Merge 693ee70e3b into 13b826a31d

tradingagents/agents/__init__.py

@@ -1,40 +1,19 @@
-from .utils.agent_utils import create_msg_delete
-from .utils.agent_states import AgentState, InvestDebateState, RiskDebateState
-from .utils.memory import FinancialSituationMemory
-
-from .analysts.fundamentals_analyst import create_fundamentals_analyst
 from .analysts.market_analyst import create_market_analyst
 from .analysts.news_analyst import create_news_analyst
+from .analysts.fundamentals_analyst import create_fundamentals_analyst
 from .analysts.social_media_analyst import create_social_media_analyst
 
-from .researchers.bear_researcher import create_bear_researcher
 from .researchers.bull_researcher import create_bull_researcher
+from .researchers.bear_researcher import create_bear_researcher
+
+from .managers.research_manager import create_research_manager
+from .managers.risk_manager import create_risk_manager
+from .managers.fact_checker import create_fact_checker  # Added
+
+from .trader.trader import create_trader
 
 from .risk_mgmt.aggresive_debator import create_risky_debator
 from .risk_mgmt.conservative_debator import create_safe_debator
 from .risk_mgmt.neutral_debator import create_neutral_debator
 
-from .managers.research_manager import create_research_manager
+from .utils.agent_utils import create_msg_delete
-from .managers.risk_manager import create_risk_manager
-
-from .trader.trader import create_trader
-
-__all__ = [
-    "FinancialSituationMemory",
-    "AgentState",
-    "create_msg_delete",
-    "InvestDebateState",
-    "RiskDebateState",
-    "create_bear_researcher",
-    "create_bull_researcher",
-    "create_research_manager",
-    "create_fundamentals_analyst",
-    "create_market_analyst",
-    "create_neutral_debator",
-    "create_news_analyst",
-    "create_risky_debator",
-    "create_risk_manager",
-    "create_safe_debator",
-    "create_social_media_analyst",
-    "create_trader",
-]

tradingagents/agents/managers/fact_checker.py

@@ -0,0 +1,205 @@
+from langchain_core.messages import AIMessage
+import json
+import re
+import requests
+import warnings
+from requests.packages.urllib3.exceptions import InsecureRequestWarning
+from concurrent.futures import ThreadPoolExecutor
+
+# Suppress only the single warning from urllib3 needed.
+warnings.simplefilter('ignore', InsecureRequestWarning)
+
+def verify_url(url):
+    try:
+        # Use requests library instead of curl for better portability across OS
+        # mimicking the headers we found effective
+        headers = {
+            'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36',
+            'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7',
+            'Accept-Language': 'en-US,en;q=0.9',
+            'Referer': 'https://www.google.com/',
+            'Upgrade-Insecure-Requests': '1',
+            'Sec-Fetch-Dest': 'document',
+            'Sec-Fetch-Mode': 'navigate',
+            'Sec-Fetch-Site': 'cross-site',
+            'Sec-Fetch-User': '?1',
+            'Cache-Control': 'max-age=0'
+        }
+
+        # Use GET with stream=True to check headers/status without downloading full body
+        # verify=False is equivalent to curl -k (insecure)
+        response = requests.get(url, headers=headers, timeout=15, stream=True, verify=False)
+        
+        status_code = response.status_code
+
+        # Treat 403 as potentially accessible but blocked by WAF
+        if 200 <= status_code < 400:
+            return url, "VALID"
+        elif status_code == 404:
+            return url, "NOT FOUND (404)"
+        elif status_code == 403:
+             return url, "VALID (Protected/403)" 
+        else:
+            return url, f"ACCESSIBLE (Status: {status_code})"
+
+    except Exception as e:
+        # Fallback error handling
+        return url, f"ERROR (Could not access: {str(e)})"
+
+def get_unique_urls(text):
+    if not text:
+        return []
+    # Simple regex to find URLs
+    urls = re.findall(r'http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\\(\\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+', text)
+    # Remove duplicates and clean trailing punctuation
+    clean_urls = []
+    for url in urls:
+        # Strip common trailing punctuation that might be captured
+        url = url.rstrip(').,;]')
+        clean_urls.append(url)
+    
+    return list(set(clean_urls))
+
+def check_urls_and_get_data(text, source_label):
+    unique_urls = get_unique_urls(text)
+    
+    if not unique_urls:
+        return []
+        
+    results = []
+    # Limit max workers to avoid being flagged as DoS
+    with ThreadPoolExecutor(max_workers=5) as executor:
+        futures = [executor.submit(verify_url, url) for url in unique_urls]
+        for future in futures:
+            url, status = future.result()
+            results.append({
+                "url": url,
+                "status": status,
+                "source": source_label
+            })
+    return results
+
+def create_fact_checker(llm):
+    def fact_checker_node(state) -> dict:
+        investment_debate_state = state["investment_debate_state"]
+        current_response = investment_debate_state.get("current_response", "")
+        
+        # Reports to verify against
+        market_research_report = state["market_report"]
+        sentiment_report = state["sentiment_report"]
+        news_report = state["news_report"]
+        fundamentals_report = state["fundamentals_report"]
+        
+        # If there's no response to check, pass
+        if not current_response:
+            return {}
+            
+        # Verify URLs - collect structured data
+        verified_data = []
+        
+        # 1. Check URLs in News Report
+        news_verified = check_urls_and_get_data(news_report, "News Analyst")
+        verified_data.extend(news_verified)
+        
+        # 2. Check URLs in Current Response (Debate)
+        response_verified = check_urls_and_get_data(current_response, "Debate Speaker")
+        verified_data.extend(response_verified)
+        
+        # Deduplicate by URL (keep first occurrence or merge sources)
+        unique_verified_map = {}
+        for item in verified_data:
+            if item["url"] not in unique_verified_map:
+                unique_verified_map[item["url"]] = item
+            else:
+                # If already exists, append source if different
+                if item["source"] not in unique_verified_map[item["url"]]["source"]:
+                    unique_verified_map[item["url"]]["source"] += f", {item['source']}"
+        
+        final_verified_list = list(unique_verified_map.values())
+
+        # Generate text report for LLM prompt
+        url_check_report = ""
+        if final_verified_list:
+            url_check_report = "\n[URL Verification Report]\n"
+            for item in final_verified_list:
+                url_check_report += f"- {item['url']}: {item['status']} (Source: {item['source']})\n"
+            
+            print(f"DEBUG: URL Verification completed.\n{url_check_report}")
+
+        prompt = f"""You are a strict Fact Checker for a financial analysis team.
+Your job is to verify the claims made in the following statement against the provided source reports AND verify the validity of the sources.
+
+Statement to Verify:
+"{current_response}"
+
+Source Reports:
+1. Market Research: {market_research_report}
+2. Sentiment Report: {sentiment_report}
+3. News Report: {news_report}
+4. Fundamentals Report: {fundamentals_report}
+
+URL Verification Status (Physical Check of Links):
+{url_check_report}
+
+Instructions:
+1. Extract every factual claim (numbers, dates, specific news events) from the statement.
+2. Check if each claim exists in the Source Reports.
+3. **CRITICAL**: Check the "URL Verification Status" section. If the statement relies on a news article whose URL is marked as "NOT FOUND", "ERROR", or "INVALID", you MUST flag this as a potential invalid source or deleted article.
+4. If a claim is NOT found or contradicts the reports, flag it as a HALLUCINATION.
+5. If the statement is mostly opinion/analysis, it is acceptable.
+6. **ALWAYS** list the Verified Sources (URLs) at the end of your response, even if verified.
+
+Output Format:
+If all facts are supported and sources are valid:
+"VERIFIED: The statement is consistent with the provided data and sources appear valid.
+
+[Verified Sources]
+- [URL1] (Status: VALID)
+...
+"
+
+If errors are found:
+"CORRECTION NEEDED:
+- Claim: [Claim] -> Error: [Not found / Contradiction / Source URL Invalid or Deleted]
+...
+
+[Verified Sources]
+- [URL1] (Status: ...)
+...
+"
+
+Be extremely strict about numbers. If revenue is 10B in reports but statement says 12B, flag it.
+Be strict about source validity. If a key argument is based on a broken link, flag it.
+"""
+        
+        response = llm.invoke(prompt)
+        check_result = response.content
+        
+        # Log the fact check result
+        print(f"\n\n[Fact Checker]:\n{check_result}\n")
+        
+        # Prepare state update
+        new_state = investment_debate_state.copy()
+        
+        # Merge existing verified urls with new ones
+        existing_verified = new_state.get("verified_urls", [])
+        # We want to accumulate unique URLs seen so far
+        existing_url_map = {item['url']: item for item in existing_verified}
+        for item in final_verified_list:
+             existing_url_map[item['url']] = item
+        new_state["verified_urls"] = list(existing_url_map.values())
+        
+        if "CORRECTION NEEDED" in check_result:
+            updated_response = f"{current_response}\n\n[SYSTEM NOTE: Fact Check Warning]\n{check_result}"
+            new_state["current_response"] = updated_response
+            new_state["history"] += f"\n\n[Fact Check Warning]: {check_result}"
+            return {"investment_debate_state": new_state}
+            
+        elif "VERIFIED" in check_result and url_check_report:
+            new_state["history"] += f"\n\n[Fact Checker]: {check_result}"
+            return {"investment_debate_state": new_state}
+        
+        # Even if no text update, we return state to save verified_urls
+        return {"investment_debate_state": new_state}
+
+    return fact_checker_node

tradingagents/agents/managers/research_manager.py

@@ -31,21 +31,21 @@ Strategic Actions: Concrete steps for implementing the recommendation.
 Take into account your past mistakes on similar situations. Use these insights to refine your decision-making and ensure you are learning and improving. Present your analysis conversationally, as if speaking naturally, without special formatting. 
 
 Here are your past reflections on mistakes:
-\"{past_memory_str}\"
+"{past_memory_str}"
 
 Here is the debate:
 Debate History:
 {history}"""
         response = llm.invoke(prompt)
         
-        new_investment_debate_state = {
+        # Log the manager's decision
+        print(f"\n\n[Research Manager Decision]\n{response.content}\n")
+
+        new_investment_debate_state = investment_debate_state.copy()
+        new_investment_debate_state.update({
             "judge_decision": response.content,
-            "history": investment_debate_state.get("history", ""),
-            "bear_history": investment_debate_state.get("bear_history", ""),
-            "bull_history": investment_debate_state.get("bull_history", ""),
             "current_response": response.content,
-            "count": investment_debate_state["count"],
+        })
-        }
 
         return {
             "investment_debate_state": new_investment_debate_state,

tradingagents/agents/utils/agent_states.py

@@ -1,4 +1,4 @@
-from typing import Annotated, Sequence
+from typing import Annotated, Sequence, List, Dict
 from datetime import date, timedelta, datetime
 from typing_extensions import TypedDict, Optional
 from langchain_openai import ChatOpenAI
@@ -19,6 +19,7 @@ class InvestDebateState(TypedDict):
     current_response: Annotated[str, "Latest response"]  # Last response
     judge_decision: Annotated[str, "Final judge decision"]  # Last response
     count: Annotated[int, "Length of the current conversation"]  # Conversation length
+    verified_urls: Annotated[List[Dict], "List of verified URLs with status and source"]
 
 
 # Risk management team state

tradingagents/dataflows/google.py

@@ -21,7 +21,9 @@ def get_google_news(
 
     for news in news_results:
         news_str += (
-            f"### {news['title']} (source: {news['source']}) \n\n{news['snippet']}\n\n"
+            f"### {news['title']} (source: {news['source']}) \n"
+            f"URL: {news['link']}\n"
+            f"{news['snippet']}\n\n"
         )
 
     if len(news_results) == 0:

tradingagents/dataflows/local.py

@@ -110,7 +110,9 @@ def get_finnhub_news(
             continue
         for entry in data:
             current_news = (
-                "### " + entry["headline"] + f" ({day})" + "\n" + entry["summary"]
+                f"### {entry['headline']} ({day})\n"
+                f"URL: {entry.get('url', 'N/A')}\n"
+                f"{entry['summary']}"
             )
             combined_result += current_news + "\n\n"
 
@@ -411,9 +413,9 @@ def get_reddit_global_news(
     news_str = ""
     for post in posts:
         if post["content"] == "":
-            news_str += f"### {post['title']}\n\n"
+            news_str += f"### {post['title']}\nURL: {post.get('url', 'N/A')}\n\n"
         else:
-            news_str += f"### {post['title']}\n\n{post['content']}\n\n"
+            news_str += f"### {post['title']}\nURL: {post.get('url', 'N/A')}\n\n{post['content']}\n\n"
 
     return f"## Global News Reddit, from {before} to {curr_date}:\n{news_str}"
 
@@ -468,8 +470,8 @@ def get_reddit_company_news(
     news_str = ""
     for post in posts:
         if post["content"] == "":
-            news_str += f"### {post['title']}\n\n"
+            news_str += f"### {post['title']}\nURL: {post.get('url', 'N/A')}\n\n"
         else:
-            news_str += f"### {post['title']}\n\n{post['content']}\n\n"
+            news_str += f"### {post['title']}\nURL: {post.get('url', 'N/A')}\n\n{post['content']}\n\n"
 
     return f"##{query} News Reddit, from {start_date} to {end_date}:\n\n{news_str}"

tradingagents/graph/setup.py

@@ -92,6 +92,8 @@ class GraphSetup:
         bear_researcher_node = create_bear_researcher(
             self.quick_thinking_llm, self.bear_memory
         )
+        fact_checker_node = create_fact_checker(self.quick_thinking_llm)
+
         research_manager_node = create_research_manager(
             self.deep_thinking_llm, self.invest_judge_memory
         )
@@ -119,6 +121,7 @@ class GraphSetup:
         # Add other nodes
         workflow.add_node("Bull Researcher", bull_researcher_node)
         workflow.add_node("Bear Researcher", bear_researcher_node)
+        workflow.add_node("Fact Checker", fact_checker_node)
         workflow.add_node("Research Manager", research_manager_node)
         workflow.add_node("Trader", trader_node)
         workflow.add_node("Risky Analyst", risky_analyst)
@@ -153,22 +156,21 @@ class GraphSetup:
                 workflow.add_edge(current_clear, "Bull Researcher")
 
         # Add remaining edges
+        # Bull/Bear Researchers now go to Fact Checker instead of conditional edge
+        workflow.add_edge("Bull Researcher", "Fact Checker")
+        workflow.add_edge("Bear Researcher", "Fact Checker")
+
+        # Fact Checker decides where to go next
         workflow.add_conditional_edges(
-            "Bull Researcher",
+            "Fact Checker",
             self.conditional_logic.should_continue_debate,
             {
+                "Bull Researcher": "Bull Researcher",
                 "Bear Researcher": "Bear Researcher",
                 "Research Manager": "Research Manager",
             },
         )
-        workflow.add_conditional_edges(
+
-            "Bear Researcher",
-            self.conditional_logic.should_continue_debate,
-            {
-                "Bull Researcher": "Bull Researcher",
-                "Research Manager": "Research Manager",
-            },
-        )
         workflow.add_edge("Research Manager", "Trader")
         workflow.add_edge("Trader", "Risky Analyst")
         workflow.add_conditional_edges(