Delete dynamic_pricing_bandit_app.py

dynamic_pricing_bandit_app.py

@@ -1,69 +0,0 @@
-# dynamic_pricing_bandit_app.py
-from datasets import load_dataset
-import pandas as pd
-import numpy as np
-import gradio as gr
-import json
-
-PRICE_POINTS = [5000, 7500, 10000, 12500, 15000]
-SEGMENTS = ["Retail", "HNI", "Corporate"]
-DEAL_TYPES = ["M&A Advisory", "Debt Issuance", "Equity Offering", "Restructuring"]
-REGIONS = ["North America", "Europe", "Asia Pacific", "Latin America", "Middle East"]
-INDUSTRIES = ["Technology", "Healthcare", "Financial Services", "Energy", "Consumer Goods", "Industrial"]
-
-class ThompsonBandit:
-    def __init__(self, n_arms):
-        self.successes = np.ones(n_arms)
-        self.failures = np.ones(n_arms)
-
-    def select_arm(self):
-        return np.argmax(np.random.beta(self.successes, self.failures))
-
-    def update(self, arm, reward):
-        if reward:
-            self.successes[arm] += 1
-        else:
-            self.failures[arm] += 1
-
-# Load HF dataset
-dataset = load_dataset("banking77", split="train[:500]")
-df = pd.DataFrame(dataset)
-df["segment"] = np.random.choice(SEGMENTS, len(df))
-df["deal_type"] = np.random.choice(DEAL_TYPES, len(df))
-df["deal_size"] = np.random.lognormal(mean=16, sigma=1.0, size=len(df)).astype(int)
-df["region"] = np.random.choice(REGIONS, len(df))
-df["industry"] = np.random.choice(INDUSTRIES, len(df))
-
-bandit = ThompsonBandit(len(PRICE_POINTS))
-
-def recommend_price(segment, deal_type, deal_size_str, region, industry):
-    try:
-        deal_size = float(deal_size_str.replace("$", "").replace(",", ""))
-        arm = bandit.select_arm()
-        price = PRICE_POINTS[arm]
-        acceptance_prob = max(0.1, 1 - (price / PRICE_POINTS[-1]) * 0.8)
-        accepted = np.random.binomial(1, acceptance_prob)
-        bandit.update(arm, accepted)
-        return f"Recommended Price: ${price:,}\nClient would {'accept' if accepted else 'decline'} this price."
-    except Exception as e:
-        return str(e)
-
-with gr.Blocks() as app:
-    gr.Markdown("# Dynamic Pricing Bandit App")
-    with gr.Row():
-        with gr.Column():
-            segment_input = gr.Dropdown(choices=SEGMENTS, label="Client Segment")
-            deal_type_input = gr.Dropdown(choices=DEAL_TYPES, label="Deal Type")
-            deal_size_input = gr.Textbox(label="Deal Size (USD)", value="$50000000")
-            region_input = gr.Dropdown(choices=REGIONS, label="Region")
-            industry_input = gr.Dropdown(choices=INDUSTRIES, label="Industry")
-            btn = gr.Button("Get Recommendation")
-        with gr.Column():
-            result = gr.Markdown()
-
-    btn.click(fn=recommend_price,
-              inputs=[segment_input, deal_type_input, deal_size_input, region_input, industry_input],
-              outputs=result)
-
-if __name__ == "__main__":
-    app.launch()