- enable a new output option in HTML format.
This commit is contained in:
adalard
parent
b9a3a2dbcc
commit
f350b32825
73
cli/main.py
73
cli/main.py
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@ -24,6 +24,40 @@ from dotenv import load_dotenv
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# Load API keys from .env
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load_dotenv()
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# HTML output template and converter
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HTML_TEMPLATE = """<!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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<title>{title}</title>
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<style>
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body {{ font-family: Arial, sans-serif; margin: 40px; }}
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h1,h2,h3,h4 {{ color: #2c3e50; }}
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table {{ border-collapse: collapse; width: 100%; margin-bottom: 20px; }}
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th, td {{ border: 1px solid #ddd; padding: 8px; }}
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th {{ background-color: #f2f2f2; text-align: left; }}
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a {{ color: #3498db; text-decoration: none; }}
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a:hover {{ text-decoration: underline; }}
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</style>
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</head>
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<body>
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{content}
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</body>
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</html>"""
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def md_to_html(md_text: str) -> str:
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"""Convert Markdown text to HTML, dynamically importing markdown."""
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try:
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import markdown
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except ImportError:
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raise RuntimeError(
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"HTML output requires the 'markdown' package. Please install it with `pip install markdown`."
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)
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return markdown.markdown(md_text, extensions=["tables", "fenced_code"])
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from tradingagents.graph.trading_graph import TradingAgentsGraph
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from tradingagents.default_config import DEFAULT_CONFIG
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from cli.models import AnalystType
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@ -484,6 +518,15 @@ def get_user_selections():
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selected_shallow_thinker = select_shallow_thinking_agent(selected_llm_provider)
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selected_deep_thinker = select_deep_thinking_agent(selected_llm_provider)
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console.print(
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create_question_box(
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"Step 7: Output Format", "Choose output format (Markdown or HTML)", "Markdown"
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)
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)
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selected_output_format = select_output_format()
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console.print(f"[green]Selected output format:[/green] {selected_output_format.upper()}")
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return {
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"ticker": selected_ticker,
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"analysis_date": analysis_date,
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@ -493,6 +536,7 @@ def get_user_selections():
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"backend_url": backend_url,
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"shallow_thinker": selected_shallow_thinker,
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"deep_thinker": selected_deep_thinker,
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"output_format": selected_output_format,
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}
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@ -738,6 +782,7 @@ def extract_content_string(content):
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def run_analysis():
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# First get all user selections
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selections = get_user_selections()
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output_format = selections["output_format"]
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# Create config with selected research depth
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config = DEFAULT_CONFIG.copy()
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@ -791,9 +836,15 @@ def run_analysis():
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if section_name in obj.report_sections and obj.report_sections[section_name] is not None:
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content = obj.report_sections[section_name]
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if content:
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file_name = f"{section_name}.md"
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with open(report_dir / file_name, "w", encoding="utf-8") as f:
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f.write(content)
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if output_format == "md":
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file_name = f"{section_name}.md"
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with open(report_dir / file_name, "w", encoding="utf-8") as f:
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f.write(content)
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else:
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file_name = f"{section_name}.html"
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html_body = md_to_html(content)
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with open(report_dir / file_name, "w", encoding="utf-8") as f:
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f.write(HTML_TEMPLATE.format(title=section_name.replace('_',' ').title(), content=html_body))
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return wrapper
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message_buffer.add_message = save_message_decorator(message_buffer, "add_message")
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@ -1099,6 +1150,22 @@ def run_analysis():
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update_display(layout)
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# Generate HTML index if HTML output selected
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if output_format == "html":
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# Convert final decision markdown to HTML
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decision_md = message_buffer.report_sections.get("final_trade_decision", "")
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decision_html = md_to_html(decision_md)
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# Build links list
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links = ""
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for section, content in message_buffer.report_sections.items():
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if section != "final_trade_decision" and content:
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filename = f"{section}.html"
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display_name = section.replace("_", " ").title()
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links += f'<li><a href="{filename}">{display_name}</a></li>'
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index_body = f"{decision_html}<h2>Other Reports</h2><ul>{links}</ul>"
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with open(report_dir / "index.html", "w", encoding="utf-8") as f:
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f.write(HTML_TEMPLATE.format(title="TradingAgents Report", content=index_body))
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@app.command()
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def analyze():
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24
cli/utils.py
24
cli/utils.py
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@ -1,4 +1,6 @@
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import questionary
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from rich.console import Console
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console = Console()
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from typing import List, Optional, Tuple, Dict
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from cli.models import AnalystType
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@ -239,6 +241,28 @@ def select_deep_thinking_agent(provider) -> str:
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return choice
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def select_output_format() -> str:
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"""Prompt the user to choose output format (Markdown or HTML)."""
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choice = questionary.select(
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"Select output format:",
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choices=[
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questionary.Choice("Markdown", "md"),
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questionary.Choice("HTML", "html"),
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],
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instruction="\n- Use arrow keys to navigate\n- Press Enter to select",
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style=questionary.Style(
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[
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("selected", "fg:cyan noinherit"),
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("highlighted", "fg:cyan noinherit"),
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("pointer", "noinherit"),
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]
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),
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).ask()
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if choice is None:
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console.print("\n[red]No output format selected. Exiting...[/red]")
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exit(1)
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return choice
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def select_llm_provider() -> tuple[str, str]:
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"""Select the OpenAI api url using interactive selection."""
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# Define OpenAI api options with their corresponding endpoints
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@ -24,3 +24,4 @@ rich
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questionary
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langchain_anthropic
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langchain-google-genai
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markdown
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