CoStrict Backend Deployment Tool

Project Overview

CoStrict Backend Deployment Tool is an enterprise-level AI code assistant backend service deployment solution based on Docker Compose. This project provides a complete microservice architecture, including core components such as AI gateway, identity authentication, code analysis, and chat services, supporting both private deployment and cloud service modes.

Core Features

Microservice Architecture: Containerized distributed service architecture
AI Gateway Integration: Support for multiple large language model access
Identity Authentication System: Integrated with Casdoor for enterprise-level identity management
Intelligent Code Analysis: Provides code review, completion, optimization and other functions
Scalable Design: Support for horizontal scaling and custom plugins

System Architecture

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│  VSCode Plugin  │────│   API Gateway   │────│ Backend Services│
│   (CoStrict)    │    │ (Apache APISIX) │    │ (Microservices) │
└─────────────────┘    └─────────────────┘    └─────────────────┘
                               │                        │
                        ┌─────────────────┐    ┌─────────────────┐
                        │   AI Gateway    │    │ Database Cluster│
                        │   (Higress)     │    │   (PostgreSQL)  │
                        └─────────────────┘    └─────────────────┘

System Requirements

Model Requirements

The core functions of CoStrict all depend on large language models, and you need to prepare the following model services and ensure that the model interfaces are functioning properly:

Chat model (providing complete http://chat_model_ip:chat_model_port/v1/chat/completions interface)
Code review model (providing complete http://review_model_ip:review_model_port/v1/chat/completions interface)
Embedding model (providing complete http://embedding_model_ip:embedding_model_port/v1/embeddings interface)
Rerank model (providing complete http://rerank_model_ip:rerank_model_port/v1/rerank interface)
Completion model (providing complete http://completion_model_ip:completion_model_port/v1/completions interface)

Note: Provide and record accurate MODEL NAMES, APIKEYs, and CONTEXT LENGTHS information. Used for configuration during service deployment.

Recommended Models and Download Addresses:

Chat Model: GLM-4.5-FP8, GLM-4.5-106B-A12B-FP8
Code Review Model: Qwen2.5-Coder-32B-Instruct, Qwen3.0-Coder-30B-A3B-Instruct
Completion Model: DeepSeek-Coder-V2-Lite-Base
Embedding Model: gte-modernbert-baseRAG/Embedding
Rerank Model: gte-reranker-modernbert-baseRAG/Rerank
Download Addresses:

https://modelscope.cn/models/ZhipuAI/GLM-4.5-FP8
https://modelscope.cn/models/ZhipuAI/GLM-4.5-Air-FP8
https://modelscope.cn/models/Qwen/Qwen2.5-Coder-32B-Instruct
https://modelscope.cn/models/Qwen/Qwen3-Coder-30B-A3B-Instruct
https://modelscope.cn/models/deepseek-ai/DeepSeek-Coder-V2-Lite-Base
https://modelscope.cn/models/iic/gte-modernbert-base
https://modelscope.cn/models/iic/gte-reranker-modernbert-base

Recommended Model Deployment Resources:

Chat Model: 4 * H20 or 4 * RTX4090
Code Review Model: 2 * H20 or 2 * RTX4090
Completion Model: 1 * H20 or 1 * RTX4090
Embedding Model: 0.5 * H20 or 0.5 * RTX4090
Rerank Model: 0.5 * H20 or 0.5 * RTX4090

Trial Reminder:

If you have resources, to try the complete functionality, please ensure all models meet the above requirements when deployed.
If you don't have resources, we can provide two options:
- Use our officially released CoStrict directly without additional deployment to experience all CoStrict features.
- We provide time-limited online conversation and code review model interfaces for short-term experience of CoStrict's main AGENT and CODE REVIEW features.

Feature	Self-deployed (Models Meet Requirements)	Official CoStrict Release	Time-limited Interface
AGENT(Vibe)	✅ Full functionality	✅ Full functionality	✅ Time-limited experience (Missing Codebase)
AGENT(Strict)	✅ Full functionality	✅ Full functionality	✅ Time-limited experience (Missing Codebase)
CODE REVIEW	✅ Full functionality	✅ Full functionality	✅ Time-limited experience
Code Completion	✅ Full functionality	✅ Full functionality	❌ Not supported
CoStrict Online Interface Access	✅ No need to access CoStrict online interface	❌ Requires access to CoStrict online interface	❌ Requires access to CoStrict online interface

Self-deployed Backend Service Instance Environment

Hardware Requirements:

CPU: Intel x64 architecture, minimum 16 cores
Memory: Minimum 32GB RAM
Storage: Minimum 512GB available storage space

Software Requirements:

Operating System: CentOS 7+ or Ubuntu 18.04+ (WSL supported)
Container Runtime: Docker 20.10+ (refer to Offline Docker Installation for offline installation)
Orchestration Tool: Docker Compose 2.0+

Deployment Checklist

Before starting the deployment, please simultaneously open and view the Deployment Checklist and check and complete all checklist items throughout the deployment process to ensure a successful final deployment.

Quick Start

1. Get Deployment Code

Method 1: Git Clone

# Clone the repository
git clone https://github.com/zgsm-ai/zgsm-backend-deploy.git

# Enter the project directory
cd zgsm-backend-deploy

# Switch to the latest version branch
git checkout v4

# Add execute permissions to all executable files in the directory
bash add-exec-permission.sh

Method 2: Download ZIP Package

# Download the latest version branch ZIP package
wget https://github.com/zgsm-ai/zgsm-backend-deploy/archive/refs/heads/v4.zip -O zgsm-backend-deploy-4.zip

# Extract the ZIP package
unzip zgsm-backend-deploy-4.zip

# Enter the extracted directory (GitHub default extraction directory name is repository-name-branch-name)
cd zgsm-backend-deploy-4

# Add execute permissions to all executable files in the directory
bash add-exec-permission.sh

2. Environment Configuration

Edit the configuration file:

vim configure.sh

Key Configuration Parameters:

Review and modify the following two types of configuration parameters and save:

Basic Service Settings

Parameter Name	Description	Default Value	Required
`COSTRICT_BACKEND_BASEURL`	Backend service base URL	-	✅
`COSTRICT_BACKEND`	Backend service host address	-	✅
`PORT_APISIX_ENTRY`	API gateway entry port	9080	✅
`PORT_HIGRESS_CONTROL`	Higress console port	8001	✅
`PORT_CASDOOR`	Casdoor authentication system port	9009	✅

Model Settings

Parameter Name	Description	Default Value	Required
`CHAT_MODEL_HOST`	IP+PORT of chat model	-	✅
`CHAT_BASEURL`	Access address of chat model	-	✅
`CHAT_DEFAULT_MODEL`	Name of chat model	-	✅
`CHAT_MODEL_CONTEXTSIZE`	Context length of chat model	-	✅
`CHAT_MODEL_DESC`	Description of chat model	-	❌
`CHAT_APIKEY`	APIKEY of chat model, required if the model enables APIKEY authentication	-	❌
`CODEREVIEW_MODEL_HOST`	IP+PORT of Codereview model	-	✅
`CODEREVIEW_BASEURL`	Access address of Codereview model	-	✅
`CODEREVIEW_MODEL`	Name of Codereview model	-	✅
`CODEREVIEW_MODEL_CONTEXTSIZE`	Context length of Codereview model	-	✅
`CODEREVIEW_MODEL_DESC`	Description of Codereview model	-	❌
`CODEREVIEW_APIKEY`	APIKEY of Codereview model, required if the model enables APIKEY authentication	-	❌
`COMPLETION_BASEURL`	Access address of code completion model	-	✅
`COMPLETION_MODEL`	Name of code completion model	-	✅
`COMPLETION_APIKEY`	APIKEY of code completion model, required if the model enables APIKEY authentication	-	❌
`EMBEDDER_BASEURL`	Access address of vector embedding model	-	✅
`EMBEDDER_MODEL`	Name of vector embedding model	-	✅
`EMBEDDER_APIKEY`	APIKEY of vector embedding model, required if the model enables APIKEY authentication	-	❌
`RERANKER_BASEURL`	Access address of rerank model	-	✅
`RERANKER_MODEL`	Name of rerank model	-	✅
`RERANKER_APIKEY`	APIKEY of rerank model, required if the model enables APIKEY authentication	-	❌

Note: Code completion, vector embedding, and rerank models are for internal use by CoStrict only and will not appear in the user-selectable model list.

3. Prepare Backend Service Images

CoStrict backend images are mainly stored in the docker hub image repository docker.io/zgsm.

Before deployment, you need to ensure that the images required for backend deployment can be pulled from the image repository normally.

The images required by CoStrict backend can be found in the scripts/newest-images.list file for a complete list.

If the scripts/newest-images.list file does not exist, you can get this list file from the cloud with the following command.

bash scripts/get-images-list.sh -o scripts

The deployment script will automatically pull all images required for backend deployment during the deployment process.

However, if the deployment server cannot access the docker hub image repository, you need to download the images in advance and save them to the specified directory of the deployment machine (assuming saved in /root/images). Then run the following command to preload them.

bash scripts/load-images.sh -l /root/images

In addition to pulling and exporting image files from the docker image repository, you can also download all image files required for CoStrict backend deployment from Baidu Netdisk.

Netdisk address:

https://pan.baidu.com/s/12kP5VyQinFNrXFsKEWFGJw?pwd=k2dh

4. Service Deployment

Note: Before executing the automated deployment script below, please ensure that checklist items in sections 1.1~2.2 of the Deployment Checklist have been completed.

Execute the automated deployment script:

bash deploy.sh

The deployment process includes the following steps:

Environment check and dependency verification
Docker image pulling and building
Database initialization
Service container startup
Health check and status verification

Service Configuration

AI Gateway Configuration (Higress)

After deployment, access the Higress console at the following address to check and adjust the configuration of the chat and code review models:

http://{COSTRICT_BACKEND}:{PORT_HIGRESS_CONTROL}

Default admin username and password (please change it after login):

Username: admin
Password: test123

Configuration steps:

Access the Higress management interface
Configure upstream LLM service providers
Set routing rules and load balancing strategies
Configure rate limiting and security policies

Detailed configuration guide: Higress Configuration Document

Optional: Identity Authentication System Configuration (Casdoor)

Access the Casdoor management interface at the following address:

http://{COSTRICT_BACKEND}:{PORT_CASDOOR}

Test Account (for development and testing environments only):

Username: demo
Password: test123

Configuration features:

User management and permission control
Third-party identity provider integration (OIDC/SAML)
Multi-factor authentication (MFA)
Session management and security policies

Detailed configuration guide: Casdoor Configuration Document

Client Integration

CoStrict Plugin Configuration

Install the CoStrict VSCode extension
Open the "Provider" page in the extension settings
Select the API provider as "CoStrict"

Configure the backend service address:

CoStrict Base URL: {COSTRICT_BACKEND_BASEURL}

Click "Login CoStrict" to complete authentication

Detailed installation guide: CoStrict Download and Installation Documentation (includes VSCode and JetBrains IDE)

Service Access Address:

Default backend entry: http://{COSTRICT_BACKEND}:{PORT_APISIX_ENTRY}

Domain Binding and Load Balancing

For production environments, it is recommended to access services through reverse proxy or load balancer:

# Nginx configuration example
upstream costrict_backend {
    server {COSTRICT_BACKEND}:{PORT_APISIX_ENTRY};
}

server {
    listen 443 ssl;
    server_name your-domain.com;
    
    location / {
        proxy_pass http://costrict_backend;
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
    }
}

Operations Management

Service Status Monitoring

Check service running status:

# View all service status
docker-compose ps

# View service logs
docker-compose logs -f [service_name]

# View resource usage
docker stats

Data Backup and Recovery

# Database backup
bash ./scripts/backup.sh

# Database recovery
bash ./scripts/restore.sh [backup_file]

Service Scaling

# Scale service instances
docker-compose up -d --scale chatgpt=3

# Update service configuration
docker-compose up -d --force-recreate [service_name]

Troubleshooting

Common Issues

1. Container startup failure

# Check port occupancy
netstat -tlnp | grep {port}

# Check disk space
df -h

# View detailed error logs
docker-compose logs [service_name]

2. Network connection issues

# Test service connectivity
curl -v http://{COSTRICT_BACKEND}:{PORT_APISIX_ENTRY}/health

# Check Docker network
docker network ls
docker network inspect {network_name}

3. Database connection issues

# Check database service status
docker-compose exec postgres pg_isready

# View database logs
docker-compose logs postgres

Log Collection

System log locations:

Application logs: ./logs/
Database logs: /var/log/postgresql/ inside container
Gateway logs: /var/log/apisix/ inside container

Security Notes

Production Environment Deployment:
- Change all default passwords
- Configure HTTPS certificates
- Enable firewall and access control
- Regularly update systems and dependencies
Network Security:
- Only open necessary ports
- Configure VPN or intranet access
- Enable API rate limiting and protection
Data Protection:
- Regularly backup important data
- Enable database encryption
- Configure access audit logs

CoStrict - Let AI power your code development journey

Project Overview​

Core Features​

System Architecture​

System Requirements​

Model Requirements​

Self-deployed Backend Service Instance Environment​

Deployment Checklist​

Quick Start​

1. Get Deployment Code​

2. Environment Configuration​

3. Prepare Backend Service Images​

4. Service Deployment​

Service Configuration​

AI Gateway Configuration (Higress)​

Optional: Identity Authentication System Configuration (Casdoor)​

Client Integration​

CoStrict Plugin Configuration​

Domain Binding and Load Balancing​

Operations Management​

Service Status Monitoring​

Data Backup and Recovery​

Service Scaling​

Troubleshooting​

Common Issues​

Log Collection​

Security Notes​