Update app.py

app.py

@@ -29,49 +29,55 @@ async def advancedPromptPipeline(InputPrompt):
     start_time = time.time()
     advanced_prompt = await enhancer.enhance_prompt(input_prompt, perform_eval=False)
     elapsed_time = time.time() - start_time
-    
-    yield {
-        "model": model,
-        "elapsed_time": elapsed_time,
-        "prompt_tokens": enhancer.prompt_tokens,
-        "completion_tokens": enhancer.completion_tokens,
-        "approximate_cost": (enhancer.prompt_tokens*i_cost)+(enhancer.completion_tokens*o_cost),
-        "inout_prompt": input_prompt,
-        "advanced_prompt": advanced_prompt["advanced_prompt"],
+
+
+    yield advanced_prompt["advanced_prompt"]
+    #return {
+        #"model": model,
+        #"elapsed_time": elapsed_time,
+        #"prompt_tokens": enhancer.prompt_tokens,
+        #"completion_tokens": enhancer.completion_tokens,
+        #"approximate_cost": (enhancer.prompt_tokens*i_cost)+(enhancer.completion_tokens*o_cost),
+        #"inout_prompt": input_prompt,
+        #"advanced_prompt": advanced_prompt["advanced_prompt"],
     }
 
 
 def respond(
     message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
+    #history: list[tuple[str, str]],
+    #system_message,
+    #max_tokens,
+    #temperature,
+    #top_p,
 ):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
+    #messages = [{"role": "system", "content": system_message}]
 
-    messages.append({"role": "user", "content": message})
+    #for val in history:
+    #    if val[0]:
+    #        messages.append({"role": "user", "content": val[0]})
+    #    if val[1]:
+    #        messages.append({"role": "assistant", "content": val[1]})
+    #
+    #messages.append({"role": "user", "content": message})
 
+    messages = []
+    
     response = ""
 
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
+    advancedPromptPipeline(InputPrompt)
+
+    #for message in client.chat_completion(
+    #    messages,
+    #    max_tokens=max_tokens,
+    #    stream=True,
+    #    temperature=temperature,
+    #    top_p=top_p,
+    #):
+    #    token = message.choices[0].delta.content
+
+    #    response += token
+    #    yield response
 
 """
 For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface