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fix(rag+llm): 60 wide treffer, Pfad-Dedup, 100k tool payload

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(Nachtrag: vorheriger Commit enthielt nur telegram_bot.)
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Homelab Cursor 2026-03-26 17:15:48 +01:00
parent 60d0ef671d
commit ae6a50d182
2 changed files with 38 additions and 16 deletions
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6
homelab-ai-bot/llm.py
View file

@ -450,7 +450,7 @@ def ask_with_tools(question: str, tool_handlers: dict, session_id: str = None, d
question
+ " Versicherung Beitrag Beitragsrechnung Jahresbetrag"
)
_rag_res = _rag_fn(query=_rag_q, top_k=25)
_rag_res = _rag_fn(query=_rag_q, top_k=60)
if _rag_res and not _rag_res.startswith("Keine"):
log.info("RAG-Pflicht: %d Zeichen — loesche Session-History", len(str(_rag_res)))
messages = [
@ -467,9 +467,9 @@ def ask_with_tools(question: str, tool_handlers: dict, session_id: str = None, d
{"role": "assistant", "content": None,
"tool_calls": [{"id": "forced_rag", "type": "function",
"function": {"name": "rag_search",
"arguments": json.dumps({"query": _rag_q, "top_k": 25})}}]},
"arguments": json.dumps({"query": _rag_q, "top_k": 60})}}]},
{"role": "tool", "tool_call_id": "forced_rag",
"content": str(_rag_res)[:32000]},
"content": str(_rag_res)[:100000]},
{"role": "user", "content": question},
]
except Exception as e:

48
homelab-ai-bot/tools/rag.py
View file

@ -21,10 +21,10 @@ OLLAMA_EMBED_URL = "http://100.84.255.83:11434/api/embeddings"
EMBED_MODEL = "nomic-embed-text"
MIN_TOP_K = 5
# Breite Übersichten: mehr ES-Runden, mehr distinct Treffer
MAX_TOP_K_NORMAL = 15
MAX_TOP_K_WIDE = 25
ES_SIZE_CAP = 150
# Breite Übersichten: mehr ES-Runden, mehr distinct Treffer (pro vollem Pfad docnm_kwd)
MAX_TOP_K_NORMAL = 25
MAX_TOP_K_WIDE = 60
ES_SIZE_CAP = 200
TOOLS = [
{
@ -146,6 +146,11 @@ def _dedup_key(name: str) -> str:
return key.lower()
def _dedup_key_full_doc(name: str) -> str:
"""Ein Chunk pro vollem docnm_kwd — gleicher Dateiname in verschiedenen Ordnern bleibt getrennt."""
return re.sub(r"\s+", " ", (name or "").strip().lower())
def _es_hybrid_search(query: str, es_size: int) -> dict:
qvec = _ollama_embed(query)
if not qvec:
@ -273,16 +278,25 @@ _WIDE_SUBQUERIES = [
]
def _merge_hits_from_queries(queries: list[str], es_size: int, pool_cap: int) -> tuple[list, str | None]:
"""Führt mehrere Hybrid-Suchen aus; pro Dokument höchster Score."""
def _merge_hits_from_queries(
queries: list[str],
es_size: int,
pool_cap: int,
*,
full_path_dedup: bool = False,
) -> tuple[list, str | None]:
"""Führt mehrere Hybrid-Suchen aus; pro Dedup-Key höchster Score."""
best: dict[str, dict] = {}
last_err: str | None = None
def dkey(dn: str) -> str:
return _dedup_key_full_doc(dn) if full_path_dedup else _dedup_key(dn)
def absorb(hits: list) -> None:
for h in hits:
src = h.get("_source") or {}
dn = src.get("docnm_kwd") or "?"
dk = _dedup_key(dn)
dk = dkey(dn)
sc = float(h.get("_score") or 0.0)
old = best.get(dk)
if old is None or sc > float(old.get("_score") or 0.0):
@ -318,15 +332,20 @@ def handle_rag_search(query: str, top_k: int = 8, **kw):
for sq in _WIDE_SUBQUERIES:
if sq.lower() not in qstrip.lower():
subqs.append(sq)
pool_cap = max(top_k * 3, 45)
hits, err = _merge_hits_from_queries(subqs[:16], es_size, pool_cap=pool_cap)
pool_cap = max(top_k * 5, 120)
hits, err = _merge_hits_from_queries(
subqs[:22],
es_size,
pool_cap=pool_cap,
full_path_dedup=True,
)
if err and not hits:
return f"Fehler bei der Dokumentensuche: {err}"
header = (
f"**Breitensuche ({len(subqs[:16])} Anfragen gemerged) fuer '{qstrip}' — "
f"{len(hits)} Kandidaten, zeige bis {top_k} distinct:**\n"
f"**Breitensuche ({len(subqs[:22])} Anfragen, Dedup=voller Pfad) '{qstrip}' — "
f"{len(hits)} Kandidaten, zeige bis {top_k}:**\n"
)
snip_len = 750
snip_len = 400
else:
data = _es_hybrid_search(qstrip, es_size)
if "_error" in data:
@ -342,12 +361,15 @@ def handle_rag_search(query: str, top_k: int = 8, **kw):
lines: list[str] = []
count = 0
def out_dkey(doc_name: str) -> str:
return _dedup_key_full_doc(doc_name) if wide else _dedup_key(doc_name)
for h in hits:
if count >= top_k:
break
src = h.get("_source") or {}
doc_name = src.get("docnm_kwd") or "?"
dk = _dedup_key(doc_name)
dk = out_dkey(doc_name)
if dk in seen_docs:
continue
seen_docs.add(dk)