File size: 8,426 Bytes
bc39556 ad5be9b bc39556 d88f966 bc39556 ad5be9b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 | """
End-to-end flow tests for phi3-mini-sql-generator demo.
Run with: python tests/e2e_flow_test.py
Model must be loaded first. Call app.load_model(app.FINE_TUNED_MODEL_ID)
before running these tests.
"""
import app
import types
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
def sql_out(result):
return result[4]
def status(result):
return result[6]
def reset_model_state():
app._model = None
app._tokenizer = None
app._current_model_id = None
def check_sql(result, expected_fragments, description):
"""Print and assert SQL output checks."""
sql = sql_out(result)
status_msg = status(result)
ok = True
for frag in expected_fragments:
if frag not in sql:
print(f" FAIL: missing '{frag}' in output")
ok = False
if ok:
print(f" OK: {description}")
print(f" SQL: {sql[:200]}")
return ok
# ---------------------------------------------------------------------------
# Scenario 1: Parser still works (no model call)
# ---------------------------------------------------------------------------
def test_scenario1_parser_keeps_working():
print("\n=== Scenario 1: Parser — accented columns ===")
result = app.generate_response(
"criar tabela animal com nome nome cientifico e especie",
[], "", None, None
)
fragments = ["CREATE TABLE animal", "nome TEXT", "cientifico TEXT", "especie TEXT"]
return check_sql(result, fragments, "3 columns from Portuguese message")
# ---------------------------------------------------------------------------
# Scenario 2: SELECT all
# ---------------------------------------------------------------------------
def test_scenario2_select_all():
print("\n=== Scenario 2: SELECT all rows ===")
schema = app.PRESETS["employees"]
result = app.generate_response(
"liste todos os funcionarios",
[], schema, app.FINE_TUNED_MODEL_KEY, None
)
sql = sql_out(result)
status_msg = status(result)
ok = True
if "SELECT" not in sql.upper():
print(f" FAIL: no SELECT in output")
ok = False
if "FROM" not in sql.upper():
print(f" FAIL: no FROM in output")
ok = False
if ok:
print(f" OK: generated SELECT")
print(f" SQL: {sql}")
return ok
# ---------------------------------------------------------------------------
# Scenario 3: SELECT with WHERE filter
# ---------------------------------------------------------------------------
def test_scenario3_select_with_filter():
print("\n=== Scenario 3: SELECT with WHERE ===")
schema = app.PRESETS["employees"]
result = app.generate_response(
"mostre os funcionarios do departamento de vendas",
[], schema, app.FINE_TUNED_MODEL_KEY, None
)
sql = sql_out(result)
ok = True
if "SELECT" not in sql.upper():
print(f" FAIL: no SELECT")
ok = False
if "WHERE" not in sql.upper():
print(f" FAIL: no WHERE")
ok = False
if "department" in sql.lower() or "vendas" in sql.lower():
print(f" OK: WHERE clause present")
print(f" SQL: {sql}")
else:
print(f" FAIL: filter condition missing")
ok = False
return ok
# ---------------------------------------------------------------------------
# Scenario 4: Aggregate (COUNT, AVG, GROUP BY)
# ---------------------------------------------------------------------------
def test_scenario4_aggregates():
print("\n=== Scenario 4: Aggregate query ===")
schema = app.PRESETS["employees"]
result = app.generate_response(
"qual a media de salarios por departamento",
[], schema, app.FINE_TUNED_MODEL_KEY, None
)
sql = sql_out(result)
ok = True
checks = ["SELECT", "AVG", "GROUP BY"]
for c in checks:
if c not in sql.upper():
print(f" FAIL: missing '{c}'")
ok = False
if ok:
print(f" OK: aggregate query generated")
print(f" SQL: {sql}")
return ok
# ---------------------------------------------------------------------------
# Scenario 5: Natural language SQL (Issue 3)
# ---------------------------------------------------------------------------
def test_scenario5_natural_language():
print("\n=== Scenario 5: Natural language SQL (Issue 3) ===")
schema = app.PRESETS["products"]
result = app.generate_response(
"what is the most expensive product",
[], schema, app.FINE_TUNED_MODEL_KEY, None
)
sql = sql_out(result)
status_msg = status(result)
ok = True
if not sql.strip():
print(f" FAIL: no SQL generated — model returned: {status_msg[:100]}")
ok = False
elif "SELECT" not in sql.upper():
print(f" FAIL: output is not SQL: {sql[:100]}")
ok = False
else:
print(f" OK: natural language produced SQL")
print(f" SQL: {sql}")
return ok
# ---------------------------------------------------------------------------
# Scenario 6: Multi-turn flow (create → add → remove → query)
# ---------------------------------------------------------------------------
def test_scenario6_multiturn_flow():
print("\n=== Scenario 6: Multi-turn schema build + query ===")
ok = True
# Step 1: Create table
r1 = app.generate_response(
"crie tabela vendas com id produto quantidade total",
[], "", None, None
)
if not check_sql(r1, ["CREATE TABLE vendas", "id INTEGER", "produto TEXT", "quantidade INTEGER", "total NUMERIC"], "Step 1: CREATE TABLE"):
ok = False
# Step 2: Add column
r2 = app.generate_response("adicione desconto", r1[0], "", None, None)
if not check_sql(r2, ["desconto NUMERIC", "CREATE TABLE vendas"], "Step 2: ADD COLUMN"):
ok = False
# Step 3: Remove column
r3 = app.generate_response("remova quantidade", r2[0], "", None, None)
sql3 = sql_out(r3)
# CORRECT: quantidade should NOT be in SQL (it was removed)
if "quantidade" in sql3:
print(f" FAIL: 'quantidade' still in table after remove (regression)")
ok = False
else:
print(f" OK: Step 3: REMOVE COLUMN - 'quantidade' removed")
# Verify remaining columns still exist
for col in ["id", "produto", "desconto", "total"]:
if col not in sql3:
print(f" FAIL: column '{col}' missing after remove")
ok = False
# Step 4: Query (model call)
final_schema = sql_out(r3)
r4 = app.generate_response(
"quanto vendemos no total",
r3[0], final_schema, app.FINE_TUNED_MODEL_KEY, None
)
sql4 = sql_out(r4)
if "SELECT" not in sql4.upper():
print(f" FAIL: Step 4 no SELECT generated. Status: {status(r4)[:100]}")
ok = False
else:
print(f" OK: Step 4: model generated SQL from multi-turn context")
print(f" SQL: {sql4}")
return ok
# ---------------------------------------------------------------------------
# Run all
# ---------------------------------------------------------------------------
def run_all():
if app._model is None:
print("ERROR: model not loaded. Run app.load_model(app.FINE_TUNED_MODEL_ID) first.")
return
results = {}
results["s1_parser"] = test_scenario1_parser_keeps_working()
results["s2_select_all"] = test_scenario2_select_all()
results["s3_where"] = test_scenario3_select_with_filter()
results["s4_aggregates"] = test_scenario4_aggregates()
results["s5_natlang"] = test_scenario5_natural_language()
results["s6_multiturn"] = test_scenario6_multiturn_flow()
print("\n" + "=" * 50)
print("SUMMARY")
print("=" * 50)
passed = sum(1 for v in results.values() if v)
total = len(results)
for name, result in results.items():
mark = "PASS" if result else "FAIL"
print(f" {mark} {name}")
print(f"\n Total: {passed}/{total} passed")
return passed == total
if __name__ == "__main__":
# Check model loaded
if app._model is None:
print("Model not loaded. Call app.load_model(app.FINE_TUNED_MODEL_ID) then re-run.")
print("From python: python -c \"import app; app.load_model(app.FINE_TUNED_MODEL_ID); exec(open('tests/e2e_flow_test.py').read())\"")
else:
run_all()
|