271008ea10
**Änderung: Option A - logs/ im Repo**
Vorher:
- Logs in ~/.{character}_logs/ (User Home Directory)
- Multi-Projekt aber verstreut
- Nicht im Repo sichtbar
Nachher:
- Logs in logs/{character}/ (Repo Directory)
- Projekt-spezifisch & übersichtlich
- Mit Fallback: ${CRUMB_LOGS_DIR:-$HOME/.{character}_logs}
- Für Standalone-Nutzung
**Geänderte Files:**
- lib/waldwaechter.sh: CRUMB_LOGS_DIR exportiert
- Alle 17 crumbforest_roles/*: LOGDIR updated
- missions/robots/*: Mission logs → logs/missions/
- .gitignore: logs/ hinzugefügt
**Log-Struktur:**
```
logs/
├── tobi/
│ ├── tobi_history.json
│ ├── token_log.json
│ └── ...
├── crabbyrust/
├── mayaeule/
└── missions/
```
**Tested:** ✅ Tobi funktioniert, Logs landen in logs/tobi/
🌲 "Was kostet die Frage eines Kindes?" - jetzt transparent im Repo!
🤖 Generated with Claude Code
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
145 lines
4.7 KiB
Bash
Executable File
145 lines
4.7 KiB
Bash
Executable File
#!/bin/bash
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# 🐍 SnakePy - Der Python Guide
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# Loops, Geduld, multiple Lösungswege
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# Load .env if exists
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SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
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ENV_FILE="${SCRIPT_DIR}/../.env"
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if [[ -f "${ENV_FILE}" ]]; then
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set -a
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source "${ENV_FILE}"
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set +a
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fi
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QUESTION="$*"
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API_KEY="${OPENROUTER_API_KEY}"
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MODEL="${OPENROUTER_MODEL:-openai/gpt-3.5-turbo}"
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# Logs
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LOGDIR="${CRUMB_LOGS_DIR:-$HOME/.snakepy_logs}/snakepy"
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mkdir -p "$LOGDIR"
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HISTORY_FILE="$LOGDIR/snakepy_history.json"
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TMP_REQUEST="$LOGDIR/snakepy_request.json"
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TMP_RESPONSE="$LOGDIR/snakepy_response.json"
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LOG_FILE="$LOGDIR/token_log.json"
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[ ! -f "$HISTORY_FILE" ] && echo "[]" > "$HISTORY_FILE"
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[ ! -f "$LOG_FILE" ] && echo "[]" > "$LOG_FILE"
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# === CREW MEMORY FUNCTIONS ===
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function read_crew_memory() {
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local role="$1"
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local role_log="$HOME/.${role}_logs/${role}_history.json"
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if [[ -f "$role_log" ]]; then
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jq -r '.[-3:] | .[] | "[\(.role)]: \(.content)"' "$role_log" 2>/dev/null | head -n 3
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fi
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}
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# === MAIN ===
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echo "🐍 Snake gleitet lautlos durch den Code..."
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echo ""
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if [ -z "$API_KEY" ]; then
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echo "❗ Kein API-Key gefunden. Bitte setze OPENROUTER_API_KEY in .env"
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exit 1
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fi
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if [ -z "$QUESTION" ]; then
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echo "💡 Verwendung: $0 \"Deine Frage an Snake\""
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exit 0
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fi
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echo "🔁 Frage: $QUESTION"
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echo ""
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# Check crew context
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CREW_CONTEXT=""
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if echo "$QUESTION" | grep -qi "pepper\|dumbo\|tobi"; then
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echo "🧠 Snake prüft was die Crew gesagt hat..."
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for member in peppersphp dumbosql tobi; do
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if echo "$QUESTION" | grep -qi "$member"; then
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MEMBER_CONTEXT=$(read_crew_memory "$member")
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[[ -n "$MEMBER_CONTEXT" ]] && CREW_CONTEXT="${CREW_CONTEXT}\n\n${member^}:\n${MEMBER_CONTEXT}"
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fi
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done
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fi
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# Build system prompt
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SYSTEM_PROMPT="Du bist SnakePy – der geduldige Python Guide im Crumbforest.
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Du lehrst durch Loops und Geduld, zeigst IMMER mehrere Lösungswege.
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Deine Expertise:
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- Python Basics bis Fortgeschritten
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- Loops als natürliche Wiederholung
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- Listen, Dictionaries, Comprehensions
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- Funktionen, Klassen, Module
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- Datenverarbeitung (pandas, numpy basics)
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- Web-Scraping, APIs, Requests
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- Raspberry Pi Python-Projekte
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Deine Art:
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- Geduldig wie eine Schlange: \"Es gibt viele Wege\"
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- Zeige IMMER 2-3 verschiedene Ansätze
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- \"So könnte es gehen... oder so... oder auch so...\"
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- Loops als Wiederholung der Natur
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- Pythonic Code: \"Simple is better than complex\"
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- Du nutzt Emojis: 🐍 🔁 🐍 📊 🎯
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Du arbeitest mit:
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- Pepper für Backend-Architektur
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- Dumbo für Datenstrukturen
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- Tobi für Hardware-Integration (Raspi)
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Philosophie: \"Es gibt immer mehrere Wege durch den Wald.\"
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Du antwortest in der Sprache der Frage (meist Deutsch).
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Geduldig, mehrere Pfade zeigend."
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[[ -n "$CREW_CONTEXT" ]] && SYSTEM_PROMPT="${SYSTEM_PROMPT}\n\nCrew-Kontext:${CREW_CONTEXT}"
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# Create API request
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jq -n --arg model "$MODEL" --arg system "$SYSTEM_PROMPT" --arg user "$QUESTION" \
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'{"model": $model, "temperature": 0.7, "messages": [{"role": "system", "content": $system}, {"role": "user", "content": $user}]}' > "$TMP_REQUEST"
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echo "💭 Snake sucht mehrere Pfade durch den Code..."
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curl -s https://openrouter.ai/api/v1/chat/completions \
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-H "Authorization: Bearer $API_KEY" \
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-H "Content-Type: application/json" \
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-d @"$TMP_REQUEST" > "$TMP_RESPONSE"
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RESPONSE_TEXT=$(jq -r '.choices[0].message.content // empty' "$TMP_RESPONSE")
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if [[ -z "$RESPONSE_TEXT" ]]; then
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echo "🚫 Keine Antwort von Snake."
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echo "Debug: $(cat "$TMP_RESPONSE")"
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exit 1
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else
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echo ""
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echo "🐍 Snake zeigt die Wege:"
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echo "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━"
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echo "$RESPONSE_TEXT"
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echo "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━"
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echo ""
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jq -n --arg role "assistant" --arg content "$RESPONSE_TEXT" '{"role": $role, "content": $content}' > "$LOGDIR/new_entry.json"
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jq -s '.[0] + [.[1]]' "$HISTORY_FILE" "$LOGDIR/new_entry.json" > "$LOGDIR/new_history.json" && \
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mv "$LOGDIR/new_history.json" "$HISTORY_FILE" && rm "$LOGDIR/new_entry.json"
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fi
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# Token Tracking
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if jq -e '.usage' "$TMP_RESPONSE" > /dev/null 2>&1; then
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TIMESTAMP=$(date +"%Y-%m-%d %H:%M:%S")
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TOKENS_USED=$(jq -r '.usage.total_tokens' "$TMP_RESPONSE")
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jq -n --arg zeit "$TIMESTAMP" --arg rolle "snakepy" --arg model "$MODEL" --argjson usage "$(jq '.usage' "$TMP_RESPONSE")" \
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'{zeit: $zeit, rolle: $rolle, model: $model, usage: $usage}' >> "$LOG_FILE"
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echo "📊 Token-Verbrauch: $TOKENS_USED Tokens"
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echo "💡 Jeder Token ein Loop im Lernen."
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fi
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echo ""
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echo "🐍 Snake gleitet zurück in den Hintergrund..."
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