Cycle-Navigator / app-backup2.py
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# -------- app_final.py --------
import os, json, math, pathlib
import numpy as np
import plotly.graph_objects as go
import gradio as gr
import openai
# โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
# 0. OpenAI API key
# โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
if "OPENAI_API_KEY" not in os.environ:
os.environ["OPENAI_API_KEY"] = input("๐Ÿ”‘ Enter your OpenAI API key: ").strip()
openai.api_key = os.environ["OPENAI_API_KEY"]
# โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
# 1. Cycle config
# โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
CENTER = 2025
CYCLES = {
"K-Wave": 50, # Kondratiev long wave
"Business": 9, # Juglar investment cycle
"Finance": 80, # Long credit cycle
"Hegemony": 250 # Power-shift cycle
}
ORDERED_PERIODS = sorted(CYCLES.values()) # [9, 50, 80, 250]
COLOR = {9:"#66ff66", 50:"#ff3333", 80:"#ffcc00", 250:"#66ccff"}
AMPL = {9:0.6, 50:1.0, 80:1.6, 250:4.0}
PERIOD_BY_CYCLE = {k:v for k,v in CYCLES.items()}
# โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
# 2. Load events JSON
# โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
EVENTS_PATH = pathlib.Path(__file__).with_name("cycle_events.json")
with open(EVENTS_PATH, encoding="utf-8") as f:
EVENTS = {int(item["year"]): item["events"] for item in json.load(f)}
# โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
# 3. Helper functions
# โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
def half_sine(xs, period, amp):
"""Half-sine โ€˜towerโ€™ with zero bottom floor."""
phase = np.mod(xs - CENTER, period)
y = amp * np.sin(np.pi * phase / period)
y[y < 0] = 0
return y
def build_chart(start: int, end: int):
"""Return (Plotly figure, summary string) for the requested year range."""
xs = np.linspace(start, end, max(1000, (end - start) * 4))
fig = go.Figure()
# โ—ผ 1) Draw gradient half-sine โ€˜towersโ€™ (30 layers each, like old matplotlib version)
for period in ORDERED_PERIODS:
base_amp = AMPL[period]
color = COLOR[period]
# โ”€โ”€ gradient layers (thin, semi-transparent) โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
for frac in np.linspace(base_amp / 30, base_amp, 30):
ys = half_sine(xs, period, frac)
fig.add_trace(go.Scatter(
x = xs,
y = ys,
mode = "lines",
line = dict(color=color, width=0.8),
opacity = 0.6,
hoverinfo = "skip",
showlegend = False
))
# โ”€โ”€ outer edge line (slightly thicker) โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
ys = half_sine(xs, period, base_amp)
fig.add_trace(go.Scatter(
x = xs,
y = ys,
mode = "lines",
line = dict(color=color, width=1.6),
hoverinfo = "skip",
showlegend = False
))
# โ—ผ 2) Event markers with bilingual hover text โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
for year, evs in EVENTS.items():
if start <= year <= end:
cycle_name = evs[0]["cycle"]
period = PERIOD_BY_CYCLE.get(cycle_name, 50)
y_val = float(half_sine(np.array([year]), period, AMPL[period]))
txt_en = "<br>".join(e["event_en"] for e in evs)
txt_ko = "<br>".join(e["event_ko"] for e in evs)
fig.add_trace(go.Scatter(
x = [year], y = [y_val],
mode = "markers",
marker = dict(color="white", size=6),
customdata = [[cycle_name, txt_en, txt_ko]],
hovertemplate = (
"Year %{x} โ€ข %{customdata[0]} cycle"
"<br>%{customdata[1]}"
"<br>%{customdata[2]}<extra></extra>"
),
showlegend = False
))
# โ—ผ 3) Cosmetic touches: centre line, 250-yr arrow, background, axes โ”€โ”€โ”€โ”€
# centre alignment marker
fig.add_vline(
x = CENTER,
line_dash = "dash",
line_color = "white",
opacity = 0.6
)
# 250-year span arrow (โ†”) across the top of chart
arrow_y = AMPL[250] * 1.05
fig.add_annotation(
x = CENTER - 125, y = arrow_y,
ax = CENTER + 125, ay = arrow_y,
xref = "x", yref = "y", axref = "x", ayref = "y",
showarrow = True,
arrowhead = 3,
arrowsize = 1,
arrowwidth = 1.2,
arrowcolor = "white"
)
fig.add_annotation(
x = CENTER, y = arrow_y + 0.15,
text = "250 yr",
showarrow = False,
font = dict(color="white", size=10)
)
# global styling
fig.update_layout(
template = "plotly_dark",
paper_bgcolor = "black",
plot_bgcolor = "black",
height = 450,
margin = dict(t=30, l=40, r=40, b=40),
hoverlabel = dict(bgcolor="#222", font_size=11)
)
fig.update_xaxes(title="Year", range=[start, end], showgrid=False)
fig.update_yaxes(title="Relative amplitude", showticklabels=False, showgrid=False)
summary = f"Range {start}-{end} | Events plotted: {sum(1 for y in EVENTS if start <= y <= end)}"
return fig, summary
# โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
# 4. GPT chat helper
# โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
BASE_PROMPT = (
"You are a concise and accurate Korean assistant. "
"If a chart summary is provided, incorporate it in your answer."
)
def chat_with_gpt(history, user_msg, chart_summary):
messages = [{"role": "system", "content": BASE_PROMPT}]
if chart_summary not in ("", "No chart yet."):
messages.append({"role": "system", "content": f"[Chart summary]\n{chart_summary}"})
for u, a in history:
messages.extend([{"role": "user", "content": u},
{"role": "assistant", "content": a}])
messages.append({"role": "user", "content": user_msg})
res = openai.chat.completions.create(
model = "gpt-3.5-turbo",
messages = messages,
max_tokens = 600,
temperature = 0.7
)
return res.choices[0].message.content.strip()
# โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
# 5. Gradio UI
# โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
def create_app():
with gr.Blocks(theme=gr.themes.Soft()) as demo:
# โ”€โ”€ Title & subtitle
gr.Markdown("## ๐Ÿ”ญ **CycleNavigator (Interactive)**")
gr.Markdown("### <sub>Interactive visual service delivering insights at a glance into the four major long cyclesโ€”9-year business cycle, 50-year Kondratiev wave, 80-year financial credit cycle, and 250-year hegemony cycleโ€”through dynamic charts and AI chat.</sub>")
gr.Markdown(
"<sub>"
"<b>Business 9y</b> (credit-investment business cycle) โ€ข "
"<b>K-Wave 50y</b> (long technological-industrial wave) โ€ข "
"<b>Finance 80y</b> (long credit-debt cycle) โ€ข "
"<b>Hegemony 250y</b> (rise & fall of global powers cycle)"
"</sub>"
)
chart_summary_state = gr.State(value="No chart yet.")
with gr.Tabs():
# โ”€โ”€ Tab 1: Timeline Chart โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
with gr.TabItem("Timeline Chart"):
with gr.Row():
start_year = gr.Number(label="Start Year", value=1500, precision=0)
end_year = gr.Number(label="End Year", value=2500, precision=0)
zoom_in = gr.Button("๐Ÿ” Zoom In")
zoom_out = gr.Button("๐Ÿ”Ž Zoom Out")
# initial plot
fig0, summ0 = build_chart(1500, 2500)
plot = gr.Plot(value=fig0)
chart_summary_state.value = summ0
# refresh on year change
def refresh(s, e):
fig, summ = build_chart(int(s), int(e))
return fig, summ
start_year.change(refresh, [start_year, end_year],
[plot, chart_summary_state])
end_year.change(refresh, [start_year, end_year],
[plot, chart_summary_state])
# zoom helpers
def zoom(s, e, factor):
mid = (s + e) / 2
span = (e - s) * factor / 2
ns, ne = int(mid - span), int(mid + span)
fig, summ = build_chart(ns, ne)
return ns, ne, fig, summ
zoom_in.click(lambda s, e: zoom(s, e, 0.5),
inputs = [start_year, end_year],
outputs = [start_year, end_year, plot, chart_summary_state])
zoom_out.click(lambda s, e: zoom(s, e, 2.0),
inputs = [start_year, end_year],
outputs = [start_year, end_year, plot, chart_summary_state])
# JSON download
gr.File(value=str(EVENTS_PATH), label="Download cycle_events.json")
# โ”€โ”€ Tab 2: GPT Chat โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
with gr.TabItem("GPT Chat"):
chatbot = gr.Chatbot(label="Assistant")
user_input = gr.Textbox(lines=3, placeholder="๋ฉ”์‹œ์ง€๋ฅผ ์ž…๋ ฅํ•˜์„ธ์š”โ€ฆ")
send_btn = gr.Button("Send")
def respond(history, msg, summ):
reply = chat_with_gpt(history, msg, summ)
history.append((msg, reply))
return history, gr.Textbox(value="")
send_btn.click(respond,
[chatbot, user_input, chart_summary_state],
[chatbot, user_input])
user_input.submit(respond,
[chatbot, user_input, chart_summary_state],
[chatbot, user_input])
return demo
if __name__ == "__main__":
create_app().launch()