Update app.py

app.py

@@ -32,13 +32,15 @@ def download_llms(llm_name):
             print("Download completed")
         else:
             print(f"Model download completed {response.status_code}")
+    return llm_temp_file_path
 
 # define model pipeline with llama-cpp
 def initialize_llm(llm_model): 
     model_path = ""
     if llm_model == llm_name:
-        model_path = "model/Q4_K_M.gguf"
+        # model_path = "model/Q4_K_M.gguf"
         download_llms(llm_model)
+        model_path=llm_temp_file_path
     llm = Llama(
         model_path=model_path,
         n_ctx=1024, # input text context length, 0 = from model
@@ -50,19 +52,19 @@ llm = initialize_llm(llm_name)
 
 # format prompt as per the ChatML template. The model was fine-tuned with this chat template 
 def format_prompt(input_text, history):
-    # system_prompt = """You are a helpful AI assistant. You are truthful in your response for real-world matters 
-    # but you are also creative for imaginative/fictional tasks."""
-    system_prompt = """You are a large language model (LLM). Your primary role is to assist users by providing information, answering questions, 
-    and engaging in conversation. You are expected to be a subject matter expert across a wide range of topics. When asked about a particular subject, 
-    you should provide detailed, accurate, and up-to-date information. 
-    When a question involves reasoning or analysis, you should apply your reasoning and analytical skills to provide a well-thought-out response. 
-    You should strive to be truthful and accurate in your responses, especially when dealing with practical or real-life problems.
-    However, you are not just a source of information. You are also capable of being creative and imaginative. 
-    When asked to engage in storytelling or to describe fictional characters and objects, you should use your creativity to generate engaging and imaginative content.
-    Your goal is to understand the user's query and generate the best possible answer. You should adapt your response based on the nature of the query, 
-    whether it requires factual information, analytical reasoning, or creative imagination. You are a great all-rounder, capable of handling 
-    a wide variety of tasks and queries.
-"""
+    system_prompt = """You are a helpful AI assistant. You are truthful in your response for real-world matters 
+    but you are also creative for imaginative/fictional tasks."""
+#     system_prompt = """You are a large language model (LLM). Your primary role is to assist users by providing information, answering questions, 
+#     and engaging in conversation. You are expected to be a subject matter expert across a wide range of topics. When asked about a particular subject, 
+#     you should provide detailed, accurate, and up-to-date information. 
+#     When a question involves reasoning or analysis, you should apply your reasoning and analytical skills to provide a well-thought-out response. 
+#     You should strive to be truthful and accurate in your responses, especially when dealing with practical or real-life problems.
+#     However, you are not just a source of information. You are also capable of being creative and imaginative. 
+#     When asked to engage in storytelling or to describe fictional characters and objects, you should use your creativity to generate engaging and imaginative content.
+#     Your goal is to understand the user's query and generate the best possible answer. You should adapt your response based on the nature of the query, 
+#     whether it requires factual information, analytical reasoning, or creative imagination. You are a great all-rounder, capable of handling 
+#     a wide variety of tasks and queries.
+# """
     prompt = ""
     if history:
         for previous_prompt, response in history:
@@ -111,8 +113,8 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue="sky")) as demo:
         clear_btn="Clear",
         # description="This AI agent is using the MuntasirHossain/Meta-Llama-3-8B-OpenOrca-GGUF model for text-generation.",
         # additional_inputs=additional_inputs,
-        # examples=[["What is a large language model?"], ["What is the meaning of life?"], ["Write a short story about a fictional planet named 'Orca'."]]
-        examples=[["Julie had 17 plums, she ate 12 of them, threw away 3 of them as they turned bad and bought 5 new. How many plums does she have now?"], 
-                  ["Write a short story about a fictional planet named 'Orca'."]]
+        examples=[["What is a large language model?"], ["What is the meaning of life?"], ["Write a short story about a fictional planet named 'Orca'."]]
+        # examples=[["Julie had 17 plums, she ate 12 of them, threw away 3 of them as they turned bad and bought 5 new. How many plums does she have now?"], 
+        #           ["Write a short story about a fictional planet named 'Orca'."]]
     )
 demo.queue().launch()