convert_to_graph_documents encounter type error str has no content property

[Jeffhaha]

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Example Code

from dotenv import load_dotenv
from langchain_community.graphs import Neo4jGraph
from langchain_experimental.graph_transformers import LLMGraphTransformer
#from langchain_openai import ChatOpenAI
from langchain_core.documents import Document
from langchain_community.llms import Ollama

load_dotenv()
os.environ["NEO4J_URI"] = "bolt://localhost:7687"
os.environ["NEO4J_USERNAME"] = "neo4j"
os.environ["NEO4J_PASSWORD"] = getpass.getpass()

graph = Neo4jGraph()

llm=Ollama(temperature=0,model="llama3",base_url="http://localhost:11434")
llm_transformer = LLMGraphTransformer(llm=llm)

text = """
Marie Curie, born in 1867, was a Polish and naturalised-French physicist and chemist who conducted pioneering research on radioactivity.
She was the first woman to win a Nobel Prize, the first person to win a Nobel Prize twice, and the only person to win a Nobel Prize in two scientific fields.
Her husband, Pierre Curie, was a co-winner of her first Nobel Prize, making them the first-ever married couple to win the Nobel Prize and launching the Curie family legacy of five Nobel Prizes.
She was, in 1906, the first woman to become a professor at the University of Paris.
"""

documents = [Document(page_content=text)]
graph_documents = llm_transformer.convert_to_graph_documents(documents)

Description

I follow the "How to construct knowledge graphs" tutorial , instead of chatgpt llm I m using ollama + llama3. But I dont have the luck when I run to convert_to_graph_documents it broke and give error message

AttributeError Traceback (most recent call last)
Cell In[56], line 1
----> 1 graph_documents = llm_transformer.convert_to_graph_documents([documents])

File /.../python3.12/site-packages/langchain_experimental/graph_transformers/llm.py:646, in LLMGraphTransformer.convert_to_graph_documents(self, documents)
634 def convert_to_graph_documents(
635 self, documents: Sequence[Document]
636 ) -> List[GraphDocument]:
637 """Convert a sequence of documents into graph documents.
638
639 Args:
(...)
644 Sequence[GraphDocument]: The transformed documents as graphs.
645 """
--> 646 return [self.process_response(document) for document in documents]

File /.../python3.12/site-packages/langchain_experimental/graph_transformers/llm.py:595, in LLMGraphTransformer.process_response(self, document)
593 nodes_set = set()
594 relationships = []
--> 595 parsed_json = self.json_repair.loads(raw_schema.content)
596 for rel in parsed_json:
597 # Nodes need to be deduplicated using a set
598 nodes_set.add((rel["head"], rel["head_type"]))

AttributeError: 'str' object has no attribute 'content'

System Info

langchain==0.1.16
langchain-anthropic==0.1.13
langchain-chroma==0.1.0
langchain-community==0.0.34
langchain-core==0.2.1
langchain-openai==0.1.4
langchain-text-splitters==0.0.1
langchainhub==0.1.15
macos big sur 11.7.10
python 3.12

[dosubot[bot]]

Hey there, @Jeffhaha! I'm here to help with any bugs, questions, or contributions you might have. Let's see what's going on with the issue you've encountered.

To resolve the AttributeError: 'str' object has no attribute 'content' when using the convert_to_graph_documents method from the LLMGraphTransformer class, ensure that the raw_schema is correctly cast to a dictionary before accessing its attributes. Specifically, in the process_response method, the raw_schema should be cast to a dictionary if it is not already one.

Here is the relevant part of the process_response method with the necessary correction:

def process_response(self, document: Document) -> GraphDocument:
    """
    Processes a single document, transforming it into a graph document using
    an LLM based on the model's schema and constraints.
    """
    text = document.page_content
    raw_schema = self.chain.invoke({"input": text})
    if self._function_call:
        raw_schema = cast(Dict[Any, Any], raw_schema)
        nodes, relationships = _convert_to_graph_document(raw_schema)
    else:
        nodes_set = set()
        relationships = []
        if not isinstance(raw_schema, str):
            raw_schema = raw_schema.content  # This line should be corrected
        parsed_json = self.json_repair.loads(raw_schema)
        for rel in parsed_json:
            # Nodes need to be deduplicated using a set
            nodes_set.add((rel["head"], rel["head_type"]))
            nodes_set.add((rel["tail"], rel["tail_type"]))

The corrected line should be:

raw_schema = raw_schema.content

This ensures that raw_schema is correctly accessed as a string when it is not already a string ^[1].

To continue talking to Dosu, mention @dosu.

[Jeffhaha]

after I edited my intalled version, now it works. thank you.

[dosubot[bot]]

Great to hear that it works now! If you have any more questions or run into any other issues, feel free to ask. Happy coding!

To continue talking to Dosu, mention @dosu.