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tharak#3
Offline, last seen last month
Joined October 7, 2024
hi,

i am facing issue when creating a property graph index

Plain Text
    kg_extractor = SchemaLLMPathExtractor(
        llm = OpenAI(model="gpt-4o", temperature=0.1),
        possible_entities=entities,
        possible_entity_props=entity_properties,
        possible_relations=relations,
        kg_validation_schema=validation_schema,
        strict=True
    )


Plain Text
    graph_store = Neo4jPropertyGraphStore(
        username=os.getenv("username"),
        password=os.getenv("password"),
        url=os.getenv("url"),
        database=os.getenv("database")
    )


Plain Text
    pg_index = PropertyGraphIndex.from_documents(
        documents,
        kg_extractors=[kg_extractor],
        embed_model = OpenAIEmbedding(model="text-embedding-3-small"),
        property_graph_store=graph_store,
        vector_store=None,
        show_progress=True,
    )


when i run it getting error
File "/home/user/.cache/pypoetry/virtualenvs/llama-graph-Kulloq32-py3.12/lib/python3.12/site-packages/llama_index/core/storage/index_store/keyval_index_store.py", line 44, in add_index_struct
key = index_struct.index_id
^^^^^^^^^^^^^^^^^^^^^
AttributeError: 'coroutine' object has no attribute 'index_id'
8 comments
t
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Hi,

How can we perform vector search on date related queries like
  1. List invoices starting from oct 2023
  2. List invoices raised in last quarter
  3. Invoices between apr 24 to jul 24
  4. Invoices with total amount exceed/lower by x amount
  5. Compare the latest invoice raised by ABC vendor with invoice from last quarter
How do you guys are handling these kind of dates, price related queries
4 comments
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tharak#3
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How can I create my own custom agent with custom reasoning loop by utilizing agent runner and agent worker.
Any resources in this will be appreciated
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tharak#3
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Hi,

How can I get the score based results directly during retrieval process instead of using similarity_top_k
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Hi, How could i store the JSON data which comes from the JSON File into a Qdrant Database using Ingestion Pipeline ?

i tried storing the documents but i get this error
[str(node.get_content(metadata_mode=MetadataMode.ALL)) for node in nodes]
^^^^^^^^^^^^^^^^
AttributeError: 'dict' object has no attribute 'get_content'
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I have a 100mb size CSV file how to parse the CSV to executable SQL file.
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