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0cac9cf | 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 | """Interactive CLI adapter over the async QueryEngine.
This module is deliberately thin: it collects human input, supplies an
interactive approval policy, drives the engine, and renders the result. All SQL
logic lives in the engine and the sql/* modules.
Author: mohamedgamal04
"""
from __future__ import annotations
import asyncio
import json
import re
from collections.abc import Callable
from pathlib import Path
import pandas as pd
from rich.console import Console
from rich import box
from rich.panel import Panel
from rich.prompt import Prompt
from rich.syntax import Syntax
from .cli import is_quit_command, normalize_prompt_input
from .core.engine import QueryEngine
from .core.models import EngineConfig, EngineResult, StatementResult, WritebackTarget
from .core.policy import Policy
from .logger import append_log
from .sql.preview import print_dataframe_as_table, print_sql_statements_table
def _print_user_prompt(console: Console, prompt: str) -> None:
"""Render the user's prompt in a colorful boxed panel."""
console.print(
Panel(
prompt,
title="[bold bright_cyan]You[/bold bright_cyan]",
border_style="bright_cyan",
box=box.ROUNDED,
padding=(0, 1),
)
)
def _print_llm_response(console: Console, output: str, provider_name: str, model_name: str) -> None:
"""Render the model response in a colorful boxed panel."""
try:
parsed_output = json.loads(output)
renderable = Syntax(
json.dumps(parsed_output, indent=2, ensure_ascii=False),
"json",
theme="monokai",
word_wrap=True,
)
except Exception:
renderable = output
console.print(
Panel(
renderable,
title=f"[bold bright_magenta]{provider_name}[/bold bright_magenta] [dim]({model_name})[/dim]",
border_style="bright_magenta",
box=box.DOUBLE,
padding=(0, 1),
)
)
async def _ask(console: Console, *args, **kwargs) -> str:
"""Run a blocking rich prompt off the event loop."""
return await asyncio.to_thread(Prompt.ask, *args, console=console, **kwargs)
class InteractivePolicy(Policy):
"""Approval policy that asks the human at the terminal."""
def __init__(self, console: Console) -> None:
self._console = console
async def approve_execution(self, statements: list[StatementResult]) -> bool:
print_sql_statements_table([statement.sql for statement in statements], self._console)
choice = await _ask(
self._console,
"Execute these SQL statements in the CLI now?",
choices=["y", "n"],
default="n",
)
return choice.strip().lower() in {"y", "yes"}
async def approve_writeback(self, target: WritebackTarget) -> bool:
choice = await _ask(
self._console,
f"Save changes to {target.file_path.name} (sheet '{target.sheet_name}', "
f"{target.affected_rows} row(s))?",
choices=["y", "n"],
default="n",
)
return choice.strip().lower() in {"y", "yes"}
def _render_result(console: Console, result: EngineResult, provider_name: str, model_name: str) -> None:
"""Render an EngineResult: raw output, per-statement previews, and errors."""
if result.raw_llm_output:
_print_llm_response(console, result.raw_llm_output, provider_name, model_name)
if result.error is not None:
console.print(f"[red]Error:[/red] {result.error}")
return
for statement in result.statements:
if statement.error is not None:
console.print(f"[red]Refused/failed:[/red] {statement.error}")
console.print(f"Skipped statement: {statement.sql}")
continue
if statement.kind == "select":
dataframe = pd.DataFrame(statement.rows, columns=statement.columns or None)
print_dataframe_as_table(dataframe, console)
if statement.truncated:
console.print(f"Showing first {len(statement.rows)} of {statement.row_count} rows.")
elif statement.row_count == 0:
if re.search(r"\bjoin\b", statement.sql, flags=re.IGNORECASE):
console.print(
"[yellow]The join matched no rows.[/yellow] The two sheets may not share a "
"matching key column, so there is nothing to join on."
)
else:
console.print(
"[yellow]The query ran successfully but matched no rows.[/yellow] "
"Check the filter or column values."
)
else:
console.print(f"[green]{statement.kind.upper()}[/green] affected {statement.row_count} row(s).")
if result.wrote_back:
console.print("[green]Changes saved.[/green]")
elif result.writeback_targets:
console.print("[yellow]Changes not saved.[/yellow]")
def run_chat_session(
console: Console,
provider_name: str,
provider_base_url: str,
model_name: str,
api_key: str,
initial_prompt: str,
system_prompt_provider: Callable[[], str],
excel_file_count_provider: Callable[[], int],
excel_dir: str | Path,
) -> None:
"""Run the interactive prompt loop driven by the async engine."""
asyncio.run(
_run_loop(
console=console,
provider_name=provider_name,
provider_base_url=provider_base_url,
model_name=model_name,
api_key=api_key,
initial_prompt=initial_prompt,
system_prompt_provider=system_prompt_provider,
excel_file_count_provider=excel_file_count_provider,
excel_dir=excel_dir,
)
)
async def _run_loop(
console: Console,
provider_name: str,
provider_base_url: str,
model_name: str,
api_key: str,
initial_prompt: str,
system_prompt_provider: Callable[[], str],
excel_file_count_provider: Callable[[], int],
excel_dir: str | Path,
) -> None:
"""Async interactive loop: read prompt, run engine, render, repeat."""
policy = InteractivePolicy(console)
prompt = initial_prompt
while True:
while not prompt:
prompt = (await _ask(console, "You")).strip()
if prompt.startswith("-"):
console.print("Please prefix options with [cyan]qq[/cyan] or [cyan]QQ[/cyan] (example: [cyan]qq -q[/cyan]).")
prompt = ""
continue
prompt, prompt_flag_only = normalize_prompt_input(prompt)
if prompt_flag_only:
console.print("Please provide prompt text after -p/--prompt.")
prompt = ""
continue
if is_quit_command(prompt):
append_log({"event": "quit", "provider": provider_name, "model": model_name})
console.print("Goodbye.")
return
_print_user_prompt(console, prompt)
excel_file_count = excel_file_count_provider()
if excel_file_count == 0:
# No data source: never call the model or suggest SQL.
console.print(
"[yellow]No Excel files available[/yellow] in the selected directory. "
"Add a workbook and try again."
)
append_log(
{
"event": "llm_skipped_no_files",
"provider": provider_name,
"model": model_name,
"input_chars": len(prompt),
}
)
prompt = ""
continue
system_prompt = system_prompt_provider()
config = EngineConfig(
base_url=provider_base_url,
api_key=api_key,
model=model_name,
provider_name=provider_name,
system_prompt=system_prompt,
excel_dir=Path(excel_dir),
excel_files_count=excel_file_count,
)
engine = QueryEngine(config)
result = await engine.run(prompt, policy)
append_log(
{
"event": "llm_success" if result.error is None else "llm_error",
"provider": provider_name,
"model": model_name,
"input_chars": len(prompt),
"system_prompt_chars": len(system_prompt),
"output_chars": len(result.raw_llm_output),
"sql_statement_count": len(result.statements),
"excel_file_count": excel_file_count,
"executed": result.executed,
"wrote_back": result.wrote_back,
"error": result.error,
}
)
_render_result(console, result, provider_name, model_name)
prompt = ""
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