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Operate GPT Academic chat, model routing, search, RAG, Mermaid, and conversation history workflows.

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Documentation de la Skill

GitHub

name: conversation description: "Operate GPT Academic chat, model routing, search, RAG, Mermaid, and conversation history workflows." disable-model-invocation: true metadata: disco-role: operating license: GPL 3.0

Conversation

Use this sub-skill for GPT Academic's text-first workflows: ordinary chat, built-in prompt buttons, model/provider selection, proxy setup, internet search, multi-model comparison, RAG/knowledge base, Mermaid generation, URL extraction, and saving/loading chat history.

Trigger phrases

Read this sub-skill when the user mentions any of:

  • LLM_MODEL, AVAIL_LLM_MODELS, API keys, proxy, OpenAI-compatible endpoint, Azure, Ollama, vLLM, local model, DashScope/Qwen, DeepSeek, GLM, Claude, Gemini;
  • “chat with GPT Academic”, “ask multiple models”, “web search”, “SearXNG”, “Jina”, “RAG”, “knowledge base”, “conversation archive”, “save chat”, “load chat”, “Mermaid”, “draw a mind map”, or “URL input”;
  • core prompt buttons such as academic polish, grammar check, Chinese/English translation, code explanation, reference-to-BibTeX, or image lookup.

First decisions

  1. Confirm whether the task is normal chat, provider setup, search, RAG, conversation persistence, or a visualization/output-format task.
  2. Check the shared root references/configuration.md for provider and proxy settings before diagnosing live model failures.
  3. Use the bundled plugin listing script when the exact plugin/button name matters:
python sub-skills/conversation/scripts/list_conversation_plugins.py --repo-root <checkout> --group 对话
  1. If the prompt involves documents, code projects, agentic execution, or media inputs, route to the owning sibling sub-skill rather than stretching conversation guidance.

Workflow routes

User goalPrimary GPT Academic surfaceRead next
normal chat or built-in prompt transformssubmit button plus core_functional prompt buttonsreferences/workflows.md
model/provider setup or model-dropdown issueLLM_MODEL, AVAIL_LLM_MODELS, provider key config, request_llms.bridge_allreferences/model-routing.md and root references/configuration.md
web search answer查互联网后回答, SearXNG/Jina/proxy configreferences/workflows.md and references/troubleshooting.md
multi-model comparison询问多个GPT模型 or manual model listreferences/model-routing.md
RAG / knowledge base构建知识库, 知识库文件注入, Rag智能召回references/workflows.md
save/load/export chat保存当前的对话, 载入对话历史存档references/workflows.md
Mermaid or mind-map outputMermaid plugin or core summarization/mind-map promptreferences/workflows.md

Boundaries

  • Route PDFs, Arxiv, LaTeX, Word, paper reading, and batch document QA to ../academic-docs/SKILL.md.
  • Route source-code project analysis, notebooks, README/Markdown translation, and docstring insertion to ../programming-code/SKILL.md.
  • Route Void Terminal, Code Interpreter, natural-language plugin dispatch, command execution, and config mutation to ../agent-tooling/SKILL.md.
  • Route image/audio/video/TTS/animation workflows to ../multimodal-media/SKILL.md.

Troubleshooting quick checks

  • Run scripts/inspect_runtime.py --repo-root <checkout> from the root skill for imports, plugin groups, and model registry size.
  • Run scripts/check_proxy.py --repo-root <checkout> --no-network before remote provider or search debugging.
  • Use references/troubleshooting.md here for conversation-specific failure modes and root references/troubleshooting.md for install/import issues.
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