refactor: remove stale imports, use configurable results path (#499)

tradingagents/agents/analysts/fundamentals_analyst.py

@@ -1,6 +1,4 @@
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
-import time
-import json
 from tradingagents.agents.utils.agent_utils import (
     build_instrument_context,
     get_balance_sheet,

tradingagents/agents/analysts/market_analyst.py

@@ -1,6 +1,4 @@
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
-import time
-import json
 from tradingagents.agents.utils.agent_utils import (
     build_instrument_context,
     get_indicators,

tradingagents/agents/analysts/news_analyst.py

@@ -1,6 +1,4 @@
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
-import time
-import json
 from tradingagents.agents.utils.agent_utils import (
     build_instrument_context,
     get_global_news,

tradingagents/agents/analysts/social_media_analyst.py

@@ -1,6 +1,4 @@
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
-import time
-import json
 from tradingagents.agents.utils.agent_utils import build_instrument_context, get_language_instruction, get_news
 from tradingagents.dataflows.config import get_config
 

tradingagents/agents/managers/research_manager.py

@@ -1,5 +1,3 @@
-import time
-import json
 
 from tradingagents.agents.utils.agent_utils import build_instrument_context
 

tradingagents/agents/researchers/bear_researcher.py

@@ -1,6 +1,3 @@
-from langchain_core.messages import AIMessage
-import time
-import json
 
 
 def create_bear_researcher(llm, memory):

tradingagents/agents/researchers/bull_researcher.py

@@ -1,6 +1,3 @@
-from langchain_core.messages import AIMessage
-import time
-import json
 
 
 def create_bull_researcher(llm, memory):

tradingagents/agents/risk_mgmt/aggressive_debator.py

@@ -1,5 +1,3 @@
-import time
-import json
 
 
 def create_aggressive_debator(llm):

tradingagents/agents/risk_mgmt/conservative_debator.py

@@ -1,6 +1,3 @@
-from langchain_core.messages import AIMessage
-import time
-import json
 
 
 def create_conservative_debator(llm):

tradingagents/agents/risk_mgmt/neutral_debator.py

@@ -1,5 +1,3 @@
-import time
-import json
 
 
 def create_neutral_debator(llm):

tradingagents/agents/trader/trader.py

@@ -1,6 +1,4 @@
 import functools
-import time
-import json
 
 from tradingagents.agents.utils.agent_utils import build_instrument_context
 

tradingagents/agents/utils/agent_states.py

@@ -1,10 +1,6 @@
-from typing import Annotated, Sequence
-from datetime import date, timedelta, datetime
-from typing_extensions import TypedDict, Optional
-from langchain_openai import ChatOpenAI
-from tradingagents.agents import *
-from langgraph.prebuilt import ToolNode
-from langgraph.graph import END, StateGraph, START, MessagesState
+from typing import Annotated
+from typing_extensions import TypedDict
+from langgraph.graph import MessagesState
 
 
 # Researcher team state

tradingagents/graph/reflection.py

@@ -1,13 +1,12 @@
 # TradingAgents/graph/reflection.py
 
-from typing import Dict, Any
-from langchain_openai import ChatOpenAI
+from typing import Any, Dict
 
 
 class Reflector:
     """Handles reflection on decisions and updating memory."""
 
-    def __init__(self, quick_thinking_llm: ChatOpenAI):
+    def __init__(self, quick_thinking_llm: Any):
         """Initialize the reflector with an LLM."""
         self.quick_thinking_llm = quick_thinking_llm
         self.reflection_system_prompt = self._get_reflection_prompt()

tradingagents/graph/setup.py

@@ -1,8 +1,7 @@
 # TradingAgents/graph/setup.py
 
-from typing import Dict, Any
-from langchain_openai import ChatOpenAI
-from langgraph.graph import END, StateGraph, START
+from typing import Any, Dict
+from langgraph.graph import END, START, StateGraph
 from langgraph.prebuilt import ToolNode
 
 from tradingagents.agents import *
@@ -16,8 +15,8 @@ class GraphSetup:
 
     def __init__(
         self,
-        quick_thinking_llm: ChatOpenAI,
-        deep_thinking_llm: ChatOpenAI,
+        quick_thinking_llm: Any,
+        deep_thinking_llm: Any,
         tool_nodes: Dict[str, ToolNode],
         bull_memory,
         bear_memory,

tradingagents/graph/signal_processing.py

@@ -1,12 +1,12 @@
 # TradingAgents/graph/signal_processing.py
 
-from langchain_openai import ChatOpenAI
+from typing import Any
 
 
 class SignalProcessor:
     """Processes trading signals to extract actionable decisions."""
 
-    def __init__(self, quick_thinking_llm: ChatOpenAI):
+    def __init__(self, quick_thinking_llm: Any):
         """Initialize with an LLM for processing."""
         self.quick_thinking_llm = quick_thinking_llm
 

tradingagents/graph/trading_graph.py

@@ -259,15 +259,12 @@ class TradingAgentsGraph:
         }
 
         # Save to file
-        directory = Path(f"eval_results/{self.ticker}/TradingAgentsStrategy_logs/")
+        directory = Path(self.config["results_dir"]) / self.ticker / "TradingAgentsStrategy_logs"
         directory.mkdir(parents=True, exist_ok=True)
 
-        with open(
-            f"eval_results/{self.ticker}/TradingAgentsStrategy_logs/full_states_log_{trade_date}.json",
-            "w",
-            encoding="utf-8",
-        ) as f:
-            json.dump(self.log_states_dict, f, indent=4)
+        log_path = directory / f"full_states_log_{trade_date}.json"
+        with open(log_path, "w", encoding="utf-8") as f:
+            json.dump(self.log_states_dict[str(trade_date)], f, indent=4)
 
     def reflect_and_remember(self, returns_losses):
         """Reflect on decisions and update memory based on returns."""