Fix langchain

app.py

@@ -26,7 +26,8 @@ cached_audio_class = "c"
 template = None
 prompt = None
 chain = None
-
+formatted_classname = "tree"
+chain = 
 
 def format_classname(classname):
   return classname.capitalize()
@@ -60,11 +61,11 @@ def audio_tag(
     # Print audio tagging top probabilities
 
     label = labels[sorted_indexes[0]]
-    return formatted_message(format_classname(label), human_input)
-
-    
+    formatted_classname = label
+    chain = construct_langchain(formatted_classname)
+    return formatted_classname
 
-def formatted_message(audio_class, human_input):
+def construct_langchain(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 
@@ -79,32 +80,31 @@ def formatted_message(audio_class, human_input):
     
     Let's begin:
     Non-human Entity: {audio_class}"""
-        suffix = f'''{{history}}
-    Human Input: {{human_input}}
-    {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_prefix=audio_class),
-        )
 
-    output = chatgpt_chain.predict(human_input=message)
+    suffix = f'''Source: {audio_class}
+    Length of Audio in Seconds: 2 seconds
+    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_prefix=audio_class),
+    )
 
-    return output
+    return chatgpt_chain
 
+def predict(input, history=[]):
+    formatted_message = chain.predict(human_input=input)
+    history.append(formatted_message)
+    return formatted_message, history
 
 demo = gr.Interface(
     audio_tag,
@@ -112,7 +112,9 @@ demo = gr.Interface(
         gr.Audio(source="upload", type="filepath", label="Your audio"),
         gr.Textbox(),
     ],
-    gr.Textbox(),
+    fn=predict,
+    inputs=["text", "state"],
+    outputs=["chatbot", "state"],
     title="AnyChat",
     description="Non-Human entities have many things to say, listen to them!",
-).launch(debug=True)
+).launch(debug=True)