Update app.py

app.py

@@ -38,6 +38,61 @@ from templates import css, bot_template, user_template
 st.set_page_config(page_title="GPT Streamlit Document Reasoner", layout="wide")
 should_save = st.sidebar.checkbox("💾 Save", value=True)
 
+# LLM engines for ChatCompletion and Chat with files
+def chat_with_model(prompt, document_section, model_choice='gpt-3.5-turbo'):
+    model = model_choice
+    conversation = [{'role': 'system', 'content': 'You are a helpful assistant.'}]
+    conversation.append({'role': 'user', 'content': prompt})
+    if len(document_section)>0:
+        conversation.append({'role': 'assistant', 'content': document_section})
+        
+    start_time = time.time()
+    report = []
+    res_box = st.empty()
+    collected_chunks = []
+    collected_messages = []
+    
+    key = os.getenv('OPENAI_API_KEY')
+    openai.api_key = key
+    for chunk in openai.ChatCompletion.create(
+        model='gpt-3.5-turbo',
+        messages=conversation,
+        temperature=0.5,
+        stream=True  
+    ):
+        
+        collected_chunks.append(chunk)  # save the event response
+        chunk_message = chunk['choices'][0]['delta']  # extract the message
+        collected_messages.append(chunk_message)  # save the message
+        
+        content=chunk["choices"][0].get("delta",{}).get("content")
+        
+        try:
+            report.append(content)
+            if len(content) > 0:
+                result = "".join(report).strip()
+                #result = result.replace("\n", "")        
+                res_box.markdown(f'*{result}*') 
+        except:
+            st.write(' ')
+        
+    full_reply_content = ''.join([m.get('content', '') for m in collected_messages])
+    st.write("Elapsed time:")
+    st.write(time.time() - start_time)
+    readitaloud(full_reply_content)
+    return full_reply_content
+
+def chat_with_file_contents(prompt, file_content, model_choice='gpt-3.5-turbo'):
+    conversation = [{'role': 'system', 'content': 'You are a helpful assistant.'}]
+    conversation.append({'role': 'user', 'content': prompt})
+    if len(file_content)>0:
+        conversation.append({'role': 'assistant', 'content': file_content})
+    response = openai.ChatCompletion.create(model=model_choice, messages=conversation)
+    return response['choices'][0]['message']['content']
+
+
+
+
 
 def link_button_with_emoji(url, title, emoji_summary):
     emojis = ["💉", "🏥", "🌡️", "🩺", "🌡️", "🔬", "💊", "🧪", "👨‍⚕️", "👩‍⚕️"]
@@ -361,57 +416,6 @@ def readitaloud(result):
     components.html(documentHTML5, width=800, height=300)
     #return result
 
-def chat_with_model(prompt, document_section, model_choice='gpt-3.5-turbo'):
-    model = model_choice
-    conversation = [{'role': 'system', 'content': 'You are a helpful assistant.'}]
-    conversation.append({'role': 'user', 'content': prompt})
-    if len(document_section)>0:
-        conversation.append({'role': 'assistant', 'content': document_section})
-        
-    start_time = time.time()
-    report = []
-    res_box = st.empty()
-    collected_chunks = []
-    collected_messages = []
-    
-    key = os.getenv('OPENAI_API_KEY')
-    openai.api_key = key
-    for chunk in openai.ChatCompletion.create(
-        model='gpt-3.5-turbo',
-        messages=conversation,
-        temperature=0.5,
-        stream=True  
-    ):
-        
-        collected_chunks.append(chunk)  # save the event response
-        chunk_message = chunk['choices'][0]['delta']  # extract the message
-        collected_messages.append(chunk_message)  # save the message
-        
-        content=chunk["choices"][0].get("delta",{}).get("content")
-        
-        try:
-            report.append(content)
-            if len(content) > 0:
-                result = "".join(report).strip()
-                #result = result.replace("\n", "")        
-                res_box.markdown(f'*{result}*') 
-        except:
-            st.write(' ')
-        
-    full_reply_content = ''.join([m.get('content', '') for m in collected_messages])
-    st.write("Elapsed time:")
-    st.write(time.time() - start_time)
-    readitaloud(full_reply_content)
-    return full_reply_content
-
-def chat_with_file_contents(prompt, file_content, model_choice='gpt-3.5-turbo'):
-    conversation = [{'role': 'system', 'content': 'You are a helpful assistant.'}]
-    conversation.append({'role': 'user', 'content': prompt})
-    if len(file_content)>0:
-        conversation.append({'role': 'assistant', 'content': file_content})
-    response = openai.ChatCompletion.create(model=model_choice, messages=conversation)
-    return response['choices'][0]['message']['content']
-
 def extract_mime_type(file):
     # Check if the input is a string
     if isinstance(file, str):