Update app.py

app.py

@@ -22,35 +22,6 @@ def classify_mood(input_string):
         if word in input_string:
             return word, True
     return None, False
-
-def generate(prompt, history, temperature=0.1, max_new_tokens=2048, top_p=0.8, repetition_penalty=1.0):
-    temperature = float(temperature)
-    if temperature < 1e-2:
-        temperature = 1e-2
-    top_p = float(top_p)
-
-    generate_kwargs = dict(
-        temperature=temperature,
-        max_new_tokens=max_new_tokens,
-        top_p=top_p,
-        repetition_penalty=repetition_penalty,
-        do_sample=True,
-        seed=42,
-    )
-
-    formatted_prompt = format_prompt(prompt, history)
-
-    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
-    output = ""
-
-    for response in stream:
-        output += response.token.text
-        mood, is_classified = classify_mood(output)
-        if is_classified:
-            playlist_message = f"Playing {mood.capitalize()} playlist for you!"
-            return playlist_message
-    return output
-
     def format_prompt(self, message, history):
         fixed_prompt = """You are a mood classification chatbot. Your ONLY goal is to accurately classify the user's mood into one of four categories: Happy, Sad, Instrumental, or Party. Follow these rules strictly:
 
@@ -111,6 +82,35 @@ Remember, NEVER classify a mood without first asking for clarification about the
     prompt += f"User: {message}\nLLM Response:"
     return prompt
 
+def generate(prompt, history, temperature=0.1, max_new_tokens=2048, top_p=0.8, repetition_penalty=1.0):
+    temperature = float(temperature)
+    if temperature < 1e-2:
+        temperature = 1e-2
+    top_p = float(top_p)
+
+    generate_kwargs = dict(
+        temperature=temperature,
+        max_new_tokens=max_new_tokens,
+        top_p=top_p,
+        repetition_penalty=repetition_penalty,
+        do_sample=True,
+        seed=42,
+    )
+
+    formatted_prompt = format_prompt(prompt, history)
+
+    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
+    output = ""
+
+    for response in stream:
+        output += response.token.text
+        mood, is_classified = classify_mood(output)
+        if is_classified:
+            playlist_message = f"Playing {mood.capitalize()} playlist for you!"
+            return playlist_message
+    return output
+
+
 async def text_to_speech(text):
     communicate = edge_tts.Communicate(text)
     with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp_file: