1 files changed, 38 insertions, 0 deletions
diff --git a/kg_rag/prompt_based_generation/Llama/run_mcq_qa.py b/kg_rag/prompt_based_generation/Llama/run_mcq_qa.py
new file mode 100644
index 0000000..e3eb1b0
--- /dev/null
+++ b/kg_rag/prompt_based_generation/Llama/run_mcq_qa.py
@@ -0,0 +1,38 @@
+from langchain import PromptTemplate, LLMChain
+from kg_rag.utility import *
+
+
+QUESTION_PATH = config_data["MCQ_PATH"]
+SYSTEM_PROMPT = system_prompts["MCQ_QUESTION_PROMPT_BASED"]
+SAVE_PATH = config_data["SAVE_RESULTS_PATH"]
+MODEL_NAME = config_data["LLAMA_MODEL_NAME"]
+BRANCH_NAME = config_data["LLAMA_MODEL_BRANCH"]
+CACHE_DIR = config_data["LLM_CACHE_DIR"]
+
+
+
+save_name = "_".join(MODEL_NAME.split("/")[-1].split("-"))+"_prompt_based_two_hop_mcq_from_monarch_and_robokop_response.csv"
+
+INSTRUCTION = "Question: {question}"
+
+
+def main():
+    start_time = time.time()
+    llm = llama_model(MODEL_NAME, BRANCH_NAME, CACHE_DIR)
+    template = get_prompt(INSTRUCTION, SYSTEM_PROMPT)
+    prompt = PromptTemplate(template=template, input_variables=["question"])
+    llm_chain = LLMChain(prompt=prompt, llm=llm)
+    question_df = pd.read_csv(QUESTION_PATH)
+    answer_list = []
+    for index, row in question_df.iterrows():
+        question = row["text"]
+        output = llm_chain.run(question)
+        answer_list.append((row["text"], row["correct_node"], output))
+    answer_df = pd.DataFrame(answer_list, columns=["question", "correct_answer", "llm_answer"])
+    answer_df.to_csv(os.path.join(SAVE_PATH, save_name), index=False, header=True)
+    print("Completed in {} min".format((time.time()-start_time)/60))
+    
+    
+
+if __name__ == "__main__":
+    main()