> ## Documentation Index
> Fetch the complete documentation index at: https://praison.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# PraisonAI Code UI

> Guide to PraisonAI's code interface for interacting with your codebase using AI, including file management, model configuration, and advanced features

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</div>

PraisonAI Code helps you to interact with your whole codebase using the power of AI.

## Different User Interfaces:

| Interface | Description                                | URL                                                                |
| --------- | ------------------------------------------ | ------------------------------------------------------------------ |
| **UI**    | Multi-Agent Systems Interface              | [https://praison.ai/docs/ui/ui](https://praison.ai/docs/ui/ui)     |
| **Chat**  | Chat with 100+ LLMs, single AI Agent       | [https://praison.ai/docs/ui/chat](https://praison.ai/docs/ui/chat) |
| **Code**  | Chat with entire Codebase, single AI Agent | [https://praison.ai/docs/ui/code](https://praison.ai/docs/ui/code) |

## Table of Contents

* [Install PraisonAI Code](#install-praisonai-code)
* [Other Models](#other-models)
* [To Use Gemini 1.5](#to-use-gemini-15)
* [Ignore Files](#ignore-files)
  * [Using .praisonignore](#using-praisonignore)
  * [Using settings.yaml](#using-settingsyaml)
  * [Using .env File](#using-env-file)
  * [Using Environment Variables in the Terminal](#using-environment-variables-in-the-terminal)
* [Include Files](#include-files-praisoninclude)
* [Set Max Tokens](#set-max-tokens)

## Install PraisonAI Code

1.

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
pip install "praisonai[code]"
```

2.

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
export OPENAI_API_KEY=xxxxxxxx
```

## AICoder Component Dependencies

The AICoder UI component requires all dependencies to be installed:

**Required dependencies:**

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
pip install litellm tavily crawl4ai
```

**Environment variables (optional):**

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
export TAVILY_API_KEY=your-tavily-key  # If using web search
```

**Error behavior**: If any dependency is missing, you'll see a `ModuleNotFoundError` when trying to import the AICoder component, since all imports are unconditional in the module.

3.

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
praisonai code
```

4. Username and Password will be asked for the first time. `admin` is the default username and password.

5. Set Model name to be gpt-4o-mini in the settings

## Other Models

* Use 100+ LLMs - [Litellm](https://litellm.vercel.app/docs/providers)
* Includes Gemini 1.5 for 2 Million Context Length

## To Use Gemini 1.5

* `export GEMINI_API_KEY=xxxxxxxxx`
* `praisonai code`
* Set Model name to be `gemini/gemini-1.5-flash` in the settings

## Ignore Files

### Using .praisonignore

* Create a `.praisonignore` file in the root folder of the project
* Add files to ignore

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
.*
*.pyc
pycache
.git
.gitignore
.vscode
.idea
.DS_Store
.lock
.pyc
.env
```

### Using settings.yaml

(.praisonignore is preferred)

* Create a `settings.yaml` file in the root folder of the project
* Add below Variables and required Ignore Files

```yaml theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
code:
  ignore_files:
  - ".*"
  - "*.pyc"
  - "pycache"
  - ".git"
  - ".gitignore"
  - ".vscode"
  - ".idea"
  - ".DS_Store"
  - ".lock"
  - ".pyc"
  - ".env"
```

### Using .env File

* Create a `.env` file in the root folder of the project
* Add below Variables and required Ignore Files

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
PRAISONAI_IGNORE_FILES=".*,*.pyc,__pycache__,.git,.gitignore,.vscode"
```

### Using Environment Variables in the Terminal

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
export PRAISONAI_IGNORE_FILES=".*,*.pyc,__pycache__,.git,.gitignore,.vscode"
```

## Include Files .praisoninclude

* Add files you wish to Include files in the context
* This will include the files/folders mentioned in `.praisoninclude` to the original context (files in the folder - .gitignore  - .praisonignore)

- Create a `.praisoninclude` file in the root folder of the project
- Add files to Include

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
projectfiles
docs
```

## Include ONLY these Files .praisoncontext (Context)

* Add files you wish to Include files in the context
* This will include ONLY the files/folders mentioned in `.praisoncontext` to the context

- Create a `.praisoncontext` file in the root folder of the project
- Add files to Include

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
projectfiles
docs
```

## Set Max Tokens

Note: By Default Max Tokens set is 900,000

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
export PRAISONAI_MAX_TOKENS=1000000
```

or

* Create a .env file in the root folder of the project
* Add below Variables and required Max Tokens
* ```
  PRAISONAI_MAX_TOKENS=1000000
  ```

## Default DB Location

`~/.praisonai/database.sqlite`

## Key Features

### Internet Search

PraisonAI Code now includes internet search capabilities using Crawl4AI and Tavily. This feature allows you to retrieve up-to-date information and code snippets during your coding sessions, enhancing your ability to find relevant programming information and examples.

To use this feature:

1. Ask a question or request information about a specific coding topic
2. The AI will use internet search to find the most relevant and current information
3. You'll receive code snippets, documentation references, or explanations based on the latest available resources

### Vision Language Model (VLM) Support

While primarily designed for code interactions, PraisonAI Code also supports Vision Language Model capabilities. This feature can be particularly useful when dealing with visual aspects of programming, such as UI design, data visualization, or understanding code structure through diagrams.

To use this feature:

1. Upload an image related to your coding query (e.g., a screenshot of a UI, a flowchart, or a code snippet image)
2. Ask questions or request analysis based on the uploaded image
3. The VLM will process the image and provide insights or answers based on its visual content, helping you understand or implement the visual concepts in your code

These new features significantly expand the capabilities of PraisonAI Code, allowing for more comprehensive and up-to-date coding assistance.

## External Agents

The PraisonAI Code interface now includes sidebar toggles for external AI coding CLIs. These toggles appear automatically when the corresponding CLI tools are installed and available on your system PATH.

### Available External Agents

* **Claude Code Toggle**: Enable Claude Code CLI integration for advanced file editing and code analysis
* **Gemini CLI Toggle**: Enable Google Gemini CLI for code analysis and search capabilities
* **Codex CLI Toggle**: Enable OpenAI Codex CLI for code refactoring and optimization
* **Cursor CLI Toggle**: Enable Cursor CLI for IDE-style development tasks

### How It Works

1. **Auto-Detection**: Toggles only appear for CLIs that are installed and available via `shutil.which()`
2. **Sidebar Integration**: Toggle switches appear in the Code UI sidebar settings
3. **Persistence**: Toggle states persist across sessions via Chainlit settings
4. **Dynamic Instructions**: Enabled agents modify the assistant's system instructions
5. **Workspace Context**: External agents operate against `PRAISONAI_CODE_REPO_PATH`

### Backward Compatibility

The new toggles replace the previous single "Enable Claude Code" switch. Legacy settings are automatically migrated:

* `claude_code_enabled` setting → `claude_enabled`
* `PRAISONAI_CLAUDECODE_ENABLED` environment variable → `claude_enabled`

<Note>
  For complete documentation on external agents UI toggles across all PraisonAI interfaces, see [External Agents in UI](/docs/features/external-agents-ui).
</Note>

## Local Docker Development with Live Reload

To facilitate local development with live reload, you can use Docker. Follow the steps below:

1. **Create a `Dockerfile.dev`**:
   ```dockerfile theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
   FROM python:3.11-slim

   WORKDIR /app

   COPY . .

   RUN pip install flask praisonai==2.2.25 watchdog

   EXPOSE 5555

   ENV FLASK_ENV=development

   CMD ["flask", "run", "--host=0.0.0.0"]
   ```

2. **Create a `docker-compose.yml`**:
   ```yaml theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
   version: '3.8'

   services:
     app:
       build:
         context: .
         dockerfile: Dockerfile.dev
       volumes:
         - .:/app
       ports:
         - "5555:5555"
       environment:
         FLASK_ENV: development
       command: flask run --host=0.0.0.0

     watch:
       image: alpine:latest
       volumes:
         - .:/app
       command: sh -c "apk add --no-cache inotify-tools && while inotifywait -r -e modify,create,delete /app; do kill -HUP 1; done"
   ```

3. **Run Docker Compose**:
   ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
   docker-compose up
   ```

This setup will allow you to develop locally with live reload, making it easier to test and iterate on your code.