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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) |