experimental[patch]: Enhance LLMGraphTransformer with async processing and improved readability (#19205)

- [x] **PR title**: "experimental: Enhance LLMGraphTransformer with
async processing and improved readability"


- [x] **PR message**: 
- **Description:** This pull request refactors the `process_response`
and `convert_to_graph_documents` methods in the LLMGraphTransformer
class to improve code readability and adds async versions of these
methods for concurrent processing.
    The main changes include:
- Simplifying list comprehensions and conditional logic in the
process_response method for better readability.
- Adding async versions aprocess_response and
aconvert_to_graph_documents to enable concurrent processing of
documents.
These enhancements aim to improve the overall efficiency and
maintainability of the `LLMGraphTransformer` class.
  - **Issue:** N/A
  - **Dependencies:** No additional dependencies required.
  - **Twitter handle:** @jjovalle99


- [x] **Add tests and docs**: N/A (This PR does not introduce a new
integration)


- [x] **Lint and test**: Ran make format, make lint, and make test from
the root of the modified package(s). All tests pass successfully.

Additional notes:

- The changes made in this PR are backwards compatible and do not
introduce any breaking changes.
- The PR touches only the `LLMGraphTransformer` class within the
experimental package.

---------

Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>

libs/experimental/langchain_experimental/graph_transformers/llm.py

@@ -1,3 +1,4 @@
+import asyncio
 from typing import Any, List, Optional, Sequence
 
 from langchain_community.graphs.graph_document import GraphDocument, Node, Relationship
@@ -207,29 +208,20 @@ class LLMGraphTransformer:
         """
         text = document.page_content
         raw_schema = self.chain.invoke({"input": text})
-        if raw_schema.nodes:
+        nodes = (
-            nodes = [map_to_base_node(node) for node in raw_schema.nodes]
+            [map_to_base_node(node) for node in raw_schema.nodes]
-        else:
+            if raw_schema.nodes
-            nodes = []
+            else []
-        if raw_schema.relationships:
+        )
-            relationships = [
+        relationships = (
-                map_to_base_relationship(rel) for rel in raw_schema.relationships
+            [map_to_base_relationship(rel) for rel in raw_schema.relationships]
-            ]
+            if raw_schema.relationships
-        else:
+            else []
-            relationships = []
+        )
 
         # Strict mode filtering
         if self.strict_mode and (self.allowed_nodes or self.allowed_relationships):
-            if self.allowed_relationships and self.allowed_nodes:
+            if self.allowed_nodes:
-                nodes = [node for node in nodes if node.type in self.allowed_nodes]
-                relationships = [
-                    rel
-                    for rel in relationships
-                    if rel.type in self.allowed_relationships
-                    and rel.source.type in self.allowed_nodes
-                    and rel.target.type in self.allowed_nodes
-                ]
-            elif self.allowed_nodes and not self.allowed_relationships:
                 nodes = [node for node in nodes if node.type in self.allowed_nodes]
                 relationships = [
                     rel
@@ -237,17 +229,14 @@ class LLMGraphTransformer:
                     if rel.source.type in self.allowed_nodes
                     and rel.target.type in self.allowed_nodes
                 ]
-            if self.allowed_relationships and not self.allowed_nodes:
+            if self.allowed_relationships:
                 relationships = [
                     rel
                     for rel in relationships
                     if rel.type in self.allowed_relationships
                 ]
 
-        graph_document = GraphDocument(
+        return GraphDocument(nodes=nodes, relationships=relationships, source=document)
-            nodes=nodes, relationships=relationships, source=document
-        )
-        return graph_document
 
     def convert_to_graph_documents(
         self, documents: Sequence[Document]
@@ -261,8 +250,54 @@ class LLMGraphTransformer:
         Returns:
             Sequence[GraphDocument]: The transformed documents as graphs.
         """
-        results = []
+        return [self.process_response(document) for document in documents]
-        for document in documents:
+
-            graph_document = self.process_response(document)
+    async def aprocess_response(self, document: Document) -> GraphDocument:
-            results.append(graph_document)
+        """
+        Asynchronously processes a single document, transforming it into a
+        graph document.
+        """
+        text = document.page_content
+        raw_schema = await self.chain.ainvoke({"input": text})
+
+        nodes = (
+            [map_to_base_node(node) for node in raw_schema.nodes]
+            if raw_schema.nodes
+            else []
+        )
+        relationships = (
+            [map_to_base_relationship(rel) for rel in raw_schema.relationships]
+            if raw_schema.relationships
+            else []
+        )
+
+        if self.strict_mode and (self.allowed_nodes or self.allowed_relationships):
+            if self.allowed_nodes:
+                nodes = [node for node in nodes if node.type in self.allowed_nodes]
+                relationships = [
+                    rel
+                    for rel in relationships
+                    if rel.source.type in self.allowed_nodes
+                    and rel.target.type in self.allowed_nodes
+                ]
+            if self.allowed_relationships:
+                relationships = [
+                    rel
+                    for rel in relationships
+                    if rel.type in self.allowed_relationships
+                ]
+
+        return GraphDocument(nodes=nodes, relationships=relationships, source=document)
+
+    async def aconvert_to_graph_documents(
+        self, documents: Sequence[Document]
+    ) -> List[GraphDocument]:
+        """
+        Asynchronously convert a sequence of documents into graph documents.
+        """
+        tasks = [
+            asyncio.create_task(self.aprocess_response(document))
+            for document in documents
+        ]
+        results = await asyncio.gather(*tasks)
         return results