Update app.py

app.py

@@ -122,12 +122,15 @@ def talk(prompt, history):
     global historylog
 #    for user_message, bot_message in history[0:]:
 #        historylog += f"<s>[INST] {user_message} [/INST] {bot_message} </s>"
-    historylog += f"<s> {prompt} \n {response} </s>"
+    historylog += f"{prompt} \n {response} "
     print("history log")
     print(str(historylog))
     print("history log printed")
-    with open('file.txt','w+') as data:  
-      data.write(str(historylog))
+    data = open('file.txt','w+')  
+    data.write(str(historylog))
+    print(data.read())
+    data.close()
+    
 
 #    from huggingface_hub import HfApi
 #    api = HfApi()
@@ -138,36 +141,18 @@ def talk(prompt, history):
 #        repo_type="space"
 #    )
     
-    print("upload section passed")
-    
-    
-    
-    
+    print("upload section passed")    
     
     for i in range(len(response)):
         time.sleep(0.05)
         yield response[: i+1]
-            
-#    return(stream['choices'][0]['message']['content'])
-    
-#    text = ""
-#    for output in stream:
-#       text += output['choices'][0]['message']['content']  
-#       print(f"{output}")
-#       print("check3H")
-#       print(text)
-#       yield text 
- 
-    
     
     # calling the model to generate response based on message/ input
     # do_sample if set to True uses strategies to select the next token from the probability distribution over the entire vocabulary
     # temperature controls randomness. more renadomness with higher temperature
     # only the tokens comprising the top_p probability mass are considered for responses
     # This output is a data structure containing all the information returned by generate(), but that can also be used as tuple or dictionary.
- 
 
-    
 TITLE = "AI Copilot for Diabetes Patients"
 
 DESCRIPTION = "I provide answers to concerns related to Diabetes"