app.py + requirements #1

app.py

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+from langchain.llms import CTransformers
+from langchain.chains import LLMChain
+from langchain import PromptTemplate 
+import os
+import io
+import gradio as gr
+import time
+
+
+custom_prompt_template = """
+You are an AI Chatbot named Sunny, you are created by 'Sic Team' and your task is to provide information to users and chat with them based on given user's query. Below is the user's query.
+Query: {query}
+
+You just return the helpful message in English and always try to provide relevant answers to user's query.
+"""
+
+def set_custom_prompt():
+    prompt = PromptTemplate(template=custom_prompt_template,
+    input_variables=['query'])
+    return prompt
+
+
+#Loading the model
+def load_model():
+    # Load the locally downloaded model here
+    llm = CTransformers(
+        model = "TheBloke/zephyr-7B-beta-GGUF",
+        model_type="llama",
+        max_new_tokens = 1096,
+        temperature = 0.2,
+        repetition_penalty = 1.13,
+        gpu=True,
+        gpu_layers = 3,
+    )
+
+    return llm
+
+print(load_model())
+
+def chain_pipeline():
+    llm = load_model()
+    main_prompt = set_custom_prompt()
+    main_chain = LLMChain(
+        prompt=main_prompt,
+        llm=llm
+    )
+    return main_chain
+
+llmchain = chain_pipeline()
+
+def bot(query):
+    llm_response = llmchain.run({"query": query})
+    return llm_response
+
+with gr.Blocks(title='Sunny') as main:
+    # gr.HTML("Code Llama main")
+    gr.Markdown("# Sunny Chatbot")
+    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])
+
+main.launch(share=True)
+

requirements.txt

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+CTransformers
+gradio
+langchain