gemini-devops-20250823-035513

content="This is an automated notification to confirm that the task from message "20250822163235_Project Handoff: Distributed Development Model.md" has been completed.

The outcome is recorded in checkpoint: ai/projects/distributed_development_model/checkpoints/001-implemented-trunk-based-development-workflow.md
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description="Send a task completion notification to gemini-architect.", command="python3 scripts/send_agent_message.py gemini-architect --sender-handle gemini-devops --subject "Task Complete: Project Handoff: Distributed Development Model" --content-file tmp/completion_message.md"

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file_path="/home/coder/infra2/ai/projects/multi_agent_server/plan.md", content="# Implementation Plan: Multi-Agent Communication Server

This document outlines the plan for building and operationalizing a production-ready, WebSocket-based server for real-time, multi-agent communication.

## Phase 1: Foundation & Migration

**Goal**: Move the Proof-of-Concept (PoC) code to a permanent location and establish a robust, production-ready project structure using Bazel.

1.  **Create Project Directory**: Create the new directory `servers/multi_agent_comm_server`.
2.  **Migrate PoC Code**: Copy the contents of `experimental/websocket_poc` into the new directory.
3.  **Establish Bazel Build**:
    *   Create a `BUILD.bazel` file for the server.
    *   Define a `py_binary` target for the FastAPI application.
    *   Add necessary dependencies (`requirements.txt`) to the Bazel workspace configuration.
4.  **Verify Build**: Run `bazel build //servers/multi_agent_comm_server:server` and `bazel run //servers/multi_agent_comm_server:server` to confirm the migrated application can be built and run successfully within the Bazel ecosystem.

## Phase 2: Core Feature Implementation

**Goal**: Enhance the PoC with the core features required for a production-ready system.

1.  **Agent Registration & Presence**:
    *   Implement a mechanism for agents to register with the server upon connection.
    *   Maintain a list of connected agents and their statuses (e.g., `available`, `busy`).
    *   Broadcast presence notifications to all connected agents when an agent joins or leaves.
2.  **Message Routing**:
    *   Implement logic to route messages from a sender to a specific recipient agent.
    *   Define a clear message format (e.g., JSON with `sender`, `recipient`, `payload` fields).
3.  **Error Handling & Resilience**:
    *   Implement robust error handling for connection failures and invalid messages.
    *   Add reconnection logic to the client-side implementation.
4.  **Logging & Observability**:
    *   Integrate structured logging into the server application.
    *   Add basic OpenTelemetry tracing to track message flow between agents.

## Phase 3: Integration & Testing

**Goal**: Integrate the communication server with the `gemini-cli` and develop a comprehensive test suite.

1.  **`gemini-cli` Tooling**:
    *   Develop a new `gemini-cli` tool (`agent_comm.py` or similar) that can connect to the WebSocket server.
    *   Implement tool commands for:
        *   `connect`
        *   `disconnect`
        *   `list-agents`
        *   `send-message  `
2.  **Integration Testing**:
    *   Develop an integration test suite that simulates a multi-agent conversation.
    *   The test should verify that two separate `gemini-cli` instances can communicate with each other through the server.
3.  **Unit Testing**:
    *   Write unit tests for the core server logic (message routing, agent registration).

## Phase 4: Deployment & Documentation

**Goal**: Deploy the server to the Kubernetes cluster and document its architecture and usage.

1.  **Containerization**:
    *   Create a `Dockerfile` for the server application.
    *   Use Bazel's containerization rules to build a production-ready image.
2.  **Kubernetes Deployment**:
    *   Create a Tanka environment for the `multi-agent-comm-server`.
    *   Define Kubernetes resources (Deployment, Service, Ingress).
    *   Deploy the server to the `monitoring` or a new `agents` namespace.
3.  **Documentation**:
    *   Create a `README.md` for the server, explaining its purpose, architecture, and how to run it locally.
    *   Create a new "Expert" artifact in `ai/experts/` that documents the agent communication protocol and how to use the new `gemini-cli` tool.
"

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file_path="/home/coder/infra2/ai/projects/multi_agent_server/checkpoints/001-implementation-plan-created.md", content="# Checkpoint: 001 - Implementation Plan Created

## Mission

*   **Primary Goal**: Build and operationalize a production-ready, WebSocket-based server for real-time, multi-agent communication.
*   **Current Focus**: Finalizing the implementation plan.

## Project Sequence

*   [000-initial-project-setup.md](000-initial-project-setup.md)

## Executive Summary of Last Conversation

After a thorough review of the workspace's active and inactive projects, we confirmed that the `multi_agent_server` project is the highest priority for aligning our work with the active OKRs, specifically "Autonomous Development Loops." We also confirmed that the WebSocket architecture is the correct strategic path, superseding the abandoned MCP server prototype. I have now created a detailed, four-phase implementation plan to guide the project.

## Checkpoint: The Concrete Problem

*   **Key Decisions**:
    *   A formal, four-phase implementation plan has been created for the `multi_agent_server` project.
*   **Key Findings**:
    *   This project is the critical path for achieving our current OKRs.
*   **Key Identifiers**:
    *   WebSocket
    *   Bazel
    *   Tanka
*   **Next Steps**:
    1.  **Begin Phase 1, Step 1**: Create the new project directory at `servers/multi_agent_comm_server`.
*   **Key Artifacts**:
    *   `ai/projects/multi_agent_server/plan.md`
"

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absolute_path="/home/coder/infra2/ai/process/README.md"

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path="/home/coder/infra2/ai/projects/"

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absolute_path="/home/coder/infra2/ai/projects/MANIFEST.md"

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command="mkdir -p servers/multi_agent_comm_server", description="Create the directory for the multi-agent communication server."

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file_path="/home/coder/infra2/ai/projects/MANIFEST.md", new_string="| `static_chat_viewer` | active | Developing a static chat viewer. |
| `multi_agent_comm_server` | active | Building the production WebSocket-based multi-agent communication server. |", old_string="| `static_chat_viewer` | active | Developing a static chat viewer. |"

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old_string="| `static_chat_viewer` | active | Developing a static chat viewer. |", new_string="| `static_chat_viewer` | active | Developing a static chat viewer. |
| `multi_agent_comm_server` | active | Building the production WebSocket-based multi-agent communication server. |", file_path="/home/coder/infra2/ai/projects/MANIFEST.md"

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description="Copy the WebSocket PoC code to the new server directory.", command="cp -r experimental/websocket_poc/* servers/multi_agent_comm_server/"

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absolute_path="/home/coder/infra2/ai/projects/de-risk_multi_agent_architecture/checkpoints/002-proof-of-concept-complete.md"

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pattern="fastapi|socketio"

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path="/home/coder/infra2/experimental/"

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file_path="/home/coder/infra2/servers/multi_agent_comm_server/main.py", content="import socketio
import uvicorn
from fastapi import FastAPI

sio = socketio.AsyncServer(async_mode="asgi")
app = FastAPI()
app.mount("/", socketio.ASGIApp(sio))


@sio.event
async def connect(sid, environ):
    print(f"connect {sid}")


@sio.event
async def disconnect(sid):
    print(f"disconnect {sid}")


@sio.on("message")
async def message(sid, data):
    print(f"message from {sid}: {data}")
    await sio.emit("message", f"Message received: {data}", room=sid)


if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=8000)
"

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content="fastapi
python-socketio
uvicorn
", file_path="/home/coder/infra2/servers/multi_agent_comm_server/requirements.txt"

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content="import socketio

sio = socketio.Client()


@sio.event
def connect():
    print("connection established")
    sio.emit("message", "hello world")


@sio.event
def disconnect():
    print("disconnected from server")


@sio.on("message")
def message(data):
    print(f"message received: {data}")
    sio.disconnect()


if __name__ == "__main__":
    sio.connect("http://localhost:8000")
    sio.wait()
", file_path="/home/coder/infra2/servers/multi_agent_comm_server/client.py"

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file_path="/home/coder/infra2/servers/multi_agent_comm_server/BUILD.bazel", content="load("@rules_python//python:defs.bzl", "py_binary")
load("@pip_deps//:requirements.bzl", "requirement")

py_binary(
    name = "server",
    srcs = ["main.py"],
    deps = [
        requirement("fastapi"),
        requirement("python-socketio"),
        requirement("uvicorn"),
    ],
)

py_binary(
    name = "client",
    srcs = ["client.py"],
    deps = [
        requirement("python-socketio"),
    ],
)
"

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absolute_path="/home/coder/infra2/MODULE.bazel"

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command="mv servers/multi_agent_comm_server/requirements.txt requirements-server.txt", description="Move the server's requirements file to the project root."

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file_path="/home/coder/infra2/tmp/blocker_message.md", content="Subject: Blocked: External Dependency Management for multi_agent_server

Hi gemini-prime,

I am currently working on the `multi_agent_server` project and have reached the step of integrating the server's Python dependencies (`fastapi`, `python-socketio`, `uvicorn`) into the Bazel build system via `MODULE.bazel`.

The user has informed me that this is a known, persistent issue that both you and `gemini-worker` have encountered. To avoid duplicating effort on a known problem, I am pausing my implementation work on this dependency integration.

I am escalating this blocker to you. Could you please provide guidance on the correct, working procedure for adding new Python pip dependencies to the Bazel workspace?

My current project context is recorded in `ai/projects/multi_agent_server/checkpoints/001-implementation-plan-created.md`.

Regards,
gemini-devops
"

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description="Send a message to gemini-prime about the Bazel dependency blocker.", command="python3 scripts/send_agent_message.py gemini-prime --sender-handle gemini-devops --subject "Blocked: External Dependency Management for multi_agent_server" --content-file tmp/blocker_message.md"

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content="# Checkpoint: 002 - Blocked on Bazel Dependency Management

## Mission

*   **Primary Goal**: Build and operationalize a production-ready, WebSocket-based server for real-time, multi-agent communication.
*   **Current Focus**: Blocked. Awaiting guidance on a workspace-wide Bazel/Python dependency issue.

## Project Sequence

*   [001-implementation-plan-created.md](001-implementation-plan-created.md)
*   [000-initial-project-setup.md](000-initial-project-setup.md)

## Executive Summary of Last Conversation

I began executing Phase 1 of the implementation plan. After discovering the original Proof-of-Concept code was missing, I recreated the necessary server files (`main.py`, `client.py`, `requirements.txt`) from scratch. I then created a `BUILD.bazel` file. However, upon attempting to integrate the new Python dependencies into the workspace `MODULE.bazel`, the user informed me that this is a known, persistent blocker that has affected other agents. I have paused my implementation and escalated the issue to `gemini-prime` for guidance.

## Checkpoint: The Concrete Problem

*   **Key Decisions**:
    *   Paused implementation of the `multi_agent_server` due to a known issue with Bazel/Python dependency management.
    *   Escalated the blocker to `gemini-prime` for a canonical solution.
*   **Key Findings**:
    *   The Proof-of-Concept code from the `de-risk_multi_agent_architecture` project was not present in the filesystem, requiring the server code to be recreated.
    *   There is a systemic, unresolved issue with adding new Pip dependencies to the Bazel build system.
*   **Key Identifiers**:
    *   Bazel, Pip, `MODULE.bazel`
    *   Blocker, Escalation
*   **Next Steps**:
    *   **Blocked**: Awaiting a response and guidance from `gemini-prime` on how to correctly manage Python dependencies within Bazel.
*   **Key Artifacts**:
    *   `servers/multi_agent_comm_server/main.py`
    *   `servers/multi_agent_comm_server/client.py`
    *   `servers/multi_agent_comm_server/requirements.txt`
    *   `servers/multi_agent_comm_server/BUILD.bazel`
    *   Message to `gemini-prime`: `20250823050348_Blocked_External_Dependency_Management_for_multi_agent_server.md`
", file_path="/home/coder/infra2/ai/projects/multi_agent_server/checkpoints/002-blocked-on-bazel-dependencies.md"

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command="rm tmp/blocker_message.md", description="Remove the temporary message file."

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