Merge pull request #52 from QAway-to/codex/analyze-project-repository-y17yqj

app.py

@@ -31,7 +31,7 @@ comparer = PortfolioComparer(llm_service, MODEL_NAME)
 
 # === Main Interface ===
 with gr.Blocks(css=base_css) as demo:
-    gr.Markdown("## Investment Portfolio Analyzer")
+    gr.Markdown("## Investment Portfolio Analyzer", elem_classes="page-title")
     gr.Markdown(
         "Professional AI-driven analytics for investment and crypto markets.",
         elem_classes="subtitle",
@@ -73,12 +73,7 @@ with gr.Blocks(css=base_css) as demo:
                 wrap=True,
                 elem_id="comparison_table",
             )
-            comp_comment = gr.Textbox(
-                label="AI Commentary",
-                lines=14,
-                elem_id="llm_comment_box",
-                interactive=False,
-            )
+            comp_comment = gr.HTML(elem_id="llm_comment_box")
             compare_btn.click(
                 fn=show_comparison_table,
                 inputs=[pid_a, pid_b],

presentation/components/comparison_table.py

@@ -7,6 +7,10 @@ import pandas as pd
 from infrastructure.cache import CacheUnavailableError
 from infrastructure.llm_client import llm_service
 from infrastructure.output_api import extract_portfolio_id, fetch_metrics_cached
+from presentation.components.analysis_formatter import (
+    render_analysis_html,
+    render_status_html,
+)
 from prompts.system_prompts import COMPARISON_SYSTEM_PROMPT
 
 
@@ -17,18 +21,18 @@ def show_comparison_table(portfolio_a: str, portfolio_b: str):
     pid_b = extract_portfolio_id(portfolio_b)
     if not pid_a or not pid_b:
         message = "❌ Invalid portfolio IDs."
-        return _message_df(message), message
+        return _message_df(message), render_status_html(message)
 
     try:
         df, commentary = _build_comparison_with_comment(pid_a, pid_b)
-        return df, commentary
+        return df, render_analysis_html(commentary)
     except CacheUnavailableError as e:
         wait = int(e.retry_in) + 1
         message = f"⚠️ Metrics temporarily unavailable. Retry in ~{wait} seconds."
-        return _message_df(message), message
+        return _message_df(message), render_status_html(message)
     except Exception:
         message = "❌ Unable to build comparison right now. Please try again later."
-        return _message_df(message), message
+        return _message_df(message), render_status_html(message)
 
 
 def _build_comparison_with_comment(p1: str, p2: str):

presentation/styles/themes/base.css

@@ -3,6 +3,35 @@
 [data-testid="block-container"] { max-width:1180px !important; margin:auto !important; }
 h2, h3, .gr-markdown { color:#f0f6fc !important; font-weight:600 !important; }
 
+/* === Page headers & footer === */
+.page-title,
+.subtitle,
+.footer {
+  width:100%;
+  margin:0 auto 18px;
+  text-align:center !important;
+}
+
+.page-title .gr-markdown,
+.subtitle .gr-markdown,
+.footer .gr-markdown {
+  text-align:center !important;
+  margin:0 auto;
+}
+
+.page-title .gr-markdown h1,
+.page-title .gr-markdown h2,
+.subtitle .gr-markdown p,
+.footer .gr-markdown p,
+.footer .gr-markdown small {
+  text-align:center !important;
+}
+
+.subtitle { margin-bottom:28px; color:#9ca3af !important; }
+.subtitle .gr-markdown { color:#9ca3af !important; font-weight:500 !important; }
+
+.footer { margin-top:40px; margin-bottom:0; }
+
 /* === Tabs Navigation === */
 #main_tabs {
   width:72%;

prompts/system_prompts.py

@@ -60,33 +60,33 @@ Analytical guidance:
 - Stream the HTML sequentially, closing tags promptly so partial updates render cleanly.
 """
 
-
 COMPARISON_SYSTEM_PROMPT = """
+You are a quantitative analyst comparing two portfolios.
+
+Output fully formed HTML using only <div>, <h2>, <p>, <span>, and <hr> tags.
+Structure the report exactly as follows:
+
+<div class="section">
+  <h2>Comparative Analysis</h2>
+  ...metrics and commentary...
+</div>
+<div class="section-divider"></div>
+<div class="section">
+  <h2>Recommendation</h2>
+  ...actionable insight...
+</div>
+
+Formatting requirements:
+- Use <p class="analysis-line metric"> for quantitative statements that cite specific figures.
+- Inside each metric line, wrap the label in <span class="metric-name">Metric</span> and place a single colon separator span.
+- Wrap every numeric value in <span class="metric-value"> containing a <span class="metric-number positive|negative|neutral"> token chosen by whether the figure signals strength, weakness, or neutral impact.
+- Provide at least two narrative paragraphs per section using <p class="analysis-line">…</p> with concise professional tone and varied phrasing.
+- Mention each metric only once; do not repeat values in multiple sentences.
+- Do not emit inline CSS, markdown, bullet characters, or placeholder text. Use single spaces only.
 
-You are a financial analysis model specializing in quantitative portfolio comparison.
-
-Your goal is to compare two portfolios **objectively** using their metrics.
-
-When analyzing:
-- Do not make emotional or vague statements.
-- Base conclusions strictly on the provided numerical data.
-- Identify *which portfolio is statistically stronger* based on performance, risk, and stability.
-
-Your output must be concise and structured in the following format:
-
-Comparative Analysis
-- Discuss which portfolio shows **better performance** (higher return / alpha).
-- Discuss **risk-adjusted efficiency** (Sharpe / Sortino ratio, volatility, maxDD).
-- Highlight **consistency** and **downside protection** if metrics imply it.
-
-Recommendation
-Provide an actionable insight:
-- If one portfolio is clearly better, state which one and why.
-- If both are weak or over-risked — say it explicitly.
-- If data is incomplete or contradictory — mention this clearly.
-
-Avoid phrases like “depends on the investor” or “might be better for risk-taking investors”.
-You are the quantitative analyst — give a judgment based on data, not preference.
+Analytical guidance:
+- Base every conclusion on the supplied Portfolio A/B metrics and explicitly contrast the stronger vs weaker portfolio on returns, risk-adjusted efficiency, volatility, drawdowns, and stability.
+- Deliver a decisive recommendation that names the favored portfolio (or flags deficiencies in both) with clear reasoning grounded in data.
 """