Update app.py

app.py

@@ -124,18 +124,30 @@ def main():
 
       if st.button("Apply"):
         query = prompt
-        st.write("in progress")
-        text_splitter = CharacterTextSplitter(chunk_size=4096, chunk_overlap=0)
-        texts = text_splitter.split_text(input_text)
-        embeddings = OpenAIEmbeddings()
-        docsearch = Chroma.from_texts(texts, embeddings, metadatas=[{"source": str(i)} for i in range(len(texts))]).as_retriever()
-        docs = docsearch.get_relevant_documents(query)
-        if st.session_state.model_name == 'gpt-4': 
-            max_tkns=5500
-        else : 
-            max_tkns=3000
-        chain = load_qa_chain(ChatOpenAI(model = st.session_state.model_name,max_tokens=max_tkns,temperature=0), chain_type="stuff")
-        st.session_state.output = chain.run(input_documents=docs, question=query)
+        with st.spinner('In progress...'):
+#        st.write("in progress")
+#        text_splitter = CharacterTextSplitter(chunk_size=4096, chunk_overlap=0)
+#        texts = text_splitter.split_text(input_text)
+#        embeddings = OpenAIEmbeddings()
+#        docsearch = Chroma.from_texts(texts, embeddings, metadatas=[{"source": str(i)} for i in range(len(texts))]).as_retriever()
+#        docs = docsearch.get_relevant_documents(query)
+            if st.session_state.model_name == 'gpt-4': 
+                max_tkns=5500
+            else : 
+                max_tkns=3000
+            openai.api_key = os.environ["OPENAI_API_KEY"]
+            response = openai.ChatCompletion.create(
+                model="gpt-4",
+                messages=[
+                    {"role": "system", "content": query},
+                    {"role": "user", "content": input_text},
+                    ],
+                temperature = 0.7,
+                max_tokens=5500
+            )
+            st.session_state.output = choice.message["content"].strip() for choice in response["choices"]
+#        chain = load_qa_chain(ChatOpenAI(model = st.session_state.model_name,max_tokens=max_tkns,temperature=0), chain_type="stuff")
+#        st.session_state.output = chain.run(input_documents=docs, question=query)
         #st.session_state["output"] = output
         #col3.text_area('Result', value=output, key="output_data", height=450)
         st.experimental_rerun()