update gptapp

app.py

@@ -19,8 +19,8 @@ parser.add_argument('-p', '--prompt', default='plant', help="String prompt templ
 parser.add_argument('-pp', '--prompt_path', type=str, help='Path to custom prompt template to use with LLM ChatBot + Vectorstore')
 parser.add_argument('-t', '--temperature', type=float, default=0.7, help='LLM temperature setting... lower == more deterministic')
 parser.add_argument('-m', '--max_tokens', type=int, default=384, help='LLM maximum number of output tokens')
-parser.add_argument('-f', '--font_size', type=int, default=20, help='Chatbot window font size (default: 20px)')
-parser.add_argument('-tp', '--use_terence_prompt', action='store_true', default=True, help="Default is to use chatGPT clone prompt")
+parser.add_argument('-w', '--memory_window', type=int, default=10, help='Chatbot context memory window size')
+parser.add_argument('-v', '--verbose', action='store_true', default=False)
 args = parser.parse_args()
 
 
@@ -149,10 +149,10 @@ def get_chain(prompt=None):
     )
 
     chatgpt_chain = LLMChain(
-        llm=OpenAIChat(temperature=0.7), 
+        llm=OpenAIChat(temperature=args.temperature, max_tokens=args.max_tokens), 
         prompt=prompt or default_prompt, 
-        verbose=True, 
-        memory=ConversationalBufferWindowMemory(k=10),
+        verbose=args.verbose, 
+        memory=ConversationalBufferWindowMemory(k=args.memory_window),
     )
 
     return chatgpt_chain
@@ -160,7 +160,7 @@ def get_chain(prompt=None):
 
 
 def initialize_chain():
-    chain = get_chain(prompt=PROMPT if args.use_terence_prompt else None)
+    chain = get_chain(prompt=PROMPT)
     return chain
 
 
@@ -239,7 +239,12 @@ with block:
 
     with gr.Column():
         with gr.Row():
-            gr.Image(type='filepath', value='McKenna3.jpg', shape=(200,100))
+            with gr.Column(min_width=200):
+                pass
+            with gr.Column():
+                gr.Image(type='filepath', value='McKenna3.jpg')
+            with gr.Column(min_width=200):
+                pass
 
     gr.HTML(
         "<center>Powered by <a href='https://github.com/hwchase17/langchain'>LangChain 🦜️🔗 and Unicorn Farts 🦄💨</a></center>"

appOG.py

@@ -19,7 +19,7 @@ parser.add_argument('-d', '--data_directory', type=str, help='Path to directory
 parser.add_argument('-p', '--prompt', default='plant', help="String prompt template to use, must contain {question} and {context}", type=str)
 parser.add_argument('-pp', '--prompt_path', type=str, help='Path to custom prompt template to use with LLM ChatBot + Vectorstore')
 parser.add_argument('-t', '--temperature', type=float, default=0.7, help='LLM temperature setting... lower == more deterministic')
-parser.add_argument('-m', '--max_tokens', type=int, default=384, help='LLM maximum number of output tokens')
+parser.add_argument('-m', '--max_tokens', type=int, default=500, help='LLM maximum number of output tokens')
 parser.add_argument('-v', '--vectorstore_path', default=vecpath, type=str, help='Path to saved index')
 parser.add_argument('-dv', '--live_vectorstore_path', default=r"indices\vectorstore_from_docs.pkl", type=str, help='Path to save temporary index')
 parser.add_argument('-f', '--font_size', type=int, default=20, help='Chatbot window font size (default: 20px)')