Update app.py

app.py

@@ -7,6 +7,7 @@ import nest_asyncio
 import os
 import subprocess
 import io
+import time
 from langchain_google_genai import ChatGoogleGenerativeAI, GoogleGenerativeAIEmbeddings
 from langchain.vectorstores import FAISS
 from langchain.text_splitter import CharacterTextSplitter
@@ -30,17 +31,60 @@ graph_config = {
 }
 
 def get_data(search_term):
-    # Combine the user input with 'grants'
-    full_prompt = f"search for {search_term} grants\n\nList me all grants or funds with:\n- Grant name/title\n- Short summary (50-100 characters)\n- Funding organization\n- Grant value (numeric only)\n- Application deadline\n- Eligible countries\n- Sector/field\n- Eligibility criteria\nReturn in JSON format."
-    search_graph = SearchGraph(
-        prompt=full_prompt,
-        config=graph_config,
+    """
+    Run the SearchGraph for a given search term.
+    If a rate-limit error (202) occurs, wait 10 seconds and retry.
+    If no results are returned or an error persists, notify the user.
+    """
+    full_prompt = (
+        f"search for {search_term} grants\n\n"
+        "List me all grants or funds with:\n"
+        "- Grant name/title\n"
+        "- Short summary (50-100 characters)\n"
+        "- Funding organization\n"
+        "- Grant value (numeric only)\n"
+        "- Application deadline\n"
+        "- Eligible countries\n"
+        "- Sector/field\n"
+        "- Eligibility criteria\n"
+        "Return in JSON format."
     )
-    return search_graph.run()
+    try:
+        search_graph = SearchGraph(
+            prompt=full_prompt,
+            config=graph_config,
+        )
+        result = search_graph.run()
+        if not result or not result.get("grants"):
+            st.error("No results returned. Please try again with different search terms.")
+            return {}
+        return result
+    except Exception as e:
+        err_str = str(e)
+        if "202" in err_str:
+            st.warning("Rate limit reached (202). Waiting 10 seconds before retrying...")
+            time.sleep(10)
+            try:
+                search_graph = SearchGraph(
+                    prompt=full_prompt,
+                    config=graph_config,
+                )
+                result = search_graph.run()
+                if not result or not result.get("grants"):
+                    st.error("No results returned after retry. Please try again with different search terms.")
+                    return {}
+                return result
+            except Exception as e2:
+                st.error(f"Retry failed: {e2}. Please try again later.")
+                return {}
+        else:
+            st.error(f"An error occurred: {e}. Please try again.")
+            return {}
 
 def process_multiple_search_terms(search_terms):
     """
-    Process multiple search terms with enhanced progress tracking and user feedback.
+    Process multiple search terms with progress tracking.
+    Returns a dictionary with a 'grants' key containing combined results.
     """
     all_data = {"grants": []}
     progress_bar = st.progress(0)
@@ -48,33 +92,29 @@ def process_multiple_search_terms(search_terms):
     total_terms = len(search_terms)
 
     for index, term in enumerate(search_terms):
-        try:
-            term = term.strip()
-            if not term:
-                continue
-
-            progress = (index + 1) / total_terms
-            progress_bar.progress(progress)
-            status_container.markdown(
-                f"""
-**Processing Grant Opportunities** 🚀
-Searching term {index+1} of {total_terms}:  `{term}`
+        term = term.strip()
+        if not term:
+            continue
+
+        progress = (index + 1) / total_terms
+        progress_bar.progress(progress)
+        status_container.markdown(
+            f"""
+**Processing Grant Opportunities** 🚀  
+Searching term {index+1} of {total_terms}:  `{term}`  
 <br>
 <p style='font-size: 0.9em; color: #6699CC;'>Completed: {index}/{total_terms} | Remaining: {total_terms - index - 1}</p>
 """,
-                unsafe_allow_html=True,
-            )
-
-            result = get_data(term)
-            # Expecting a JSON with a "grants" key
-            if result and "grants" in result:
-                all_data["grants"].extend(result["grants"])
-        except Exception as e:
-            st.error(f"⚠️ Error processing search term: {term} - {str(e)}")
-            continue
+            unsafe_allow_html=True,
+        )
 
+        result = get_data(term)
+        if result and result.get("grants"):
+            all_data["grants"].extend(result["grants"])
     progress_bar.empty()
     status_container.empty()
+    if not all_data["grants"]:
+        st.error("No grant opportunities were found. Please try again with different search terms.")
     return all_data
 
 def convert_to_csv(data):
@@ -106,11 +146,9 @@ Here is the extracted grant data in JSON format:
 User's question: {query}
 Answer the question based on the provided grant data.
 """
-
     llm = ChatGoogleGenerativeAI(
         model="gemini-2.0-flash-thinking-exp", google_api_key=GOOGLE_API_KEY, temperature=0
     )
-    
     response = llm.invoke(prompt)
     return response
 
@@ -121,7 +159,6 @@ def get_shareable_link(file_data, file_name, file_type):
 def main():
     st.set_page_config(page_title="Quantilytix Grant Finder", page_icon="💰", layout="wide")
     st.title("💰 Quantilytix Grant Finder")
-
     st.markdown("""
 <div style="text-align: justify;">
     <p>
@@ -141,7 +178,7 @@ def main():
     if "chat_interface_active" not in st.session_state:
         st.session_state.chat_interface_active = False
 
-    # Search Term Input in Sidebar
+    # Sidebar: Search Term Input
     search_input = st.sidebar.text_area(
         "Enter Search Terms (one per line)",
         height=150,
@@ -153,23 +190,20 @@ def main():
         if search_input:
             search_terms = [term.strip() for term in search_input.split("\n") if term.strip()]
             if search_terms:
-                try:
-                    with st.spinner("Searching in progress... Please wait patiently."):
-                        result = process_multiple_search_terms(search_terms)
-                        st.session_state.scraped_data = result
+                with st.spinner("Searching in progress... Please wait patiently."):
+                    result = process_multiple_search_terms(search_terms)
+                    st.session_state.scraped_data = result
+                    if result.get("grants"):
                         st.sidebar.success(f"✅ Found {len(result['grants'])} grant opportunities from {len(search_terms)} search terms!")
-                except Exception as e:
-                    st.sidebar.error(f"🚨 Searching process encountered an error: {e}")
             else:
                 st.sidebar.warning("⚠️ Please enter valid search terms.")
         else:
             st.sidebar.warning("⚠️ Please enter at least one search term to begin.")
 
-    # Sidebar: Download and Share Options
+    # Sidebar: Download & Share Controls
     if st.session_state.scraped_data and st.session_state.scraped_data.get('grants'):
         st.sidebar.markdown("---")
         st.sidebar.subheader("Download & Share")
-
         selected_format = st.sidebar.selectbox("Download As:", ("CSV", "Excel"), key="download_format_selector")
         if selected_format == "CSV":
             file_data = convert_to_csv(st.session_state.scraped_data)
@@ -179,16 +213,13 @@ def main():
             file_data = convert_to_excel(st.session_state.scraped_data)
             file_name = "grants_data.xlsx"
             file_type = "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
-
         download_link_html = f"<a href='data:{file_type};base64,{base64.b64encode(file_data).decode()}' download='{file_name}'><button style='background-color:#4CAF50;color:white;padding:10px 15px;border:none;border-radius:4px;'>⬇️ Download {selected_format}</button></a>"
         st.sidebar.markdown(download_link_html, unsafe_allow_html=True)
-
         shareable_link = get_shareable_link(file_data, file_name, file_type)
         whatsapp_url = f"https://api.whatsapp.com/send?text={urllib.parse.quote(f'Check out these grant opportunities: {shareable_link}')}"
         email_subject = urllib.parse.quote("Grant Opportunities File")
         email_body = urllib.parse.quote(f"Download the grant opportunities file here: {shareable_link}")
         email_url = f"mailto:?subject={email_subject}&body={email_body}"
-
         st.sidebar.markdown("<div style='margin-top:10px;'>Share via:</div>", unsafe_allow_html=True)
         st.sidebar.markdown(f"📱 [WhatsApp]({whatsapp_url}) | 📧 [Email]({email_url})", unsafe_allow_html=True)
 
@@ -200,25 +231,22 @@ def main():
                 st.session_state.chat_history = []
             st.sidebar.success("Knowledge base loaded!")
 
-        # Sidebar: Chat Interface
-        if st.session_state.get("chat_interface_active"):
-            st.sidebar.markdown("---")
-            st.sidebar.subheader("💬 Chat with Grants Bot")
-            query = st.sidebar.text_input("Your question:", key="chat_input")
-            if query:
-                with st.spinner("Generating response..."):
-                    response = chat_with_knowledge_base(query)
-                    # Assume response returns a dictionary with key 'answer'
-                    answer = response["answer"] if isinstance(response, dict) and "answer" in response else response
-                    st.session_state.chat_history.append({"query": query, "response": answer})
-
-    # Main area: Preview data and chat history
+    # Main area: Data Preview
     st.markdown("---")
     if st.session_state.scraped_data and st.session_state.scraped_data.get('grants'):
         st.header("📊 Found Grant Data")
         with st.expander(f"📊 Preview Grant Data ({len(st.session_state.scraped_data['grants'])} grants)"):
             st.dataframe(st.session_state.scraped_data["grants"])
 
+    # Main area: Chat UI (shown if knowledge base is loaded)
+    if st.session_state.get("chat_interface_active"):
+        st.header("💬 Chat with Grants Bot")
+        query = st.text_input("Your question:", key="chat_input_main")
+        if query:
+            with st.spinner("Generating response..."):
+                response = chat_with_knowledge_base(query)
+                answer = response["answer"] if isinstance(response, dict) and "answer" in response else response
+                st.session_state.chat_history.append({"query": query, "response": answer})
         if st.session_state.chat_history:
             st.subheader("Chat History")
             for chat in st.session_state.chat_history: