fix(platform/copilot): add SuggestedGoalResponse to ToolResponseUnion for OpenAPI schema

Adds SuggestedGoalResponse to the ToolResponseUnion in routes.py so it is
included in the generated OpenAPI schema. Regenerates openapi.json from the
live backend spec.

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

@@ -41,18 +41,13 @@ jobs:
         ports:
           - 6379:6379
       rabbitmq:
-        image: rabbitmq:4.1.4
+        image: rabbitmq:3.12-management
         ports:
           - 5672:5672
+          - 15672:15672
         env:
           RABBITMQ_DEFAULT_USER: ${{ env.RABBITMQ_DEFAULT_USER }}
           RABBITMQ_DEFAULT_PASS: ${{ env.RABBITMQ_DEFAULT_PASS }}
-        options: >-
-          --health-cmd "rabbitmq-diagnostics -q ping"
-          --health-interval 30s
-          --health-timeout 10s
-          --health-retries 5
-          --health-start-period 10s
       clamav:
         image: clamav/clamav-debian:latest
         ports:

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

@@ -6,16 +6,10 @@ on:
     paths:
       - ".github/workflows/platform-frontend-ci.yml"
       - "autogpt_platform/frontend/**"
-      - "autogpt_platform/backend/Dockerfile"
-      - "autogpt_platform/docker-compose.yml"
-      - "autogpt_platform/docker-compose.platform.yml"
   pull_request:
     paths:
       - ".github/workflows/platform-frontend-ci.yml"
       - "autogpt_platform/frontend/**"
-      - "autogpt_platform/backend/Dockerfile"
-      - "autogpt_platform/docker-compose.yml"
-      - "autogpt_platform/docker-compose.platform.yml"
   merge_group:
   workflow_dispatch:
 

autogpt_platform/backend/Dockerfile

@@ -53,6 +53,63 @@ COPY autogpt_platform/backend/backend/data/partial_types.py ./backend/data/parti
 COPY autogpt_platform/backend/gen_prisma_types_stub.py ./
 RUN poetry run prisma generate && poetry run gen-prisma-stub
 
+# ============================== BACKEND SERVER ============================== #
+
+FROM debian:13-slim AS server
+
+WORKDIR /app
+
+ENV POETRY_HOME=/opt/poetry \
+    POETRY_NO_INTERACTION=1 \
+    POETRY_VIRTUALENVS_CREATE=true \
+    POETRY_VIRTUALENVS_IN_PROJECT=true \
+    DEBIAN_FRONTEND=noninteractive
+ENV PATH=/opt/poetry/bin:$PATH
+
+# Install Python, FFmpeg, ImageMagick, and CLI tools for agent use.
+# bubblewrap provides OS-level sandbox (whitelist-only FS + no network)
+# for the bash_exec MCP tool.
+# Using --no-install-recommends saves ~650MB by skipping unnecessary deps like llvm, mesa, etc.
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    python3.13 \
+    python3-pip \
+    ffmpeg \
+    imagemagick \
+    jq \
+    ripgrep \
+    tree \
+    bubblewrap \
+    && rm -rf /var/lib/apt/lists/*
+
+COPY --from=builder /usr/local/lib/python3* /usr/local/lib/python3*
+COPY --from=builder /usr/local/bin/poetry /usr/local/bin/poetry
+# Copy Node.js installation for Prisma
+COPY --from=builder /usr/bin/node /usr/bin/node
+COPY --from=builder /usr/lib/node_modules /usr/lib/node_modules
+COPY --from=builder /usr/bin/npm /usr/bin/npm
+COPY --from=builder /usr/bin/npx /usr/bin/npx
+COPY --from=builder /root/.cache/prisma-python/binaries /root/.cache/prisma-python/binaries
+
+WORKDIR /app/autogpt_platform/backend
+
+# Copy only the .venv from builder (not the entire /app directory)
+# The .venv includes the generated Prisma client
+COPY --from=builder /app/autogpt_platform/backend/.venv ./.venv
+ENV PATH="/app/autogpt_platform/backend/.venv/bin:$PATH"
+
+# Copy dependency files + autogpt_libs (path dependency)
+COPY autogpt_platform/autogpt_libs /app/autogpt_platform/autogpt_libs
+COPY autogpt_platform/backend/poetry.lock autogpt_platform/backend/pyproject.toml ./
+
+# Copy backend code + docs (for Copilot docs search)
+COPY autogpt_platform/backend ./
+COPY docs /app/docs
+RUN poetry install --no-ansi --only-root
+
+ENV PORT=8000
+
+CMD ["poetry", "run", "rest"]
+
 # =============================== DB MIGRATOR =============================== #
 
 # Lightweight migrate stage - only needs Prisma CLI, not full Python environment
@@ -84,59 +141,3 @@ COPY autogpt_platform/backend/schema.prisma ./
 COPY autogpt_platform/backend/backend/data/partial_types.py ./backend/data/partial_types.py
 COPY autogpt_platform/backend/gen_prisma_types_stub.py ./
 COPY autogpt_platform/backend/migrations ./migrations
-
-# ============================== BACKEND SERVER ============================== #
-
-FROM debian:13-slim AS server
-
-WORKDIR /app
-
-ENV DEBIAN_FRONTEND=noninteractive
-
-# Install Python, FFmpeg, ImageMagick, and CLI tools for agent use.
-# bubblewrap provides OS-level sandbox (whitelist-only FS + no network)
-# for the bash_exec MCP tool.
-# Using --no-install-recommends saves ~650MB by skipping unnecessary deps like llvm, mesa, etc.
-RUN apt-get update && apt-get install -y --no-install-recommends \
-    python3.13 \
-    python3-pip \
-    ffmpeg \
-    imagemagick \
-    jq \
-    ripgrep \
-    tree \
-    bubblewrap \
-    && rm -rf /var/lib/apt/lists/*
-
-# Copy poetry (build-time only, for `poetry install --only-root` to create entry points)
-COPY --from=builder /usr/local/lib/python3* /usr/local/lib/python3*
-COPY --from=builder /usr/local/bin/poetry /usr/local/bin/poetry
-# Copy Node.js installation for Prisma
-COPY --from=builder /usr/bin/node /usr/bin/node
-COPY --from=builder /usr/lib/node_modules /usr/lib/node_modules
-COPY --from=builder /usr/bin/npm /usr/bin/npm
-COPY --from=builder /usr/bin/npx /usr/bin/npx
-COPY --from=builder /root/.cache/prisma-python/binaries /root/.cache/prisma-python/binaries
-
-WORKDIR /app/autogpt_platform/backend
-
-# Copy only the .venv from builder (not the entire /app directory)
-# The .venv includes the generated Prisma client
-COPY --from=builder /app/autogpt_platform/backend/.venv ./.venv
-ENV PATH="/app/autogpt_platform/backend/.venv/bin:$PATH"
-
-# Copy dependency files + autogpt_libs (path dependency)
-COPY autogpt_platform/autogpt_libs /app/autogpt_platform/autogpt_libs
-COPY autogpt_platform/backend/poetry.lock autogpt_platform/backend/pyproject.toml ./
-
-# Copy backend code + docs (for Copilot docs search)
-COPY autogpt_platform/backend ./
-COPY docs /app/docs
-# Install the project package to create entry point scripts in .venv/bin/
-# (e.g., rest, executor, ws, db, scheduler, notification - see [tool.poetry.scripts])
-RUN POETRY_VIRTUALENVS_CREATE=true POETRY_VIRTUALENVS_IN_PROJECT=true \
-    poetry install --no-ansi --only-root
-
-ENV PORT=8000
-
-CMD ["rest"]

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

@@ -23,7 +23,6 @@ from .model import (
     ChatSession,
     append_and_save_message,
     create_chat_session,
-    delete_chat_session,
     get_chat_session,
     get_user_sessions,
 )
@@ -50,6 +49,7 @@ from .tools.models import (
     OperationPendingResponse,
     OperationStartedResponse,
     SetupRequirementsResponse,
+    SuggestedGoalResponse,
     UnderstandingUpdatedResponse,
 )
 from .tracking import track_user_message
@@ -212,43 +212,6 @@ async def create_session(
     )
 
 
-@router.delete(
-    "/sessions/{session_id}",
-    dependencies=[Security(auth.requires_user)],
-    status_code=204,
-    responses={404: {"description": "Session not found or access denied"}},
-)
-async def delete_session(
-    session_id: str,
-    user_id: Annotated[str, Security(auth.get_user_id)],
-) -> Response:
-    """
-    Delete a chat session.
-
-    Permanently removes a chat session and all its messages.
-    Only the owner can delete their sessions.
-
-    Args:
-        session_id: The session ID to delete.
-        user_id: The authenticated user's ID.
-
-    Returns:
-        204 No Content on success.
-
-    Raises:
-        HTTPException: 404 if session not found or not owned by user.
-    """
-    deleted = await delete_chat_session(session_id, user_id)
-
-    if not deleted:
-        raise HTTPException(
-            status_code=404,
-            detail=f"Session {session_id} not found or access denied",
-        )
-
-    return Response(status_code=204)
-
-
 @router.get(
     "/sessions/{session_id}",
 )
@@ -1089,6 +1052,7 @@ ToolResponseUnion = (
     | AgentPreviewResponse
     | AgentSavedResponse
     | ClarificationNeededResponse
+    | SuggestedGoalResponse
     | BlockListResponse
     | BlockDetailsResponse
     | BlockOutputResponse

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

@@ -120,6 +120,8 @@ Adapt flexibly to the conversation context. Not every interaction requires all s
    - Find reusable components with `find_block`
    - Create custom solutions with `create_agent` if nothing suitable exists
    - Modify existing library agents with `edit_agent`
+   - **When `create_agent` returns `suggested_goal`**: Present the suggestion to the user and ask "Would you like me to proceed with this refined goal?" If they accept, call `create_agent` again with the suggested goal.
+   - **When `create_agent` returns `clarifying_questions`**: After the user answers, call `create_agent` again with the original description AND the answers in the `context` parameter.
 
 5. **Execute**: Run automations immediately, schedule them, or set up webhooks using `run_agent`. Test specific components with `run_block`.
 
@@ -166,6 +168,11 @@ Adapt flexibly to the conversation context. Not every interaction requires all s
 - Use `add_understanding` to capture valuable business context
 - When tool calls fail, try alternative approaches
 
+**Handle Feedback Loops:**
+- When a tool returns a suggested alternative (like a refined goal), present it clearly and ask the user for confirmation before proceeding
+- When clarifying questions are answered, immediately re-call the tool with the accumulated context
+- Don't ask redundant questions if the user has already provided context in the conversation
+
 ## CRITICAL REMINDER
 
 You are NOT a chatbot. You are NOT documentation. You are a partner who helps busy business owners get value quickly by showing proof through working automations. Bias toward action over explanation."""

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

@@ -22,6 +22,7 @@ from .models import (
     ClarificationNeededResponse,
     ClarifyingQuestion,
     ErrorResponse,
+    SuggestedGoalResponse,
     ToolResponseBase,
 )
 
@@ -186,26 +187,25 @@ class CreateAgentTool(BaseTool):
         if decomposition_result.get("type") == "unachievable_goal":
             suggested = decomposition_result.get("suggested_goal", "")
             reason = decomposition_result.get("reason", "")
-            return ErrorResponse(
+            return SuggestedGoalResponse(
                 message=(
-                    f"This goal cannot be accomplished with the available blocks. "
-                    f"{reason} "
-                    f"Suggestion: {suggested}"
+                    f"This goal cannot be accomplished with the available blocks. {reason}"
                 ),
-                error="unachievable_goal",
-                details={"suggested_goal": suggested, "reason": reason},
+                suggested_goal=suggested,
+                reason=reason,
+                original_goal=description,
+                goal_type="unachievable",
                 session_id=session_id,
             )
 
         if decomposition_result.get("type") == "vague_goal":
             suggested = decomposition_result.get("suggested_goal", "")
-            return ErrorResponse(
-                message=(
-                    f"The goal is too vague to create a specific workflow. "
-                    f"Suggestion: {suggested}"
-                ),
-                error="vague_goal",
-                details={"suggested_goal": suggested},
+            return SuggestedGoalResponse(
+                message="The goal is too vague to create a specific workflow.",
+                suggested_goal=suggested,
+                reason="The goal needs more specific details",
+                original_goal=description,
+                goal_type="vague",
                 session_id=session_id,
             )
 

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

@@ -0,0 +1,142 @@
+"""Tests for CreateAgentTool response types."""
+
+from unittest.mock import AsyncMock, patch
+
+import pytest
+
+from backend.api.features.chat.tools.create_agent import CreateAgentTool
+from backend.api.features.chat.tools.models import (
+    ClarificationNeededResponse,
+    ErrorResponse,
+    SuggestedGoalResponse,
+)
+
+from ._test_data import make_session
+
+_TEST_USER_ID = "test-user-create-agent"
+
+
+@pytest.fixture
+def tool():
+    return CreateAgentTool()
+
+
+@pytest.fixture
+def session():
+    return make_session(_TEST_USER_ID)
+
+
+@pytest.mark.asyncio
+async def test_missing_description_returns_error(tool, session):
+    """Missing description returns ErrorResponse."""
+    result = await tool._execute(user_id=_TEST_USER_ID, session=session, description="")
+    assert isinstance(result, ErrorResponse)
+    assert result.error == "Missing description parameter"
+
+
+@pytest.mark.asyncio
+async def test_vague_goal_returns_suggested_goal_response(tool, session):
+    """vague_goal decomposition result returns SuggestedGoalResponse, not ErrorResponse."""
+    vague_result = {
+        "type": "vague_goal",
+        "suggested_goal": "Monitor Twitter mentions for a specific keyword and send a daily digest email",
+    }
+
+    with (
+        patch(
+            "backend.api.features.chat.tools.create_agent.get_all_relevant_agents_for_generation",
+            new_callable=AsyncMock,
+            return_value=[],
+        ),
+        patch(
+            "backend.api.features.chat.tools.create_agent.decompose_goal",
+            new_callable=AsyncMock,
+            return_value=vague_result,
+        ),
+    ):
+        result = await tool._execute(
+            user_id=_TEST_USER_ID,
+            session=session,
+            description="monitor social media",
+        )
+
+    assert isinstance(result, SuggestedGoalResponse)
+    assert result.goal_type == "vague"
+    assert result.suggested_goal == vague_result["suggested_goal"]
+    assert result.original_goal == "monitor social media"
+    assert result.reason == "The goal needs more specific details"
+    assert not isinstance(result, ErrorResponse)
+
+
+@pytest.mark.asyncio
+async def test_unachievable_goal_returns_suggested_goal_response(tool, session):
+    """unachievable_goal decomposition result returns SuggestedGoalResponse, not ErrorResponse."""
+    unachievable_result = {
+        "type": "unachievable_goal",
+        "suggested_goal": "Summarize the latest news articles on a topic and send them by email",
+        "reason": "There are no blocks for mind-reading.",
+    }
+
+    with (
+        patch(
+            "backend.api.features.chat.tools.create_agent.get_all_relevant_agents_for_generation",
+            new_callable=AsyncMock,
+            return_value=[],
+        ),
+        patch(
+            "backend.api.features.chat.tools.create_agent.decompose_goal",
+            new_callable=AsyncMock,
+            return_value=unachievable_result,
+        ),
+    ):
+        result = await tool._execute(
+            user_id=_TEST_USER_ID,
+            session=session,
+            description="read my mind",
+        )
+
+    assert isinstance(result, SuggestedGoalResponse)
+    assert result.goal_type == "unachievable"
+    assert result.suggested_goal == unachievable_result["suggested_goal"]
+    assert result.original_goal == "read my mind"
+    assert result.reason == unachievable_result["reason"]
+    assert not isinstance(result, ErrorResponse)
+
+
+@pytest.mark.asyncio
+async def test_clarifying_questions_returns_clarification_needed_response(
+    tool, session
+):
+    """clarifying_questions decomposition result returns ClarificationNeededResponse."""
+    clarifying_result = {
+        "type": "clarifying_questions",
+        "questions": [
+            {
+                "question": "What platform should be monitored?",
+                "keyword": "platform",
+                "example": "Twitter, Reddit",
+            }
+        ],
+    }
+
+    with (
+        patch(
+            "backend.api.features.chat.tools.create_agent.get_all_relevant_agents_for_generation",
+            new_callable=AsyncMock,
+            return_value=[],
+        ),
+        patch(
+            "backend.api.features.chat.tools.create_agent.decompose_goal",
+            new_callable=AsyncMock,
+            return_value=clarifying_result,
+        ),
+    ):
+        result = await tool._execute(
+            user_id=_TEST_USER_ID,
+            session=session,
+            description="monitor social media and alert me",
+        )
+
+    assert isinstance(result, ClarificationNeededResponse)
+    assert len(result.questions) == 1
+    assert result.questions[0].keyword == "platform"

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

@@ -50,6 +50,8 @@ class ResponseType(str, Enum):
     # Feature request types
     FEATURE_REQUEST_SEARCH = "feature_request_search"
     FEATURE_REQUEST_CREATED = "feature_request_created"
+    # Goal refinement
+    SUGGESTED_GOAL = "suggested_goal"
 
 
 # Base response model
@@ -296,6 +298,22 @@ class ClarificationNeededResponse(ToolResponseBase):
     questions: list[ClarifyingQuestion] = Field(default_factory=list)
 
 
+class SuggestedGoalResponse(ToolResponseBase):
+    """Response when the goal needs refinement with a suggested alternative."""
+
+    type: ResponseType = ResponseType.SUGGESTED_GOAL
+    suggested_goal: str = Field(description="The suggested alternative goal")
+    reason: str = Field(
+        default="", description="Why the original goal needs refinement"
+    )
+    original_goal: str = Field(
+        default="", description="The user's original goal for context"
+    )
+    goal_type: str = Field(
+        default="vague", description="Type: 'vague' or 'unachievable'"
+    )
+
+
 # Documentation search models
 class DocSearchResult(BaseModel):
     """A single documentation search result."""

autogpt_platform/backend/backend/blocks/llm.py

@@ -106,6 +106,8 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
     GPT41_MINI = "gpt-4.1-mini-2025-04-14"
     GPT4O_MINI = "gpt-4o-mini"
     GPT4O = "gpt-4o"
+    GPT4_TURBO = "gpt-4-turbo"
+    GPT3_5_TURBO = "gpt-3.5-turbo"
     # Anthropic models
     CLAUDE_4_1_OPUS = "claude-opus-4-1-20250805"
     CLAUDE_4_OPUS = "claude-opus-4-20250514"
@@ -253,6 +255,12 @@ MODEL_METADATA = {
     LlmModel.GPT4O: ModelMetadata(
         "openai", 128000, 16384, "GPT-4o", "OpenAI", "OpenAI", 2
     ),  # gpt-4o-2024-08-06
+    LlmModel.GPT4_TURBO: ModelMetadata(
+        "openai", 128000, 4096, "GPT-4 Turbo", "OpenAI", "OpenAI", 3
+    ),  # gpt-4-turbo-2024-04-09
+    LlmModel.GPT3_5_TURBO: ModelMetadata(
+        "openai", 16385, 4096, "GPT-3.5 Turbo", "OpenAI", "OpenAI", 1
+    ),  # gpt-3.5-turbo-0125
     # https://docs.anthropic.com/en/docs/about-claude/models
     LlmModel.CLAUDE_4_1_OPUS: ModelMetadata(
         "anthropic", 200000, 32000, "Claude Opus 4.1", "Anthropic", "Anthropic", 3

autogpt_platform/backend/backend/data/block_cost_config.py

@@ -75,6 +75,8 @@ MODEL_COST: dict[LlmModel, int] = {
     LlmModel.GPT41_MINI: 1,
     LlmModel.GPT4O_MINI: 1,
     LlmModel.GPT4O: 3,
+    LlmModel.GPT4_TURBO: 10,
+    LlmModel.GPT3_5_TURBO: 1,
     LlmModel.CLAUDE_4_1_OPUS: 21,
     LlmModel.CLAUDE_4_OPUS: 21,
     LlmModel.CLAUDE_4_SONNET: 5,

autogpt_platform/backend/backend/data/credit_test.py

@@ -79,7 +79,7 @@ async def test_block_credit_usage(server: SpinTestServer):
             node_exec_id="test_node_exec",
             block_id=AITextGeneratorBlock().id,
             inputs={
-                "model": "gpt-4o",
+                "model": "gpt-4-turbo",
                 "credentials": {
                     "id": openai_credentials.id,
                     "provider": openai_credentials.provider,
@@ -100,7 +100,7 @@ async def test_block_credit_usage(server: SpinTestServer):
             graph_exec_id="test_graph_exec",
             node_exec_id="test_node_exec",
             block_id=AITextGeneratorBlock().id,
-            inputs={"model": "gpt-4o", "api_key": "owned_api_key"},
+            inputs={"model": "gpt-4-turbo", "api_key": "owned_api_key"},
             execution_context=ExecutionContext(user_timezone="UTC"),
         ),
     )

autogpt_platform/backend/docker-compose.test.yaml

@@ -53,7 +53,7 @@ services:
 
   rabbitmq:
     <<: *agpt-services
-    image: rabbitmq:4.1.4
+    image: rabbitmq:management
     container_name: rabbitmq
     healthcheck:
       test: rabbitmq-diagnostics -q ping
@@ -66,6 +66,7 @@ services:
       - RABBITMQ_DEFAULT_PASS=k0VMxyIJF9S35f3x2uaw5IWAl6Y536O7
     ports:
       - "5672:5672"
+      - "15672:15672"
   clamav:
     image: clamav/clamav-debian:latest
     ports:

autogpt_platform/backend/migrations/20260216120000_migrate_deprecated_gpt4_gpt35_models/migration.sql

@@ -1,42 +0,0 @@
--- Migrate deprecated OpenAI GPT-4-turbo and GPT-3.5-turbo models
--- This updates all AgentNode blocks that use deprecated models
--- OpenAI is retiring these models:
---   - gpt-4-turbo: March 26, 2026 -> migrate to gpt-4o
---   - gpt-3.5-turbo: September 28, 2026 -> migrate to gpt-4o-mini
-
--- Update gpt-4-turbo to gpt-4o (staying in same capability tier)
-UPDATE "AgentNode"
-SET    "constantInput" = JSONB_SET(
-         "constantInput"::jsonb,
-         '{model}',
-         '"gpt-4o"'::jsonb
-       )
-WHERE  "constantInput"::jsonb->>'model' = 'gpt-4-turbo';
-
--- Update gpt-3.5-turbo to gpt-4o-mini (appropriate replacement for lightweight model)
-UPDATE "AgentNode"
-SET    "constantInput" = JSONB_SET(
-         "constantInput"::jsonb,
-         '{model}',
-         '"gpt-4o-mini"'::jsonb
-       )
-WHERE  "constantInput"::jsonb->>'model' = 'gpt-3.5-turbo';
-
--- Update AgentPreset input overrides (stored in AgentNodeExecutionInputOutput)
-UPDATE "AgentNodeExecutionInputOutput"
-SET    "data" = JSONB_SET(
-         "data"::jsonb,
-         '{model}',
-         '"gpt-4o"'::jsonb
-       )
-WHERE  "agentPresetId" IS NOT NULL
-  AND  "data"::jsonb->>'model' = 'gpt-4-turbo';
-
-UPDATE "AgentNodeExecutionInputOutput"
-SET    "data" = JSONB_SET(
-         "data"::jsonb,
-         '{model}',
-         '"gpt-4o-mini"'::jsonb
-       )
-WHERE  "agentPresetId" IS NOT NULL
-  AND  "data"::jsonb->>'model' = 'gpt-3.5-turbo';

autogpt_platform/docker-compose.platform.yml

@@ -75,7 +75,7 @@ services:
       timeout: 5s
       retries: 5
   rabbitmq:
-    image: rabbitmq:4.1.4
+    image: rabbitmq:management
     container_name: rabbitmq
     healthcheck:
       test: rabbitmq-diagnostics -q ping
@@ -88,13 +88,14 @@ services:
       <<: *backend-env
     ports:
       - "5672:5672"
+      - "15672:15672"
 
   rest_server:
     build:
       context: ../
       dockerfile: autogpt_platform/backend/Dockerfile
       target: server
-    command: ["rest"] # points to entry in [tool.poetry.scripts] in pyproject.toml
+    command: ["python", "-m", "backend.rest"]
     develop:
       watch:
         - path: ./
@@ -127,7 +128,7 @@ services:
       context: ../
       dockerfile: autogpt_platform/backend/Dockerfile
       target: server
-    command: ["executor"] # points to entry in [tool.poetry.scripts] in pyproject.toml
+    command: ["python", "-m", "backend.exec"]
     develop:
       watch:
         - path: ./
@@ -162,7 +163,7 @@ services:
       context: ../
       dockerfile: autogpt_platform/backend/Dockerfile
       target: server
-    command: ["ws"] # points to entry in [tool.poetry.scripts] in pyproject.toml
+    command: ["python", "-m", "backend.ws"]
     develop:
       watch:
         - path: ./
@@ -195,7 +196,7 @@ services:
       context: ../
       dockerfile: autogpt_platform/backend/Dockerfile
       target: server
-    command: ["db"] # points to entry in [tool.poetry.scripts] in pyproject.toml
+    command: ["python", "-m", "backend.db"]
     develop:
       watch:
         - path: ./
@@ -224,7 +225,7 @@ services:
       context: ../
       dockerfile: autogpt_platform/backend/Dockerfile
       target: server
-    command: ["scheduler"] # points to entry in [tool.poetry.scripts] in pyproject.toml
+    command: ["python", "-m", "backend.scheduler"]
     develop:
       watch:
         - path: ./
@@ -272,7 +273,7 @@ services:
       context: ../
       dockerfile: autogpt_platform/backend/Dockerfile
       target: server
-    command: ["notification"] # points to entry in [tool.poetry.scripts] in pyproject.toml
+    command: ["python", "-m", "backend.notification"]
     develop:
       watch:
         - path: ./

autogpt_platform/frontend/src/app/(platform)/build/components/BuilderActions/components/RunGraph/useRunGraph.ts

@@ -4,7 +4,7 @@ import {
 } from "@/app/api/__generated__/endpoints/graphs/graphs";
 import { useToast } from "@/components/molecules/Toast/use-toast";
 import { parseAsInteger, parseAsString, useQueryStates } from "nuqs";
-import { GraphExecutionMeta } from "@/app/api/__generated__/models/graphExecutionMeta";
+import { GraphExecutionMeta } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/use-agent-runs";
 import { useGraphStore } from "@/app/(platform)/build/stores/graphStore";
 import { useShallow } from "zustand/react/shallow";
 import { useEffect, useState } from "react";

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/RunnerInputUI.tsx

@@ -1,6 +1,6 @@
 import { useCallback } from "react";
 
-import { AgentRunDraftView } from "@/app/(platform)/build/components/legacy-builder/agent-run-draft-view";
+import { AgentRunDraftView } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-draft-view";
 import { Dialog } from "@/components/molecules/Dialog/Dialog";
 import type {
   CredentialsMetaInput,

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/SaveControl.tsx

@@ -18,7 +18,7 @@ import {
 import { useToast } from "@/components/molecules/Toast/use-toast";
 import { useQueryClient } from "@tanstack/react-query";
 import { getGetV2ListMySubmissionsQueryKey } from "@/app/api/__generated__/endpoints/store/store";
-import { CronExpressionDialog } from "@/components/contextual/CronScheduler/cron-scheduler-dialog";
+import { CronExpressionDialog } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/cron-scheduler-dialog";
 import { humanizeCronExpression } from "@/lib/cron-expression-utils";
 import { CalendarClockIcon } from "lucide-react";
 

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

@@ -1,8 +1,6 @@
 "use client";
 
 import { SidebarProvider } from "@/components/ui/sidebar";
-// TODO: Replace with modern Dialog component when available
-import DeleteConfirmDialog from "@/components/__legacy__/delete-confirm-dialog";
 import { ChatContainer } from "./components/ChatContainer/ChatContainer";
 import { ChatSidebar } from "./components/ChatSidebar/ChatSidebar";
 import { MobileDrawer } from "./components/MobileDrawer/MobileDrawer";
@@ -33,12 +31,6 @@ export function CopilotPage() {
     handleDrawerOpenChange,
     handleSelectSession,
     handleNewChat,
-    // Delete functionality
-    sessionToDelete,
-    isDeleting,
-    handleDeleteClick,
-    handleConfirmDelete,
-    handleCancelDelete,
   } = useCopilotPage();
 
   if (isUserLoading || !isLoggedIn) {
@@ -56,19 +48,7 @@ export function CopilotPage() {
     >
       {!isMobile && <ChatSidebar />}
       <div className="relative flex h-full w-full flex-col overflow-hidden bg-[#f8f8f9] px-0">
-        {isMobile && (
-          <MobileHeader
-            onOpenDrawer={handleOpenDrawer}
-            showDelete={!!sessionId}
-            isDeleting={isDeleting}
-            onDelete={() => {
-              const session = sessions.find((s) => s.id === sessionId);
-              if (session) {
-                handleDeleteClick(session.id, session.title);
-              }
-            }}
-          />
-        )}
+        {isMobile && <MobileHeader onOpenDrawer={handleOpenDrawer} />}
         <div className="flex-1 overflow-hidden">
           <ChatContainer
             messages={messages}
@@ -95,16 +75,6 @@ export function CopilotPage() {
           onOpenChange={handleDrawerOpenChange}
         />
       )}
-      {/* Delete confirmation dialog - rendered at top level for proper z-index on mobile */}
-      {isMobile && (
-        <DeleteConfirmDialog
-          entityType="chat"
-          entityName={sessionToDelete?.title || "Untitled chat"}
-          open={!!sessionToDelete}
-          onOpenChange={(open) => !open && handleCancelDelete()}
-          onDoDelete={handleConfirmDelete}
-        />
-      )}
     </SidebarProvider>
   );
 }

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

@@ -1,15 +1,8 @@
 "use client";
-import {
-  getGetV2ListSessionsQueryKey,
-  useDeleteV2DeleteSession,
-  useGetV2ListSessions,
-} from "@/app/api/__generated__/endpoints/chat/chat";
+import { useGetV2ListSessions } from "@/app/api/__generated__/endpoints/chat/chat";
 import { Button } from "@/components/atoms/Button/Button";
 import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
 import { Text } from "@/components/atoms/Text/Text";
-import { toast } from "@/components/molecules/Toast/use-toast";
-// TODO: Replace with modern Dialog component when available
-import DeleteConfirmDialog from "@/components/__legacy__/delete-confirm-dialog";
 import {
   Sidebar,
   SidebarContent,
@@ -19,52 +12,18 @@ import {
   useSidebar,
 } from "@/components/ui/sidebar";
 import { cn } from "@/lib/utils";
-import { PlusCircleIcon, PlusIcon, TrashIcon } from "@phosphor-icons/react";
-import { useQueryClient } from "@tanstack/react-query";
+import { PlusCircleIcon, PlusIcon } from "@phosphor-icons/react";
 import { motion } from "framer-motion";
-import { useState } from "react";
 import { parseAsString, useQueryState } from "nuqs";
 
 export function ChatSidebar() {
   const { state } = useSidebar();
   const isCollapsed = state === "collapsed";
   const [sessionId, setSessionId] = useQueryState("sessionId", parseAsString);
-  const [sessionToDelete, setSessionToDelete] = useState<{
-    id: string;
-    title: string | null | undefined;
-  } | null>(null);
-
-  const queryClient = useQueryClient();
 
   const { data: sessionsResponse, isLoading: isLoadingSessions } =
     useGetV2ListSessions({ limit: 50 });
 
-  const { mutate: deleteSession, isPending: isDeleting } =
-    useDeleteV2DeleteSession({
-      mutation: {
-        onSuccess: () => {
-          // Invalidate sessions list to refetch
-          queryClient.invalidateQueries({
-            queryKey: getGetV2ListSessionsQueryKey(),
-          });
-          // If we deleted the current session, clear selection
-          if (sessionToDelete?.id === sessionId) {
-            setSessionId(null);
-          }
-          setSessionToDelete(null);
-        },
-        onError: (error) => {
-          toast({
-            title: "Failed to delete chat",
-            description:
-              error instanceof Error ? error.message : "An error occurred",
-            variant: "destructive",
-          });
-          setSessionToDelete(null);
-        },
-      },
-    });
-
   const sessions =
     sessionsResponse?.status === 200 ? sessionsResponse.data.sessions : [];
 
@@ -76,22 +35,6 @@ export function ChatSidebar() {
     setSessionId(id);
   }
 
-  function handleDeleteClick(
-    e: React.MouseEvent,
-    id: string,
-    title: string | null | undefined,
-  ) {
-    e.stopPropagation(); // Prevent session selection
-    if (isDeleting) return; // Prevent double-click during deletion
-    setSessionToDelete({ id, title });
-  }
-
-  function handleConfirmDelete() {
-    if (sessionToDelete) {
-      deleteSession({ sessionId: sessionToDelete.id });
-    }
-  }
-
   function formatDate(dateString: string) {
     const date = new Date(dateString);
     const now = new Date();
@@ -118,152 +61,128 @@ export function ChatSidebar() {
   }
 
   return (
-    <>
-      <Sidebar
-        variant="inset"
-        collapsible="icon"
-        className="!top-[50px] !h-[calc(100vh-50px)] border-r border-zinc-100 px-0"
-      >
-        {isCollapsed && (
-          <SidebarHeader
-            className={cn(
-              "flex",
-              isCollapsed
-                ? "flex-row items-center justify-between gap-y-4 md:flex-col md:items-start md:justify-start"
-                : "flex-row items-center justify-between",
-            )}
+    <Sidebar
+      variant="inset"
+      collapsible="icon"
+      className="!top-[50px] !h-[calc(100vh-50px)] border-r border-zinc-100 px-0"
+    >
+      {isCollapsed && (
+        <SidebarHeader
+          className={cn(
+            "flex",
+            isCollapsed
+              ? "flex-row items-center justify-between gap-y-4 md:flex-col md:items-start md:justify-start"
+              : "flex-row items-center justify-between",
+          )}
+        >
+          <motion.div
+            key={isCollapsed ? "header-collapsed" : "header-expanded"}
+            className="flex flex-col items-center gap-3 pt-4"
+            initial={{ opacity: 0, filter: "blur(3px)" }}
+            animate={{ opacity: 1, filter: "blur(0px)" }}
+            transition={{ type: "spring", bounce: 0.2 }}
           >
-            <motion.div
-              key={isCollapsed ? "header-collapsed" : "header-expanded"}
-              className="flex flex-col items-center gap-3 pt-4"
-              initial={{ opacity: 0, filter: "blur(3px)" }}
-              animate={{ opacity: 1, filter: "blur(0px)" }}
-              transition={{ type: "spring", bounce: 0.2 }}
-            >
-              <div className="flex flex-col items-center gap-2">
-                <SidebarTrigger />
-                <Button
-                  variant="ghost"
-                  onClick={handleNewChat}
-                  style={{ minWidth: "auto", width: "auto" }}
-                >
-                  <PlusCircleIcon className="!size-5" />
-                  <span className="sr-only">New Chat</span>
-                </Button>
-              </div>
-            </motion.div>
-          </SidebarHeader>
-        )}
-        <SidebarContent className="gap-4 overflow-y-auto px-4 py-4 [-ms-overflow-style:none] [scrollbar-width:none] [&::-webkit-scrollbar]:hidden">
-          {!isCollapsed && (
-            <motion.div
-              initial={{ opacity: 0 }}
-              animate={{ opacity: 1 }}
-              transition={{ duration: 0.2, delay: 0.1 }}
-              className="flex items-center justify-between px-3"
-            >
-              <Text variant="h3" size="body-medium">
-                Your chats
-              </Text>
-              <div className="relative left-6">
-                <SidebarTrigger />
-              </div>
-            </motion.div>
-          )}
-
-          {!isCollapsed && (
-            <motion.div
-              initial={{ opacity: 0 }}
-              animate={{ opacity: 1 }}
-              transition={{ duration: 0.2, delay: 0.15 }}
-              className="mt-4 flex flex-col gap-1"
-            >
-              {isLoadingSessions ? (
-                <div className="flex min-h-[30rem] items-center justify-center py-4">
-                  <LoadingSpinner size="small" className="text-neutral-600" />
-                </div>
-              ) : sessions.length === 0 ? (
-                <p className="py-4 text-center text-sm text-neutral-500">
-                  No conversations yet
-                </p>
-              ) : (
-                sessions.map((session) => (
-                  <div
-                    key={session.id}
-                    className={cn(
-                      "group relative w-full rounded-lg transition-colors",
-                      session.id === sessionId
-                        ? "bg-zinc-100"
-                        : "hover:bg-zinc-50",
-                    )}
-                  >
-                    <button
-                      onClick={() => handleSelectSession(session.id)}
-                      className="w-full px-3 py-2.5 pr-10 text-left"
-                    >
-                      <div className="flex min-w-0 max-w-full flex-col overflow-hidden">
-                        <div className="min-w-0 max-w-full">
-                          <Text
-                            variant="body"
-                            className={cn(
-                              "truncate font-normal",
-                              session.id === sessionId
-                                ? "text-zinc-600"
-                                : "text-zinc-800",
-                            )}
-                          >
-                            {session.title || `Untitled chat`}
-                          </Text>
-                        </div>
-                        <Text variant="small" className="text-neutral-400">
-                          {formatDate(session.updated_at)}
-                        </Text>
-                      </div>
-                    </button>
-                    <button
-                      onClick={(e) =>
-                        handleDeleteClick(e, session.id, session.title)
-                      }
-                      disabled={isDeleting}
-                      className="absolute right-2 top-1/2 -translate-y-1/2 rounded p-1.5 text-zinc-400 opacity-0 transition-all group-hover:opacity-100 hover:bg-red-100 hover:text-red-600 focus-visible:opacity-100 disabled:cursor-not-allowed disabled:opacity-50"
-                      aria-label="Delete chat"
-                    >
-                      <TrashIcon className="h-4 w-4" />
-                    </button>
-                  </div>
-                ))
-              )}
-            </motion.div>
-          )}
-        </SidebarContent>
-        {!isCollapsed && sessionId && (
-          <SidebarFooter className="shrink-0 bg-zinc-50 p-3 pb-1 shadow-[0_-4px_6px_-1px_rgba(0,0,0,0.05)]">
-            <motion.div
-              initial={{ opacity: 0 }}
-              animate={{ opacity: 1 }}
-              transition={{ duration: 0.2, delay: 0.2 }}
-            >
+            <div className="flex flex-col items-center gap-2">
+              <SidebarTrigger />
               <Button
-                variant="primary"
-                size="small"
+                variant="ghost"
                 onClick={handleNewChat}
-                className="w-full"
-                leftIcon={<PlusIcon className="h-4 w-4" weight="bold" />}
+                style={{ minWidth: "auto", width: "auto" }}
               >
-                New Chat
+                <PlusCircleIcon className="!size-5" />
+                <span className="sr-only">New Chat</span>
               </Button>
-            </motion.div>
-          </SidebarFooter>
+            </div>
+          </motion.div>
+        </SidebarHeader>
+      )}
+      <SidebarContent className="gap-4 overflow-y-auto px-4 py-4 [-ms-overflow-style:none] [scrollbar-width:none] [&::-webkit-scrollbar]:hidden">
+        {!isCollapsed && (
+          <motion.div
+            initial={{ opacity: 0 }}
+            animate={{ opacity: 1 }}
+            transition={{ duration: 0.2, delay: 0.1 }}
+            className="flex items-center justify-between px-3"
+          >
+            <Text variant="h3" size="body-medium">
+              Your chats
+            </Text>
+            <div className="relative left-6">
+              <SidebarTrigger />
+            </div>
+          </motion.div>
         )}
-      </Sidebar>
 
-      <DeleteConfirmDialog
-        entityType="chat"
-        entityName={sessionToDelete?.title || "Untitled chat"}
-        open={!!sessionToDelete}
-        onOpenChange={(open) => !open && setSessionToDelete(null)}
-        onDoDelete={handleConfirmDelete}
-      />
-    </>
+        {!isCollapsed && (
+          <motion.div
+            initial={{ opacity: 0 }}
+            animate={{ opacity: 1 }}
+            transition={{ duration: 0.2, delay: 0.15 }}
+            className="mt-4 flex flex-col gap-1"
+          >
+            {isLoadingSessions ? (
+              <div className="flex min-h-[30rem] items-center justify-center py-4">
+                <LoadingSpinner size="small" className="text-neutral-600" />
+              </div>
+            ) : sessions.length === 0 ? (
+              <p className="py-4 text-center text-sm text-neutral-500">
+                No conversations yet
+              </p>
+            ) : (
+              sessions.map((session) => (
+                <button
+                  key={session.id}
+                  onClick={() => handleSelectSession(session.id)}
+                  className={cn(
+                    "w-full rounded-lg px-3 py-2.5 text-left transition-colors",
+                    session.id === sessionId
+                      ? "bg-zinc-100"
+                      : "hover:bg-zinc-50",
+                  )}
+                >
+                  <div className="flex min-w-0 max-w-full flex-col overflow-hidden">
+                    <div className="min-w-0 max-w-full">
+                      <Text
+                        variant="body"
+                        className={cn(
+                          "truncate font-normal",
+                          session.id === sessionId
+                            ? "text-zinc-600"
+                            : "text-zinc-800",
+                        )}
+                      >
+                        {session.title || `Untitled chat`}
+                      </Text>
+                    </div>
+                    <Text variant="small" className="text-neutral-400">
+                      {formatDate(session.updated_at)}
+                    </Text>
+                  </div>
+                </button>
+              ))
+            )}
+          </motion.div>
+        )}
+      </SidebarContent>
+      {!isCollapsed && sessionId && (
+        <SidebarFooter className="shrink-0 bg-zinc-50 p-3 pb-1 shadow-[0_-4px_6px_-1px_rgba(0,0,0,0.05)]">
+          <motion.div
+            initial={{ opacity: 0 }}
+            animate={{ opacity: 1 }}
+            transition={{ duration: 0.2, delay: 0.2 }}
+          >
+            <Button
+              variant="primary"
+              size="small"
+              onClick={handleNewChat}
+              className="w-full"
+              leftIcon={<PlusIcon className="h-4 w-4" weight="bold" />}
+            >
+              New Chat
+            </Button>
+          </motion.div>
+        </SidebarFooter>
+      )}
+    </Sidebar>
   );
 }

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

@@ -1,46 +1,22 @@
 import { Button } from "@/components/atoms/Button/Button";
 import { NAVBAR_HEIGHT_PX } from "@/lib/constants";
-import { ListIcon, TrashIcon } from "@phosphor-icons/react";
+import { ListIcon } from "@phosphor-icons/react";
 
 interface Props {
   onOpenDrawer: () => void;
-  showDelete?: boolean;
-  isDeleting?: boolean;
-  onDelete?: () => void;
 }
 
-export function MobileHeader({
-  onOpenDrawer,
-  showDelete,
-  isDeleting,
-  onDelete,
-}: Props) {
+export function MobileHeader({ onOpenDrawer }: Props) {
   return (
-    <div
-      className="fixed z-50 flex gap-2"
+    <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` }}
     >
-      <Button
-        variant="icon"
-        size="icon"
-        aria-label="Open sessions"
-        onClick={onOpenDrawer}
-        className="bg-white shadow-md"
-      >
-        <ListIcon width="1.25rem" height="1.25rem" />
-      </Button>
-      {showDelete && onDelete && (
-        <Button
-          variant="icon"
-          size="icon"
-          aria-label="Delete current chat"
-          onClick={onDelete}
-          disabled={isDeleting}
-          className="bg-white text-red-500 shadow-md hover:bg-red-50 hover:text-red-600 disabled:opacity-50"
-        >
-          <TrashIcon width="1.25rem" height="1.25rem" />
-        </Button>
-      )}
-    </div>
+      <ListIcon width="1.25rem" height="1.25rem" />
+    </Button>
   );
 }

autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/CreateAgent.tsx

@@ -4,11 +4,11 @@ import { Button } from "@/components/atoms/Button/Button";
 import { Text } from "@/components/atoms/Text/Text";
 import {
   BookOpenIcon,
+  CheckFatIcon,
   PencilSimpleIcon,
   WarningDiamondIcon,
 } from "@phosphor-icons/react";
 import type { ToolUIPart } from "ai";
-import Image from "next/image";
 import NextLink from "next/link";
 import { useCopilotChatActions } from "../../components/CopilotChatActionsProvider/useCopilotChatActions";
 import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
@@ -24,8 +24,8 @@ import {
   ClarificationQuestionsCard,
   ClarifyingQuestion,
 } from "./components/ClarificationQuestionsCard";
-import sparklesImg from "./components/MiniGame/assets/sparkles.png";
 import { MiniGame } from "./components/MiniGame/MiniGame";
+import { SuggestedGoalCard } from "./components/SuggestedGoalCard";
 import {
   AccordionIcon,
   formatMaybeJson,
@@ -38,6 +38,7 @@ import {
   isOperationInProgressOutput,
   isOperationPendingOutput,
   isOperationStartedOutput,
+  isSuggestedGoalOutput,
   ToolIcon,
   truncateText,
   type CreateAgentToolOutput,
@@ -77,6 +78,13 @@ function getAccordionMeta(output: CreateAgentToolOutput) {
       expanded: true,
     };
   }
+  if (isSuggestedGoalOutput(output)) {
+    return {
+      icon,
+      title: "Goal needs refinement",
+      expanded: true,
+    };
+  }
   if (
     isOperationStartedOutput(output) ||
     isOperationPendingOutput(output) ||
@@ -84,8 +92,7 @@ function getAccordionMeta(output: CreateAgentToolOutput) {
   ) {
     return {
       icon,
-      title:
-        "Creating agent, this may take a few minutes. Play while you wait.",
+      title: "Creating agent, this may take a few minutes. Sit back and relax.",
       expanded: true,
     };
   }
@@ -125,8 +132,13 @@ export function CreateAgentTool({ part }: Props) {
       isAgentPreviewOutput(output) ||
       isAgentSavedOutput(output) ||
       isClarificationNeededOutput(output) ||
+      isSuggestedGoalOutput(output) ||
       isErrorOutput(output));
 
+  function handleUseSuggestedGoal(goal: string) {
+    onSend(`Please create an agent with this goal: ${goal}`);
+  }
+
   function handleClarificationAnswers(answers: Record<string, string>) {
     const questions =
       output && isClarificationNeededOutput(output)
@@ -169,20 +181,16 @@ export function CreateAgentTool({ part }: Props) {
           {isAgentSavedOutput(output) && (
             <div className="rounded-xl border border-border/60 bg-card p-4 shadow-sm">
               <div className="flex items-baseline gap-2">
-                <Image
-                  src={sparklesImg}
-                  alt="sparkles"
-                  width={24}
-                  height={24}
-                  className="relative top-1"
+                <CheckFatIcon
+                  size={18}
+                  weight="regular"
+                  className="relative top-1 text-green-500"
                 />
                 <Text
                   variant="body-medium"
-                  className="mb-2 text-[16px] text-black"
+                  className="text-blacks mb-2 text-[16px]"
                 >
-                  Agent{" "}
-                  <span className="text-violet-600">{output.agent_name}</span>{" "}
-                  has been saved to your library!
+                  {output.message}
                 </Text>
               </div>
               <div className="mt-3 flex flex-wrap gap-4">
@@ -245,6 +253,15 @@ export function CreateAgentTool({ part }: Props) {
             />
           )}
 
+          {isSuggestedGoalOutput(output) && (
+            <SuggestedGoalCard
+              message={output.message}
+              suggestedGoal={output.suggested_goal}
+              goalType={output.goal_type ?? "vague"}
+              onUseSuggestedGoal={handleUseSuggestedGoal}
+            />
+          )}
+
           {isErrorOutput(output) && (
             <ContentGrid>
               <ContentMessage>{output.message}</ContentMessage>
@@ -258,6 +275,22 @@ export function CreateAgentTool({ part }: Props) {
                   {formatMaybeJson(output.details)}
                 </ContentCodeBlock>
               )}
+              <div className="flex gap-2">
+                <Button
+                  variant="outline"
+                  size="small"
+                  onClick={() => onSend("Please try creating the agent again.")}
+                >
+                  Try again
+                </Button>
+                <Button
+                  variant="outline"
+                  size="small"
+                  onClick={() => onSend("Can you help me simplify this goal?")}
+                >
+                  Simplify goal
+                </Button>
+              </div>
             </ContentGrid>
           )}
         </ToolAccordion>

autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/components/MiniGame/MiniGame.tsx

@@ -2,65 +2,20 @@
 
 import { useMiniGame } from "./useMiniGame";
 
-function Key({ children }: { children: React.ReactNode }) {
-  return <strong>[{children}]</strong>;
-}
-
 export function MiniGame() {
-  const { canvasRef, activeMode, showOverlay, score, highScore, onContinue } =
-    useMiniGame();
-
-  const isRunActive =
-    activeMode === "run" || activeMode === "idle" || activeMode === "over";
-
-  let overlayText: string | undefined;
-  let buttonLabel = "Continue";
-  if (activeMode === "idle") {
-    buttonLabel = "Start";
-  } else if (activeMode === "boss-intro") {
-    overlayText = "Face the bandit!";
-  } else if (activeMode === "boss-defeated") {
-    overlayText = "Great job, keep on going";
-  } else if (activeMode === "over") {
-    overlayText = `Score: ${score} / Record: ${highScore}`;
-    buttonLabel = "Retry";
-  }
+  const { canvasRef } = useMiniGame();
 
   return (
-    <div className="flex flex-col gap-2">
-      <p className="text-sm font-medium text-purple-500">
-        {isRunActive ? (
-          <>
-            Run mode: <Key>Space</Key> to jump
-          </>
-        ) : (
-          <>
-            Duel mode: <Key>←→</Key> to move · <Key>Z</Key> to attack ·{" "}
-            <Key>X</Key> to block · <Key>Space</Key> to jump
-          </>
-        )}
-      </p>
-      <div className="relative w-full overflow-hidden rounded-md border border-accent bg-background text-foreground">
-        <canvas
-          ref={canvasRef}
-          tabIndex={0}
-          className="block w-full outline-none"
-        />
-        {showOverlay && (
-          <div className="absolute inset-0 flex flex-col items-center justify-center gap-3 bg-black/40">
-            {overlayText && (
-              <p className="text-lg font-bold text-white">{overlayText}</p>
-            )}
-            <button
-              type="button"
-              onClick={onContinue}
-              className="rounded-md bg-white px-4 py-2 text-sm font-semibold text-zinc-800 shadow-md transition-colors hover:bg-zinc-100"
-            >
-              {buttonLabel}
-            </button>
-          </div>
-        )}
-      </div>
+    <div
+      className="w-full overflow-hidden rounded-md bg-background text-foreground"
+      style={{ border: "1px solid #d17fff" }}
+    >
+      <canvas
+        ref={canvasRef}
+        tabIndex={0}
+        className="block w-full outline-none"
+        style={{ imageRendering: "pixelated" }}
+      />
     </div>
   );
 }

autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/components/SuggestedGoalCard.tsx

@@ -0,0 +1,61 @@
+"use client";
+
+import { Button } from "@/components/atoms/Button/Button";
+import { Text } from "@/components/atoms/Text/Text";
+import { ArrowRightIcon, LightbulbIcon } from "@phosphor-icons/react";
+
+interface Props {
+  message: string;
+  suggestedGoal: string;
+  goalType: string;
+  onUseSuggestedGoal: (goal: string) => void;
+}
+
+export function SuggestedGoalCard({
+  message,
+  suggestedGoal,
+  goalType,
+  onUseSuggestedGoal,
+}: Props) {
+  return (
+    <div className="rounded-xl border border-amber-200 bg-amber-50/50 p-4">
+      <div className="flex items-start gap-3">
+        <LightbulbIcon
+          size={20}
+          weight="fill"
+          className="mt-0.5 text-amber-600"
+        />
+        <div className="flex-1 space-y-3">
+          <div>
+            <Text variant="body-medium" className="font-medium text-slate-900">
+              {goalType === "unachievable"
+                ? "Goal cannot be accomplished"
+                : "Goal needs more detail"}
+            </Text>
+            <Text variant="small" className="text-slate-600">
+              {message}
+            </Text>
+          </div>
+
+          <div className="rounded-lg border border-amber-300 bg-white p-3">
+            <Text variant="small" className="mb-1 font-semibold text-amber-800">
+              Suggested alternative:
+            </Text>
+            <Text variant="body-medium" className="text-slate-900">
+              {suggestedGoal}
+            </Text>
+          </div>
+
+          <Button
+            onClick={() => onUseSuggestedGoal(suggestedGoal)}
+            variant="primary"
+          >
+            <span className="inline-flex items-center gap-1.5">
+              Use this goal <ArrowRightIcon size={14} weight="bold" />
+            </span>
+          </Button>
+        </div>
+      </div>
+    </div>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/helpers.tsx

@@ -6,6 +6,7 @@ import type { OperationInProgressResponse } from "@/app/api/__generated__/models
 import type { OperationPendingResponse } from "@/app/api/__generated__/models/operationPendingResponse";
 import type { OperationStartedResponse } from "@/app/api/__generated__/models/operationStartedResponse";
 import { ResponseType } from "@/app/api/__generated__/models/responseType";
+import type { SuggestedGoalResponse } from "@/app/api/__generated__/models/suggestedGoalResponse";
 import {
   PlusCircleIcon,
   PlusIcon,
@@ -21,6 +22,7 @@ export type CreateAgentToolOutput =
   | AgentPreviewResponse
   | AgentSavedResponse
   | ClarificationNeededResponse
+  | SuggestedGoalResponse
   | ErrorResponse;
 
 function parseOutput(output: unknown): CreateAgentToolOutput | null {
@@ -43,6 +45,7 @@ function parseOutput(output: unknown): CreateAgentToolOutput | null {
       type === ResponseType.agent_preview ||
       type === ResponseType.agent_saved ||
       type === ResponseType.clarification_needed ||
+      type === ResponseType.suggested_goal ||
       type === ResponseType.error
     ) {
       return output as CreateAgentToolOutput;
@@ -55,6 +58,7 @@ function parseOutput(output: unknown): CreateAgentToolOutput | null {
     if ("agent_id" in output && "library_agent_id" in output)
       return output as AgentSavedResponse;
     if ("questions" in output) return output as ClarificationNeededResponse;
+    if ("suggested_goal" in output) return output as SuggestedGoalResponse;
     if ("error" in output || "details" in output)
       return output as ErrorResponse;
   }
@@ -114,6 +118,14 @@ export function isClarificationNeededOutput(
   );
 }
 
+export function isSuggestedGoalOutput(
+  output: CreateAgentToolOutput,
+): output is SuggestedGoalResponse {
+  return (
+    output.type === ResponseType.suggested_goal || "suggested_goal" in output
+  );
+}
+
 export function isErrorOutput(
   output: CreateAgentToolOutput,
 ): output is ErrorResponse {
@@ -136,9 +148,10 @@ export function getAnimationText(part: {
       if (isOperationPendingOutput(output)) return "Agent creation in progress";
       if (isOperationInProgressOutput(output))
         return "Agent creation already in progress";
-      if (isAgentSavedOutput(output)) return `Saved ${output.agent_name}`;
+      if (isAgentSavedOutput(output)) return `Saved "${output.agent_name}"`;
       if (isAgentPreviewOutput(output)) return `Preview "${output.agent_name}"`;
       if (isClarificationNeededOutput(output)) return "Needs clarification";
+      if (isSuggestedGoalOutput(output)) return "Goal needs refinement";
       return "Error creating agent";
     }
     case "output-error":

autogpt_platform/frontend/src/app/(platform)/copilot/tools/EditAgent/EditAgent.tsx

@@ -5,6 +5,7 @@ import type { ToolUIPart } from "ai";
 import { useCopilotChatActions } from "../../components/CopilotChatActionsProvider/useCopilotChatActions";
 import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
 import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
+import { ProgressBar } from "../../components/ProgressBar/ProgressBar";
 import {
   ContentCardDescription,
   ContentCodeBlock,
@@ -14,7 +15,7 @@ import {
   ContentMessage,
 } from "../../components/ToolAccordion/AccordionContent";
 import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
-import { MiniGame } from "../CreateAgent/components/MiniGame/MiniGame";
+import { useAsymptoticProgress } from "../../hooks/useAsymptoticProgress";
 import {
   ClarificationQuestionsCard,
   ClarifyingQuestion,
@@ -53,7 +54,6 @@ function getAccordionMeta(output: EditAgentToolOutput): {
   title: string;
   titleClassName?: string;
   description?: string;
-  expanded?: boolean;
 } {
   const icon = <AccordionIcon />;
 
@@ -80,11 +80,7 @@ function getAccordionMeta(output: EditAgentToolOutput): {
     isOperationPendingOutput(output) ||
     isOperationInProgressOutput(output)
   ) {
-    return {
-      icon: <OrbitLoader size={32} />,
-      title: "Editing agent, this may take a few minutes. Play while you wait.",
-      expanded: true,
-    };
+    return { icon: <OrbitLoader size={32} />, title: "Editing agent" };
   }
   return {
     icon: (
@@ -109,6 +105,7 @@ export function EditAgentTool({ part }: Props) {
     (isOperationStartedOutput(output) ||
       isOperationPendingOutput(output) ||
       isOperationInProgressOutput(output));
+  const progress = useAsymptoticProgress(isOperating);
   const hasExpandableContent =
     part.state === "output-available" &&
     !!output &&
@@ -152,9 +149,9 @@ export function EditAgentTool({ part }: Props) {
         <ToolAccordion {...getAccordionMeta(output)}>
           {isOperating && (
             <ContentGrid>
-              <MiniGame />
+              <ProgressBar value={progress} className="max-w-[280px]" />
               <ContentHint>
-                This could take a few minutes — play while you wait!
+                This could take a few minutes, grab a coffee ☕
               </ContentHint>
             </ContentGrid>
           )}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/RunAgent.tsx

@@ -2,14 +2,8 @@
 
 import type { ToolUIPart } from "ai";
 import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
-import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
 import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
-import {
-  ContentGrid,
-  ContentHint,
-  ContentMessage,
-} from "../../components/ToolAccordion/AccordionContent";
-import { MiniGame } from "../CreateAgent/components/MiniGame/MiniGame";
+import { ContentMessage } from "../../components/ToolAccordion/AccordionContent";
 import {
   getAccordionMeta,
   getAnimationText,
@@ -66,21 +60,6 @@ export function RunAgentTool({ part }: Props) {
         />
       </div>
 
-      {isStreaming && !output && (
-        <ToolAccordion
-          icon={<OrbitLoader size={32} />}
-          title="Running agent, this may take a few minutes. Play while you wait."
-          expanded={true}
-        >
-          <ContentGrid>
-            <MiniGame />
-            <ContentHint>
-              This could take a few minutes — play while you wait!
-            </ContentHint>
-          </ContentGrid>
-        </ToolAccordion>
-      )}
-
       {hasExpandableContent && output && (
         <ToolAccordion {...getAccordionMeta(output)}>
           {isRunAgentExecutionStartedOutput(output) && (

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

@@ -1,15 +1,10 @@
-import {
-  getGetV2ListSessionsQueryKey,
-  useDeleteV2DeleteSession,
-  useGetV2ListSessions,
-} from "@/app/api/__generated__/endpoints/chat/chat";
+import { useGetV2ListSessions } from "@/app/api/__generated__/endpoints/chat/chat";
 import { toast } from "@/components/molecules/Toast/use-toast";
 import { useBreakpoint } from "@/lib/hooks/useBreakpoint";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
 import { useChat } from "@ai-sdk/react";
-import { useQueryClient } from "@tanstack/react-query";
 import { DefaultChatTransport } from "ai";
-import { useCallback, useEffect, useMemo, useRef, useState } from "react";
+import { useEffect, useMemo, useRef, useState } from "react";
 import { useChatSession } from "./useChatSession";
 import { useLongRunningToolPolling } from "./hooks/useLongRunningToolPolling";
 
@@ -19,11 +14,6 @@ export function useCopilotPage() {
   const { isUserLoading, isLoggedIn } = useSupabase();
   const [isDrawerOpen, setIsDrawerOpen] = useState(false);
   const [pendingMessage, setPendingMessage] = useState<string | null>(null);
-  const [sessionToDelete, setSessionToDelete] = useState<{
-    id: string;
-    title: string | null | undefined;
-  } | null>(null);
-  const queryClient = useQueryClient();
 
   const {
     sessionId,
@@ -34,30 +24,6 @@ export function useCopilotPage() {
     isCreatingSession,
   } = useChatSession();
 
-  const { mutate: deleteSessionMutation, isPending: isDeleting } =
-    useDeleteV2DeleteSession({
-      mutation: {
-        onSuccess: () => {
-          queryClient.invalidateQueries({
-            queryKey: getGetV2ListSessionsQueryKey(),
-          });
-          if (sessionToDelete?.id === sessionId) {
-            setSessionId(null);
-          }
-          setSessionToDelete(null);
-        },
-        onError: (error) => {
-          toast({
-            title: "Failed to delete chat",
-            description:
-              error instanceof Error ? error.message : "An error occurred",
-            variant: "destructive",
-          });
-          setSessionToDelete(null);
-        },
-      },
-    });
-
   const breakpoint = useBreakpoint();
   const isMobile =
     breakpoint === "base" || breakpoint === "sm" || breakpoint === "md";
@@ -177,24 +143,6 @@ export function useCopilotPage() {
     if (isMobile) setIsDrawerOpen(false);
   }
 
-  const handleDeleteClick = useCallback(
-    (id: string, title: string | null | undefined) => {
-      if (isDeleting) return;
-      setSessionToDelete({ id, title });
-    },
-    [isDeleting],
-  );
-
-  const handleConfirmDelete = useCallback(() => {
-    if (sessionToDelete) {
-      deleteSessionMutation({ sessionId: sessionToDelete.id });
-    }
-  }, [sessionToDelete, deleteSessionMutation]);
-
-  const handleCancelDelete = useCallback(() => {
-    setSessionToDelete(null);
-  }, []);
-
   return {
     sessionId,
     messages,
@@ -217,11 +165,5 @@ export function useCopilotPage() {
     handleDrawerOpenChange,
     handleSelectSession,
     handleNewChat,
-    // Delete functionality
-    sessionToDelete,
-    isDeleting,
-    handleDeleteClick,
-    handleConfirmDelete,
-    handleCancelDelete,
   };
 }

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

@@ -0,0 +1,631 @@
+"use client";
+import { useParams, useRouter } from "next/navigation";
+import { useQueryState } from "nuqs";
+import React, {
+  useCallback,
+  useEffect,
+  useMemo,
+  useRef,
+  useState,
+} from "react";
+
+import {
+  Graph,
+  GraphExecution,
+  GraphExecutionID,
+  GraphExecutionMeta,
+  GraphID,
+  LibraryAgent,
+  LibraryAgentID,
+  LibraryAgentPreset,
+  LibraryAgentPresetID,
+  Schedule,
+  ScheduleID,
+} from "@/lib/autogpt-server-api";
+import { useBackendAPI } from "@/lib/autogpt-server-api/context";
+import { exportAsJSONFile } from "@/lib/utils";
+
+import DeleteConfirmDialog from "@/components/__legacy__/delete-confirm-dialog";
+import type { ButtonAction } from "@/components/__legacy__/types";
+import { Button } from "@/components/__legacy__/ui/button";
+import {
+  Dialog,
+  DialogContent,
+  DialogDescription,
+  DialogFooter,
+  DialogHeader,
+  DialogTitle,
+} from "@/components/__legacy__/ui/dialog";
+import LoadingBox, { LoadingSpinner } from "@/components/__legacy__/ui/loading";
+import {
+  useToast,
+  useToastOnFail,
+} from "@/components/molecules/Toast/use-toast";
+import { AgentRunDetailsView } from "./components/agent-run-details-view";
+import { AgentRunDraftView } from "./components/agent-run-draft-view";
+import { CreatePresetDialog } from "./components/create-preset-dialog";
+import { useAgentRunsInfinite } from "./use-agent-runs";
+import { AgentRunsSelectorList } from "./components/agent-runs-selector-list";
+import { AgentScheduleDetailsView } from "./components/agent-schedule-details-view";
+
+export function OldAgentLibraryView() {
+  const { id: agentID }: { id: LibraryAgentID } = useParams();
+  const [executionId, setExecutionId] = useQueryState("executionId");
+  const toastOnFail = useToastOnFail();
+  const { toast } = useToast();
+  const router = useRouter();
+  const api = useBackendAPI();
+
+  // ============================ STATE =============================
+
+  const [graph, setGraph] = useState<Graph | null>(null); // Graph version corresponding to LibraryAgent
+  const [agent, setAgent] = useState<LibraryAgent | null>(null);
+  const agentRunsQuery = useAgentRunsInfinite(graph?.id); // only runs once graph.id is known
+  const agentRuns = agentRunsQuery.agentRuns;
+  const [agentPresets, setAgentPresets] = useState<LibraryAgentPreset[]>([]);
+  const [schedules, setSchedules] = useState<Schedule[]>([]);
+  const [selectedView, selectView] = useState<
+    | { type: "run"; id?: GraphExecutionID }
+    | { type: "preset"; id: LibraryAgentPresetID }
+    | { type: "schedule"; id: ScheduleID }
+  >({ type: "run" });
+  const [selectedRun, setSelectedRun] = useState<
+    GraphExecution | GraphExecutionMeta | null
+  >(null);
+  const selectedSchedule =
+    selectedView.type == "schedule"
+      ? schedules.find((s) => s.id == selectedView.id)
+      : null;
+  const [isFirstLoad, setIsFirstLoad] = useState<boolean>(true);
+  const [agentDeleteDialogOpen, setAgentDeleteDialogOpen] =
+    useState<boolean>(false);
+  const [confirmingDeleteAgentRun, setConfirmingDeleteAgentRun] =
+    useState<GraphExecutionMeta | null>(null);
+  const [confirmingDeleteAgentPreset, setConfirmingDeleteAgentPreset] =
+    useState<LibraryAgentPresetID | null>(null);
+  const [copyAgentDialogOpen, setCopyAgentDialogOpen] = useState(false);
+  const [creatingPresetFromExecutionID, setCreatingPresetFromExecutionID] =
+    useState<GraphExecutionID | null>(null);
+
+  // Set page title with agent name
+  useEffect(() => {
+    if (agent) {
+      document.title = `${agent.name} - Library - AutoGPT Platform`;
+    }
+  }, [agent]);
+
+  const openRunDraftView = useCallback(() => {
+    selectView({ type: "run" });
+  }, []);
+
+  const selectRun = useCallback((id: GraphExecutionID) => {
+    selectView({ type: "run", id });
+  }, []);
+
+  const selectPreset = useCallback((id: LibraryAgentPresetID) => {
+    selectView({ type: "preset", id });
+  }, []);
+
+  const selectSchedule = useCallback((id: ScheduleID) => {
+    selectView({ type: "schedule", id });
+  }, []);
+
+  const graphVersions = useRef<Record<number, Graph>>({});
+  const loadingGraphVersions = useRef<Record<number, Promise<Graph>>>({});
+  const getGraphVersion = useCallback(
+    async (graphID: GraphID, version: number) => {
+      if (version in graphVersions.current)
+        return graphVersions.current[version];
+      if (version in loadingGraphVersions.current)
+        return loadingGraphVersions.current[version];
+
+      const pendingGraph = api.getGraph(graphID, version).then((graph) => {
+        graphVersions.current[version] = graph;
+        return graph;
+      });
+      // Cache promise as well to avoid duplicate requests
+      loadingGraphVersions.current[version] = pendingGraph;
+      return pendingGraph;
+    },
+    [api, graphVersions, loadingGraphVersions],
+  );
+
+  const lastRefresh = useRef<number>(0);
+  const refreshPageData = useCallback(() => {
+    if (Date.now() - lastRefresh.current < 2e3) return; // 2 second debounce
+    lastRefresh.current = Date.now();
+
+    api.getLibraryAgent(agentID).then((agent) => {
+      setAgent(agent);
+
+      getGraphVersion(agent.graph_id, agent.graph_version).then(
+        (_graph) =>
+          (graph && graph.version == _graph.version) || setGraph(_graph),
+      );
+      Promise.all([
+        agentRunsQuery.refetchRuns(),
+        api.listLibraryAgentPresets({
+          graph_id: agent.graph_id,
+          page_size: 100,
+        }),
+      ]).then(([runsQueryResult, presets]) => {
+        setAgentPresets(presets.presets);
+
+        const newestAgentRunsResponse = runsQueryResult.data?.pages[0];
+        if (!newestAgentRunsResponse || newestAgentRunsResponse.status != 200)
+          return;
+        const newestAgentRuns = newestAgentRunsResponse.data.executions;
+        // Preload the corresponding graph versions for the latest 10 runs
+        new Set(
+          newestAgentRuns.slice(0, 10).map((run) => run.graph_version),
+        ).forEach((version) => getGraphVersion(agent.graph_id, version));
+      });
+    });
+  }, [api, agentID, getGraphVersion, graph]);
+
+  // On first load: select the latest run
+  useEffect(() => {
+    // Only for first load or first execution
+    if (selectedView.id || !isFirstLoad) return;
+    if (agentRuns.length == 0 && agentPresets.length == 0) return;
+
+    setIsFirstLoad(false);
+    if (agentRuns.length > 0) {
+      // select latest run
+      const latestRun = agentRuns.reduce((latest, current) => {
+        if (!latest.started_at && !current.started_at) return latest;
+        if (!latest.started_at) return current;
+        if (!current.started_at) return latest;
+        return latest.started_at > current.started_at ? latest : current;
+      }, agentRuns[0]);
+      selectRun(latestRun.id as GraphExecutionID);
+    } else {
+      // select top preset
+      const latestPreset = agentPresets.toSorted(
+        (a, b) => b.updated_at.getTime() - a.updated_at.getTime(),
+      )[0];
+      selectPreset(latestPreset.id);
+    }
+  }, [
+    isFirstLoad,
+    selectedView.id,
+    agentRuns,
+    agentPresets,
+    selectRun,
+    selectPreset,
+  ]);
+
+  useEffect(() => {
+    if (executionId) {
+      selectRun(executionId as GraphExecutionID);
+      setExecutionId(null);
+    }
+  }, [executionId, selectRun, setExecutionId]);
+
+  // Initial load
+  useEffect(() => {
+    refreshPageData();
+
+    // Show a toast when the WebSocket connection disconnects
+    let connectionToast: ReturnType<typeof toast> | null = null;
+    const cancelDisconnectHandler = api.onWebSocketDisconnect(() => {
+      connectionToast ??= toast({
+        title: "Connection to server was lost",
+        variant: "destructive",
+        description: (
+          <div className="flex items-center">
+            Trying to reconnect...
+            <LoadingSpinner className="ml-1.5 size-3.5" />
+          </div>
+        ),
+        duration: Infinity,
+        dismissable: true,
+      });
+    });
+    const cancelConnectHandler = api.onWebSocketConnect(() => {
+      if (connectionToast)
+        connectionToast.update({
+          id: connectionToast.id,
+          title: "✅ Connection re-established",
+          variant: "default",
+          description: (
+            <div className="flex items-center">
+              Refreshing data...
+              <LoadingSpinner className="ml-1.5 size-3.5" />
+            </div>
+          ),
+          duration: 2000,
+          dismissable: true,
+        });
+      connectionToast = null;
+    });
+    return () => {
+      cancelDisconnectHandler();
+      cancelConnectHandler();
+    };
+  }, []);
+
+  // Subscribe to WebSocket updates for agent runs
+  useEffect(() => {
+    if (!agent?.graph_id) return;
+
+    return api.onWebSocketConnect(() => {
+      refreshPageData(); // Sync up on (re)connect
+
+      // Subscribe to all executions for this agent
+      api.subscribeToGraphExecutions(agent.graph_id);
+    });
+  }, [api, agent?.graph_id, refreshPageData]);
+
+  // Handle execution updates
+  useEffect(() => {
+    const detachExecUpdateHandler = api.onWebSocketMessage(
+      "graph_execution_event",
+      (data) => {
+        if (data.graph_id != agent?.graph_id) return;
+
+        agentRunsQuery.upsertAgentRun(data);
+        if (data.id === selectedView.id) {
+          // Update currently viewed run
+          setSelectedRun(data);
+        }
+      },
+    );
+
+    return () => {
+      detachExecUpdateHandler();
+    };
+  }, [api, agent?.graph_id, selectedView.id]);
+
+  // Pre-load selectedRun based on selectedView
+  useEffect(() => {
+    if (selectedView.type != "run" || !selectedView.id) return;
+
+    const newSelectedRun = agentRuns.find((run) => run.id == selectedView.id);
+    if (selectedView.id !== selectedRun?.id) {
+      // Pull partial data from "cache" while waiting for the rest to load
+      setSelectedRun((newSelectedRun as GraphExecutionMeta) ?? null);
+    }
+  }, [api, selectedView, agentRuns, selectedRun?.id]);
+
+  // Load selectedRun based on selectedView; refresh on agent refresh
+  useEffect(() => {
+    if (selectedView.type != "run" || !selectedView.id || !agent) return;
+
+    api
+      .getGraphExecutionInfo(agent.graph_id, selectedView.id)
+      .then(async (run) => {
+        // Ensure corresponding graph version is available before rendering I/O
+        await getGraphVersion(run.graph_id, run.graph_version);
+        setSelectedRun(run);
+      });
+  }, [api, selectedView, agent, getGraphVersion]);
+
+  const fetchSchedules = useCallback(async () => {
+    if (!agent) return;
+
+    setSchedules(await api.listGraphExecutionSchedules(agent.graph_id));
+  }, [api, agent?.graph_id]);
+
+  useEffect(() => {
+    fetchSchedules();
+  }, [fetchSchedules]);
+
+  // =========================== ACTIONS ============================
+
+  const deleteRun = useCallback(
+    async (run: GraphExecutionMeta) => {
+      if (run.status == "RUNNING" || run.status == "QUEUED") {
+        await api.stopGraphExecution(run.graph_id, run.id);
+      }
+      await api.deleteGraphExecution(run.id);
+
+      setConfirmingDeleteAgentRun(null);
+      if (selectedView.type == "run" && selectedView.id == run.id) {
+        openRunDraftView();
+      }
+      agentRunsQuery.removeAgentRun(run.id);
+    },
+    [api, selectedView, openRunDraftView],
+  );
+
+  const deletePreset = useCallback(
+    async (presetID: LibraryAgentPresetID) => {
+      await api.deleteLibraryAgentPreset(presetID);
+
+      setConfirmingDeleteAgentPreset(null);
+      if (selectedView.type == "preset" && selectedView.id == presetID) {
+        openRunDraftView();
+      }
+      setAgentPresets((presets) => presets.filter((p) => p.id !== presetID));
+    },
+    [api, selectedView, openRunDraftView],
+  );
+
+  const deleteSchedule = useCallback(
+    async (scheduleID: ScheduleID) => {
+      const removedSchedule =
+        await api.deleteGraphExecutionSchedule(scheduleID);
+
+      setSchedules((schedules) => {
+        const newSchedules = schedules.filter(
+          (s) => s.id !== removedSchedule.id,
+        );
+        if (
+          selectedView.type == "schedule" &&
+          selectedView.id == removedSchedule.id
+        ) {
+          if (newSchedules.length > 0) {
+            // Select next schedule if available
+            selectSchedule(newSchedules[0].id);
+          } else {
+            // Reset to draft view if current schedule was deleted
+            openRunDraftView();
+          }
+        }
+        return newSchedules;
+      });
+      openRunDraftView();
+    },
+    [schedules, api],
+  );
+
+  const handleCreatePresetFromRun = useCallback(
+    async (name: string, description: string) => {
+      if (!creatingPresetFromExecutionID) return;
+
+      await api
+        .createLibraryAgentPreset({
+          name,
+          description,
+          graph_execution_id: creatingPresetFromExecutionID,
+        })
+        .then((preset) => {
+          setAgentPresets((prev) => [...prev, preset]);
+          selectPreset(preset.id);
+          setCreatingPresetFromExecutionID(null);
+        })
+        .catch(toastOnFail("create a preset"));
+    },
+    [api, creatingPresetFromExecutionID, selectPreset, toast],
+  );
+
+  const downloadGraph = useCallback(
+    async () =>
+      agent &&
+      // Export sanitized graph from backend
+      api
+        .getGraph(agent.graph_id, agent.graph_version, true)
+        .then((graph) =>
+          exportAsJSONFile(graph, `${graph.name}_v${graph.version}.json`),
+        ),
+    [api, agent],
+  );
+
+  const copyAgent = useCallback(async () => {
+    setCopyAgentDialogOpen(false);
+    api
+      .forkLibraryAgent(agentID)
+      .then((newAgent) => {
+        router.push(`/library/agents/${newAgent.id}`);
+      })
+      .catch((error) => {
+        console.error("Error copying agent:", error);
+        toast({
+          title: "Error copying agent",
+          description: `An error occurred while copying the agent: ${error.message}`,
+          variant: "destructive",
+        });
+      });
+  }, [agentID, api, router, toast]);
+
+  const agentActions: ButtonAction[] = useMemo(
+    () => [
+      {
+        label: "Customize agent",
+        href: `/build?flowID=${agent?.graph_id}&flowVersion=${agent?.graph_version}`,
+        disabled: !agent?.can_access_graph,
+      },
+      { label: "Export agent to file", callback: downloadGraph },
+      ...(!agent?.can_access_graph
+        ? [
+            {
+              label: "Edit a copy",
+              callback: () => setCopyAgentDialogOpen(true),
+            },
+          ]
+        : []),
+      {
+        label: "Delete agent",
+        callback: () => setAgentDeleteDialogOpen(true),
+      },
+    ],
+    [agent, downloadGraph],
+  );
+
+  const runGraph =
+    graphVersions.current[selectedRun?.graph_version ?? 0] ?? graph;
+
+  const onCreateSchedule = useCallback(
+    (schedule: Schedule) => {
+      setSchedules((prev) => [...prev, schedule]);
+      selectSchedule(schedule.id);
+    },
+    [selectView],
+  );
+
+  const onCreatePreset = useCallback(
+    (preset: LibraryAgentPreset) => {
+      setAgentPresets((prev) => [...prev, preset]);
+      selectPreset(preset.id);
+    },
+    [selectPreset],
+  );
+
+  const onUpdatePreset = useCallback(
+    (updated: LibraryAgentPreset) => {
+      setAgentPresets((prev) =>
+        prev.map((p) => (p.id === updated.id ? updated : p)),
+      );
+      selectPreset(updated.id);
+    },
+    [selectPreset],
+  );
+
+  if (!agent || !graph) {
+    return <LoadingBox className="h-[90vh]" />;
+  }
+
+  return (
+    <div className="container justify-stretch p-0 pt-16 lg:flex">
+      {/* Sidebar w/ list of runs */}
+      {/* TODO: render this below header in sm and md layouts */}
+      <AgentRunsSelectorList
+        className="agpt-div w-full border-b pb-2 lg:w-auto lg:border-b-0 lg:border-r lg:pb-0"
+        agent={agent}
+        agentRunsQuery={agentRunsQuery}
+        agentPresets={agentPresets}
+        schedules={schedules}
+        selectedView={selectedView}
+        onSelectRun={selectRun}
+        onSelectPreset={selectPreset}
+        onSelectSchedule={selectSchedule}
+        onSelectDraftNewRun={openRunDraftView}
+        doDeleteRun={setConfirmingDeleteAgentRun}
+        doDeletePreset={setConfirmingDeleteAgentPreset}
+        doDeleteSchedule={deleteSchedule}
+        doCreatePresetFromRun={setCreatingPresetFromExecutionID}
+      />
+
+      <div className="flex-1">
+        {/* Header */}
+        <div className="agpt-div w-full border-b">
+          <h1
+            data-testid="agent-title"
+            className="font-poppins text-3xl font-medium"
+          >
+            {
+              agent.name /* TODO: use dynamic/custom run title - https://github.com/Significant-Gravitas/AutoGPT/issues/9184 */
+            }
+          </h1>
+        </div>
+
+        {/* Run / Schedule views */}
+        {(selectedView.type == "run" && selectedView.id ? (
+          selectedRun && runGraph ? (
+            <AgentRunDetailsView
+              agent={agent}
+              graph={runGraph}
+              run={selectedRun}
+              agentActions={agentActions}
+              onRun={selectRun}
+              doDeleteRun={() => setConfirmingDeleteAgentRun(selectedRun)}
+              doCreatePresetFromRun={() =>
+                setCreatingPresetFromExecutionID(selectedRun.id)
+              }
+            />
+          ) : null
+        ) : selectedView.type == "run" ? (
+          /* Draft new runs / Create new presets */
+          <AgentRunDraftView
+            graph={graph}
+            onRun={selectRun}
+            onCreateSchedule={onCreateSchedule}
+            onCreatePreset={onCreatePreset}
+            agentActions={agentActions}
+            recommendedScheduleCron={agent?.recommended_schedule_cron || null}
+          />
+        ) : selectedView.type == "preset" ? (
+          /* Edit & update presets */
+          <AgentRunDraftView
+            graph={graph}
+            agentPreset={
+              agentPresets.find((preset) => preset.id == selectedView.id)!
+            }
+            onRun={selectRun}
+            recommendedScheduleCron={agent?.recommended_schedule_cron || null}
+            onCreateSchedule={onCreateSchedule}
+            onUpdatePreset={onUpdatePreset}
+            doDeletePreset={setConfirmingDeleteAgentPreset}
+            agentActions={agentActions}
+          />
+        ) : selectedView.type == "schedule" ? (
+          selectedSchedule &&
+          graph && (
+            <AgentScheduleDetailsView
+              graph={graph}
+              schedule={selectedSchedule}
+              // agent={agent}
+              agentActions={agentActions}
+              onForcedRun={selectRun}
+              doDeleteSchedule={deleteSchedule}
+            />
+          )
+        ) : null) || <LoadingBox className="h-[70vh]" />}
+
+        <DeleteConfirmDialog
+          entityType="agent"
+          open={agentDeleteDialogOpen}
+          onOpenChange={setAgentDeleteDialogOpen}
+          onDoDelete={() =>
+            agent &&
+            api.deleteLibraryAgent(agent.id).then(() => router.push("/library"))
+          }
+        />
+
+        <DeleteConfirmDialog
+          entityType="agent run"
+          open={!!confirmingDeleteAgentRun}
+          onOpenChange={(open) => !open && setConfirmingDeleteAgentRun(null)}
+          onDoDelete={() =>
+            confirmingDeleteAgentRun && deleteRun(confirmingDeleteAgentRun)
+          }
+        />
+        <DeleteConfirmDialog
+          entityType={agent.has_external_trigger ? "trigger" : "agent preset"}
+          open={!!confirmingDeleteAgentPreset}
+          onOpenChange={(open) => !open && setConfirmingDeleteAgentPreset(null)}
+          onDoDelete={() =>
+            confirmingDeleteAgentPreset &&
+            deletePreset(confirmingDeleteAgentPreset)
+          }
+        />
+        {/* Copy agent confirmation dialog */}
+        <Dialog
+          onOpenChange={setCopyAgentDialogOpen}
+          open={copyAgentDialogOpen}
+        >
+          <DialogContent>
+            <DialogHeader>
+              <DialogTitle>You&apos;re making an editable copy</DialogTitle>
+              <DialogDescription className="pt-2">
+                The original Marketplace agent stays the same and cannot be
+                edited. We&apos;ll save a new version of this agent to your
+                Library. From there, you can customize it however you&apos;d
+                like by clicking &quot;Customize agent&quot; — this will open
+                the builder where you can see and modify the inner workings.
+              </DialogDescription>
+            </DialogHeader>
+            <DialogFooter className="justify-end">
+              <Button
+                type="button"
+                variant="outline"
+                onClick={() => setCopyAgentDialogOpen(false)}
+              >
+                Cancel
+              </Button>
+              <Button type="button" onClick={copyAgent}>
+                Continue
+              </Button>
+            </DialogFooter>
+          </DialogContent>
+        </Dialog>
+        <CreatePresetDialog
+          open={!!creatingPresetFromExecutionID}
+          onOpenChange={() => setCreatingPresetFromExecutionID(null)}
+          onConfirm={handleCreatePresetFromRun}
+        />
+      </div>
+    </div>
+  );
+}

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

@@ -0,0 +1,445 @@
+"use client";
+import { format, formatDistanceToNow, formatDistanceStrict } from "date-fns";
+import React, { useCallback, useMemo, useEffect } from "react";
+
+import {
+  Graph,
+  GraphExecution,
+  GraphExecutionID,
+  GraphExecutionMeta,
+  LibraryAgent,
+} from "@/lib/autogpt-server-api";
+import { useBackendAPI } from "@/lib/autogpt-server-api/context";
+
+import ActionButtonGroup from "@/components/__legacy__/action-button-group";
+import type { ButtonAction } from "@/components/__legacy__/types";
+import {
+  Card,
+  CardContent,
+  CardHeader,
+  CardTitle,
+} from "@/components/__legacy__/ui/card";
+import {
+  IconRefresh,
+  IconSquare,
+  IconCircleAlert,
+} from "@/components/__legacy__/ui/icons";
+import { Input } from "@/components/__legacy__/ui/input";
+import LoadingBox from "@/components/__legacy__/ui/loading";
+import {
+  Tooltip,
+  TooltipContent,
+  TooltipProvider,
+  TooltipTrigger,
+} from "@/components/atoms/Tooltip/BaseTooltip";
+import { useToastOnFail } from "@/components/molecules/Toast/use-toast";
+
+import { AgentRunStatus, agentRunStatusMap } from "./agent-run-status-chip";
+import useCredits from "@/hooks/useCredits";
+import { AgentRunOutputView } from "./agent-run-output-view";
+import { analytics } from "@/services/analytics";
+import { PendingReviewsList } from "@/components/organisms/PendingReviewsList/PendingReviewsList";
+import { usePendingReviewsForExecution } from "@/hooks/usePendingReviews";
+
+export function AgentRunDetailsView({
+  agent,
+  graph,
+  run,
+  agentActions,
+  onRun,
+  doDeleteRun,
+  doCreatePresetFromRun,
+}: {
+  agent: LibraryAgent;
+  graph: Graph;
+  run: GraphExecution | GraphExecutionMeta;
+  agentActions: ButtonAction[];
+  onRun: (runID: GraphExecutionID) => void;
+  doDeleteRun: () => void;
+  doCreatePresetFromRun: () => void;
+}): React.ReactNode {
+  const api = useBackendAPI();
+  const { formatCredits } = useCredits();
+
+  const runStatus: AgentRunStatus = useMemo(
+    () => agentRunStatusMap[run.status],
+    [run],
+  );
+
+  const {
+    pendingReviews,
+    isLoading: reviewsLoading,
+    refetch: refetchReviews,
+  } = usePendingReviewsForExecution(run.id);
+
+  const toastOnFail = useToastOnFail();
+
+  // Refetch pending reviews when execution status changes to REVIEW
+  useEffect(() => {
+    if (runStatus === "review" && run.id) {
+      refetchReviews();
+    }
+  }, [runStatus, run.id, refetchReviews]);
+
+  const infoStats: { label: string; value: React.ReactNode }[] = useMemo(() => {
+    if (!run) return [];
+    return [
+      {
+        label: "Status",
+        value: runStatus.charAt(0).toUpperCase() + runStatus.slice(1),
+      },
+      {
+        label: "Started",
+        value: run.started_at
+          ? `${formatDistanceToNow(run.started_at, { addSuffix: true })}, ${format(run.started_at, "HH:mm")}`
+          : "—",
+      },
+      ...(run.stats
+        ? [
+            {
+              label: "Duration",
+              value: formatDistanceStrict(0, run.stats.duration * 1000),
+            },
+            { label: "Steps", value: run.stats.node_exec_count },
+            { label: "Cost", value: formatCredits(run.stats.cost) },
+          ]
+        : []),
+    ];
+  }, [run, runStatus, formatCredits]);
+
+  const agentRunInputs:
+    | Record<
+        string,
+        {
+          title?: string;
+          /* type: BlockIOSubType; */
+          value: string | number | undefined;
+        }
+      >
+    | undefined = useMemo(() => {
+    if (!run.inputs) return undefined;
+    // TODO: show (link to) preset - https://github.com/Significant-Gravitas/AutoGPT/issues/9168
+
+    // Add type info from agent input schema
+    return Object.fromEntries(
+      Object.entries(run.inputs).map(([k, v]) => [
+        k,
+        {
+          title: graph.input_schema.properties[k]?.title,
+          // type: graph.input_schema.properties[k].type, // TODO: implement typed graph inputs
+          value: typeof v == "object" ? JSON.stringify(v, undefined, 2) : v,
+        },
+      ]),
+    );
+  }, [graph, run]);
+
+  const runAgain = useCallback(() => {
+    if (
+      !run.inputs ||
+      !(graph.credentials_input_schema?.required ?? []).every(
+        (k) => k in (run.credential_inputs ?? {}),
+      )
+    )
+      return;
+
+    if (run.preset_id) {
+      return api
+        .executeLibraryAgentPreset(
+          run.preset_id,
+          run.inputs!,
+          run.credential_inputs!,
+        )
+        .then(({ id }) => {
+          analytics.sendDatafastEvent("run_agent", {
+            name: graph.name,
+            id: graph.id,
+          });
+          onRun(id);
+        })
+        .catch(toastOnFail("execute agent preset"));
+    }
+
+    return api
+      .executeGraph(
+        graph.id,
+        graph.version,
+        run.inputs!,
+        run.credential_inputs!,
+        "library",
+      )
+      .then(({ id }) => {
+        analytics.sendDatafastEvent("run_agent", {
+          name: graph.name,
+          id: graph.id,
+        });
+        onRun(id);
+      })
+      .catch(toastOnFail("execute agent"));
+  }, [api, graph, run, onRun, toastOnFail]);
+
+  const stopRun = useCallback(
+    () => api.stopGraphExecution(graph.id, run.id),
+    [api, graph.id, run.id],
+  );
+
+  const agentRunOutputs:
+    | Record<
+        string,
+        {
+          title?: string;
+          /* type: BlockIOSubType; */
+          values: Array<React.ReactNode>;
+        }
+      >
+    | null
+    | undefined = useMemo(() => {
+    if (!("outputs" in run)) return undefined;
+    if (!["running", "success", "failed", "stopped"].includes(runStatus))
+      return null;
+
+    // Add type info from agent input schema
+    return Object.fromEntries(
+      Object.entries(run.outputs).map(([k, vv]) => [
+        k,
+        {
+          title: graph.output_schema.properties[k].title,
+          /* type: agent.output_schema.properties[k].type */
+          values: vv.map((v) =>
+            typeof v == "object" ? JSON.stringify(v, undefined, 2) : v,
+          ),
+        },
+      ]),
+    );
+  }, [graph, run, runStatus]);
+
+  const runActions: ButtonAction[] = useMemo(
+    () => [
+      ...(["running", "queued"].includes(runStatus)
+        ? ([
+            {
+              label: (
+                <>
+                  <IconSquare className="mr-2 size-4" />
+                  Stop run
+                </>
+              ),
+              variant: "secondary",
+              callback: stopRun,
+            },
+          ] satisfies ButtonAction[])
+        : []),
+      ...(["success", "failed", "stopped"].includes(runStatus) &&
+      !graph.has_external_trigger &&
+      (graph.credentials_input_schema?.required ?? []).every(
+        (k) => k in (run.credential_inputs ?? {}),
+      )
+        ? [
+            {
+              label: (
+                <>
+                  <IconRefresh className="mr-2 size-4" />
+                  Run again
+                </>
+              ),
+              callback: runAgain,
+              dataTestId: "run-again-button",
+            },
+          ]
+        : []),
+      ...(agent.can_access_graph
+        ? [
+            {
+              label: "Open run in builder",
+              href: `/build?flowID=${run.graph_id}&flowVersion=${run.graph_version}&flowExecutionID=${run.id}`,
+            },
+          ]
+        : []),
+      { label: "Create preset from run", callback: doCreatePresetFromRun },
+      { label: "Delete run", variant: "secondary", callback: doDeleteRun },
+    ],
+    [
+      runStatus,
+      runAgain,
+      stopRun,
+      doDeleteRun,
+      doCreatePresetFromRun,
+      graph.has_external_trigger,
+      graph.credentials_input_schema?.required,
+      agent.can_access_graph,
+      run.graph_id,
+      run.graph_version,
+      run.id,
+    ],
+  );
+
+  return (
+    <div className="agpt-div flex gap-6">
+      <div className="flex flex-1 flex-col gap-4">
+        <Card className="agpt-box">
+          <CardHeader>
+            <CardTitle className="font-poppins text-lg">Info</CardTitle>
+          </CardHeader>
+
+          <CardContent>
+            <div className="flex justify-stretch gap-4">
+              {infoStats.map(({ label, value }) => (
+                <div key={label} className="flex-1">
+                  <p className="text-sm font-medium text-black">{label}</p>
+                  <p className="text-sm text-neutral-600">{value}</p>
+                </div>
+              ))}
+            </div>
+            {run.status === "FAILED" && (
+              <div className="mt-4 rounded-md border border-red-200 bg-red-50 p-3 dark:border-red-800 dark:bg-red-900/20">
+                <p className="text-sm text-red-800 dark:text-red-200">
+                  <strong>Error:</strong>{" "}
+                  {run.stats?.error ||
+                    "The execution failed due to an internal error. You can re-run the agent to retry."}
+                </p>
+              </div>
+            )}
+          </CardContent>
+        </Card>
+
+        {/* Smart Agent Execution Summary */}
+        {run.stats?.activity_status && (
+          <Card className="agpt-box">
+            <CardHeader>
+              <CardTitle className="flex items-center gap-2 font-poppins text-lg">
+                Task Summary
+                <TooltipProvider>
+                  <Tooltip>
+                    <TooltipTrigger asChild>
+                      <IconCircleAlert className="size-4 cursor-help text-neutral-500 hover:text-neutral-700" />
+                    </TooltipTrigger>
+                    <TooltipContent>
+                      <p className="max-w-xs">
+                        This AI-generated summary describes how the agent
+                        handled your task. It’s an experimental feature and may
+                        occasionally be inaccurate.
+                      </p>
+                    </TooltipContent>
+                  </Tooltip>
+                </TooltipProvider>
+              </CardTitle>
+            </CardHeader>
+            <CardContent className="space-y-4">
+              <p className="text-sm leading-relaxed text-neutral-700">
+                {run.stats.activity_status}
+              </p>
+
+              {/* Correctness Score */}
+              {typeof run.stats.correctness_score === "number" && (
+                <div className="flex items-center gap-3 rounded-lg bg-neutral-50 p-3">
+                  <div className="flex items-center gap-2">
+                    <span className="text-sm font-medium text-neutral-600">
+                      Success Estimate:
+                    </span>
+                    <div className="flex items-center gap-2">
+                      <div className="relative h-2 w-16 overflow-hidden rounded-full bg-neutral-200">
+                        <div
+                          className={`h-full transition-all ${
+                            run.stats.correctness_score >= 0.8
+                              ? "bg-green-500"
+                              : run.stats.correctness_score >= 0.6
+                                ? "bg-yellow-500"
+                                : run.stats.correctness_score >= 0.4
+                                  ? "bg-orange-500"
+                                  : "bg-red-500"
+                          }`}
+                          style={{
+                            width: `${Math.round(run.stats.correctness_score * 100)}%`,
+                          }}
+                        />
+                      </div>
+                      <span className="text-sm font-medium">
+                        {Math.round(run.stats.correctness_score * 100)}%
+                      </span>
+                    </div>
+                  </div>
+                  <TooltipProvider>
+                    <Tooltip>
+                      <TooltipTrigger asChild>
+                        <IconCircleAlert className="size-4 cursor-help text-neutral-400 hover:text-neutral-600" />
+                      </TooltipTrigger>
+                      <TooltipContent>
+                        <p className="max-w-xs">
+                          AI-generated estimate of how well this execution
+                          achieved its intended purpose. This score indicates
+                          {run.stats.correctness_score >= 0.8
+                            ? " the agent was highly successful."
+                            : run.stats.correctness_score >= 0.6
+                              ? " the agent was mostly successful with minor issues."
+                              : run.stats.correctness_score >= 0.4
+                                ? " the agent was partially successful with some gaps."
+                                : " the agent had limited success with significant issues."}
+                        </p>
+                      </TooltipContent>
+                    </Tooltip>
+                  </TooltipProvider>
+                </div>
+              )}
+            </CardContent>
+          </Card>
+        )}
+
+        {agentRunOutputs !== null && (
+          <AgentRunOutputView agentRunOutputs={agentRunOutputs} />
+        )}
+
+        {/* Pending Reviews Section */}
+        {runStatus === "review" && (
+          <Card className="agpt-box">
+            <CardHeader>
+              <CardTitle className="font-poppins text-lg">
+                Pending Reviews ({pendingReviews.length})
+              </CardTitle>
+            </CardHeader>
+            <CardContent>
+              {reviewsLoading ? (
+                <LoadingBox spinnerSize={12} className="h-24" />
+              ) : pendingReviews.length > 0 ? (
+                <PendingReviewsList
+                  reviews={pendingReviews}
+                  onReviewComplete={refetchReviews}
+                  emptyMessage="No pending reviews for this execution"
+                />
+              ) : (
+                <div className="py-4 text-neutral-600">
+                  No pending reviews for this execution
+                </div>
+              )}
+            </CardContent>
+          </Card>
+        )}
+
+        <Card className="agpt-box">
+          <CardHeader>
+            <CardTitle className="font-poppins text-lg">Input</CardTitle>
+          </CardHeader>
+          <CardContent className="flex flex-col gap-4">
+            {agentRunInputs !== undefined ? (
+              Object.entries(agentRunInputs).map(([key, { title, value }]) => (
+                <div key={key} className="flex flex-col gap-1.5">
+                  <label className="text-sm font-medium">{title || key}</label>
+                  <Input value={value} className="rounded-full" disabled />
+                </div>
+              ))
+            ) : (
+              <LoadingBox spinnerSize={12} className="h-24" />
+            )}
+          </CardContent>
+        </Card>
+      </div>
+
+      {/* Run / Agent Actions */}
+      <aside className="w-48 xl:w-56">
+        <div className="flex flex-col gap-8">
+          <ActionButtonGroup title="Run actions" actions={runActions} />
+
+          <ActionButtonGroup title="Agent actions" actions={agentActions} />
+        </div>
+      </aside>
+    </div>
+  );
+}

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

@@ -20,7 +20,7 @@ import {
 import { useBackendAPI } from "@/lib/autogpt-server-api/context";
 
 import { RunAgentInputs } from "@/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentInputs/RunAgentInputs";
-import { ScheduleTaskDialog } from "@/components/contextual/CronScheduler/cron-scheduler-dialog";
+import { ScheduleTaskDialog } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/cron-scheduler-dialog";
 import ActionButtonGroup from "@/components/__legacy__/action-button-group";
 import type { ButtonAction } from "@/components/__legacy__/types";
 import {
@@ -53,10 +53,7 @@ import { ClockIcon, CopyIcon, InfoIcon } from "@phosphor-icons/react";
 import { CalendarClockIcon, Trash2Icon } from "lucide-react";
 
 import { analytics } from "@/services/analytics";
-import {
-  AgentStatus,
-  AgentStatusChip,
-} from "@/app/(platform)/build/components/legacy-builder/agent-status-chip";
+import { AgentStatus, AgentStatusChip } from "./agent-status-chip";
 
 export function AgentRunDraftView({
   graph,

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

@@ -0,0 +1,178 @@
+"use client";
+
+import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
+import React, { useMemo } from "react";
+
+import {
+  Card,
+  CardContent,
+  CardHeader,
+  CardTitle,
+} from "@/components/__legacy__/ui/card";
+
+import LoadingBox from "@/components/__legacy__/ui/loading";
+import type { OutputMetadata } from "../../../../../../../../components/contextual/OutputRenderers";
+import {
+  globalRegistry,
+  OutputActions,
+  OutputItem,
+} from "../../../../../../../../components/contextual/OutputRenderers";
+
+export function AgentRunOutputView({
+  agentRunOutputs,
+}: {
+  agentRunOutputs:
+    | Record<
+        string,
+        {
+          title?: string;
+          /* type: BlockIOSubType; */
+          values: Array<React.ReactNode>;
+        }
+      >
+    | undefined;
+}) {
+  const enableEnhancedOutputHandling = useGetFlag(
+    Flag.ENABLE_ENHANCED_OUTPUT_HANDLING,
+  );
+
+  // Prepare items for the renderer system
+  const outputItems = useMemo(() => {
+    if (!agentRunOutputs) return [];
+
+    const items: Array<{
+      key: string;
+      label: string;
+      value: unknown;
+      metadata?: OutputMetadata;
+      renderer: any;
+    }> = [];
+
+    Object.entries(agentRunOutputs).forEach(([key, { title, values }]) => {
+      values.forEach((value, index) => {
+        // Enhanced metadata extraction
+        const metadata: OutputMetadata = {};
+
+        // Type guard to safely access properties
+        if (
+          typeof value === "object" &&
+          value !== null &&
+          !React.isValidElement(value)
+        ) {
+          const objValue = value as any;
+          if (objValue.type) metadata.type = objValue.type;
+          if (objValue.mimeType) metadata.mimeType = objValue.mimeType;
+          if (objValue.filename) metadata.filename = objValue.filename;
+        }
+
+        const renderer = globalRegistry.getRenderer(value, metadata);
+        if (renderer) {
+          items.push({
+            key: `${key}-${index}`,
+            label: index === 0 ? title || key : "",
+            value,
+            metadata,
+            renderer,
+          });
+        } else {
+          const textRenderer = globalRegistry
+            .getAllRenderers()
+            .find((r) => r.name === "TextRenderer");
+          if (textRenderer) {
+            items.push({
+              key: `${key}-${index}`,
+              label: index === 0 ? title || key : "",
+              value: JSON.stringify(value, null, 2),
+              metadata,
+              renderer: textRenderer,
+            });
+          }
+        }
+      });
+    });
+
+    return items;
+  }, [agentRunOutputs]);
+
+  return (
+    <>
+      {enableEnhancedOutputHandling ? (
+        <Card className="agpt-box" style={{ maxWidth: "950px" }}>
+          <CardHeader>
+            <div className="flex items-center justify-between">
+              <CardTitle className="font-poppins text-lg">Output</CardTitle>
+              {outputItems.length > 0 && (
+                <OutputActions
+                  items={outputItems.map((item) => ({
+                    value: item.value,
+                    metadata: item.metadata,
+                    renderer: item.renderer,
+                  }))}
+                />
+              )}
+            </div>
+          </CardHeader>
+
+          <CardContent
+            className="flex flex-col gap-4"
+            style={{ maxWidth: "660px" }}
+          >
+            {agentRunOutputs !== undefined ? (
+              outputItems.length > 0 ? (
+                outputItems.map((item) => (
+                  <OutputItem
+                    key={item.key}
+                    value={item.value}
+                    metadata={item.metadata}
+                    renderer={item.renderer}
+                    label={item.label}
+                  />
+                ))
+              ) : (
+                <p className="text-sm text-muted-foreground">
+                  No outputs to display
+                </p>
+              )
+            ) : (
+              <LoadingBox spinnerSize={12} className="h-24" />
+            )}
+          </CardContent>
+        </Card>
+      ) : (
+        <Card className="agpt-box" style={{ maxWidth: "950px" }}>
+          <CardHeader>
+            <CardTitle className="font-poppins text-lg">Output</CardTitle>
+          </CardHeader>
+
+          <CardContent
+            className="flex flex-col gap-4"
+            style={{ maxWidth: "660px" }}
+          >
+            {agentRunOutputs !== undefined ? (
+              Object.entries(agentRunOutputs).map(
+                ([key, { title, values }]) => (
+                  <div key={key} className="flex flex-col gap-1.5">
+                    <label className="text-sm font-medium">
+                      {title || key}
+                    </label>
+                    {values.map((value, i) => (
+                      <p
+                        className="resize-none overflow-x-auto whitespace-pre-wrap break-words border-none text-sm text-neutral-700 disabled:cursor-not-allowed"
+                        key={i}
+                      >
+                        {value}
+                      </p>
+                    ))}
+                    {/* TODO: pretty type-dependent rendering */}
+                  </div>
+                ),
+              )
+            ) : (
+              <LoadingBox spinnerSize={12} className="h-24" />
+            )}
+          </CardContent>
+        </Card>
+      )}
+    </>
+  );
+}

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

@@ -0,0 +1,68 @@
+import React from "react";
+
+import { Badge } from "@/components/__legacy__/ui/badge";
+
+import { GraphExecutionMeta } from "@/lib/autogpt-server-api/types";
+
+export type AgentRunStatus =
+  | "success"
+  | "failed"
+  | "queued"
+  | "running"
+  | "stopped"
+  | "scheduled"
+  | "draft"
+  | "review";
+
+export const agentRunStatusMap: Record<
+  GraphExecutionMeta["status"],
+  AgentRunStatus
+> = {
+  INCOMPLETE: "draft",
+  COMPLETED: "success",
+  FAILED: "failed",
+  QUEUED: "queued",
+  RUNNING: "running",
+  TERMINATED: "stopped",
+  REVIEW: "review",
+};
+
+const statusData: Record<
+  AgentRunStatus,
+  { label: string; variant: keyof typeof statusStyles }
+> = {
+  success: { label: "Success", variant: "success" },
+  running: { label: "Running", variant: "info" },
+  failed: { label: "Failed", variant: "destructive" },
+  queued: { label: "Queued", variant: "warning" },
+  draft: { label: "Draft", variant: "secondary" },
+  stopped: { label: "Stopped", variant: "secondary" },
+  scheduled: { label: "Scheduled", variant: "secondary" },
+  review: { label: "In Review", variant: "warning" },
+};
+
+const statusStyles = {
+  success:
+    "bg-green-100 text-green-800 hover:bg-green-100 hover:text-green-800",
+  destructive: "bg-red-100 text-red-800 hover:bg-red-100 hover:text-red-800",
+  warning:
+    "bg-yellow-100 text-yellow-800 hover:bg-yellow-100 hover:text-yellow-800",
+  info: "bg-blue-100 text-blue-800 hover:bg-blue-100 hover:text-blue-800",
+  secondary:
+    "bg-slate-100 text-slate-800 hover:bg-slate-100 hover:text-slate-800",
+};
+
+export function AgentRunStatusChip({
+  status,
+}: {
+  status: AgentRunStatus;
+}): React.ReactElement {
+  return (
+    <Badge
+      variant="secondary"
+      className={`text-xs font-medium ${statusStyles[statusData[status]?.variant]} rounded-[45px] px-[9px] py-[3px]`}
+    >
+      {statusData[status]?.label}
+    </Badge>
+  );
+}

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

@@ -0,0 +1,130 @@
+import React from "react";
+import { formatDistanceToNow, isPast } from "date-fns";
+
+import { cn } from "@/lib/utils";
+
+import { Link2Icon, Link2OffIcon, MoreVertical } from "lucide-react";
+import { Card, CardContent } from "@/components/__legacy__/ui/card";
+import { Button } from "@/components/__legacy__/ui/button";
+import {
+  DropdownMenu,
+  DropdownMenuContent,
+  DropdownMenuItem,
+  DropdownMenuTrigger,
+} from "@/components/__legacy__/ui/dropdown-menu";
+
+import { AgentStatus, AgentStatusChip } from "./agent-status-chip";
+import { AgentRunStatus, AgentRunStatusChip } from "./agent-run-status-chip";
+import { PushPinSimpleIcon } from "@phosphor-icons/react";
+
+export type AgentRunSummaryProps = (
+  | {
+      type: "run";
+      status: AgentRunStatus;
+    }
+  | {
+      type: "preset";
+      status?: undefined;
+    }
+  | {
+      type: "preset.triggered";
+      status: AgentStatus;
+    }
+  | {
+      type: "schedule";
+      status: "scheduled";
+    }
+) & {
+  title: string;
+  timestamp?: number | Date;
+  selected?: boolean;
+  onClick?: () => void;
+  // onRename: () => void;
+  onDelete: () => void;
+  onPinAsPreset?: () => void;
+  className?: string;
+};
+
+export function AgentRunSummaryCard({
+  type,
+  status,
+  title,
+  timestamp,
+  selected = false,
+  onClick,
+  // onRename,
+  onDelete,
+  onPinAsPreset,
+  className,
+}: AgentRunSummaryProps): React.ReactElement {
+  return (
+    <Card
+      className={cn(
+        "agpt-rounded-card cursor-pointer border-zinc-300",
+        selected ? "agpt-card-selected" : "",
+        className,
+      )}
+      onClick={onClick}
+    >
+      <CardContent className="relative p-2.5 lg:p-4">
+        {(type == "run" || type == "schedule") && (
+          <AgentRunStatusChip status={status} />
+        )}
+        {type == "preset" && (
+          <div className="flex items-center text-sm font-medium text-neutral-700">
+            <PushPinSimpleIcon className="mr-1 size-4 text-foreground" /> Preset
+          </div>
+        )}
+        {type == "preset.triggered" && (
+          <div className="flex items-center justify-between">
+            <AgentStatusChip status={status} />
+
+            <div className="flex items-center text-sm font-medium text-neutral-700">
+              {status == "inactive" ? (
+                <Link2OffIcon className="mr-1 size-4 text-foreground" />
+              ) : (
+                <Link2Icon className="mr-1 size-4 text-foreground" />
+              )}{" "}
+              Trigger
+            </div>
+          </div>
+        )}
+
+        <div className="mt-5 flex items-center justify-between">
+          <h3 className="truncate pr-2 text-base font-medium text-neutral-900">
+            {title}
+          </h3>
+
+          <DropdownMenu>
+            <DropdownMenuTrigger asChild>
+              <Button variant="ghost" className="h-5 w-5 p-0">
+                <MoreVertical className="h-5 w-5" />
+              </Button>
+            </DropdownMenuTrigger>
+            <DropdownMenuContent>
+              {onPinAsPreset && (
+                <DropdownMenuItem onClick={onPinAsPreset}>
+                  Pin as a preset
+                </DropdownMenuItem>
+              )}
+
+              {/* <DropdownMenuItem onClick={onRename}>Rename</DropdownMenuItem> */}
+
+              <DropdownMenuItem onClick={onDelete}>Delete</DropdownMenuItem>
+            </DropdownMenuContent>
+          </DropdownMenu>
+        </div>
+
+        {timestamp && (
+          <p
+            className="mt-1 text-sm font-normal text-neutral-500"
+            title={new Date(timestamp).toString()}
+          >
+            {isPast(timestamp) ? "Ran" : "Runs in"}{" "}
+            {formatDistanceToNow(timestamp, { addSuffix: true })}
+          </p>
+        )}
+      </CardContent>
+    </Card>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-runs-selector-list.tsx

@@ -0,0 +1,237 @@
+"use client";
+import { Plus } from "lucide-react";
+import React, { useEffect, useState } from "react";
+
+import {
+  GraphExecutionID,
+  GraphExecutionMeta,
+  LibraryAgent,
+  LibraryAgentPreset,
+  LibraryAgentPresetID,
+  Schedule,
+  ScheduleID,
+} from "@/lib/autogpt-server-api";
+import { cn } from "@/lib/utils";
+
+import { Badge } from "@/components/__legacy__/ui/badge";
+import { Button } from "@/components/atoms/Button/Button";
+import LoadingBox, { LoadingSpinner } from "@/components/__legacy__/ui/loading";
+import { Separator } from "@/components/__legacy__/ui/separator";
+import { ScrollArea } from "@/components/__legacy__/ui/scroll-area";
+import { InfiniteScroll } from "@/components/contextual/InfiniteScroll/InfiniteScroll";
+import { AgentRunsQuery } from "../use-agent-runs";
+import { agentRunStatusMap } from "./agent-run-status-chip";
+import { AgentRunSummaryCard } from "./agent-run-summary-card";
+
+interface AgentRunsSelectorListProps {
+  agent: LibraryAgent;
+  agentRunsQuery: AgentRunsQuery;
+  agentPresets: LibraryAgentPreset[];
+  schedules: Schedule[];
+  selectedView: { type: "run" | "preset" | "schedule"; id?: string };
+  allowDraftNewRun?: boolean;
+  onSelectRun: (id: GraphExecutionID) => void;
+  onSelectPreset: (preset: LibraryAgentPresetID) => void;
+  onSelectSchedule: (id: ScheduleID) => void;
+  onSelectDraftNewRun: () => void;
+  doDeleteRun: (id: GraphExecutionMeta) => void;
+  doDeletePreset: (id: LibraryAgentPresetID) => void;
+  doDeleteSchedule: (id: ScheduleID) => void;
+  doCreatePresetFromRun?: (id: GraphExecutionID) => void;
+  className?: string;
+}
+
+export function AgentRunsSelectorList({
+  agent,
+  agentRunsQuery: {
+    agentRuns,
+    agentRunCount,
+    agentRunsLoading,
+    hasMoreRuns,
+    fetchMoreRuns,
+    isFetchingMoreRuns,
+  },
+  agentPresets,
+  schedules,
+  selectedView,
+  allowDraftNewRun = true,
+  onSelectRun,
+  onSelectPreset,
+  onSelectSchedule,
+  onSelectDraftNewRun,
+  doDeleteRun,
+  doDeletePreset,
+  doDeleteSchedule,
+  doCreatePresetFromRun,
+  className,
+}: AgentRunsSelectorListProps): React.ReactElement {
+  const [activeListTab, setActiveListTab] = useState<"runs" | "scheduled">(
+    "runs",
+  );
+
+  useEffect(() => {
+    if (selectedView.type === "schedule") {
+      setActiveListTab("scheduled");
+    } else {
+      setActiveListTab("runs");
+    }
+  }, [selectedView]);
+
+  const listItemClasses = "h-28 w-72 lg:w-full lg:h-32";
+
+  return (
+    <aside className={cn("flex flex-col gap-4", className)}>
+      {allowDraftNewRun ? (
+        <Button
+          className={"mb-4 hidden lg:flex"}
+          onClick={onSelectDraftNewRun}
+          leftIcon={<Plus className="h-6 w-6" />}
+        >
+          New {agent.has_external_trigger ? "trigger" : "run"}
+        </Button>
+      ) : null}
+
+      <div className="flex gap-2">
+        <Badge
+          variant={activeListTab === "runs" ? "secondary" : "outline"}
+          className="cursor-pointer gap-2 rounded-full text-base"
+          onClick={() => setActiveListTab("runs")}
+        >
+          <span>Runs</span>
+          <span className="text-neutral-600">
+            {agentRunCount ?? <LoadingSpinner className="size-4" />}
+          </span>
+        </Badge>
+
+        <Badge
+          variant={activeListTab === "scheduled" ? "secondary" : "outline"}
+          className="cursor-pointer gap-2 rounded-full text-base"
+          onClick={() => setActiveListTab("scheduled")}
+        >
+          <span>Scheduled</span>
+          <span className="text-neutral-600">{schedules.length}</span>
+        </Badge>
+      </div>
+
+      {/* Runs / Schedules list */}
+      {agentRunsLoading && activeListTab === "runs" ? (
+        <LoadingBox className="h-28 w-full lg:h-[calc(100vh-300px)] lg:w-72 xl:w-80" />
+      ) : (
+        <ScrollArea
+          className="w-full lg:h-[calc(100vh-300px)] lg:w-72 xl:w-80"
+          orientation={window.innerWidth >= 1024 ? "vertical" : "horizontal"}
+        >
+          <InfiniteScroll
+            direction={window.innerWidth >= 1024 ? "vertical" : "horizontal"}
+            hasNextPage={hasMoreRuns}
+            fetchNextPage={fetchMoreRuns}
+            isFetchingNextPage={isFetchingMoreRuns}
+          >
+            <div className="flex items-center gap-2 lg:flex-col">
+              {/* New Run button - only in small layouts */}
+              {allowDraftNewRun && (
+                <Button
+                  size="large"
+                  className={
+                    "flex h-12 w-40 items-center gap-2 py-6 lg:hidden " +
+                    (selectedView.type == "run" && !selectedView.id
+                      ? "agpt-card-selected text-accent"
+                      : "")
+                  }
+                  onClick={onSelectDraftNewRun}
+                  leftIcon={<Plus className="h-6 w-6" />}
+                >
+                  New {agent.has_external_trigger ? "trigger" : "run"}
+                </Button>
+              )}
+
+              {activeListTab === "runs" ? (
+                <>
+                  {agentPresets
+                    .filter((preset) => preset.webhook) // Triggers
+                    .toSorted(
+                      (a, b) => b.updated_at.getTime() - a.updated_at.getTime(),
+                    )
+                    .map((preset) => (
+                      <AgentRunSummaryCard
+                        className={cn(listItemClasses, "lg:h-auto")}
+                        key={preset.id}
+                        type="preset.triggered"
+                        status={preset.is_active ? "active" : "inactive"}
+                        title={preset.name}
+                        // timestamp={preset.last_run_time} // TODO: implement this
+                        selected={selectedView.id === preset.id}
+                        onClick={() => onSelectPreset(preset.id)}
+                        onDelete={() => doDeletePreset(preset.id)}
+                      />
+                    ))}
+                  {agentPresets
+                    .filter((preset) => !preset.webhook) // Presets
+                    .toSorted(
+                      (a, b) => b.updated_at.getTime() - a.updated_at.getTime(),
+                    )
+                    .map((preset) => (
+                      <AgentRunSummaryCard
+                        className={cn(listItemClasses, "lg:h-auto")}
+                        key={preset.id}
+                        type="preset"
+                        title={preset.name}
+                        // timestamp={preset.last_run_time} // TODO: implement this
+                        selected={selectedView.id === preset.id}
+                        onClick={() => onSelectPreset(preset.id)}
+                        onDelete={() => doDeletePreset(preset.id)}
+                      />
+                    ))}
+                  {agentPresets.length > 0 && <Separator className="my-1" />}
+                  {agentRuns
+                    .toSorted((a, b) => {
+                      const aTime = a.started_at?.getTime() ?? 0;
+                      const bTime = b.started_at?.getTime() ?? 0;
+                      return bTime - aTime;
+                    })
+                    .map((run) => (
+                      <AgentRunSummaryCard
+                        className={listItemClasses}
+                        key={run.id}
+                        type="run"
+                        status={agentRunStatusMap[run.status]}
+                        title={
+                          (run.preset_id
+                            ? agentPresets.find((p) => p.id == run.preset_id)
+                                ?.name
+                            : null) ?? agent.name
+                        }
+                        timestamp={run.started_at ?? undefined}
+                        selected={selectedView.id === run.id}
+                        onClick={() => onSelectRun(run.id)}
+                        onDelete={() => doDeleteRun(run as GraphExecutionMeta)}
+                        onPinAsPreset={
+                          doCreatePresetFromRun
+                            ? () => doCreatePresetFromRun(run.id)
+                            : undefined
+                        }
+                      />
+                    ))}
+                </>
+              ) : (
+                schedules.map((schedule) => (
+                  <AgentRunSummaryCard
+                    className={listItemClasses}
+                    key={schedule.id}
+                    type="schedule"
+                    status="scheduled" // TODO: implement active/inactive status for schedules
+                    title={schedule.name}
+                    timestamp={schedule.next_run_time}
+                    selected={selectedView.id === schedule.id}
+                    onClick={() => onSelectSchedule(schedule.id)}
+                    onDelete={() => doDeleteSchedule(schedule.id)}
+                  />
+                ))
+              )}
+            </div>
+          </InfiniteScroll>
+        </ScrollArea>
+      )}
+    </aside>
+  );
+}

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

@@ -0,0 +1,180 @@
+"use client";
+import React, { useCallback, useMemo } from "react";
+
+import {
+  Graph,
+  GraphExecutionID,
+  Schedule,
+  ScheduleID,
+} from "@/lib/autogpt-server-api";
+import { useBackendAPI } from "@/lib/autogpt-server-api/context";
+
+import ActionButtonGroup from "@/components/__legacy__/action-button-group";
+import type { ButtonAction } from "@/components/__legacy__/types";
+import {
+  Card,
+  CardContent,
+  CardHeader,
+  CardTitle,
+} from "@/components/__legacy__/ui/card";
+import { IconCross } from "@/components/__legacy__/ui/icons";
+import { Input } from "@/components/__legacy__/ui/input";
+import LoadingBox from "@/components/__legacy__/ui/loading";
+import { useToastOnFail } from "@/components/molecules/Toast/use-toast";
+import { humanizeCronExpression } from "@/lib/cron-expression-utils";
+import { formatScheduleTime } from "@/lib/timezone-utils";
+import { useUserTimezone } from "@/lib/hooks/useUserTimezone";
+import { PlayIcon } from "lucide-react";
+
+import { AgentRunStatus } from "./agent-run-status-chip";
+
+export function AgentScheduleDetailsView({
+  graph,
+  schedule,
+  agentActions,
+  onForcedRun,
+  doDeleteSchedule,
+}: {
+  graph: Graph;
+  schedule: Schedule;
+  agentActions: ButtonAction[];
+  onForcedRun: (runID: GraphExecutionID) => void;
+  doDeleteSchedule: (scheduleID: ScheduleID) => void;
+}): React.ReactNode {
+  const api = useBackendAPI();
+
+  const selectedRunStatus: AgentRunStatus = "scheduled";
+
+  const toastOnFail = useToastOnFail();
+
+  // Get user's timezone for displaying schedule times
+  const userTimezone = useUserTimezone();
+
+  const infoStats: { label: string; value: React.ReactNode }[] = useMemo(() => {
+    return [
+      {
+        label: "Status",
+        value:
+          selectedRunStatus.charAt(0).toUpperCase() +
+          selectedRunStatus.slice(1),
+      },
+      {
+        label: "Schedule",
+        value: humanizeCronExpression(schedule.cron),
+      },
+      {
+        label: "Next run",
+        value: formatScheduleTime(schedule.next_run_time, userTimezone),
+      },
+    ];
+  }, [schedule, selectedRunStatus, userTimezone]);
+
+  const agentRunInputs: Record<
+    string,
+    { title?: string; /* type: BlockIOSubType; */ value: any }
+  > = useMemo(() => {
+    // TODO: show (link to) preset - https://github.com/Significant-Gravitas/AutoGPT/issues/9168
+
+    // Add type info from agent input schema
+    return Object.fromEntries(
+      Object.entries(schedule.input_data).map(([k, v]) => [
+        k,
+        {
+          title: graph.input_schema.properties[k].title,
+          /* TODO: type: agent.input_schema.properties[k].type */
+          value: v,
+        },
+      ]),
+    );
+  }, [graph, schedule]);
+
+  const runNow = useCallback(
+    () =>
+      api
+        .executeGraph(
+          graph.id,
+          graph.version,
+          schedule.input_data,
+          schedule.input_credentials,
+          "library",
+        )
+        .then((run) => onForcedRun(run.id))
+        .catch(toastOnFail("execute agent")),
+    [api, graph, schedule, onForcedRun, toastOnFail],
+  );
+
+  const runActions: ButtonAction[] = useMemo(
+    () => [
+      {
+        label: (
+          <>
+            <PlayIcon className="mr-2 size-4" />
+            Run now
+          </>
+        ),
+        callback: runNow,
+      },
+      {
+        label: (
+          <>
+            <IconCross className="mr-2 size-4 px-0.5" />
+            Delete schedule
+          </>
+        ),
+        callback: () => doDeleteSchedule(schedule.id),
+        variant: "destructive",
+      },
+    ],
+    [runNow],
+  );
+
+  return (
+    <div className="agpt-div flex gap-6">
+      <div className="flex flex-1 flex-col gap-4">
+        <Card className="agpt-box">
+          <CardHeader>
+            <CardTitle className="font-poppins text-lg">Info</CardTitle>
+          </CardHeader>
+
+          <CardContent>
+            <div className="flex justify-stretch gap-4">
+              {infoStats.map(({ label, value }) => (
+                <div key={label} className="flex-1">
+                  <p className="text-sm font-medium text-black">{label}</p>
+                  <p className="text-sm text-neutral-600">{value}</p>
+                </div>
+              ))}
+            </div>
+          </CardContent>
+        </Card>
+
+        <Card className="agpt-box">
+          <CardHeader>
+            <CardTitle className="font-poppins text-lg">Input</CardTitle>
+          </CardHeader>
+          <CardContent className="flex flex-col gap-4">
+            {agentRunInputs !== undefined ? (
+              Object.entries(agentRunInputs).map(([key, { title, value }]) => (
+                <div key={key} className="flex flex-col gap-1.5">
+                  <label className="text-sm font-medium">{title || key}</label>
+                  <Input value={value} className="rounded-full" disabled />
+                </div>
+              ))
+            ) : (
+              <LoadingBox spinnerSize={12} className="h-24" />
+            )}
+          </CardContent>
+        </Card>
+      </div>
+
+      {/* Run / Agent Actions */}
+      <aside className="w-48 xl:w-56">
+        <div className="flex flex-col gap-8">
+          <ActionButtonGroup title="Run actions" actions={runActions} />
+
+          <ActionButtonGroup title="Agent actions" actions={agentActions} />
+        </div>
+      </aside>
+    </div>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/create-preset-dialog.tsx

@@ -0,0 +1,100 @@
+"use client";
+
+import React, { useState } from "react";
+import { Button } from "@/components/__legacy__/ui/button";
+import {
+  Dialog,
+  DialogContent,
+  DialogDescription,
+  DialogFooter,
+  DialogHeader,
+  DialogTitle,
+} from "@/components/__legacy__/ui/dialog";
+import { Input } from "@/components/__legacy__/ui/input";
+import { Textarea } from "@/components/__legacy__/ui/textarea";
+
+interface CreatePresetDialogProps {
+  open: boolean;
+  onOpenChange: (open: boolean) => void;
+  onConfirm: (name: string, description: string) => Promise<void> | void;
+}
+
+export function CreatePresetDialog({
+  open,
+  onOpenChange,
+  onConfirm,
+}: CreatePresetDialogProps) {
+  const [name, setName] = useState("");
+  const [description, setDescription] = useState("");
+
+  const handleSubmit = async () => {
+    if (name.trim()) {
+      await onConfirm(name.trim(), description.trim());
+      setName("");
+      setDescription("");
+      onOpenChange(false);
+    }
+  };
+
+  const handleCancel = () => {
+    setName("");
+    setDescription("");
+    onOpenChange(false);
+  };
+
+  const handleKeyDown = (e: React.KeyboardEvent) => {
+    if (e.key === "Enter" && (e.metaKey || e.ctrlKey)) {
+      e.preventDefault();
+      handleSubmit();
+    }
+  };
+
+  return (
+    <Dialog open={open} onOpenChange={onOpenChange}>
+      <DialogContent className="sm:max-w-[425px]">
+        <DialogHeader>
+          <DialogTitle>Create Preset</DialogTitle>
+          <DialogDescription>
+            Give your preset a name and description to help identify it later.
+          </DialogDescription>
+        </DialogHeader>
+        <div className="grid gap-4 py-4">
+          <div className="grid gap-2">
+            <label htmlFor="preset-name" className="text-sm font-medium">
+              Name *
+            </label>
+            <Input
+              id="preset-name"
+              placeholder="Enter preset name"
+              value={name}
+              onChange={(e) => setName(e.target.value)}
+              onKeyDown={handleKeyDown}
+              autoFocus
+            />
+          </div>
+          <div className="grid gap-2">
+            <label htmlFor="preset-description" className="text-sm font-medium">
+              Description
+            </label>
+            <Textarea
+              id="preset-description"
+              placeholder="Optional description"
+              value={description}
+              onChange={(e) => setDescription(e.target.value)}
+              onKeyDown={handleKeyDown}
+              rows={3}
+            />
+          </div>
+        </div>
+        <DialogFooter>
+          <Button variant="outline" onClick={handleCancel}>
+            Cancel
+          </Button>
+          <Button onClick={handleSubmit} disabled={!name.trim()}>
+            Create Preset
+          </Button>
+        </DialogFooter>
+      </DialogContent>
+    </Dialog>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/cron-scheduler-dialog.tsx

@@ -2,7 +2,7 @@ import { useEffect, useState } from "react";
 import { Input } from "@/components/__legacy__/ui/input";
 import { Button } from "@/components/__legacy__/ui/button";
 import { useToast } from "@/components/molecules/Toast/use-toast";
-import { CronScheduler } from "@/components/contextual/CronScheduler/cron-scheduler";
+import { CronScheduler } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/cron-scheduler";
 import { Dialog } from "@/components/molecules/Dialog/Dialog";
 import { getTimezoneDisplayName } from "@/lib/timezone-utils";
 import { useUserTimezone } from "@/lib/hooks/useUserTimezone";

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/use-agent-runs.ts

@@ -0,0 +1,210 @@
+import {
+  GraphExecutionMeta as LegacyGraphExecutionMeta,
+  GraphID,
+  GraphExecutionID,
+} from "@/lib/autogpt-server-api";
+import { getQueryClient } from "@/lib/react-query/queryClient";
+import {
+  getPaginatedTotalCount,
+  getPaginationNextPageNumber,
+  unpaginate,
+} from "@/app/api/helpers";
+import {
+  getV1ListGraphExecutionsResponse,
+  getV1ListGraphExecutionsResponse200,
+  useGetV1ListGraphExecutionsInfinite,
+} from "@/app/api/__generated__/endpoints/graphs/graphs";
+import { GraphExecutionsPaginated } from "@/app/api/__generated__/models/graphExecutionsPaginated";
+import { GraphExecutionMeta as RawGraphExecutionMeta } from "@/app/api/__generated__/models/graphExecutionMeta";
+
+export type GraphExecutionMeta = Omit<
+  RawGraphExecutionMeta,
+  "id" | "user_id" | "graph_id" | "preset_id" | "stats"
+> &
+  Pick<
+    LegacyGraphExecutionMeta,
+    "id" | "user_id" | "graph_id" | "preset_id" | "stats"
+  >;
+
+/** Hook to fetch runs for a specific graph, with support for infinite scroll.
+ *
+ * @param graphID - The ID of the graph to fetch agent runs for. This parameter is
+ *                  optional in the sense that the hook doesn't run unless it is passed.
+ *                  This way, it can be used in components where the graph ID is not
+ *                  immediately available.
+ */
+export const useAgentRunsInfinite = (graphID?: GraphID) => {
+  const queryClient = getQueryClient();
+  const {
+    data: queryResults,
+    refetch: refetchRuns,
+    isPending: agentRunsLoading,
+    isRefetching: agentRunsReloading,
+    hasNextPage: hasMoreRuns,
+    fetchNextPage: fetchMoreRuns,
+    isFetchingNextPage: isFetchingMoreRuns,
+    queryKey,
+  } = useGetV1ListGraphExecutionsInfinite(
+    graphID!,
+    { page: 1, page_size: 20 },
+    {
+      query: {
+        getNextPageParam: getPaginationNextPageNumber,
+
+        // Prevent query from running if graphID is not available (yet)
+        ...(!graphID
+          ? {
+              enabled: false,
+              queryFn: () =>
+                // Fake empty response if graphID is not available (yet)
+                Promise.resolve({
+                  status: 200,
+                  data: {
+                    executions: [],
+                    pagination: {
+                      current_page: 1,
+                      page_size: 20,
+                      total_items: 0,
+                      total_pages: 0,
+                    },
+                  },
+                  headers: new Headers(),
+                } satisfies getV1ListGraphExecutionsResponse),
+            }
+          : {}),
+      },
+    },
+    queryClient,
+  );
+
+  const agentRuns = queryResults ? unpaginate(queryResults, "executions") : [];
+  const agentRunCount = getPaginatedTotalCount(queryResults);
+
+  const upsertAgentRun = (newAgentRun: GraphExecutionMeta) => {
+    queryClient.setQueryData(
+      queryKey,
+      (currentQueryData: typeof queryResults) => {
+        if (!currentQueryData?.pages || agentRunCount === undefined)
+          return currentQueryData;
+
+        const exists = currentQueryData.pages.some((page) => {
+          if (page.status !== 200) return false;
+
+          const response = page.data;
+          return response.executions.some((run) => run.id === newAgentRun.id);
+        });
+        if (exists) {
+          // If the run already exists, we update it
+          return {
+            ...currentQueryData,
+            pages: currentQueryData.pages.map((page) => {
+              if (page.status !== 200) return page;
+              const response = page.data;
+              const executions = response.executions;
+
+              const index = executions.findIndex(
+                (run) => run.id === newAgentRun.id,
+              );
+              if (index === -1) return page;
+
+              const newExecutions = [...executions];
+              newExecutions[index] = newAgentRun;
+
+              return {
+                ...page,
+                data: {
+                  ...response,
+                  executions: newExecutions,
+                },
+              } satisfies getV1ListGraphExecutionsResponse;
+            }),
+          };
+        }
+
+        // If the run does not exist, we add it to the first page
+        const page = currentQueryData
+          .pages[0] as getV1ListGraphExecutionsResponse200 & {
+          headers: Headers;
+        };
+        const updatedExecutions = [newAgentRun, ...page.data.executions];
+        const updatedPage = {
+          ...page,
+          data: {
+            ...page.data,
+            executions: updatedExecutions,
+          },
+        } satisfies getV1ListGraphExecutionsResponse;
+        const updatedPages = [updatedPage, ...currentQueryData.pages.slice(1)];
+        return {
+          ...currentQueryData,
+          pages: updatedPages.map(
+            // Increment the total runs count in the pagination info of all pages
+            (page) =>
+              page.status === 200
+                ? {
+                    ...page,
+                    data: {
+                      ...page.data,
+                      pagination: {
+                        ...page.data.pagination,
+                        total_items: agentRunCount + 1,
+                      },
+                    },
+                  }
+                : page,
+          ),
+        };
+      },
+    );
+  };
+
+  const removeAgentRun = (runID: GraphExecutionID) => {
+    queryClient.setQueryData(
+      [queryKey, { page: 1, page_size: 20 }],
+      (currentQueryData: typeof queryResults) => {
+        if (!currentQueryData?.pages) return currentQueryData;
+
+        let found = false;
+        return {
+          ...currentQueryData,
+          pages: currentQueryData.pages.map((page) => {
+            const response = page.data as GraphExecutionsPaginated;
+            const filteredExecutions = response.executions.filter(
+              (run) => run.id !== runID,
+            );
+            if (filteredExecutions.length < response.executions.length) {
+              found = true;
+            }
+
+            return {
+              ...page,
+              data: {
+                ...response,
+                executions: filteredExecutions,
+                pagination: {
+                  ...response.pagination,
+                  total_items:
+                    response.pagination.total_items - (found ? 1 : 0),
+                },
+              },
+            };
+          }),
+        };
+      },
+    );
+  };
+
+  return {
+    agentRuns: agentRuns as GraphExecutionMeta[],
+    refetchRuns,
+    agentRunCount,
+    agentRunsLoading: agentRunsLoading || agentRunsReloading,
+    hasMoreRuns,
+    fetchMoreRuns,
+    isFetchingMoreRuns,
+    upsertAgentRun,
+    removeAgentRun,
+  };
+};
+
+export type AgentRunsQuery = ReturnType<typeof useAgentRunsInfinite>;

autogpt_platform/frontend/src/app/(platform)/library/legacy/[id]/page.tsx

@@ -0,0 +1,7 @@
+"use client";
+
+import { OldAgentLibraryView } from "../../agents/[id]/components/OldAgentLibraryView/OldAgentLibraryView";
+
+export default function OldAgentLibraryPage() {
+  return <OldAgentLibraryView />;
+}

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

@@ -1052,6 +1052,7 @@
                     {
                       "$ref": "#/components/schemas/ClarificationNeededResponse"
                     },
+                    { "$ref": "#/components/schemas/SuggestedGoalResponse" },
                     { "$ref": "#/components/schemas/BlockListResponse" },
                     { "$ref": "#/components/schemas/BlockDetailsResponse" },
                     { "$ref": "#/components/schemas/BlockOutputResponse" },
@@ -1151,36 +1152,6 @@
       }
     },
     "/api/chat/sessions/{session_id}": {
-      "delete": {
-        "tags": ["v2", "chat", "chat"],
-        "summary": "Delete Session",
-        "description": "Delete a chat session.\n\nPermanently removes a chat session and all its messages.\nOnly the owner can delete their sessions.\n\nArgs:\n    session_id: The session ID to delete.\n    user_id: The authenticated user's ID.\n\nReturns:\n    204 No Content on success.\n\nRaises:\n    HTTPException: 404 if session not found or not owned by user.",
-        "operationId": "deleteV2DeleteSession",
-        "security": [{ "HTTPBearerJWT": [] }],
-        "parameters": [
-          {
-            "name": "session_id",
-            "in": "path",
-            "required": true,
-            "schema": { "type": "string", "title": "Session Id" }
-          }
-        ],
-        "responses": {
-          "204": { "description": "Successful Response" },
-          "401": {
-            "$ref": "#/components/responses/HTTP401NotAuthenticatedError"
-          },
-          "404": { "description": "Session not found or access denied" },
-          "422": {
-            "description": "Validation Error",
-            "content": {
-              "application/json": {
-                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
-              }
-            }
-          }
-        }
-      },
       "get": {
         "tags": ["v2", "chat", "chat"],
         "summary": "Get Session",
@@ -10796,7 +10767,8 @@
           "bash_exec",
           "operation_status",
           "feature_request_search",
-          "feature_request_created"
+          "feature_request_created",
+          "suggested_goal"
         ],
         "title": "ResponseType",
         "description": "Types of tool responses."
@@ -11677,6 +11649,46 @@
         "enum": ["DRAFT", "PENDING", "APPROVED", "REJECTED"],
         "title": "SubmissionStatus"
       },
+      "SuggestedGoalResponse": {
+        "properties": {
+          "type": {
+            "$ref": "#/components/schemas/ResponseType",
+            "default": "suggested_goal"
+          },
+          "message": { "type": "string", "title": "Message" },
+          "session_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Session Id"
+          },
+          "suggested_goal": {
+            "type": "string",
+            "title": "Suggested Goal",
+            "description": "The suggested alternative goal"
+          },
+          "reason": {
+            "type": "string",
+            "title": "Reason",
+            "description": "Why the original goal needs refinement",
+            "default": ""
+          },
+          "original_goal": {
+            "type": "string",
+            "title": "Original Goal",
+            "description": "The user's original goal for context",
+            "default": ""
+          },
+          "goal_type": {
+            "type": "string",
+            "title": "Goal Type",
+            "description": "Type: 'vague' or 'unachievable'",
+            "default": "vague"
+          }
+        },
+        "type": "object",
+        "required": ["message", "suggested_goal"],
+        "title": "SuggestedGoalResponse",
+        "description": "Response when the goal needs refinement with a suggested alternative."
+      },
       "SuggestionsResponse": {
         "properties": {
           "otto_suggestions": {

autogpt_platform/frontend/src/components/__legacy__/ui/dialog.tsx

@@ -115,7 +115,7 @@ const DialogFooter = ({
 }: React.HTMLAttributes<HTMLDivElement>) => (
   <div
     className={cn(
-      "flex flex-col-reverse gap-2 sm:flex-row sm:justify-end",
+      "flex flex-col-reverse sm:flex-row sm:justify-end sm:space-x-2",
       className,
     )}
     {...props}

autogpt_platform/frontend/src/components/contextual/PublishAgentModal/components/AgentInfoStep/AgentInfoStep.tsx

@@ -1,6 +1,6 @@
 "use client";
 
-import { CronExpressionDialog } from "@/components/contextual/CronScheduler/cron-scheduler-dialog";
+import { CronExpressionDialog } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/cron-scheduler-dialog";
 import { Form, FormField } from "@/components/__legacy__/ui/form";
 import { Button } from "@/components/atoms/Button/Button";
 import { Input } from "@/components/atoms/Input/Input";

autogpt_platform/frontend/src/services/feature-flags/use-get-flag.ts

@@ -7,6 +7,7 @@ import { useFlags } from "launchdarkly-react-client-sdk";
 export enum Flag {
   BETA_BLOCKS = "beta-blocks",
   NEW_BLOCK_MENU = "new-block-menu",
+  NEW_AGENT_RUNS = "new-agent-runs",
   GRAPH_SEARCH = "graph-search",
   ENABLE_ENHANCED_OUTPUT_HANDLING = "enable-enhanced-output-handling",
   SHARE_EXECUTION_RESULTS = "share-execution-results",
@@ -21,6 +22,7 @@ const isPwMockEnabled = process.env.NEXT_PUBLIC_PW_TEST === "true";
 const defaultFlags = {
   [Flag.BETA_BLOCKS]: [],
   [Flag.NEW_BLOCK_MENU]: false,
+  [Flag.NEW_AGENT_RUNS]: false,
   [Flag.GRAPH_SEARCH]: false,
   [Flag.ENABLE_ENHANCED_OUTPUT_HANDLING]: false,
   [Flag.SHARE_EXECUTION_RESULTS]: false,

autogpt_platform/frontend/src/types/images.d.ts

@@ -1,4 +0,0 @@
-declare module "*.png" {
-  const content: import("next/image").StaticImageData;
-  export default content;
-}

docs/integrations/block-integrations/llm.md

@@ -65,7 +65,7 @@ The result routes data to yes_output or no_output, enabling intelligent branchin
 | condition | A plaintext English description of the condition to evaluate | str | Yes |
 | yes_value | (Optional) Value to output if the condition is true. If not provided, input_value will be used. | Yes Value | No |
 | no_value | (Optional) Value to output if the condition is false. If not provided, input_value will be used. | No Value | No |
-| model | The language model to use for evaluating the condition. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
+| model | The language model to use for evaluating the condition. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
 
 ### Outputs
 
@@ -103,7 +103,7 @@ The block sends the entire conversation history to the chosen LLM, including sys
 |-------|-------------|------|----------|
 | prompt | The prompt to send to the language model. | str | No |
 | messages | List of messages in the conversation. | List[Any] | Yes |
-| model | The language model to use for the conversation. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
+| model | The language model to use for the conversation. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
 | max_tokens | The maximum number of tokens to generate in the chat completion. | int | No |
 | ollama_host | Ollama host for local  models | str | No |
 
@@ -257,7 +257,7 @@ The block formulates a prompt based on the given focus or source data, sends it
 |-------|-------------|------|----------|
 | focus | The focus of the list to generate. | str | No |
 | source_data | The data to generate the list from. | str | No |
-| model | The language model to use for generating the list. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
+| model | The language model to use for generating the list. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
 | max_retries | Maximum number of retries for generating a valid list. | int | No |
 | force_json_output | Whether to force the LLM to produce a JSON-only response. This can increase the block's reliability, but may also reduce the quality of the response because it prohibits the LLM from reasoning before providing its JSON response. | bool | No |
 | max_tokens | The maximum number of tokens to generate in the chat completion. | int | No |
@@ -424,7 +424,7 @@ The block sends the input prompt to a chosen LLM, along with any system prompts
 | prompt | The prompt to send to the language model. | str | Yes |
 | expected_format | Expected format of the response. If provided, the response will be validated against this format. The keys should be the expected fields in the response, and the values should be the description of the field. | Dict[str, str] | Yes |
 | list_result | Whether the response should be a list of objects in the expected format. | bool | No |
-| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
+| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
 | force_json_output | Whether to force the LLM to produce a JSON-only response. This can increase the block's reliability, but may also reduce the quality of the response because it prohibits the LLM from reasoning before providing its JSON response. | bool | No |
 | sys_prompt | The system prompt to provide additional context to the model. | str | No |
 | conversation_history | The conversation history to provide context for the prompt. | List[Dict[str, Any]] | No |
@@ -464,7 +464,7 @@ The block sends the input prompt to a chosen LLM, processes the response, and re
 | Input | Description | Type | Required |
 |-------|-------------|------|----------|
 | prompt | The prompt to send to the language model. You can use any of the {keys} from Prompt Values to fill in the prompt with values from the prompt values dictionary by putting them in curly braces. | str | Yes |
-| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
+| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
 | sys_prompt | The system prompt to provide additional context to the model. | str | No |
 | retry | Number of times to retry the LLM call if the response does not match the expected format. | int | No |
 | prompt_values | Values used to fill in the prompt. The values can be used in the prompt by putting them in a double curly braces, e.g. {{variable_name}}. | Dict[str, str] | No |
@@ -501,7 +501,7 @@ The block splits the input text into smaller chunks, sends each chunk to an LLM
 | Input | Description | Type | Required |
 |-------|-------------|------|----------|
 | text | The text to summarize. | str | Yes |
-| model | The language model to use for summarizing the text. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
+| model | The language model to use for summarizing the text. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
 | focus | The topic to focus on in the summary | str | No |
 | style | The style of the summary to generate. | "concise" \| "detailed" \| "bullet points" \| "numbered list" | No |
 | max_tokens | The maximum number of tokens to generate in the chat completion. | int | No |
@@ -763,7 +763,7 @@ Configure agent_mode_max_iterations to control loop behavior: 0 for single decis
 | Input | Description | Type | Required |
 |-------|-------------|------|----------|
 | prompt | The prompt to send to the language model. | str | Yes |
-| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
+| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
 | multiple_tool_calls | Whether to allow multiple tool calls in a single response. | bool | No |
 | sys_prompt | The system prompt to provide additional context to the model. | str | No |
 | conversation_history | The conversation history to provide context for the prompt. | List[Dict[str, Any]] | No |