110 lines
3.7 KiB
Python
110 lines
3.7 KiB
Python
"""Phase 5 — tight Top-K retrieval evaluation gates."""
|
|
from __future__ import annotations
|
|
|
|
from app.services.ai.ai_constants import MAX_TOOLS_AUTONOMOUS, MAX_TOOLS_PER_REQUEST
|
|
from app.services.ai.ai_tool_discovery import discover_tools
|
|
from app.services.ai.ai_tool_discovery_eval import (
|
|
CI_LEGACY_RECALL_AT_48_MIN,
|
|
CI_RECALL_AT_10_MIN,
|
|
CI_RECALL_AT_20_MIN,
|
|
CI_RECALL_AT_48_MIN,
|
|
CI_RETRIEVAL_SUCCESS_AT_15_MIN,
|
|
evaluate_at_k,
|
|
permissioned_catalog,
|
|
recommend_k,
|
|
)
|
|
from app.services.ai.ai_tool_discovery_gold import gold_stats, load_gold_queries
|
|
from app.services.ai.ai_tool_intent import filter_function_definitions
|
|
|
|
|
|
def test_gold_dataset_is_large_enough_to_measure_retrieval():
|
|
stats = gold_stats()
|
|
assert stats["queries"] >= 300
|
|
assert stats["match_queries"] >= 280
|
|
assert stats["tools_covered"] >= 120
|
|
assert stats["legacy_queries"] == 22
|
|
assert stats["no_match_queries"] >= 15
|
|
assert stats["write_queries"] >= 20
|
|
assert stats["destructive_queries"] >= 8
|
|
assert stats["memory_queries"] >= 6
|
|
assert stats["report_queries"] >= 20
|
|
|
|
|
|
def test_gold_queries_are_not_just_tool_names():
|
|
named = 0
|
|
for row in load_gold_queries():
|
|
if row.no_match:
|
|
continue
|
|
q = row.query.replace("-", "_").lower()
|
|
if any(tool == q or tool.replace("_", " ") == q for tool in row.primary_expected_tools):
|
|
named += 1
|
|
assert named == 0
|
|
|
|
|
|
def test_legacy_gold_recall_at_baseline_k48():
|
|
gold = [row for row in load_gold_queries() if row.source == "legacy"]
|
|
summary, _ = evaluate_at_k(48, rows=gold)
|
|
assert summary["recall"] >= CI_LEGACY_RECALL_AT_48_MIN
|
|
|
|
|
|
def test_retrieval_ci_gates_match_measured_baseline():
|
|
gold = load_gold_queries()
|
|
catalog = permissioned_catalog()
|
|
s10, _ = evaluate_at_k(10, rows=gold, catalog=catalog)
|
|
s20, _ = evaluate_at_k(20, rows=gold, catalog=catalog)
|
|
s48, _ = evaluate_at_k(48, rows=gold, catalog=catalog)
|
|
s15, _ = evaluate_at_k(15, rows=gold, catalog=catalog)
|
|
assert s10["recall"] >= CI_RECALL_AT_10_MIN
|
|
assert s20["recall"] >= CI_RECALL_AT_20_MIN
|
|
assert s48["recall"] >= CI_RECALL_AT_48_MIN
|
|
assert s15["retrieval_success_rate"] >= CI_RETRIEVAL_SUCCESS_AT_15_MIN
|
|
rec = recommend_k({
|
|
"10": s10,
|
|
"15": s15,
|
|
"20": s20,
|
|
"48": s48,
|
|
})
|
|
# Production K stays 48 in Phase 6 regardless of eval decision.
|
|
assert MAX_TOOLS_PER_REQUEST == 48
|
|
assert MAX_TOOLS_AUTONOMOUS == 128
|
|
assert rec["keep_autonomous_k"] == 128
|
|
|
|
|
|
def test_no_match_is_marked_low_confidence():
|
|
offer = discover_tools(
|
|
"هوا امروز چطوره؟",
|
|
permissioned_names=permissioned_catalog(),
|
|
execution_mode="analyzer",
|
|
channel="eval",
|
|
)
|
|
assert offer.low_confidence is True
|
|
assert offer.top_score <= 4
|
|
assert offer.candidates == ()
|
|
|
|
|
|
def test_ranked_candidates_are_score_descending():
|
|
offer = discover_tools(
|
|
"گزارش فروش این ماه را بده",
|
|
permissioned_names=permissioned_catalog(),
|
|
execution_mode="analyzer",
|
|
limit=48,
|
|
)
|
|
scores = [item.score for item in offer.candidates]
|
|
assert scores == sorted(scores, reverse=True)
|
|
assert offer.candidates
|
|
assert offer.score_gap == offer.top_score - offer.second_score
|
|
|
|
|
|
def test_filter_definitions_preserves_discovery_order():
|
|
defs = [
|
|
{"function": {"name": "search_invoices"}},
|
|
{"function": {"name": "get_sales_report"}},
|
|
{"function": {"name": "query_business_data"}},
|
|
]
|
|
ordered = filter_function_definitions(
|
|
defs, ["get_sales_report", "search_invoices"]
|
|
)
|
|
assert [d["function"]["name"] for d in ordered] == [
|
|
"get_sales_report",
|
|
"search_invoices",
|
|
]
|