Update app.py

app.py

@@ -14,6 +14,58 @@ 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"
+
+# claim_to_check = "The Earth is round"
+# result = query_fact_check_api(claim_to_check)
+
+# if result.get("claims"):
+#     for claim in result["claims"]:
+#         print("Claim:", claim["text"])
+#         print("Fact Check Results:")
+#         for review in claim["claimReview"]:
+#             print(f"\tPublisher: {review['publisher']['name']}")
+#             print(f"\tURL: {review['url']}")
+#             print(f"\tRating: {review['textualRating']}\n")
+# else:
+#     print("No fact checks found for this claim.")
+
+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"""
+        for claim in response["claims"]:
+            answer = agent_chain.invoke(answer + """claim: """ + claim)
+            for review in claim["claimReview"]:
+                answer = agent_chain.invoke(answer + """publisher: """ + review['publisher']['name'])
+                answer = agent_chain.invoke(answer + """rating: """ + review['textualRating'])
+        break
+    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, \
@@ -53,15 +105,19 @@ 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, 
         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.
         """
         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)