wanyaokun
88 lines
3.7 KiB
Python
88 lines
3.7 KiB
Python
from llama_index.core.indices.property_graph import LLMSynonymRetriever,VectorContextRetriever,PGRetriever
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from llama_index.core.indices.property_graph.transformations.schema_llm import *
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from llama_index.core import SimpleDirectoryReader
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from llama_index.core import settings
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from llama_index.core import PropertyGraphIndex
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from typing import List,Tuple,Literal
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from app.settings import init_settings
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import os
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from llama_index.core.storage.storage_context import StorageContext
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from llama_index.core import load_index_from_storage
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from app.observability import init_observability
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from app.engine.vectordb import get_Neo4j_Graph_Store,get_vector_store
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from llama_index.core.response_synthesizers import ResponseMode
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from util.register import *
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from llama_index.core.query_engine import RetrieverQueryEngine
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from app.engine.prompt import text_qa_template, refine_template, summary_template, simple_template
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from app.engine.engine import get_node_postprocessors
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class PropertyGraph:
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def __init__(self,prjFlag:str) -> None:
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self._prjFlag = prjFlag
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def create_query_engine(self,retriever):
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postprocess = get_node_postprocessors()
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query_engine = RetrieverQueryEngine.from_args(
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retriever = retriever,
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text_qa_template=text_qa_template,
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refine_template=refine_template,
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summary_template = summary_template,
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simple_template = simple_template,
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node_postprocessors=postprocess,
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use_async=True,
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streaming=False,
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response_mode = ResponseMode.TREE_SUMMARIZE
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)
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return query_engine
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def getPropertyGraphIndex(self):
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GRAPH_STORE_TYPE = os.getenv("GRAPH_STORE_TYPE", "")
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if GRAPH_STORE_TYPE == 'neo4j':
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index = PropertyGraphIndex.from_existing(property_graph_store= get_Neo4j_Graph_Store(self._prjFlag))
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else:
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GRAPH_STORAGE_DIR = os.getenv("GRAPH_STORAGE_PATH", "storage_graph")
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prjCachePath = GRAPH_STORAGE_DIR + f"/{self._prjFlag}"
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if not os.path.exists(prjCachePath):
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return None
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storeContext = StorageContext.from_defaults(persist_dir = prjCachePath,vector_store = get_vector_store(self._prjFlag))
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index = load_index_from_storage(storeContext)
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return index
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def query(self,query_str:str):
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index = self.getPropertyGraphIndex()
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synonym_retriver = LLMSynonymRetriever(index.property_graph_store,
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llm=settings.Settings.llm,
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max_keywords=10,
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include_text=False
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)
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if index.property_graph_store.supports_vector_queries:
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vector_store = None
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else:
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vector_store = index.vector_store
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vector_retriver = VectorContextRetriever(index.property_graph_store,
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vector_store = vector_store,
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embed_model=settings.Settings.embed_model,
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similarity_top_k=5,
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include_text=False
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)
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retriever = index.as_retriever(sub_retrievers=[synonym_retriver,vector_retriver])
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query_engine = self.create_query_engine(retriever)
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response = query_engine.query(query_str)
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print(response)
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return str(response)
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if __name__ == "__main__":
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init_settings()
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init_observability()
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graph = PropertyGraph('projects_1b20bbf4-3243-4ac3-bcf0-8a91e9157521')
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graph.query('代码为XLBT的金额是')
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