Create app.py

app.py

@@ -0,0 +1,189 @@
+import gradio as gr
+
+CUSTOM_CSS = """
+body, .gradio-container {
+    background: linear-gradient(180deg, #08101e 0%, #0b1020 100%);
+    color: white !important;
+    font-family: Inter, Arial, sans-serif;
+}
+.hero {
+    padding: 24px;
+    border: 1px solid rgba(255,255,255,0.08);
+    border-radius: 20px;
+    background: rgba(255,255,255,0.03);
+    margin-bottom: 16px;
+}
+.metric {
+    padding: 16px;
+    border-radius: 16px;
+    background: rgba(255,255,255,0.03);
+    border: 1px solid rgba(255,255,255,0.08);
+}
+"""
+
+def analyze_thesis(ticker, direction, horizon, position_size, thesis):
+    thesis_lower = thesis.lower()
+
+    thesis_score = 60
+    evidence_score = 55
+    risk_score = 45
+
+    if "valuation" in thesis_lower:
+        thesis_score += 8
+        evidence_score += 8
+    if "risk" in thesis_lower:
+        thesis_score += 6
+    if "earnings" in thesis_lower or "catalyst" in thesis_lower:
+        evidence_score += 8
+    if "guaranteed" in thesis_lower or "100%" in thesis_lower:
+        risk_score += 20
+        thesis_score -= 10
+
+    if position_size > 20:
+        risk_score += 15
+
+    thesis_score = max(0, min(100, thesis_score))
+    evidence_score = max(0, min(100, evidence_score))
+    risk_score = max(0, min(100, risk_score))
+    capital_readiness = max(0, min(100, int(thesis_score * 0.5 + evidence_score * 0.3 + (100 - risk_score) * 0.2)))
+
+    contradictions = []
+    if direction == "Bullish" and "overvalued" in thesis_lower:
+        contradictions.append("Bullish view conflicts with 'overvalued' wording.")
+    if direction == "Bearish" and "undervalued" in thesis_lower:
+        contradictions.append("Bearish view conflicts with 'undervalued' wording.")
+    if not contradictions:
+        contradictions.append("No major contradiction detected.")
+
+    missing = []
+    if "valuation" not in thesis_lower:
+        missing.append("Valuation context missing.")
+    if "risk" not in thesis_lower:
+        missing.append("Risk definition missing.")
+    if "stop loss" not in thesis_lower and "invalidation" not in thesis_lower:
+        missing.append("Exit or invalidation plan missing.")
+    if "macro" not in thesis_lower:
+        missing.append("Macro sensitivity not discussed.")
+
+    counter_case = []
+    if direction == "Bullish":
+        counter_case = [
+            "Positive expectations may already be priced in.",
+            "Weak guidance can break the thesis quickly.",
+            "Position sizing may be too aggressive for current evidence."
+        ]
+    else:
+        counter_case = [
+            "Negative sentiment may already be priced in.",
+            "A strong earnings beat can invalidate the bearish view.",
+            "Bear thesis may underestimate business resilience."
+        ]
+
+    memo = f"""
+# BetaTwins Memo
+
+**Ticker:** {ticker}  
+**Direction:** {direction}  
+**Horizon:** {horizon}  
+**Position Size:** {position_size}%  
+
+## Thesis
+{thesis}
+
+## Scores
+- Thesis Score: {thesis_score}/100
+- Evidence Score: {evidence_score}/100
+- Risk Score: {risk_score}/100
+- Capital Readiness: {capital_readiness}/100
+
+## Contradictions
+- """ + "\n- ".join(contradictions) + """
+
+## Missing Factors
+- """ + "\n- ".join(missing) + """
+
+## Counter-Case
+- """ + "\n- ".join(counter_case)
+
+    summary = f"""
+### Executive Summary
+**{ticker}** thesis reviewed with a **{direction.lower()}** stance.
+
+- Thesis Score: **{thesis_score}**
+- Evidence Score: **{evidence_score}**
+- Risk Score: **{risk_score}**
+- Capital Readiness: **{capital_readiness}**
+"""
+
+    return (
+        f"<div class='metric'><b>Thesis Score</b><br><span style='font-size:32px'>{thesis_score}</span></div>",
+        f"<div class='metric'><b>Evidence Score</b><br><span style='font-size:32px'>{evidence_score}</span></div>",
+        f"<div class='metric'><b>Risk Score</b><br><span style='font-size:32px'>{risk_score}</span></div>",
+        f"<div class='metric'><b>Capital Readiness</b><br><span style='font-size:32px'>{capital_readiness}</span></div>",
+        summary,
+        "\n".join([f"- {x}" for x in contradictions]),
+        "\n".join([f"- {x}" for x in missing]),
+        "\n".join([f"- {x}" for x in counter_case]),
+        memo
+    )
+
+with gr.Blocks(css=CUSTOM_CSS, title="BetaTwins AI") as demo:
+    gr.HTML("""
+    <div class="hero">
+        <h1>Stress-test every investment thesis before capital is deployed.</h1>
+        <p>BetaTwins helps traders, investors, and fintech teams detect weak reasoning, hidden assumptions, and missing risks before a decision becomes expensive.</p>
+    </div>
+    """)
+
+    with gr.Tabs():
+        with gr.Tab("Analyzer"):
+            with gr.Row():
+                with gr.Column(scale=4):
+                    ticker = gr.Textbox(label="Ticker", placeholder="e.g. NVDA")
+                    direction = gr.Dropdown(["Bullish", "Bearish", "Neutral"], value="Bullish", label="Direction")
+                    horizon = gr.Dropdown(["Short-Term", "Swing", "Long-Term"], value="Swing", label="Time Horizon")
+                    position_size = gr.Slider(1, 100, value=10, step=1, label="Position Size %")
+                    thesis = gr.Textbox(label="Investment Thesis", lines=10, placeholder="Write your thesis here...")
+                    run_btn = gr.Button("Run Analysis")
+                with gr.Column(scale=6):
+                    with gr.Row():
+                        score1 = gr.HTML()
+                        score2 = gr.HTML()
+                        score3 = gr.HTML()
+                        score4 = gr.HTML()
+                    with gr.Tabs():
+                        with gr.Tab("Executive Summary"):
+                            summary = gr.Markdown()
+                        with gr.Tab("Contradictions"):
+                            contradictions = gr.Markdown()
+                        with gr.Tab("Missing Factors"):
+                            missing = gr.Markdown()
+                        with gr.Tab("Counter-Case"):
+                            counter = gr.Markdown()
+                        with gr.Tab("Memo"):
+                            memo = gr.Markdown()
+
+            run_btn.click(
+                fn=analyze_thesis,
+                inputs=[ticker, direction, horizon, position_size, thesis],
+                outputs=[score1, score2, score3, score4, summary, contradictions, missing, counter, memo]
+            )
+
+        with gr.Tab("About"):
+            gr.Markdown("""
+## BetaTwins AI
+AI-powered thesis stress testing for smarter investment decisions.
+
+### What it does
+- Scores thesis quality
+- Detects contradictions
+- Finds missing factors
+- Generates counter-case
+- Builds memo-style output
+
+### Disclaimer
+This tool is for research and decision-support only. It is not financial advice.
+""")
+
+if __name__ == "__main__":
+    demo.launch()