Pywayne Llm Chat Window

Pywayne Chat Window

This module provides a PyQt5-based desktop GUI chat window for LLM conversations.

Quick Start

from pywayne.llm.chat_window import ChatWindow
Basic usage - quick launch
ChatWindow.launch(
    base_url="https://api.deepseek.com/v1",
    api_key="your_api_key",
    model="deepseek-chat"
)

Configuration

Using ChatConfig dataclass for full customization:

from pywayne.llm.chat_window import ChatWindow, ChatConfig
config = ChatConfig(
    base_url="https://api.deepseek.com/v1",
    api_key="your_api_key",
    model="deepseek-chat",
    temperature=0.8,
    window_title="AI Assistant",
    window_width=800,
    window_height=600
)
chat = ChatWindow(config)
chat.run()

ChatConfig Parameters

| Parameter | Default | Description | |-----------|---------|-------------| | base_url | required | API base URL | | api_key | required | API key | | model | "deepseek-chat" | Model name | | temperature | 0.7 | Temperature (0-2) | | max_tokens | 2048 | Max output tokens | | top_p | 1.0 | Nucleus sampling | | frequency_penalty | 0.0 | Frequency penalty (-2 to 2) | | presence_penalty | 0.0 | Presence penalty (-2 to 2) | | system_prompt | "你是一个严谨的助手" | System prompt | | window_title | "AI Chat" | Window title | | window_width | 600 | Window width | | window_height | 800 | Window height | | window_x | 300 | Window X position | | window_y | 300 | Window Y position |

System Messages

Set custom system prompts:

# Replace all system messages
chat.set_system_messages([
    {"role": "system", "content": "You are a Python expert"},
    {"role": "system", "content": "Provide code examples"}
])
Add single system message
chat.add_system_message("You are now a creative writer")

Quick Launch with System Messages

ChatWindow.launch(
    base_url="https://api.deepseek.com/v1",
    api_key="your_api_key",
    model="deepseek-coder",
    system_messages=[
        {"role": "system", "content": "You are a Python expert"},
        {"role": "system", "content": "Keep answers concise with code"}
    ],
    window_title="Python Assistant"
)

Features

Requirements

API Reference

ChatWindow

| Method | Description | |---------|-------------| | __init__(config) | Initialize with ChatConfig | | set_system_messages(messages) | Replace all system messages | | add_system_message(content) | Add single system message | | run() | Show window and start event loop | | launch(base_url, api_key, ...) | Class method to quickly launch chat window |

ChatConfig

Dataclass for window and LLM configuration. All parameters optional except base_url and api_key.

from pywayne.llm.chat_window import ChatWindow
Basic usage - quick launch
ChatWindow.launch(
    base_url="https://api.deepseek.com/v1",
    api_key="your_api_key",
    model="deepseek-chat"
)

Using ChatConfig dataclass for full customization:

from pywayne.llm.chat_window import ChatWindow, ChatConfig
config = ChatConfig(
    base_url="https://api.deepseek.com/v1",
    api_key="your_api_key",
    model="deepseek-chat",
    temperature=0.8,
    window_title="AI Assistant",
    window_width=800,
    window_height=600
)
chat = ChatWindow(config)
chat.run()

ChatConfig Parameters

| Parameter | Default | Description | |-----------|---------|-------------| | base_url | required | API base URL | | api_key | required | API key | | model | "deepseek-chat" | Model name | | temperature | 0.7 | Temperature (0-2) | | max_tokens | 2048 | Max output tokens | | top_p | 1.0 | Nucleus sampling | | frequency_penalty | 0.0 | Frequency penalty (-2 to 2) | | presence_penalty | 0.0 | Presence penalty (-2 to 2) | | system_prompt | "你是一个严谨的助手" | System prompt | | window_title | "AI Chat" | Window title | | window_width | 600 | Window width | | window_height | 800 | Window height | | window_x | 300 | Window X position | | window_y | 300 | Window Y position |