Update app.py

app.py

@@ -14,6 +14,8 @@ from langchain.vectorstores import FAISS
 from langchain.text_splitter import CharacterTextSplitter
 from langchain.chains import ConversationalRetrievalChain
 from langchain.memory import ConversationBufferMemory
+from google import genai
+from google.genai import types
 
 # Import Supadata and initialize the client
 from supadata import Supadata, SupadataError
@@ -87,6 +89,7 @@ def get_data(search_term):
             st.error(f"An error occurred for search term: {search_term}, error: {e}. Please try again.")
             return {}
 
+
 def get_data_from_url(url):
     """
     Scrape the provided URL using Supadata and pass the page content directly to the Gemini model
@@ -97,7 +100,6 @@ def get_data_from_url(url):
         page_content = web_content.content
         full_prompt = (
             "Extract the following grant data from the provided web content. "
-            "List me all grants or funds with:\n"
             "- Grant name/title\n"
             "- Short summary\n"
             "- Funding organization\n"
@@ -109,12 +111,12 @@ def get_data_from_url(url):
             "Return in JSON format.\n\n"
             f"Web content: {page_content}"
         )
-        llm = ChatGoogleGenerativeAI(
-            model="gemini-2.0-flash-thinking-exp", google_api_key=GOOGLE_API_KEY, temperature=0
-        )
-        response = llm.invoke(full_prompt)
+        client = genai.Client(api_key=GOOGLE_API_KEY)
+        new_answer = client.models.generate_content(model="models/gemini-2.0-flash-lite", contents=f"{full_prompt}, return the json string and nothing else")
+        response = new_answer.text
         try:
-            result = json.loads(response.content)
+            result = json.loads(response)
+            st.success(f"{result[0]}")
         except Exception as parse_error:
             st.error("Error parsing JSON from Gemini model response.")
             return {}