Empty graph guards

packages/graphrag/graphrag/api/index.py

@@ -86,8 +86,9 @@ async def build_index(
         input_documents=input_documents,
     ):
         outputs.append(output)
-        if output.errors and len(output.errors) > 0:
+        if output.error is not None:
             logger.error("Workflow %s completed with errors", output.workflow)
+            workflow_callbacks.pipeline_error(output.error)
         else:
             logger.info("Workflow %s completed successfully", output.workflow)
         logger.debug(str(output.result))

packages/graphrag/graphrag/callbacks/console_workflow_callbacks.py

@@ -37,6 +37,10 @@ def workflow_end(self, name: str, instance: object) -> None:
         if self._verbose:
             print(instance)
 
+    def pipeline_error(self, error: BaseException) -> None:
+        """Execute this callback when an error occurs in the pipeline."""
+        print(f"Pipeline error: {error}")
+
     def progress(self, progress: Progress) -> None:
         """Handle when progress occurs."""
         complete = progress.completed_items or 0

packages/graphrag/graphrag/callbacks/noop_workflow_callbacks.py

@@ -25,3 +25,6 @@ def workflow_end(self, name: str, instance: object) -> None:
 
     def progress(self, progress: Progress) -> None:
         """Handle when progress occurs."""
+
+    def pipeline_error(self, error: BaseException) -> None:
+        """Execute this callback when an error occurs in the pipeline."""

packages/graphrag/graphrag/callbacks/workflow_callbacks.py

@@ -35,3 +35,7 @@ def workflow_end(self, name: str, instance: object) -> None:
     def progress(self, progress: Progress) -> None:
         """Handle when progress occurs."""
         ...
+
+    def pipeline_error(self, error: BaseException) -> None:
+        """Execute this callback when an error occurs in the pipeline."""
+        ...

packages/graphrag/graphrag/callbacks/workflow_callbacks_manager.py

@@ -50,3 +50,9 @@ def progress(self, progress: Progress) -> None:
         for callback in self._callbacks:
             if hasattr(callback, "progress"):
                 callback.progress(progress)
+
+    def pipeline_error(self, error: BaseException) -> None:
+        """Execute this callback when an error occurs in the pipeline."""
+        for callback in self._callbacks:
+            if hasattr(callback, "pipeline_error"):
+                callback.pipeline_error(error)

packages/graphrag/graphrag/cli/index.py

@@ -134,15 +134,6 @@ def _run_index(
             verbose=verbose,
         )
     )
-    encountered_errors = any(
-        output.errors and len(output.errors) > 0 for output in outputs
-    )
-
-    if encountered_errors:
-        logger.error(
-            "Errors occurred during the pipeline run, see logs for more details."
-        )
-    else:
-        logger.info("All workflows completed successfully.")
+    encountered_errors = any(output.error is not None for output in outputs)
 
     sys.exit(1 if encountered_errors else 0)

packages/graphrag/graphrag/index/operations/extract_graph/extract_graph.py

@@ -5,17 +5,11 @@
 
 import logging
 
-import networkx as nx
 import pandas as pd
 
 from graphrag.callbacks.workflow_callbacks import WorkflowCallbacks
 from graphrag.config.enums import AsyncType
 from graphrag.index.operations.extract_graph.graph_extractor import GraphExtractor
-from graphrag.index.operations.extract_graph.typing import (
-    Document,
-    EntityExtractionResult,
-    EntityTypes,
-)
 from graphrag.index.utils.derive_from_rows import derive_from_rows
 from graphrag.language_model.protocol.base import ChatModel
 
@@ -42,14 +36,15 @@ async def run_strategy(row):
         text = row[text_column]
         id = row[id_column]
         result = await run_extract_graph(
-            [Document(text=text, id=id)],
-            entity_types,
-            model,
-            prompt,
-            max_gleanings,
+            text=text,
+            source_id=id,
+            entity_types=entity_types,
+            model=model,
+            prompt=prompt,
+            max_gleanings=max_gleanings,
         )
         num_started += 1
-        return [result.entities, result.relationships, result.graph]
+        return result
 
     results = await derive_from_rows(
         text_units,
@@ -64,8 +59,8 @@ async def run_strategy(row):
     relationship_dfs = []
     for result in results:
         if result:
-            entity_dfs.append(pd.DataFrame(result[0]))
-            relationship_dfs.append(pd.DataFrame(result[1]))
+            entity_dfs.append(result[0])
+            relationship_dfs.append(result[1])
 
     entities = _merge_entities(entity_dfs)
     relationships = _merge_relationships(relationship_dfs)
@@ -74,12 +69,13 @@ async def run_strategy(row):
 
 
 async def run_extract_graph(
-    docs: list[Document],
-    entity_types: EntityTypes,
+    text: str,
+    source_id: str,
+    entity_types: list[str],
     model: ChatModel,
     prompt: str,
     max_gleanings: int,
-) -> EntityExtractionResult:
+) -> tuple[pd.DataFrame, pd.DataFrame]:
     """Run the graph intelligence entity extraction strategy."""
     extractor = GraphExtractor(
         model=model,
@@ -89,36 +85,15 @@ async def run_extract_graph(
             "Entity Extraction Error", exc_info=e, extra={"stack": s, "details": d}
         ),
     )
-    text_list = [doc.text.strip() for doc in docs]
+    text = text.strip()
 
-    results = await extractor(
-        list(text_list),
+    entities_df, relationships_df = await extractor(
+        text,
         entity_types=entity_types,
+        source_id=source_id,
     )
 
-    graph = results.output
-    # Map the "source_id" back to the "id" field
-    for _, node in graph.nodes(data=True):  # type: ignore
-        if node is not None:
-            node["source_id"] = ",".join(
-                docs[int(id)].id for id in node["source_id"].split(",")
-            )
-
-    for _, _, edge in graph.edges(data=True):  # type: ignore
-        if edge is not None:
-            edge["source_id"] = ",".join(
-                docs[int(id)].id for id in edge["source_id"].split(",")
-            )
-
-    entities = [
-        ({"title": item[0], **(item[1] or {})})
-        for item in graph.nodes(data=True)
-        if item is not None
-    ]
-
-    relationships = nx.to_pandas_edgelist(graph)
-
-    return EntityExtractionResult(entities, relationships, graph)
+    return (entities_df, relationships_df)
 
 
 def _merge_entities(entity_dfs) -> pd.DataFrame: