Merge remote-tracking branch 'upstream/main' into crypto-analysis-mvp

# Conflicts:
#	tradingagents/agents/researchers/bear_researcher.py
#	tradingagents/agents/researchers/bull_researcher.py
#	tradingagents/graph/propagation.py

tradingagents/agents/researchers/bear_researcher.py

@@ -1,6 +1,6 @@
 
 
-def create_bear_researcher(llm, memory):
+def create_bear_researcher(llm):
     def bear_node(state) -> dict:
         investment_debate_state = state["investment_debate_state"]
         history = investment_debate_state.get("history", "")
@@ -19,13 +19,6 @@ def create_bear_researcher(llm, memory):
             else "Asset fundamentals report (may be unavailable for crypto)"
         )
 
-        curr_situation = f"{market_research_report}\n\n{sentiment_report}\n\n{news_report}\n\n{fundamentals_report}"
-        past_memories = memory.get_memories(curr_situation, n_matches=2)
-
-        past_memory_str = ""
-        for i, rec in enumerate(past_memories, 1):
-            past_memory_str += rec["recommendation"] + "\n\n"
-
         prompt = f"""You are a Bear Analyst making the case against investing in the {target_label}. Your goal is to present a well-reasoned argument emphasizing risks, challenges, and negative indicators. Leverage the provided research and data to highlight potential downsides and counter bullish arguments effectively.
 
 Key points to focus on:
@@ -44,8 +37,7 @@ Latest world affairs news: {news_report}
 {fundamentals_label}: {fundamentals_report}
 Conversation history of the debate: {history}
 Last bull argument: {current_response}
-Reflections from similar situations and lessons learned: {past_memory_str}
-Use this information to deliver a compelling bear argument, refute the bull's claims, and engage in a dynamic debate that demonstrates the risks and weaknesses of investing in the {target_label}. You must also address reflections and learn from lessons and mistakes you made in the past.
+Use this information to deliver a compelling bear argument, refute the bull's claims, and engage in a dynamic debate that demonstrates the risks and weaknesses of investing in the {target_label}.
 """
 
         response = llm.invoke(prompt)

tradingagents/agents/researchers/bull_researcher.py

@@ -1,6 +1,6 @@
 
 
-def create_bull_researcher(llm, memory):
+def create_bull_researcher(llm):
     def bull_node(state) -> dict:
         investment_debate_state = state["investment_debate_state"]
         history = investment_debate_state.get("history", "")
@@ -19,13 +19,6 @@ def create_bull_researcher(llm, memory):
             else "Asset fundamentals report (may be unavailable for crypto)"
         )
 
-        curr_situation = f"{market_research_report}\n\n{sentiment_report}\n\n{news_report}\n\n{fundamentals_report}"
-        past_memories = memory.get_memories(curr_situation, n_matches=2)
-
-        past_memory_str = ""
-        for i, rec in enumerate(past_memories, 1):
-            past_memory_str += rec["recommendation"] + "\n\n"
-
         prompt = f"""You are a Bull Analyst advocating for investing in the {target_label}. Your task is to build a strong, evidence-based case emphasizing growth potential, competitive advantages, and positive market indicators. Leverage the provided research and data to address concerns and counter bearish arguments effectively.
 
 Key points to focus on:
@@ -42,8 +35,7 @@ Latest world affairs news: {news_report}
 {fundamentals_label}: {fundamentals_report}
 Conversation history of the debate: {history}
 Last bear argument: {current_response}
-Reflections from similar situations and lessons learned: {past_memory_str}
-Use this information to deliver a compelling bull argument, refute the bear's concerns, and engage in a dynamic debate that demonstrates the strengths of the bull position. You must also address reflections and learn from lessons and mistakes you made in the past.
+Use this information to deliver a compelling bull argument, refute the bear's concerns, and engage in a dynamic debate that demonstrates the strengths of the bull position.
 """
 
         response = llm.invoke(prompt)