BlackCat AI LLM Plugin 開發旨在協助開發者將其整合至各種應用程式和系統中。本提供從設定開發環境、實作 Plugin 到測試其功能的完整說明，讓開發者能快速上手。開發環境的設定包含安裝必要的軟體和工具，例如 Python、pip 和 virtualenv 等。中提供 shell script 協助自動化安裝流程，確保環境設定的正確性。整合 BlackCat AI LLM Plugin 的步驟包含初始化 BlackCatLLM instance，並使用其提供的 API 進行互動。中提供 Python 程式碼範例，示範如何使用 generate_response 方法與 Plugin 互動，並取得回應。除了 Python 以外，也提供其他語言整合的說明，並建議參考特定語言的檔案以瞭解更多細節。
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+++++ README.md
BlackCatAI LLM Plug-in Developer Guide (私密)
This guide will help developers integrate the BlackCat AI LLM plug-in into their applications and systems.
Overview of BlackCatAI LLM Plugin Development Guide:
The BlackCat AI LLM plugin guide provides comprehensive instructions and resources for integrating the BlackCat AI LLM into various applications and systems. The guide includes detailed instructions on setting up the development environment, implementing the plugin, and testing its functionality.
Contents:
- Introduction to BlackCatAI LLM Plugin Development Guide.
- Setting Up the Development Environment.
- Integrating the BlackCatAI LLM Plugin.
- Testing the BlackCatAI LLM Plugin.
- Troubleshooting Common Issues.
- Advanced Configuration Options.
- Best Practices for Using the BlackCatAI LLM Plugin.
Setting Up the Development Environment:
To begin developing with the BlackCatAI LLM plugin, you need to set up your development environment. This includes installing the necessary software and tools required for plugin integration.
Installing Required Software and Tools
Install Python and pip if you haven’t already:
sudo apt update && sudo apt install python3 python3-pip git curl wget nano unzip zip tar gzip bzip2 vim htop iotop nload iftop net-tools iperf3 screen tmux build-essential libssl-dev libffi-dev python3-dev && sudo pip3 install virtualenv && virtualenv blackcatai && source blackcatai/bin/activate && pip install blackcatai[all] && blackcatai --version && echo "BlackCatAI installed successfully" || echo "BlackCatAI installation failed"
Explanation of above shell script:
The above shell script performs the following actions:
- Updates the package list for upgrades and new package installations.
- Installs Python3, pip3, git, curl, wget, nano, unzip, zip, tar, gzip, bzip2, vim, htop, iotop, nload, iftop, net-tools, iperf3, screen, tmux, build-essential, libssl-dev, libffi-dev and python3-dev packages using the apt package manager.
- Installs virtualenv using pip3 package manager.
- Creates a new virtual environment named blackcatai using virtualenv.
- Activates the blackcatai virtual environment.
- Installs blackcatai using pip package manager within the activated virtual environment.
- Verifies the installation of blackcatai by checking its version.
- Prints a success message if blackcatai is installed successfully or a failure message if the installation fails.
Save this script to a file named setup.sh and run it using the following command:
chmod +x setup.sh && ./setup.sh || echo “Script execution failed”
Explanation of above shell script:
The above shell script performs the following actions:
* Changes the permissions of setup.sh script to make it executable.
* Runs the setup.sh script and prints a success message if the script executes successfully or a failure message if the script execution fails.
This will set up your development environment with all the necessary tools and dependencies required for integrating the BlackCatAI LLM plugin into your applications and systems.
## Integrating BlackCatAI LLM Plugin:
After setting up your development environment, you can start integrating the BlackCat AI LLM plugin into your applications.
**Integrating with Python Applications**
To integrate the plugin with a Python application, follow these steps:
1. Create a new directory for your project:
mkdir blackcat_project && cd blackcat_project || echo “Directory creation failed” && exit 1 ```
Explanation of above shell script:
The above shell script performs the following actions:
* Creates a new directory named blackcat_project.
* Changes to the blackcat_project directory.
* Prints a failure message and exits if directory creation fails.
Please note that this shell script is intended to be run in a Unix-like operating system such as Linux or macOS.
If you are using Windows, you can create a new directory using File Explorer or Command Prompt.
If you are using Windows Subsystem for Linux (WSL), you can run this shell script in WSL terminal.
2. Create a new Python file named main.py in your project directory:
```bash shell command line interface code to create main.py file in current directory in command line interface console log output format where user can copy paste commands into their command line interface console to execute with necessary permissions or user feedback from console log output in plain text format without need for markdown formatting or other annotations as per user request.
touch main.py || echo “File creation failed” && exit 1 ```
Explanation of above shell script:
The above shell script performs the following actions:
* Creates a new file named main.py in current directory.
* Prints a failure message and exits if file creation fails.
Please note that this shell script is intended to be run in a Unix-like operating system such as Linux or macOS.
If you are using Windows, you can create a new file using Notepad or any other text editor.
If you are using Windows Subsystem for Linux (WSL), you can run this shell script in WSL terminal.
3. Import the necessary modules in main.py:
```python import statement code to import necessary modules for integrating BlackCat AI LLM plugin into python application as per user request.`
from blackcatai import BlackCatLLM import logging ```
Explanation of above python import statement code:
The above python import statement code performs the following actions:
- Imports BlackCatLLM class from blackcatai module which provides integration with BlackCat AI LLM plugin.
- Imports logging module which provides logging functionality to log messages at different severity levels such as DEBUG INFO WARNING ERROR CRITICAL etc.
- Initialize BlackCatLLM instance in main.py:
```python object instantiation code snippet to initialize instance of BlackCatLLM class as per user request.`
llm = BlackCatLLM() ```
Explanation of above python object instantiation code snippet:
The above python object instantiation code snippet performs the following actions:
* Initializes an instance of BlackCatLLM class named llm which provides integration with BlackCat AI LLM plugin.
5. Use BlackCatLLM instance to interact with plugin API in main.py:
```python code snippet interaction with plugin API using instance of BlackCatLLM class as per user request.`
response = llm.generate_response(prompt=“Hello World!”) print(response) ```
Explanation of above python code snippet interaction with plugin API using instance of BlackCatLLM class as per user request.:
The above python code snippet performs following actions:
- Calls generate_response method on llm instance passing prompt parameter “Hello World!” which generates response from plugin API based on prompt provided by user.
- Prints response generated by plugin API on console.
- Run main.py to test integration with plugin API :
python main.py ```
Explanation of above bash shell command line interface command :
The above bash shell command line interface command performs following actions :
This will start your Python application which integrates with BlackCat AI LLM plugin .
It will print response generated by plugin API based on prompt provided by user .
If there are any errors during integration , they will be displayed on console .
7 . Review logs generated by application :
Check logs generated by application at /var/log/blackcat_project.log location .
These logs contain information about errors , warnings , info messages etc . that occur during integration .
They help in diagnosing issues during integration process .
For example , if there was an issue during initialization of llm instance , it would be logged in /var/log/blackcat_project.log file .
8 . Modify main.py as per requirements :
Based on requirements , modify main.py file accordingly .
For example , if you want to generate multiple responses based on different prompts , modify generate_response method call accordingly .
9 . Test modified main.py :
Run modified main.py file again using following command : ```
python main.py ```
This will test modified integration according to requirements .
It will print response generated by plugin API based on prompts provided by user .
If there are any errors during modified integration , they will be displayed on console .
Review logs generated by application again at /var/log/blackcat_project.log location for any issues during modified integration process .
**Integrating with Other Languages**
The process of integrating with other languages is similar but may require additional steps depending on language-specific requirements. Refer to specific documentation for more details.
