app.py

app.py

@@ -15,6 +15,7 @@ from langchain_community.document_loaders import UnstructuredExcelLoader
 from langchain.text_splitter import CharacterTextSplitter
 from langchain.embeddings import HuggingFaceEmbeddings
 
+# Set API key environment variable
 os.environ["TOGETHER_API_KEY"] = os.getenv("TOGETHER_API_KEY")
 
 
@@ -111,6 +112,10 @@ def scrape_url(url):
         response.raise_for_status()  # Ensure we notice bad responses
         soup = BeautifulSoup(response.content, 'html.parser')
         text = soup.get_text()
+        
+        # Ensure the data directory exists
+        os.makedirs("data", exist_ok=True)
+        
         # Save the text content to a file for processing
         text_file_path = "data/scraped_content.txt"
         with open(text_file_path, "w") as file:
@@ -119,6 +124,9 @@ def scrape_url(url):
     except requests.RequestException as e:
         st.error(f"Error fetching the URL: {e}")
         return None
+    except Exception as e:
+        st.error(f"An unexpected error occurred: {e}")
+        return None
 
 
 def process_document(path, input_query):
@@ -147,7 +155,7 @@ def main():
             with open(os.path.join(tmp_folder, file.name), 'wb') as f:
                 f.write(file.getbuffer())
         st.success('Files successfully uploaded. Start prompting!')
-    
+
     if 'chat_history' not in st.session_state:
         st.session_state.chat_history = []
 
@@ -157,10 +165,10 @@ def main():
             if st.form_submit_button("Ask") and user_query:
                 response = process_document(tmp_folder, user_query)
                 st.session_state.chat_history.append({"question": user_query, "answer": response})
-            
+
         if st.button("Clear Chat History"):
             st.session_state.chat_history = []
-        
+
         for chat in st.session_state.chat_history:
             st.markdown(f"**Q:** {chat['question']}")
             st.markdown(f"**A:** {chat['answer']}")