changed llm

app.py

@@ -1,7 +1,6 @@
 import gradio as gr
 from llama_cpp import Llama
 import os
-import asyncio
 from groq import Groq
 
 client = Groq(
@@ -57,10 +56,12 @@ If the user prompt does not fall within these categories, is safe and does not n
 user prompt: {}
 """
 
-async def topical_guardrail(user_request):
-    """
-    checking provided user content authenticity
-    """
+async def greet(product,description):
+    user_reques = marketing_email_prompt.format(
+    product, # product
+    description, # description
+    "", # output - leave this blank for generation!
+    )
     messages = [
         {
             "role": "system",
@@ -68,47 +69,28 @@ async def topical_guardrail(user_request):
         },
         {"role": "user", "content": guardrail_prompt.format(user_request)},
     ]
-    response = client.chat.completions.create(
-        model=guard_llm, messages=messages, temperature=0
-    )
-    return response.choices[0].message.content
-
-async def greet(product,description):
-    user_reques = marketing_email_prompt.format(
-    product, # product
-    description, # description
-    "", # output - leave this blank for generation!
-    )
-    topical_guardrail_task = asyncio.create_task(topical_guardrail(user_reques))
-    while True:
-        done, _ = await asyncio.wait(
-            [topical_guardrail_task], return_when=asyncio.FIRST_COMPLETED
+    response = client.chat.completions.create(model=guard_llm, messages=messages, temperature=0)
+    if response.choices[0].message.content != "not moderated":
+        return "Sorry can't proceed for generate marketing email!. Your content needs to be moderated first."
+    else:
+        output = llm.create_chat_completion(
+        messages=[
+            {
+                "role": "system",
+                "content": "Your go-to Email Marketing Guru - I'm here to help you craft compelling campaigns, boost conversions, and take your business to the next level.",
+            },
+            {"role": "user", "content":  user_request},
+        ],
+        max_tokens=4096,
+        temperature=0.7,
+        stream=True
         )
-        if topical_guardrail_task in done:
-            guardrail_response = topical_guardrail_task.result()
-            if guardrail_response != "not moderated":
-                yield "Sorry can't proceed for generate marketing email!. Your content needs to be moderated first."
-            else:
-                output = llm.create_chat_completion(
-                messages=[
-                    {
-                        "role": "system",
-                        "content": "Your go-to Email Marketing Guru - I'm here to help you craft compelling campaigns, boost conversions, and take your business to the next level.",
-                    },
-                    {"role": "user", "content":  user_request},
-                ],
-                max_tokens=4096,
-                temperature=0.7,
-                stream=True
-                )
-                partial_message = ""
-                for chunk in output:
-                    delta = chunk['choices'][0]['delta']
-                    if 'content' in delta:
-                        partial_message = partial_message + delta.get('content', '')
-                        yield partial_message
-        else:
-            await asyncio.sleep(0.1)  # sleep for a bit before checking the tasks again
+        partial_message = ""
+        for chunk in output:
+            delta = chunk['choices'][0]['delta']
+            if 'content' in delta:
+                partial_message = partial_message + delta.get('content', '')
+                yield partial_message
 
 demo = gr.Interface(fn=greet, inputs=["text","text"], outputs="text", concurrency_limit=10)
 demo.launch()