w-0 flex-1 flex-col",
               isUser && "items-end",
             )}
           >
-            <MessageBubble variant={isUser ? "user" : "assistant"}>
+            {isUser ? (
-              <MarkdownContent content={message.content} />
+              <UserChatBubble>
-              {agentOutput &&
+                <MarkdownContent content={displayContent} />
-                agentOutput.type === "tool_response" &&
+              </UserChatBubble>
-                !isUser && (
+            ) : (
+              <AIChatBubble>
+                <MarkdownContent content={displayContent} />
+                {agentOutput && agentOutput.type === "tool_response" && (
                   <div className="mt-4">
                     <ToolResponseMessage
-                      toolName={
+                      toolId={agentOutput.toolId}
-                        agentOutput.toolName
+                      toolName={agentOutput.toolName || "Agent Output"}
-                          ? getToolActionPhrase(agentOutput.toolName)
-                          : "Agent Output"
-                      }
                       result={agentOutput.result}
                     />
                   </div>
                 )}
-            </MessageBubble>
+              </AIChatBubble>
+            )}
             <div
               className={cn(
-                "mt-1 flex gap-1",
+                "flex gap-0",
                 isUser ? "justify-end" : "justify-start",
               )}
             >
@@ -300,37 +331,25 @@ export function ChatMessage({
                   onClick={handleTryAgain}
                   aria-label="Try again"
                 >
-                  <ArrowClockwise className="size-3 text-neutral-500" />
+                  <ArrowsClockwiseIcon className="size-4 text-zinc-600" />
+                </Button>
+              )}
+              {!isUser && isFinalMessage && isLongResponse(displayContent) && (
+                <Button
+                  variant="ghost"
+                  size="icon"
+                  onClick={handleCopy}
+                  aria-label="Copy message"
+                >
+                  {copied ? (
+                    <CheckIcon className="size-4 text-green-600" />
+                  ) : (
+                    <CopyIcon className="size-4 text-zinc-600" />
+                  )}
                 </Button>
               )}
-              <Button
-                variant="ghost"
-                size="icon"
-                onClick={handleCopy}
-                aria-label="Copy message"
-              >
-                {copied ? (
-                  <CheckIcon className="size-3 text-green-600" />
-                ) : (
-                  <CopyIcon className="size-3 text-neutral-500" />
-                )}
-              </Button>
             </div>
           </div>
-
-          {isUser && (
-            <div className="flex-shrink-0">
-              <Avatar className="h-7 w-7">
-                <AvatarImage
-                  src={profile?.avatar_url ?? ""}
-                  alt={profile?.username ?? "User"}
-                />
-                <AvatarFallback className="rounded-lg bg-neutral-200 text-neutral-600">
-                  {profile?.username?.charAt(0)?.toUpperCase() || "U"}
-                </AvatarFallback>
-              </Avatar>
-            </div>
-          )}
         </div>
       </div>
     );

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

@@ -13,10 +13,9 @@ export function MessageBubble({
   className,
 }: MessageBubbleProps) {
   const userTheme = {
-    bg: "bg-slate-900",
+    bg: "bg-purple-100",
-    border: "border-slate-800",
+    border: "border-purple-100",
-    gradient: "from-slate-900/30 via-slate-800/20 to-transparent",
+    text: "text-slate-900",
-    text: "text-slate-50",
   };
 
   const assistantTheme = {
@@ -40,9 +39,7 @@ export function MessageBubble({
       )}
     >
       {/* Gradient flare background */}
-      <div
+      <div className={cn("absolute inset-0 bg-gradient-to-br")} />
-        className={cn("absolute inset-0 bg-gradient-to-br", theme.gradient)}
-      />
       <div
         className={cn(
           "relative z-10 transition-all duration-500 ease-in-out",

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

@@ -0,0 +1,119 @@
+"use client";
+
+import { cn } from "@/lib/utils";
+import type { ChatMessageData } from "../ChatMessage/useChatMessage";
+import { StreamingMessage } from "../StreamingMessage/StreamingMessage";
+import { ThinkingMessage } from "../ThinkingMessage/ThinkingMessage";
+import { LastToolResponse } from "./components/LastToolResponse/LastToolResponse";
+import { MessageItem } from "./components/MessageItem/MessageItem";
+import { findLastMessageIndex, shouldSkipAgentOutput } from "./helpers";
+import { useMessageList } from "./useMessageList";
+
+export interface MessageListProps {
+  messages: ChatMessageData[];
+  streamingChunks?: string[];
+  isStreaming?: boolean;
+  className?: string;
+  onStreamComplete?: () => void;
+  onSendMessage?: (content: string) => void;
+}
+
+export function MessageList({
+  messages,
+  streamingChunks = [],
+  isStreaming = false,
+  className,
+  onStreamComplete,
+  onSendMessage,
+}: MessageListProps) {
+  const { messagesEndRef, messagesContainerRef } = useMessageList({
+    messageCount: messages.length,
+    isStreaming,
+  });
+
+  /**
+   * Keeps this for debugging purposes 💆🏽
+   */
+  console.log(messages);
+
+  return (
+    <div className="relative flex min-h-0 flex-1 flex-col">
+      {/* Top fade shadow */}
+      <div className="pointer-events-none absolute top-0 z-10 h-8 w-full bg-gradient-to-b from-[#f8f8f9] to-transparent" />
+
+      <div
+        ref={messagesContainerRef}
+        className={cn(
+          "flex-1 overflow-y-auto overflow-x-hidden",
+          "scrollbar-thin scrollbar-track-transparent scrollbar-thumb-zinc-300",
+          className,
+        )}
+      >
+        <div className="mx-auto flex min-w-0 flex-col hyphens-auto break-words py-4">
+          {/* Render all persisted messages */}
+          {(() => {
+            const lastAssistantMessageIndex = findLastMessageIndex(
+              messages,
+              (msg) => msg.type === "message" && msg.role === "assistant",
+            );
+
+            const lastToolResponseIndex = findLastMessageIndex(
+              messages,
+              (msg) => msg.type === "tool_response",
+            );
+
+            return messages.map((message, index) => {
+              // Skip agent_output tool_responses that should be rendered inside assistant messages
+              if (shouldSkipAgentOutput(message, messages[index - 1])) {
+                return null;
+              }
+
+              // Render last tool_response as AIChatBubble
+              if (
+                message.type === "tool_response" &&
+                index === lastToolResponseIndex
+              ) {
+                return (
+                  <LastToolResponse
+                    key={index}
+                    message={message}
+                    prevMessage={messages[index - 1]}
+                  />
+                );
+              }
+
+              return (
+                <MessageItem
+                  key={index}
+                  message={message}
+                  messages={messages}
+                  index={index}
+                  lastAssistantMessageIndex={lastAssistantMessageIndex}
+                  isStreaming={isStreaming}
+                  onSendMessage={onSendMessage}
+                />
+              );
+            });
+          })()}
+
+          {/* Render thinking message when streaming but no chunks yet */}
+          {isStreaming && streamingChunks.length === 0 && <ThinkingMessage />}
+
+          {/* Render streaming message if active */}
+          {isStreaming && streamingChunks.length > 0 && (
+            <StreamingMessage
+              chunks={streamingChunks}
+              onComplete={onStreamComplete}
+            />
+          )}
+
+          {/* Invisible div to scroll to */}
+          <div ref={messagesEndRef} />
+        </div>
+      </div>
+
+      {/* Bottom fade shadow */}
+      <div className="pointer-events-none absolute bottom-0 z-10 h-8 w-full bg-gradient-to-t from-[#f8f8f9] to-transparent" />
+    </div>
+  );
+}

autogpt_platform/frontend/src/components/contextual/Chat/components/MessageList/components/LastToolResponse/LastToolResponse.tsx

@@ -0,0 +1,30 @@
+import { AIChatBubble } from "../../../AIChatBubble/AIChatBubble";
+import type { ChatMessageData } from "../../../ChatMessage/useChatMessage";
+import { MarkdownContent } from "../../../MarkdownContent/MarkdownContent";
+import { formatToolResponse } from "../../../ToolResponseMessage/helpers";
+import { shouldSkipAgentOutput } from "../../helpers";
+
+export interface LastToolResponseProps {
+  message: ChatMessageData;
+  prevMessage: ChatMessageData | undefined;
+}
+
+export function LastToolResponse({
+  message,
+  prevMessage,
+}: LastToolResponseProps) {
+  if (message.type !== "tool_response") return null;
+
+  // Skip if this is an agent_output that should be rendered inside assistant message
+  if (shouldSkipAgentOutput(message, prevMessage)) return null;
+
+  const formattedText = formatToolResponse(message.result, message.toolName);
+
+  return (
+    <div className="min-w-0 overflow-x-hidden hyphens-auto break-words px-4 py-2">
+      <AIChatBubble>
+        <MarkdownContent content={formattedText} />
+      </AIChatBubble>
+    </div>
+  );
+}

autogpt_platform/frontend/src/components/contextual/Chat/components/MessageList/components/MessageItem/MessageItem.tsx

@@ -0,0 +1,40 @@
+import { ChatMessage } from "../../../ChatMessage/ChatMessage";
+import type { ChatMessageData } from "../../../ChatMessage/useChatMessage";
+import { useMessageItem } from "./useMessageItem";
+
+export interface MessageItemProps {
+  message: ChatMessageData;
+  messages: ChatMessageData[];
+  index: number;
+  lastAssistantMessageIndex: number;
+  isStreaming?: boolean;
+  onSendMessage?: (content: string) => void;
+}
+
+export function MessageItem({
+  message,
+  messages,
+  index,
+  lastAssistantMessageIndex,
+  isStreaming = false,
+  onSendMessage,
+}: MessageItemProps) {
+  const { messageToRender, agentOutput, isFinalMessage } = useMessageItem({
+    message,
+    messages,
+    index,
+    lastAssistantMessageIndex,
+  });
+
+  return (
+    <ChatMessage
+      message={messageToRender}
+      messages={messages}
+      index={index}
+      isStreaming={isStreaming}
+      onSendMessage={onSendMessage}
+      agentOutput={agentOutput}
+      isFinalMessage={isFinalMessage}
+    />
+  );
+}

autogpt_platform/frontend/src/components/contextual/Chat/components/MessageList/components/MessageItem/useMessageItem.ts

@@ -0,0 +1,62 @@
+import type { ChatMessageData } from "../../../ChatMessage/useChatMessage";
+import { isAgentOutputResult, isToolOutputPattern } from "../../helpers";
+
+export interface UseMessageItemArgs {
+  message: ChatMessageData;
+  messages: ChatMessageData[];
+  index: number;
+  lastAssistantMessageIndex: number;
+}
+
+export function useMessageItem({
+  message,
+  messages,
+  index,
+  lastAssistantMessageIndex,
+}: UseMessageItemArgs) {
+  let agentOutput: ChatMessageData | undefined;
+  let messageToRender: ChatMessageData = message;
+
+  // Check if assistant message follows a tool_call and looks like a tool output
+  if (message.type === "message" && message.role === "assistant") {
+    const prevMessage = messages[index - 1];
+
+    // Check if next message is an agent_output tool_response to include in current assistant message
+    const nextMessage = messages[index + 1];
+    if (
+      nextMessage &&
+      nextMessage.type === "tool_response" &&
+      nextMessage.result
+    ) {
+      if (isAgentOutputResult(nextMessage.result)) {
+        agentOutput = nextMessage;
+      }
+    }
+
+    // Only convert to tool_response if it follows a tool_call AND looks like a tool output
+    if (prevMessage && prevMessage.type === "tool_call") {
+      if (isToolOutputPattern(message.content)) {
+        // Convert this message to a tool_response format for rendering
+        messageToRender = {
+          type: "tool_response",
+          toolId: prevMessage.toolId,
+          toolName: prevMessage.toolName,
+          result: message.content,
+          success: true,
+          timestamp: message.timestamp,
+        } as ChatMessageData;
+      }
+    }
+  }
+
+  const isFinalMessage =
+    messageToRender.type !== "message" ||
+    messageToRender.role !== "assistant" ||
+    index === lastAssistantMessageIndex;
+
+  return {
+    messageToRender,
+    agentOutput,
+    isFinalMessage,
+  };
+}

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

@@ -0,0 +1,68 @@
+import type { ChatMessageData } from "../ChatMessage/useChatMessage";
+
+export function parseToolResult(
+  result: unknown,
+): Record<string, unknown> | null {
+  try {
+    return typeof result === "string"
+      ? JSON.parse(result)
+      : (result as Record<string, unknown>);
+  } catch {
+    return null;
+  }
+}
+
+export function isAgentOutputResult(result: unknown): boolean {
+  const parsed = parseToolResult(result);
+  return parsed?.type === "agent_output";
+}
+
+export function isToolOutputPattern(content: string): boolean {
+  const normalizedContent = content.toLowerCase().trim();
+
+  return (
+    normalizedContent.startsWith("no agents found") ||
+    normalizedContent.startsWith("no results found") ||
+    normalizedContent.includes("no agents found matching") ||
+    !!normalizedContent.match(/^no \w+ found/i) ||
+    (content.length < 150 && normalizedContent.includes("try different")) ||
+    (content.length < 200 &&
+      !normalizedContent.includes("i'll") &&
+      !normalizedContent.includes("let me") &&
+      !normalizedContent.includes("i can") &&
+      !normalizedContent.includes("i will"))
+  );
+}
+
+export function formatToolResultValue(result: unknown): string {
+  return typeof result === "string"
+    ? result
+    : result
+      ? JSON.stringify(result, null, 2)
+      : "";
+}
+
+export function findLastMessageIndex(
+  messages: ChatMessageData[],
+  predicate: (msg: ChatMessageData) => boolean,
+): number {
+  for (let i = messages.length - 1; i >= 0; i--) {
+    if (predicate(messages[i])) return i;
+  }
+  return -1;
+}
+
+export function shouldSkipAgentOutput(
+  message: ChatMessageData,
+  prevMessage: ChatMessageData | undefined,
+): boolean {
+  if (message.type !== "tool_response" || !message.result) return false;
+
+  const isAgentOutput = isAgentOutputResult(message.result);
+  return (
+    isAgentOutput &&
+    !!prevMessage &&
+    prevMessage.type === "message" &&
+    prevMessage.role === "assistant"
+  );
+}

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

@@ -81,9 +81,9 @@ export function SessionsDrawer({
                 </Text>
               </div>
             ) : sessions.length === 0 ? (
-              <div className="flex items-center justify-center py-8">
+              <div className="flex h-full items-center justify-center">
                 <Text variant="body" className="text-zinc-500">
-                  No sessions found
+                  You don&apos;t have previously started chats
                 </Text>
               </div>
             ) : (

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

@@ -1,7 +1,6 @@
 import { cn } from "@/lib/utils";
-import { RobotIcon } from "@phosphor-icons/react";
+import { AIChatBubble } from "../AIChatBubble/AIChatBubble";
 import { MarkdownContent } from "../MarkdownContent/MarkdownContent";
-import { MessageBubble } from "../MessageBubble/MessageBubble";
 import { useStreamingMessage } from "./useStreamingMessage";
 
 export interface StreamingMessageProps {
@@ -25,16 +24,10 @@ export function StreamingMessage({
       )}
     >
       <div className="flex w-full max-w-3xl gap-3">
-        <div className="flex-shrink-0">
-          <div className="flex h-7 w-7 items-center justify-center rounded-lg bg-indigo-600">
-            <RobotIcon className="h-4 w-4 text-indigo-50" />
-          </div>
-        </div>
-
         <div className="flex min-w-0 flex-1 flex-col">
-          <MessageBubble variant="assistant">
+          <AIChatBubble>
             <MarkdownContent content={displayText} />
-          </MessageBubble>
+          </AIChatBubble>
         </div>
       </div>
     </div>

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

@@ -1,7 +1,7 @@
 import { cn } from "@/lib/utils";
-import { RobotIcon } from "@phosphor-icons/react";
 import { useEffect, useRef, useState } from "react";
-import { MessageBubble } from "../MessageBubble/MessageBubble";
+import { AIChatBubble } from "../AIChatBubble/AIChatBubble";
+import { ChatLoader } from "../ChatLoader/ChatLoader";
 
 export interface ThinkingMessageProps {
   className?: string;
@@ -34,22 +34,11 @@ export function ThinkingMessage({ className }: ThinkingMessageProps) {
       )}
     >
       <div className="flex w-full max-w-3xl gap-3">
-        <div className="flex-shrink-0">
-          <div className="flex h-7 w-7 items-center justify-center rounded-lg bg-indigo-500">
-            <RobotIcon className="h-4 w-4 text-indigo-50" />
-          </div>
-        </div>
-
         <div className="flex min-w-0 flex-1 flex-col">
-          <MessageBubble variant="assistant">
+          <AIChatBubble>
             <div className="transition-all duration-500 ease-in-out">
               {showSlowLoader ? (
-                <div className="flex flex-col items-center gap-3 py-2">
+                <ChatLoader />
-                  <div className="loader" style={{ flexShrink: 0 }} />
-                  <p className="text-sm text-slate-700">
-                    Taking a bit longer to think, wait a moment please
-                  </p>
-                </div>
               ) : (
                 <span
                   className="inline-block bg-gradient-to-r from-neutral-400 via-neutral-600 to-neutral-400 bg-clip-text text-transparent"
@@ -62,7 +51,7 @@ export function ThinkingMessage({ className }: ThinkingMessageProps) {
                 </span>
               )}
             </div>
-          </MessageBubble>
+          </AIChatBubble>
         </div>
       </div>
     </div>

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

@@ -0,0 +1,55 @@
+import { Text } from "@/components/atoms/Text/Text";
+import { cn } from "@/lib/utils";
+import type { ToolArguments } from "@/types/chat";
+import { AIChatBubble } from "../AIChatBubble/AIChatBubble";
+import {
+  formatToolArguments,
+  getToolActionPhrase,
+  getToolIcon,
+} from "./helpers";
+
+export interface ToolCallMessageProps {
+  toolId?: string;
+  toolName: string;
+  arguments?: ToolArguments;
+  isStreaming?: boolean;
+  className?: string;
+}
+
+export function ToolCallMessage({
+  toolName,
+  arguments: toolArguments,
+  isStreaming = false,
+  className,
+}: ToolCallMessageProps) {
+  const actionPhrase = getToolActionPhrase(toolName);
+  const argumentsText = formatToolArguments(toolName, toolArguments);
+  const displayText = `${actionPhrase}${argumentsText}`;
+  const IconComponent = getToolIcon(toolName);
+
+  return (
+    <AIChatBubble className={className}>
+      <div className="flex items-center gap-2">
+        <IconComponent
+          size={14}
+          weight={isStreaming ? "regular" : "regular"}
+          className={cn(
+            "shrink-0",
+            isStreaming ? "text-neutral-500" : "text-neutral-400",
+          )}
+        />
+        <Text
+          variant="small"
+          className={cn(
+            "text-xs",
+            isStreaming
+              ? "bg-gradient-to-r from-neutral-600 via-neutral-500 to-neutral-600 bg-[length:200%_100%] bg-clip-text text-transparent [animation:shimmer_2s_ease-in-out_infinite]"
+              : "text-neutral-500",
+          )}
+        >
+          {displayText}
+        </Text>
+      </div>
+    </AIChatBubble>
+  );
+}

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

@@ -0,0 +1,184 @@
+import type { ToolArguments } from "@/types/chat";
+import {
+  BrainIcon,
+  EyeIcon,
+  FileMagnifyingGlassIcon,
+  FileTextIcon,
+  MagnifyingGlassIcon,
+  PackageIcon,
+  PencilLineIcon,
+  PlayIcon,
+  PlusIcon,
+  SquaresFourIcon,
+  type Icon,
+} from "@phosphor-icons/react";
+
+/**
+ * Maps internal tool names to human-friendly action phrases (present continuous).
+ * Used for tool call messages to indicate what action is currently happening.
+ *
+ * @param toolName - The internal tool name from the backend
+ * @returns A human-friendly action phrase in present continuous tense
+ */
+export function getToolActionPhrase(toolName: string): string {
+  const normalizedName = toolName.trim();
+  if (!normalizedName) return "Executing";
+  if (normalizedName.toLowerCase().startsWith("executing")) {
+    return normalizedName;
+  }
+  if (normalizedName.toLowerCase() === "unknown") return "Executing";
+  const toolActionPhrases: Record<string, string> = {
+    add_understanding: "Updating your business information",
+    create_agent: "Creating a new agent",
+    edit_agent: "Editing the agent",
+    find_agent: "Looking for agents in the marketplace",
+    find_block: "Searching for blocks",
+    find_library_agent: "Looking for library agents",
+    run_agent: "Running the agent",
+    run_block: "Running the block",
+    view_agent_output: "Retrieving agent output",
+    search_docs: "Searching documentation",
+    get_doc_page: "Loading documentation page",
+    agent_carousel: "Looking for agents in the marketplace",
+    execution_started: "Running the agent",
+    get_required_setup_info: "Getting setup requirements",
+    schedule_agent: "Scheduling the agent to run",
+  };
+
+  // Return mapped phrase or generate human-friendly fallback
+  return (
+    toolActionPhrases[toolName] ||
+    toolName
+      .replace(/_/g, " ")
+      .replace(/\b\w/g, (l) => l.toUpperCase())
+      .replace(/^/, "Executing ")
+  );
+}
+
+/**
+ * Formats tool call arguments into user-friendly text.
+ * Handles different tool types and formats their arguments nicely.
+ *
+ * @param toolName - The tool name
+ * @param args - The tool arguments
+ * @returns Formatted user-friendly text to append to action phrase
+ */
+export function formatToolArguments(
+  toolName: string,
+  args: ToolArguments | undefined,
+): string {
+  if (!args || Object.keys(args).length === 0) {
+    return "";
+  }
+
+  switch (toolName) {
+    case "find_agent":
+    case "find_library_agent":
+    case "agent_carousel":
+      if (args.query) {
+        return ` matching "${args.query as string}"`;
+      }
+      break;
+
+    case "find_block":
+      if (args.query) {
+        return ` matching "${args.query as string}"`;
+      }
+      break;
+
+    case "search_docs":
+      if (args.query) {
+        return ` for "${args.query as string}"`;
+      }
+      break;
+
+    case "get_doc_page":
+      if (args.path) {
+        return ` "${args.path as string}"`;
+      }
+      break;
+
+    case "run_agent":
+      if (args.username_agent_slug) {
+        return ` "${args.username_agent_slug as string}"`;
+      }
+      if (args.library_agent_id) {
+        return ` (library agent)`;
+      }
+      break;
+
+    case "run_block":
+      if (args.block_id) {
+        return ` "${args.block_id as string}"`;
+      }
+      break;
+
+    case "view_agent_output":
+      if (args.library_agent_id) {
+        return ` (library agent)`;
+      }
+      if (args.username_agent_slug) {
+        return ` "${args.username_agent_slug as string}"`;
+      }
+      break;
+
+    case "create_agent":
+    case "edit_agent":
+      if (args.name) {
+        return ` "${args.name as string}"`;
+      }
+      break;
+
+    case "add_understanding":
+      const understandingFields = Object.entries(args)
+        .filter(
+          ([_, value]) => value !== null && value !== undefined && value !== "",
+        )
+        .map(([key, value]) => {
+          if (key === "user_name" && typeof value === "string") {
+            return `for ${value}`;
+          }
+          if (typeof value === "string") {
+            return `${key}: ${value}`;
+          }
+          if (Array.isArray(value) && value.length > 0) {
+            return `${key}: ${value.slice(0, 2).join(", ")}${value.length > 2 ? ` (+${value.length - 2} more)` : ""}`;
+          }
+          return key;
+        });
+      if (understandingFields.length > 0) {
+        return ` ${understandingFields[0]}`;
+      }
+      break;
+  }
+
+  return "";
+}
+
+/**
+ * Maps tool names to their corresponding Phosphor icon components.
+ *
+ * @param toolName - The tool name from the backend
+ * @returns The Icon component for the tool
+ */
+export function getToolIcon(toolName: string): Icon {
+  const iconMap: Record<string, Icon> = {
+    add_understanding: BrainIcon,
+    create_agent: PlusIcon,
+    edit_agent: PencilLineIcon,
+    find_agent: SquaresFourIcon,
+    find_library_agent: MagnifyingGlassIcon,
+    find_block: PackageIcon,
+    run_agent: PlayIcon,
+    run_block: PlayIcon,
+    view_agent_output: EyeIcon,
+    search_docs: FileMagnifyingGlassIcon,
+    get_doc_page: FileTextIcon,
+    agent_carousel: MagnifyingGlassIcon,
+    execution_started: PlayIcon,
+    get_required_setup_info: SquaresFourIcon,
+    schedule_agent: PlayIcon,
+  };
+
+  return iconMap[toolName] || SquaresFourIcon;
+}

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

@@ -0,0 +1,28 @@
+import type { ToolResult } from "@/types/chat";
+import { AIChatBubble } from "../AIChatBubble/AIChatBubble";
+import { MarkdownContent } from "../MarkdownContent/MarkdownContent";
+import { formatToolResponse } from "./helpers";
+
+export interface ToolResponseMessageProps {
+  toolId?: string;
+  toolName: string;
+  result?: ToolResult;
+  success?: boolean;
+  className?: string;
+}
+
+export function ToolResponseMessage({
+  toolId: _toolId,
+  toolName,
+  result,
+  success: _success,
+  className,
+}: ToolResponseMessageProps) {
+  const formattedText = formatToolResponse(result, toolName);
+
+  return (
+    <AIChatBubble className={className}>
+      <MarkdownContent content={formattedText} />
+    </AIChatBubble>
+  );
+}

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

@@ -0,0 +1,256 @@
+function getToolCompletionPhrase(toolName: string): string {
+  const toolCompletionPhrases: Record<string, string> = {
+    add_understanding: "Updated your business information",
+    create_agent: "Created the agent",
+    edit_agent: "Updated the agent",
+    find_agent: "Found agents in the marketplace",
+    find_block: "Found blocks",
+    find_library_agent: "Found library agents",
+    run_agent: "Started agent execution",
+    run_block: "Executed the block",
+    view_agent_output: "Retrieved agent output",
+    search_docs: "Found documentation",
+    get_doc_page: "Loaded documentation page",
+  };
+
+  // Return mapped phrase or generate human-friendly fallback
+  return (
+    toolCompletionPhrases[toolName] ||
+    `Completed ${toolName.replace(/_/g, " ").replace("...", "")}`
+  );
+}
+
+export function formatToolResponse(result: unknown, toolName: string): string {
+  if (typeof result === "string") {
+    const trimmed = result.trim();
+    if (trimmed.startsWith("{") && trimmed.endsWith("}")) {
+      try {
+        const parsed = JSON.parse(trimmed);
+        return formatToolResponse(parsed, toolName);
+      } catch {
+        return trimmed;
+      }
+    }
+    return result;
+  }
+
+  if (typeof result !== "object" || result === null) {
+    return String(result);
+  }
+
+  const response = result as Record<string, unknown>;
+
+  // Handle different response types
+  const responseType = response.type as string | undefined;
+
+  if (!responseType) {
+    if (response.message) {
+      return String(response.message);
+    }
+    return getToolCompletionPhrase(toolName);
+  }
+
+  switch (responseType) {
+    case "agents_found":
+      const agents = (response.agents as Array<{ name: string }>) || [];
+      const count =
+        typeof response.count === "number" && !isNaN(response.count)
+          ? response.count
+          : agents.length;
+      if (count === 0) {
+        return "No agents found matching your search.";
+      }
+      return `Found ${count} agent${count === 1 ? "" : "s"}: ${agents
+        .slice(0, 3)
+        .map((a) => a.name)
+        .join(", ")}${count > 3 ? ` and ${count - 3} more` : ""}`;
+
+    case "agent_details":
+      const agent = response.agent as { name: string; description?: string };
+      if (agent) {
+        return `Agent: ${agent.name}${agent.description ? `\n\n${agent.description}` : ""}`;
+      }
+      break;
+
+    case "block_list":
+      const blocks = (response.blocks as Array<{ name: string }>) || [];
+      const blockCount =
+        typeof response.count === "number" && !isNaN(response.count)
+          ? response.count
+          : blocks.length;
+      if (blockCount === 0) {
+        return "No blocks found matching your search.";
+      }
+      return `Found ${blockCount} block${blockCount === 1 ? "" : "s"}: ${blocks
+        .slice(0, 3)
+        .map((b) => b.name)
+        .join(", ")}${blockCount > 3 ? ` and ${blockCount - 3} more` : ""}`;
+
+    case "block_output":
+      const blockName = (response.block_name as string) || "Block";
+      const outputs = response.outputs as Record<string, unknown> | undefined;
+      if (outputs && Object.keys(outputs).length > 0) {
+        const outputKeys = Object.keys(outputs);
+        return `${blockName} executed successfully. Outputs: ${outputKeys.join(", ")}`;
+      }
+      return `${blockName} executed successfully.`;
+
+    case "doc_search_results":
+      const docResults = (response.results as Array<{ title: string }>) || [];
+      const docCount =
+        typeof response.count === "number" && !isNaN(response.count)
+          ? response.count
+          : docResults.length;
+      if (docCount === 0) {
+        return "No documentation found matching your search.";
+      }
+      return `Found ${docCount} documentation result${docCount === 1 ? "" : "s"}: ${docResults
+        .slice(0, 3)
+        .map((r) => r.title)
+        .join(", ")}${docCount > 3 ? ` and ${docCount - 3} more` : ""}`;
+
+    case "doc_page":
+      const title = (response.title as string) || "Documentation";
+      const content = (response.content as string) || "";
+      if (content) {
+        const preview = content.substring(0, 200).trim();
+        return `${title}\n\n${preview}${content.length > 200 ? "..." : ""}`;
+      }
+      return title;
+
+    case "understanding_updated":
+      const currentUnderstanding = response.current_understanding as
+        | Record<string, unknown>
+        | undefined;
+      const fields = (response.updated_fields as string[]) || [];
+
+      if (response.message && typeof response.message === "string") {
+        let message = response.message;
+        if (currentUnderstanding) {
+          for (const [key, value] of Object.entries(currentUnderstanding)) {
+            if (value !== null && value !== undefined && value !== "") {
+              const placeholder = key;
+              const actualValue = String(value);
+              message = message.replace(
+                new RegExp(`\\b${placeholder}\\b`, "g"),
+                actualValue,
+              );
+            }
+          }
+        }
+        return message;
+      }
+
+      if (
+        currentUnderstanding &&
+        Object.keys(currentUnderstanding).length > 0
+      ) {
+        const understandingEntries = Object.entries(currentUnderstanding)
+          .filter(
+            ([_, value]) =>
+              value !== null && value !== undefined && value !== "",
+          )
+          .map(([key, value]) => {
+            if (key === "user_name" && typeof value === "string") {
+              return `Updated information for ${value}`;
+            }
+            return `${key}: ${String(value)}`;
+          });
+        if (understandingEntries.length > 0) {
+          return understandingEntries[0];
+        }
+      }
+      if (fields.length > 0) {
+        return `Updated business information: ${fields.join(", ")}`;
+      }
+      return "Updated your business information.";
+
+    case "agent_saved":
+      const agentName = (response.agent_name as string) || "Agent";
+      return `Successfully saved "${agentName}" to your library.`;
+
+    case "agent_preview":
+      const previewAgentName = (response.agent_name as string) || "Agent";
+      const nodeCount = (response.node_count as number) || 0;
+      const linkCount = (response.link_count as number) || 0;
+      const description = (response.description as string) || "";
+      let previewText = `Preview: "${previewAgentName}"`;
+      if (description) {
+        previewText += `\n\n${description}`;
+      }
+      previewText += `\n\n${nodeCount} node${nodeCount === 1 ? "" : "s"}, ${linkCount} link${linkCount === 1 ? "" : "s"}`;
+      return previewText;
+
+    case "clarification_needed":
+      const questions =
+        (response.questions as Array<{ question: string }>) || [];
+      if (questions.length === 0) {
+        return response.message
+          ? String(response.message)
+          : "I need more information to proceed.";
+      }
+      if (questions.length === 1) {
+        return questions[0].question;
+      }
+      return `I need clarification on ${questions.length} points:\n\n${questions
+        .map((q, i) => `${i + 1}. ${q.question}`)
+        .join("\n")}`;
+
+    case "agent_output":
+      if (response.message) {
+        return String(response.message);
+      }
+      const outputAgentName = (response.agent_name as string) || "Agent";
+      const execution = response.execution as
+        | {
+            status?: string;
+            outputs?: Record<string, unknown>;
+          }
+        | undefined;
+      if (execution) {
+        const status = execution.status || "completed";
+        const outputs = execution.outputs || {};
+        const outputKeys = Object.keys(outputs);
+        if (outputKeys.length > 0) {
+          return `${outputAgentName} execution ${status}. Outputs: ${outputKeys.join(", ")}`;
+        }
+        return `${outputAgentName} execution ${status}.`;
+      }
+      return `${outputAgentName} output retrieved.`;
+
+    case "execution_started":
+      const execAgentName = (response.graph_name as string) || "Agent";
+      if (response.message) {
+        return String(response.message);
+      }
+      return `Started execution of "${execAgentName}".`;
+
+    case "error":
+      const errorMsg =
+        (response.error as string) || response.message || "An error occurred";
+      return `Error: ${errorMsg}`;
+
+    case "no_results":
+      const suggestions = (response.suggestions as string[]) || [];
+      let noResultsText = (response.message as string) || "No results found.";
+      if (suggestions.length > 0) {
+        noResultsText += `\n\nSuggestions: ${suggestions.join(", ")}`;
+      }
+      return noResultsText;
+
+    default:
+      // Try to extract a message field
+      if (response.message) {
+        return String(response.message);
+      }
+      // Fallback: try to stringify nicely
+      if (Object.keys(response).length === 0) {
+        return getToolCompletionPhrase(toolName);
+      }
+      // If we have a response object but no recognized type, try to format it nicely
+      // Don't return raw JSON - return a completion phrase instead
+      return getToolCompletionPhrase(toolName);
+  }
+
+  return getToolCompletionPhrase(toolName);
+}

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

@@ -0,0 +1,25 @@
+import { cn } from "@/lib/utils";
+import { ReactNode } from "react";
+
+export interface UserChatBubbleProps {
+  children: ReactNode;
+  className?: string;
+}
+
+export function UserChatBubble({ children, className }: UserChatBubbleProps) {
+  return (
+    <div
+      className={cn(
+        "group relative min-w-20 overflow-hidden rounded-xl bg-purple-100 px-3 text-right text-[1rem] leading-relaxed transition-all duration-500 ease-in-out",
+        className,
+      )}
+      style={{
+        borderBottomRightRadius: 0,
+      }}
+    >
+      <div className="relative z-10 text-slate-900 transition-all duration-500 ease-in-out">
+        {children}
+      </div>
+    </div>
+  );
+}