1241 lines
50 KiB
Python
1241 lines
50 KiB
Python
from typing import Optional
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import datetime
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import typer
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from pathlib import Path
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from functools import wraps
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from rich.console import Console
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from dotenv import load_dotenv
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# Load environment variables from .env file
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load_dotenv()
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from rich.panel import Panel
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from rich.spinner import Spinner
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from rich.live import Live
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from rich.columns import Columns
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from rich.markdown import Markdown
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from rich.layout import Layout
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from rich.text import Text
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from rich.table import Table
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from collections import deque
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import time
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from rich.tree import Tree
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from rich import box
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from rich.align import Align
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from rich.rule import Rule
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from tradingagents.graph.trading_graph import TradingAgentsGraph
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from tradingagents.custom_prompt import (
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CUSTOM_PROMPT_SECTION_TITLE,
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CUSTOM_PROMPT_STATUS_LABEL,
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)
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from tradingagents.default_config import DEFAULT_CONFIG
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from cli.models import AnalystType
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from cli.utils import *
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from cli.announcements import fetch_announcements, display_announcements
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from cli.stats_handler import StatsCallbackHandler
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console = Console()
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app = typer.Typer(
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name="TradingAgents",
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help="TradingAgents CLI: Multi-Agents LLM Financial Trading Framework",
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add_completion=True, # Enable shell completion
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)
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# Create a deque to store recent messages with a maximum length
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class MessageBuffer:
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# Fixed teams that always run (not user-selectable)
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FIXED_AGENTS = {
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"Research Team": ["Bull Researcher", "Bear Researcher", "Research Manager"],
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"Trading Team": ["Trader"],
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"Risk Management": ["Aggressive Analyst", "Neutral Analyst", "Conservative Analyst"],
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"Portfolio Management": ["Portfolio Manager"],
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}
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# Analyst name mapping
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ANALYST_MAPPING = {
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"market": "Market Analyst",
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"social": "Social Analyst",
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"news": "News Analyst",
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"fundamentals": "Fundamentals Analyst",
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}
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# Report section mapping: section -> (analyst_key for filtering, finalizing_agent)
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# analyst_key: which analyst selection controls this section (None = always included)
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# finalizing_agent: which agent must be "completed" for this report to count as done
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REPORT_SECTIONS = {
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"market_report": ("market", "Market Analyst"),
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"sentiment_report": ("social", "Social Analyst"),
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"news_report": ("news", "News Analyst"),
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"fundamentals_report": ("fundamentals", "Fundamentals Analyst"),
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"investment_plan": (None, "Research Manager"),
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"trader_investment_plan": (None, "Trader"),
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"final_trade_decision": (None, "Portfolio Manager"),
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}
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def __init__(self, max_length=100):
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self.messages = deque(maxlen=max_length)
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self.tool_calls = deque(maxlen=max_length)
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self.current_report = None
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self.final_report = None # Store the complete final report
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self.agent_status = {}
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self.current_agent = None
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self.report_sections = {}
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self.selected_analysts = []
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self._last_message_id = None
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def init_for_analysis(self, selected_analysts):
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"""Initialize agent status and report sections based on selected analysts.
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Args:
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selected_analysts: List of analyst type strings (e.g., ["market", "news"])
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"""
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self.selected_analysts = [a.lower() for a in selected_analysts]
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# Build agent_status dynamically
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self.agent_status = {}
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# Add selected analysts
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for analyst_key in self.selected_analysts:
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if analyst_key in self.ANALYST_MAPPING:
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self.agent_status[self.ANALYST_MAPPING[analyst_key]] = "pending"
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# Add fixed teams
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for team_agents in self.FIXED_AGENTS.values():
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for agent in team_agents:
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self.agent_status[agent] = "pending"
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# Build report_sections dynamically
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self.report_sections = {}
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for section, (analyst_key, _) in self.REPORT_SECTIONS.items():
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if analyst_key is None or analyst_key in self.selected_analysts:
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self.report_sections[section] = None
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# Reset other state
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self.current_report = None
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self.final_report = None
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self.current_agent = None
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self.messages.clear()
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self.tool_calls.clear()
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self._last_message_id = None
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def get_completed_reports_count(self):
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"""Count reports that are finalized (their finalizing agent is completed).
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A report is considered complete when:
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1. The report section has content (not None), AND
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2. The agent responsible for finalizing that report has status "completed"
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This prevents interim updates (like debate rounds) from counting as completed.
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"""
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count = 0
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for section in self.report_sections:
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if section not in self.REPORT_SECTIONS:
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continue
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_, finalizing_agent = self.REPORT_SECTIONS[section]
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# Report is complete if it has content AND its finalizing agent is done
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has_content = self.report_sections.get(section) is not None
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agent_done = self.agent_status.get(finalizing_agent) == "completed"
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if has_content and agent_done:
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count += 1
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return count
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def add_message(self, message_type, content):
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timestamp = datetime.datetime.now().strftime("%H:%M:%S")
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self.messages.append((timestamp, message_type, content))
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def add_tool_call(self, tool_name, args):
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timestamp = datetime.datetime.now().strftime("%H:%M:%S")
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self.tool_calls.append((timestamp, tool_name, args))
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def update_agent_status(self, agent, status):
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if agent in self.agent_status:
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self.agent_status[agent] = status
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self.current_agent = agent
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def update_report_section(self, section_name, content):
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if section_name in self.report_sections:
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self.report_sections[section_name] = content
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self._update_current_report()
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def _update_current_report(self):
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# For the panel display, only show the most recently updated section
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latest_section = None
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latest_content = None
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# Find the most recently updated section
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for section, content in self.report_sections.items():
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if content is not None:
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latest_section = section
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latest_content = content
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if latest_section and latest_content:
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# Format the current section for display
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section_titles = {
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"market_report": "Market Analysis",
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"sentiment_report": "Social Sentiment",
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"news_report": "News Analysis",
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"fundamentals_report": "Fundamentals Analysis",
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"investment_plan": "Research Team Decision",
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"trader_investment_plan": "Trading Team Plan",
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"final_trade_decision": "Portfolio Management Decision",
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}
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self.current_report = (
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f"### {section_titles[latest_section]}\n{latest_content}"
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)
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# Update the final complete report
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self._update_final_report()
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def _update_final_report(self):
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report_parts = []
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# Analyst Team Reports - use .get() to handle missing sections
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analyst_sections = ["market_report", "sentiment_report", "news_report", "fundamentals_report"]
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if any(self.report_sections.get(section) for section in analyst_sections):
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report_parts.append("## Analyst Team Reports")
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if self.report_sections.get("market_report"):
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report_parts.append(
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f"### Market Analysis\n{self.report_sections['market_report']}"
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)
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if self.report_sections.get("sentiment_report"):
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report_parts.append(
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f"### Social Sentiment\n{self.report_sections['sentiment_report']}"
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)
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if self.report_sections.get("news_report"):
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report_parts.append(
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f"### News Analysis\n{self.report_sections['news_report']}"
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)
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if self.report_sections.get("fundamentals_report"):
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report_parts.append(
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f"### Fundamentals Analysis\n{self.report_sections['fundamentals_report']}"
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)
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# Research Team Reports
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if self.report_sections.get("investment_plan"):
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report_parts.append("## Research Team Decision")
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report_parts.append(f"{self.report_sections['investment_plan']}")
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# Trading Team Reports
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if self.report_sections.get("trader_investment_plan"):
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report_parts.append("## Trading Team Plan")
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report_parts.append(f"{self.report_sections['trader_investment_plan']}")
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# Portfolio Management Decision
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if self.report_sections.get("final_trade_decision"):
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report_parts.append("## Portfolio Management Decision")
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report_parts.append(f"{self.report_sections['final_trade_decision']}")
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self.final_report = "\n\n".join(report_parts) if report_parts else None
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message_buffer = MessageBuffer()
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def create_layout():
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layout = Layout()
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layout.split_column(
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Layout(name="header", size=3),
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Layout(name="main"),
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Layout(name="footer", size=3),
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)
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layout["main"].split_column(
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Layout(name="upper", ratio=3), Layout(name="analysis", ratio=5)
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)
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layout["upper"].split_row(
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Layout(name="progress", ratio=2), Layout(name="messages", ratio=3)
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)
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return layout
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def format_tokens(n):
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"""Format token count for display."""
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if n >= 1000:
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return f"{n/1000:.1f}k"
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return str(n)
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def update_display(layout, spinner_text=None, stats_handler=None, start_time=None):
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# Header with welcome message
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layout["header"].update(
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Panel(
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"[bold green]Welcome to TradingAgents CLI[/bold green]\n"
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"[dim]© [Tauric Research](https://github.com/TauricResearch)[/dim]",
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title="Welcome to TradingAgents",
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border_style="green",
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padding=(1, 2),
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expand=True,
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)
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)
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# Progress panel showing agent status
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progress_table = Table(
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show_header=True,
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header_style="bold magenta",
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show_footer=False,
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box=box.SIMPLE_HEAD, # Use simple header with horizontal lines
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title=None, # Remove the redundant Progress title
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padding=(0, 2), # Add horizontal padding
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expand=True, # Make table expand to fill available space
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)
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progress_table.add_column("Team", style="cyan", justify="center", width=20)
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progress_table.add_column("Agent", style="green", justify="center", width=20)
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progress_table.add_column("Status", style="yellow", justify="center", width=20)
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# Group agents by team - filter to only include agents in agent_status
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all_teams = {
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"Analyst Team": [
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"Market Analyst",
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"Social Analyst",
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"News Analyst",
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"Fundamentals Analyst",
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],
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"Research Team": ["Bull Researcher", "Bear Researcher", "Research Manager"],
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"Trading Team": ["Trader"],
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"Risk Management": ["Aggressive Analyst", "Neutral Analyst", "Conservative Analyst"],
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"Portfolio Management": ["Portfolio Manager"],
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}
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# Filter teams to only include agents that are in agent_status
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teams = {}
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for team, agents in all_teams.items():
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active_agents = [a for a in agents if a in message_buffer.agent_status]
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if active_agents:
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teams[team] = active_agents
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for team, agents in teams.items():
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# Add first agent with team name
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first_agent = agents[0]
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status = message_buffer.agent_status.get(first_agent, "pending")
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if status == "in_progress":
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spinner = Spinner(
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"dots", text="[blue]in_progress[/blue]", style="bold cyan"
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)
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status_cell = spinner
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else:
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status_color = {
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"pending": "yellow",
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"completed": "green",
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"error": "red",
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}.get(status, "white")
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status_cell = f"[{status_color}]{status}[/{status_color}]"
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progress_table.add_row(team, first_agent, status_cell)
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# Add remaining agents in team
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for agent in agents[1:]:
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status = message_buffer.agent_status.get(agent, "pending")
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if status == "in_progress":
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spinner = Spinner(
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"dots", text="[blue]in_progress[/blue]", style="bold cyan"
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)
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status_cell = spinner
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else:
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status_color = {
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"pending": "yellow",
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"completed": "green",
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"error": "red",
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}.get(status, "white")
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status_cell = f"[{status_color}]{status}[/{status_color}]"
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progress_table.add_row("", agent, status_cell)
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# Add horizontal line after each team
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progress_table.add_row("─" * 20, "─" * 20, "─" * 20, style="dim")
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layout["progress"].update(
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Panel(progress_table, title="Progress", border_style="cyan", padding=(1, 2))
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)
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# Messages panel showing recent messages and tool calls
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messages_table = Table(
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show_header=True,
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header_style="bold magenta",
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show_footer=False,
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expand=True, # Make table expand to fill available space
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box=box.MINIMAL, # Use minimal box style for a lighter look
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show_lines=True, # Keep horizontal lines
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padding=(0, 1), # Add some padding between columns
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)
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messages_table.add_column("Time", style="cyan", width=8, justify="center")
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messages_table.add_column("Type", style="green", width=10, justify="center")
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messages_table.add_column(
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"Content", style="white", no_wrap=False, ratio=1
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) # Make content column expand
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# Combine tool calls and messages
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all_messages = []
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# Add tool calls
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for timestamp, tool_name, args in message_buffer.tool_calls:
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formatted_args = format_tool_args(args)
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all_messages.append((timestamp, "Tool", f"{tool_name}: {formatted_args}"))
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# Add regular messages
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for timestamp, msg_type, content in message_buffer.messages:
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content_str = str(content) if content else ""
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if len(content_str) > 200:
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content_str = content_str[:197] + "..."
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all_messages.append((timestamp, msg_type, content_str))
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# Sort by timestamp descending (newest first)
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all_messages.sort(key=lambda x: x[0], reverse=True)
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# Calculate how many messages we can show based on available space
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max_messages = 12
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# Get the first N messages (newest ones)
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recent_messages = all_messages[:max_messages]
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# Add messages to table (already in newest-first order)
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for timestamp, msg_type, content in recent_messages:
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# Format content with word wrapping
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wrapped_content = Text(content, overflow="fold")
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messages_table.add_row(timestamp, msg_type, wrapped_content)
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layout["messages"].update(
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Panel(
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messages_table,
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title="Messages & Tools",
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border_style="blue",
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padding=(1, 2),
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)
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)
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# Analysis panel showing current report
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if message_buffer.current_report:
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layout["analysis"].update(
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Panel(
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Markdown(message_buffer.current_report),
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title="Current Report",
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border_style="green",
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padding=(1, 2),
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)
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)
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else:
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layout["analysis"].update(
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Panel(
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"[italic]Waiting for analysis report...[/italic]",
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title="Current Report",
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border_style="green",
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padding=(1, 2),
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)
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)
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# Footer with statistics
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# Agent progress - derived from agent_status dict
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agents_completed = sum(
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1 for status in message_buffer.agent_status.values() if status == "completed"
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)
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agents_total = len(message_buffer.agent_status)
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# Report progress - based on agent completion (not just content existence)
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reports_completed = message_buffer.get_completed_reports_count()
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reports_total = len(message_buffer.report_sections)
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|
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# Build stats parts
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stats_parts = [f"Agents: {agents_completed}/{agents_total}"]
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# LLM and tool stats from callback handler
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if stats_handler:
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stats = stats_handler.get_stats()
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stats_parts.append(f"LLM: {stats['llm_calls']}")
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stats_parts.append(f"Tools: {stats['tool_calls']}")
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# Token display with graceful fallback
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if stats["tokens_in"] > 0 or stats["tokens_out"] > 0:
|
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tokens_str = f"Tokens: {format_tokens(stats['tokens_in'])}\u2191 {format_tokens(stats['tokens_out'])}\u2193"
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else:
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tokens_str = "Tokens: --"
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stats_parts.append(tokens_str)
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stats_parts.append(f"Reports: {reports_completed}/{reports_total}")
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|
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# Elapsed time
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if start_time:
|
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elapsed = time.time() - start_time
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elapsed_str = f"\u23f1 {int(elapsed // 60):02d}:{int(elapsed % 60):02d}"
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stats_parts.append(elapsed_str)
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|
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stats_table = Table(show_header=False, box=None, padding=(0, 2), expand=True)
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stats_table.add_column("Stats", justify="center")
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stats_table.add_row(" | ".join(stats_parts))
|
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|
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layout["footer"].update(Panel(stats_table, border_style="grey50"))
|
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|
|
|
|
def get_user_selections():
|
|
"""Get all user selections before starting the analysis display."""
|
|
# Display ASCII art welcome message
|
|
with open(Path(__file__).parent / "static" / "welcome.txt", "r") as f:
|
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welcome_ascii = f.read()
|
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|
|
# Create welcome box content
|
|
welcome_content = f"{welcome_ascii}\n"
|
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welcome_content += "[bold green]TradingAgents: Multi-Agents LLM Financial Trading Framework - CLI[/bold green]\n\n"
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welcome_content += "[bold]Workflow Steps:[/bold]\n"
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welcome_content += "I. Analyst Team → II. Research Team → III. Trader → IV. Risk Management → V. Portfolio Management\n\n"
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welcome_content += (
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"[dim]Built by [Tauric Research](https://github.com/TauricResearch)[/dim]"
|
|
)
|
|
|
|
# Create and center the welcome box
|
|
welcome_box = Panel(
|
|
welcome_content,
|
|
border_style="green",
|
|
padding=(1, 2),
|
|
title="Welcome to TradingAgents",
|
|
subtitle="Multi-Agents LLM Financial Trading Framework",
|
|
)
|
|
console.print(Align.center(welcome_box))
|
|
console.print()
|
|
console.print() # Add vertical space before announcements
|
|
|
|
# Fetch and display announcements (silent on failure)
|
|
announcements = fetch_announcements()
|
|
display_announcements(console, announcements)
|
|
|
|
# Create a boxed questionnaire for each step
|
|
def create_question_box(title, prompt, default=None):
|
|
box_content = f"[bold]{title}[/bold]\n"
|
|
box_content += f"[dim]{prompt}[/dim]"
|
|
if default:
|
|
box_content += f"\n[dim]Default: {default}[/dim]"
|
|
return Panel(box_content, border_style="blue", padding=(1, 2))
|
|
|
|
# Step 1: Ticker symbol
|
|
console.print(
|
|
create_question_box(
|
|
"Step 1: Ticker Symbol",
|
|
"Enter the exact ticker symbol to analyze, including exchange suffix when needed (examples: SPY, CNC.TO, 7203.T, 0700.HK)",
|
|
"SPY",
|
|
)
|
|
)
|
|
selected_ticker = get_ticker()
|
|
|
|
# Step 2: Analysis date
|
|
default_date = datetime.datetime.now().strftime("%Y-%m-%d")
|
|
console.print(
|
|
create_question_box(
|
|
"Step 2: Analysis Date",
|
|
"Enter the analysis date (YYYY-MM-DD)",
|
|
default_date,
|
|
)
|
|
)
|
|
analysis_date = get_analysis_date()
|
|
|
|
# Step 3: Optional custom prompt
|
|
console.print(
|
|
create_question_box(
|
|
"Step 3: Custom Prompt",
|
|
"Optionally add run-specific instructions such as short-term/long-term horizon, only new positions, or risks to emphasize"
|
|
)
|
|
)
|
|
custom_prompt = ask_custom_prompt()
|
|
|
|
# Step 4: Output language
|
|
console.print(
|
|
create_question_box(
|
|
"Step 4: Output Language",
|
|
"Select the language for analyst reports and final decision"
|
|
)
|
|
)
|
|
output_language = ask_output_language()
|
|
|
|
# Step 5: Select analysts
|
|
console.print(
|
|
create_question_box(
|
|
"Step 5: Analysts Team", "Select your LLM analyst agents for the analysis"
|
|
)
|
|
)
|
|
selected_analysts = select_analysts()
|
|
console.print(
|
|
f"[green]Selected analysts:[/green] {', '.join(analyst.value for analyst in selected_analysts)}"
|
|
)
|
|
|
|
# Step 6: Research depth
|
|
console.print(
|
|
create_question_box(
|
|
"Step 6: Research Depth", "Select your research depth level"
|
|
)
|
|
)
|
|
selected_research_depth = select_research_depth()
|
|
|
|
# Step 7: LLM Provider
|
|
console.print(
|
|
create_question_box(
|
|
"Step 7: LLM Provider", "Select your LLM provider"
|
|
)
|
|
)
|
|
selected_llm_provider, backend_url = select_llm_provider()
|
|
|
|
# Step 8: Thinking agents
|
|
console.print(
|
|
create_question_box(
|
|
"Step 8: Thinking Agents", "Select your thinking agents for analysis"
|
|
)
|
|
)
|
|
selected_shallow_thinker = select_shallow_thinking_agent(selected_llm_provider)
|
|
selected_deep_thinker = select_deep_thinking_agent(selected_llm_provider)
|
|
|
|
# Step 9: Provider-specific thinking configuration
|
|
thinking_level = None
|
|
reasoning_effort = None
|
|
anthropic_effort = None
|
|
|
|
provider_lower = selected_llm_provider.lower()
|
|
if provider_lower == "google":
|
|
console.print(
|
|
create_question_box(
|
|
"Step 9: Thinking Mode",
|
|
"Configure Gemini thinking mode"
|
|
)
|
|
)
|
|
thinking_level = ask_gemini_thinking_config()
|
|
elif provider_lower == "openai":
|
|
console.print(
|
|
create_question_box(
|
|
"Step 9: Reasoning Effort",
|
|
"Configure OpenAI reasoning effort level"
|
|
)
|
|
)
|
|
reasoning_effort = ask_openai_reasoning_effort()
|
|
elif provider_lower == "anthropic":
|
|
console.print(
|
|
create_question_box(
|
|
"Step 9: Effort Level",
|
|
"Configure Claude effort level"
|
|
)
|
|
)
|
|
anthropic_effort = ask_anthropic_effort()
|
|
|
|
return {
|
|
"ticker": selected_ticker,
|
|
"analysis_date": analysis_date,
|
|
"custom_prompt": custom_prompt,
|
|
"analysts": selected_analysts,
|
|
"research_depth": selected_research_depth,
|
|
"llm_provider": selected_llm_provider.lower(),
|
|
"backend_url": backend_url,
|
|
"shallow_thinker": selected_shallow_thinker,
|
|
"deep_thinker": selected_deep_thinker,
|
|
"google_thinking_level": thinking_level,
|
|
"openai_reasoning_effort": reasoning_effort,
|
|
"anthropic_effort": anthropic_effort,
|
|
"output_language": output_language,
|
|
}
|
|
|
|
|
|
def get_ticker():
|
|
"""Get ticker symbol from user input."""
|
|
return typer.prompt("", default="SPY")
|
|
|
|
|
|
def get_analysis_date():
|
|
"""Get the analysis date from user input."""
|
|
while True:
|
|
date_str = typer.prompt(
|
|
"", default=datetime.datetime.now().strftime("%Y-%m-%d")
|
|
)
|
|
try:
|
|
# Validate date format and ensure it's not in the future
|
|
analysis_date = datetime.datetime.strptime(date_str, "%Y-%m-%d")
|
|
if analysis_date.date() > datetime.datetime.now().date():
|
|
console.print("[red]Error: Analysis date cannot be in the future[/red]")
|
|
continue
|
|
return date_str
|
|
except ValueError:
|
|
console.print(
|
|
"[red]Error: Invalid date format. Please use YYYY-MM-DD[/red]"
|
|
)
|
|
|
|
|
|
def save_report_to_disk(final_state, ticker: str, save_path: Path):
|
|
"""Save complete analysis report to disk with organized subfolders."""
|
|
save_path.mkdir(parents=True, exist_ok=True)
|
|
sections = []
|
|
|
|
# 1. Analysts
|
|
analysts_dir = save_path / "1_analysts"
|
|
analyst_parts = []
|
|
if final_state.get("market_report"):
|
|
analysts_dir.mkdir(exist_ok=True)
|
|
(analysts_dir / "market.md").write_text(final_state["market_report"])
|
|
analyst_parts.append(("Market Analyst", final_state["market_report"]))
|
|
if final_state.get("sentiment_report"):
|
|
analysts_dir.mkdir(exist_ok=True)
|
|
(analysts_dir / "sentiment.md").write_text(final_state["sentiment_report"])
|
|
analyst_parts.append(("Social Analyst", final_state["sentiment_report"]))
|
|
if final_state.get("news_report"):
|
|
analysts_dir.mkdir(exist_ok=True)
|
|
(analysts_dir / "news.md").write_text(final_state["news_report"])
|
|
analyst_parts.append(("News Analyst", final_state["news_report"]))
|
|
if final_state.get("fundamentals_report"):
|
|
analysts_dir.mkdir(exist_ok=True)
|
|
(analysts_dir / "fundamentals.md").write_text(final_state["fundamentals_report"])
|
|
analyst_parts.append(("Fundamentals Analyst", final_state["fundamentals_report"]))
|
|
if analyst_parts:
|
|
content = "\n\n".join(f"### {name}\n{text}" for name, text in analyst_parts)
|
|
sections.append(f"## I. Analyst Team Reports\n\n{content}")
|
|
|
|
# 2. Research
|
|
if final_state.get("investment_debate_state"):
|
|
research_dir = save_path / "2_research"
|
|
debate = final_state["investment_debate_state"]
|
|
research_parts = []
|
|
if debate.get("bull_history"):
|
|
research_dir.mkdir(exist_ok=True)
|
|
(research_dir / "bull.md").write_text(debate["bull_history"])
|
|
research_parts.append(("Bull Researcher", debate["bull_history"]))
|
|
if debate.get("bear_history"):
|
|
research_dir.mkdir(exist_ok=True)
|
|
(research_dir / "bear.md").write_text(debate["bear_history"])
|
|
research_parts.append(("Bear Researcher", debate["bear_history"]))
|
|
if debate.get("judge_decision"):
|
|
research_dir.mkdir(exist_ok=True)
|
|
(research_dir / "manager.md").write_text(debate["judge_decision"])
|
|
research_parts.append(("Research Manager", debate["judge_decision"]))
|
|
if research_parts:
|
|
content = "\n\n".join(f"### {name}\n{text}" for name, text in research_parts)
|
|
sections.append(f"## II. Research Team Decision\n\n{content}")
|
|
|
|
# 3. Trading
|
|
if final_state.get("trader_investment_plan"):
|
|
trading_dir = save_path / "3_trading"
|
|
trading_dir.mkdir(exist_ok=True)
|
|
(trading_dir / "trader.md").write_text(final_state["trader_investment_plan"])
|
|
sections.append(f"## III. Trading Team Plan\n\n### Trader\n{final_state['trader_investment_plan']}")
|
|
|
|
# 4. Risk Management
|
|
if final_state.get("risk_debate_state"):
|
|
risk_dir = save_path / "4_risk"
|
|
risk = final_state["risk_debate_state"]
|
|
risk_parts = []
|
|
if risk.get("aggressive_history"):
|
|
risk_dir.mkdir(exist_ok=True)
|
|
(risk_dir / "aggressive.md").write_text(risk["aggressive_history"])
|
|
risk_parts.append(("Aggressive Analyst", risk["aggressive_history"]))
|
|
if risk.get("conservative_history"):
|
|
risk_dir.mkdir(exist_ok=True)
|
|
(risk_dir / "conservative.md").write_text(risk["conservative_history"])
|
|
risk_parts.append(("Conservative Analyst", risk["conservative_history"]))
|
|
if risk.get("neutral_history"):
|
|
risk_dir.mkdir(exist_ok=True)
|
|
(risk_dir / "neutral.md").write_text(risk["neutral_history"])
|
|
risk_parts.append(("Neutral Analyst", risk["neutral_history"]))
|
|
if risk_parts:
|
|
content = "\n\n".join(f"### {name}\n{text}" for name, text in risk_parts)
|
|
sections.append(f"## IV. Risk Management Team Decision\n\n{content}")
|
|
|
|
# 5. Portfolio Manager
|
|
if risk.get("judge_decision"):
|
|
portfolio_dir = save_path / "5_portfolio"
|
|
portfolio_dir.mkdir(exist_ok=True)
|
|
(portfolio_dir / "decision.md").write_text(risk["judge_decision"])
|
|
sections.append(f"## V. Portfolio Manager Decision\n\n### Portfolio Manager\n{risk['judge_decision']}")
|
|
|
|
# Write consolidated report
|
|
header = f"# Trading Analysis Report: {ticker}\n\nGenerated: {datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n"
|
|
if final_state.get("custom_prompt"):
|
|
header += f"## {CUSTOM_PROMPT_SECTION_TITLE}\n\n{final_state['custom_prompt']}\n\n"
|
|
(save_path / "complete_report.md").write_text(header + "\n\n".join(sections))
|
|
return save_path / "complete_report.md"
|
|
|
|
|
|
def display_complete_report(final_state):
|
|
"""Display the complete analysis report sequentially (avoids truncation)."""
|
|
console.print()
|
|
console.print(Rule("Complete Analysis Report", style="bold green"))
|
|
|
|
if final_state.get("custom_prompt"):
|
|
console.print(
|
|
Panel(
|
|
Markdown(final_state["custom_prompt"]),
|
|
title=CUSTOM_PROMPT_SECTION_TITLE,
|
|
border_style="magenta",
|
|
padding=(1, 2),
|
|
)
|
|
)
|
|
|
|
# I. Analyst Team Reports
|
|
analysts = []
|
|
if final_state.get("market_report"):
|
|
analysts.append(("Market Analyst", final_state["market_report"]))
|
|
if final_state.get("sentiment_report"):
|
|
analysts.append(("Social Analyst", final_state["sentiment_report"]))
|
|
if final_state.get("news_report"):
|
|
analysts.append(("News Analyst", final_state["news_report"]))
|
|
if final_state.get("fundamentals_report"):
|
|
analysts.append(("Fundamentals Analyst", final_state["fundamentals_report"]))
|
|
if analysts:
|
|
console.print(Panel("[bold]I. Analyst Team Reports[/bold]", border_style="cyan"))
|
|
for title, content in analysts:
|
|
console.print(Panel(Markdown(content), title=title, border_style="blue", padding=(1, 2)))
|
|
|
|
# II. Research Team Reports
|
|
if final_state.get("investment_debate_state"):
|
|
debate = final_state["investment_debate_state"]
|
|
research = []
|
|
if debate.get("bull_history"):
|
|
research.append(("Bull Researcher", debate["bull_history"]))
|
|
if debate.get("bear_history"):
|
|
research.append(("Bear Researcher", debate["bear_history"]))
|
|
if debate.get("judge_decision"):
|
|
research.append(("Research Manager", debate["judge_decision"]))
|
|
if research:
|
|
console.print(Panel("[bold]II. Research Team Decision[/bold]", border_style="magenta"))
|
|
for title, content in research:
|
|
console.print(Panel(Markdown(content), title=title, border_style="blue", padding=(1, 2)))
|
|
|
|
# III. Trading Team
|
|
if final_state.get("trader_investment_plan"):
|
|
console.print(Panel("[bold]III. Trading Team Plan[/bold]", border_style="yellow"))
|
|
console.print(Panel(Markdown(final_state["trader_investment_plan"]), title="Trader", border_style="blue", padding=(1, 2)))
|
|
|
|
# IV. Risk Management Team
|
|
if final_state.get("risk_debate_state"):
|
|
risk = final_state["risk_debate_state"]
|
|
risk_reports = []
|
|
if risk.get("aggressive_history"):
|
|
risk_reports.append(("Aggressive Analyst", risk["aggressive_history"]))
|
|
if risk.get("conservative_history"):
|
|
risk_reports.append(("Conservative Analyst", risk["conservative_history"]))
|
|
if risk.get("neutral_history"):
|
|
risk_reports.append(("Neutral Analyst", risk["neutral_history"]))
|
|
if risk_reports:
|
|
console.print(Panel("[bold]IV. Risk Management Team Decision[/bold]", border_style="red"))
|
|
for title, content in risk_reports:
|
|
console.print(Panel(Markdown(content), title=title, border_style="blue", padding=(1, 2)))
|
|
|
|
# V. Portfolio Manager Decision
|
|
if risk.get("judge_decision"):
|
|
console.print(Panel("[bold]V. Portfolio Manager Decision[/bold]", border_style="green"))
|
|
console.print(Panel(Markdown(risk["judge_decision"]), title="Portfolio Manager", border_style="blue", padding=(1, 2)))
|
|
|
|
|
|
def update_research_team_status(status):
|
|
"""Update status for research team members (not Trader)."""
|
|
research_team = ["Bull Researcher", "Bear Researcher", "Research Manager"]
|
|
for agent in research_team:
|
|
message_buffer.update_agent_status(agent, status)
|
|
|
|
|
|
# Ordered list of analysts for status transitions
|
|
ANALYST_ORDER = ["market", "social", "news", "fundamentals"]
|
|
ANALYST_AGENT_NAMES = {
|
|
"market": "Market Analyst",
|
|
"social": "Social Analyst",
|
|
"news": "News Analyst",
|
|
"fundamentals": "Fundamentals Analyst",
|
|
}
|
|
ANALYST_REPORT_MAP = {
|
|
"market": "market_report",
|
|
"social": "sentiment_report",
|
|
"news": "news_report",
|
|
"fundamentals": "fundamentals_report",
|
|
}
|
|
|
|
|
|
def update_analyst_statuses(message_buffer, chunk):
|
|
"""Update analyst statuses based on accumulated report state.
|
|
|
|
Logic:
|
|
- Store new report content from the current chunk if present
|
|
- Check accumulated report_sections (not just current chunk) for status
|
|
- Analysts with reports = completed
|
|
- First analyst without report = in_progress
|
|
- Remaining analysts without reports = pending
|
|
- When all analysts done, set Bull Researcher to in_progress
|
|
"""
|
|
selected = message_buffer.selected_analysts
|
|
found_active = False
|
|
|
|
for analyst_key in ANALYST_ORDER:
|
|
if analyst_key not in selected:
|
|
continue
|
|
|
|
agent_name = ANALYST_AGENT_NAMES[analyst_key]
|
|
report_key = ANALYST_REPORT_MAP[analyst_key]
|
|
|
|
# Capture new report content from current chunk
|
|
if chunk.get(report_key):
|
|
message_buffer.update_report_section(report_key, chunk[report_key])
|
|
|
|
# Determine status from accumulated sections, not just current chunk
|
|
has_report = bool(message_buffer.report_sections.get(report_key))
|
|
|
|
if has_report:
|
|
message_buffer.update_agent_status(agent_name, "completed")
|
|
elif not found_active:
|
|
message_buffer.update_agent_status(agent_name, "in_progress")
|
|
found_active = True
|
|
else:
|
|
message_buffer.update_agent_status(agent_name, "pending")
|
|
|
|
# When all analysts complete, transition research team to in_progress
|
|
if not found_active and selected:
|
|
if message_buffer.agent_status.get("Bull Researcher") == "pending":
|
|
message_buffer.update_agent_status("Bull Researcher", "in_progress")
|
|
|
|
def extract_content_string(content):
|
|
"""Extract string content from various message formats.
|
|
Returns None if no meaningful text content is found.
|
|
"""
|
|
import ast
|
|
|
|
def is_empty(val):
|
|
"""Check if value is empty using Python's truthiness."""
|
|
if val is None or val == '':
|
|
return True
|
|
if isinstance(val, str):
|
|
s = val.strip()
|
|
if not s:
|
|
return True
|
|
try:
|
|
return not bool(ast.literal_eval(s))
|
|
except (ValueError, SyntaxError):
|
|
return False # Can't parse = real text
|
|
return not bool(val)
|
|
|
|
if is_empty(content):
|
|
return None
|
|
|
|
if isinstance(content, str):
|
|
return content.strip()
|
|
|
|
if isinstance(content, dict):
|
|
text = content.get('text', '')
|
|
return text.strip() if not is_empty(text) else None
|
|
|
|
if isinstance(content, list):
|
|
text_parts = [
|
|
item.get('text', '').strip() if isinstance(item, dict) and item.get('type') == 'text'
|
|
else (item.strip() if isinstance(item, str) else '')
|
|
for item in content
|
|
]
|
|
result = ' '.join(t for t in text_parts if t and not is_empty(t))
|
|
return result if result else None
|
|
|
|
return str(content).strip() if not is_empty(content) else None
|
|
|
|
|
|
def classify_message_type(message) -> tuple[str, str | None]:
|
|
"""Classify LangChain message into display type and extract content.
|
|
|
|
Returns:
|
|
(type, content) - type is one of: User, Agent, Data, Control
|
|
- content is extracted string or None
|
|
"""
|
|
from langchain_core.messages import AIMessage, HumanMessage, ToolMessage
|
|
|
|
content = extract_content_string(getattr(message, 'content', None))
|
|
|
|
if isinstance(message, HumanMessage):
|
|
if content and content.strip() == "Continue":
|
|
return ("Control", content)
|
|
return ("User", content)
|
|
|
|
if isinstance(message, ToolMessage):
|
|
return ("Data", content)
|
|
|
|
if isinstance(message, AIMessage):
|
|
return ("Agent", content)
|
|
|
|
# Fallback for unknown types
|
|
return ("System", content)
|
|
|
|
|
|
def format_tool_args(args, max_length=80) -> str:
|
|
"""Format tool arguments for terminal display."""
|
|
result = str(args)
|
|
if len(result) > max_length:
|
|
return result[:max_length - 3] + "..."
|
|
return result
|
|
|
|
def run_analysis():
|
|
# First get all user selections
|
|
selections = get_user_selections()
|
|
|
|
# Create config with selected research depth
|
|
config = DEFAULT_CONFIG.copy()
|
|
config["max_debate_rounds"] = selections["research_depth"]
|
|
config["max_risk_discuss_rounds"] = selections["research_depth"]
|
|
config["quick_think_llm"] = selections["shallow_thinker"]
|
|
config["deep_think_llm"] = selections["deep_thinker"]
|
|
config["backend_url"] = selections["backend_url"]
|
|
config["llm_provider"] = selections["llm_provider"].lower()
|
|
# Provider-specific thinking configuration
|
|
config["google_thinking_level"] = selections.get("google_thinking_level")
|
|
config["openai_reasoning_effort"] = selections.get("openai_reasoning_effort")
|
|
config["anthropic_effort"] = selections.get("anthropic_effort")
|
|
config["output_language"] = selections.get("output_language", "English")
|
|
|
|
# Create stats callback handler for tracking LLM/tool calls
|
|
stats_handler = StatsCallbackHandler()
|
|
|
|
# Normalize analyst selection to predefined order (selection is a 'set', order is fixed)
|
|
selected_set = {analyst.value for analyst in selections["analysts"]}
|
|
selected_analyst_keys = [a for a in ANALYST_ORDER if a in selected_set]
|
|
|
|
# Initialize the graph with callbacks bound to LLMs
|
|
graph = TradingAgentsGraph(
|
|
selected_analyst_keys,
|
|
config=config,
|
|
debug=True,
|
|
callbacks=[stats_handler],
|
|
)
|
|
|
|
# Initialize message buffer with selected analysts
|
|
message_buffer.init_for_analysis(selected_analyst_keys)
|
|
|
|
# Track start time for elapsed display
|
|
start_time = time.time()
|
|
|
|
# Create result directory
|
|
results_dir = Path(config["results_dir"]) / selections["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)
|
|
log_file = results_dir / "message_tool.log"
|
|
log_file.touch(exist_ok=True)
|
|
|
|
def save_message_decorator(obj, func_name):
|
|
func = getattr(obj, func_name)
|
|
@wraps(func)
|
|
def wrapper(*args, **kwargs):
|
|
func(*args, **kwargs)
|
|
timestamp, message_type, content = obj.messages[-1]
|
|
content = content.replace("\n", " ") # Replace newlines with spaces
|
|
with open(log_file, "a") as f:
|
|
f.write(f"{timestamp} [{message_type}] {content}\n")
|
|
return wrapper
|
|
|
|
def save_tool_call_decorator(obj, func_name):
|
|
func = getattr(obj, func_name)
|
|
@wraps(func)
|
|
def wrapper(*args, **kwargs):
|
|
func(*args, **kwargs)
|
|
timestamp, tool_name, args = obj.tool_calls[-1]
|
|
args_str = ", ".join(f"{k}={v}" for k, v in args.items())
|
|
with open(log_file, "a") as f:
|
|
f.write(f"{timestamp} [Tool Call] {tool_name}({args_str})\n")
|
|
return wrapper
|
|
|
|
def save_report_section_decorator(obj, func_name):
|
|
func = getattr(obj, func_name)
|
|
@wraps(func)
|
|
def wrapper(section_name, content):
|
|
func(section_name, content)
|
|
if section_name in obj.report_sections and obj.report_sections[section_name] is not None:
|
|
content = obj.report_sections[section_name]
|
|
if content:
|
|
file_name = f"{section_name}.md"
|
|
text = "\n".join(str(item) for item in content) if isinstance(content, list) else content
|
|
with open(report_dir / file_name, "w") as f:
|
|
f.write(text)
|
|
return wrapper
|
|
|
|
message_buffer.add_message = save_message_decorator(message_buffer, "add_message")
|
|
message_buffer.add_tool_call = save_tool_call_decorator(message_buffer, "add_tool_call")
|
|
message_buffer.update_report_section = save_report_section_decorator(message_buffer, "update_report_section")
|
|
|
|
# Now start the display layout
|
|
layout = create_layout()
|
|
|
|
with Live(layout, refresh_per_second=4) as live:
|
|
# Initial display
|
|
update_display(layout, stats_handler=stats_handler, start_time=start_time)
|
|
|
|
# Add initial messages
|
|
message_buffer.add_message("System", f"Selected ticker: {selections['ticker']}")
|
|
message_buffer.add_message(
|
|
"System", f"Analysis date: {selections['analysis_date']}"
|
|
)
|
|
if selections.get("custom_prompt"):
|
|
message_buffer.add_message(
|
|
"System", f"{CUSTOM_PROMPT_STATUS_LABEL}: {selections['custom_prompt']}"
|
|
)
|
|
message_buffer.add_message(
|
|
"System",
|
|
f"Selected analysts: {', '.join(analyst.value for analyst in selections['analysts'])}",
|
|
)
|
|
update_display(layout, stats_handler=stats_handler, start_time=start_time)
|
|
|
|
# Update agent status to in_progress for the first analyst
|
|
first_analyst = f"{selections['analysts'][0].value.capitalize()} Analyst"
|
|
message_buffer.update_agent_status(first_analyst, "in_progress")
|
|
update_display(layout, stats_handler=stats_handler, start_time=start_time)
|
|
|
|
# Create spinner text
|
|
spinner_text = (
|
|
f"Analyzing {selections['ticker']} on {selections['analysis_date']}..."
|
|
)
|
|
update_display(layout, spinner_text, stats_handler=stats_handler, start_time=start_time)
|
|
|
|
# Initialize state and get graph args with callbacks
|
|
init_agent_state = graph.propagator.create_initial_state(
|
|
selections["ticker"],
|
|
selections["analysis_date"],
|
|
selections.get("custom_prompt"),
|
|
)
|
|
# Pass callbacks to graph config for tool execution tracking
|
|
# (LLM tracking is handled separately via LLM constructor)
|
|
args = graph.propagator.get_graph_args(callbacks=[stats_handler])
|
|
|
|
# Stream the analysis
|
|
trace = []
|
|
for chunk in graph.graph.stream(init_agent_state, **args):
|
|
# Process messages if present (skip duplicates via message ID)
|
|
if len(chunk["messages"]) > 0:
|
|
last_message = chunk["messages"][-1]
|
|
msg_id = getattr(last_message, "id", None)
|
|
|
|
if msg_id != message_buffer._last_message_id:
|
|
message_buffer._last_message_id = msg_id
|
|
|
|
# Add message to buffer
|
|
msg_type, content = classify_message_type(last_message)
|
|
if content and content.strip():
|
|
message_buffer.add_message(msg_type, content)
|
|
|
|
# Handle tool calls
|
|
if hasattr(last_message, "tool_calls") and last_message.tool_calls:
|
|
for tool_call in last_message.tool_calls:
|
|
if isinstance(tool_call, dict):
|
|
message_buffer.add_tool_call(
|
|
tool_call["name"], tool_call["args"]
|
|
)
|
|
else:
|
|
message_buffer.add_tool_call(tool_call.name, tool_call.args)
|
|
|
|
# Update analyst statuses based on report state (runs on every chunk)
|
|
update_analyst_statuses(message_buffer, chunk)
|
|
|
|
# Research Team - Handle Investment Debate State
|
|
if chunk.get("investment_debate_state"):
|
|
debate_state = chunk["investment_debate_state"]
|
|
bull_hist = debate_state.get("bull_history", "").strip()
|
|
bear_hist = debate_state.get("bear_history", "").strip()
|
|
judge = debate_state.get("judge_decision", "").strip()
|
|
|
|
# Only update status when there's actual content
|
|
if bull_hist or bear_hist:
|
|
update_research_team_status("in_progress")
|
|
if bull_hist:
|
|
message_buffer.update_report_section(
|
|
"investment_plan", f"### Bull Researcher Analysis\n{bull_hist}"
|
|
)
|
|
if bear_hist:
|
|
message_buffer.update_report_section(
|
|
"investment_plan", f"### Bear Researcher Analysis\n{bear_hist}"
|
|
)
|
|
if judge:
|
|
message_buffer.update_report_section(
|
|
"investment_plan", f"### Research Manager Decision\n{judge}"
|
|
)
|
|
update_research_team_status("completed")
|
|
message_buffer.update_agent_status("Trader", "in_progress")
|
|
|
|
# Trading Team
|
|
if chunk.get("trader_investment_plan"):
|
|
message_buffer.update_report_section(
|
|
"trader_investment_plan", chunk["trader_investment_plan"]
|
|
)
|
|
if message_buffer.agent_status.get("Trader") != "completed":
|
|
message_buffer.update_agent_status("Trader", "completed")
|
|
message_buffer.update_agent_status("Aggressive Analyst", "in_progress")
|
|
|
|
# Risk Management Team - Handle Risk Debate State
|
|
if chunk.get("risk_debate_state"):
|
|
risk_state = chunk["risk_debate_state"]
|
|
agg_hist = risk_state.get("aggressive_history", "").strip()
|
|
con_hist = risk_state.get("conservative_history", "").strip()
|
|
neu_hist = risk_state.get("neutral_history", "").strip()
|
|
judge = risk_state.get("judge_decision", "").strip()
|
|
|
|
if agg_hist:
|
|
if message_buffer.agent_status.get("Aggressive Analyst") != "completed":
|
|
message_buffer.update_agent_status("Aggressive Analyst", "in_progress")
|
|
message_buffer.update_report_section(
|
|
"final_trade_decision", f"### Aggressive Analyst Analysis\n{agg_hist}"
|
|
)
|
|
if con_hist:
|
|
if message_buffer.agent_status.get("Conservative Analyst") != "completed":
|
|
message_buffer.update_agent_status("Conservative Analyst", "in_progress")
|
|
message_buffer.update_report_section(
|
|
"final_trade_decision", f"### Conservative Analyst Analysis\n{con_hist}"
|
|
)
|
|
if neu_hist:
|
|
if message_buffer.agent_status.get("Neutral Analyst") != "completed":
|
|
message_buffer.update_agent_status("Neutral Analyst", "in_progress")
|
|
message_buffer.update_report_section(
|
|
"final_trade_decision", f"### Neutral Analyst Analysis\n{neu_hist}"
|
|
)
|
|
if judge:
|
|
if message_buffer.agent_status.get("Portfolio Manager") != "completed":
|
|
message_buffer.update_agent_status("Portfolio Manager", "in_progress")
|
|
message_buffer.update_report_section(
|
|
"final_trade_decision", f"### Portfolio Manager Decision\n{judge}"
|
|
)
|
|
message_buffer.update_agent_status("Aggressive Analyst", "completed")
|
|
message_buffer.update_agent_status("Conservative Analyst", "completed")
|
|
message_buffer.update_agent_status("Neutral Analyst", "completed")
|
|
message_buffer.update_agent_status("Portfolio Manager", "completed")
|
|
|
|
# Update the display
|
|
update_display(layout, stats_handler=stats_handler, start_time=start_time)
|
|
|
|
trace.append(chunk)
|
|
|
|
# Get final state and decision
|
|
final_state = trace[-1]
|
|
decision = graph.process_signal(final_state["final_trade_decision"])
|
|
|
|
# Update all agent statuses to completed
|
|
for agent in message_buffer.agent_status:
|
|
message_buffer.update_agent_status(agent, "completed")
|
|
|
|
message_buffer.add_message(
|
|
"System", f"Completed analysis for {selections['analysis_date']}"
|
|
)
|
|
|
|
# Update final report sections
|
|
for section in message_buffer.report_sections.keys():
|
|
if section in final_state:
|
|
message_buffer.update_report_section(section, final_state[section])
|
|
|
|
update_display(layout, stats_handler=stats_handler, start_time=start_time)
|
|
|
|
# Post-analysis prompts (outside Live context for clean interaction)
|
|
console.print("\n[bold cyan]Analysis Complete![/bold cyan]\n")
|
|
|
|
# Prompt to save report
|
|
save_choice = typer.prompt("Save report?", default="Y").strip().upper()
|
|
if save_choice in ("Y", "YES", ""):
|
|
timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
|
|
default_path = Path.cwd() / "reports" / f"{selections['ticker']}_{timestamp}"
|
|
save_path_str = typer.prompt(
|
|
"Save path (press Enter for default)",
|
|
default=str(default_path)
|
|
).strip()
|
|
save_path = Path(save_path_str)
|
|
try:
|
|
report_file = save_report_to_disk(final_state, selections["ticker"], save_path)
|
|
console.print(f"\n[green]✓ Report saved to:[/green] {save_path.resolve()}")
|
|
console.print(f" [dim]Complete report:[/dim] {report_file.name}")
|
|
except Exception as e:
|
|
console.print(f"[red]Error saving report: {e}[/red]")
|
|
|
|
# Prompt to display full report
|
|
display_choice = typer.prompt("\nDisplay full report on screen?", default="Y").strip().upper()
|
|
if display_choice in ("Y", "YES", ""):
|
|
display_complete_report(final_state)
|
|
|
|
|
|
@app.command()
|
|
def analyze():
|
|
run_analysis()
|
|
|
|
|
|
if __name__ == "__main__":
|
|
app()
|