feat: add content normalization for multi-provider support

Handle Gemini's list-of-dicts response format alongside OpenAI/Anthropic strings

tradingagents/agents/analysts/fundamentals_analyst.py

@@ -1,7 +1,7 @@
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
 import time
 import json
-from tradingagents.agents.utils.agent_utils import get_fundamentals, get_balance_sheet, get_cashflow, get_income_statement, get_insider_sentiment, get_insider_transactions
+from tradingagents.agents.utils.agent_utils import get_fundamentals, get_balance_sheet, get_cashflow, get_income_statement, get_insider_sentiment, get_insider_transactions, normalize_content
 from tradingagents.dataflows.config import get_config
 
 
@@ -53,7 +53,7 @@ def create_fundamentals_analyst(llm):
         report = ""
 
         if len(result.tool_calls) == 0:
-            report = result.content
+            report = normalize_content(result.content)
 
         return {
             "messages": [result],

tradingagents/agents/analysts/market_analyst.py

@@ -1,7 +1,7 @@
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
 import time
 import json
-from tradingagents.agents.utils.agent_utils import get_stock_data, get_indicators
+from tradingagents.agents.utils.agent_utils import get_stock_data, get_indicators, normalize_content
 from tradingagents.dataflows.config import get_config
 
 
@@ -75,7 +75,7 @@ Volume-Based Indicators:
         report = ""
 
         if len(result.tool_calls) == 0:
-            report = result.content
+            report = normalize_content(result.content)
        
         return {
             "messages": [result],

tradingagents/agents/analysts/news_analyst.py

@@ -1,7 +1,7 @@
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
 import time
 import json
-from tradingagents.agents.utils.agent_utils import get_news, get_global_news
+from tradingagents.agents.utils.agent_utils import get_news, get_global_news, normalize_content
 from tradingagents.dataflows.config import get_config
 
 
@@ -48,7 +48,7 @@ def create_news_analyst(llm):
         report = ""
 
         if len(result.tool_calls) == 0:
-            report = result.content
+            report = normalize_content(result.content)
 
         return {
             "messages": [result],

tradingagents/agents/analysts/social_media_analyst.py

@@ -1,7 +1,7 @@
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
 import time
 import json
-from tradingagents.agents.utils.agent_utils import get_news
+from tradingagents.agents.utils.agent_utils import get_news, normalize_content
 from tradingagents.dataflows.config import get_config
 
 
@@ -49,7 +49,7 @@ def create_social_media_analyst(llm):
         report = ""
 
         if len(result.tool_calls) == 0:
-            report = result.content
+            report = normalize_content(result.content)
 
         return {
             "messages": [result],

tradingagents/agents/utils/agent_utils.py

@@ -1,5 +1,20 @@
 from langchain_core.messages import HumanMessage, RemoveMessage
 
+
+def normalize_content(content):
+    """Normalize LLM response content to string.
+
+    Gemini returns content as a list of dicts with 'text' keys,
+    while OpenAI/Anthropic return a simple string.
+    """
+    if isinstance(content, list):
+        return "".join(
+            block.get("text", "") if isinstance(block, dict) else str(block)
+            for block in content
+        )
+    return content
+
+
 # Import tools from separate utility files
 from tradingagents.agents.utils.core_stock_tools import (
     get_stock_data