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PRODUCTION_GUIDE.md

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Agent Production Guide

A Complete Guide from Demo to Production

Table of Contents

1. Demo Features

This project is a teaching-level demo that demonstrates the core concepts and execution flow of an Agent. To reach production level, many complex issues still need to be addressed.

What We've Implemented (Demo Level)

Feature Demo Implementation
Context Management ✅ Simple persistence via SessionNoteTool with file storage; basic summarization when approaching context window limit
Tool Calling ✅ Basic Read/Write/Edit/Bash
Error Handling ✅ Basic exception catching
Logging ✅ Simple print output

2. Upgrade Directions

2.1 Advanced Context Management

  • Introduce distributed file systems for unified context persistence management and backup
  • Use more precise methods for token counting
  • Introduce more strategies for message compression, including keeping the most recent N messages, preserving fixed metadata, prompt optimization for summarization, introducing recall systems, etc.

2.2 Model Fallback Mechanism

Currently using a single fixed model (MiniMax-M2), which will directly report errors on failure.

  • Introduce a model pool by configuring multiple model accounts to improve availability
  • Introduce automatic health checks, failure removal, circuit breaker strategies for the model pool

2.3 Model Hallucination Detection and Correction

Currently directly trusts model output without validation mechanism

  • Perform security checks on input parameters for certain tool calls to prevent high-risk actions
  • Perform reflection on results from certain tool calls to check if they are reasonable

3. Production Deployment

3.1 Container Deployment Recommendations

We recommend using K8s/Docker environments for Agent deployment. Containerized deployment has the following advantages:

  • Resource Isolation: Each Agent instance runs in an independent container without interference
  • Elastic Scaling: Automatically adjust instance count based on load
  • Version Management: Easy rollback and canary releases
  • Environment Consistency: Development, testing, and production environments are completely consistent

3.2 Resource Limit Configuration

3.2.1 CPU and Memory Limits

To prevent the Agent from consuming excessive CPU/Memory resources and affecting the host, CPU and memory limits must be set:

Docker Configuration Example:

# docker-compose.yml
services:
  agent:
    image: agent-demo:latest
    deploy:
      resources:
        limits:
          cpus: '2.0'      # Maximum 2 CPU cores
          memory: 2G       # Maximum 2GB memory
        reservations:
          cpus: '0.5'      # Guarantee at least 0.5 cores
          memory: 512M     # Guarantee at least 512MB

3.2.2 Disk Limits

Agents may generate large amounts of temporary files and log files, so disk usage needs to be limited:

Docker Volume Configuration:

# docker-compose.yml
services:
  agent:
    volumes:
      - type: tmpfs
        target: /tmp
        tmpfs:
          size: 1G         # Maximum 1GB for temporary files
      - type: volume
        source: agent-data
        target: /app/data
        volume:
          driver_opts:
            size: 5G       # Maximum 5GB for data volume

3.3 Linux Account Permission Restrictions

3.3.1 Principle of Least Privilege

Never run the Agent as root user, as this poses serious security risks.

Dockerfile Best Practices:

FROM python:3.11-slim

# Install necessary system tools
RUN apt-get update && apt-get install -y \
    git \
    curl \
    && rm -rf /var/lib/apt/lists/*

# Install uv
RUN curl -LsSf https://astral.sh/uv/install.sh | sh
ENV PATH="/root/.cargo/bin:$PATH"

# Create non-privileged user
RUN groupadd -r agent && useradd -r -g agent agent

# Set working directory
WORKDIR /app

# Option 1: Clone from Git repository (for public repos)
RUN git clone https://github.com/MiniMax-AI/agent-demo.git . && \
    chown -R agent:agent /app

# Option 2: Copy code from local (for private deployments)
# COPY --chown=agent:agent . /app

# Switch to non-privileged user before installing dependencies
USER agent

# Sync dependencies using uv
RUN uv sync

# Start the application
CMD ["uv", "run", "python", "main.py"]

3.3.2 File System Permissions

Restrict the Agent to only access necessary directories:

# Create restricted workspace directory
mkdir -p /app/workspace
chown agent:agent /app/workspace
chmod 750 /app/workspace  # Owner: read/write/execute, Group: read/execute

# Restrict access to sensitive directories
chmod 700 /etc/agent      # Config directory only accessible by owner
chmod 600 /etc/agent/*.yaml  # Config files only readable/writable by owner