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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)}
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