Fixed several bugs. First working solution. But uses CPUs rather than NVIDIA GPUs

This commit is contained in:
2026-01-28 22:02:12 +01:00
parent 394edc1709
commit c3ab22a9bc
5 changed files with 223 additions and 121 deletions

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@@ -8,77 +8,14 @@ aufrufbar **vom Terminal**, ohne direkte DB-Verbindung (nur Copy & Paste / Datei
- **Host Networking:** nutzt den Host-Netzwerkstack (Routing/DNS wie Host; ideal wenn nur `br0` zuverlässig ist)
- **Auto-Updates:** Runtime + Models via `systemd --user` Timer
- **Viele Logs:** jede Ausführung schreibt detaillierte Logs unter `./logs/`
- **Freie SQL Server 2022 Q&A:** Modus `ask` für allgemeine Fragen, ohne Pipe via `--text`
## Voraussetzungen (Arch Linux)
- docker + docker compose
- curl
- python (für JSON-Quoting/Parsing)
- python
## Quickstart
```bash
cp .env.example .env
./scripts/bootstrap.sh
echo "SELECT 1;" | ./bin/sqlai analyze-tsql
```
## Verwendung (Copy & Paste)
### T-SQL
```bash
cat query.sql | ./bin/sqlai analyze-tsql
```
### Stored Procedure
```bash
cat dbo.usp_Something.sql | ./bin/sqlai analyze-proc
```
### View
```bash
cat dbo.vw_Something.sql | ./bin/sqlai analyze-view
```
### Execution Plan
- Unterstützt Showplan XML oder Text.
```bash
./bin/sqlai analyze-plan --file showplan.xml
```
### UTF-8 Migration Plan
```bash
cat schema_snippet.sql | ./bin/sqlai utf8-migration
```
## Prompt Library (Templates)
Unter `./prompts/` findest du Copy&Paste-Templates:
- `prompts/tsql_review.md`
- `prompts/plan_review.md`
- `prompts/utf8_migration_runbook.md`
- `prompts/indexing_checklist.md`
- `prompts/sniffing_stats_playbook.md`
- `prompts/proc_refactor_template.md`
- `prompts/view_analysis_template.md`
## Logs
- CLI Logs: `./logs/sqlai-YYYY-MM-DD.log`
- Bootstrap Logs: `./logs/bootstrap-YYYY-MM-DDTHH:MM:SS.log`
- Update Logs: `./logs/update-YYYY-MM-DDTHH:MM:SS.log`
Die Logs enthalten:
- Input-Bytes, Mode, Model
- Roh-Metriken aus Ollama (Token Counts, Durations)
- Fehler inkl. curl exit codes
## Auto-Updates aktivieren (systemd --user)
```bash
mkdir -p ~/.config/systemd/user
cp systemd/user/* ~/.config/systemd/user/
systemctl --user daemon-reload
systemctl --user enable --now jr-sql-ai-update.timer
systemctl --user list-timers | grep jr-sql-ai
```
## Troubleshooting
- **API nicht erreichbar**: Prüfe `docker ps` und ob Port 11434 lokal erreichbar ist (Host-Netz).
- **Langsam/OOM**: setze `BASE_MODEL` kleiner (z.B. 7b) und re-run `./scripts/update.sh`.
- **Model fehlt**: `./scripts/update.sh` ausführen und prüfen ob `ollama list` im Container das Model zeigt:
`docker exec -it ollama ollama list`

193
bin/sqlai
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@@ -14,22 +14,33 @@ log_dir="${ROOT}/logs"
mkdir -p "$log_dir"
log_file="${log_dir}/sqlai-$(date -I).log"
# log everything (stdout+stderr)
# Log everything (stdout+stderr)
exec > >(tee -a "$log_file") 2>&1
usage() {
cat <<EOF
cat <<'EOF'
Usage:
sqlai <mode> [--file path]
sqlai <mode> [--file path] [--text "free text"] [--no-metrics]
Modes:
analyze-tsql
analyze-proc
analyze-view
analyze-plan
utf8-migration
ask General SQL Server 2022 Q&A (free text)
analyze-tsql Analyze a T-SQL query
analyze-proc Analyze a stored procedure
analyze-view Analyze a view
analyze-plan Analyze an execution plan (Showplan XML or text)
utf8-migration Create a UTF-8 migration plan (SQL Server 2022)
Input options:
--text "..." Provide input text directly (no pipe needed)
--file path Read input from file
(no args) Reads from STDIN
Other options:
--no-metrics Do not print metrics line
Examples:
cat query.sql | sqlai analyze-tsql
sqlai ask --text "How do I troubleshoot parameter sniffing in SQL Server 2022?"
echo "SELECT 1;" | sqlai analyze-tsql
sqlai analyze-plan --file showplan.xml
EOF
}
@@ -39,44 +50,58 @@ mode="${1:-}"
shift || true
file=""
text=""
no_metrics="0"
while [[ $# -gt 0 ]]; do
case "$1" in
--file) file="$2"; shift 2;;
--file) file="${2:-}"; shift 2;;
--text) text="${2:-}"; shift 2;;
--no-metrics) no_metrics="1"; shift 1;;
-h|--help) usage; exit 0;;
*) echo "[$(ts)] ERROR: Unknown arg: $1"; usage; exit 2;;
esac
done
# Read input (priority: --text > --file > stdin)
input=""
if [[ -n "$file" ]]; then
if [[ ! -f "$file" ]]; then
echo "[$(ts)] ERROR: file not found: $file"
exit 3
fi
input_src=""
if [[ -n "$text" ]]; then
input="$text"
input_src="text"
elif [[ -n "$file" ]]; then
[[ -f "$file" ]] || { echo "[$(ts)] ERROR: file not found: $file"; exit 3; }
input="$(cat "$file")"
input_src="file:${file}"
else
input="$(cat)"
input_src="stdin"
fi
if [[ -z "${input//[[:space:]]/}" ]]; then
echo "[$(ts)] ERROR: empty input"
echo "[$(ts)] ERROR: empty input (source=$input_src)"
exit 4
fi
# Short instruction per mode (core policy is in Modelfile SYSTEM prompt)
case "$mode" in
ask)
instruction=$'Beantworte die Frage als SQL Server 2022 Experte.\n\nWichtig:\n- Wenn Kontext fehlt: keine Rückfragen stellen; stattdessen Annahmen offenlegen und Optionen (A/B/C) mit Vor-/Nachteilen geben.\n- Ergebnis immer strukturiert mit: Kurzfazit, Optionen, Risiken/Checks, Nächste Schritte.\n- Wenn sinnvoll: konkrete T-SQL/DDL Snippets und Checklisten liefern.'
;;
analyze-tsql)
instruction="Analysiere das folgende T-SQL (SQL Server 2022). Finde Performance-Probleme, SARGability, Indizes, Statistiken, Parameter Sniffing Risiken und gib konkrete Verbesserungen."
instruction=$'Analysiere das folgende T-SQL (SQL Server 2022): Performance, SARGability, Datentypen, Joins/Predicates, Indizes/Stats, Parameter Sniffing. Gib konkrete Rewrite- und Index-Ideen.'
;;
analyze-proc)
instruction="Analysiere die folgende Stored Procedure (SQL Server 2022). Finde Performance-/Correctness-Risiken, Transaktions-/Locking-Themen, Parameter Sniffing, fehlende Indizes. Gib konkrete Refactorings."
instruction=$'Analysiere die folgende Stored Procedure (SQL Server 2022): Performance/Correctness, Transaktionen/Locking, Sniffing, Temp tables vs table variables, RBAR. Gib konkrete Refactorings.'
;;
analyze-view)
instruction="Analysiere die folgende View (SQL Server 2022). Prüfe SARGability, Expand/Inlining-Effekte, mögliche Indexing-Optionen (z.B. indexed view falls sinnvoll) und Plan-Auswirkungen."
instruction=$'Analysiere die folgende View (SQL Server 2022): SARGability, Predicate Pushdown, Expand/Inlining, Aggregationen/Distinct/Union, UDF-Risiken. Gib konkrete Verbesserungen.'
;;
analyze-plan)
instruction="Analysiere den folgenden SQL Server Execution Plan (XML Showplan oder Text). Identifiziere teure Operatoren, Spills, Warnungen, Kardinalitätsfehler, fehlende Indizes und gib konkrete Fixes."
instruction=$'Analysiere den folgenden SQL Server Execution Plan (Showplan XML oder Text): Hotspots, Spills/Warnings, Memory Grants, Kardinalität, Fixes (Rewrite/Stats/Indexing vorsichtig/Sniffing Mitigation).'
;;
utf8-migration)
instruction="Erstelle einen Migrationsplan, um Tabellen/Spalten auf UTF-8 umzustellen (UTF-8 enabled collations mit _UTF8). Berücksichtige Abhängigkeiten (FK/PK/Indexes/Computed/Triggers), Risiken und gib eine Schritt-für-Schritt Checkliste."
instruction=$'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.'
;;
*)
echo "[$(ts)] ERROR: unknown mode: $mode"
@@ -85,46 +110,118 @@ case "$mode" in
;;
esac
req_id="$(date +%Y%m%d-%H%M%S)-$$-$RANDOM"
echo "================================================================================"
echo "[$(ts)] sqlai: REQUEST_START id=$req_id"
echo "[$(ts)] sqlai: MODE=$mode MODEL=$EXPERT_MODEL OLLAMA_URL=$OLLAMA_URL"
echo "[$(ts)] sqlai: INPUT_SOURCE=$input_src INPUT_BYTES=$(printf "%s" "$input" | wc -c)"
# Delimited markup
prompt=$(cat <<EOF
${instruction}
---BEGIN INPUT---
---BEGIN INPUT (${mode})---
${input}
---END INPUT---
---END INPUT (${mode})---
EOF
)
echo "[$(ts)] sqlai: MODE=$mode MODEL=$EXPERT_MODEL OLLAMA_URL=$OLLAMA_URL"
echo "[$(ts)] sqlai: INPUT_BYTES=$(printf "%s" "$input" | wc -c)"
payload="$(python - <<'PY'
# Build JSON safely (no heredoc+herestring combos)
payload="$(
printf '%s' "$prompt" | python -c '
import json, os, sys
model=os.environ.get("EXPERT_MODEL","jr-sql-expert")
prompt=sys.stdin.read()
print(json.dumps({"model": model, "prompt": prompt, "stream": False}, ensure_ascii=False))
PY
<<<"$prompt")"
'
)"
echo "[$(ts)] sqlai: sending request..."
resp="$(curl -sS -X POST "${OLLAMA_URL}/api/generate" -H 'Content-Type: application/json' --data-binary "$payload")" || {
rc=$?
echo "[$(ts)] sqlai: ERROR: curl failed rc=$rc"
exit 10
}
resp_file="$(mktemp)"
http_code="$(
curl -sS -o "$resp_file" -w "%{http_code}" \
-X POST "${OLLAMA_URL}/api/generate" \
-H 'Content-Type: application/json' \
--data-binary "$payload" \
|| true
)"
python - <<'PY'
resp="$(cat "$resp_file")"
rm -f "$resp_file"
echo "[$(ts)] sqlai: HTTP_CODE=$http_code RESP_BYTES=$(printf "%s" "$resp" | wc -c) id=$req_id"
# Validate JSON
if ! printf '%s' "$resp" | python -c 'import json,sys; json.load(sys.stdin)' >/dev/null 2>&1; then
echo "[$(ts)] sqlai: ERROR: response is not valid JSON id=$req_id"
echo "[$(ts)] sqlai: RAW_RESPONSE_BEGIN id=$req_id"
printf '%s\n' "$resp"
echo "[$(ts)] sqlai: RAW_RESPONSE_END id=$req_id"
echo "[$(ts)] sqlai: REQUEST_END id=$req_id status=error"
exit 11
fi
# Extract error/response/metrics in one pass
extracted="$(
printf '%s' "$resp" | python -c '
import json,sys
obj=json.loads(sys.stdin.read())
print("\n" + (obj.get("response","").rstrip()) + "\n")
md = {
"total_duration": obj.get("total_duration"),
"load_duration": obj.get("load_duration"),
"prompt_eval_count": obj.get("prompt_eval_count"),
"prompt_eval_duration": obj.get("prompt_eval_duration"),
"eval_count": obj.get("eval_count"),
"eval_duration": obj.get("eval_duration"),
obj=json.load(sys.stdin)
out={
"error": obj.get("error"),
"response": obj.get("response",""),
"metrics": {
"total_duration": obj.get("total_duration"),
"load_duration": obj.get("load_duration"),
"prompt_eval_count": obj.get("prompt_eval_count"),
"prompt_eval_duration": obj.get("prompt_eval_duration"),
"eval_count": obj.get("eval_count"),
"eval_duration": obj.get("eval_duration"),
}
}
print("METRICS=" + json.dumps(md, ensure_ascii=False))
PY <<<"$resp"
print(json.dumps(out, ensure_ascii=False))
'
)"
echo "[$(ts)] sqlai: done"
error_msg="$(printf '%s' "$extracted" | python -c 'import json,sys; print((json.load(sys.stdin).get("error") or "").strip())')"
response_txt="$(printf '%s' "$extracted" | python -c 'import json,sys; print(json.load(sys.stdin).get("response") or "")')"
# HTTP != 200 is error
if [[ "$http_code" != "200" ]]; then
echo "[$(ts)] sqlai: ERROR: non-200 HTTP_CODE=$http_code id=$req_id"
if [[ -n "$error_msg" ]]; then
echo "[$(ts)] sqlai: OLLAMA_ERROR=$error_msg id=$req_id"
else
echo "[$(ts)] sqlai: BODY_SNIPPET_BEGIN id=$req_id"
printf '%s\n' "$resp" | head -n 120
echo "[$(ts)] sqlai: BODY_SNIPPET_END id=$req_id"
fi
echo "[$(ts)] sqlai: REQUEST_END id=$req_id status=error"
exit 12
fi
# API-level error
if [[ -n "$error_msg" ]]; then
echo "[$(ts)] sqlai: ERROR: OLLAMA_ERROR=$error_msg id=$req_id"
echo "[$(ts)] sqlai: REQUEST_END id=$req_id status=error"
exit 13
fi
# Print answer
printf "\n%s\n\n" "$(printf "%s" "$response_txt" | sed 's/[[:space:]]*$//')"
# If response empty, dump JSON snippet to log
if [[ -z "${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
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@@ -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 36 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---

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@@ -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"

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@@ -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"