chore(release): v0.1.0 – initial public release of TradingAgents

cli/models.py

@@ -0,0 +1,10 @@
+from enum import Enum
+from typing import List, Optional, Dict
+from pydantic import BaseModel
+
+
+class AnalystType(str, Enum):
+    MARKET = "market"
+    SOCIAL = "social"
+    NEWS = "news"
+    FUNDAMENTALS = "fundamentals"

cli/static/welcome.txt

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+
+  ______               ___             ___                    __      
+ /_  __/________ _____/ (_)___  ____ _/   | ____ ____  ____  / /______
+  / / / ___/ __ `/ __  / / __ \/ __ `/ /| |/ __ `/ _ \/ __ \/ __/ ___/
+ / / / /  / /_/ / /_/ / / / / / /_/ / ___ / /_/ /  __/ / / / /_(__  ) 
+/_/ /_/   \__,_/\__,_/_/_/ /_/\__, /_/  |_\__, /\___/_/ /_/\__/____/  
+                             /____/      /____/                       

cli/utils.py

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+import questionary
+from typing import List, Optional, Tuple, Dict
+
+from cli.models import AnalystType
+
+ANALYST_ORDER = [
+    ("Market Analyst", AnalystType.MARKET),
+    ("Social Media Analyst", AnalystType.SOCIAL),
+    ("News Analyst", AnalystType.NEWS),
+    ("Fundamentals Analyst", AnalystType.FUNDAMENTALS),
+]
+
+
+def get_ticker() -> str:
+    """Prompt the user to enter a ticker symbol."""
+    ticker = questionary.text(
+        "Enter the ticker symbol to analyze:",
+        validate=lambda x: len(x.strip()) > 0 or "Please enter a valid ticker symbol.",
+        style=questionary.Style(
+            [
+                ("text", "fg:green"),
+                ("highlighted", "noinherit"),
+            ]
+        ),
+    ).ask()
+
+    if not ticker:
+        console.print("\n[red]No ticker symbol provided. Exiting...[/red]")
+        exit(1)
+
+    return ticker.strip().upper()
+
+
+def get_analysis_date() -> str:
+    """Prompt the user to enter a date in YYYY-MM-DD format."""
+    import re
+    from datetime import datetime
+
+    def validate_date(date_str: str) -> bool:
+        if not re.match(r"^\d{4}-\d{2}-\d{2}$", date_str):
+            return False
+        try:
+            datetime.strptime(date_str, "%Y-%m-%d")
+            return True
+        except ValueError:
+            return False
+
+    date = questionary.text(
+        "Enter the analysis date (YYYY-MM-DD):",
+        validate=lambda x: validate_date(x.strip())
+        or "Please enter a valid date in YYYY-MM-DD format.",
+        style=questionary.Style(
+            [
+                ("text", "fg:green"),
+                ("highlighted", "noinherit"),
+            ]
+        ),
+    ).ask()
+
+    if not date:
+        console.print("\n[red]No date provided. Exiting...[/red]")
+        exit(1)
+
+    return date.strip()
+
+
+def select_analysts() -> List[AnalystType]:
+    """Select analysts using an interactive checkbox."""
+    choices = questionary.checkbox(
+        "Select Your [Analysts Team]:",
+        choices=[
+            questionary.Choice(display, value=value) for display, value in ANALYST_ORDER
+        ],
+        instruction="\n- Press Space to select/unselect analysts\n- Press 'a' to select/unselect all\n- Press Enter when done",
+        validate=lambda x: len(x) > 0 or "You must select at least one analyst.",
+        style=questionary.Style(
+            [
+                ("checkbox-selected", "fg:green"),
+                ("selected", "fg:green noinherit"),
+                ("highlighted", "noinherit"),
+                ("pointer", "noinherit"),
+            ]
+        ),
+    ).ask()
+
+    if not choices:
+        console.print("\n[red]No analysts selected. Exiting...[/red]")
+        exit(1)
+
+    return choices
+
+
+def select_research_depth() -> int:
+    """Select research depth using an interactive selection."""
+
+    # Define research depth options with their corresponding values
+    DEPTH_OPTIONS = [
+        ("Shallow - Quick research, few debate and strategy discussion rounds", 1),
+        ("Medium - Middle ground, moderate debate rounds and strategy discussion", 3),
+        ("Deep - Comprehensive research, in depth debate and strategy discussion", 5),
+    ]
+
+    choice = questionary.select(
+        "Select Your [Research Depth]:",
+        choices=[
+            questionary.Choice(display, value=value) for display, value in DEPTH_OPTIONS
+        ],
+        instruction="\n- Use arrow keys to navigate\n- Press Enter to select",
+        style=questionary.Style(
+            [
+                ("selected", "fg:yellow noinherit"),
+                ("highlighted", "fg:yellow noinherit"),
+                ("pointer", "fg:yellow noinherit"),
+            ]
+        ),
+    ).ask()
+
+    if choice is None:
+        console.print("\n[red]No research depth selected. Exiting...[/red]")
+        exit(1)
+
+    return choice
+
+
+def select_shallow_thinking_agent() -> str:
+    """Select shallow thinking llm engine using an interactive selection."""
+
+    # Define shallow thinking llm engine options with their corresponding model names
+    SHALLOW_AGENT_OPTIONS = [
+        ("GPT-4o-mini - Fast and efficient for quick tasks", "gpt-4o-mini"),
+        ("GPT-4.1-nano - Ultra-lightweight model for basic operations", "gpt-4.1-nano"),
+        ("GPT-4.1-mini - Compact model with good performance", "gpt-4.1-mini"),
+        ("GPT-4o - Standard model with solid capabilities", "gpt-4o"),
+    ]
+
+    choice = questionary.select(
+        "Select Your [Quick-Thinking LLM Engine]:",
+        choices=[
+            questionary.Choice(display, value=value)
+            for display, value in SHALLOW_AGENT_OPTIONS
+        ],
+        instruction="\n- Use arrow keys to navigate\n- Press Enter to select",
+        style=questionary.Style(
+            [
+                ("selected", "fg:magenta noinherit"),
+                ("highlighted", "fg:magenta noinherit"),
+                ("pointer", "fg:magenta noinherit"),
+            ]
+        ),
+    ).ask()
+
+    if choice is None:
+        console.print(
+            "\n[red]No shallow thinking llm engine selected. Exiting...[/red]"
+        )
+        exit(1)
+
+    return choice
+
+
+def select_deep_thinking_agent() -> str:
+    """Select deep thinking llm engine using an interactive selection."""
+
+    # Define deep thinking llm engine options with their corresponding model names
+    DEEP_AGENT_OPTIONS = [
+        ("GPT-4.1-nano - Ultra-lightweight model for basic operations", "gpt-4.1-nano"),
+        ("GPT-4.1-mini - Compact model with good performance", "gpt-4.1-mini"),
+        ("GPT-4o - Standard model with solid capabilities", "gpt-4o"),
+        ("o4-mini - Specialized reasoning model (compact)", "o4-mini"),
+        ("o3-mini - Advanced reasoning model (lightweight)", "o3-mini"),
+        ("o3 - Full advanced reasoning model", "o3"),
+        ("o1 - Premier reasoning and problem-solving model", "o1"),
+    ]
+
+    choice = questionary.select(
+        "Select Your [Deep-Thinking LLM Engine]:",
+        choices=[
+            questionary.Choice(display, value=value)
+            for display, value in DEEP_AGENT_OPTIONS
+        ],
+        instruction="\n- Use arrow keys to navigate\n- Press Enter to select",
+        style=questionary.Style(
+            [
+                ("selected", "fg:magenta noinherit"),
+                ("highlighted", "fg:magenta noinherit"),
+                ("pointer", "fg:magenta noinherit"),
+            ]
+        ),
+    ).ask()
+
+    if choice is None:
+        console.print("\n[red]No deep thinking llm engine selected. Exiting...[/red]")
+        exit(1)
+
+    return choice