Templates (#12294)

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Lance Martin <lance@langchain.dev>
Co-authored-by: Jacob Lee <jacoblee93@gmail.com>

templates/neo4j-parent/ingest.py

@@ -0,0 +1,46 @@
+from langchain.graphs import Neo4jGraph
+from langchain.vectorstores import Neo4jVector
+from langchain.document_loaders import TextLoader
+from langchain.text_splitter import TokenTextSplitter
+from langchain.embeddings.openai import OpenAIEmbeddings
+from pathlib import Path
+
+txt_path = Path(__file__).parent / "dune.txt"
+
+graph = Neo4jGraph()
+
+# Load the text file
+loader = TextLoader(txt_path)
+documents = loader.load()
+
+# Define chunking strategy
+parent_splitter = TokenTextSplitter(chunk_size=512, chunk_overlap=24)
+child_splitter = TokenTextSplitter(chunk_size=100, chunk_overlap=24)
+
+# Store parent-child patterns into graph
+parent_documents = parent_splitter.split_documents(documents)
+for parent in parent_documents:
+    child_documents = child_splitter.split_documents([parent])
+    params = {
+        "parent": parent.page_content,
+        "children": [c.page_content for c in child_documents],
+    }
+    graph.query(
+        """
+    CREATE (p:Parent {text: $parent})
+    WITH p 
+    UNWIND $children AS child
+    CREATE (c:Child {text: child})
+    CREATE (c)-[:HAS_PARENT]->(p)
+    """,
+        params,
+    )
+
+# Calculate embedding values on the child nodes
+Neo4jVector.from_existing_graph(
+    OpenAIEmbeddings(),
+    index_name="retrieval",
+    node_label="Child",
+    text_node_properties=["text"],
+    embedding_node_property="embedding",
+)