feat: Add Trade Strategist node + SQLite checkpointing + .gitignore restore

- Add Trade Strategist agent (trade_strategist_node.py): generates 5
  actionable trade setups (Entry, SL, TP, R:R, Win%) after Portfolio Manager
- Wire Trade Strategist into LangGraph pipeline (setup.py)
- Add 'trade_possibilities' field to AgentState schema
- Initialize trade_possibilities in Propagator initial state
- Integrate SqliteSaver (langgraph-checkpoint-sqlite) for node-by-node
  state persistence to trading_agents_state.sqlite
- Add unique thread_id (ticker_date) to graph config for checkpoint isolation
- Update CLI (main.py) to display Trade Strategist progress + save report section
- Restore full standard Python .gitignore (200+ rules) stripped in prior PR
- Fix: convert trade_strategist_node to factory function (create_trade_strategist)
  to resolve LangGraph TypeError on missing 'llm' argument
- Fix: use sqlite3.connect() directly instead of SqliteSaver.from_conn_string()
  to avoid _GeneratorContextManager TypeError

.gitignore

@@ -1,9 +1,195 @@
-venv/
+# ============================
+# TradingAgents Custom Ignores
+# ============================
+
+# API Keys / Secrets
 .env
-__pycache__/
+.envrc
-*.egg-info/
+
+# Virtual environments
+venv/
+.venv
+env/
+ENV/
+env.bak/
+venv.bak/
+
+# Reports and results (generated output)
 reports/
 results/
+eval_results/
+
+# SQLite state database
+*.sqlite
+
+# ============================
+# Standard Python Ignores
+# ============================
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
 build/
+develop-eggs/
 dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# Pyenv
+.python-version
+
+# pipenv
+Pipfile.lock
+
+# poetry
+poetry.lock
+
+# pdm
+.pdm.toml
+.pdm-python
+.pdm-build/
+
+# PEP 582
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# Ruff
+.ruff_cache/
+
+# PyPI configuration file
+.pypirc
+
+# ============================
+# IDE / Editor Ignores
+# ============================
+
+# PyCharm
+.idea/
+
+# Visual Studio Code
+.vscode/
+
+# ============================
+# OS Ignores
+# ============================
+
+# macOS
 .DS_Store
+.AppleDouble
+.LSOverride
+
+# Windows
+Thumbs.db
+ehthumbs.db
+Desktop.ini
+$RECYCLE.BIN/
+
+# ============================
+# Cache / Data
+# ============================
+
+**/data_cache/
+.streamlit/secrets.toml

cli/main.py

@@ -46,7 +46,7 @@ class MessageBuffer:
         "Research Team": ["Bull Researcher", "Bear Researcher", "Research Manager"],
         "Trading Team": ["Trader"],
         "Risk Management": ["Aggressive Analyst", "Neutral Analyst", "Conservative Analyst"],
-        "Portfolio Management": ["Portfolio Manager"],
+        "Portfolio Management": ["Portfolio Manager", "Trade Strategist"],
     }
 
     # Analyst name mapping
@@ -68,6 +68,7 @@ class MessageBuffer:
         "investment_plan": (None, "Research Manager"),
         "trader_investment_plan": (None, "Trader"),
         "final_trade_decision": (None, "Portfolio Manager"),
+        "trade_possibilities": (None, "Trade Strategist"),
     }
 
     def __init__(self, max_length=100):
@@ -1046,8 +1047,11 @@ def run_analysis():
             selections["ticker"], selections["analysis_date"]
         )
         # Pass callbacks to graph config for tool execution tracking
-        # (LLM tracking is handled separately via LLM constructor)
+        args = graph.propagator.get_graph_args(
-        args = graph.propagator.get_graph_args(callbacks=[stats_handler])
+            selections["ticker"], 
+            selections["analysis_date"], 
+            callbacks=[stats_handler]
+        )
 
         # Stream the analysis
         trace = []
@@ -1148,6 +1152,15 @@ def run_analysis():
                         message_buffer.update_agent_status("Conservative Analyst", "completed")
                         message_buffer.update_agent_status("Neutral Analyst", "completed")
                         message_buffer.update_agent_status("Portfolio Manager", "completed")
+                        message_buffer.update_agent_status("Trade Strategist", "in_progress")
+
+            # Trade Strategist
+            if chunk.get("trade_possibilities"):
+                message_buffer.update_report_section(
+                    "trade_possibilities", chunk["trade_possibilities"]
+                )
+                if message_buffer.agent_status.get("Trade Strategist") != "completed":
+                    message_buffer.update_agent_status("Trade Strategist", "completed")
 
             # Update the display
             update_display(layout, stats_handler=stats_handler, start_time=start_time)

tradingagents/agents/trade_strategist_node.py

@@ -0,0 +1,55 @@
+from langchain_core.prompts import ChatPromptTemplate
+from tradingagents.agents.utils.agent_states import AgentState
+
+def create_trade_strategist(llm):
+    def trade_strategist_node(state: AgentState):
+        """
+        Agent that analyzes the final trade decision and outputs 5 distinct trade setups.
+        """
+        
+        prompt = ChatPromptTemplate.from_messages(
+            [
+                (
+                    "system",
+                    """You are an elite Trade Strategist at a premier quantitative hedge fund.
+Your job is to take the final consensus decision from the Portfolio Manager and the Trader's investment plan, and synthesize them into exactly 5 specific, actionable trade setups.
+
+For the given asset, you must provide exactly 5 trade possibilities with the following parameters explicitly defined for each:
+- Trade Direction (Long/Short, Options, etc.)
+- Entry Price / Condition (e.g., Buy at market, Limit buy at $X, Wait for breakout above $X)
+- Stop Loss (SL) (Specific price level)
+- Take Profit (TP) (Specific price level)
+- Risk/Reward Ratio
+- Estimated Win Percentage (Probability of success based on current technicals/fundamentals, e.g., 65%)
+- Brief Rationale (1-2 sentences explaining why this setup makes sense)
+
+Format your output as a clean, highly readable Markdown document.
+Do not output anything besides the 5 trades and a brief introductory/concluding sentence.
+Use bullet points and bold text for the parameters so they are easily scannable."""
+                ),
+                (
+                    "human",
+                    """Asset: {company}
+
+Portfolio Manager's Final Decision:
+{final_decision}
+
+Trader's Investment Plan:
+{trader_plan}
+
+Please formulate the 5 Trade Possibilities based on the above data."""
+                ),
+            ]
+        )
+
+        chain = prompt | llm
+
+        result = chain.invoke({
+            "company": state.get("company_of_interest", ""),
+            "final_decision": state.get("final_trade_decision", ""),
+            "trader_plan": state.get("trader_investment_plan", "")
+        })
+        
+        return {"trade_possibilities": result.content}
+        
+    return trade_strategist_node

tradingagents/agents/utils/agent_states.py

@@ -74,3 +74,6 @@ class AgentState(MessagesState):
         RiskDebateState, "Current state of the debate on evaluating risk"
     ]
     final_trade_decision: Annotated[str, "Final decision made by the Risk Analysts"]
+
+    # final strategies
+    trade_possibilities: Annotated[str, "5 Trade Possibilities with percentages, SL/TP"]

tradingagents/graph/propagation.py

@@ -11,7 +11,7 @@ from tradingagents.agents.utils.agent_states import (
 class Propagator:
     """Handles state initialization and propagation through the graph."""
 
-    def __init__(self, max_recur_limit=100):
+    def __init__(self, max_recur_limit=1000):
         """Initialize with configuration parameters."""
         self.max_recur_limit = max_recur_limit
 
@@ -51,16 +51,23 @@ class Propagator:
             "fundamentals_report": "",
             "sentiment_report": "",
             "news_report": "",
+            "trade_possibilities": "",
         }
 
-    def get_graph_args(self, callbacks: Optional[List] = None) -> Dict[str, Any]:
+    def get_graph_args(self, company_name: str, trade_date: str, callbacks: Optional[List] = None) -> Dict[str, Any]:
         """Get arguments for the graph invocation.
 
         Args:
+            company_name: The ticker being analyzed
+            trade_date: The date of analysis
             callbacks: Optional list of callback handlers for tool execution tracking.
                        Note: LLM callbacks are handled separately via LLM constructor.
         """
-        config = {"recursion_limit": self.max_recur_limit}
+        thread_id = f"{company_name}_{trade_date}"
+        config = {
+            "recursion_limit": self.max_recur_limit,
+            "configurable": {"thread_id": thread_id}
+        }
         if callbacks:
             config["callbacks"] = callbacks
         return {

tradingagents/graph/setup.py

@@ -2,11 +2,15 @@
 
 from typing import Dict, Any
 from langchain_openai import ChatOpenAI
+
 from langgraph.graph import END, StateGraph, START
 from langgraph.prebuilt import ToolNode
+import sqlite3
+from langgraph.checkpoint.sqlite import SqliteSaver
 
 from tradingagents.agents import *
 from tradingagents.agents.utils.agent_states import AgentState
+from tradingagents.agents.trade_strategist_node import create_trade_strategist
 
 from .conditional_logic import ConditionalLogic
 
@@ -104,6 +108,7 @@ class GraphSetup:
         portfolio_manager_node = create_portfolio_manager(
             self.deep_thinking_llm, self.portfolio_manager_memory
         )
+        trade_strategist_node = create_trade_strategist(self.quick_thinking_llm)
 
         # Create workflow
         workflow = StateGraph(AgentState)
@@ -125,6 +130,7 @@ class GraphSetup:
         workflow.add_node("Neutral Analyst", neutral_analyst)
         workflow.add_node("Conservative Analyst", conservative_analyst)
         workflow.add_node("Portfolio Manager", portfolio_manager_node)
+        workflow.add_node("Trade Strategist", trade_strategist_node)
 
         # Define edges
         # Start with the first analyst
@@ -196,7 +202,10 @@ class GraphSetup:
             },
         )
 
-        workflow.add_edge("Portfolio Manager", END)
+        workflow.add_edge("Portfolio Manager", "Trade Strategist")
+        workflow.add_edge("Trade Strategist", END)
 
-        # Compile and return
+        # Compile and return with SQLite memory
-        return workflow.compile()
+        conn = sqlite3.connect("trading_agents_state.sqlite", check_same_thread=False)
+        memory = SqliteSaver(conn)
+        return workflow.compile(checkpointer=memory)

tradingagents/graph/trading_graph.py

@@ -200,7 +200,7 @@ class TradingAgentsGraph:
         init_agent_state = self.propagator.create_initial_state(
             company_name, trade_date
         )
-        args = self.propagator.get_graph_args()
+        args = self.propagator.get_graph_args(company_name, trade_date)
 
         if self.debug:
             # Debug mode with tracing
@@ -256,6 +256,7 @@ class TradingAgentsGraph:
             },
             "investment_plan": final_state["investment_plan"],
             "final_trade_decision": final_state["final_trade_decision"],
+            "trade_possibilities": final_state.get("trade_possibilities", ""),
         }
 
         # Save to file