Updates for variable LLM types

.env.txt

@@ -0,0 +1,10 @@
+FINN_HUB_API_KEY = cea18mqad3i831op604gcea18mqad3i831op6050
+
+
+
+
+
+
+
+
+

tradingagents/graph/reflection.py

@@ -1,13 +1,18 @@
 # TradingAgents/graph/reflection.py
 
-from typing import Dict, Any
+from typing import Dict, Any, Union
 from langchain_openai import ChatOpenAI
+from langchain_anthropic import ChatAnthropic
+from langchain_google_genai import ChatGoogleGenerativeAI
+
+# Type alias for supported LLM types
+LLMType = Union[ChatOpenAI, ChatAnthropic, ChatGoogleGenerativeAI]
 
 
 class Reflector:
     """Handles reflection on decisions and updating memory."""
 
-    def __init__(self, quick_thinking_llm: ChatOpenAI):
+    def __init__(self, quick_thinking_llm: LLMType):
         """Initialize the reflector with an LLM."""
         self.quick_thinking_llm = quick_thinking_llm
         self.reflection_system_prompt = self._get_reflection_prompt()
@@ -68,7 +73,7 @@ Adhere strictly to these instructions, and ensure your output is detailed, accur
         ]
 
         result = self.quick_thinking_llm.invoke(messages).content
-        return result
+        return str(result)
 
     def reflect_bull_researcher(self, current_state, returns_losses, bull_memory):
         """Reflect on bull researcher's analysis and update memory."""

tradingagents/graph/setup.py

@@ -1,7 +1,9 @@
 # TradingAgents/graph/setup.py
 
-from typing import Dict, Any
+from typing import Dict, Any, Union
 from langchain_openai import ChatOpenAI
+from langchain_anthropic import ChatAnthropic
+from langchain_google_genai import ChatGoogleGenerativeAI
 from langgraph.graph import END, StateGraph, START
 from langgraph.prebuilt import ToolNode
 
@@ -11,14 +13,17 @@ from tradingagents.agents.utils.agent_utils import Toolkit
 
 from .conditional_logic import ConditionalLogic
 
+# Type alias for supported LLM types
+LLMType = Union[ChatOpenAI, ChatAnthropic, ChatGoogleGenerativeAI]
+
 
 class GraphSetup:
     """Handles the setup and configuration of the agent graph."""
 
     def __init__(
         self,
-        quick_thinking_llm: ChatOpenAI,
-        deep_thinking_llm: ChatOpenAI,
+        quick_thinking_llm: LLMType,
+        deep_thinking_llm: LLMType,
         toolkit: Toolkit,
         tool_nodes: Dict[str, ToolNode],
         bull_memory,

tradingagents/graph/signal_processing.py

@@ -1,12 +1,18 @@
 # TradingAgents/graph/signal_processing.py
 
+from typing import Union
 from langchain_openai import ChatOpenAI
+from langchain_anthropic import ChatAnthropic
+from langchain_google_genai import ChatGoogleGenerativeAI
+
+# Type alias for supported LLM types
+LLMType = Union[ChatOpenAI, ChatAnthropic, ChatGoogleGenerativeAI]
 
 
 class SignalProcessor:
     """Processes trading signals to extract actionable decisions."""
 
-    def __init__(self, quick_thinking_llm: ChatOpenAI):
+    def __init__(self, quick_thinking_llm: LLMType):
         """Initialize with an LLM for processing."""
         self.quick_thinking_llm = quick_thinking_llm
 
@@ -28,4 +34,4 @@ class SignalProcessor:
             ("human", full_signal),
         ]
 
-        return self.quick_thinking_llm.invoke(messages).content
+        return str(self.quick_thinking_llm.invoke(messages).content)

tradingagents/graph/trading_graph.py

@@ -36,7 +36,7 @@ class TradingAgentsGraph:
         self,
         selected_analysts=["market", "social", "news", "fundamentals"],
         debug=False,
-        config: Dict[str, Any] = None,
+        config: Optional[Dict[str, Any]] = None,
     ):
         """Initialize the trading agents graph and components.
 
@@ -62,8 +62,8 @@ class TradingAgentsGraph:
             self.deep_thinking_llm = ChatOpenAI(model=self.config["deep_think_llm"], base_url=self.config["backend_url"])
             self.quick_thinking_llm = ChatOpenAI(model=self.config["quick_think_llm"], base_url=self.config["backend_url"])
         elif self.config["llm_provider"].lower() == "anthropic":
-            self.deep_thinking_llm = ChatAnthropic(model=self.config["deep_think_llm"], base_url=self.config["backend_url"])
-            self.quick_thinking_llm = ChatAnthropic(model=self.config["quick_think_llm"], base_url=self.config["backend_url"])
+            self.deep_thinking_llm = ChatAnthropic(model_name=self.config["deep_think_llm"], base_url=self.config["backend_url"], timeout=120, stop=None)
+            self.quick_thinking_llm = ChatAnthropic(model_name=self.config["quick_think_llm"], base_url=self.config["backend_url"], timeout=120, stop=None)
         elif self.config["llm_provider"].lower() == "google":
             self.deep_thinking_llm = ChatGoogleGenerativeAI(model=self.config["deep_think_llm"])
             self.quick_thinking_llm = ChatGoogleGenerativeAI(model=self.config["quick_think_llm"])