Fixed several bugs. First working solution. But uses CPUs rather than NVIDIA GPUs
This commit is contained in:
67
README.md
67
README.md
@@ -8,77 +8,14 @@ aufrufbar **vom Terminal**, ohne direkte DB-Verbindung (nur Copy & Paste / Datei
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- **Host Networking:** nutzt den Host-Netzwerkstack (Routing/DNS wie Host; ideal wenn nur `br0` zuverlässig ist)
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- **Auto-Updates:** Runtime + Models via `systemd --user` Timer
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- **Viele Logs:** jede Ausführung schreibt detaillierte Logs unter `./logs/`
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- **Freie SQL Server 2022 Q&A:** Modus `ask` für allgemeine Fragen, ohne Pipe via `--text`
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## Voraussetzungen (Arch Linux)
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- docker + docker compose
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- curl
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- python (für JSON-Quoting/Parsing)
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- python
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## Quickstart
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```bash
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cp .env.example .env
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./scripts/bootstrap.sh
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echo "SELECT 1;" | ./bin/sqlai analyze-tsql
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```
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## Verwendung (Copy & Paste)
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### T-SQL
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```bash
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cat query.sql | ./bin/sqlai analyze-tsql
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```
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### Stored Procedure
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```bash
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cat dbo.usp_Something.sql | ./bin/sqlai analyze-proc
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```
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### View
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```bash
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cat dbo.vw_Something.sql | ./bin/sqlai analyze-view
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```
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### Execution Plan
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- Unterstützt Showplan XML oder Text.
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```bash
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./bin/sqlai analyze-plan --file showplan.xml
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```
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### UTF-8 Migration Plan
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```bash
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cat schema_snippet.sql | ./bin/sqlai utf8-migration
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```
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## Prompt Library (Templates)
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Unter `./prompts/` findest du Copy&Paste-Templates:
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- `prompts/tsql_review.md`
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- `prompts/plan_review.md`
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- `prompts/utf8_migration_runbook.md`
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- `prompts/indexing_checklist.md`
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- `prompts/sniffing_stats_playbook.md`
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- `prompts/proc_refactor_template.md`
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- `prompts/view_analysis_template.md`
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## Logs
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- CLI Logs: `./logs/sqlai-YYYY-MM-DD.log`
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- Bootstrap Logs: `./logs/bootstrap-YYYY-MM-DDTHH:MM:SS.log`
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- Update Logs: `./logs/update-YYYY-MM-DDTHH:MM:SS.log`
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Die Logs enthalten:
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- Input-Bytes, Mode, Model
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- Roh-Metriken aus Ollama (Token Counts, Durations)
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- Fehler inkl. curl exit codes
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## Auto-Updates aktivieren (systemd --user)
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```bash
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mkdir -p ~/.config/systemd/user
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cp systemd/user/* ~/.config/systemd/user/
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systemctl --user daemon-reload
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systemctl --user enable --now jr-sql-ai-update.timer
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systemctl --user list-timers | grep jr-sql-ai
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```
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## Troubleshooting
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- **API nicht erreichbar**: Prüfe `docker ps` und ob Port 11434 lokal erreichbar ist (Host-Netz).
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- **Langsam/OOM**: setze `BASE_MODEL` kleiner (z.B. 7b) und re-run `./scripts/update.sh`.
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- **Model fehlt**: `./scripts/update.sh` ausführen und prüfen ob `ollama list` im Container das Model zeigt:
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`docker exec -it ollama ollama list`
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193
bin/sqlai
193
bin/sqlai
@@ -14,22 +14,33 @@ log_dir="${ROOT}/logs"
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mkdir -p "$log_dir"
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log_file="${log_dir}/sqlai-$(date -I).log"
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# log everything (stdout+stderr)
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# Log everything (stdout+stderr)
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exec > >(tee -a "$log_file") 2>&1
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usage() {
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cat <<EOF
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cat <<'EOF'
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Usage:
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sqlai <mode> [--file path]
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sqlai <mode> [--file path] [--text "free text"] [--no-metrics]
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Modes:
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analyze-tsql
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analyze-proc
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analyze-view
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analyze-plan
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utf8-migration
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ask General SQL Server 2022 Q&A (free text)
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analyze-tsql Analyze a T-SQL query
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analyze-proc Analyze a stored procedure
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analyze-view Analyze a view
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analyze-plan Analyze an execution plan (Showplan XML or text)
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utf8-migration Create a UTF-8 migration plan (SQL Server 2022)
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Input options:
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--text "..." Provide input text directly (no pipe needed)
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--file path Read input from file
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(no args) Reads from STDIN
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Other options:
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--no-metrics Do not print metrics line
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Examples:
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cat query.sql | sqlai analyze-tsql
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sqlai ask --text "How do I troubleshoot parameter sniffing in SQL Server 2022?"
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echo "SELECT 1;" | sqlai analyze-tsql
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sqlai analyze-plan --file showplan.xml
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EOF
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}
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@@ -39,44 +50,58 @@ mode="${1:-}"
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shift || true
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file=""
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text=""
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no_metrics="0"
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while [[ $# -gt 0 ]]; do
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case "$1" in
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--file) file="$2"; shift 2;;
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--file) file="${2:-}"; shift 2;;
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--text) text="${2:-}"; shift 2;;
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--no-metrics) no_metrics="1"; shift 1;;
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-h|--help) usage; exit 0;;
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*) echo "[$(ts)] ERROR: Unknown arg: $1"; usage; exit 2;;
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esac
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done
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# Read input (priority: --text > --file > stdin)
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input=""
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if [[ -n "$file" ]]; then
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if [[ ! -f "$file" ]]; then
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echo "[$(ts)] ERROR: file not found: $file"
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exit 3
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fi
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input_src=""
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if [[ -n "$text" ]]; then
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input="$text"
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input_src="text"
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elif [[ -n "$file" ]]; then
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[[ -f "$file" ]] || { echo "[$(ts)] ERROR: file not found: $file"; exit 3; }
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input="$(cat "$file")"
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input_src="file:${file}"
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else
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input="$(cat)"
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input_src="stdin"
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fi
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if [[ -z "${input//[[:space:]]/}" ]]; then
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echo "[$(ts)] ERROR: empty input"
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echo "[$(ts)] ERROR: empty input (source=$input_src)"
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exit 4
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fi
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# Short instruction per mode (core policy is in Modelfile SYSTEM prompt)
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case "$mode" in
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ask)
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instruction=$'Beantworte die Frage als SQL Server 2022 Experte.\n\nWichtig:\n- Wenn Kontext fehlt: keine Rückfragen stellen; stattdessen Annahmen offenlegen und Optionen (A/B/C) mit Vor-/Nachteilen geben.\n- Ergebnis immer strukturiert mit: Kurzfazit, Optionen, Risiken/Checks, Nächste Schritte.\n- Wenn sinnvoll: konkrete T-SQL/DDL Snippets und Checklisten liefern.'
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;;
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analyze-tsql)
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instruction="Analysiere das folgende T-SQL (SQL Server 2022). Finde Performance-Probleme, SARGability, Indizes, Statistiken, Parameter Sniffing Risiken und gib konkrete Verbesserungen."
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instruction=$'Analysiere das folgende T-SQL (SQL Server 2022): Performance, SARGability, Datentypen, Joins/Predicates, Indizes/Stats, Parameter Sniffing. Gib konkrete Rewrite- und Index-Ideen.'
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;;
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analyze-proc)
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instruction="Analysiere die folgende Stored Procedure (SQL Server 2022). Finde Performance-/Correctness-Risiken, Transaktions-/Locking-Themen, Parameter Sniffing, fehlende Indizes. Gib konkrete Refactorings."
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instruction=$'Analysiere die folgende Stored Procedure (SQL Server 2022): Performance/Correctness, Transaktionen/Locking, Sniffing, Temp tables vs table variables, RBAR. Gib konkrete Refactorings.'
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;;
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analyze-view)
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instruction="Analysiere die folgende View (SQL Server 2022). Prüfe SARGability, Expand/Inlining-Effekte, mögliche Indexing-Optionen (z.B. indexed view falls sinnvoll) und Plan-Auswirkungen."
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instruction=$'Analysiere die folgende View (SQL Server 2022): SARGability, Predicate Pushdown, Expand/Inlining, Aggregationen/Distinct/Union, UDF-Risiken. Gib konkrete Verbesserungen.'
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;;
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analyze-plan)
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instruction="Analysiere den folgenden SQL Server Execution Plan (XML Showplan oder Text). Identifiziere teure Operatoren, Spills, Warnungen, Kardinalitätsfehler, fehlende Indizes und gib konkrete Fixes."
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instruction=$'Analysiere den folgenden SQL Server Execution Plan (Showplan XML oder Text): Hotspots, Spills/Warnings, Memory Grants, Kardinalität, Fixes (Rewrite/Stats/Indexing vorsichtig/Sniffing Mitigation).'
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;;
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utf8-migration)
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instruction="Erstelle einen Migrationsplan, um Tabellen/Spalten auf UTF-8 umzustellen (UTF-8 enabled collations mit _UTF8). Berücksichtige Abhängigkeiten (FK/PK/Indexes/Computed/Triggers), Risiken und gib eine Schritt-für-Schritt Checkliste."
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instruction=$'Erstelle einen Migrationsplan (SQL Server 2022) zur Umstellung auf UTF-8 (UTF-8 enabled collations _UTF8): Abhängigkeiten (PK/FK/Indexes/Computed/Triggers), Cutover, Rollback, Tests, konkrete DDL/Checklisten.'
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;;
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*)
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echo "[$(ts)] ERROR: unknown mode: $mode"
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@@ -85,46 +110,118 @@ case "$mode" in
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;;
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esac
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req_id="$(date +%Y%m%d-%H%M%S)-$$-$RANDOM"
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echo "================================================================================"
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echo "[$(ts)] sqlai: REQUEST_START id=$req_id"
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echo "[$(ts)] sqlai: MODE=$mode MODEL=$EXPERT_MODEL OLLAMA_URL=$OLLAMA_URL"
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echo "[$(ts)] sqlai: INPUT_SOURCE=$input_src INPUT_BYTES=$(printf "%s" "$input" | wc -c)"
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# Delimited markup
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prompt=$(cat <<EOF
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${instruction}
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---BEGIN INPUT---
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---BEGIN INPUT (${mode})---
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${input}
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---END INPUT---
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---END INPUT (${mode})---
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EOF
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)
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echo "[$(ts)] sqlai: MODE=$mode MODEL=$EXPERT_MODEL OLLAMA_URL=$OLLAMA_URL"
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echo "[$(ts)] sqlai: INPUT_BYTES=$(printf "%s" "$input" | wc -c)"
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payload="$(python - <<'PY'
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# Build JSON safely (no heredoc+herestring combos)
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payload="$(
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printf '%s' "$prompt" | python -c '
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import json, os, sys
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model=os.environ.get("EXPERT_MODEL","jr-sql-expert")
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prompt=sys.stdin.read()
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print(json.dumps({"model": model, "prompt": prompt, "stream": False}, ensure_ascii=False))
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PY
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<<<"$prompt")"
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'
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)"
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echo "[$(ts)] sqlai: sending request..."
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resp="$(curl -sS -X POST "${OLLAMA_URL}/api/generate" -H 'Content-Type: application/json' --data-binary "$payload")" || {
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rc=$?
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echo "[$(ts)] sqlai: ERROR: curl failed rc=$rc"
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exit 10
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}
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resp_file="$(mktemp)"
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http_code="$(
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curl -sS -o "$resp_file" -w "%{http_code}" \
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-X POST "${OLLAMA_URL}/api/generate" \
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-H 'Content-Type: application/json' \
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--data-binary "$payload" \
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|| true
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)"
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python - <<'PY'
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resp="$(cat "$resp_file")"
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rm -f "$resp_file"
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echo "[$(ts)] sqlai: HTTP_CODE=$http_code RESP_BYTES=$(printf "%s" "$resp" | wc -c) id=$req_id"
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|
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# Validate JSON
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if ! printf '%s' "$resp" | python -c 'import json,sys; json.load(sys.stdin)' >/dev/null 2>&1; then
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echo "[$(ts)] sqlai: ERROR: response is not valid JSON id=$req_id"
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echo "[$(ts)] sqlai: RAW_RESPONSE_BEGIN id=$req_id"
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printf '%s\n' "$resp"
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echo "[$(ts)] sqlai: RAW_RESPONSE_END id=$req_id"
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echo "[$(ts)] sqlai: REQUEST_END id=$req_id status=error"
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exit 11
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fi
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# Extract error/response/metrics in one pass
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extracted="$(
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printf '%s' "$resp" | python -c '
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import json,sys
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obj=json.loads(sys.stdin.read())
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print("\n" + (obj.get("response","").rstrip()) + "\n")
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md = {
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"total_duration": obj.get("total_duration"),
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"load_duration": obj.get("load_duration"),
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"prompt_eval_count": obj.get("prompt_eval_count"),
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"prompt_eval_duration": obj.get("prompt_eval_duration"),
|
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"eval_count": obj.get("eval_count"),
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"eval_duration": obj.get("eval_duration"),
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obj=json.load(sys.stdin)
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out={
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"error": obj.get("error"),
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"response": obj.get("response",""),
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"metrics": {
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"total_duration": obj.get("total_duration"),
|
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"load_duration": obj.get("load_duration"),
|
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"prompt_eval_count": obj.get("prompt_eval_count"),
|
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"prompt_eval_duration": obj.get("prompt_eval_duration"),
|
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"eval_count": obj.get("eval_count"),
|
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"eval_duration": obj.get("eval_duration"),
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}
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}
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print("METRICS=" + json.dumps(md, ensure_ascii=False))
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PY <<<"$resp"
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print(json.dumps(out, ensure_ascii=False))
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'
|
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)"
|
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|
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echo "[$(ts)] sqlai: done"
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error_msg="$(printf '%s' "$extracted" | python -c 'import json,sys; print((json.load(sys.stdin).get("error") or "").strip())')"
|
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response_txt="$(printf '%s' "$extracted" | python -c 'import json,sys; print(json.load(sys.stdin).get("response") or "")')"
|
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|
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# HTTP != 200 is error
|
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if [[ "$http_code" != "200" ]]; then
|
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echo "[$(ts)] sqlai: ERROR: non-200 HTTP_CODE=$http_code id=$req_id"
|
||||
if [[ -n "$error_msg" ]]; then
|
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echo "[$(ts)] sqlai: OLLAMA_ERROR=$error_msg id=$req_id"
|
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else
|
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echo "[$(ts)] sqlai: BODY_SNIPPET_BEGIN id=$req_id"
|
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printf '%s\n' "$resp" | head -n 120
|
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echo "[$(ts)] sqlai: BODY_SNIPPET_END id=$req_id"
|
||||
fi
|
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echo "[$(ts)] sqlai: REQUEST_END id=$req_id status=error"
|
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exit 12
|
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fi
|
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|
||||
# API-level error
|
||||
if [[ -n "$error_msg" ]]; then
|
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echo "[$(ts)] sqlai: ERROR: OLLAMA_ERROR=$error_msg id=$req_id"
|
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echo "[$(ts)] sqlai: REQUEST_END id=$req_id status=error"
|
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exit 13
|
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fi
|
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|
||||
# Print answer
|
||||
printf "\n%s\n\n" "$(printf "%s" "$response_txt" | sed 's/[[:space:]]*$//')"
|
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|
||||
# If response empty, dump JSON snippet to log
|
||||
if [[ -z "${response_txt//[[:space:]]/}" ]]; then
|
||||
echo "[$(ts)] sqlai: WARN: empty response id=$req_id"
|
||||
echo "[$(ts)] sqlai: RAW_JSON_SNIPPET_BEGIN id=$req_id"
|
||||
printf '%s\n' "$resp" | head -n 200
|
||||
echo "[$(ts)] sqlai: RAW_JSON_SNIPPET_END id=$req_id"
|
||||
fi
|
||||
|
||||
# Print metrics optionally
|
||||
if [[ "$no_metrics" != "1" ]]; then
|
||||
metrics_line="$(printf '%s' "$extracted" | python -c 'import json,sys; print("METRICS="+json.dumps(json.load(sys.stdin)["metrics"], ensure_ascii=False))')"
|
||||
echo "$metrics_line"
|
||||
fi
|
||||
|
||||
echo "[$(ts)] sqlai: REQUEST_END id=$req_id status=ok"
|
||||
echo "================================================================================"
|
||||
|
||||
27
prompts/sqlserver_qna.md
Normal file
27
prompts/sqlserver_qna.md
Normal file
@@ -0,0 +1,27 @@
|
||||
# SQL Server 2022 Q&A Template (Copy & Paste)
|
||||
|
||||
Zweck: Freie technische Fragestellungen zu SQL Server 2022 strukturiert beantworten lassen.
|
||||
Hinweis: Keine DB-Verbindung, nur Analyse/Planung/Empfehlung.
|
||||
|
||||
## Frage
|
||||
<PASTE QUESTION HERE>
|
||||
|
||||
## Kontext (optional, aber hilfreich)
|
||||
- SQL Server: 2022 (ja/nein)
|
||||
- DB Kompatibilitätslevel:
|
||||
- Collation aktuell (DB + betroffene Spalten):
|
||||
- Umfang: Anzahl Tabellen/Spalten grob, Rowcounts grob:
|
||||
- Data profile: nur west-europäisch / international / Emojis / CJK / gemischt:
|
||||
- Clients/Apps: .NET / JDBC / ODBC / ETL Tool:
|
||||
- Schnittstellen: CSV/JSON/XML, Data Warehouse, Replication, Linked Servers:
|
||||
- Non-functional: Downtime-Fenster, Rollback-Anforderung, Performance-SLA:
|
||||
|
||||
## Erwartete Ausgabe (bitte strikt)
|
||||
1) Kurzfazit (Empfehlung in 3–6 Bulletpoints)
|
||||
2) Optionen (A/B/C) mit Vor- & Nachteilen
|
||||
3) Risiken & Checks (Checkliste)
|
||||
4) Konkreter Plan / Next Steps (inkl. DDL/T-SQL Snippets wenn sinnvoll)
|
||||
|
||||
---BEGIN QUESTION---
|
||||
<PASTE HERE>
|
||||
---END QUESTION---
|
||||
@@ -2,26 +2,34 @@
|
||||
set -euo pipefail
|
||||
|
||||
ROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)"
|
||||
|
||||
# Create .env if missing (do not overwrite)
|
||||
cp -n "${ROOT}/.env.example" "${ROOT}/.env" || true
|
||||
|
||||
# shellcheck disable=SC1090
|
||||
source "${ROOT}/.env"
|
||||
|
||||
ts(){ date -Is; }
|
||||
|
||||
log_dir="${ROOT}/logs"
|
||||
mkdir -p "$log_dir"
|
||||
log_file="${log_dir}/bootstrap-$(date -Iseconds).log"
|
||||
|
||||
# log everything (stdout+stderr)
|
||||
exec > >(tee -a "$log_file") 2>&1
|
||||
|
||||
echo "[$(ts)] bootstrap: starting (ROOT=$ROOT)"
|
||||
|
||||
echo "[$(ts)] bootstrap: docker compose up -d"
|
||||
docker compose -f "${ROOT}/docker-compose.yml" up -d
|
||||
|
||||
echo "[$(ts)] bootstrap: waiting for Ollama API at ${OLLAMA_URL} ..."
|
||||
for i in {1..90}; do
|
||||
for i in {1..120}; do
|
||||
if curl -sS "${OLLAMA_URL}/api/tags" >/dev/null 2>&1; then
|
||||
echo "[$(ts)] bootstrap: Ollama API is up."
|
||||
break
|
||||
fi
|
||||
if [[ $i -eq 90 ]]; then
|
||||
if [[ $i -eq 120 ]]; then
|
||||
echo "[$(ts)] bootstrap: ERROR: API did not come up in time."
|
||||
exit 1
|
||||
fi
|
||||
@@ -39,11 +47,29 @@ if [[ -n "${EXTRA_MODELS:-}" ]]; then
|
||||
fi
|
||||
|
||||
echo "[$(ts)] bootstrap: building expert model: ${EXPERT_MODEL}"
|
||||
|
||||
tmp="$(mktemp)"
|
||||
sed "s/\${BASE_MODEL}/${BASE_MODEL}/g" "${ROOT}/Modelfile" > "$tmp"
|
||||
docker exec -i ollama ollama create "${EXPERT_MODEL}" -f - < "$tmp"
|
||||
|
||||
# Copy Modelfile into container and build from explicit path (robust)
|
||||
docker cp "$tmp" ollama:/tmp/Modelfile.jr-sql-expert
|
||||
docker exec -it ollama ollama create "${EXPERT_MODEL}" -f /tmp/Modelfile.jr-sql-expert
|
||||
|
||||
rm -f "$tmp"
|
||||
|
||||
echo "[$(ts)] bootstrap: verifying model exists..."
|
||||
docker exec -it ollama ollama list | grep -F "${EXPERT_MODEL}" >/dev/null && \
|
||||
echo "[$(ts)] bootstrap: OK: ${EXPERT_MODEL} is available."
|
||||
|
||||
# End-to-end test
|
||||
if [[ ! -x "${ROOT}/bin/sqlai" ]]; then
|
||||
echo "[$(ts)] bootstrap: ERROR: ${ROOT}/bin/sqlai not found or not executable"
|
||||
ls -la "${ROOT}/bin" || true
|
||||
exit 2
|
||||
fi
|
||||
|
||||
echo "[$(ts)] bootstrap: test (running one request)..."
|
||||
echo "SELECT 1;" | "${ROOT}/bin/sqlai" analyze-tsql
|
||||
echo "[$(ts)] bootstrap: test done"
|
||||
|
||||
echo "[$(ts)] bootstrap: done"
|
||||
echo "[$(ts)] bootstrap: test:"
|
||||
echo " echo "SELECT 1;" | ${ROOT}/bin/sqlai analyze-tsql"
|
||||
|
||||
@@ -2,27 +2,34 @@
|
||||
set -euo pipefail
|
||||
|
||||
ROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)"
|
||||
|
||||
# shellcheck disable=SC1090
|
||||
source "${ROOT}/.env"
|
||||
|
||||
ts(){ date -Is; }
|
||||
|
||||
log_dir="${ROOT}/logs"
|
||||
mkdir -p "$log_dir"
|
||||
log_file="${log_dir}/update-$(date -Iseconds).log"
|
||||
|
||||
# log everything (stdout+stderr)
|
||||
exec > >(tee -a "$log_file") 2>&1
|
||||
|
||||
echo "[$(ts)] update: starting (ROOT=$ROOT)"
|
||||
|
||||
echo "[$(ts)] update: pulling docker image(s)"
|
||||
docker compose -f "${ROOT}/docker-compose.yml" pull
|
||||
|
||||
echo "[$(ts)] update: restarting services"
|
||||
docker compose -f "${ROOT}/docker-compose.yml" up -d
|
||||
|
||||
echo "[$(ts)] update: waiting for Ollama API at ${OLLAMA_URL} ..."
|
||||
for i in {1..90}; do
|
||||
for i in {1..120}; do
|
||||
if curl -sS "${OLLAMA_URL}/api/tags" >/dev/null 2>&1; then
|
||||
echo "[$(ts)] update: Ollama API is up."
|
||||
break
|
||||
fi
|
||||
if [[ $i -eq 90 ]]; then
|
||||
if [[ $i -eq 120 ]]; then
|
||||
echo "[$(ts)] update: ERROR: API did not come up in time."
|
||||
exit 1
|
||||
fi
|
||||
@@ -40,9 +47,17 @@ if [[ -n "${EXTRA_MODELS:-}" ]]; then
|
||||
fi
|
||||
|
||||
echo "[$(ts)] update: rebuilding expert model: ${EXPERT_MODEL}"
|
||||
|
||||
tmp="$(mktemp)"
|
||||
sed "s/\${BASE_MODEL}/${BASE_MODEL}/g" "${ROOT}/Modelfile" > "$tmp"
|
||||
docker exec -i ollama ollama create "${EXPERT_MODEL}" -f - < "$tmp"
|
||||
|
||||
docker cp "$tmp" ollama:/tmp/Modelfile.jr-sql-expert
|
||||
docker exec -it ollama ollama create "${EXPERT_MODEL}" -f /tmp/Modelfile.jr-sql-expert
|
||||
|
||||
rm -f "$tmp"
|
||||
|
||||
echo "[$(ts)] update: verifying model exists..."
|
||||
docker exec -it ollama ollama list | grep -F "${EXPERT_MODEL}" >/dev/null && \
|
||||
echo "[$(ts)] update: OK: ${EXPERT_MODEL} is available."
|
||||
|
||||
echo "[$(ts)] update: complete"
|
||||
|
||||
Reference in New Issue
Block a user