Update app.py

app.py

@@ -1,20 +1,20 @@
 import gradio as gr
-import ctypes
+import ctypes #to run on C api directly 
 import llama_cpp
 from llama_cpp import Llama
-from huggingface_hub import hf_hub_download
+from huggingface_hub import hf_hub_download #load from huggingfaces 
 
 
 llm = Llama(model_path= hf_hub_download(repo_id="TheBloke/StableBeluga-7B-GGML", filename="stablebeluga-7b.ggmlv3.q6_K.bin"))
 
 def generate_text(input_text):
-    output = llm(f"Q: {input_text} A:", max_tokens=521, stop=["Q:", "\n"], echo=True)
+    output = llm(f"Q: {input_text}  A:", max_tokens=521, stop=["Q:", "\n"], echo=True)
     return output['choices'][0]['text']
 
 input_text = gr.inputs.Textbox(lines= 10, label="Enter your input text")
 output_text = gr.outputs.Textbox(label="Output text")
 
-description = "llama.cpp implementation in python [https://github.com/abetlen/llama-cpp-python]"
+description = "bro neil it currently dosent work two people sending it request at the same time so going to fix that but currently running ggml models with llama.cpp implementation in python [https://github.com/abetlen/llama-cpp-python]"
 
 examples = [
     ["What is the capital of France? ", "The capital of France is Paris."],
@@ -23,6 +23,6 @@ examples = [
 ]
 
 
-demo = gr.Interface(fn=generate_text, inputs=input_text, outputs=output_text, title="Llama Language Model", description=description, examples=examples).queue()
+demo = gr.Interface(fn=generate_text, inputs=input_text, outputs=output_text, title="Llama Language Model", description=description, examples=examples).queue
 demo.queue(concurrency_count=3)
 demo.launch()