Update app.py

app.py

@@ -64,9 +64,9 @@ def audio_tag(
     
 
 def formatted_message(audio_class):
-    if cached_audio_class != audio_class:
-        cached_audio_class = audio_class
-        prefix = f"""You are going to act as a magical tool that allows for humans to communicate with non-human entities like 
+    #if cached_audio_class != audio_class:
+    cached_audio_class = audio_class
+    prefix = f"""You are going to act as a magical tool that allows for humans to communicate with non-human entities like 
 rocks, crackling fire, trees, animals, and the wind. In order to do this, we're going to provide you the human's text input for the conversation. 
 The goal is for you to embody that non-human entity and converse with the human.
 
@@ -78,27 +78,27 @@ Tree: Hello human, I am a tree
 
 Let's begin:
 Non-human Entity: {formatted_classname}"""
-        suffix = f'''{{history}}
+    suffix = f'''{{history}}
 Human Input: {{human_input}}
 {formatted_classname}:'''
 
-        suffix = f'''Source: {audio_class}
-        Length of Audio in Seconds: {audio_length} 
-        Human Input: {userText}
-        {audio_class} Response:'''
-        template = prefix + suffix
-
-        prompt = PromptTemplate(
-            input_variables=["history", "human_input"], 
-            template=template
-        )
-
-        chatgpt_chain = LLMChain(
-            llm=OpenAI(temperature=.5, openai_api_key=session_token), 
-            prompt=prompt, 
-            verbose=True, 
-            memory=ConversationalBufferWindowMemory(k=2, ai=audio_class),
-        )
+    suffix = f'''Source: {audio_class}
+    Length of Audio in Seconds: {audio_length} 
+    Human Input: {userText}
+    {audio_class} Response:'''
+    template = prefix + suffix
+
+    prompt = PromptTemplate(
+        input_variables=["history", "human_input"], 
+        template=template
+    )
+
+    chatgpt_chain = LLMChain(
+        llm=OpenAI(temperature=.5, openai_api_key=session_token), 
+        prompt=prompt, 
+        verbose=True, 
+        memory=ConversationalBufferWindowMemory(k=2, ai=audio_class),
+    )
 
     output = chatgpt_chain.predict(human_input=message)