update

app.py

@@ -15,21 +15,23 @@ def transcript_audio(audio_file) -> str:
 
 
 def summarize_text(text: str, bullet_points: int, conclusion: bool) -> str:
-    llm_model = "meta-llama/Meta-Llama-3-8B-Instruct"
+    llm_model = "meta-llama/Meta-Llama-3-70B-Instruct"
     api = InferenceClient(llm_model, token=HUGGINGFACE_API_KEY)
     tokenizer = AutoTokenizer.from_pretrained(llm_model, token=HUGGINGFACE_API_KEY)
     if conclusion:
-        user_chat = f"Summarize the following text into {bullet_points} bullet points and a conclusion: {text}"
+        user_chat = f"Summarize the following text, into {bullet_points} bullet points and a conclusion:\n{text}"
     else:
         user_chat = (
-            f"Summarize the following text into {bullet_points} bullet points: {text}"
+            f"Summarize the following text, into {bullet_points} bullet points:\n{text}"
         )
     chat = [
+        {"role": "system", "content": "You are a Meeting Summarizer AI. You well help summarize the text into bullet points and a conclusion. Please return a Markdown formatted text. Remember to give it a title."},
         {"role": "user", "content": user_chat},
     ]
     prompt = tokenizer.apply_chat_template(
         chat, tokenize=False, add_generation_prompt=True
     )
+    
     summary = api.text_generation(prompt, max_new_tokens=250, do_sample=True)
     print(summary)
     return summary