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langchain/libs/experimental
Istvan/Nebulinq 513e491ce9
experimental: LLMGraphTransformer - added relationship properties. (#21856)
- **Description:** 
The generated relationships in the graph had no properties, but the
Relationship class was properly defined with properties. This made it
very difficult to transform conditional sentences into a graph. Adding
properties to relationships can solve this issue elegantly.
The changes expand on the existing LLMGraphTransformer implementation
but add the possibility to define allowed relationship properties like
this: LLMGraphTransformer(llm=llm, relationship_properties=["Condition",
"Time"],)
- **Issue:** 
    no issue found
 - **Dependencies:**
    n/a
- **Twitter handle:** 
    @IstvanSpace


-Quick Test
=================================================================
from dotenv import load_dotenv
import os
from langchain_community.graphs import Neo4jGraph
from langchain_experimental.graph_transformers import
LLMGraphTransformer
from langchain_openai import ChatOpenAI
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.documents import Document

load_dotenv()
os.environ["NEO4J_URI"] = os.getenv("NEO4J_URI")
os.environ["NEO4J_USERNAME"] = os.getenv("NEO4J_USERNAME")
os.environ["NEO4J_PASSWORD"] = os.getenv("NEO4J_PASSWORD")
graph = Neo4jGraph()
llm = ChatOpenAI(temperature=0, model_name="gpt-4o")
llm_transformer = LLMGraphTransformer(llm=llm)
#text = "Harry potter likes pies, but only if it rains outside"
text = "Jack has a dog named Max. Jack only walks Max if it is sunny
outside."
documents = [Document(page_content=text)]
llm_transformer_props = LLMGraphTransformer(
    llm=llm,
    relationship_properties=["Condition"],
)
graph_documents_props =
llm_transformer_props.convert_to_graph_documents(documents)
print(f"Nodes:{graph_documents_props[0].nodes}")
print(f"Relationships:{graph_documents_props[0].relationships}")
graph.add_graph_documents(graph_documents_props)

---------

Co-authored-by: Istvan Lorincz <istvan.lorincz@pm.me>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
3 months ago
..
langchain_experimental experimental: LLMGraphTransformer - added relationship properties. (#21856) 3 months ago
scripts infra: add print rule to ruff (#16221) 8 months ago
tests Fix: lint errors and update Field alias in models.py and AutoSelectionScorer initialization (#22846) 3 months ago
LICENSE Library Licenses (#13300) 10 months ago
Makefile create mypy cache dir if it doesn't exist (#14579) 9 months ago
README.md CONTRIBUTING.md Quick Start: focus on langchain core; clarify docs and experimental are separate (#10906) 1 year ago
extended_testing_deps.txt ci: add testing with Python 3.12 (#22813) 3 months ago
poetry.lock ci: add testing with Python 3.12 (#22813) 3 months ago
poetry.toml Harrison/move experimental (#8084) 1 year ago
pyproject.toml ci: add testing with Python 3.12 (#22813) 3 months ago

README.md

🦜🧪 LangChain Experimental

This package holds experimental LangChain code, intended for research and experimental uses.

[!WARNING] Portions of the code in this package may be dangerous if not properly deployed in a sandboxed environment. Please be wary of deploying experimental code to production unless you've taken appropriate precautions and have already discussed it with your security team.

Some of the code here may be marked with security notices. However, given the exploratory and experimental nature of the code in this package, the lack of a security notice on a piece of code does not mean that the code in question does not require additional security considerations in order to be safe to use.