From e2b82111fec50c29ddc875e49dfe9f2e971e41c2 Mon Sep 17 00:00:00 2001 From: Bowen Xian Date: Fri, 2 Aug 2024 06:12:49 +0000 Subject: [PATCH] demo changes --- rdagent/log/ui/app.py | 109 +++++++++++++++++++++++------------------- 1 file changed, 60 insertions(+), 49 deletions(-) diff --git a/rdagent/log/ui/app.py b/rdagent/log/ui/app.py index 8bd30e6d8..610e62799 100644 --- a/rdagent/log/ui/app.py +++ b/rdagent/log/ui/app.py @@ -195,21 +195,28 @@ def evolving_feedback_window(wsf: FactorSingleFeedback | ModelCoderFeedback): st.markdown(wsf.value_feedback) -def display_hypotheses(hypotheses: dict[int, Hypothesis], decisions: dict[int, bool]): - shd = {k: v.__dict__ for k, v in hypotheses.items()} +def display_hypotheses(hypotheses: dict[int, Hypothesis], decisions: dict[int, bool], success_only: bool = False): + if success_only: + shd = {k: v.__dict__ for k, v in hypotheses.items() if decisions[k]} + else: + shd = {k: v.__dict__ for k, v in hypotheses.items()} df = pd.DataFrame(shd).T + if "reason" in df.columns: + df.drop(["reason"], axis=1, inplace=True) + df.columns = df.columns.map(lambda x: x.replace("_", " ").capitalize()) - def highlight_rows(row): + def style_rows(row): if decisions[row.name]: - return ['color: green; font-weight: bold;'] * len(row) - - def background_color_columns(col): - if col.name == 'hypothesis': - return ['background-color: lightgrey'] * len(col) + return ['color: green;'] * len(row) + return [''] * len(row) - st.dataframe(df.style.apply(highlight_rows, axis=1).apply(background_color_columns, axis=0)) + def style_columns(col): + if col.name != 'Hypothesis': + return ['font-style: italic;'] * len(col) + return ['font-weight: bold;'] * len(col) - st.markdown(df.style.apply(highlight_rows, axis=1).apply(background_color_columns, axis=0).to_html(), unsafe_allow_html=True) + # st.dataframe(df.style.apply(style_rows, axis=1).apply(style_columns, axis=0)) + st.markdown(df.style.apply(style_rows, axis=1).apply(style_columns, axis=0).to_html(), unsafe_allow_html=True) def metrics_window(df: pd.DataFrame, R: int, C: int, *, height: int = 300, colors: list[str] = None): @@ -219,7 +226,9 @@ def hypothesis_hover_text(h: Hypothesis, d: bool = False): text = h.hypothesis lines = textwrap.wrap(text, width=60) return f"{'
'.join(lines)}" - hover_texts = [hypothesis_hover_text(state.hypotheses[int(i[6:])], state.h_decisions[int(i[6:])]) for i in df.index] + hover_texts = [hypothesis_hover_text(state.hypotheses[int(i[6:])], state.h_decisions[int(i[6:])]) for i in df.index if i != "alpha158"] + if state.alpha158_metrics is not None: + hover_texts = ["Baseline: alpha158"] + hover_texts for ci, col in enumerate(df.columns): row = ci // C + 1 col_num = ci % C + 1 @@ -256,52 +265,41 @@ def summary_window(): with st.container(): # TODO: not fixed height with st.container(): - ac,bc,cc = st.columns([2,1,2], vertical_alignment="center") - with ac: - st.subheader("Hypotheses🏅", anchor="_hypotheses") + bc,cc = st.columns([2,2], vertical_alignment="center") with bc: st.subheader("Metrics📈", anchor="_metrics") with cc: show_true_only = st.toggle("successful hypotheses", value=False) - hypotheses_c, chart_c = st.columns([2, 3]) - with hypotheses_c: - with st.container(height=700): - h_strs = [] - for id, h in state.hypotheses.items(): - if state.h_decisions[id]: - h_strs.append(f"{id}. :green[**{h.hypothesis}**]\n\t>:green-background[*{h.__dict__.get('concise_reason', '')}*]") - else: - h_strs.append(f"{id}. {h.hypothesis}\n\t>*{h.__dict__.get('concise_reason', '')}*") + # hypotheses_c, chart_c = st.columns([2, 3]) + chart_c = st.container() + hypotheses_c = st.container() - if hasattr(h, "concise_observation"): - h_strs[-1] += f"\n\n\t>:blue[**Observation**]: {h.concise_observation}" - h_strs[-1] += f"\n\n\t>:blue[**Justification**]: {h.concise_justification}" - h_strs[-1] += f"\n\n\t>:blue[**Knowledge**]: {h.concise_knowledge}" - st.markdown("\n".join(h_strs)) + with hypotheses_c: + st.subheader("Hypotheses🏅", anchor="_hypotheses") + display_hypotheses(state.hypotheses, state.h_decisions, show_true_only) with chart_c: - with st.container(height=700): - if state.log_type == "qlib_factor": - df = pd.DataFrame([state.alpha158_metrics] + state.metric_series) + if state.log_type == "qlib_factor": + df = pd.DataFrame([state.alpha158_metrics] + state.metric_series) + else: + df = pd.DataFrame(state.metric_series) + if show_true_only and len(state.hypotheses) >= len(state.metric_series): + if state.alpha158_metrics is not None: + selected = ["alpha158"] + [i for i in df.index if state.h_decisions[int(i[6:])]] else: - df = pd.DataFrame(state.metric_series) - if show_true_only and len(state.hypotheses) >= len(state.metric_series): - if state.alpha158_metrics is not None: - selected = ["alpha158"] + [i for i in df.index if state.h_decisions[int(i[6:])]] - else: - selected = [i for i in df.index if state.h_decisions[int(i[6:])]] - df = df.loc[selected] - if df.shape[0] == 1: - st.table(df.iloc[0]) - elif df.shape[0] > 1: - if df.shape[1] == 1: - # suhan's scenario - fig = px.line(df, x=df.index, y=df.columns, markers=True) - fig.update_layout(xaxis_title="Loop Round", yaxis_title=None) - st.plotly_chart(fig) - else: - metrics_window(df, 2, 2, height=650, colors=['red', 'blue', 'orange', 'green']) + selected = [i for i in df.index if state.h_decisions[int(i[6:])]] + df = df.loc[selected] + if df.shape[0] == 1: + st.table(df.iloc[0]) + elif df.shape[0] > 1: + if df.shape[1] == 1: + # suhan's scenario + fig = px.line(df, x=df.index, y=df.columns, markers=True) + fig.update_layout(xaxis_title="Loop Round", yaxis_title=None) + st.plotly_chart(fig) + else: + metrics_window(df, 1, 4, height=300, colors=['red', 'blue', 'orange', 'green']) elif state.log_type == "model_extraction_and_implementation" and len(state.msgs[state.lround]["d.evolving code"]) > 0: @@ -443,10 +441,23 @@ def tasks_window(tasks: list[FactorTask | ModelTask]): if isinstance(state.last_msg.content, list): st.write(state.last_msg.content[0]) elif not isinstance(state.last_msg.content, str): - st.write(state.last_msg.content) + st.write(state.last_msg.content.__dict__) # Main Window +header_c1, header_c3 = st.columns([1, 6], vertical_alignment="center") +with st.container(): + with header_c1: + st.image("https://img-prod-cms-rt-microsoft-com.akamaized.net/cms/api/am/imageFileData/RE1Mu3b?ver=5c31") + with header_c3: + st.markdown( + """ +

+ RD-Agent:
LLM-based autonomous evolving agents for industrial data-driven R&D +

+ """, + unsafe_allow_html=True + ) # Project Info with st.container():