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Productivity · SKILL.md

local-integrations

local-integrations

Routes Chinese-LLaMA-Alpaca-2 llama.cpp wrappers and external integration notes.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill documentation

GitHub

name: local-integrations description: "Routes Chinese-LLaMA-Alpaca-2 llama.cpp wrappers and external integration notes." metadata: disco-role: operating disable-model-invocation: true license: Apache 2.0

local-integrations

Use this sub-skill when the task is outside the direct HF scripts but still tied to the repo's local deployment or downstream integration examples.

Use it when

  • the user mentions llama.cpp, GGUF, chat.sh, or the llama.cpp completion server
  • the task is about reproducing the repo's Alpaca-2 prompt format in a local runtime
  • the user asks about the LangChain or privateGPT examples from this repo snapshot
  • the task needs a quick explanation of why those external examples are reference-only here

Workflow

  1. Read references/workflows.md for llama.cpp wrapper usage and external integration notes.
  2. Use scripts/llama-cpp/chat.sh only when a llama.cpp main binary and compatible model path are already available.
  3. Use scripts/llama-cpp/server_curl_example.sh only after a llama.cpp server is already running.
  4. Treat LangChain/privateGPT guidance as adaptation notes rather than a bundled runtime stack.
  5. Read references/troubleshooting.md when an external binary, model, or third-party package is missing.

Bundled runtime files

  • scripts/llama-cpp/chat.sh
  • scripts/llama-cpp/server_curl_example.sh

What to read first

  • references/workflows.md for the integration surfaces and prompt format
  • references/troubleshooting.md for external binary/server/scaffold failures

Routing notes

  • Use api-serving for the repo's FastAPI OpenAI-compatible server.
  • Use this sub-skill for llama.cpp or downstream integration notes.
  • Use a dedicated RAG or LangChain skill when the task is generic framework work and no longer depends on Chinese-LLaMA-Alpaca-2 prompts or model paths.
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