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Bridge Feishu to ACP-compatible agents with automatic session management for non-developers.

Project description

ACP Bridge

CI Version License Python Last Commit

ACP Bridge is a bridge service that connects Feishu (Lark) group chats to ACP-compatible AI agents (such as Kiro CLI).

Core features:

  • Auto session creation — @mention the bot in group chats, or just send a message in DM
  • Message threading via reply chains — reply to any message in a thread to continue the conversation
  • LRU + TTL session management — automatic eviction of idle sessions to control resource usage
  • Message buffering — messages sent while the agent is busy are queued and delivered in order
  • Evaluator quality gate — optional independent agent review of responses before sending to users

Installation

Prerequisites

  • Python 3.11+
  • uv package manager
  • Kiro CLI — the default ACP agent

Feishu App Setup

  1. Go to the Feishu Open Platform and create a new app.

  2. Under Credentials, copy the App ID and App Secret.

  3. Under Event Subscriptions, enable WebSocket (long connection) mode, then add the im.message.receive_v1 event.

  4. Under Permissions, enable:

    • im:message — send and update messages
    • im:message:send_as_bot — send messages as bot
    • im:message.group_at_msg:readonly — receive group chat messages with @mention
    • im:message.group_msg — receive all group messages (required for reply-chain routing)
    • im:message.p2p_msg:readonly — receive P2P messages
    • im:resource — download file resources from messages
    • im:chat:readonly — read chat info
    • contact:contact.base:readonly — get user name (optional, for identifying sender in prompts)
    • contact:user.email:readonly — get user email (optional, for matching accounts in external systems)

    For contact permissions to work, ensure the Data Permission (数据权限) contact scope includes all bot users.

Steps

  1. Install dependencies:

    uv sync
    
  2. Generate a config file:

    uv run python -m acp_bridge.main init
    
  3. Edit bridge.toml with your Feishu app credentials:

    [feishu]
    app_id = "your_app_id"
    app_secret = "your_app_secret"
    
    [bridge]
    default_workspace = "~"          # Agent working directory (cwd)
    attachment_dir = "tmp/attachments" # Where user attachments from Feishu are saved
    output_dir = "tmp/output"        # Where agent output files (images, scripts) are saved
    auto_approve = false             # Auto-approve all tool permission requests
    max_sessions = 10                # Max concurrent agent sessions (LRU eviction)
    session_ttl_minutes = 720        # Idle session timeout
    show_thinking = false            # Forward agent thinking/reasoning to user
    show_intermediate = false        # Forward intermediate tool output to user
    
    [agent]
    name = "kiro"                    # Agent identifier
    description = "Kiro CLI - https://kiro.dev/cli/"
    # command = "kiro-cli"           # Command to spawn the agent process (default: kiro-cli)
    args = ["acp"]                   # Command arguments
    auto_approve = true              # Auto-approve at agent level
    
    [[evaluator]]                    # Optional: quality gate for agent responses
    name = "my-evaluator"            # Evaluator identifier
    trigger_pattern = "Conclusion|Result|Finding" # Regex to match agent response, triggers evaluation
    # command = "kiro-cli"           # Inherits from [agent].command if empty
    args = ["acp", "--agent", "my-evaluator"] # Spawns a separate agent process
    # workspace = ""                 # Inherits from bridge.default_workspace if empty
    # auto_approve = true            # Inherits from [agent].auto_approve if not set
    # Prepended to agent text sent to evaluator
    prompt = """Please evaluate the following report.
    End the final text response with a standalone line: RESULT: PASS or RESULT: FAIL.""" 
    pass_pattern = "(?mi)^\\s*RESULT\\s*:\\s*PASS\\s*$" # Regex to match evaluator PASS verdict
    max_retries = 2                  # Retry count on FAIL before sending with warning
    retry_prompt = """The evaluator found issues with your previous response
    Please revise and output the complete response again from the beginning
    (do not only output the changed parts):
    
    {feedback}"""
    
  4. Start the service:

    uv run python -m acp_bridge.main run
    

Tip: It's recommended to run in tmux so it persists in the background:

tmux new -s acp-bridge "uv run python -m acp_bridge.main run"

Image & File Support

The bridge automatically detects markdown links in agent responses and uploads them to Feishu:

  • ![description](path) — uploaded as image messages
  • [description](path) — uploaded as file messages

For security, only files under output_dir and attachment_dir (relative to default_workspace) are allowed to be uploaded. Files outside these directories are blocked with a warning.

To enable this, configure your ACP client's system prompt to instruct the agent to save images to the output_dir and reference them in markdown format. Each client has its own system prompt mechanism:

  • Kiro CLI: .kiro/agents/<name>.jsonprompt field
  • Claude Code: CLAUDE.md
  • Cursor: .cursorrules

Example

Given bridge.toml:

[bridge]
default_workspace = "~/code/ops-copilot"
attachment_dir = "bridge/tmp/attachments"
output_dir = "bridge/tmp/output"

For Kiro CLI, add to .kiro/agents/cli.json:

{
  "prompt": "When you need to create temp files (scripts, debug output, test data, etc.), always save them under bridge/tmp/output/.\nWhen you need to visualize data (trends, comparisons, etc.), always use matplotlib to save charts to bridge/tmp/output/ and reference them as ![description](bridge/tmp/output/xxx.png).\nWhen you need to share generated files (scripts, configs, logs, etc.), save them under bridge/tmp/output/ and reference them as [description](bridge/tmp/output/xxx.sh).\nNever copy external files into the output directory to send them. Only send files you generated yourself."
}

The agent generates a chart → saves to bridge/tmp/output/trend.png → responds with ![trend](bridge/tmp/output/trend.png) → bridge uploads the image to Feishu and replaces the markdown with [pic1] in the text message.

Similarly, [deploy script](bridge/tmp/output/deploy.sh) → bridge uploads the file and replaces the markdown with [file1].

Evaluator

The bridge supports an optional evaluator quality gate. When configured, agent responses are reviewed by a separate evaluator agent before being sent to the user.

Flow:

  1. Agent completes a response
  2. Bridge checks trigger_pattern against the response text
  3. If matched, spawns (or reuses) an evaluator agent session and sends the response for review
  4. Evaluator responds with a verdict — if it matches pass_pattern, the response is sent to the user
  5. If FAIL and retries remain, the evaluator's feedback is sent back to the original agent for revision
  6. If the final allowed evaluation still FAILs, the bridge sends that same evaluated response with a warning plus the final evaluator feedback

Evaluator sessions are persistent per main session, so retries share context. The evaluator agent is a separate process with its own system prompt and tools — it can use read-only tools to spot-check evidence in the report.

The bridge applies pass_pattern to the evaluator's final text response. Keep the evaluator prompt aligned with that pattern; for example, the config above expects a standalone RESULT: PASS line. Verdicts written only in tool calls, task context, plans, or other intermediate state are not matched.

Notification routing: the bridge distinguishes main agent sessions from evaluator sessions via SessionManager.find_by_session_id() — main sessions are tracked in the session manager, everything else is routed to the evaluator notification handler.

Commands

Command Description
#mode Show available modes and current mode
#mode <value> Switch to a different mode
#model Show available models and current model
#model <value> Switch to a different model
#cancel Cancel ongoing agent operation
#end End current agent session
#read <file_path> Read local file content
#diff [args] Show git diff
#session Show current agent session info
#sessions Show all active sessions
#help Show help message

License

MIT License. See LICENSE for details.

This project is derived from Juan by DiscreteTom.

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