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diff --git a/kg_rag/prompt_based_generation/Llama/text_generation.py b/kg_rag/prompt_based_generation/Llama/text_generation.py
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+++ b/kg_rag/prompt_based_generation/Llama/text_generation.py
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+from langchain import PromptTemplate, LLMChain
+from kg_rag.utility import *
+import argparse
+
+parser = argparse.ArgumentParser()
+parser.add_argument('-m', type=str, default='method-1', help='Method to choose for Llama model')
+args = parser.parse_args()
+
+METHOD = args.m
+
+
+SYSTEM_PROMPT = system_prompts["PROMPT_BASED_TEXT_GENERATION"]
+MODEL_NAME = config_data["LLAMA_MODEL_NAME"]
+BRANCH_NAME = config_data["LLAMA_MODEL_BRANCH"]
+CACHE_DIR = config_data["LLM_CACHE_DIR"]
+
+
+
+INSTRUCTION = "Question: {question}"
+
+
+def main():
+    llm = llama_model(MODEL_NAME, BRANCH_NAME, CACHE_DIR, stream=True, method=METHOD)
+    template = get_prompt(INSTRUCTION, SYSTEM_PROMPT)
+    prompt = PromptTemplate(template=template, input_variables=["question"])    
+    llm_chain = LLMChain(prompt=prompt, llm=llm)
+    print(" ")
+    question = input("Enter your question : ")
+    print("Here is the prompt-based answer:")
+    print("")
+    output = llm_chain.run(question)
+
+
+
+if __name__ == "__main__":
+    main()