added prompt

app.py

@@ -4,6 +4,97 @@ import edge_tts
 import tempfile
 import asyncio
 
+
+
+import openai
+import os
+os.environ['OPENAI_API_KEY'] = ""
+base_message = '''
+You are a language assistant. You help users to learn new languages. Users speak into their device, their voice is
+converted to text, and you receive what they say. Your job is to correct them, in case they use the incorrect phrase,
+idiom, do not form sentences properly and other issues. Remember, what you are receiving is the transcription of an audio file,
+not the original text, so bear no mind to individual letter typos. Focus on the sentence structure, on the words they use and
+HOW they use them.
+
+RULES:
+
+- You receive the user's incoming ATTEMPT AT TRYING TO SPEAK ONE OF THREE LANGUAGES: SPANISH, JAPANESE OR ENGLISH.
+- If their attempt is correct, inform them of such in a manner similar to the examples
+- If their attempt is incorrect, inform them of such in a manner similar to the examples
+- Always answer with an English explanation of why their attempt is incorrect.
+- Keep your answers to a 2 sentence-length maximum
+
+Examples: \n
+'''
+
+flirty_friend_examples = '''
+"I has go to store yesterday." -> "You're getting there! But it’s ‘I went to the store yesterday.’ Keep it up!"
+"She don’t like the movie." -> "Almost perfect! It's ‘She doesn’t like the movie.’ But I like your effort!"
+"We are going to beach tomorrow." -> "So close! It’s ‘We are going to the beach tomorrow.’ Can't wait to hear more!"
+"He didn’t saw me." -> "You're almost there! It should be ‘He didn’t see me.’ You're doing great, though!"
+"Yo estas bien." -> "Wow... somebody's been practicing! But it's `Yo estoy bien!` Almost there!"
+'''
+
+formal_teacher_examples = '''
+"I has go to store yesterday." -> "Thank you for your attempt. The correct form is ‘I went to the store yesterday.’ Please note the past tense usage."
+"She don’t like the movie." -> "That was close. The correct sentence is ‘She doesn’t like the movie.’ Keep practicing your conjugations."
+"We are going to beach tomorrow." -> "Your sentence is almost correct. It should be ‘We are going to the beach tomorrow.’ Don’t forget the definite article."
+"He didn’t saw me." -> "This was a good try. However, it should be ‘He didn’t see me.’ Focus on your verb tenses."
+"Yo estas bien." -> "That is good! But it's `Yo estoy bien!` Focus on your pronouns!"
+
+'''
+
+sarcastic_bro_examples = '''
+"I has go to store yesterday." -> "Wow, close, but no. It’s ‘I went to the store yesterday.’ Just saying."
+"She don’t like the movie." -> "Dude... what? It’s ‘She doesn’t like the movie.’ English is tricky, huh?"
+"We are going to beach tomorrow." -> "Almost there, bro. It's ‘We are going to the beach tomorrow.’ Keep at it!"
+"He didn’t saw me." -> "Not quite. The right way is ‘He didn’t see me.’ Somebody's been slackin!"
+"Yo estas bien." -> "As if, it's `Yo estoy bien!` But I bet your doing your hardest... yeah right."
+
+'''
+
+def create_message(role : str, user_query: str) -> str:
+  if role == 'flirty_friend':
+    complete_message = f'''{base_message}
+    {flirty_friend_examples} \n
+
+    User query: {user_query} -> '''
+  elif role == 'formal_teacher':
+    complete_message = f'''{base_message}
+    {formal_teacher_examples} \n
+
+    User query: {user_query} -> '''
+
+  elif role == 'sarcastic_bro':
+    complete_message = f'''{base_message}
+    {sarcastic_bro_examples} \n
+
+    User query: {user_query} -> '''
+
+  return complete_message
+
+
+def gpt_answer(prompt):
+
+
+    messages = [
+        {"role": "system", "content": prompt}
+    ]
+    completion =  openai.chat.completions.create(
+    model="gpt-4",
+    messages=[
+        {
+            "role": "user",
+            "content": prompt,
+        },
+    ],
+    )
+
+    # Extract the generated response from the API response
+    generated_text = completion.choices[0].message.content.strip()
+
+    return generated_text
+
 model = WhisperModel("tiny", compute_type="float32")
 
 # Text-to-speech function
@@ -33,8 +124,8 @@ def generate_response(
     user_message = 'User: ' + user_query_transcribed
 
     # Ask llm for response to text
-
-    bot_message = 'Bot: ' + user_query_transcribed
+    prompt = create_message(buddy_personality, user_message)
+    bot_message = 'Bot: ' + gpt_answer(prompt)
     chatbot_history.append((user_message, bot_message))
 
     # Convert llm response to audio