Docs: add MODEL, SERP_CACHE_TTL_HOURS, and LOG_LEVEL to .env.example

These environment variables were already supported in config.py but
were not documented in .env.example, making them hard to discover.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

.env.example

@@ -47,12 +47,27 @@ STORAGE_BACKEND=local
 # AWS_SECRET_ACCESS_KEY=minioadmin
 # To start MinIO locally: docker compose --profile s3 up -d minio
 
+# ---- LLM ----
+
+# LLM model to use via OpenRouter
+# Supported: anthropic/claude-3.5-sonnet, openai/gpt-4o, openai/gpt-4o-mini,
+#            google/gemini-pro-1.5, meta-llama/llama-3.1-70b-instruct
+# MODEL=anthropic/claude-3.5-sonnet
+
 # ---- Cache ----
 
 # When USE_CACHE=true: check database for cached responses before making API calls
 # When USE_CACHE=false: always make fresh API calls (still stores results in database)
 USE_CACHE=true
 
+# SERP API cache TTL in hours (how long cached search results are considered fresh)
+# SERP_CACHE_TTL_HOURS=24
+
+# ---- Logging ----
+
+# Log level: DEBUG, INFO, WARNING, ERROR, CRITICAL
+# LOG_LEVEL=INFO
+
 # ---- Webhooks ----
 
 # Comma-separated list of webhook URLs for job completion and alert notifications

SPARC/api.py

@@ -621,6 +621,164 @@ async def export_company_csv(
     )
 
 
+@app.get("/export/{company_name}/pdf", tags=["Export"])
+async def export_company_pdf(
+    company_name: str,
+    _: UserResponse = Depends(get_current_user),
+):
+    """Export analysis results for a company as a formatted PDF report.
+
+    Returns all stored analysis records for the given company, including
+    analysis type, model used, response text, and timestamp, formatted
+    as a downloadable PDF document.
+
+    Args:
+        company_name: Company name to export results for
+
+    Returns:
+        PDF file download
+    """
+    import io
+    import textwrap
+
+    from reportlab.lib import colors
+    from reportlab.lib.pagesizes import letter
+    from reportlab.lib.styles import ParagraphStyle, getSampleStyleSheet
+    from reportlab.lib.units import inch
+    from reportlab.platypus import (
+        Paragraph,
+        SimpleDocTemplate,
+        Spacer,
+        Table,
+        TableStyle,
+    )
+
+    db = get_db_client()
+    with db.get_conn() as conn:
+        with conn.cursor() as cur:
+            cur.execute(
+                """
+                SELECT company_name, analysis_type, model, response, timestamp
+                FROM llm_messages
+                WHERE LOWER(company_name) = LOWER(%s) AND is_cached = FALSE
+                ORDER BY timestamp DESC
+                """,
+                (company_name,),
+            )
+            rows = cur.fetchall()
+
+    if not rows:
+        raise HTTPException(status_code=404, detail=f"No analysis results found for '{company_name}'")
+
+    buffer = io.BytesIO()
+    doc = SimpleDocTemplate(
+        buffer,
+        pagesize=letter,
+        rightMargin=0.75 * inch,
+        leftMargin=0.75 * inch,
+        topMargin=0.75 * inch,
+        bottomMargin=0.75 * inch,
+    )
+
+    styles = getSampleStyleSheet()
+    title_style = ParagraphStyle(
+        "CustomTitle",
+        parent=styles["Title"],
+        fontSize=20,
+        spaceAfter=6,
+    )
+    subtitle_style = ParagraphStyle(
+        "Subtitle",
+        parent=styles["Normal"],
+        fontSize=11,
+        textColor=colors.grey,
+        spaceAfter=20,
+    )
+    heading_style = ParagraphStyle(
+        "SectionHeading",
+        parent=styles["Heading2"],
+        fontSize=13,
+        spaceBefore=16,
+        spaceAfter=8,
+        textColor=colors.HexColor("#1a1a2e"),
+    )
+    body_style = ParagraphStyle(
+        "BodyText",
+        parent=styles["Normal"],
+        fontSize=9,
+        leading=13,
+        spaceAfter=10,
+    )
+
+    elements = []
+
+    # Title and date
+    display_name = rows[0][0]  # Use the casing from the database
+    analysis_date = datetime.now().strftime("%Y-%m-%d")
+    elements.append(Paragraph(f"SPARC Analysis Report: {display_name}", title_style))
+    elements.append(Paragraph(f"Generated on {analysis_date}", subtitle_style))
+
+    # Summary table
+    summary_data = [
+        ["Total Analyses", str(len(rows))],
+        ["Analysis Types", ", ".join(sorted(set(r[1] for r in rows)))],
+        ["Models Used", ", ".join(sorted(set(r[2] for r in rows)))],
+    ]
+    summary_table = Table(summary_data, colWidths=[2 * inch, 4.5 * inch])
+    summary_table.setStyle(
+        TableStyle(
+            [
+                ("BACKGROUND", (0, 0), (0, -1), colors.HexColor("#f0f0f5")),
+                ("FONTNAME", (0, 0), (0, -1), "Helvetica-Bold"),
+                ("FONTSIZE", (0, 0), (-1, -1), 9),
+                ("PADDING", (0, 0), (-1, -1), 6),
+                ("GRID", (0, 0), (-1, -1), 0.5, colors.HexColor("#cccccc")),
+                ("VALIGN", (0, 0), (-1, -1), "TOP"),
+            ]
+        )
+    )
+    elements.append(summary_table)
+    elements.append(Spacer(1, 16))
+
+    # Individual analysis sections
+    for i, row in enumerate(rows, 1):
+        _, analysis_type, model, response, timestamp = row
+        ts_str = timestamp.strftime("%Y-%m-%d %H:%M:%S") if hasattr(timestamp, "strftime") else str(timestamp)
+
+        elements.append(
+            Paragraph(f"Analysis {i}: {analysis_type} (via {model})", heading_style)
+        )
+        elements.append(
+            Paragraph(f"<i>Performed: {ts_str}</i>", body_style)
+        )
+
+        # Wrap long response text into paragraphs, escaping XML special chars
+        safe_response = (
+            response.replace("&", "&amp;")
+            .replace("<", "&lt;")
+            .replace(">", "&gt;")
+        )
+        # Split into manageable paragraphs to avoid overflow
+        for line in safe_response.split("\n"):
+            if line.strip():
+                elements.append(Paragraph(line, body_style))
+            else:
+                elements.append(Spacer(1, 4))
+
+        elements.append(Spacer(1, 10))
+
+    doc.build(elements)
+    buffer.seek(0)
+
+    safe_name = company_name.replace(" ", "_").lower()
+    filename = f"{safe_name}-analysis-{analysis_date}.pdf"
+    return StreamingResponse(
+        iter([buffer.getvalue()]),
+        media_type="application/pdf",
+        headers={"Content-Disposition": f'attachment; filename="{filename}"'},
+    )
+
+
 # ============== System Endpoints ==============
 
 

frontend/src/api/client.ts

@@ -141,6 +141,21 @@ export const exportApi = {
     link.remove();
     window.URL.revokeObjectURL(url);
   },
+  exportPdf: async (companyName: string): Promise<void> => {
+    const response = await api.get(`/export/${encodeURIComponent(companyName)}/pdf`, {
+      responseType: 'blob',
+    });
+    const safeName = companyName.toLowerCase().replace(/\s+/g, '_');
+    const date = new Date().toISOString().split('T')[0];
+    const url = window.URL.createObjectURL(new Blob([response.data], { type: 'application/pdf' }));
+    const link = document.createElement('a');
+    link.href = url;
+    link.setAttribute('download', `${safeName}-analysis-${date}.pdf`);
+    document.body.appendChild(link);
+    link.click();
+    link.remove();
+    window.URL.revokeObjectURL(url);
+  },
 };
 
 // Analytics API

frontend/src/pages/Analysis.tsx

@@ -110,13 +110,22 @@ export function Analysis() {
                 <h3 className="text-lg font-semibold text-text-primary">
                   AI Analysis Results
                 </h3>
-                <button
+                <div className="flex items-center gap-2">
-                  onClick={() => exportApi.exportCsv(result.company_name)}
+                  <button
-                  className="flex items-center gap-2 text-sm bg-primary/20 hover:bg-primary/30 text-primary font-medium px-3 py-1.5 rounded-lg transition-colors"
+                    onClick={() => exportApi.exportCsv(result.company_name)}
-                >
+                    className="flex items-center gap-2 text-sm bg-primary/20 hover:bg-primary/30 text-primary font-medium px-3 py-1.5 rounded-lg transition-colors"
-                  <Download size={14} />
+                  >
-                  Export CSV
+                    <Download size={14} />
-                </button>
+                    Export CSV
+                  </button>
+                  <button
+                    onClick={() => exportApi.exportPdf(result.company_name)}
+                    className="flex items-center gap-2 text-sm bg-primary/20 hover:bg-primary/30 text-primary font-medium px-3 py-1.5 rounded-lg transition-colors"
+                  >
+                    <FileText size={14} />
+                    Export PDF
+                  </button>
+                </div>
               </div>
               <div className="prose prose-invert max-w-none">
                 <div className="text-text-primary whitespace-pre-wrap leading-relaxed">

requirements.txt

@@ -17,3 +17,4 @@ PyJWT
 slowapi
 apscheduler
 boto3
+reportlab