Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
PyQt5-based GUI chat window for LLM conversations with streaming responses and stop functionality. Use when working with pywayne.llm.chat_window module to cr...
PyQt5-based GUI chat window for LLM conversations with streaming responses and stop functionality. Use when working with pywayne.llm.chat_window module to cr...
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
This module provides a PyQt5-based desktop GUI chat window for LLM conversations.
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()
ParameterDefaultDescriptionbase_urlrequiredAPI base URLapi_keyrequiredAPI keymodel"deepseek-chat"Model nametemperature0.7Temperature (0-2)max_tokens2048Max output tokenstop_p1.0Nucleus samplingfrequency_penalty0.0Frequency penalty (-2 to 2)presence_penalty0.0Presence penalty (-2 to 2)system_prompt"你是一个严谨的助手"System promptwindow_title"AI Chat"Window titlewindow_width600Window widthwindow_height800Window heightwindow_x300Window X positionwindow_y300Window Y position
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")
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" )
Streaming responses: Real-time token-by-token display Stop generation: Button toggles between "发送" (Send) and "停止" (Stop) Message history: Maintains conversation context Enter to send: Press Enter in input field to send message System messages: Support for multiple system prompts
PyQt5 - GUI framework openai - OpenAI-compatible API client
MethodDescription__init__(config)Initialize with ChatConfigset_system_messages(messages)Replace all system messagesadd_system_message(content)Add single system messagerun()Show window and start event looplaunch(base_url, api_key, ...)Class method to quickly launch chat window
Dataclass for window and LLM configuration. All parameters optional except base_url and api_key.
Messaging, meetings, inboxes, CRM, and teammate communication surfaces.
Largest current source with strong distribution and engagement signals.