Update app.py

app.py

@@ -1,6 +1,16 @@
 import streamlit as st
 import openai
 
+def chunk_text(text, chunk_size=2000):
+    chunks = []
+    start = 0
+    while start < len(text):
+        end = start + chunk_size
+        chunk = text[start:end]
+        chunks.append(chunk)
+        start = end
+    return chunks
+
 # Streamlit Session State
 if 'learning_objectives' not in st.session_state:
     st.session_state.learning_objectives = ""
@@ -32,25 +42,36 @@ claims_extraction = ""
 # Initialize status placeholder
 learning_status_placeholder = st.empty()
 disable_button_bool = False
-if userinput and api_key and st.button("Extract Claims",key="claims_extraction",disabled=disable_button_bool):
-
-    # Display status message
-    learning_status_placeholder.text("Generating learning objectives...")
-    # API call to generate objectives
-    claims_extraction_response = openai.ChatCompletion.create(
-        model=model_choice,
-        messages=[
-            {"role": "user", "content": f"Extract any patentable claims from the following: \n {userinput}. \n extract each claim. Briefly explain why you extracted this wordphrase. Exclude any additional commentary."}
-        ]
-    )
-    # Extract the generated objectives from the API response
-    claims_extraction=claims_extraction_response['choices'][0]['message']['content']
+if userinput and api_key and st.button("Extract Claims", key="claims_extraction", disabled=disable_button_bool):
+    # Split the user input into chunks
+    input_chunks = chunk_text(userinput)
     
-    # Save generated objectives to session state
-    # st.session_state.claims_extraction = claims_extraction.strip()
-    
-    # Display generated objectives
-    learning_status_placeholder.text(f"Patentable Claims Extracted!\n{claims_extraction.strip()}")
+    # Initialize a variable to store the extracted claims
+    all_extracted_claims = ""
+
+    for chunk in input_chunks:
+        # Display status message for the current chunk
+        learning_status_placeholder.text(f"Extracting Patentable Claims for chunk {input_chunks.index(chunk) + 1}...")
+
+        # API call to generate objectives for the current chunk
+        claims_extraction_response = openai.ChatCompletion.create(
+            model=model_choice,
+            messages=[
+                {"role": "user", "content": f"Extract any patentable claims from the following: \n {chunk}. \n extract each claim. Briefly explain why you extracted this word phrase. Exclude any additional commentary."}
+            ]
+        )
+
+        # Extract the generated objectives from the API response
+        claims_extraction = claims_extraction_response['choices'][0]['message']['content']
+
+        # Append the extracted claims from the current chunk to the overall results
+        all_extracted_claims += claims_extraction.strip()
+
+    # Save the generated objectives to session state
+    st.session_state.claims_extraction = all_extracted_claims
+
+    # Display generated objectives for all chunks
+    learning_status_placeholder.text(f"Patentable Claims Extracted!\n{all_extracted_claims.strip()}")
 
 # Generate Lesson Plan Button
 if st.button("Extract Claims") and api_key: