| from langchain_community.llms.huggingface_pipeline import HuggingFacePipeline | |
| from langchain.chains.summarize import load_summarize_chain | |
| from langchain.prompts import PromptTemplate | |
| def get_refine_chain(pipeline_or_llm, model_type): | |
| if model_type == "openai": | |
| llm = pipeline_or_llm | |
| question_template = """Write a concise summary of the following: | |
| {text} | |
| CONCISE SUMMARY:""" | |
| question_prompt = PromptTemplate.from_template(question_template) | |
| refine_template = """Your job is to produce a final summary | |
| We have provided an existing summary up to a certain point: {existing_answer} | |
| We have the opportunity to refine the existing summary (only if needed) with some more context below. | |
| ------------ | |
| {text} | |
| ------------ | |
| Given the new context, refine the original summary in bullets. If the context isn't useful return the original summary.""" | |
| refine_prompt = PromptTemplate.from_template(refine_template) | |
| else: | |
| question_prompt = PromptTemplate.from_template(template="{text}") | |
| refine_prompt = PromptTemplate.from_template(template= "{existing_answer}\n{text}") | |
| llm = HuggingFacePipeline(pipeline=pipeline_or_llm) | |
| refine_chain = load_summarize_chain( | |
| llm=llm, | |
| chain_type="refine", | |
| question_prompt=question_prompt, | |
| refine_prompt=refine_prompt, | |
| return_intermediate_steps=False, | |
| input_key="input_documents", | |
| output_key="output_text", | |
| verbose=True, | |
| ) | |
| return refine_chain | |