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5e93c1d3d7
- ask-agent : ajout /no_think pour agents system et monitor (Qwen3-1.7B en mode thinking consommait tous les tokens sur le raisonnement interne, laissant content: "" vide) - SKILL.md v1.1.0 : règles OBLIGATOIRES de délégation, distinction ask-agent vs delegate_task, exemples concrets, syntaxe exacte - test.sh : suite 10 tests end-to-end — CLI disponible, LiteLLM, system/monitor/brain, données réelles, skill présence/activation, Hermes funk-ai appelle Terminal: ask-agent Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
80 lines
2.1 KiB
Bash
80 lines
2.1 KiB
Bash
#!/usr/bin/env bash
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# ask-agent — Délègue une question à un agent Funk via LiteLLM.
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#
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# Usage:
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# ask-agent <agent> "<question>"
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# ask-agent <agent> "<question>" [--max-tokens N] [--system "<prompt>"]
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#
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# Agents: system | monitor | brain | funk-ai
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set -euo pipefail
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LITELLM_URL="http://127.0.0.1:4000/v1/chat/completions"
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API_KEY="lm-studio"
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MAX_TOKENS=1000
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SYSTEM_PROMPT=""
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declare -A MODELS=(
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[system]="qwen3-1.7b-system"
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[monitor]="qwen3-1.7b-monitor"
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[brain]="claude-sonnet-4-6"
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[funk-ai]="qwen3-8b"
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)
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usage() {
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echo "Usage: ask-agent <agent> \"<question>\" [--max-tokens N] [--system \"<prompt>\"]"
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echo "Agents: system | monitor | brain | funk-ai"
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exit 1
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}
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[ $# -lt 2 ] && usage
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AGENT="$1"
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QUESTION="$2"
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shift 2
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# Qwen3 thinking mode : les agents rapides (system/monitor) doivent répondre
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# directement sans passer du temps en raisonnement interne.
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# /no_think désactive le mode thinking pour system et monitor.
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case "$AGENT" in
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system|monitor) QUESTION="/no_think ${QUESTION}" ;;
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esac
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while [ $# -gt 0 ]; do
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case "$1" in
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--max-tokens) MAX_TOKENS="$2"; shift 2 ;;
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--system) SYSTEM_PROMPT="$2"; shift 2 ;;
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*) echo "Option inconnue : $1" >&2; exit 1 ;;
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esac
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done
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MODEL="${MODELS[$AGENT]:-}"
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if [ -z "$MODEL" ]; then
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echo "Agent inconnu : $AGENT. Agents valides : ${!MODELS[*]}" >&2
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exit 1
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fi
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# Construire le tableau messages JSON
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if [ -n "$SYSTEM_PROMPT" ]; then
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MESSAGES=$(jq -n \
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--arg sp "$SYSTEM_PROMPT" \
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--arg q "$QUESTION" \
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'[{"role":"system","content":$sp},{"role":"user","content":$q}]')
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else
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MESSAGES=$(jq -n \
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--arg q "$QUESTION" \
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'[{"role":"user","content":$q}]')
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fi
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PAYLOAD=$(jq -n \
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--arg model "$MODEL" \
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--argjson messages "$MESSAGES" \
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--argjson max_tokens "$MAX_TOKENS" \
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'{model:$model, messages:$messages, max_tokens:$max_tokens, stream:false}')
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curl -s -f \
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-X POST "$LITELLM_URL" \
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-H "Authorization: Bearer $API_KEY" \
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-H "Content-Type: application/json" \
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-d "$PAYLOAD" \
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| jq -r '.choices[0].message.content'
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