| from data_ingestion import data_ingestion |
| from vectorStore import vectorStore,embedding |
| from llm_configuration import llm, prompt_helper |
| from langchain_core.runnables import RunnablePassthrough |
| from langchain_core.output_parsers import StrOutputParser |
|
|
| def main(path,question): |
| path = path |
| data = data_ingestion(path) |
| retriever = vectorStore(data,embedding) |
| prompt = prompt_helper() |
| chain = ( |
| {'context': retriever, 'question': RunnablePassthrough()} |
| | prompt |
| | llm |
| | StrOutputParser() |
| ) |
| return chain.invoke(question) |
|
|
| if __name__ == "__main__": |
| main() |
|
|