### Initialize Whisker Server with One-Click Script

Source: https://github.com/petercat-ai/whiskerrag/blob/main/server/readme.md

This Python script automates the initial setup steps, including cloning the project, installing Poetry, configuring virtual environments, and installing dependencies.

```python
python init.py
```

--------------------------------

### Start the Whisker Server Development Server

Source: https://github.com/petercat-ai/whiskerrag/blob/main/server/readme.md

This command starts the development server for the Whisker Server project, allowing you to run and test the application locally.

```bash
poetry run dev
```

--------------------------------

### Troubleshoot Dependency Installation Failure

Source: https://github.com/petercat-ai/whiskerrag/blob/main/server/readme.md

If the standard 'poetry install' command fails, this alternative command can be used to attempt installation without the root project.

```bash
poetry install --no-root
```

--------------------------------

### Install Specific Plugin Dependencies

Source: https://github.com/petercat-ai/whiskerrag/blob/main/server/readme.md

This command allows for the individual installation of dependencies for a specific plugin, such as 'supabase' and 'boto3'.

```bash
poetry run pip install supabase boto3
```

--------------------------------

### Install Project Dependencies with Poetry

Source: https://github.com/petercat-ai/whiskerrag/blob/main/server/readme.md

This command installs all the necessary dependencies for the Whisker Server project as defined in the pyproject.toml file.

```bash
poetry install
```

--------------------------------

### Install Plugin Dependencies

Source: https://github.com/petercat-ai/whiskerrag/blob/main/server/readme.md

This command installs dependencies required for plugins located in the 'plugins' directory, specifically for the supabase_aws_plugin.

```bash
poetry run pip install -r supabase_aws_plugin/requirements.txt
```

--------------------------------

### Format Code with Black and Isort

Source: https://github.com/petercat-ai/whiskerrag/blob/main/server/readme.md

This command formats the project's code according to predefined style guides using the 'black' and 'isort' tools, ensuring code consistency.

```bash
poetry run format
```

--------------------------------

### Install Poetry for Dependency Management

Source: https://github.com/petercat-ai/whiskerrag/blob/main/server/readme.md

This command installs Poetry, a tool for dependency management and packaging in Python. It's a prerequisite for managing the project's dependencies.

```bash
pip install poetry
```

--------------------------------

### Clone and Navigate Whisker Server Project

Source: https://github.com/petercat-ai/whiskerrag/blob/main/server/readme.md

This snippet shows how to clone the Whisker Server repository from GitHub and navigate into the server directory. It's the first step in setting up the project.

```bash
git clone https://github.com/petercat-ai/whiskerrag.git
cd whisker/server
```

--------------------------------

### Run Project Tests

Source: https://github.com/petercat-ai/whiskerrag/blob/main/server/readme.md

This command executes the project's test suite to ensure all functionalities are working as expected.

```bash
poetry run test
```

--------------------------------

### Check Python Version

Source: https://github.com/petercat-ai/whiskerrag/blob/main/server/readme.md

This command verifies that the installed Python version meets the project's requirement of Python 3.11 or higher.

```bash
python3 --version
```

--------------------------------

### Uninstall Plugin Dependencies

Source: https://github.com/petercat-ai/whiskerrag/blob/main/server/readme.md

This command uninstalls dependencies associated with the supabase_aws_plugin, helping to maintain a clean environment.

```bash
poetry run pip uninstall -r supabase_aws_plugin/requirements.txt
```

--------------------------------

### Docker Deployment for WhiskerRAG

Source: https://github.com/petercat-ai/whiskerrag/blob/main/README.md

This snippet outlines the Docker commands for building, starting, stopping, restarting, and managing WhiskerRAG services. It includes commands for individual service management and full stack operations.

```bash
docker login

  # 先构建镜像
docker-compose build --no-cache
 # 后台启动服务
docker-compose up -d

# 启动所有服务
docker-compose start

# 停止所有服务
docker-compose stop

# 重启所有服务
docker-compose restart

# 启动特定服务
docker-compose start postgres

# 停止特定服务
docker-compose stop postgres

# 删除所有服务
docker-compose down
```

--------------------------------

### Local Deployment with Docker Compose

Source: https://github.com/petercat-ai/whiskerrag/blob/main/README.en-US.md

Commands to manage the WhiskerRAG services using Docker Compose for local deployment. This includes logging in, building, starting, stopping, restarting, and removing services.

```Bash
docker login

# Build all images
docker-compose up --build -d
docker-compose up -e API_KEY=mysecretkey -e DEBUG=true -e DB_HOST=postgres

# Start all services
docker-compose start

# Stop all services
docker-compose stop

# Restart all services
docker-compose restart

# Start specific service
docker-compose start postgres

# Stop specific service
docker-compose stop postgres

# Remove all services
docker-compose down
```

--------------------------------

### Configure Poetry to Use Local Virtual Environments

Source: https://github.com/petercat-ai/whiskerrag/blob/main/server/readme.md

This command configures Poetry to create virtual environments within the project directory, which is highly recommended for project isolation.

```bash
poetry config virtualenvs.in-project true
```

--------------------------------

### Run Type Checking

Source: https://github.com/petercat-ai/whiskerrag/blob/main/server/readme.md

This command performs static type checking on the project's codebase using 'mypy' to catch potential type-related errors.

```bash
poetry run type-check
```

--------------------------------

### AWS and Supabase Configuration for WhiskerRAG

Source: https://github.com/petercat-ai/whiskerrag/blob/main/README.md

This snippet shows environment variable configurations for deploying WhiskerRAG using AWS Cloud and Supabase. It covers settings for task engines, database connections, table names, and API keys for OpenAI and AWS.

```bash
TASK_ENGINE_CLASSNAME="AWSLambdaTaskEnginePlugin"
DB_ENGINE_CLASSNAME="SupaBasePlugin"
# 数据库
SUPABASE_URL=your-supabase-url
SUPABASE_SERVICE_KEY=your-supabase-service-key
# 表名
KNOWLEDGE_TABLE_NAME=knowledge
API_KEY_TABLE_NAME=api_key
CHUNK_TABLE_NAME=chunk
TASK_TABLE_NAME=task
TENANT_TABLE_NAME=tenant
# LLM
OPENAI_API_KEY=your-openai-api-key
# AWS
SQS_QUEUE_URL=your-sqs-queue-url
```

--------------------------------

### AWS Cloud & Supabase Configuration

Source: https://github.com/petercat-ai/whiskerrag/blob/main/README.en-US.md

Environment variables required for configuring WhiskerRAG for AWS Cloud and Supabase integration. This includes settings for task engines, database engines, Supabase credentials, table names, OpenAI API key, and AWS SQS queue URL.

```Bash
TASK_ENGINE_CLASSNAME="AWSLambdaTaskEnginePlugin"
DB_ENGINE_CLASSNAME="SupaBasePlugin"
FASTAPI_ENGINE_CLASSNAME="fastAPIPlugin"
# db
SUPABASE_URL=your-supabase-url
SUPABASE_SERVICE_KEY=your-supabase-service-key
# table name
KNOWLEDGE_TABLE_NAME=knowledge
API_KEY_TABLE_NAME=api_key
CHUNK_TABLE_NAME=chunk
TASK_TABLE_NAME=task
TENANT_TABLE_NAME=tenant
# llm
OPENAI_API_KEY=your-openai-api-key
# aws
SQS_QUEUE_URL=your-sqs-queue-url
```

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