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e1ec4e5e4d
* remove symbols under the haystack.document_stores namespace * Update haystack/document_stores/types/protocol.py Co-authored-by: Silvano Cerza <3314350+silvanocerza@users.noreply.github.com> * fix * same for retrievers * leftovers * more leftovers * add relnote * leftovers * one more * fix examples --------- Co-authored-by: Silvano Cerza <3314350+silvanocerza@users.noreply.github.com>
55 lines
2.2 KiB
Python
55 lines
2.2 KiB
Python
import os
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from pathlib import Path
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from haystack import Document
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from haystack import Pipeline
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from haystack.components.builders.answer_builder import AnswerBuilder
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from haystack.components.builders.prompt_builder import PromptBuilder
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from haystack.components.generators import OpenAIGenerator
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from haystack.components.retrievers.in_memory import InMemoryBM25Retriever
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from haystack.document_stores.in_memory import InMemoryDocumentStore
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# Create a RAG query pipeline
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prompt_template = """
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Given these documents, answer the question.\nDocuments:
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{% for doc in documents %}
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{{ doc.content }}
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{% endfor %}
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\nQuestion: {{question}}
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\nAnswer:
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"""
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rag_pipeline = Pipeline()
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rag_pipeline.add_component(instance=InMemoryBM25Retriever(document_store=InMemoryDocumentStore()), name="retriever")
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rag_pipeline.add_component(instance=PromptBuilder(template=prompt_template), name="prompt_builder")
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rag_pipeline.add_component(instance=OpenAIGenerator(api_key=os.environ.get("OPENAI_API_KEY")), name="llm")
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rag_pipeline.add_component(instance=AnswerBuilder(), name="answer_builder")
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rag_pipeline.connect("retriever", "prompt_builder.documents")
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rag_pipeline.connect("prompt_builder", "llm")
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rag_pipeline.connect("llm.replies", "answer_builder.replies")
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rag_pipeline.connect("llm.meta", "answer_builder.meta")
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rag_pipeline.connect("retriever", "answer_builder.documents")
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# Draw the pipeline
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rag_pipeline.draw(Path("./rag_pipeline.png"))
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# Add Documents
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documents = [
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Document(content="There are over 7,000 languages spoken around the world today."),
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Document(
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content="Elephants have been observed to behave in a way that indicates a high level of self-awareness, such as recognizing themselves in mirrors."
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),
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Document(
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content="In certain parts of the world, like the Maldives, Puerto Rico, and San Diego, you can witness the phenomenon of bioluminescent waves."
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),
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]
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rag_pipeline.get_component("retriever").document_store.write_documents(documents) # type: ignore
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# Run the pipeline
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question = "How many languages are there?"
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result = rag_pipeline.run(
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{"retriever": {"query": question}, "prompt_builder": {"question": question}, "answer_builder": {"query": question}}
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)
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print(result["answer_builder"]["answers"][0])
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