import logging import os from typing import Dict, Any from haystack import Pipeline from haystack.nodes import PromptNode, PromptTemplate, TopPSampler from haystack.nodes.ranker.diversity import DiversityRanker from haystack.nodes.ranker.lost_in_the_middle import LostInTheMiddleRanker from haystack.nodes.retriever.web import WebRetriever search_key = os.environ.get("SERPERDEV_API_KEY") if not search_key: raise ValueError("Please set the SERPERDEV_API_KEY environment variable") models_config: Dict[str, Any] = { "openai": {"api_key": os.environ.get("OPENAI_API_KEY"), "model_name": "gpt-3.5-turbo"}, "anthropic": {"api_key": os.environ.get("ANTHROPIC_API_KEY"), "model_name": "claude-instant-1"}, "hf": {"api_key": os.environ.get("HF_API_KEY"), "model_name": "tiiuae/falcon-7b-instruct"}, } prompt_text = """ Synthesize a comprehensive answer from the provided paragraphs and the given question.\n Answer in full sentences and paragraphs, don't use bullet points or lists.\n If the answer includes multiple chronological events, order them chronologically.\n \n\n Paragraphs: {join(documents)} \n\n Question: {query} \n\n Answer: """ stream = True model: Dict[str, str] = models_config["openai"] prompt_node = PromptNode( model["model_name"], default_prompt_template=PromptTemplate(prompt_text), api_key=model["api_key"], max_length=768, model_kwargs={"stream": stream}, ) web_retriever = WebRetriever(api_key=search_key, top_search_results=5, mode="preprocessed_documents", top_k=50) sampler = TopPSampler(top_p=0.97) diversity_ranker = DiversityRanker() litm_ranker = LostInTheMiddleRanker(word_count_threshold=1024) pipeline = Pipeline() pipeline.add_node(component=web_retriever, name="Retriever", inputs=["Query"]) pipeline.add_node(component=sampler, name="Sampler", inputs=["Retriever"]) pipeline.add_node(component=diversity_ranker, name="DiversityRanker", inputs=["Sampler"]) pipeline.add_node(component=litm_ranker, name="LostInTheMiddleRanker", inputs=["DiversityRanker"]) pipeline.add_node(component=prompt_node, name="PromptNode", inputs=["LostInTheMiddleRanker"]) logging.disable(logging.CRITICAL) questions = [ "What are the main reasons for long-standing animosities between Russia and Poland?", "What are the primary causes and effects of climate change on global and local scales?", "What were the key events and influences that led to Renaissance; how did these developments " "shape modern Western culture?", "How have advances in technology in the 21st century affected job markets and economies around the world?", "What are the main reasons behind the Israel-Palestine conflict and how have they evolved over time?", "How has the European Union influenced the political, economic, and social dynamics of Europe?", ] print(f"\nRunning pipeline with {model['model_name']}\n") for q in questions: print(f"\nQuestion: {q}") if stream: print("Answer:") response = pipeline.run(query=q) if not stream: print(f"Answer: {response['results'][0]}")