Feat/0.1.0 #2

Merged
jiawei merged 7 commits from feat/0.1.0 into main 2026-10-10 22:06:50 +08:00
22 changed files with 457 additions and 327 deletions
Showing only changes of commit e3699d1a30 - Show all commits
+19 -10
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@@ -7,7 +7,7 @@ apply_actions 里的 $query 也通过 DataContext.query 执行,见 tools.py
上下文类型因 agent 而异,所以写 ToolRuntime[Any](不写类型参数时按 None 处理,序列化会告警)
"""
from dataclasses import dataclass
from dataclasses import dataclass, field
from pathlib import Path
from typing import Annotated, Any
@@ -17,7 +17,8 @@ from pydantic import Field
from app.config import settings
from app.datafiles.query import MAX_ROWS, QueryError, QueryResult, run_query
from app.schemas.data_file import RequestDataFile, RequestDataTable
from app.datafiles.storage import table_path
from app.schemas.data_file import DataFileRecord, DataTable
# 列超过这么多时,不指定 columns 只返回列名和类型,避免一次塞进太多概况
BRIEF_COLUMNS = 50
@@ -25,9 +26,12 @@ BRIEF_COLUMNS = 50
@dataclass(frozen=True)
class DataContext:
files: tuple[RequestDataFile, ...] = ()
"""本次运行可用的数据文件;root 是数据文件的根目录,Parquet 路径由它和文件记录算出"""
def find(self, name: str) -> tuple[RequestDataFile, RequestDataTable] | None:
files: tuple[DataFileRecord, ...] = ()
root: Path = field(default_factory=lambda: settings.data_file_dir)
def find(self, name: str) -> tuple[DataFileRecord, DataTable] | None:
for file in self.files:
for table in file.tables:
if table.table == name:
@@ -36,7 +40,7 @@ class DataContext:
def paths(self) -> dict[str, Path]:
return {
table.table: Path(table.path)
table.table: table_path(self.root, file.file_id, table)
for file in self.files
for table in file.tables
}
@@ -86,7 +90,7 @@ def describe_data(
if found is None:
return _error(runtime, f"没有表 {table},可用的表:{_table_list(data)}")
file, item = found
profiled: list[dict[str, Any]] = item.profile["columns"]
profiled = item.profile.columns
result: dict[str, Any] = {
"table": item.table,
"label": item.label,
@@ -94,20 +98,25 @@ def describe_data(
}
if columns is None and len(profiled) > BRIEF_COLUMNS:
result["columns"] = [
{key: column[key] for key in ("name", "type", "format") if key in column}
column.model_dump(
mode="json", include={"name", "type", "format"}, exclude_none=True
)
for column in profiled
]
result["note"] = (
f"共 {len(profiled)} 列,只列出列名和类型;用 columns 指定列查看详细概况和样例"
)
else:
index = {column["name"]: position for position, column in enumerate(profiled)}
index = {column.name: position for position, column in enumerate(profiled)}
names = list(index) if columns is None else list(dict.fromkeys(columns))
positions = [index[name] for name in names if name in index]
result["columns"] = [profiled[position] for position in positions]
result["columns"] = [
profiled[position].model_dump(mode="json", exclude_none=True)
for position in positions
]
# 样例行的值和 columns 一一对应
result["sample_rows"] = [
[row[position] for position in positions] for row in item.profile["sample"]
[row[position] for position in positions] for row in item.profile.sample
]
if missing := [name for name in names if name not in index]:
result["missing_columns"] = missing
+45 -4
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@@ -3,13 +3,17 @@
from typing import Annotated, Literal, get_args
from fastapi import APIRouter, Depends, File, Form, Query, Request, UploadFile
from fastapi.responses import JSONResponse
from starlette.types import ASGIApp, Receive, Scope, Send
from app.common.response import ApiResponse, success_response
from app.common.response import ApiResponse, error_content, success_response
from app.core.auth import get_current_user
from app.datafiles.base import MAX_TABLE_ROWS
from app.datafiles.service import (
MAX_FILES_PER_CONVERSATION,
PARSE_CONCURRENCY,
DataFileService,
file_too_large,
)
from app.schemas.base import NonBlankString
from app.schemas.data_file import (
@@ -31,18 +35,55 @@ from app.schemas.user import CurrentUser
limits_router = APIRouter(prefix="/files", tags=["DataFile"])
router = APIRouter(prefix="/files", tags=["DataFile"])
# 文件选择框的过滤条件;后端按文件内容识别格式,不看扩展名
# 翻页取表数据:单页上限,和一张表最多的行数(100 万)
# 翻页取表数据:单页上限,offset 不超过一张表最多的行数
MAX_PAGE_ROWS = 500
MAX_OFFSET = 1_000_000
MAX_OFFSET = MAX_TABLE_ROWS
# 文件选择框的过滤条件;后端按文件内容识别格式,不看扩展名
ACCEPT = ".csv,.tsv,.txt,.xlsx,.xls,.xlsb,.json,.jsonl,.ndjson,.parquet"
# 上传的请求体比文件本身多出 multipart 的分隔行、字段名和会话 ID
UPLOAD_OVERHEAD_BYTES = 64 * 1024
def _service(request: Request) -> DataFileService:
return request.app.state.data_file_service
class UploadSizeLimit:
"""上传接口在读取请求体之前按 Content-Length 拒绝过大的请求
FastAPI 会先把整个 multipart 请求体收完、写进临时文件,再调用接口函数;
只在 DataFileService 里边写边查大小的话,超大的上传已经占满了带宽和磁盘
"""
def __init__(self, app: ASGIApp, path: str):
self.app = app
self.path = path
async def __call__(self, scope: Scope, receive: Receive, send: Send) -> None:
if (
scope["type"] == "http"
and scope["method"] == "POST"
and scope["path"] == self.path
and (rejection := self._reject(scope)) is not None
):
await rejection(scope, receive, send)
return
await self.app(scope, receive, send)
@staticmethod
def _reject(scope: Scope) -> JSONResponse | None:
max_mb = scope["app"].state.data_file_service.max_mb
length = dict(scope["headers"]).get(b"content-length")
if length is None or not length.isdigit():
return JSONResponse(error_content(411, "缺少 Content-Length"), 411)
if int(length) > max_mb * 1024 * 1024 + UPLOAD_OVERHEAD_BYTES:
error = file_too_large(max_mb)
return JSONResponse(error_content(error.code, error.msg), error.code)
return None
def _detail(record: DataFileRecord) -> DataFileDetail:
# 按接口模型重新校验,去掉 owner_id、sha256、列概况等只在后端用的字段
return DataFileDetail.model_validate(record.model_dump())
+33 -3
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@@ -3,9 +3,18 @@
列名、别名一律通过 quote_identifier 引用,请求里的字符串不会拼进 SQL 的其他位置
"""
from pathlib import Path
from app.config import settings
from app.core.exceptions import BizException
from app.datafiles.query import quote_identifier
from app.schemas.data_file import AggregateRequest, DataColumn, GroupBy, Metric
from app.datafiles.query import quote_identifier, run_query
from app.schemas.data_file import (
AggregateRequest,
AggregateResult,
DataColumn,
GroupBy,
Metric,
)
# 只能用于数值列的聚合;其余聚合对列类型没有要求
NUMBER_ONLY = {"sum", "avg"}
@@ -20,7 +29,28 @@ TEMPLATES = {
TIME_TYPES = {"date", "datetime"}
def build_aggregate_sql(
def run_aggregate(
path: Path, request: AggregateRequest, columns: list[DataColumn]
) -> AggregateResult:
"""对一张表的 Parquet 执行汇总;接口和上传后的分析共用
请求不合法时抛 422;执行失败(包括文件已被删除)抛 QueryError
"""
sql, names = _build_sql(request, columns)
result = run_query(
sql,
{"t": path},
timeout=settings.data_query_timeout,
max_rows=request.limit,
)
return AggregateResult(
columns=names,
rows=[dict(zip(names, row)) for row in result.rows],
truncated=result.truncated,
)
def _build_sql(
request: AggregateRequest, columns: list[DataColumn]
) -> tuple[str, list[str]]:
"""返回 SQL(表名固定为 t)和结果列名;请求不合法时抛 422
+8 -1
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@@ -1,4 +1,6 @@
"""数据文件各环节共用的异常和上限"""
"""数据文件各环节共用的异常、上限和警告文案的写法"""
from collections.abc import Sequence
# 每张表的数据行数上限
MAX_TABLE_ROWS = 1_000_000
@@ -26,6 +28,11 @@ def where(sheet: str | None) -> str:
return f"{sheet}:" if sheet else ""
def brief(items: Sequence[str], sep: str = "、", limit: int = 5) -> str:
"""警告里列举的内容最多写 limit 个,多出的用“等”概括"""
return sep.join(items[:limit]) + ("等" if len(items) > limit else "")
def rows_exceeded(sheet: str | None) -> DataFileError:
return DataFileError(
422, f"{where(sheet)}超过 {MAX_TABLE_ROWS // 10_000} 万行,请拆分后上传"
+23 -29
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@@ -15,7 +15,7 @@ from typing import Any
import pyarrow as pa
from app.datafiles.base import where
from app.datafiles.base import brief, where
from app.schemas.data_file import DataColumn, ParseWarning
NULL_TOKENS = {"", "-", "--", "—", "——", "N/A", "n/a", "NULL", "null", "#N/A"}
@@ -63,7 +63,7 @@ def clean_names(
"""去掉空白和换行;空列名按位置命名,重复列名加后缀"""
names, changes, seen = [], [], set()
for position, value in enumerate(raw, start=1):
name = re.sub(r"\s*[\r\n]+\s*", " ", label_text(value)).strip()
name = re.sub(r"\s*[\r\n]+\s*", " ", as_text(value)).strip()
if not name:
name = f"列{position}"
changes.append(f"第 {position} 列没有列名,命名为「{name}」")
@@ -77,19 +77,9 @@ def clean_names(
names.append(name)
if not changes:
return names, None
shown = ";".join(changes[:5]) + ("等" if len(changes) > 5 else "")
return names, ParseWarning(code="column_renamed", message=f"{where(sheet)}{shown}")
def label_text(value: Any) -> str:
"""表头单元格转成列名;Excel 里年份等数字表头读出来是 2025.0"""
if value is None:
return ""
if isinstance(value, float) and value.is_integer():
return str(int(value))
if isinstance(value, (date, time)):
return value.isoformat()
return str(value)
return names, ParseWarning(
code="column_renamed", message=f"{where(sheet)}{brief(changes, ';')}"
)
def build_columns(
@@ -257,29 +247,29 @@ def classify(value: Any) -> tuple[str, Any]:
def parse_number(text: str) -> int | float | None:
"""千分位和货币符号可以有;有前导零或 16 位以上的数字串是编号,不算数值"""
# 最常见的纯数字走快速路径,不用正则
if text.isdigit():
if len(text) >= MIN_ID_DIGITS or (len(text) > 1 and text[0] == "0"):
return None
return int(text)
"""千分位和货币符号可以有;有前导零或 16 位以上的数字串是编号,不算数值
判断数字一律用 isdecimal:isdigit 对 ²、① 也返回 True,但 int() 解析不了它们
"""
if text and text[0] in CURRENCY_SYMBOLS:
text = text[1:].lstrip()
if not NUMBER.match(text):
# 最常见的纯数字不用正则
plain = text.isdecimal()
if not plain and not NUMBER.match(text):
return None
digits = text.lstrip("+-")
if len(digits) > 1 and digits[0] == "0" and digits[1].isdigit():
if len(digits) > 1 and digits[0] == "0" and digits[1].isdecimal():
return None
if digits.isdigit() and len(digits) >= MIN_ID_DIGITS:
if digits.isdecimal() and len(digits) >= MIN_ID_DIGITS:
return None
text = text.replace(",", "")
if INTEGER.match(text):
if plain:
return int(text)
return float(text)
text = text.replace(",", "")
return int(text) if INTEGER.match(text) else float(text)
def parse_datetime(text: str) -> date | datetime | None:
if len(text) < 6 or not text[:4].isdigit():
if len(text) < 6 or not text[:4].isdecimal():
return None
# 标准 ISO 写法先用 fromisoformat,比 strptime 快一个数量级
if ":" in text:
@@ -307,6 +297,9 @@ def parse_datetime(text: str) -> date | datetime | None:
def as_text(value: Any) -> str:
"""单元格转成文本:列名、保留为文本的值、警告里引用的内容都用它;Excel 里年份等数字读出来是 2025.0"""
if value is None:
return ""
if isinstance(value, str):
return value.strip()
if isinstance(value, bool):
@@ -318,7 +311,8 @@ def as_text(value: Any) -> str:
if isinstance(value, (date, time)):
return value.isoformat()
if isinstance(value, (dict, list)):
return json.dumps(value, ensure_ascii=False)
# Parquet 的嵌套值里可能有日期、Decimal、bytes,JSON 表示不了的写成字符串
return json.dumps(value, ensure_ascii=False, default=str)
return str(value)
+7 -2
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@@ -3,6 +3,7 @@
import codecs
import csv
import json
import re
import zipfile
from dataclasses import dataclass
from pathlib import Path
@@ -29,6 +30,10 @@ DELIMITERS = (",", "\t", ";", "|")
# 判断分隔符只看开头这么多行
SNIFF_LINES = 50
# 开头像 JSON 才按 JSON 处理:对象的 { 后面只能是 " 或 },数组的 [ 后面是一个值的开头;
# CSV 的列名也可能以 [ 开头,例如 [日期],[销售额]
JSON_START = re.compile(r'\{\s*["}]|\[\s*(?:[\[{"\]\d-]|(?:true|false|null)\s*[,\]])')
@dataclass(frozen=True)
class Detected:
@@ -56,7 +61,7 @@ def detect(path: Path) -> Detected:
stripped = text.lstrip()
if not stripped:
raise DataFileError(422, "文件是空的")
if stripped[0] in "[{":
if JSON_START.match(stripped):
return _json_format(text, encoding)
delimiter = sniff_delimiter(text)
return Detected("tsv" if delimiter == "\t" else "csv", encoding, text, delimiter)
@@ -115,7 +120,7 @@ def _json_format(text: str, encoding: str) -> Detected:
return Detected("jsonl", encoding, text)
except ValueError:
pass
# 以 [ 或 { 开头却不是合法 JSON,按 JSON 报错比当成 CSV 解析出一堆乱码更有用
# 开头像 JSON 却不是合法 JSON,按 JSON 报错比当成 CSV 解析出一堆乱码更有用
line = getattr(json_error, "lineno", None)
position = f"第 {line} 行" if line else ""
raise DataFileError(
+13 -28
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@@ -9,7 +9,6 @@ import json
from collections.abc import Awaitable, Callable
from pathlib import Path
import duckdb
from langchain_core.exceptions import OutputParserException
from langchain_core.messages import HumanMessage, SystemMessage
from loguru import logger
@@ -18,9 +17,9 @@ from pydantic import BaseModel, Field, ValidationError
from app.clients.llm import get_llm
from app.config import settings
from app.core.exceptions import BizException
from app.datafiles.aggregate import build_aggregate_sql
from app.datafiles.query import QueryError, run_query
from app.datafiles.storage import file_dir
from app.datafiles.aggregate import run_aggregate
from app.datafiles.query import QueryError
from app.datafiles.storage import table_path
from app.prompt.insights import INSIGHTS_SYSTEM_PROMPT
from app.schemas.data_file import (
MAX_SUGGESTIONS,
@@ -106,21 +105,16 @@ def build_input(record: DataFileRecord) -> dict:
def _table_input(table: DataTable) -> dict:
columns = table.profile.get("columns", [])[:MAX_COLUMNS]
keep = {column["name"] for column in columns}
positions = [
position for position, column in enumerate(table.columns) if column.name in keep
]
return {
"table": table.table,
"label": table.label,
"rows": table.rows,
"columns": columns,
# 样例行只保留上面那些列,顺序与 columns 一致
"sample": [
[row[position] for position in positions]
for row in table.profile.get("sample", [])
"columns": [
column.model_dump(mode="json", exclude_none=True)
for column in table.profile.columns[:MAX_COLUMNS]
],
# 样例行和 columns 都按表的列顺序排列,截掉同样的列
"sample": [row[:MAX_COLUMNS] for row in table.profile.sample],
}
@@ -140,7 +134,7 @@ def check_draft(
if not title or table is None or key in seen:
continue
if not _fits_chart(item) or not _runs(
item, table, file_dir(root, record.file_id)
item, table, table_path(root, record.file_id, table)
):
logger.info("丢弃不可用的图表推荐:{} {}", record.file_id, item.title)
continue
@@ -162,20 +156,11 @@ def _fits_chart(item: ChartSuggestion) -> bool:
return len(request.metrics) == 1 or item.chart not in ("pie", "funnel")
def _runs(item: ChartSuggestion, table: DataTable, directory: Path) -> bool:
"""真实跑一遍汇总:能编译、能执行,并且有足够的行数画图"""
path = directory / table.parquet
if not path.is_file():
return False
def _runs(item: ChartSuggestion, table: DataTable, path: Path) -> bool:
"""真实跑一遍汇总:能编译、能执行(文件已被删除也算不能),并且有足够的行数画图"""
try:
sql, _ = build_aggregate_sql(item.request, table.columns)
result = run_query(
sql,
{"t": path},
timeout=settings.data_query_timeout,
max_rows=item.request.limit,
)
except (BizException, QueryError, duckdb.Error):
result = run_aggregate(path, item.request, table.columns)
except (BizException, QueryError):
return False
return len(result.rows) >= MIN_RESULT_ROWS
+39 -44
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@@ -3,7 +3,6 @@
只读写本地文件,不碰数据库;上传流程在子进程里调用(worker.py),超时直接终止子进程
"""
from dataclasses import dataclass
from pathlib import Path
from typing import Any
@@ -29,7 +28,7 @@ from app.datafiles.readers import (
read_parquet,
)
from app.datafiles.tables import split_tables
from app.schemas.data_file import DataColumn, DataFormat, ParseWarning
from app.schemas.data_file import DataColumn, DataFormat, ParseWarning, TableProfile
# 子进程把解析结果转成 JSON 交回上传流程,所以用 pydantic 模型
@@ -39,8 +38,9 @@ class ParsedTable(BaseModel):
part: int | None
rows: int
columns: list[DataColumn]
path: Path
profile: dict[str, Any]
# out_dir 下的 Parquet 文件名
parquet: str
profile: TableProfile
preview: list[list[Any]]
warnings: list[ParseWarning]
@@ -53,40 +53,53 @@ class ParsedFile(BaseModel):
warnings: list[ParseWarning]
@dataclass
class _Built:
sheet: str | None
part: int | None
typed: TypedColumns
warnings: list[ParseWarning]
def parse_file(path: Path, out_dir: Path) -> ParsedFile:
"""解析 path,Parquet 写到 out_dir/1.parquet、2.parquet……"""
"""解析 path,每张表在 out_dir 下写一个 Parquet:1.parquet、2.parquet……"""
detected = detect(path)
out_dir.mkdir(parents=True, exist_ok=True)
warnings: list[ParseWarning] = []
built: list[_Built] = []
tables: list[ParsedTable] = []
def add_table(
sheet: str | None,
part: int | None,
typed: TypedColumns,
table_warnings: list[ParseWarning],
) -> None:
target = out_dir / f"{len(tables) + 1}.parquet"
pq.write_table(typed.table, target)
profile, preview = profile_table(target, typed.columns, typed.notes)
tables.append(
ParsedTable(
sheet=sheet,
part=part,
rows=typed.table.num_rows,
columns=typed.columns,
parquet=target.name,
profile=profile,
preview=preview,
warnings=table_warnings,
)
)
def add_grid(grid: Grid) -> None:
tables, dropped = split_tables(grid)
found, dropped = split_tables(grid)
warnings.extend(dropped)
for table in tables:
for table in found:
names, renamed = clean_names(table.header, table.sheet)
typed, kept = build_columns(names, list(zip(*table.rows)), table.sheet)
built.append(
_Built(
table.sheet,
table.part,
typed,
[*table.warnings, *_present(renamed, kept)],
)
add_table(
table.sheet,
table.part,
typed,
[*table.warnings, *_present(renamed, kept)],
)
def add_records(records: Records) -> None:
warnings.extend(records.warnings)
names, renamed = clean_names(records.names, None)
typed, kept = build_columns(names, records.columns, None)
built.append(_Built(None, None, typed, _present(renamed, kept)))
add_table(None, None, typed, _present(renamed, kept))
match detected.format:
case "csv" | "tsv":
@@ -107,28 +120,10 @@ def parse_file(path: Path, out_dir: Path) -> ParsedFile:
case "parquet":
typed, renamed = arrow_columns(read_parquet(path))
if typed.table.num_rows:
built.append(_Built(None, None, typed, _present(renamed)))
add_table(None, None, typed, _present(renamed))
if not built:
if not tables:
raise DataFileError(422, "文件里没有找到数据")
out_dir.mkdir(parents=True, exist_ok=True)
tables = []
for index, item in enumerate(built, start=1):
target = out_dir / f"{index}.parquet"
pq.write_table(item.typed.table, target)
profile, preview = profile_table(target, item.typed.columns, item.typed.notes)
tables.append(
ParsedTable(
sheet=item.sheet,
part=item.part,
rows=item.typed.table.num_rows,
columns=item.typed.columns,
path=target,
profile=profile,
preview=preview,
warnings=item.warnings,
)
)
return ParsedFile(
format=detected.format,
encoding=detected.encoding,
+29 -30
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@@ -1,4 +1,4 @@
"""列概况和预览:上传时在 Parquet 上用 DuckDB 计算,存进文件记录,供 describe_data 和接口返回"""
"""列概况和预览:上传时在 Parquet 上用 DuckDB 计算,存进文件记录,供 describe_data、上传后的分析和接口返回"""
import math
from pathlib import Path
@@ -6,8 +6,9 @@ from typing import Any
import duckdb
from app.datafiles.columns import EXACT_FLOAT_INT
from app.datafiles.query import connect, json_value, quote_identifier
from app.schemas.data_file import DataColumn
from app.schemas.data_file import ColumnProfile, DataColumn, TableProfile, TopValue
PREVIEW_ROWS = 20
SAMPLE_ROWS = 5
@@ -23,11 +24,10 @@ PREVIEW_CELL_CHARS = 200
def profile_table(
path: Path, columns: list[DataColumn], notes: dict[str, str]
) -> tuple[dict[str, Any], list[list[Any]]]:
) -> tuple[TableProfile, list[list[Any]]]:
"""返回列概况和接口用的预览(前 PREVIEW_ROWS 行)"""
connection = connect({"t": path})
try:
rows = connection.execute("SELECT count(*) FROM t").fetchone()[0]
connection.execute("SUMMARIZE t")
fields = [column[0] for column in connection.description]
summary = {row[0]: dict(zip(fields, row)) for row in connection.fetchall()}
@@ -48,13 +48,12 @@ def profile_table(
).fetchall()
finally:
connection.close()
profile = {
"rows": rows,
"columns": profiled,
"sample": [
profile = TableProfile(
columns=profiled,
sample=[
[json_value(value, PROFILE_CELL_CHARS) for value in row] for row in sample
],
}
)
preview = [
[json_value(value, PREVIEW_CELL_CHARS) for value in row]
for row in head[:PREVIEW_ROWS]
@@ -92,25 +91,19 @@ def _profile_column(
head: list[tuple],
position: int,
note: str | None,
) -> dict[str, Any]:
item: dict[str, Any] = {"name": column.name, "type": column.type}
if column.format:
item["format"] = column.format
null_ratio = float(stats["null_percentage"]) / 100
item["null_ratio"] = round(null_ratio, 4)
# approx_unique 是估算值,小表上可能比行数还大
item["distinct"] = min(
stats["approx_unique"], round(stats["count"] * (1 - null_ratio))
)
) -> ColumnProfile:
item: dict[str, Any] = {}
if column.type == "number":
for key in ("min", "max", "avg", "q25", "q50", "q75"):
item[key] = _number(stats[key])
item = {
key: _number(stats[key])
for key in ("min", "max", "avg", "q25", "q50", "q75")
}
elif column.type in ("date", "datetime"):
# SUMMARIZE 的时间用空格分隔,和预览里的 ISO 写法统一
item["min"], item["max"] = (
None if stats[key] is None else stats[key].replace(" ", "T", 1)
item = {
key: None if stats[key] is None else stats[key].replace(" ", "T", 1)
for key in ("min", "max")
)
}
if (
column.type in ("text", "boolean")
and stats["approx_unique"] <= TOP_VALUES_MAX_DISTINCT
@@ -121,7 +114,7 @@ def _profile_column(
f"GROUP BY 1 ORDER BY n DESC, 1 LIMIT {TOP_VALUES}"
).fetchall()
item["top_values"] = [
{"value": json_value(value, PROFILE_CELL_CHARS), "count": count}
TopValue(value=json_value(value, PROFILE_CELL_CHARS), count=count)
for value, count in counts
]
examples: list[Any] = []
@@ -131,10 +124,16 @@ def _profile_column(
examples.append(value)
if len(examples) == EXAMPLES:
break
item["examples"] = examples
if note:
item["note"] = note
return item
null_ratio = float(stats["null_percentage"]) / 100
return ColumnProfile(
**column.model_dump(),
null_ratio=round(null_ratio, 4),
# approx_unique 是估算值,小表上可能比行数还大
distinct=min(stats["approx_unique"], round(stats["count"] * (1 - null_ratio))),
examples=examples,
note=note,
**item,
)
def _number(text: str | None) -> int | float | None:
@@ -144,6 +143,6 @@ def _number(text: str | None) -> int | float | None:
value = float(text)
if not math.isfinite(value):
return None
if value.is_integer() and abs(value) < 2**53:
if value.is_integer() and abs(value) < EXACT_FLOAT_INT:
return int(value)
return round(value, 6)
+5 -10
View File
@@ -19,7 +19,8 @@ from python_calamine import (
SheetVisibleEnum,
)
from app.datafiles.base import MAX_TABLE_ROWS, DataFileError, rows_exceeded
from app.datafiles.base import MAX_TABLE_ROWS, DataFileError, brief, rows_exceeded
from app.datafiles.columns import as_text
from app.schemas.data_file import ParseWarning
# 原始网格比数据多出的标题、表头、空行,读取时先粗略拦住明显超限的文件,精确的行数在拆表后检查
@@ -153,7 +154,7 @@ def read_jsonl(text: str) -> Records:
result.warnings.append(
ParseWarning(
code="bad_lines_skipped",
message=f"跳过了 {len(bad)} 行无法解析的内容:{_line_list(bad)}",
message=f"跳过了 {len(bad)} 行无法解析的内容:{brief([f'第 {n} 行' for n in bad])}",
)
)
return result
@@ -230,11 +231,5 @@ def _flatten(record: dict, prefix: str, level: int, out: dict[str, Any]) -> None
def _scalar(value: Any) -> Any:
if isinstance(value, (dict, list)):
return json.dumps(value, ensure_ascii=False)
return value
def _line_list(numbers: list[int]) -> str:
shown = "、".join(f"第 {number} 行" for number in numbers[:5])
return shown + ("等" if len(numbers) > 5 else "")
# 嵌套的对象、数组存成 JSON 字符串,其余原样交给类型推断
return as_text(value) if isinstance(value, (dict, list)) else value
+66 -112
View File
@@ -14,12 +14,11 @@ from pathlib import Path
from typing import BinaryIO
from uuid import uuid4
import duckdb
from loguru import logger
from app.config import PROJECT_ROOT, settings
from app.core.exceptions import BizException
from app.datafiles.aggregate import build_aggregate_sql
from app.datafiles.aggregate import run_aggregate
from app.datafiles.insights import (
INSIGHTS_CONCURRENCY,
INSIGHTS_TIMEOUT,
@@ -27,9 +26,8 @@ from app.datafiles.insights import (
)
from app.datafiles.parse import ParsedFile, ParsedTable
from app.datafiles.profile import read_rows
from app.datafiles.query import QueryError, run_query
from app.datafiles.storage import SOURCE_NAME, DataFileStore, file_dir
from app.schemas.base import JsonObject
from app.datafiles.query import QueryError
from app.datafiles.storage import SOURCE_NAME, DataFileStore, table_path
from app.schemas.data_file import (
AggregateRequest,
AggregateResult,
@@ -37,8 +35,6 @@ from app.schemas.data_file import (
DataTable,
DataTableRows,
FileInsights,
RequestDataFile,
RequestDataTable,
)
from app.services.conversation import ConversationStore
@@ -75,14 +71,18 @@ class DataFileService:
self._conversations = conversations
self._ttl = timedelta(seconds=ttl or settings.data_file_ttl)
self._parsing = asyncio.Semaphore(PARSE_CONCURRENCY)
# 文件数检查、分配表名和写入记录要一起完成,并发上传时才不会超限或重名;单实例部署,进程内的锁就够了
# 文件数检查和写入记录要一起完成,并发上传时才不会超限;单实例部署,进程内的锁就够了
self._saving = asyncio.Lock()
# 上传后的 LLM 分析;为空表示不分析,文件的 insights 为空
self._insights = insights
self._insight_slots = asyncio.Semaphore(INSIGHTS_CONCURRENCY)
# 正在本进程里分析的文件。记录里是 pending 却不在这里,说明进程重启过、任务已丢失
# 本进程里正在分析的文件,用来拒绝重复的重新分析
self._analysing: set[str] = set()
self._tasks: set[asyncio.Task] = set()
# 在这之前开始、记录里仍是 pending 的分析属于上一个进程,已随重启丢失;
# MongoDB 里的时间只精确到毫秒,这里也截到毫秒,刚启动就开始的分析读回后才不会早于它
now = datetime.now(UTC)
self._started_at = now.replace(microsecond=now.microsecond // 1000 * 1000)
async def upload(
self, user_id: int, conversation_id: str, name: str | None, source: BinaryIO
@@ -91,14 +91,16 @@ class DataFileService:
# 先粗查一次,满了就不必上传和解析;写入前在锁里再查一次
_check_count(await self.store.find(conversation_id))
file_id = f"f_{uuid4().hex}"
directory = file_dir(self.root, file_id)
directory = self.root / file_id
try:
size, sha256 = await asyncio.to_thread(self._save, source, directory)
async with self._parsing:
parsed = await _parse(directory)
async with self._saving:
existing = await self.store.find(conversation_id, include_deleted=True)
_check_count([record for record in existing if not record.deleted])
_check_count(await self.store.find(conversation_id))
first_number = await self.store.reserve_table_numbers(
conversation_id, len(parsed.tables)
)
record = self._record(
file_id,
user_id,
@@ -107,18 +109,11 @@ class DataFileService:
size,
sha256,
parsed,
_next_table_number(existing),
first_number,
)
if self._insights is not None:
# 先登记再写入,别的请求读到 pending 时不会把它当成丢失的任务
self._analysing.add(file_id)
record = record.model_copy(
update={"insights": FileInsights(status="pending")}
)
await self.store.insert(record)
except BaseException:
# 失败的上传不留文件,会话内的文件数不变
self._analysing.discard(file_id)
await asyncio.to_thread(shutil.rmtree, directory, ignore_errors=True)
raise
if self._insights is not None:
@@ -137,9 +132,7 @@ class DataFileService:
await self._check_conversation(conversation_id, user_id)
records = await self.store.find(conversation_id)
return [
await self._settle(record)
for record in records
if record.owner_id == user_id
self._settle(record) for record in records if record.owner_id == user_id
]
async def get_file(self, user_id: int, file_id: str) -> DataFileRecord:
@@ -147,7 +140,7 @@ class DataFileService:
# 他人的文件与不存在同样返回 404
if record is None or record.owner_id != user_id:
raise BizException(404, NOT_FOUND)
return await self._settle(record)
return self._settle(record)
async def regenerate_insights(self, user_id: int, file_id: str) -> DataFileRecord:
"""重新分析,用于上次失败之后;正在分析时 409"""
@@ -157,7 +150,7 @@ class DataFileService:
if file_id in self._analysing:
raise BizException(409, "正在分析,请稍后")
self._analysing.add(file_id)
pending = FileInsights(status="pending")
pending = FileInsights(status="pending", started_at=datetime.now(UTC))
try:
await self.store.update_insights(file_id, pending)
except BaseException:
@@ -179,19 +172,12 @@ class DataFileService:
) -> DataTableRows:
"""表的一页数据;表或排序列不存在时 404 / 422,文件已被清理时同样 404"""
record = await self.get_file(user_id, file_id)
table = next((item for item in record.tables if item.table == table_name), None)
if table is None:
raise BizException(404, "数据表不存在")
table, path = self._table(record, table_name)
if sort_by is not None and sort_by not in {c.name for c in table.columns}:
raise BizException(422, f"排序列不存在:{sort_by}")
path = file_dir(self.root, file_id) / table.parquet
try:
rows = await asyncio.to_thread(
read_rows, path, offset, limit, sort_by, descending
)
except duckdb.IOException:
# 记录还在但 Parquet 已被删除(过期清理、删除时目录没删净)
raise BizException(404, NOT_FOUND) from None
rows = await asyncio.to_thread(
read_rows, path, offset, limit, sort_by, descending
)
return DataTableRows(total=table.rows, offset=offset, rows=rows)
async def aggregate(
@@ -199,81 +185,36 @@ class DataFileService:
) -> AggregateResult:
"""对一张表分组汇总,供前端做图表数据;和 agent 的 query_data 同一套只读沙箱"""
record = await self.get_file(user_id, file_id)
table = next((item for item in record.tables if item.table == table_name), None)
if table is None:
raise BizException(404, "数据表不存在")
sql, names = build_aggregate_sql(request, table.columns)
path = file_dir(self.root, file_id) / table.parquet
if not path.is_file():
raise BizException(404, NOT_FOUND)
table, path = self._table(record, table_name)
try:
result = await asyncio.to_thread(
run_query,
sql,
{"t": path},
timeout=settings.data_query_timeout,
max_rows=request.limit,
)
return await asyncio.to_thread(run_aggregate, path, request, table.columns)
except QueryError as error:
raise BizException(422, str(error)) from None
return AggregateResult(
columns=names,
rows=[dict(zip(names, row)) for row in result.rows],
truncated=result.truncated,
)
async def delete_file(self, user_id: int, file_id: str) -> None:
await self.get_file(user_id, file_id)
await self.store.mark_deleted(file_id)
# Windows 上正在查询的 Parquet 删不掉,留给定时清理
await asyncio.to_thread(
shutil.rmtree, file_dir(self.root, file_id), ignore_errors=True
)
await asyncio.to_thread(shutil.rmtree, self.root / file_id, ignore_errors=True)
async def request_files(
self, user_id: int, conversation_id: str, attachments: list[JsonObject]
) -> list[RequestDataFile]:
"""本次请求可用的文件,调用方已校验会话归属
self, user_id: int, conversation_id: str, attached: set[str]
) -> list[DataFileRecord]:
"""本次请求可用的文件:当前用户在本会话里未过期的文件,调用方已校验会话归属
attachments 里 kind 为 data_file 的引用必须是本会话未过期的文件,否则 404;其他种类不处理
attached 是本轮附件引用的文件,必须都在其中,否则 404
"""
records = [
record
for record in await self.store.find(conversation_id)
if record.owner_id == user_id
]
attached = set()
for item in attachments:
if item.get("kind") != "data_file":
continue
if not isinstance(file_id := item.get("file_id"), str):
raise BizException(422, "data_file 附件缺少 file_id")
attached.add(file_id)
if attached - {record.file_id for record in records}:
raise BizException(404, NOT_FOUND)
return [
RequestDataFile(
file_id=record.file_id,
name=record.name,
attached_this_turn=record.file_id in attached,
tables=[
RequestDataTable.model_validate(
{
**table.model_dump(),
"path": str(
file_dir(self.root, record.file_id) / table.parquet
),
}
)
for table in record.tables
],
warnings=record.warnings,
)
for record in records
]
return records
async def aclose(self) -> None:
"""应用退出时取消还在进行的分析,记录里留下的 pending 下次读取时会记为失败"""
"""应用退出时取消还在进行的分析,记录里留下的 pending 下次启动后读取时按失败返回"""
for task in list(self._tasks):
task.cancel()
await asyncio.gather(*self._tasks, return_exceptions=True)
@@ -293,6 +234,7 @@ class DataFileService:
await asyncio.sleep(SWEEP_INTERVAL)
def _start_insights(self, record: DataFileRecord) -> None:
self._analysing.add(record.file_id)
task = asyncio.create_task(self._analyse(record))
self._tasks.add(task)
task.add_done_callback(self._tasks.discard)
@@ -323,18 +265,32 @@ class DataFileService:
finally:
self._analysing.discard(record.file_id)
async def _settle(self, record: DataFileRecord) -> DataFileRecord:
"""pending 但本进程没有在分析(重启丢了任务),记为失败,免得前端一直等"""
def _settle(self, record: DataFileRecord) -> DataFileRecord:
"""服务启动前开始、仍是 pending 的分析已随重启丢失,按失败返回,免得前端一直等
只看记录本身,不写回存储:读到的记录可能已经过时,写回会覆盖刚完成的结果
"""
insights = record.insights
if (
insights is None
or insights.status != "pending"
or record.file_id in self._analysing
insights is not None
and insights.status == "pending"
and (insights.started_at is None or insights.started_at < self._started_at)
):
return record
failed = FileInsights(status="failed")
await self.store.update_insights(record.file_id, failed)
return record.model_copy(update={"insights": failed})
return record.model_copy(update={"insights": FileInsights(status="failed")})
return record
def _table(self, record: DataFileRecord, name: str) -> tuple[DataTable, Path]:
"""文件里的一张表和它的 Parquet
表不存在,或 Parquet 已被删除(删除时目录没删净、过期清理)时 404
"""
table = next((item for item in record.tables if item.table == name), None)
if table is None:
raise BizException(404, "数据表不存在")
path = table_path(self.root, record.file_id, table)
if not path.is_file():
raise BizException(404, NOT_FOUND)
return table, path
async def _check_conversation(self, conversation_id: str, user_id: int) -> None:
if not await self._conversations.exists(conversation_id, user_id):
@@ -348,7 +304,7 @@ class DataFileService:
while chunk := source.read(CHUNK_BYTES):
size += len(chunk)
if size > self.max_mb * 1024 * 1024:
raise BizException(413, f"文件不能超过 {self.max_mb} MB")
raise file_too_large(self.max_mb)
digest.update(chunk)
target.write(chunk)
return size, digest.hexdigest()
@@ -371,12 +327,7 @@ class DataFileService:
DataTable(
table=table_name,
label=_label(name, table),
sheet=table.sheet,
rows=table.rows,
columns=table.columns,
preview=table.preview,
profile=table.profile,
parquet=table.path.name,
**table.model_dump(exclude={"part", "warnings"}),
)
)
warnings.extend(
@@ -397,6 +348,11 @@ class DataFileService:
expires_at=now + self._ttl,
tables=tables,
warnings=warnings,
insights=(
None
if self._insights is None
else FileInsights(status="pending", started_at=now)
),
)
def _remove_orphans(self, live: set[str]) -> int:
@@ -466,6 +422,10 @@ def _python() -> tuple[str, dict[str, str] | None]:
return sys.executable, None
def file_too_large(max_mb: int) -> BizException:
return BizException(413, f"文件不能超过 {max_mb} MB")
def _check_count(records: list[DataFileRecord]) -> None:
if len(records) >= MAX_FILES_PER_CONVERSATION:
raise BizException(
@@ -473,12 +433,6 @@ def _check_count(records: list[DataFileRecord]) -> None:
)
def _next_table_number(records: list[DataFileRecord]) -> int:
"""表名在会话内递增,已删除文件的表名也不再使用"""
used = (int(table.table[1:]) for record in records for table in record.tables)
return max(used, default=0) + 1
def _clean_name(name: str | None) -> str:
# 有的浏览器会带上本地路径,只保留文件名
base = re.split(r"[\\/]", name or "")[-1].strip()
+34 -19
View File
@@ -2,6 +2,7 @@
目录结构是 DATA_FILE_DIR/<file_id>/,里面有原文件 source 和每张表的 1.parquet、2.parquet……
DuckDB 只能读本地文件,所以文件不进 MongoDB;单实例部署,本地磁盘就够了
会话内的表名 t1、t2……由每个会话一个的计数器分配,文件删除、过期后表名也不再使用
"""
from datetime import UTC, datetime
@@ -9,16 +10,16 @@ from pathlib import Path
from typing import Any, Protocol
from bson.codec_options import CodecOptions
from pymongo import ASCENDING
from pymongo import ASCENDING, ReturnDocument
from app.schemas.data_file import DataFileRecord, FileInsights
from app.schemas.data_file import DataFileRecord, DataTable, FileInsights
# 原文件不带扩展名:calamine 见到 .xls 等扩展名会按扩展名打开,用户的扩展名和内容不符时会失败
SOURCE_NAME = "source"
def file_dir(root: Path, file_id: str) -> Path:
return root / file_id
def table_path(root: Path, file_id: str, table: DataTable) -> Path:
return root / file_id / table.parquet
def _now() -> datetime:
@@ -34,10 +35,12 @@ class DataFileStore(Protocol):
"""未过期且未删除的记录"""
...
async def find(
self, conversation_id: str, *, include_deleted: bool = False
) -> list[DataFileRecord]:
"""会话内未过期的记录,按上传时间排列"""
async def find(self, conversation_id: str) -> list[DataFileRecord]:
"""会话内未过期且未删除的记录,按上传时间排列"""
...
async def reserve_table_numbers(self, conversation_id: str, count: int) -> int:
"""为会话预留 count 个连续的表号,返回第一个;表号从 1 开始,不会重复分配"""
...
async def mark_deleted(self, file_id: str) -> None: ...
@@ -54,6 +57,8 @@ class DataFileStore(Protocol):
class InMemoryDataFileStore:
def __init__(self) -> None:
self._records: dict[str, DataFileRecord] = {}
# 会话 → 已分配的最大表号
self._table_numbers: dict[str, int] = {}
def _purge_expired(self) -> None:
now = _now()
@@ -71,18 +76,20 @@ class InMemoryDataFileStore:
record = self._records.get(file_id)
return None if record is None or record.deleted else record
async def find(
self, conversation_id: str, *, include_deleted: bool = False
) -> list[DataFileRecord]:
async def find(self, conversation_id: str) -> list[DataFileRecord]:
self._purge_expired()
records = [
record
for record in self._records.values()
if record.conversation_id == conversation_id
and (include_deleted or not record.deleted)
if record.conversation_id == conversation_id and not record.deleted
]
return sorted(records, key=lambda record: record.created_at)
async def reserve_table_numbers(self, conversation_id: str, count: int) -> int:
first = self._table_numbers.get(conversation_id, 0) + 1
self._table_numbers[conversation_id] = first + count - 1
return first
async def mark_deleted(self, file_id: str) -> None:
if (record := self._records.get(file_id)) is not None:
self._records[file_id] = record.model_copy(update={"deleted": True})
@@ -101,6 +108,8 @@ class MongoDataFileStore:
# 读回的时间统一带 UTC 时区;集合名前缀用于测试隔离
options = CodecOptions(tz_aware=True, tzinfo=UTC)
self._files = db.get_collection(f"{prefix}data_files", codec_options=options)
# 每个会话一条:_id 是会话 ID,tables 是已分配的最大表号;会话一直保留,计数器也不过期
self._table_numbers = db.get_collection(f"{prefix}data_file_table_numbers")
async def ensure_indexes(self) -> None:
# 过期记录由 TTL 索引删除;TTL 每分钟才扫一次,查询时仍按 expires_at 过滤
@@ -118,15 +127,12 @@ class MongoDataFileStore:
)
return None if document is None else _record(document)
async def find(
self, conversation_id: str, *, include_deleted: bool = False
) -> list[DataFileRecord]:
query: dict[str, Any] = {
async def find(self, conversation_id: str) -> list[DataFileRecord]:
query = {
"conversation_id": conversation_id,
"deleted": False,
"expires_at": {"$gt": _now()},
}
if not include_deleted:
query["deleted"] = False
documents = await (
self._files.find(query)
.sort([("created_at", ASCENDING), ("_id", ASCENDING)])
@@ -134,6 +140,15 @@ class MongoDataFileStore:
)
return [_record(document) for document in documents]
async def reserve_table_numbers(self, conversation_id: str, count: int) -> int:
document = await self._table_numbers.find_one_and_update(
{"_id": conversation_id},
{"$inc": {"tables": count}},
upsert=True,
return_document=ReturnDocument.AFTER,
)
return document["tables"] - count + 1
async def mark_deleted(self, file_id: str) -> None:
await self._files.update_one({"_id": file_id}, {"$set": {"deleted": True}})
+5 -7
View File
@@ -8,8 +8,8 @@ import re
from dataclasses import dataclass, field
from typing import Any
from app.datafiles.base import MAX_TABLE_ROWS, rows_exceeded, where
from app.datafiles.columns import classify, label_text
from app.datafiles.base import MAX_TABLE_ROWS, brief, rows_exceeded, where
from app.datafiles.columns import as_text, classify
from app.datafiles.readers import Grid
from app.schemas.data_file import ParseWarning
@@ -209,9 +209,7 @@ def _finish(rows: list[list[Any]], piece: _Piece, sheet: str | None) -> RawTable
totals = [index for index, row in data if _is_total(row)]
if totals:
data = [(index, row) for index, row in data if not _is_total(row)]
listed = "、".join(str(index + 1) for index in totals[:5]) + (
"等" if len(totals) > 5 else ""
)
listed = brief([str(index + 1) for index in totals])
warnings.append(
ParseWarning(
code="total_rows_removed",
@@ -250,7 +248,7 @@ def _merge_header(top: list[Any], sub: list[Any]) -> list[str]:
for upper, lower in zip(top, sub):
if upper is not None:
carry = upper
parts = [label_text(part) for part in (carry, lower) if part is not None]
parts = [as_text(part) for part in (carry, lower) if part is not None]
merged.append("-".join(parts))
return merged
@@ -280,7 +278,7 @@ def _quote(row: list[Any]) -> str:
value = next((value for value in row if value is not None), None)
if value is None:
return ""
text = label_text(value)
text = as_text(value)
if len(text) > QUOTE_CHARS:
text = text[:QUOTE_CHARS] + "…"
return f"「{text}」"
+3
View File
@@ -8,6 +8,7 @@ from loguru import logger
from app.api.agent import router
from app.api.conversations import router as conversation_router
from app.api.files import UploadSizeLimit
from app.api.files import limits_router as file_limits_router
from app.api.files import router as file_router
from app.api.materials import router as material_router
@@ -98,6 +99,8 @@ def create_app() -> FastAPI:
# 上传限制无需登录;要先于 /files/{file_id} 注册,否则会被当成文件 ID
application.include_router(file_limits_router, prefix="/api")
application.include_router(file_router, prefix="/api", dependencies=authenticated)
# 上传在读请求体之前先按 Content-Length 检查大小
application.add_middleware(UploadSizeLimit, path=f"/api{file_router.prefix}")
application.include_router(material_router, prefix="/api")
return application
+10 -3
View File
@@ -55,14 +55,21 @@ def flush_tracing() -> None:
logger.opt(exception=exc).warning("Langfuse flush 失败")
async def astream_screen(graph, payload, *, thread_id, session_id=None, user_id=None):
"""同一轮流保持同一个追踪上下文,关闭流时结束追踪"""
async def astream_screen(
graph, payload, *, thread_id, session_id=None, user_id=None, context=None
):
"""同一轮流保持同一个追踪上下文,关闭流时结束追踪;context 是图的运行上下文,不进检查点"""
from contextlib import aclosing
result = {}
with _screen_trace(payload, thread_id, session_id, user_id) as (config, root):
async with aclosing(
graph.astream(payload, config=config, stream_mode=["custom", "values"])
graph.astream(
payload,
config=config,
context=context,
stream_mode=["custom", "values"],
)
) as events:
async for mode, data in events:
if mode == "values":
+2 -2
View File
@@ -11,7 +11,7 @@ from app.processor.nodes.intent_node import IntentNode
from app.processor.nodes.qa_node import QANode
from app.processor.nodes.screen_agent_node import ScreenAgentNode
from app.processor.nodes.wait_for_user_node import WaitForUserNode
from app.processor.state import QueryState
from app.processor.state import QueryState, RunContext
def build_checkpoint_serde() -> JsonPlusSerializer:
@@ -47,7 +47,7 @@ def route_after_wait(state: QueryState) -> str:
def build_graph(checkpointer=None):
workflow = StateGraph(QueryState)
workflow = StateGraph(QueryState, context_schema=RunContext)
nodes = {
"input_node": InputNode(),
"intent_node": IntentNode(),
+2 -3
View File
@@ -10,11 +10,10 @@ from langchain_core.messages import AIMessageChunk, HumanMessage
from langchain_core.output_parsers import StrOutputParser
from langgraph.config import get_stream_writer
from app.agent.data_tools import DataContext
from app.agent.qa_agent import QAContext, get_qa_agent
from app.processor.base import BaseNode
from app.processor.history import history_messages
from app.processor.state import QueryState
from app.processor.state import QueryState, run_data
from app.processor.summary import data_file_summary
# 模型在一次回答里分几次输出文字(例如查询前后各说一段)时,段落之间空一行
@@ -56,7 +55,7 @@ class QANode(BaseNode):
HumanMessage(content=json.dumps(payload, ensure_ascii=False)),
]
},
context=QAContext(data=DataContext(tuple(context.data_files))),
context=QAContext(data=run_data()),
stream_mode="messages",
):
# 工具结果、工具调用和中间件插入的消息都不推送
+2 -3
View File
@@ -7,12 +7,11 @@ import json
from langchain_core.messages import HumanMessage
from app.agent.data_tools import DataContext
from app.agent.screen_agent import AgentReply, get_screen_agent
from app.agent.tools import ScreenAgentContext
from app.processor.base import BaseNode
from app.processor.history import history_messages
from app.processor.state import QueryState
from app.processor.state import QueryState, run_data
from app.processor.summary import request_summary
from app.resources.component import get_catalog_cache
@@ -68,7 +67,7 @@ class ScreenAgentNode(BaseNode):
context=ScreenAgentContext(
screen=context.screen,
catalog=catalog,
data=DataContext(tuple(context.data_files)),
data=run_data(),
),
)
if result.get("structured_response") is None:
+22
View File
@@ -1,5 +1,9 @@
from dataclasses import dataclass, field
from typing import Literal, NotRequired, TypedDict
from langgraph.runtime import get_runtime
from app.agent.data_tools import DataContext
from app.schemas.actions import Action
from app.schemas.base import JsonObject
from app.schemas.clarification import Clarification
@@ -25,3 +29,21 @@ class QueryState(TypedDict):
status: NotRequired[
Literal["running", "waiting_for_input", "completed", "cancelled", "failed"]
] # 后端处理、等待补充、处理完成、用户取消或失败,完成不代表前端已执行
@dataclass(frozen=True)
class RunContext:
"""图的运行上下文:本次运行要用、但不进检查点的依赖,每次启动和恢复时由调用方传入"""
# 本会话的数据文件;状态里的 input_context.data_files 只有摘要,列概况和路径在这里
data: DataContext = field(default_factory=DataContext)
def run_data() -> DataContext:
"""当前运行可用的数据表;单独调用节点(不在图里执行)或调用方没传 context 时为空"""
try:
runtime = get_runtime(RunContext)
except RuntimeError:
return DataContext()
context = runtime.context if runtime is not None else None
return context.data if context is not None else DataContext()
+43 -12
View File
@@ -44,6 +44,41 @@ class ParseWarning(BaseModel):
message: str
class TopValue(BaseModel):
value: JsonValue
count: int
class ColumnProfile(DataColumn):
"""一列的概况,上传时在全表上算出;不适用的统计为空,交给模型时省略"""
null_ratio: float
# 去重值个数,是估算值
distinct: int
# 数值列是数字,日期、日期时间列是 ISO 写法的字符串
min: int | float | str | None = None
max: int | float | str | None = None
# 只有数值列有
avg: int | float | None = None
q25: int | float | None = None
q50: int | float | None = None
q75: int | float | None = None
# 去重值不多的文本、布尔列才有,按出现次数从多到少
top_values: list[TopValue] | None = None
# 开头几行里不同的取值
examples: list[JsonValue]
# 保留为文本的原因等说明
note: str | None = None
class TableProfile(BaseModel):
"""表的列概况,给 describe_data 和上传后的分析用"""
columns: list[ColumnProfile]
# 随机抽的几行,顺序与 columns 一致
sample: list[list[JsonValue]]
class DataTableInfo(BaseModel):
# 会话内的表名 t1、t2……,模型写 SQL 时用
table: str
@@ -60,8 +95,7 @@ class DataTableDetail(DataTableInfo):
class DataTable(DataTableDetail):
# 列概况,给 describe_data 用
profile: dict[str, JsonValue]
profile: TableProfile
# 文件目录下的 Parquet 文件名
parquet: str
@@ -162,6 +196,8 @@ class FileInsights(BaseModel):
version: int = 1
# pending:正在分析;ready:已完成(推荐可能为空);failed:分析失败,文件本身可用
status: Literal["pending", "ready", "failed"]
# pending 时是开始分析的时间;服务启动前开始、至今仍是 pending 的分析已随重启丢失,读取时按失败返回
started_at: datetime | None = None
summary: str = ""
suggestions: list[ChartSuggestion] = Field(default_factory=list)
columns: list[ColumnInsight] = Field(default_factory=list)
@@ -224,19 +260,14 @@ class DataFileLimits(BaseModel):
aggregate_max_rows: int
class RequestDataTable(DataTableInfo):
"""本次请求可用的表:多出工具要用的列概况和 Parquet 路径,不带预览"""
profile: dict[str, JsonValue]
path: str
class RequestDataFile(BaseModel):
"""本次请求可用的文件:服务端按会话读取后放进请求,前端传的同名字段会被覆盖"""
"""本次请求可用的文件:服务端按会话读取后放进请求,前端传的同名字段会被覆盖
请求会进检查点,所以只放表名、行数和列;列概况和文件路径在图的运行上下文里,见 processor/state.py
"""
file_id: str
name: str
# 本轮消息的 attachments 里带了这个文件,通常是刚上传的
attached_this_turn: bool
tables: list[RequestDataTable]
warnings: list[ParseWarning]
tables: list[DataTableInfo]
+20 -1
View File
@@ -1,6 +1,6 @@
"""前端设计请求:原始需求、当前大屏及可选补充上下文"""
from pydantic import Field
from pydantic import Field, field_validator
from .base import ExtensibleModel, JsonObject, NonBlankString
from .screen import Screen
@@ -20,3 +20,22 @@ class DesignRequest(ExtensibleModel):
# 本条消息附带的材料;{"kind": "data_file", "file_id": "..."} 引用本会话上传的数据文件,
# 其他种类只原样进入摘要,不读取文件或远程资源
attachments: list[JsonObject] = Field(default_factory=list)
@field_validator("attachments")
@classmethod
def _data_files_have_ids(cls, value: list[JsonObject]) -> list[JsonObject]:
for item in value:
if item.get("kind") == "data_file" and not isinstance(
item.get("file_id"), str
):
raise ValueError("data_file 附件缺少 file_id")
return value
@property
def data_file_ids(self) -> set[str]:
"""本条消息附带的数据文件"""
return {
str(item["file_id"])
for item in self.attachments
if item.get("kind") == "data_file"
}
+27 -4
View File
@@ -7,13 +7,16 @@ from uuid import uuid4
from langgraph.types import Command
from loguru import logger
from app.agent.data_tools import DataContext
from app.config import settings
from app.core.exceptions import BizException
from app.datafiles.service import DataFileService
from app.observability.tracing import astream_screen
from app.processor.history import trim_history
from app.processor.state import RunContext
from app.schemas.agent import AgentResult, ResumeRequest
from app.schemas.conversation import Turn
from app.schemas.data_file import DataFileRecord, RequestDataFile
from app.schemas.request import DesignRequest
from app.services.conversation import ConversationStore
@@ -43,8 +46,9 @@ class AgentService:
conversation_id, settings.conversation_history_turns
)
# 附件引用的文件不属于本会话时在流开始前返回 404
data_files = await self.data_files.request_files(
user_id, conversation_id, request.attachments
attached = request.data_file_ids
records = await self.data_files.request_files(
user_id, conversation_id, attached
)
except BaseException:
self.release(thread_id)
@@ -64,7 +68,16 @@ class AgentService:
settings.history_max_tokens,
)
# 同样只信任服务端读取的结果;会话内的文件每一轮都可用,不附带也能查询
payload["data_files"] = [item.model_dump(mode="json") for item in data_files]
# 请求会进检查点,只放摘要;工具要用的列概况和路径通过运行上下文传给图
payload["data_files"] = [
RequestDataFile(
file_id=record.file_id,
name=record.name,
attached_this_turn=record.file_id in attached,
tables=record.tables,
).model_dump(mode="json")
for record in records
]
return (
thread_id,
@@ -76,6 +89,7 @@ class AgentService:
},
conversation_id,
user_id,
self._run_context(records),
)
async def prepare_resume(self, request: ResumeRequest, user_id: int):
@@ -117,6 +131,10 @@ class AgentService:
)
}
)
# 运行上下文不在检查点里,恢复时按会话重新读取;期间删除或过期的文件工具查不到
records = await self.data_files.request_files(
user_id, conversation_id, set()
)
# 每次有效补充或取消生成新的输入 ID,任务和会话保持不变
return (
@@ -127,11 +145,15 @@ class AgentService:
),
conversation_id,
user_id,
self._run_context(records),
)
except BaseException:
self.release(thread_id)
raise
def _run_context(self, records: list[DataFileRecord]) -> RunContext:
return RunContext(data=DataContext(tuple(records), self.data_files.root))
def release(self, thread_id):
self._active.discard(thread_id)
self._conversation_of.pop(thread_id, None)
@@ -199,7 +221,7 @@ class AgentService:
clarification=state.get("clarification") if waiting else None,
)
async def stream(self, thread_id, payload, session_id, user_id=None):
async def stream(self, thread_id, payload, session_id, user_id=None, context=None):
"""消费图事件,完整状态只用于整理最终结果,不直接暴露给客户端"""
state = None
with logger.contextualize(thread_id=thread_id):
@@ -210,6 +232,7 @@ class AgentService:
thread_id=thread_id,
session_id=session_id,
user_id=user_id,
context=context,
)
) as events:
async for mode, data in events: