Upload app.py

app.py

@@ -0,0 +1,66 @@
+from langchain_community.llms.ctransformers import CTransformers
+from langchain.chains.llm import LLMChain
+from langchain.prompts import PromptTemplate
+import os
+import gradio as gr
+import time
+
+custom_prompt_template=""""
+You are an AI coding assistant and your task is to solve coding problems
+and return code snippets based on the user's query. Below is the user's query.
+Query:{query}
+You just return the helpful code and related details.
+Helpful code and related details:
+"""
+
+def set_custom_prompt():
+    prompt=PromptTemplate(
+        template=custom_prompt_template,
+        input_variables=['query']
+    )
+    return prompt
+
+def load_model():
+    llm=CTransformers(
+        model='codellama-7b-instruct.ggmlv3.Q4_K_M.bin',
+        model_type='llama',
+        max_new_tokens=1096,
+        temperature=0.2,
+        repetition_penalty=1.13
+                
+    )
+    
+    return llm
+
+def chain_pipeline():
+    llm=load_model()
+    qa_prompt=set_custom_prompt()
+    qa_chain=LLMChain(
+        prompt=qa_prompt,
+        llm=llm
+    )
+    return qa_chain
+
+llmchain=chain_pipeline()
+
+def bot(query):
+    llm_response=llmchain.run({'query':query})
+    return llm_response
+
+with gr.Blocks(title="Can AI code ? ") as demo:
+    gr.Markdown('# Code LLAMA demo')
+    chatbot=gr.Chatbot([],elem_id='chatbot',height=700)
+    msg=gr.Textbox()
+    clear=gr.ClearButton([msg,chatbot])
+    
+    
+    def respond(message,chat_history):
+        bot_message=bot(message)
+        chat_history.append((message,bot_message))
+        time.sleep(2)
+        return "",chat_history
+    
+    msg.submit(respond,[msg,chatbot],[msg,chatbot])
+    
+
+demo.launch()