Files
AutoGPT/autogpt_platform
Otto 649d4ab7f5 feat(chat): Add delete chat session endpoint and UI (#12112)
## Summary

Adds the ability to delete chat sessions from the CoPilot interface.

## Changes

### Backend
- Add `DELETE /api/chat/sessions/{session_id}` endpoint in `routes.py`
- Returns 204 on success, 404 if not found or not owned by user
- Reuses existing `delete_chat_session` function from `model.py`

### Frontend
- Add delete button (trash icon) that appears on hover for each chat
session
- Add confirmation dialog before deletion using existing
`DeleteConfirmDialog` component
- Refresh session list after successful delete
- Clear current session selection if the deleted session was active
- Update OpenAPI spec with new endpoint

## Testing

1. Hover over a chat session in sidebar → trash icon appears
2. Click trash icon → confirmation dialog
3. Confirm deletion → session removed, list refreshes
4. If deleted session was active, selection is cleared

## Screenshots

Delete button appears on hover, confirmation dialog on click.

## Related Issues

Closes SECRT-1928

<!-- greptile_comment -->

<h2>Greptile Overview</h2>

<details><summary><h3>Greptile Summary</h3></summary>

Adds the ability to delete chat sessions from the CoPilot interface — a
new `DELETE /api/chat/sessions/{session_id}` backend endpoint and a
corresponding delete button with confirmation dialog in the
`ChatSidebar` frontend component.

- **Backend route** (`routes.py`): Clean implementation reusing the
existing `delete_chat_session` model function with proper auth guards
and 204/404 responses. No issues.
- **Frontend** (`ChatSidebar.tsx`): Adds hover-visible trash icon per
session, confirmation dialog, mutation with cache invalidation, and
active session clearing on delete. However, it uses a `__legacy__`
component (`DeleteConfirmDialog`) which violates the project's style
guide — new code should use the modern design system components. Error
handling only logs to console without user-facing feedback (project
convention is to use toast notifications for mutation errors).
`isDeleting` is destructured but unused.
- **OpenAPI spec** updated correctly.
- **Unrelated file included**:
`notes/plan-SECRT-1959-graph-edge-desync.md` is a planning document for
a different ticket and should be removed from this PR. The `notes/`
directory is newly introduced and both plan files should be reconsidered
for inclusion.
</details>


<details><summary><h3>Confidence Score: 3/5</h3></summary>

- Functionally correct but has style guide violations and includes
unrelated files that should be addressed before merge.
- The core feature implementation (backend DELETE endpoint and frontend
mutation logic) is sound and follows existing patterns. Score is lowered
because: (1) the frontend uses a legacy component explicitly prohibited
by the project's style guide, (2) mutation errors are not surfaced to
the user, and (3) the PR includes an unrelated planning document for a
different ticket.
- Pay close attention to `ChatSidebar.tsx` for the legacy component
import and error handling, and
`notes/plan-SECRT-1959-graph-edge-desync.md` which should be removed.
</details>


<details><summary><h3>Sequence Diagram</h3></summary>

```mermaid
sequenceDiagram
    participant User
    participant ChatSidebar as ChatSidebar (Frontend)
    participant ReactQuery as React Query
    participant API as DELETE /api/chat/sessions/{id}
    participant Model as model.delete_chat_session
    participant DB as db.delete_chat_session (Prisma)
    participant Redis as Redis Cache

    User->>ChatSidebar: Click trash icon on session
    ChatSidebar->>ChatSidebar: Show DeleteConfirmDialog
    User->>ChatSidebar: Confirm deletion
    ChatSidebar->>ReactQuery: deleteSession({ sessionId })
    ReactQuery->>API: DELETE /api/chat/sessions/{session_id}
    API->>Model: delete_chat_session(session_id, user_id)
    Model->>DB: delete_many(where: {id, userId})
    DB-->>Model: bool (deleted count > 0)
    Model->>Redis: Delete session cache key
    Model->>Model: Clean up session lock
    Model-->>API: True
    API-->>ReactQuery: 204 No Content
    ReactQuery->>ChatSidebar: onSuccess callback
    ChatSidebar->>ReactQuery: invalidateQueries(sessions list)
    ChatSidebar->>ChatSidebar: Clear sessionId if deleted was active
```
</details>


<sub>Last reviewed commit: 44a92c6</sub>

<!-- greptile_other_comments_section -->

<details><summary><h4>Context used (3)</h4></summary>

- Context from `dashboard` - autogpt_platform/frontend/CLAUDE.md
([source](https://app.greptile.com/review/custom-context?memory=39861924-d320-41ba-a1a7-a8bff44f780a))
- Context from `dashboard` - autogpt_platform/frontend/CONTRIBUTING.md
([source](https://app.greptile.com/review/custom-context?memory=cc4f1b17-cb5c-4b63-b218-c772b48e20ee))
- Context from `dashboard` - autogpt_platform/CLAUDE.md
([source](https://app.greptile.com/review/custom-context?memory=6e9dc5dc-8942-47df-8677-e60062ec8c3a))
</details>


<!-- /greptile_comment -->

---------

Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
2026-02-16 12:19:18 +00:00
..

AutoGPT Platform

Welcome to the AutoGPT Platform - a powerful system for creating and running AI agents to solve business problems. This platform enables you to harness the power of artificial intelligence to automate tasks, analyze data, and generate insights for your organization.

Getting Started

Prerequisites

  • Docker
  • Docker Compose V2 (comes with Docker Desktop, or can be installed separately)

Running the System

To run the AutoGPT Platform, follow these steps:

  1. Clone this repository to your local machine and navigate to the autogpt_platform directory within the repository:

    git clone <https://github.com/Significant-Gravitas/AutoGPT.git | git@github.com:Significant-Gravitas/AutoGPT.git>
    cd AutoGPT/autogpt_platform
    
  2. Run the following command:

    cp .env.default .env
    

    This command will copy the .env.default file to .env. You can modify the .env file to add your own environment variables.

  3. Run the following command:

    docker compose up -d
    

    This command will start all the necessary backend services defined in the docker-compose.yml file in detached mode.

  4. After all the services are in ready state, open your browser and navigate to http://localhost:3000 to access the AutoGPT Platform frontend.

Running Just Core services

You can now run the following to enable just the core services.

# For help
make help

# Run just Supabase + Redis + RabbitMQ
make start-core

# Stop core services
make stop-core

# View logs from core services 
make logs-core

# Run formatting and linting for backend and frontend
make format

# Run migrations for backend database
make migrate

# Run backend server
make run-backend

# Run frontend development server
make run-frontend

Docker Compose Commands

Here are some useful Docker Compose commands for managing your AutoGPT Platform:

  • docker compose up -d: Start the services in detached mode.
  • docker compose stop: Stop the running services without removing them.
  • docker compose rm: Remove stopped service containers.
  • docker compose build: Build or rebuild services.
  • docker compose down: Stop and remove containers, networks, and volumes.
  • docker compose watch: Watch for changes in your services and automatically update them.

Sample Scenarios

Here are some common scenarios where you might use multiple Docker Compose commands:

  1. Updating and restarting a specific service:

    docker compose build api_srv
    docker compose up -d --no-deps api_srv
    

    This rebuilds the api_srv service and restarts it without affecting other services.

  2. Viewing logs for troubleshooting:

    docker compose logs -f api_srv ws_srv
    

    This shows and follows the logs for both api_srv and ws_srv services.

  3. Scaling a service for increased load:

    docker compose up -d --scale executor=3
    

    This scales the executor service to 3 instances to handle increased load.

  4. Stopping the entire system for maintenance:

    docker compose stop
    docker compose rm -f
    docker compose pull
    docker compose up -d
    

    This stops all services, removes containers, pulls the latest images, and restarts the system.

  5. Developing with live updates:

    docker compose watch
    

    This watches for changes in your code and automatically updates the relevant services.

  6. Checking the status of services:

    docker compose ps
    

    This shows the current status of all services defined in your docker-compose.yml file.

These scenarios demonstrate how to use Docker Compose commands in combination to manage your AutoGPT Platform effectively.

Persisting Data

To persist data for PostgreSQL and Redis, you can modify the docker-compose.yml file to add volumes. Here's how:

  1. Open the docker-compose.yml file in a text editor.

  2. Add volume configurations for PostgreSQL and Redis services:

    services:
      postgres:
        # ... other configurations ...
        volumes:
          - postgres_data:/var/lib/postgresql/data
    
      redis:
        # ... other configurations ...
        volumes:
          - redis_data:/data
    
    volumes:
      postgres_data:
      redis_data:
    
  3. Save the file and run docker compose up -d to apply the changes.

This configuration will create named volumes for PostgreSQL and Redis, ensuring that your data persists across container restarts.

API Client Generation

The platform includes scripts for generating and managing the API client:

  • pnpm fetch:openapi: Fetches the OpenAPI specification from the backend service (requires backend to be running on port 8006)
  • pnpm generate:api-client: Generates the TypeScript API client from the OpenAPI specification using Orval
  • pnpm generate:api: Runs both fetch and generate commands in sequence

Manual API Client Updates

If you need to update the API client after making changes to the backend API:

  1. Ensure the backend services are running:

    docker compose up -d
    
  2. Generate the updated API client:

    pnpm generate:api
    

This will fetch the latest OpenAPI specification and regenerate the TypeScript client code.