Files
NexQuant/rdagent/log/ui/llm_st.py
T
you-n-g f78175b37a feat: refactor for general data science (#498)
* refine ds modal for more cases: eval and es

* update model template

* prompts for model and ensemble

* fix a bug

* fix a bug

* init: ds workflow evovingstrategy

* Adding ensemble (#505)

* Initial Draft

* Updating logic for init

* Revising

* Successful Testing

* Updating to use the latest & right class

* bug: bug-fixing for testing

* data science loop changes

* data science loop base

* ds loop feedback

* fix

* remove measure_time because it's duplicated (in LoopBase)

* add the knowledge query for data_loader & feature

* edit ds workflow evaluator

* data_loader bug fix

* stop evolving when all tasks completed

* llm app change

* fix break all complete strategy

* Adding queried knowledge (#508)

Co-authored-by: XianBW <36835909+XianBW@users.noreply.github.com>

* fix loop bug

* ds workflow evaluator; test; refine prompts

* workflow spec

* fix ci

* feature task changes

* ds loop change

* fix a bug in feat

* add query knowledge for model and workflow

* llm_debug info(for show) using pickle instead of json

* remove NextLoopException

* loop change

* coder raise CoderError when all sub_tasks failed

* rename code_dict to file_dict in FBWorkspace

* add CoSTEER unittest

* now show self.version in Task.get_task_information(), simplify CoSTEER sub tasks definition

* remove some properties in ModelTask, add model_type in it.

* fix llm app bug

* llm web app bug fix

* ds loop bug fix

* fix: give component code to feature&ens eval

* loop catch error bug

* rename load_from_raw_data to load_data

* feat: Add debug data creation functionality for data science scenarios

* support local folder (#511)

* support local folder

* remove unnecessary random

* KaggleScen Subclass

* small fix

* use template for style description

* update default scen to kaggle

* update sample data script

* make sure frac < 1

* fix a bug

* feature spec changes

* fix

* changeimport order

* clear unnecessary std outputs

* fix a typo

* create sample folder after unzip kaggle data

* feature/model test script update

* Align the data types across modules.

* fix a bug in model eval

* show line number

* move sample entry point to app

* spec & model prompt changes

* Refine the competition specification to address the data type problem and the coherence issue.

* fix some bugs

* add file filter in FBworkspace.code property

* support non-binary prediction

* avoid too much warnings

* fix a bug in ensemble module

* filtered the knowledge query in all modules

* delete RAG in idea proposal

* refine the code in ensemble

* show exp workspace in llm_st

* exp_gen bug fix

* feedback bug fix

* use `feature` instead of `feat01`

* Trace & method of judging if exp is completed change

* fix a bug in package calling and execute ci

* fix code

* bug fix

* bug fix

* fix a bug

* fix some bugs

* fix a bug

* refactor: Enhance error handling and feedback in data science loop

* support different use_azure on chat and embedding models

* multi-model proposal logic

* fix a small syntax error

* loopBase and some changes

* ensemble scores change

* fbworkspace.code -> .all_codes

* use all model codes in workflow coder

* check scores.csv's keys(model_names)

* model name changes

* add a todo in  ensemble test

* sota_exp changes

* give model info in exp gen

* add runner time limit

* config using debug data or not in evals

* exp to feedback base

* add feature code when writing model task

* small problem

* copying during sampling

* update

* refactor: Simplify code handling and improve workspace management

* model part output fix

* print model's execution time

* bug fix

* ensemble test fix

* ens small change

* ens_test bug fix

* Refine partial expansion logic to display only a few subfolders when their structure is uniform, improving readability in nested directories.

* several update on prompts

* sample subfolders

* Filter the stdout after code execution to remove irrelevant information e.g. progress bars, whitespace characters, excessive line breaks.

* Add some more prompts and comments

* several update on the first init rounds

* model timeout as error

* fix pattern of getting model codes in workspace

* small bux fix on model prompts

* remove get_code_with_key since we have regex pattern

* fix: Correct tqdm progress bar update logic in LoopBase class

* feat: Add diff generation and enhance feedback mechanism in data science loop

* update some fix to model and workflow prompts

* refine the logic of progress bar filter

* add last_successful_exp in exp_gen

* fix a one line bug

* add a hint in prompt

* fix data sample for bms

* fix data sample for bms

* hypothesis small fix

* crawler readme update

* fix component gen

* fix bug

* annotation change

* load description.md if it exists

* refactor: Simplify SOTA description handling in feedback and prompts

* refactor: Use shared templates for feedback and experiment descriptions

* change webapp for model codes changes

* update proposal

* add timeout message for docker run output

* fix

* refine the code in docker time processing

* use .shape instead of len() when do shape eval

* won't change size during iteration

* support bson sample

* sample support jsonl and bson

* add former_code to coder prompts

* a little speed us in debug data creating

* filter progress bar when eval ens and main

* avoid costeer makes no change to former code

* fix several log error

* add timeout judge threshold

* fix some bugs in the evaluation of component output shapes

* File structure for supporting litellm (#517)

Co-authored-by: Young <afe.young@gmail.com>

* ignore submission and show processing

* ignore submission and show processing

* add efficiency notice

* refactor: Enhance error message with detailed feedback summary

* refactor: Simplify component handling in DSExpGen class

* refactor: Update code structure and add docstring for clarity

* reserve one sample to each label in data sampling

* add Evaluation info

* refine costeer code to avoid giving same code twice

* use raw_description as plain text

* add a prompt hint to avoid same dict key

* model task name bug in first model exp gen

* fix a typo

* add some debug info in costeer tests

* task init change

* enhance data sampling

* refine the code in data_loader

* more reasonable loop

* fix a bug in data folder description

* add error msg & traceback to execution feedback

* fix llm error msg detection

* add task information to costeer eval & add cache to docker run(use zipfile to store the whole workspace)

* fix CI first round

* fix CI second round

* use txt to store test script to avoid pytest

* remove zipfile in requirements

* add azure.identity to requirements

* ignore debug web page

* component test changes

* remove redundent task_desc in model coder

* feat: Add APE module and prompts for automated prompt engineering

* fix: Update .gitignore and improve text formatting in eval.py

* refactor: Update print output and improve code comments and imports

* style: Fix string formatting and import order in ape.py and fmt.py

* exclude ape

* add a data folder notice

* reduce unnecessary output to stdout

* refine the code of describe_data_folder

* fix ci

* style: streamlit style update (#522)

* streamlit style update

* fix import

* fix format

* fix llm_st loop progress bar

* debugapp small change

* fix model str

* refine some prompts

* fix model str

* fix CI

* refine the logic associated with the data_folder

* fix ci

* small change

* set filter_progress_bar as default in execute

* model proposal with workflow

* add submission check in workflow eval

* fix bug

* small change

* fix CI

* fix CI

* refactor: Move generate_diff to utils and update DSExpGen logic

* more reasonable prompt describing metric direction

* fix a minor jinja2 bug

* quick fix exp_gen bugs

* fix the following bug

* fix

* fix some bugs

* remove workflow from model

* add pending_tasks_list in data science to enable coding model and workflow

* refine the code for handling JSON-formatted data descriptions

* assert with information

* ensure correct csv file name

* add logging to help record the output

* log competition

* add log tag for debug llm app

* test: Test ds refactor ll (#523)

* fix bugs to former scenario

* fix a bug because coding in rdloop changed

* fix the bug when feedback gets no hypothesis

* fix trace structure

* change all trace hist when merging hypothesis to experiments

* ignore some error in ruff

* fix kaggle scenario bugs

* refine one line

* another bug

* another small bug

* fix ui bugs

* chage kaggle  train.py path

---------

Co-authored-by: Xu Yang <peteryang@vip.qq.com>

* fix CI

* Update rdagent/app/data_science/loop.py

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* add samplecsv into spec prompts

* fix CI

---------

Co-authored-by: TPLin22 <tplin2@163.com>
Co-authored-by: yuanteli <1957922024@qq.com>
Co-authored-by: Xisen Wang <118058822+xisen-w@users.noreply.github.com>
Co-authored-by: Bowen Xian <xianbowen@outlook.com>
Co-authored-by: Xu Yang <peteryang@vip.qq.com>
Co-authored-by: XianBW <36835909+XianBW@users.noreply.github.com>
Co-authored-by: Tim <illking@foxmail.com>
Co-authored-by: 炼金术师华华 <37462254+YeewahChan@users.noreply.github.com>
Co-authored-by: Linlang <30293408+SunsetWolf@users.noreply.github.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
2025-01-17 22:53:05 +08:00

254 lines
8.9 KiB
Python

import argparse
import json
import pickle
import re
import time
from pathlib import Path
import streamlit as st
from streamlit import session_state
st.set_page_config(layout="wide", page_title="debug_llm", page_icon="🎓", initial_sidebar_state="expanded")
# 获取 log_path 参数
parser = argparse.ArgumentParser(description="RD-Agent Streamlit App")
parser.add_argument("--log_dir", type=str, help="Path to the log directory")
args = parser.parse_args()
@st.cache_data
def get_folders_sorted(log_path):
"""缓存并返回排序后的文件夹列表,并加入进度打印"""
with st.spinner("正在加载文件夹列表..."):
folders = sorted(
(folder for folder in log_path.iterdir() if folder.is_dir() and list(folder.iterdir())),
key=lambda folder: folder.stat().st_mtime,
reverse=True,
)
st.write(f"找到 {len(folders)} 个文件夹")
return [folder.name for folder in folders]
# 设置主日志路径
main_log_path = Path(args.log_dir) if args.log_dir else Path("./log")
if not main_log_path.exists():
st.error(f"Log dir {main_log_path} does not exist!")
st.stop()
if "data" not in session_state:
session_state.data = []
if "log_path" not in session_state:
session_state.log_path = None
tlist = []
def load_data():
"""加载数据到 session_state 并显示进度"""
log_file = main_log_path / session_state.log_path / "debug_llm.pkl"
try:
with st.spinner(f"正在加载数据文件 {log_file}..."):
start_time = time.time()
with open(log_file, "rb") as f:
session_state.data = pickle.load(f)
st.success(f"数据加载完成!耗时 {time.time() - start_time:.2f} 秒")
st.session_state["current_loop"] = 1
except Exception as e:
session_state.data = [{"error": str(e)}]
st.error(f"加载数据失败: {e}")
# UI - Sidebar
with st.sidebar:
st.markdown(":blue[**Log Path**]")
manually = st.toggle("Manual Input")
if manually:
st.text_input("log path", key="log_path", label_visibility="collapsed")
else:
folders = get_folders_sorted(main_log_path)
st.selectbox(f"**Select from {main_log_path.absolute()}**", folders, key="log_path")
if st.button("Refresh Data"):
load_data()
st.rerun()
expand_all = st.toggle("Expand All", key="expand_all")
# Helper functions
def show_text(text, lang=None):
"""显示文本代码块"""
if lang:
st.code(text, language=lang, wrap_lines=True)
elif "\n" in text:
st.code(text, language="python", wrap_lines=True)
else:
st.code(text, language="html", wrap_lines=True)
def highlight_prompts_uri(uri):
"""高亮 URI 的格式"""
parts = uri.split(":")
return f"**{parts[0]}:**:green[**{parts[1]}**]"
def extract_loopid_func_name(tag):
"""提取 Loop ID 和函数名称"""
match = re.search(r"Loop_(\d+)\.(\w+)\.", tag)
return match.groups() if match else (None, None)
def extract_evoid(tag):
"""提取 EVO ID"""
match = re.search(r"\.evo_loop_(\d+)\.", tag)
return match.group(1) if match else None
# Display Data
progress_text = st.empty()
progress_bar = st.progress(0)
# 每页展示一个 Loop
LOOPS_PER_PAGE = 1
# 获取所有的 Loop ID
loop_groups = {}
for i, d in enumerate(session_state.data):
tag = d["tag"]
loop_id, _ = extract_loopid_func_name(tag)
if loop_id:
if loop_id not in loop_groups:
loop_groups[loop_id] = []
loop_groups[loop_id].append(d)
# 按 Loop ID 排序
sorted_loop_ids = sorted(loop_groups.keys(), key=int) # 假设 Loop ID 是数字
total_loops = len(sorted_loop_ids)
total_pages = total_loops # 每页展示一个 Loop
if total_pages:
# 初始化 current_loop
if "current_loop" not in st.session_state:
st.session_state["current_loop"] = 1
# Loop 导航按钮
col1, col2, col3, col4, col5 = st.sidebar.columns([1.2, 1, 2, 1, 1.2])
with col1:
if st.button("|<"): # 首页
st.session_state["current_loop"] = 1
with col2:
if st.button("<") and st.session_state["current_loop"] > 1: # 上一页
st.session_state["current_loop"] -= 1
with col3:
# 下拉列表显示所有 Loop
st.session_state["current_loop"] = st.selectbox(
"选择 Loop",
options=list(range(1, total_loops + 1)),
index=st.session_state["current_loop"] - 1, # 默认选中当前 Loop
label_visibility="collapsed", # 隐藏标签
)
with col4:
if st.button("\>") and st.session_state["current_loop"] < total_loops: # 下一页
st.session_state["current_loop"] += 1
with col5:
if st.button("\>|"): # 最后一页
st.session_state["current_loop"] = total_loops
# 获取当前 Loop
current_loop = st.session_state["current_loop"]
# 渲染当前 Loop 数据
loop_id = sorted_loop_ids[current_loop - 1]
progress_text = st.empty()
progress_text.text(f"正在处理 Loop {loop_id}...")
progress_bar.progress(current_loop / total_loops, text=f"Loop :green[**{current_loop}**] / {total_loops}")
# 渲染 Loop Header
loop_anchor = f"Loop_{loop_id}"
if loop_anchor not in tlist:
tlist.append(loop_anchor)
st.header(loop_anchor, anchor=loop_anchor, divider="blue")
# 渲染当前 Loop 的所有数据
loop_data = loop_groups[loop_id]
for d in loop_data:
tag = d["tag"]
obj = d["obj"]
_, func_name = extract_loopid_func_name(tag)
evo_id = extract_evoid(tag)
func_anchor = f"loop_{loop_id}.{func_name}"
if func_anchor not in tlist:
tlist.append(func_anchor)
st.header(f"in *{func_name}*", anchor=func_anchor, divider="green")
evo_anchor = f"loop_{loop_id}.evo_step_{evo_id}"
if evo_id and evo_anchor not in tlist:
tlist.append(evo_anchor)
st.subheader(f"evo_step_{evo_id}", anchor=evo_anchor, divider="orange")
# 根据 tag 渲染内容
if "debug_exp_gen" in tag:
with st.expander(
f"Exp in :violet[**{obj.experiment_workspace.workspace_path}**]", expanded=False, icon="🧩"
):
st.write(obj)
elif "debug_tpl" in tag:
uri = obj["uri"]
tpl = obj["template"]
cxt = obj["context"]
rd = obj["rendered"]
with st.expander(highlight_prompts_uri(uri), expanded=False, icon="⚙️"):
t1, t2, t3 = st.tabs([":green[**Rendered**]", ":blue[**Template**]", ":orange[**Context**]"])
with t1:
show_text(rd)
with t2:
show_text(tpl, lang="django")
with t3:
st.json(cxt)
elif "debug_llm" in tag:
system = obj.get("system", None)
user = obj["user"]
resp = obj["resp"]
with st.expander(f"**LLM**", expanded=False, icon="🤖"):
t1, t2, t3 = st.tabs([":green[**Response**]", ":blue[**User**]", ":orange[**System**]"])
with t1:
try:
rdict = json.loads(resp)
if "code" in rdict:
code = rdict["code"]
st.markdown(":red[**Code in response dict:**]")
st.code(code, language="python", wrap_lines=True, line_numbers=True)
rdict.pop("code")
elif "spec" in rdict:
spec = rdict["spec"]
st.markdown(":red[**Spec in response dict:**]")
st.markdown(spec)
rdict.pop("spec")
else:
# show model codes
showed_keys = []
for k, v in rdict.items():
if k.startswith("model_") and k.endswith(".py"):
st.markdown(f":red[**{k}**]")
st.code(v, language="python", wrap_lines=True, line_numbers=True)
showed_keys.append(k)
for k in showed_keys:
rdict.pop(k)
st.write(":red[**Other parts (except for the code or spec) in response dict:**]")
st.json(rdict)
except:
st.json(resp)
with t2:
show_text(user)
with t3:
show_text(system or "No system prompt available")
progress_text.text("当前 Loop 数据处理完成!")
# Sidebar TOC
with st.sidebar:
toc = "\n".join([f"- [{t}](#{t})" if t.startswith("L") else f" - [{t.split('.')[1]}](#{t})" for t in tlist])
st.markdown(toc, unsafe_allow_html=True)