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fix: use Ollama directly for correction generation (bypass SDK think-mode)

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SDK LLM chat returns empty content due to Qwen think-mode. Direct Ollama
/api/generate call with stream:false gets the full response including
think tags which we strip.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
Benjamin Admin
2026-04-28 16:30:51 +02:00
parent b175ad2594
commit 0106f3b5b6
1 changed files with 17 additions and 20 deletions
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37
backend-compliance/compliance/api/agent_scan_routes.py
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@@ -233,30 +233,27 @@ async def _add_corrections(findings: list[ScanFinding], dse_text: str) -> None:
if finding.severity in ("HIGH", "MEDIUM") and "MISSING" in finding.code:
service_name = finding.code.replace("DSE-MISSING-", "").replace("_", " ").title()
try:
async with httpx.AsyncClient(timeout=90.0) as client:
resp = await client.post(f"{SDK_URL}/sdk/v1/llm/chat", headers=SDK_HEADERS, json={
"messages": [
{"role": "system", "content": (
"/no_think\n"
"Du bist Datenschutzexperte. Erstelle einen einbaufertigen "
"Textbaustein fuer eine deutsche Datenschutzerklaerung fuer "
f"den Dienst '{service_name}'. Enthalte: Ueberschrift, "
"Anbietername, Zweck, Rechtsgrundlage nach DSGVO, "
"Drittlandtransfer-Hinweis wenn noetig, "
"Widerspruchsmoeglichkeit. Max 150 Woerter."
)},
{"role": "user", "content": f"Erstelle DSE-Textbaustein fuer: {service_name}"},
],
# Call Ollama directly (bypasses SDK RBAC + Think-mode issues)
ollama_url = os.environ.get("OLLAMA_URL", "http://host.docker.internal:11434")
ollama_model = os.environ.get("OLLAMA_MODEL", "qwen3.5:35b-a3b")
async with httpx.AsyncClient(timeout=120.0) as client:
resp = await client.post(f"{ollama_url}/api/generate", json={
"model": ollama_model,
"prompt": (
f"Erstelle einen einbaufertigen Textbaustein fuer eine deutsche "
f"Datenschutzerklaerung fuer den Dienst '{service_name}'. "
f"Enthalte: Ueberschrift, Anbietername mit Sitz, Zweck der Verarbeitung, "
f"Rechtsgrundlage nach DSGVO, Drittlandtransfer-Hinweis wenn noetig, "
f"Widerspruchsmoeglichkeit. Max 150 Woerter. "
f"Antworte NUR mit dem fertigen Textbaustein."
),
"stream": False,
})
data = resp.json()
import re
raw = (
data.get("response", "")
or (data.get("message", {}) or {}).get("content", "")
or ""
).strip()
raw = data.get("response", "").strip()
raw = re.sub(r"<think>.*?</think>", "", raw, flags=re.DOTALL).strip()
if raw:
if raw and len(raw) > 50:
finding.correction = raw
except Exception as e:
logger.warning("Correction generation failed for %s: %s", service_name, e)