Update app.py

app.py

@@ -1,5 +1,7 @@
 import streamlit as st
 from getpass import getpass
+import requests
+import json
 from langchain_google_genai import GoogleGenerativeAI
 from langchain.prompts import PromptTemplate
 from langchain.agents import AgentExecutor, initialize_agent, AgentType
@@ -12,6 +14,44 @@ from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
 from langchain_core.pydantic_v1 import BaseModel, Field
 from langchain_google_genai import ChatGoogleGenerativeAI
 
+API_GOOGLE_SEARCH_KEY = "AIzaSyA4oDDFtPxAfmPC8EcfQrkByb9xKm2QfMc"
+
+def query_fact_check_api(claim):
+    """Queries the Google Fact Check Tools API for a given claim.
+    Args:
+        claim (str): The claim to search for fact checks.
+    Returns:
+        dict: The API response parsed as a JSON object.
+    """
+
+    url = "https://factchecktools.googleapis.com/v1alpha1/claims:search"
+    params = {
+        "key": API_GOOGLE_SEARCH_KEY,
+        "query": claim,
+    }
+
+    response = requests.get(url, params=params)
+    response.raise_for_status()  # Raise an exception for error HTTP statuses
+
+    return response.json()
+
+def response_break_out(response):
+    if response.get("claims"):
+        iteration = 0
+        answer = """Below is the searched result: \n"""
+        for claim in response["claims"]:
+            answer = answer + """claim: """ + claim['text'] + "\n"
+            for review in claim["claimReview"]:
+                answer = answer + """publisher: """ + review['publisher']['name'] + "\n"
+                answer = answer + """rating: """ + review['textualRating']  + "\n"
+            if iteration >= 1:
+              break
+            iteration += 1
+    else:
+        answer = """No fact checks found for this claim."""
+
+    return answer
+
 def create_tools():
     search = TavilySearchAPIWrapper(tavily_api_key='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')
     description = """"A search engine optimized for comprehensive, accurate, \
@@ -51,15 +91,19 @@ def main():
         response = llm.invoke(user_input)
         display_response(response)
         prompt = """
-        You are a fact-checker. You are asked to verify the following statement based on the information you get from your tool
+        You are a fact-checker. You are asked to verify the following statement based on the information you get from your tool, the search result we provided, 
         and your knowledge. You should provide a response that is based on the information you have and that is as accurate as possible.
-        Your response should be True or False. If you are not sure, you should say that you are not sure.
+        Your response should be True or False!!! If you are not sure, you should say that you are not sure.
         """
         new_prompt = st.text_area(prompt)
+
+        result = query_fact_check_api(user_input)
+        facts = response_break_out(result)
+        
         if new_prompt:
             prompt = new_prompt
         answer = agent_chain.invoke(
-            prompt + "\n " + user_input,
+            prompt + "\n " + facts + "\n" + user_input,
         )
         display_response(answer)