---

name: llm-providers description: "Configure transcript-based and video-understanding LLM clipping routes, provider prefixes, API keys, prompt format, and timestamp normalization for FunClip." metadata: disco-role: operating disable-model-invocation: true license: MIT

LLM Providers

Use this sub-skill when the user needs to choose, configure, or debug a FunClip LLM backend.

Handles

• funclip/launch.py llm_inference routing for transcript-based and video-understanding models.
• funclip/llm/openai_api.py, qwen_api.py, litellm_api.py, g4f_openai_api.py, and twelvelabs_api.py.
• The default prompt shape in funclip/llm/demo_prompt.py.
• The timestamp format expected by funclip/utils/trans_utils.py::extract_timestamps.
• AI Clip handoff: producing parseable LLM Clipper Result text for the clip-workflows sub-skill.

Route elsewhere

• Transcript/video/audio state, clip execution, subtitle burn-in, offsets, and clip output files -> ../clip-workflows/SKILL.md.
• Release archives, version packaging, and publishing -> ../release-packaging/SKILL.md.

Start here

• Read references/providers.md for the provider table and key/env rules.
• Read references/prompt-format.md for parseable N. [HH:MM:SS,mmm-HH:MM:SS,mmm] text output.
• Read references/troubleshooting.md for auth, import, timeout, and timestamp failures.
• Run scripts/provider_route_smoke.py --repo-root <repo-root> to check prefix stripping and Pegasus normalization without API calls.

Natural requests this covers

• Set up GPT, Qwen, DeepSeek, AtlasCloud, MiniMax, LiteLLM, g4f, or TwelveLabs Pegasus for LLM clipping.
• Diagnose missing API keys, wrong model prefixes, empty model names, or region/base-URL mismatches.
• Make LLM output parseable by AI Clip.
• Normalize Pegasus decimal-second timestamps into SRT form.
• Decide when Pegasus needs an uploaded video instead of transcript-only input.