feat: add date filtering to PDF report compiler
Adds --date arg to filter reports by date and auto-generate filename with date and symbols
This commit is contained in:
MUmarJ
parent
202901c6a4
commit
b950e3a018
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@ -0,0 +1,501 @@
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#!/usr/bin/env python3
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"""
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Compile all trading agent reports into a single consolidated PDF.
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Creates a PDF with:
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1. Summary table showing all symbols, their decisions, and analysis dates
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2. Detailed reports for each symbol (in order specified by REPORT_ORDER)
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Usage:
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python cli/compile_reports.py # Compile all results into single PDF
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python cli/compile_reports.py --output report.pdf # Custom output filename
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python cli/compile_reports.py --date 2026-01-18 # Filter to specific date (auto-names output)
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"""
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import argparse
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import re
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import sys
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from datetime import datetime
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from pathlib import Path
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import markdown2
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from playwright.sync_api import sync_playwright
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# Report order (top to bottom for each symbol's section)
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REPORT_ORDER = [
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("final_trade_decision.md", "Final Trade Decision"),
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("trader_investment_plan.md", "Trader Investment Plan"),
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("investment_plan.md", "Investment Plan"),
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("fundamentals_report.md", "Fundamentals Analysis"),
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("news_report.md", "News Analysis"),
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("sentiment_report.md", "Sentiment Analysis"),
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("market_report.md", "Market Analysis"),
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]
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# Clean GitHub-style markdown CSS
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CSS_STYLES = """
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@page {
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size: A4;
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margin: 0.75in;
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}
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body {
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font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', 'Noto Sans', Helvetica, Arial, sans-serif;
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font-size: 14px;
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line-height: 1.6;
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color: #24292f;
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max-width: 100%;
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margin: 0;
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padding: 0;
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}
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h1 {
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font-size: 2em;
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font-weight: 600;
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border-bottom: 1px solid #d0d7de;
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padding-bottom: 0.3em;
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margin-top: 24px;
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margin-bottom: 16px;
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}
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h2 {
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font-size: 1.5em;
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font-weight: 600;
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border-bottom: 1px solid #d0d7de;
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padding-bottom: 0.3em;
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margin-top: 24px;
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margin-bottom: 16px;
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}
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h3 {
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font-size: 1.25em;
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font-weight: 600;
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margin-top: 24px;
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margin-bottom: 16px;
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}
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h4 {
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font-size: 1em;
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font-weight: 600;
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margin-top: 24px;
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margin-bottom: 16px;
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}
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p {
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margin-top: 0;
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margin-bottom: 16px;
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}
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ul, ol {
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padding-left: 2em;
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margin-top: 0;
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margin-bottom: 16px;
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}
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li {
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margin-bottom: 4px;
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}
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li + li {
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margin-top: 4px;
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}
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table {
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border-collapse: collapse;
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width: 100%;
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margin-top: 0;
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margin-bottom: 16px;
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}
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th, td {
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padding: 6px 13px;
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border: 1px solid #d0d7de;
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}
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th {
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background-color: #f6f8fa;
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font-weight: 600;
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}
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tr:nth-child(2n) {
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background-color: #f6f8fa;
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}
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hr {
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border: 0;
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border-top: 1px solid #d0d7de;
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margin: 24px 0;
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}
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code {
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background-color: rgba(175, 184, 193, 0.2);
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padding: 0.2em 0.4em;
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border-radius: 6px;
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font-family: ui-monospace, SFMono-Regular, 'SF Mono', Menlo, Consolas, monospace;
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font-size: 85%;
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}
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pre {
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background-color: #f6f8fa;
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padding: 16px;
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border-radius: 6px;
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overflow-x: auto;
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margin-bottom: 16px;
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font-size: 85%;
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line-height: 1.45;
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}
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pre code {
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padding: 0;
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background: none;
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font-size: 100%;
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}
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blockquote {
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border-left: 0.25em solid #d0d7de;
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padding: 0 1em;
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margin: 0 0 16px 0;
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color: #57606a;
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}
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strong {
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font-weight: 600;
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}
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/* Decision color styling */
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.decision-buy { color: #1a7f37; font-weight: 700; }
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.decision-sell { color: #cf222e; font-weight: 700; }
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.decision-hold { color: #9a6700; font-weight: 700; }
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/* Symbol section - page break before each new symbol */
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.symbol-section {
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page-break-before: always;
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}
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.symbol-section:first-of-type {
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page-break-before: avoid;
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}
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/* Report title styling */
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.report-title {
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color: #0969da;
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font-size: 1.3em;
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font-weight: 600;
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margin-top: 32px;
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margin-bottom: 16px;
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padding-bottom: 8px;
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border-bottom: 2px solid #0969da;
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}
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.report-title:first-of-type {
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margin-top: 16px;
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}
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"""
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def extract_decision(content: str) -> str:
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"""Extract BUY/SELL/HOLD decision from final trade decision content."""
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content_lower = content.lower()
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patterns = [
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r"recommendation[:\s]*\*{0,2}(buy|sell|hold)\*{0,2}",
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r"\*{0,2}(buy|sell|hold)\*{0,2}[:\s]*recommendation",
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r"final.*?decision[:\s]*\*{0,2}(buy|sell|hold)\*{0,2}",
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r"recommend.*?(buy|sell|hold)",
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r"action[:\s]*\*{0,2}(buy|sell|hold)\*{0,2}",
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]
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for pattern in patterns:
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match = re.search(pattern, content_lower)
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if match:
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return match.group(1).upper()
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buy_count = len(re.findall(r"\bbuy\b", content_lower))
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sell_count = len(re.findall(r"\bsell\b", content_lower))
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hold_count = len(re.findall(r"\bhold\b", content_lower))
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max_count = max(buy_count, sell_count, hold_count)
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if max_count > 0:
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if sell_count == max_count:
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return "SELL"
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if buy_count == max_count:
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return "BUY"
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return "HOLD"
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return "N/A"
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def markdown_to_html(md_content: str) -> str:
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"""Convert markdown to HTML with extras."""
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return markdown2.markdown(
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md_content,
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extras=[
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"tables",
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"fenced-code-blocks",
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"strike",
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"task_list",
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"cuddled-lists",
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],
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)
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def find_all_reports(results_dir: Path, date_filter: str | None = None) -> list[dict]:
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"""Find all report directories and extract their data.
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Args:
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results_dir: Path to the results directory
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date_filter: Optional date string (YYYY-MM-DD) to filter reports
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"""
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all_reports = []
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if not results_dir.exists():
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return all_reports
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for symbol_dir in sorted(results_dir.iterdir()):
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if not symbol_dir.is_dir():
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continue
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symbol = symbol_dir.name
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if symbol.startswith(".") or " " in symbol:
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continue
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for date_dir in sorted(symbol_dir.iterdir(), reverse=True):
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if not date_dir.is_dir():
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continue
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date = date_dir.name
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# Skip if date doesn't match filter
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if date_filter and date != date_filter:
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continue
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reports_dir = date_dir / "reports"
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if not reports_dir.exists():
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continue
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report_files = []
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decision = "N/A"
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for filename, title in REPORT_ORDER:
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file_path = reports_dir / filename
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if file_path.exists():
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content = file_path.read_text(encoding="utf-8")
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html_content = markdown_to_html(content)
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report_files.append((filename, title, html_content))
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if filename == "final_trade_decision.md":
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decision = extract_decision(content)
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if report_files:
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all_reports.append({
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"symbol": symbol,
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"date": date,
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"decision": decision,
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"reports_dir": reports_dir,
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"reports": report_files,
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})
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return all_reports
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def build_html_document(all_reports: list[dict]) -> str:
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"""Build complete HTML document with summary table and all reports."""
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# Build summary table rows
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summary_rows = []
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for report_data in all_reports:
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decision = report_data["decision"]
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decision_class = f"decision-{decision.lower()}" if decision in ["BUY", "SELL", "HOLD"] else ""
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summary_rows.append(f'''<tr>
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<td><strong>{report_data["symbol"]}</strong></td>
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<td>{report_data["date"]}</td>
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<td class="{decision_class}">{decision}</td>
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<td>{len(report_data["reports"])} reports</td>
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</tr>''')
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summary_table = "\n".join(summary_rows)
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# Build symbol sections
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symbol_sections = []
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for report_data in all_reports:
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symbol = report_data["symbol"]
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date = report_data["date"]
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decision = report_data["decision"]
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decision_class = f"decision-{decision.lower()}" if decision in ["BUY", "SELL", "HOLD"] else ""
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# Build report content - simple flowing structure
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reports_html_parts = []
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for _, title, html_content in report_data["reports"]:
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reports_html_parts.append(f'''<div class="report-title">{title}</div>
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{html_content}''')
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reports_html = "\n".join(reports_html_parts)
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symbol_sections.append(f'''<div class="symbol-section">
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<h1>{symbol} Trading Analysis Report</h1>
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<p><strong>Date:</strong> {date} | <strong>Recommendation:</strong> <span class="{decision_class}">{decision}</span></p>
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<hr>
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{reports_html}
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</div>''')
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all_symbols_html = "\n".join(symbol_sections)
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generated_date = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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html = f'''<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>Trading Analysis Report</title>
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<style>
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{CSS_STYLES}
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</style>
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</head>
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<body>
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<h1>Trading Analysis Report</h1>
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<p><em>Generated: {generated_date}</em></p>
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<h2>Summary of Recommendations</h2>
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<table>
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<thead>
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<tr>
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<th>Symbol</th>
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<th>Analysis Date</th>
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<th>Decision</th>
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<th>Reports</th>
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</tr>
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</thead>
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<tbody>
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{summary_table}
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</tbody>
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</table>
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<hr>
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{all_symbols_html}
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<hr>
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<p><em>Report generated by TradingAgents</em></p>
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</body>
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</html>'''
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return html
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def compile_to_pdf(html_content: str, output_path: Path) -> bool:
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"""Generate PDF from HTML using Playwright."""
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try:
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with sync_playwright() as p:
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browser = p.chromium.launch()
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page = browser.new_page()
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page.set_content(html_content, wait_until="networkidle")
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page.pdf(
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path=str(output_path),
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format="A4",
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margin={
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"top": "0.5in",
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"bottom": "0.5in",
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"left": "0.5in",
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"right": "0.5in",
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},
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print_background=True,
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)
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browser.close()
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return True
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except Exception as e:
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print(f"Error generating PDF: {e}")
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return False
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def main():
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parser = argparse.ArgumentParser(
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description="Compile all trading agent reports into a single consolidated PDF",
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formatter_class=argparse.RawDescriptionHelpFormatter,
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epilog="""
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Examples:
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python cli/compile_reports.py
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python cli/compile_reports.py --output my_report.pdf
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python cli/compile_reports.py --date 2026-01-18
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python cli/compile_reports.py --date 2026-01-18 --output custom.pdf
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""",
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)
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parser.add_argument(
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"--output", "-o",
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default="./results/trading_analysis_report.pdf",
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help="Output PDF filename (default: ./results/trading_analysis_report.pdf)",
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)
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parser.add_argument(
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"--results-dir", "-r",
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default="./results",
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help="Results directory (default: ./results)",
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)
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parser.add_argument(
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"--date", "-d",
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help="Filter reports to a specific date (format: YYYY-MM-DD)",
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)
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args = parser.parse_args()
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# Validate date format if provided
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if args.date:
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import re as re_module
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if not re_module.match(r"^\d{4}-\d{2}-\d{2}$", args.date):
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print(f"Error: Invalid date format '{args.date}'. Expected YYYY-MM-DD")
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sys.exit(1)
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results_dir = Path(args.results_dir)
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default_output = "./results/trading_analysis_report.pdf"
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if not results_dir.exists():
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print(f"Error: Results directory not found: {results_dir}")
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sys.exit(1)
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if args.date:
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print(f"Scanning {results_dir} for reports on {args.date}...")
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else:
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print(f"Scanning {results_dir} for reports...")
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all_reports = find_all_reports(results_dir, date_filter=args.date)
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if not all_reports:
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if args.date:
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print(f"No reports found for date {args.date}")
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else:
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print("No reports found")
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sys.exit(1)
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print(f"Found {len(all_reports)} symbol analysis report(s):\n")
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for report_data in all_reports:
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decision_indicator = {
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"BUY": "[BUY]",
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"SELL": "[SELL]",
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"HOLD": "[HOLD]",
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}.get(report_data["decision"], "[N/A]")
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print(f" {report_data['symbol']:6} | {report_data['date']} | {decision_indicator:6} | {len(report_data['reports'])} reports")
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# Determine output path
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if args.date and args.output == default_output:
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# Generate dynamic filename from date + symbols (up to 5)
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symbols = [r["symbol"] for r in all_reports[:5]]
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symbols_str = "_".join(symbols)
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output_path = Path(f"./results/trading_report_{args.date}_{symbols_str}.pdf")
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else:
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output_path = Path(args.output)
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print("\nGenerating PDF...")
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html_document = build_html_document(all_reports)
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if compile_to_pdf(html_document, output_path):
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print(f"\n+ PDF created: {output_path}")
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else:
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print("\n- Failed to create PDF")
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sys.exit(1)
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if __name__ == "__main__":
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main()
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44
cli/main.py
44
cli/main.py
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@ -429,10 +429,12 @@ def get_user_selections():
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box_content += f"\n[dim]Default: {default}[/dim]"
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return Panel(box_content, border_style="blue", padding=(1, 2))
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# Step 1: Ticker symbol
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# Step 1: Ticker symbol(s)
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console.print(
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create_question_box(
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"Step 1: Ticker Symbol", "Enter the ticker symbol to analyze", "SPY"
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"Step 1: Ticker Symbol(s)",
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"Enter ticker symbol(s) to analyze (comma-separated for multiple)",
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"SPY",
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)
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)
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selected_ticker = get_ticker()
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@ -504,8 +506,11 @@ def get_user_selections():
|
|||
|
||||
|
||||
def get_ticker():
|
||||
"""Get ticker symbol from user input."""
|
||||
return typer.prompt("", default="SPY")
|
||||
"""Get ticker symbol(s) from user input. Supports comma-separated symbols."""
|
||||
raw_input = typer.prompt("", default="SPY")
|
||||
# Split by comma, strip whitespace, convert to uppercase
|
||||
symbols = [s.strip().upper() for s in raw_input.split(",") if s.strip()]
|
||||
return symbols if len(symbols) > 1 else symbols[0]
|
||||
|
||||
|
||||
def get_analysis_date():
|
||||
|
|
@ -743,6 +748,7 @@ def extract_content_string(content):
|
|||
return str(content)
|
||||
|
||||
def run_analysis():
|
||||
"""Run analysis for one or more ticker symbols."""
|
||||
# First get all user selections
|
||||
selections = get_user_selections()
|
||||
|
||||
|
|
@ -755,13 +761,33 @@ def run_analysis():
|
|||
config["backend_url"] = selections["backend_url"]
|
||||
config["llm_provider"] = selections["llm_provider"].lower()
|
||||
|
||||
# Initialize the graph
|
||||
# Normalize ticker(s) to list
|
||||
tickers = selections["ticker"] if isinstance(selections["ticker"], list) else [selections["ticker"]]
|
||||
|
||||
# Initialize the graph once and reuse for all symbols
|
||||
graph = TradingAgentsGraph(
|
||||
[analyst.value for analyst in selections["analysts"]], config=config, debug=True
|
||||
)
|
||||
|
||||
for i, ticker in enumerate(tickers, 1):
|
||||
if len(tickers) > 1:
|
||||
console.print(f"\n[bold cyan]{'═' * 50}[/bold cyan]")
|
||||
console.print(f"[bold cyan] Analyzing {ticker} ({i}/{len(tickers)})[/bold cyan]")
|
||||
console.print(f"[bold cyan]{'═' * 50}[/bold cyan]\n")
|
||||
|
||||
run_single_analysis(ticker, selections, config, graph)
|
||||
|
||||
if i < len(tickers):
|
||||
console.print(f"\n[dim]Moving to next symbol...[/dim]\n")
|
||||
|
||||
if len(tickers) > 1:
|
||||
console.print(f"\n[bold green]Completed analysis for all {len(tickers)} symbols: {', '.join(tickers)}[/bold green]")
|
||||
|
||||
|
||||
def run_single_analysis(ticker: str, selections: dict, config: dict, graph: TradingAgentsGraph):
|
||||
"""Run analysis for a single ticker symbol."""
|
||||
# Create result directory
|
||||
results_dir = Path(config["results_dir"]) / selections["ticker"] / selections["analysis_date"]
|
||||
results_dir = Path(config["results_dir"]) / ticker / selections["analysis_date"]
|
||||
results_dir.mkdir(parents=True, exist_ok=True)
|
||||
report_dir = results_dir / "reports"
|
||||
report_dir.mkdir(parents=True, exist_ok=True)
|
||||
|
|
@ -815,7 +841,7 @@ def run_analysis():
|
|||
update_display(layout)
|
||||
|
||||
# Add initial messages
|
||||
message_buffer.add_message("System", f"Selected ticker: {selections['ticker']}")
|
||||
message_buffer.add_message("System", f"Selected ticker: {ticker}")
|
||||
message_buffer.add_message(
|
||||
"System", f"Analysis date: {selections['analysis_date']}"
|
||||
)
|
||||
|
|
@ -842,13 +868,13 @@ def run_analysis():
|
|||
|
||||
# Create spinner text
|
||||
spinner_text = (
|
||||
f"Analyzing {selections['ticker']} on {selections['analysis_date']}..."
|
||||
f"Analyzing {ticker} on {selections['analysis_date']}..."
|
||||
)
|
||||
update_display(layout, spinner_text)
|
||||
|
||||
# Initialize state and get graph args
|
||||
init_agent_state = graph.propagator.create_initial_state(
|
||||
selections["ticker"], selections["analysis_date"]
|
||||
ticker, selections["analysis_date"]
|
||||
)
|
||||
args = graph.propagator.get_graph_args()
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue