Update app.py

app.py

@@ -68,7 +68,7 @@ class Journal:
     def __repr__(self):
         return f"Journal(name='{self.name}', bytes='{self.bytes}')"
 
-llm = ChatOpenAI(temperature=0, model="gpt-4-1106-preview")
+llm = ChatOpenAI(temperature=0, model="gpt-3.5-turbo-1106")
 
 textex_chain = create_extraction_chain(textex_schema, llm)
 tablex_chain = create_extraction_chain(tablex_schema, llm)
@@ -104,7 +104,7 @@ if uploaded_files:
             if on_h:
                 chunk_size_h = st.selectbox(
                     'Tokens amounts per process :',
-                    (64000, 32000,25000, 16000, 12000, 10000, 8000, 5000), key='table_h'
+                    (15000, 12000, 10000, 8000, 5000), key='table_h'
                 )
                 parseButtonH = st.button("Get Result", key='table_H')
         
@@ -116,7 +116,7 @@ if uploaded_files:
             if on_v:
                 chunk_size_v = st.selectbox(
                     'Tokens amounts per process :',
-                    (64000, 32000, 25000, 16000, 12000, 10000, 8000, 5000), key='table_v'
+                    (15000, 12000, 10000, 8000, 5000), key='table_v'
                 )
                 parseButtonV = st.button("Get Result", key='table_V')
     with col3:
@@ -127,7 +127,7 @@ if uploaded_files:
             if on_t:
                 chunk_size_t = st.selectbox(
                     'Tokens amounts per process :',
-                    (64000, 32000, 25000, 16000, 12000, 10000, 8000, 5000), key='no_table'
+                    (15000, 12000, 10000, 8000, 5000), key='no_table'
                 )
                 parseButtonT = st.button("Get Result", key="no_Table")
 
@@ -198,7 +198,7 @@ if uploaded_files:
                                 embeddings = OpenAIEmbeddings()
 
                                 db = Chroma.from_documents(docs, embeddings)
-                                llm_table = ChatOpenAI(model_name="gpt-4-1106-preview", temperature=0)
+                                llm_table = ChatOpenAI(model_name="gpt-3.5-turbo-1106", temperature=0)
                                 qa_chain = RetrievalQA.from_chain_type(llm_table, retriever=db.as_retriever())
                                 
                                 # List of questions
@@ -650,7 +650,7 @@ if uploaded_files:
                                     embeddings = OpenAIEmbeddings()
 
                                     db = Chroma.from_documents(docs, embeddings)
-                                    llm_table = ChatOpenAI(model_name="gpt-4-1106-preview", temperature=0)
+                                    llm_table = ChatOpenAI(model_name="gpt-3.5-turbo-1106", temperature=0)
                                     qa_chain = RetrievalQA.from_chain_type(llm_table, retriever=db.as_retriever())
                                     
                                     # List of questions