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