Working Clean

.vs/ProjectSettings.json

@@ -0,0 +1,3 @@
+{
+  "CurrentProjectSetting": null
+}

app.py

@@ -1,10 +1,11 @@
-
-import os
-import openai
+import os
 import gradio as gr
+import json
+import requests
+import openai
 
 try:
-    openai.api_key = os.environ["OPENAI_API_KEY"]
+     openai.api_key = os.environ["OPENAI_API_KEY"]
 
 except KeyError:
     error_message = "System is at capacity right now.Please try again later"
@@ -16,26 +17,121 @@ else:
         {"role": "system", "content": "My AI Assistant"},
     ]
 
-messages = [
-    {"role": "system", "content": ""},
-]
-
-def chatbot(input):
-    try:
-        if input:
-            messages.append({"role": "user", "content": input})
-            prompt = "\n".join([f"{m['role']}: {m['content']}" for m in messages])
-            chat = openai.Completion.create(
-                engine="text-davinci-003", prompt=prompt, max_tokens=1024, n=1, stop=None, temperature=0.7
-            )
-            reply = chat.choices[0].text.strip()
-            messages.append({"role": "assistant", "content": reply})
-            return reply
-    except openai.error.OpenAIError as e:
-        return "System is at capacity right now.Please try again later"
-
-inputs = gr.inputs.Textbox(lines=7, label="Query")
-outputs = gr.outputs.Textbox(label="Response")
-
-gr.Interface(fn=chatbot, inputs=inputs, outputs=outputs,
-             theme=gr.themes.Default(primary_hue="slate")).launch()
+#Streaming endpoint for OPENAI ChatGPT
+API_URL = "https://api.openai.com/v1/chat/completions"
+top_p_chatgpt = 1.0
+temperature_chatgpt = 1.0
+
+#Predict function for CHATGPT
+def chatbot(inputs, chat_counter_chatgpt, chatbot_chatgpt=[], history=[]):  
+    #Define payload and header for chatgpt API
+    payload = {
+    "model": "gpt-3.5-turbo",
+    "messages": [{"role": "user", "content": f"{inputs}"}],
+    "temperature" : 1.0,
+    "top_p":1.0,
+    "n" : 1,
+    "stream": True,
+    "presence_penalty":0,
+    "frequency_penalty":0,
+    }
+
+    headers = {
+    "Content-Type": "application/json",
+    "Authorization": f"Bearer {openai.api_key}"
+    }
+    
+    #Handling the different roles for ChatGPT
+    if chat_counter_chatgpt != 0 :
+        messages=[]
+        for data in chatbot_chatgpt:
+          temp1 = {}
+          temp1["role"] = "user" 
+          temp1["content"] = data[0] 
+          temp2 = {}
+          temp2["role"] = "assistant" 
+          temp2["content"] = data[1]
+          messages.append(temp1)
+          messages.append(temp2)
+        temp3 = {}
+        temp3["role"] = "user" 
+        temp3["content"] = inputs
+        messages.append(temp3)
+        payload = {
+        "engine": "text-davinci-003",
+        "messages": messages, #[{"role": "user", "content": f"{inputs}"}],
+        "temperature" : temperature_chatgpt, #1.0,
+        "top_p": top_p_chatgpt, #1.0,
+        "n" : 1,
+        "stream": True,
+        "presence_penalty":0,
+        "frequency_penalty":0,
+        }
+
+    chat_counter_chatgpt+=1
+
+    history.append("You asked:  "+ inputs)
+
+    # make a POST request to the API endpoint using the requests.post method, passing in stream=True
+    response = requests.post(API_URL, headers=headers, json=payload, stream=True)
+    token_counter = 0 
+    partial_words = ""  
+
+    counter=0
+    for chunk in response.iter_lines():
+        #Skipping the first chunk
+        if counter == 0:
+          counter+=1
+          continue
+        # check whether each line is non-empty
+        if chunk.decode() :
+          chunk = chunk.decode()
+          # decode each line as response data is in bytes
+          if len(chunk) > 13 and "content" in json.loads(chunk[6:])['choices'][0]["delta"]:
+              partial_words = partial_words + json.loads(chunk[6:])['choices'][0]["delta"]["content"]
+              if token_counter == 0:
+                history.append(" " + partial_words)
+              else:
+                history[-1] = partial_words
+              chat = [(history[i], history[i + 1]) for i in range(0, len(history) - 1, 2) ]  # convert to tuples of list
+              token_counter+=1
+              yield chat, history, chat_counter_chatgpt  # this resembles {chatbot: chat, state: history}  
+
+
+def reset_textbox():
+    return gr.update(value="")
+
+def reset_chat(chatbot, state):
+    return None, []
+
+with gr.Blocks(css="""#col_container {width: 1000px; margin-left: auto; margin-right: auto;}
+                #chatgpt {height: 400px; overflow: auto;}} """, theme=gr.themes.Default(primary_hue="slate") ) as ChatGPTDavinci:
+    with gr.Row():
+      with gr.Column(scale=14):
+          with gr.Box():
+              with gr.Row():
+                  with gr.Column(scale=13):
+                    inputs = gr.Textbox(label="Ask me anything ⤵️   Try: Value of pi" )
+                  with gr.Column(scale=1):
+                      b1 = gr.Button('Submit', elem_id = 'submit').style(full_width=True)
+                      b2 = gr.Button('Clear', elem_id = 'clear').style(full_width=True)
+                  state_chatgpt = gr.State([])
+
+          with gr.Box():
+              with gr.Row():
+                  chatbot_chatgpt = gr.Chatbot(elem_id="chatgpt", label='My ChatGPT  Davinci')
+    chat_counter_chatgpt = gr.Number(value=0, visible=False, precision=0)
+             
+
+    inputs.submit(reset_textbox, [], [inputs])
+    
+    b1.click( chatbot, 
+                [ inputs,  chat_counter_chatgpt, chatbot_chatgpt, state_chatgpt], 
+                [chatbot_chatgpt, state_chatgpt],)
+
+    b2.click(reset_chat, [chatbot_chatgpt, state_chatgpt], [chatbot_chatgpt, state_chatgpt])
+
+    ChatGPTDavinci.queue(concurrency_count=16).launch(height= 2500, debug=True)
+
+
+