File size: 27,276 Bytes
de36225
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from typing import Any, Dict, Optional, List
import asyncio
import importlib
import uuid
import os
import re

# Attempt to import agent workflow for schema/inspector & utilities (optional)
try:
    import Agent.agentic_workflow as aw
    print(f"[MCP STARTUP] Successfully imported Agent.agentic_workflow")
except Exception as e:
    print(f"[MCP STARTUP] Failed to import Agent.agentic_workflow: {e}")
    aw = None

app = FastAPI(title="Minimal MCP Server (dev)")

# Simple tool registry
TOOLS: Dict[str, Any] = {}


class CompleteRequest(BaseModel):
    prompt: str
    context: Optional[Dict[str, Any]] = None
    timeout: Optional[float] = 30.0


def register_tool(name: str, fn: Any):
    TOOLS[name] = fn


async def _call_tool(name: str, args: Dict[str, Any]) -> Any:
    if name not in TOOLS:
        raise KeyError(f"Tool '{name}' not registered")
    fn = TOOLS[name]
    if asyncio.iscoroutinefunction(fn):
        return await fn(**(args or {}))
    else:
        # run sync in threadpool
        loop = asyncio.get_running_loop()
        return await loop.run_in_executor(None, lambda: fn(**(args or {})))


@app.on_event("startup")
async def _startup():
    # Register built-in/mock tools lazily to avoid importing heavy modules at import time
    # Try to register a real document scanner implementation; otherwise register a mock
    ds_registered = None
    try:
        from .tools import document_scanner as ds
        register_tool("document_scanner.process", ds.process_image)
        ds_registered = f"Agent.tools.document_scanner.process_image (relative import)"
    except Exception:
        # If relative import fails (running as script), try absolute import
        try:
            import Agent.tools.document_scanner as ds2
            register_tool("document_scanner.process", ds2.process_image)
            ds_registered = f"Agent.tools.document_scanner.process_image (absolute import)"
        except Exception:
            # Register a fallback mock tool
            def _mock_doc(**kwargs):
                # Accept arbitrary keyword args (image_url, image_bytes, etc.) to be tolerant
                return {"doc_id": str(uuid.uuid4()), "text": "(mock OCR output)", "metadata": {"pages": 1, "confidence": 0.0}, "received_args": kwargs}
            register_tool("document_scanner.process", _mock_doc)
            ds_registered = "mock(document_scanner.process)"

    # Log which document scanner implementation was registered for easier debugging
    try:
        print(f"[MCP STARTUP] Registered document_scanner.process -> {ds_registered}")
    except Exception:
        pass

    # Register Granite Vision direct visual Q&A tool
    gv_registered = None
    try:
        from .tools import granite_vision as gv
        register_tool("granite_vision.qa", gv.qa)
        gv_registered = "Agent.tools.granite_vision.qa (relative import)"
    except Exception as e1:
        print(f"[MCP STARTUP] granite_vision relative import FAILED: {type(e1).__name__}: {e1}")
        try:
            import Agent.tools.granite_vision as gv2
            register_tool("granite_vision.qa", gv2.qa)
            gv_registered = "Agent.tools.granite_vision.qa (absolute import)"
        except Exception as e2:
            print(f"[MCP STARTUP] granite_vision absolute import FAILED: {type(e2).__name__}: {e2}")
            def _mock_gv(**kwargs):
                return {"answer": "(granite_vision unavailable - mock)", "model": "mock", "received_args": kwargs}
            register_tool("granite_vision.qa", _mock_gv)
            gv_registered = "mock(granite_vision.qa)"
    print(f"[MCP STARTUP] Registered granite_vision.qa -> {gv_registered}")


    # Register OCR QA composite tool: runs OCR then runs the agent OCR QA helper
    try:
        # Use the global aw variable instead of re-importing
        if not aw:
            raise ImportError("Agent workflow not available")

        async def _ocr_qa_tool(image_url: Optional[str] = None, image_bytes: Optional[bytes] = None, question: Optional[str] = None, **kwargs):
            # Call the document scanner tool first (use the registered one to allow mocks)
            ds_fn = TOOLS.get("document_scanner.process")
            if not ds_fn:
                raise RuntimeError("document_scanner.process not registered")

            loop = asyncio.get_running_loop()
            try:
                if asyncio.iscoroutinefunction(ds_fn):
                    tool_res = await ds_fn(image_url=image_url, image_bytes=image_bytes, options=kwargs)
                else:
                    tool_res = await loop.run_in_executor(None, lambda: ds_fn(image_url=image_url, image_bytes=image_bytes, options=kwargs))
            except Exception as e:
                return {"error": f"OCR tool failed: {e}"}

            doc_id = tool_res.get("doc_id") if isinstance(tool_res, dict) else None
            ocr_text = (tool_res.get("text") if isinstance(tool_res, dict) else str(tool_res)) or ""

            # Persist OCR text so downstream callers can retrieve it via doc_id
            try:
                if doc_id and ocr_text:
                    docs_dir = os.path.join("chat_store", "docs")
                    os.makedirs(docs_dir, exist_ok=True)
                    doc_path = os.path.join(docs_dir, f"{doc_id}.txt")
                    # Write file (overwrite if exists)
                    with open(doc_path, "w", encoding="utf-8") as df:
                        df.write(ocr_text)
                    # Also add a short history entry if agent chat store available
                    try:
                        if hasattr(aw, 'chat_store_private') and hasattr(aw, 'ChatMessage') and hasattr(aw, 'MessageRole'):
                            user_msg = aw.ChatMessage(role=aw.MessageRole.USER, content=f"Uploaded document {doc_id}")
                            assistant_msg = aw.ChatMessage(role=aw.MessageRole.ASSISTANT, content=f"OCR stored: {ocr_text[:400]}")
                            aw.chat_store_private.add_message(key="conversation", message=user_msg)
                            aw.chat_store_private.add_message(key="conversation", message=assistant_msg)
                            try:
                                aw.chat_store_private.persist(str(aw.private_store_path))
                            except Exception:
                                pass
                    except Exception:
                        pass
            except Exception:
                # Non-fatal: continue even if persistence fails
                pass

            # If a question was provided, answer it using the agent helper (run in executor to avoid blocking)
            if question:
                try:
                    # Use executor if helper is sync to avoid blocking event loop
                    if callable(getattr(aw, 'ocr_agent_qa', None)):
                        answer = await loop.run_in_executor(None, lambda: aw.ocr_agent_qa(question, doc_id))
                        return {"doc_id": doc_id, "answer": answer}
                    else:
                        return {"doc_id": doc_id, "answer": "ocr_agent_qa not available"}
                except Exception as e:
                    return {"error": f"ocr_agent_qa failed: {e}", "tool_result": tool_res}

            # No question: return the OCR result and doc_id
            return {"doc_id": doc_id, "ocr_text": ocr_text}

        register_tool("ocr_qa", _ocr_qa_tool)
        print(f"[MCP STARTUP] Registered ocr_qa -> real _ocr_qa_tool (agent available)")
    except Exception:
        # If agent import fails, register a tolerant mock tool
        def _ocr_qa_mock(**kwargs):
            return {"doc_id": str(uuid.uuid4()), "answer": "(ocr_qa unavailable - mock response)", "received_args": kwargs}
        register_tool("ocr_qa", _ocr_qa_mock)
        print(f"[MCP STARTUP] Registered ocr_qa -> mock(ocr_qa)")

    # ------------------------------------------------------------------
    # Deterministic schema-aware SQL helper tools (agentic compliant)
    # ------------------------------------------------------------------
    ENABLE_FAST_SQL = os.environ.get("ENABLE_MCP_FAST_TOOLS", "1") in ("1","true","True")
    if not ENABLE_FAST_SQL:
        print("[MCP STARTUP] Fast SQL tools disabled via ENABLE_MCP_FAST_TOOLS=0")
        return

    # Initialize database connection if not already done
    if not aw:
        print("[MCP STARTUP][FAST] Agent workflow not available; skipping fast SQL tool registration.")
        return
        
    if not getattr(aw, 'inspector', None) or not getattr(aw, 'available_tables', None):
        print("[MCP STARTUP][FAST] Database not initialized; attempting to initialize...")
        try:
            # Initialize database connection - use await since we're in async context
            db_uri = os.environ.get("DB_CONNECTION_URL")
            if not db_uri:
                print("[MCP STARTUP][FAST] DB_CONNECTION_URL not set; skipping fast SQL tool registration.")
                return
            db_result = await aw.initialize_database(db_uri)
            if db_result.get("tables"):
                print(f"[MCP STARTUP][FAST] Database initialized with {len(db_result['tables'])} tables")
            else:
                print("[MCP STARTUP][FAST] Database initialization failed; skipping fast SQL tool registration.")
                return
        except Exception as db_err:
            print(f"[MCP STARTUP][FAST] Database initialization error: {db_err}; skipping fast SQL tool registration.")
            return

    inspector = aw.inspector
    available_tables = aw.available_tables

    def _colnames(table: str) -> List[str]:
        try:
            return [c['name'] for c in inspector.get_columns(table_name=table)]
        except Exception:
            return []

    def _has_tables(*tables: str) -> bool:
        at_lower = {t.lower() for t in available_tables}
        return all(t.lower() in at_lower for t in tables)

    # Simple validation & sanitization re-use
    validate_sql_query = getattr(aw, 'validate_sql_query', lambda q: {"valid": True})
    fix_common_sql_errors = getattr(aw, 'fix_common_sql_errors', lambda q: q)

    async def _verify_sql(sql: str, question: str, tag: str) -> str:
        """Optional light LLM verification (short prompt) if LLM available."""
        if not aw or not getattr(aw, 'Settings', None) or not getattr(aw.Settings, 'llm', None):
            return sql
        try:
            prompt = (
                f"{aw.EMPLOYEE_DB_SCHEMA}\n\nYou are an SQL verifier. Tag={tag}."
                " If the candidate SQL is valid and uses only existing tables/columns keep it."
                " If SMALL fixes (alias, LIMIT 100, semicolon) needed, fix them. Never invent tables/columns."
                f"\nQuestion: {question}\nCandidate SQL:\n{sql}\nReturn ONLY final SQL." )
            resp = aw.Settings.llm.complete(prompt=prompt)
            txt = getattr(resp, 'text', str(resp)).strip()
            if '```' in txt:
                parts = re.split(r"```(?:sql)?", txt, flags=re.IGNORECASE)
                txt = '\n'.join(p for p in parts if 'select' in p.lower() or 'with' in p.lower())
            if txt.lower().startswith('sql'):
                txt = txt[3:].strip()
            txt = fix_common_sql_errors(txt)
            v = validate_sql_query(txt)
            if v.get('valid'):
                return txt
        except Exception as ve:
            print(f"[FAST][VERIFY][WARN] Verification failed: {ve}; using original SQL")
        return sql

    def _build_sql(select_cols: List[str], base_table: str, joins: Optional[List[str]] = None,
                   where: Optional[List[str]] = None, group_by: Optional[List[str]] = None,
                   order_by: Optional[str] = None, limit: Optional[int] = 100) -> str:
        parts = ["SELECT " + ", ".join(select_cols), "FROM " + base_table]
        for j in (joins or []):
            parts.append(j)
        if where:
            parts.append("WHERE " + " AND ".join(where))
        if group_by:
            parts.append("GROUP BY " + ", ".join(group_by))
        if order_by:
            parts.append("ORDER BY " + order_by)
        if limit is not None:
            parts.append(f"LIMIT {limit}")
        sql = " ".join(parts)
        if not sql.strip().endswith(';'):
            sql += ';'
        return sql

    async def tool_list_departments(question: str = ""):
        if not _has_tables('department'):
            return {"error": "department table not available"}
        cols = _colnames('department')
        name_col = 'dept_name' if 'dept_name' in cols else (cols[0] if cols else 'dept_name')
        sql = _build_sql([f"d.{name_col} AS department_name"], 'department d', order_by='department_name ASC')
        sql = fix_common_sql_errors(sql)
        sql = await _verify_sql(sql, question or 'List departments', 'list_departments')
        return {"sql": sql}

    async def tool_count_employees(question: str = ""):
        if not _has_tables('employee'):
            return {"error": "employee table not available"}
        sql = _build_sql(["COUNT(*) AS total_employees"], 'employee e', limit=None)
        sql = fix_common_sql_errors(sql)
        sql = await _verify_sql(sql, question or 'Total employees', 'count_employees')
        return {"sql": sql}

    async def tool_employee_count_by_department(question: str = ""):
        if not _has_tables('department','dept_emp'):
            return {"error": "required tables missing"}
        dcols = _colnames('department'); decols = _colnames('dept_emp')
        dept_name = 'dept_name' if 'dept_name' in dcols else (dcols[0] if dcols else 'dept_name')
        dept_no = 'dept_no' if 'dept_no' in dcols or 'dept_no' in decols else 'dept_no'
        emp_no = 'emp_no' if 'emp_no' in decols else 'emp_no'
        where = []
        if 'to_date' in decols:
            where.append("de.to_date = '9999-01-01'")
        sql = _build_sql([f"d.{dept_name} AS department_name", f"COUNT(DISTINCT de.{emp_no}) AS employee_count"],
                         'department d', joins=[f"JOIN dept_emp de ON d.{dept_no} = de.{dept_no}"],
                         where=where, group_by=[f"d.{dept_name}"], order_by='employee_count DESC')
        sql = fix_common_sql_errors(sql)
        sql = await _verify_sql(sql, question or 'Employees per department', 'employee_count_by_department')
        return {"sql": sql}

    async def tool_gender_pay_gap(question: str = ""):
        if not _has_tables('department','dept_emp','employee','salary'):
            return {"error": "required tables missing"}
        scolumns = _colnames('salary')
        sval = 'salary' if 'salary' in scolumns else ('amount' if 'amount' in scolumns else (scolumns[0] if scolumns else 'salary'))
        where = ["de.to_date = '9999-01-01'", "s.to_date = '9999-01-01'"]
        sql = _build_sql([
            "d.dept_name",
            f"AVG(CASE WHEN e.gender='M' THEN s.{sval} END) AS avg_male_salary",
            f"AVG(CASE WHEN e.gender='F' THEN s.{sval} END) AS avg_female_salary",
            f"(AVG(CASE WHEN e.gender='M' THEN s.{sval} END) - AVG(CASE WHEN e.gender='F' THEN s.{sval} END)) AS gap",
            f"CASE WHEN AVG(CASE WHEN e.gender='M' THEN s.{sval} END)=0 THEN NULL ELSE ((AVG(CASE WHEN e.gender='M' THEN s.{sval} END) - AVG(CASE WHEN e.gender='F' THEN s.{sval} END))/NULLIF(AVG(CASE WHEN e.gender='M' THEN s.{sval} END),0))*100 END AS pct_gap"
        ], 'department d',
            joins=['JOIN dept_emp de ON d.dept_no = de.dept_no','JOIN employee e ON de.emp_no = e.emp_no','JOIN salary s ON e.emp_no = s.emp_no'],
            where=where, group_by=['d.dept_name'], order_by='gap DESC')
        sql = fix_common_sql_errors(sql)
        sql = await _verify_sql(sql, question or 'Gender pay gap', 'gender_pay_gap')
        return {"sql": sql}

    async def tool_salary_extremes(question: str = ""):
        if not _has_tables('salary'):
            return {"error": "salary table missing"}
        scolumns = _colnames('salary'); sval = 'salary' if 'salary' in scolumns else ('amount' if 'amount' in scolumns else (scolumns[0] if scolumns else 'salary'))
        where = ["s.to_date = '9999-01-01'"] if 'to_date' in scolumns else []
        sql = _build_sql([f"MAX(s.{sval}) AS highest_salary", f"MIN(s.{sval}) AS lowest_salary"], 'salary s', where=where, limit=None)
        sql = fix_common_sql_errors(sql)
        sql = await _verify_sql(sql, question or 'Salary extremes', 'salary_extremes')
        return {"sql": sql}

    async def tool_salary_range_department(department_name: str = "Development", question: str = ""):
        if not _has_tables('department','dept_emp','salary'):
            return {"error": "required tables missing"}
        scolumns = _colnames('salary'); sval = 'salary' if 'salary' in scolumns else ('amount' if 'amount' in scolumns else (scolumns[0] if scolumns else 'salary'))
        # Escape single quotes in department_name for SQL safety (basic)
        escaped_dept = department_name.replace("'", "''")
        where = ["de.to_date = '9999-01-01'", "s.to_date = '9999-01-01'", f"d.dept_name = '{escaped_dept}'"]
        sql = _build_sql(["d.dept_name", f"MAX(s.{sval}) AS max_salary", f"MIN(s.{sval}) AS min_salary"], 'department d',
                         joins=['JOIN dept_emp de ON d.dept_no = de.dept_no','JOIN salary s ON de.emp_no = s.emp_no'],
                         where=where, group_by=['d.dept_name'], limit=None)
        sql = fix_common_sql_errors(sql)
        sql = await _verify_sql(sql, question or 'Department salary range', 'salary_range_department')
        return {"sql": sql, "department": department_name}

    async def tool_top_paid_employees(top_n: int = 10, question: str = ""):
        if not _has_tables('employee','salary'):
            return {"error": "required tables missing"}
        scolumns = _colnames('salary'); sval = 'salary' if 'salary' in scolumns else (scolumns[0] if scolumns else 'salary')
        where = ["s.to_date = '9999-01-01'"] if 'to_date' in scolumns else []
        sql = _build_sql(["e.emp_no","e.first_name","e.last_name", f"s.{sval} AS salary"], 'employee e',
                         joins=['JOIN salary s ON e.emp_no = s.emp_no'], where=where,
                         order_by=f"s.{sval} DESC", limit=top_n)
        sql = fix_common_sql_errors(sql)
        sql = await _verify_sql(sql, question or 'Top paid employees', 'top_paid_employees')
        return {"sql": sql, "top_n": top_n}

    async def tool_department_highest_avg_salary(question: str = ""):
        if not _has_tables('department','dept_emp','salary'):
            return {"error": "required tables missing"}
        scolumns = _colnames('salary'); sval = 'salary' if 'salary' in scolumns else (scolumns[0] if scolumns else 'salary')
        where = ["de.to_date = '9999-01-01'", "s.to_date = '9999-01-01'"]
        sql = _build_sql(["d.dept_name", f"AVG(s.{sval}) AS avg_salary"], 'department d',
                         joins=['JOIN dept_emp de ON d.dept_no = de.dept_no','JOIN salary s ON de.emp_no = s.emp_no'],
                         where=where, group_by=['d.dept_name'], order_by='avg_salary DESC', limit=1)
        sql = fix_common_sql_errors(sql)
        sql = await _verify_sql(sql, question or 'Department highest average salary', 'dept_highest_avg_salary')
        return {"sql": sql}

    async def tool_department_manager_listing(question: str = ""):
        if not _has_tables('department','dept_manager','employee'):
            return {"error": "required tables missing"}
        where = ["dm.to_date = '9999-01-01'"]
        sql = _build_sql(["d.dept_name AS department_name","e.first_name","e.last_name"], 'department d',
                         joins=['JOIN dept_manager dm ON d.dept_no = dm.dept_no','JOIN employee e ON dm.emp_no = e.emp_no'],
                         where=where, order_by='department_name ASC')
        sql = fix_common_sql_errors(sql)
        sql = await _verify_sql(sql, question or 'Department managers', 'department_manager_listing')
        return {"sql": sql}

    # NEW: Complex analytical tools for business intelligence
    async def tool_gender_distribution_by_dept(question: str = ""):
        if not _has_tables('department','dept_emp','employee'):
            return {"error": "required tables missing"}
        where = ["de.to_date = '9999-01-01'"]
        sql = _build_sql([
            "d.dept_name AS department_name",
            "e.gender",
            "COUNT(*) AS count",
            "ROUND(COUNT(*) * 100.0 / SUM(COUNT(*)) OVER (PARTITION BY d.dept_name), 2) AS percentage"
        ], 'department d',
            joins=['JOIN dept_emp de ON d.dept_no = de.dept_no','JOIN employee e ON de.emp_no = e.emp_no'],
            where=where, group_by=['d.dept_name', 'e.gender'], order_by='department_name, gender')
        sql = fix_common_sql_errors(sql)
        sql = await _verify_sql(sql, question or 'Gender distribution by department', 'gender_distribution_by_dept')
        return {"sql": sql}

    async def tool_hiring_trend_by_year(question: str = ""):
        if not _has_tables('employee'):
            return {"error": "required table employee missing"}
        sql = _build_sql([
            "EXTRACT(YEAR FROM e.hire_date) AS hire_year",
            "COUNT(*) AS employees_hired",
            "COUNT(CASE WHEN e.gender='M' THEN 1 END) AS male_hires",
            "COUNT(CASE WHEN e.gender='F' THEN 1 END) AS female_hires"
        ], 'employee e', group_by=['EXTRACT(YEAR FROM e.hire_date)'], order_by='hire_year ASC')
        sql = fix_common_sql_errors(sql)
        sql = await _verify_sql(sql, question or 'Hiring trends by year', 'hiring_trend_by_year')
        return {"sql": sql}

    async def tool_employee_tenure_by_dept(question: str = ""):
        if not _has_tables('department','dept_emp','employee'):
            return {"error": "required tables missing"}
        where = ["de.to_date = '9999-01-01'"]
        sql = _build_sql([
            "d.dept_name AS department_name",
            "AVG(EXTRACT(DAYS FROM (CURRENT_DATE - e.hire_date))/365.25) AS avg_tenure_years",
            "MIN(EXTRACT(DAYS FROM (CURRENT_DATE - e.hire_date))/365.25) AS min_tenure_years", 
            "MAX(EXTRACT(DAYS FROM (CURRENT_DATE - e.hire_date))/365.25) AS max_tenure_years"
        ], 'department d',
            joins=['JOIN dept_emp de ON d.dept_no = de.dept_no','JOIN employee e ON de.emp_no = e.emp_no'],
            where=where, group_by=['d.dept_name'], order_by='avg_tenure_years DESC')
        sql = fix_common_sql_errors(sql)
        sql = await _verify_sql(sql, question or 'Employee tenure by department', 'employee_tenure_by_dept')
        return {"sql": sql}

    async def tool_female_managers_count(question: str = ""):
        if not _has_tables('dept_manager','employee'):
            return {"error": "required tables missing"}
        where = ["dm.to_date = '9999-01-01'", "e.gender = 'F'"]
        sql = _build_sql([
            "COUNT(*) AS female_managers_count",
            "COUNT(*) * 100.0 / (SELECT COUNT(*) FROM dept_manager dm2 WHERE dm2.to_date = '9999-01-01') AS percentage_female_managers"
        ], 'dept_manager dm',
            joins=['JOIN employee e ON dm.emp_no = e.emp_no'],
            where=where, limit=None)
        sql = fix_common_sql_errors(sql)
        sql = await _verify_sql(sql, question or 'Female managers count', 'female_managers_count')
        return {"sql": sql}

    async def tool_avg_salary_by_title_dept(question: str = ""):
        """Get average salary by title and department."""
        if not _has_tables('department', 'dept_emp', 'salary', 'title', 'employee'):
            return {"error": "required tables missing"}
        where = ["de.to_date = '9999-01-01'", "s.to_date = '9999-01-01'", "t.to_date = '9999-01-01'"]
        sql = _build_sql(["d.dept_name AS department_name", "t.title", "AVG(s.salary) AS avg_salary"], 'department d',
                         joins=['JOIN dept_emp de ON d.dept_no = de.dept_no',
                               'JOIN employee e ON de.emp_no = e.emp_no',
                               'JOIN salary s ON e.emp_no = s.emp_no',
                               'JOIN title t ON e.emp_no = t.emp_no'],
                         where=where, group_by=['d.dept_name', 't.title'], 
                         order_by='d.dept_name, avg_salary DESC', limit=100)
        sql = fix_common_sql_errors(sql)
        sql = await _verify_sql(sql, question or 'Average salary by title and department', 'avg_salary_by_title_dept')
        return {"sql": sql}

    register_tool('fast_sql.list_departments', tool_list_departments)
    register_tool('fast_sql.count_employees', tool_count_employees)
    register_tool('fast_sql.employee_count_by_department', tool_employee_count_by_department)
    register_tool('fast_sql.gender_pay_gap', tool_gender_pay_gap)  # RE-ENABLED: Complex analytical queries
    register_tool('fast_sql.salary_extremes', tool_salary_extremes)
    register_tool('fast_sql.salary_range_department', tool_salary_range_department)
    register_tool('fast_sql.top_paid_employees', tool_top_paid_employees)
    register_tool('fast_sql.department_highest_avg_salary', tool_department_highest_avg_salary)
    register_tool('fast_sql.department_manager_listing', tool_department_manager_listing)
    
    # Register new complex analytical tools
    register_tool('fast_sql.gender_distribution_by_dept', tool_gender_distribution_by_dept)
    register_tool('fast_sql.hiring_trend_by_year', tool_hiring_trend_by_year)
    register_tool('fast_sql.employee_tenure_by_dept', tool_employee_tenure_by_dept)
    register_tool('fast_sql.female_managers_count', tool_female_managers_count)
    register_tool('fast_sql.avg_salary_by_title_dept', tool_avg_salary_by_title_dept)
    print('[MCP STARTUP] Registered fast SQL tools: ' + ', '.join([k for k in TOOLS if k.startswith('fast_sql.')]))


@app.post("/complete")
async def complete(req: CompleteRequest):
    """Minimal completion endpoint:
    - If context contains {'tool_call': {'name': ..., 'args': {...}}}, the server will run the tool and return its result.
    - Otherwise it returns a simple echo of the prompt under 'text'.
    This scaffold is purposely small so you can extend tool orchestration later.
    """
    ctx = req.context or {}
    # Tool invocation flow
    if 'tool_call' in ctx:
        tc = ctx['tool_call']
        name = tc.get('name')
        args = tc.get('args', {})
        try:
            tool_res = await _call_tool(name, args)
            return {"text": f"Tool '{name}' executed.", "tool_result": tool_res}
        except KeyError as ke:
            raise HTTPException(status_code=404, detail=str(ke))
        except Exception as e:
            raise HTTPException(status_code=500, detail=f"Tool call failed: {e}")

    # No tool requested: return a simple completion echo for now
    # Future: integrate a local model here and tool loop orchestration
    return {"text": req.prompt}


@app.get("/tools")
def list_tools():
    return {"tools": list(TOOLS.keys())}


@app.get("/health")
def health():
    return {"status": "ok", "tools_registered": len(TOOLS)}