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import base64
import gzip
import io
import json
import traceback
import numpy as np
import pandas as pd
from sklearn.preprocessing import StandardScaler
import streamlit as st
from workflow.dataloading.dataloading_core import process_complex_data
from utils.sanitize_code import sanitize_code, to_json_serializable
def infer_load_data(agent) -> None:
uploaded_files = st.file_uploader(
"选择推理数据集",
accept_multiple_files=True,
help="拖拽或点击上传多个文件",
)
if uploaded_files:
try:
with st.spinner("正在处理数据..."):
big_df, dfs = process_complex_data(uploaded_files, agent)
if big_df is not None:
agent.save_inference_data(big_df)
st.success("导入并处理完成！")
except Exception as err:
st.error(f"导入失败：{err}")
def infer_execution(agent):
inference_df = agent.load_inference_processed_df()
edited_code = agent.load_inference_code()
try:
model_obj = agent.load_best_model()
exec_ns = {
"inference_df": inference_df,
'model_obj': model_obj,
"np": np,
"pd": pd,
"StandardScaler": StandardScaler
}
with st.spinner("正在进行推断分析..."):
exec(edited_code, exec_ns)
result_dict = exec_ns.get("result_dict")
if result_dict is None:
st.error("脚本未写入 `result_dict`。请确保编辑后的脚本在末尾赋值 result_dict。")
else:
art = result_dict.get('artifacts', {})
b64 = art.pop('predictions_df_b64', None)
if not art:
result_dict.pop('artifacts', None)
serializable = to_json_serializable(result_dict)
try:
result_json = json.dumps(serializable, ensure_ascii=False)
except Exception:
result_json = json.dumps(serializable, default=str, ensure_ascii=False)
with st.expander("推理结果", True):
if b64:
try:
gz_bytes = base64.b64decode(b64)
csv_bytes = gzip.decompress(gz_bytes)
df_pred = pd.read_csv(io.BytesIO(csv_bytes))
st.success("已加载带预测结果的 DataFrame")
st.dataframe(df_pred)
st.download_button(
label="下载带预测结果（predictions.csv）",
data=csv_bytes,
file_name="predictions.csv",
mime="text/csv"
)
except Exception as e:
st.error(f"解码 predictions_df 失败: {e}")
# 兜底：尝试从 records 字段恢复
records = result_dict.get('predictions_df_records')
if records:
try:
df_pred = pd.DataFrame(records)
st.dataframe(df_pred)
except Exception as e2:
st.error(f"从 records 恢复表格失败: {e2}")
except Exception as e:
st.error(f"推断失败：{e}")
st.text(traceback.format_exc())
agent.save_inference_error(traceback.format_exc())
raw = agent.code_generation_for_inference(agent.load_code(), inference_data.head(), auto=True)
code = sanitize_code(raw)
agent.save_inference_code(code) |