diff --git a/libs/arangodb/langchain_arangodb/chains/graph_qa/prompts.py b/libs/arangodb/langchain_arangodb/chains/graph_qa/prompts.py index d0c77ba..658bbc4 100644 --- a/libs/arangodb/langchain_arangodb/chains/graph_qa/prompts.py +++ b/libs/arangodb/langchain_arangodb/chains/graph_qa/prompts.py @@ -8,6 +8,8 @@ You are given an `ArangoDB Schema`. It is a YAML Spec containing: 1. `Graph Schema`: Lists all Graphs within the ArangoDB Database Instance, along with their Edge Relationships. 2. `Collection Schema`: Lists all Collections within the ArangoDB Database Instance, along with their document/edge properties and a document/edge example. +3. `View Schema`: Lists all Views within the ArangoDB Database Instance, along with their linked collections and analyzers. +4. `Analyzer Schema`: Lists all custom-built Analyzers within the ArangoDB Database Instance, along with their properties and features. Does not mention the default ArangoDB analyzers (i.e text_en, text_fr, etc.) You may also be given a set of `AQL Query Examples` to help you create the `AQL Query`. If provided, the `AQL Query Examples` should be used as a reference, similar to how `ArangoDB Schema` should be used. @@ -15,6 +17,8 @@ - Think step by step. - Rely on `ArangoDB Schema` and `AQL Query Examples` (if provided) to generate the query. - Begin the `AQL Query` by the `WITH` AQL keyword to specify all of the ArangoDB Collections required. +- If a `View Schema` is defined and contains analyzers for specific fields, prefer using the View with the `SEARCH` and `ANALYZER` clauses instead of a direct collection scan. +- Use `PHRASE(...)`, `TOKENS(...)`, or `IN TOKENS(...)` as appropriate when analyzers are available on a field. - Return the `AQL Query` wrapped in 3 backticks (```). - Use only the provided relationship types and properties in the `ArangoDB Schema` and any `AQL Query Examples` queries. - Only answer to requests related to generating an AQL Query. @@ -56,6 +60,8 @@ You are also given the `ArangoDB Schema`. It is a YAML Spec containing: 1. `Graph Schema`: Lists all Graphs within the ArangoDB Database Instance, along with their Edge Relationships. 2. `Collection Schema`: Lists all Collections within the ArangoDB Database Instance, along with their document/edge properties and a document/edge example. +3. `View Schema`: Lists all Views within the ArangoDB Database Instance, along with their linked collections and analyzers. +4. `Analyzer Schema`: Lists all custom-built Analyzers within the ArangoDB Database Instance, along with their properties and features. Does not mention the default ArangoDB analyzers (i.e text_en, text_fr, etc.) You will output the `Corrected AQL Query` wrapped in 3 backticks (```). Do not include any text except the Corrected AQL Query. diff --git a/libs/arangodb/langchain_arangodb/graphs/arangodb_graph.py b/libs/arangodb/langchain_arangodb/graphs/arangodb_graph.py index 5d3a226..797ade1 100644 --- a/libs/arangodb/langchain_arangodb/graphs/arangodb_graph.py +++ b/libs/arangodb/langchain_arangodb/graphs/arangodb_graph.py @@ -20,6 +20,22 @@ ) from langchain_arangodb.graphs.graph_store import GraphStore +DEFAULT_ANALYZERS = { + "text_fr", + "text_pt", + "identity", + "text_de", + "text_zh", + "text_fi", + "text_it", + "text_no", + "text_nl", + "text_es", + "text_ru", + "text_en", + "text_sv", +} + def get_arangodb_client( url: Optional[str] = None, @@ -85,7 +101,9 @@ class ArangoGraph(GraphStore): in a string. If the string is longer than this limit, a string describing the string will be used in the schema instead. Default is 256. :type schema_string_limit: int - + :param schema_include_views: Whether to include ArangoDB Views and Analyzers as + part of the schema passed to the AQL Generation prompt. Default is False. + :type schema_include_views: bool :return: None :rtype: None :raises ArangoClientError: If the ArangoDB client cannot be created. @@ -116,6 +134,7 @@ def __init__( schema_include_examples: bool = True, schema_list_limit: int = 32, schema_string_limit: int = 256, + schema_include_views: bool = False, ) -> None: """ Initializes the ArangoGraph instance. @@ -132,6 +151,7 @@ def __init__( schema_include_examples, schema_list_limit, schema_string_limit, + schema_include_views, ) @property @@ -224,6 +244,7 @@ def generate_schema( include_examples: bool = True, list_limit: int = 32, schema_string_limit: int = 256, + schema_include_views: bool = False, ) -> Dict[str, List[Dict[str, Any]]]: """ Generates the schema of the ArangoDB Database and returns it @@ -247,6 +268,9 @@ def generate_schema( in a string. If the string is longer than this limit, a string describing the string will be used in the schema instead. Default is 128. :type schema_string_limit: int + :param schema_include_views: Whether to include ArangoDB Views and Analyzers as + part of the schema passed to the AQL Generation prompt. Default is False. + :type schema_include_views: bool :return: A dictionary containing the graph schema and collection schema. :rtype: Dict[str, List[Dict[str, Any]]] :raises ValueError: If the sample ratio is not between 0 and 1. @@ -257,6 +281,10 @@ def generate_schema( if not 0 <= sample_ratio <= 1: raise ValueError("**sample_ratio** value must be in between 0 to 1") + ##### + # Step 1: Generate Graph Schema + #### + graph_schema: List[Dict[str, Any]] = [] if graph_name: # Fetch a single graph @@ -283,6 +311,10 @@ def generate_schema( for collection in self.db.collections() # type: ignore } + ##### + # Step 2: Generate Collection Schema + #### + # Stores the schema of every ArangoDB Document/Edge collection collection_schema: List[Dict[str, Any]] = [] for collection in self.db.collections(): # type: ignore @@ -324,7 +356,41 @@ def generate_schema( collection_schema.append(collection_schema_entry) - return {"graph_schema": graph_schema, "collection_schema": collection_schema} + if not schema_include_views: + return { + "graph_schema": graph_schema, + "collection_schema": collection_schema, + } + + ##### + # Step 3: Generate View Schema + ##### + + view_schema: List[Dict[str, Any]] = [] + for view in self.db.views(): # type: ignore + view_name = view["name"] + view_type = view["type"] + view_info = self.db.view(view_name) + key = "links" if view_type == "arangosearch" else "indexes" + view_schema.append( + {"name": view_name, "type": view_type, key: view_info.get(key, [])} # type: ignore + ) + + ##### + # Step 4: Generate Analyzer Schema + ##### + + analyzer_schema: List[Dict[str, Any]] = [] + for a in self.db.analyzers(): # type: ignore + if a["name"] not in DEFAULT_ANALYZERS: + analyzer_schema.append({a["name"]: a["properties"]}) + + return { + "graph_schema": graph_schema, + "collection_schema": collection_schema, + "view_schema": view_schema, + "analyzer_schema": analyzer_schema, + } def query( self, diff --git a/libs/arangodb/poetry.lock b/libs/arangodb/poetry.lock index 210813b..ab6ee97 100644 --- a/libs/arangodb/poetry.lock +++ b/libs/arangodb/poetry.lock @@ -77,14 +77,14 @@ dev = ["backports.zoneinfo ; python_version < \"3.9\"", "freezegun (>=1.0,<2.0)" [[package]] name = "certifi" -version = "2025.1.31" +version = "2025.7.14" description = "Python package for providing Mozilla's CA Bundle." optional = false -python-versions = ">=3.6" +python-versions = ">=3.7" groups = ["main", "dev", "test", "typing"] files = [ - {file = "certifi-2025.1.31-py3-none-any.whl", hash = "sha256:ca78db4565a652026a4db2bcdf68f2fb589ea80d0be70e03929ed730746b84fe"}, - {file = "certifi-2025.1.31.tar.gz", hash = "sha256:3d5da6925056f6f18f119200434a4780a94263f10d1c21d032a6f6b2baa20651"}, + {file = "certifi-2025.7.14-py3-none-any.whl", hash = "sha256:6b31f564a415d79ee77df69d757bb49a5bb53bd9f756cbbe24394ffd6fc1f4b2"}, + {file = "certifi-2025.7.14.tar.gz", hash = "sha256:8ea99dbdfaaf2ba2f9bac77b9249ef62ec5218e7c2b2e903378ed5fccf765995"}, ] [[package]] @@ -170,104 +170,104 @@ pycparser = "*" [[package]] name = "charset-normalizer" -version = "3.4.1" +version = "3.4.2" description = "The Real First Universal Charset Detector. 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is correctly generated and executed.""" - graph = ArangoGraph(db) + graph = ArangoGraph(db, schema_include_views=True) - assert graph.schema == { - "collection_schema": [], - "graph_schema": [], - } + # Check schema structure - analyzer_schema may contain default analyzers + assert "collection_schema" in graph.schema + assert "graph_schema" in graph.schema + assert "view_schema" in graph.schema + assert "analyzer_schema" in graph.schema + assert graph.schema["collection_schema"] == [] + assert graph.schema["graph_schema"] == [] + # analyzer_schema and view_schema may contain default/system entries # Create two nodes and a relationship graph.db.create_collection("Actor") @@ -68,12 +72,16 @@ def test_aql_generating_run(db: StandardDatabase) -> None: def test_aql_top_k(db: StandardDatabase) -> None: """Test top_k parameter correctly limits the number of results in the context.""" TOP_K = 1 - graph = ArangoGraph(db) - - assert graph.schema == { - "collection_schema": [], - "graph_schema": [], - } + graph = ArangoGraph(db, schema_include_views=True) + + # Check schema structure - analyzer_schema may contain default analyzers + assert "collection_schema" in graph.schema + assert "graph_schema" in graph.schema + assert "view_schema" in graph.schema + assert "analyzer_schema" in graph.schema + assert graph.schema["collection_schema"] == [] + assert graph.schema["graph_schema"] == [] + # analyzer_schema and view_schema may contain default/system entries # Create two nodes and a relationship graph.db.create_collection("Actor") diff --git a/libs/arangodb/tests/integration_tests/graphs/test_arangodb.py b/libs/arangodb/tests/integration_tests/graphs/test_arangodb.py index 06cd024..367a670 100644 --- a/libs/arangodb/tests/integration_tests/graphs/test_arangodb.py +++ b/libs/arangodb/tests/integration_tests/graphs/test_arangodb.py @@ -673,6 +673,74 @@ def test_generate_schema_with_graph_name(db: StandardDatabase) -> None: assert edge_col in col_names +@pytest.mark.usefixtures("clear_arangodb_database") +def test_generate_schema_views_and_analyzers(db: StandardDatabase) -> None: + # Step 1: Create the Actor collection and insert sample data + if not db.has_collection("Actor"): + db.create_collection("Actor") + actor_collection = db.collection("Actor") + actor_collection.insert({"_key": "1", "name": "Robert Downey Jr."}, overwrite=True) + + # Step 2: Create an ArangoSearch view on the Actor collection + db.delete_view("ActorView", ignore_missing=True) + db.create_view( + "ActorView", + "arangosearch", + { + "links": { + "Actor": { + "analyzers": ["text_en"], + "fields": { + "name": { + "analyzers": ["text_en"], + }, + }, + "includeAllFields": True, + "storeValues": "none", + "trackListPositions": False, + }, + } + }, + ) + + # Step 3: Create a custom analyzer + db.delete_analyzer("custom_analyzer", ignore_missing=True) + db.create_analyzer( + name="custom_analyzer", + analyzer_type="text", + properties={ + "locale": "en.UTF-8", + "stopwords": ["the", "a", "an"], + "stemming": True, + "case": "lower", + "accent": False, + }, + features=["frequency", "norm", "position"], + ) + + # Step 4: Generate schema + graph = ArangoGraph(db, generate_schema_on_init=False, schema_include_views=True) + schema = graph.generate_schema(schema_include_views=True) + + # Step 5: Validate ActorView is present in view_schema + view_schema = schema["view_schema"] + actor_view = next((v for v in view_schema if v["name"] == "ActorView"), None) + assert actor_view is not None + assert actor_view["type"] == "arangosearch" + + links = actor_view["links"] + assert "Actor" in links + assert "fields" in links["Actor"] + assert "name" in links["Actor"]["fields"] + assert "analyzers" in links["Actor"] + assert "text_en" in links["Actor"]["analyzers"] + + # Step 6: Validate analyzer is present in analyzer_schema + analyzer_schema = schema["analyzer_schema"] + assert "_system::custom_analyzer" in analyzer_schema[0] + assert analyzer_schema[0]["_system::custom_analyzer"]["case"] == "lower" + + @pytest.mark.usefixtures("clear_arangodb_database") def test_add_graph_documents_requires_embedding(db: StandardDatabase) -> None: graph = ArangoGraph(db, generate_schema_on_init=False) @@ -686,7 +754,8 @@ def test_add_graph_documents_requires_embedding(db: StandardDatabase) -> None: with pytest.raises(ValueError, match="embedding.*required"): graph.add_graph_documents( [doc], - embed_source=True, # requires embedding, but embeddings=None + embed_source=True, + # requires embedding, but embeddings=None ) @@ -1099,12 +1168,12 @@ def test_embed_relationships_and_include_source(db: StandardDatabase) -> None: all_relationship_edges = relationship_edge_calls[0] pprint.pprint(all_relationship_edges) - assert any( - "embedding" in e for e in all_relationship_edges - ), "Expected embedding in relationship" # noqa: E501 - assert any( - "source_id" in e for e in all_relationship_edges - ), "Expected source_id in relationship" # noqa: E501 + assert any("embedding" in e for e in all_relationship_edges), ( + "Expected embedding in relationship" + ) # noqa: E501 + assert any("source_id" in e for e in all_relationship_edges), ( + "Expected source_id in relationship" + ) # noqa: E501 @pytest.mark.usefixtures("clear_arangodb_database") diff --git a/libs/arangodb/tests/integration_tests/vectorstores/test_arangodb_vector.py b/libs/arangodb/tests/integration_tests/vectorstores/test_arangodb_vector.py index f7abed5..83ab812 100644 --- a/libs/arangodb/tests/integration_tests/vectorstores/test_arangodb_vector.py +++ b/libs/arangodb/tests/integration_tests/vectorstores/test_arangodb_vector.py @@ -69,9 +69,9 @@ def test_arangovector_from_texts_and_similarity_search( index_info = None indexes_raw = collection.indexes() assert indexes_raw is not None, "collection.indexes() returned None" - assert isinstance( - indexes_raw, list - ), f"collection.indexes() expected list, got {type(indexes_raw)}" + assert isinstance(indexes_raw, list), ( + f"collection.indexes() expected list, got {type(indexes_raw)}" + ) indexes: List[Dict[str, Any]] = indexes_raw for index in indexes: if index.get("name") == "test_index" and index.get("type") == "vector": @@ -121,13 +121,13 @@ def test_arangovector_euclidean_distance( collection_euclidean: StandardCollection = _collection_obj_euclidean index_info = None indexes_raw_euclidean = collection_euclidean.indexes() - assert ( - indexes_raw_euclidean is not None - ), "collection_euclidean.indexes() returned None" - assert isinstance( - indexes_raw_euclidean, list - ), f"collection_euclidean.indexes() expected list, \ + assert indexes_raw_euclidean is not None, ( + "collection_euclidean.indexes() returned None" + ) + assert isinstance(indexes_raw_euclidean, list), ( + f"collection_euclidean.indexes() expected list, \ got {type(indexes_raw_euclidean)}" + ) indexes_euclidean: List[Dict[str, Any]] = indexes_raw_euclidean for index in indexes_euclidean: if index.get("name") == "test_index" and index.get("type") == "vector": @@ -380,26 +380,26 @@ def test_arangovector_delete_documents( # Check that deleted documents are indeed gone deleted_docs_check_raw = collection_delete.get_many(ids_to_delete) - assert ( - deleted_docs_check_raw is not None - ), "collection.get_many() returned None for deleted_docs_check" - assert isinstance( - deleted_docs_check_raw, list - ), f"collection.get_many() expected list for deleted_docs_check,\ + assert deleted_docs_check_raw is not None, ( + "collection.get_many() returned None for deleted_docs_check" + ) + assert isinstance(deleted_docs_check_raw, list), ( + f"collection.get_many() expected list for deleted_docs_check,\ got {type(deleted_docs_check_raw)}" + ) deleted_docs_check: List[Dict[str, Any]] = deleted_docs_check_raw assert len(deleted_docs_check) == 0 # Check that remaining documents are still present remaining_ids_expected = ["id_keep1", "id_keep2"] remaining_docs_check_raw = collection_delete.get_many(remaining_ids_expected) - assert ( - remaining_docs_check_raw is not None - ), "collection.get_many() returned None for remaining_docs_check" - assert isinstance( - remaining_docs_check_raw, list - ), f"collection.get_many() expected list for remaining_docs_check,\ + assert remaining_docs_check_raw is not None, ( + "collection.get_many() returned None for remaining_docs_check" + ) + assert isinstance(remaining_docs_check_raw, list), ( + f"collection.get_many() expected list for remaining_docs_check,\ got {type(remaining_docs_check_raw)}" + ) remaining_docs_check: List[Dict[str, Any]] = remaining_docs_check_raw assert len(remaining_docs_check) == 2 @@ -831,9 +831,9 @@ def test_arangovector_core_functionality( # 8. Testing search by ID all_docs_cursor = collection_core.all() assert all_docs_cursor is not None, "collection.all() returned None" - assert isinstance( - all_docs_cursor, Cursor - ), f"collection.all() expected Cursor, got {type(all_docs_cursor)}" + assert isinstance(all_docs_cursor, Cursor), ( + f"collection.all() expected Cursor, got {type(all_docs_cursor)}" + ) all_ids = [doc["_key"] for doc in all_docs_cursor] assert new_ids[0] in all_ids @@ -958,9 +958,9 @@ def test_arangovector_from_existing_collection( # Check that embeddings were added to the original documents doc_data1 = collection_exist.get("doc1") assert doc_data1 is not None, "Document 'doc1' not found in collection_exist" - assert isinstance( - doc_data1, dict - ), f"Expected 'doc1' to be a dict, got {type(doc_data1)}" + assert isinstance(doc_data1, dict), ( + f"Expected 'doc1' to be a dict, got {type(doc_data1)}" + ) doc1: Dict[str, Any] = doc_data1 assert "embedding" in doc1 assert isinstance(doc1["embedding"], list) @@ -991,9 +991,9 @@ def test_arangovector_from_existing_collection( # Check that custom embeddings were added doc_data2 = collection_exist.get("doc1") assert doc_data2 is not None, "Document 'doc1' not found after custom processing" - assert isinstance( - doc_data2, dict - ), f"Expected 'doc1' after custom processing to be a dict, got {type(doc_data2)}" + assert isinstance(doc_data2, dict), ( + f"Expected 'doc1' after custom processing to be a dict, got {type(doc_data2)}" + ) doc2: Dict[str, Any] = doc_data2 assert "custom_embedding" in doc2 assert "custom_text" in doc2 @@ -1036,12 +1036,12 @@ def test_arangovector_from_existing_collection( # Check that the combined text was inserted doc_data3 = collection_exist.get("doc1") - assert ( - doc_data3 is not None - ), "Document 'doc1' not found after insert_text processing" - assert isinstance( - doc_data3, dict - ), f"Expected 'doc1' after insert_text to be a dict, got {type(doc_data3)}" + assert doc_data3 is not None, ( + "Document 'doc1' not found after insert_text processing" + ) + assert isinstance(doc_data3, dict), ( + f"Expected 'doc1' after insert_text to be a dict, got {type(doc_data3)}" + ) doc3: Dict[str, Any] = doc_data3 assert "combined_title_content" in doc3 assert "The Solar System" in doc3["combined_title_content"] diff --git a/libs/arangodb/tests/unit_tests/graphs/test_arangodb.py b/libs/arangodb/tests/unit_tests/graphs/test_arangodb.py index 7522cdb..e1d1616 100644 --- a/libs/arangodb/tests/unit_tests/graphs/test_arangodb.py +++ b/libs/arangodb/tests/unit_tests/graphs/test_arangodb.py @@ -1051,6 +1051,88 @@ def test_add_graph_documents_raises_if_embedding_missing(self) -> None: embed_source=True, # any of these True triggers the check ) + @patch("langchain_arangodb.graphs.arangodb_graph.ArangoClient") + def test_generate_schema_includes_view_and_analyzer( + self, mock_client_cls: MagicMock + ) -> None: + # Setup mock DB and ArangoGraph instance + mock_db = MagicMock() + mock_client = MagicMock() + mock_client.db.return_value = mock_db + mock_client_cls.return_value = mock_client + graph = ArangoGraph(db=mock_db, schema_include_views=True) + + # ---- Mock views ---- + mock_db.views.return_value = [ + {"name": "SearchView", "type": "arangosearch"}, + {"name": "AliasView", "type": "search-alias"}, + ] + + mock_db.view.side_effect = [ + { + "links": { + "TestCollection": { + "analyzers": ["identity"], + "fields": { + "title": {"analyzers": ["text_en"]}, + "desc": {"analyzers": ["text_en"]}, + }, + "includeAllFields": False, + "storeValues": "none", + "trackListPositions": False, + } + } + }, + { + "indexes": [ + {"collection": "TestCollection", "index": "inverted_index_1"} + ] + }, + ] + + # ---- Mock analyzers ---- + mock_db.analyzers.return_value = [ + { + "name": "custom_analyzer", + "analyzer_type": "text", + "properties": { + "locale": "en", + "case": "lower", + "stopwords": [], + "accent": False, + "stemming": True, + }, + } + ] + + # ---- Call generate_schema() ---- + schema = graph.generate_schema(schema_include_views=True) + + # ---- Assertions ---- + assert "view_schema" in schema + assert "analyzer_schema" in schema + + view_schema = schema["view_schema"] + analyzer_schema = schema["analyzer_schema"] + + # --- Check arangosearch view --- + search_view = next(v for v in view_schema if v["name"] == "SearchView") + assert search_view["type"] == "arangosearch" + links = search_view["links"] + assert "TestCollection" in links + assert links["TestCollection"]["analyzers"] == ["identity"] + assert links["TestCollection"]["fields"]["title"]["analyzers"] == ["text_en"] + + # --- Check search-alias view --- + alias_view = next(v for v in view_schema if v["name"] == "AliasView") + assert alias_view["type"] == "search-alias" + assert alias_view["indexes"][0]["collection"] == "TestCollection" + assert alias_view["indexes"][0]["index"] == "inverted_index_1" + + # --- Check analyzer schema --- + assert "custom_analyzer" in analyzer_schema[0] + assert analyzer_schema[0]["custom_analyzer"]["case"] == "lower" + class DummyEmbeddings(Embeddings): def embed_documents(self, texts: List[str]) -> List[List[float]]: return [[0.0] * 5 for _ in texts]