From c6e73eba71cba53fedbe2c46d67aada094670f3a Mon Sep 17 00:00:00 2001 From: sankalp-uipath Date: Tue, 16 Jun 2026 18:19:02 +0530 Subject: [PATCH 01/13] feat(datafabric): add fetch_ontology tool to DF inner SQL agent --- .../datafabric_tool/datafabric_subgraph.py | 64 +++++++-- .../tools/datafabric_tool/datafabric_tool.py | 16 +++ .../agent/tools/datafabric_tool/models.py | 9 ++ .../tools/datafabric_tool/ontology_client.py | 118 ++++++++++++++++ .../datafabric_tool/ontology_fetch_tool.py | 130 ++++++++++++++++++ 5 files changed, 326 insertions(+), 11 deletions(-) create mode 100644 src/uipath_langchain/agent/tools/datafabric_tool/ontology_client.py create mode 100644 src/uipath_langchain/agent/tools/datafabric_tool/ontology_fetch_tool.py diff --git a/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_subgraph.py b/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_subgraph.py index 591227962..6ae6e8912 100644 --- a/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_subgraph.py +++ b/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_subgraph.py @@ -34,6 +34,7 @@ from ..datafabric_query_tool import DataFabricQueryTool from . import datafabric_prompt_builder from .models import DataFabricExecuteSqlInput +from .ontology_fetch_tool import create_ontology_fetch_tool logger = logging.getLogger(__name__) @@ -88,18 +89,32 @@ def __init__( max_iterations: int = 25, resource_description: str = "", base_system_prompt: str = "", + ontology_name: str | None = None, + folder_key: str | None = None, ) -> None: self._max_iterations = max_iterations self._execute_sql_tool = self._create_execute_sql_tool( entities_service, entities ) + # Inner toolset: always execute_sql; optionally an LLM-decided + # fetch_ontology tool when an ontology name is configured. + inner_tools: list[BaseTool] = [self._execute_sql_tool] + if ontology_name: + inner_tools.append( + create_ontology_fetch_tool( + entities_service, ontology_name, folder_key + ) + ) + self._tools_by_name: dict[str, BaseTool] = { + tool.name: tool for tool in inner_tools + } self._system_message = SystemMessage( content=datafabric_prompt_builder.build( entities, resource_description, base_system_prompt ) ) self._inner_llm = llm.model_copy(update={"disable_streaming": True}).bind_tools( - [self._execute_sql_tool] + inner_tools ) # Build and compile the graph @@ -139,19 +154,42 @@ async def tool_node(self, state: DataFabricSubgraphState) -> dict[str, Any]: } async def _execute_tool_call(self, tool_call: ToolCall) -> tuple[ToolMessage, bool]: - """Execute a single tool call and report whether it succeeded.""" + """Execute a single tool call and report whether it is a terminal success. + + Dispatches by tool name so the sub-graph can host more than one tool + (e.g. ``execute_sql`` and ``fetch_ontology``). Only a successful + ``execute_sql`` that returned rows is terminal; every other tool + (including ontology fetch) reports ``False`` so the router loops back to + the inner LLM, letting it use the result to write or refine SQL. + """ + name = tool_call.get("name", "") args = tool_call.get("args", {}) + tool = self._tools_by_name.get(name) + if tool is None: + return ( + ToolMessage( + content=f"Unknown tool: {name}", + tool_call_id=tool_call["id"], + name=name, + status="error", + ), + False, + ) try: - result = await self._execute_sql_tool.ainvoke(args) + result = await tool.ainvoke(args) except ValueError as e: - result = { - "records": [], - "total_count": 0, - "error": str(e), - "sql_query": args.get("sql_query", ""), - } + if name == self._execute_sql_tool.name: + result = { + "records": [], + "total_count": 0, + "error": str(e), + "sql_query": args.get("sql_query", ""), + } + else: + result = f"Tool '{name}' failed: {e}" succeeded = ( - isinstance(result, dict) + name == self._execute_sql_tool.name + and isinstance(result, dict) and not result.get("error") and result.get("total_count", 0) > 0 ) @@ -159,7 +197,7 @@ async def _execute_tool_call(self, tool_call: ToolCall) -> tuple[ToolMessage, bo ToolMessage( content=str(result), tool_call_id=tool_call["id"], - name="execute_sql", + name=name, ), succeeded, ) @@ -226,6 +264,8 @@ def create( max_iterations: int = 25, resource_description: str = "", base_system_prompt: str = "", + ontology_name: str | None = None, + folder_key: str | None = None, ) -> CompiledStateGraph[Any]: """Create and return a compiled Data Fabric sub-graph.""" graph = DataFabricGraph( @@ -235,5 +275,7 @@ def create( max_iterations, resource_description, base_system_prompt, + ontology_name, + folder_key, ) return graph.compiled_graph diff --git a/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py b/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py index aab4e4cfc..0e13c917e 100644 --- a/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py +++ b/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py @@ -13,6 +13,7 @@ import asyncio import logging +import os from typing import Any from langchain_core.language_models import BaseChatModel @@ -28,6 +29,8 @@ logger = logging.getLogger(__name__) BASE_SYSTEM_PROMPT = "base_system_prompt" +ONTOLOGY_NAME = "ontology_name" +FOLDER_KEY = "folder_key" class DataFabricTextQueryHandler: @@ -44,11 +47,15 @@ def __init__( llm: BaseChatModel, resource_description: str = "", base_system_prompt: str = "", + ontology_name: str | None = None, + folder_key: str | None = None, ) -> None: self._entity_set = entity_set self._llm = llm self._resource_description = resource_description self._base_system_prompt = base_system_prompt + self._ontology_name = ontology_name + self._folder_key = folder_key self._compiled: CompiledStateGraph[Any] | None = None self._init_lock = asyncio.Lock() @@ -82,6 +89,8 @@ async def _ensure_datafabric_graph(self) -> CompiledStateGraph[Any]: entities_service=resolution.entities_service, resource_description=self._resource_description, base_system_prompt=self._base_system_prompt, + ontology_name=self._ontology_name, + folder_key=self._folder_key, ) return self._compiled @@ -159,11 +168,18 @@ def create_datafabric_query_tool( DataFabricEntityItem.model_validate(item.model_dump(by_alias=True)) for item in (resource.entity_set or []) ] + # Ontology name is pinned from configuration (not chosen by the LLM). + # Falls back to env vars for local/demo runs that have no Agent Builder UI. + # When unset, no fetch_ontology tool is added (fully backward compatible). + ontology_name = config.get(ONTOLOGY_NAME) or os.getenv("UIPATH_ONTOLOGY_NAME") + folder_key = config.get(FOLDER_KEY) or os.getenv("UIPATH_FOLDER_KEY") handler = DataFabricTextQueryHandler( entity_set=entity_set, llm=llm, resource_description=resource.description or "", base_system_prompt=config.get(BASE_SYSTEM_PROMPT, ""), + ontology_name=ontology_name, + folder_key=folder_key, ) entity_lines = [] for e in entity_set: diff --git a/src/uipath_langchain/agent/tools/datafabric_tool/models.py b/src/uipath_langchain/agent/tools/datafabric_tool/models.py index 09f4436ee..89bd481f3 100644 --- a/src/uipath_langchain/agent/tools/datafabric_tool/models.py +++ b/src/uipath_langchain/agent/tools/datafabric_tool/models.py @@ -94,3 +94,12 @@ class DataFabricExecuteSqlInput(BaseModel): "Use exact table and column names from the entity schemas." ), ) + + +class OntologyFetchInput(BaseModel): + """Input schema for the ontology fetch tool — intentionally empty. + + The ontology name is pinned from configuration, never supplied by the + LLM, so the model cannot redirect the fetch to an arbitrary resource. The + tool simply triggers a fetch of the configured ontology. + """ diff --git a/src/uipath_langchain/agent/tools/datafabric_tool/ontology_client.py b/src/uipath_langchain/agent/tools/datafabric_tool/ontology_client.py new file mode 100644 index 000000000..2d832051d --- /dev/null +++ b/src/uipath_langchain/agent/tools/datafabric_tool/ontology_client.py @@ -0,0 +1,118 @@ +"""Client for fetching ontology files from UiPath Data Fabric (QueryEngine). + +The QueryEngine ontology REST API is hosted under the same ``datafabric_`` +service as Data Fabric entities, so we reuse the SDK's authenticated +``EntitiesService`` — its ``request_async`` already injects auth, tenant/account +scoping, and retries — instead of building a second auth path. The only +caller-influenced value is ``ontology_name``, which is validated against the +QueryEngine name contract before it becomes part of the request URL. + +The ``owl`` file's content may be serialized as Turtle (.ttl) or as OWL +Functional Notation (.ofn) — both are valid OWL 2 QL serializations and both +are plain text. To stay agnostic to the stored serialization we request the +JSON wrapper (``Accept: application/json``), which always returns ``content`` +plus its ``mediaType`` regardless of notation. Requesting a specific text type +(e.g. ``text/turtle``) would 406 when the stored file is the other notation. + +Naming follows the REST API: the resource is identified by ``ontologyName`` +(``OntologyController`` route ``/{ontologyName}/files/{fileType}``). +""" + +import logging +import re +from typing import Any + +logger = logging.getLogger(__name__) + +# QueryEngine ontology name contract (OntologyCreateRequestValidator): +# lowercase, must start with a letter, max 64 chars. +_ONTOLOGY_NAME_RE = re.compile(r"^[a-z][a-z0-9-]{0,63}$") + +# Defensive cap so a malformed or oversized file can never blow up the prompt +# or token budget. Real OWL 2 QL files are a few KB; QueryEngine caps at 10 MB. +_MAX_OWL_BYTES = 1_000_000 + +_FOLDER_KEY_HEADER = "X-UiPath-FolderKey" + + +def _validate_ontology_name(ontology_name: str) -> str: + """Validate the ontology name against the QueryEngine name contract. + + The name becomes a path segment in the request URL, so only the documented + charset is permitted. This blocks path-segment injection and traversal via + crafted name values. + + Args: + ontology_name: The ontology name to validate. + + Returns: + The validated name (unchanged). + + Raises: + ValueError: If the name does not match ``^[a-z][a-z0-9-]{0,63}$``. + """ + if not isinstance(ontology_name, str) or not _ONTOLOGY_NAME_RE.match( + ontology_name + ): + raise ValueError( + f"Invalid ontology name {ontology_name!r}. " + "Must match ^[a-z][a-z0-9-]{0,63}$." + ) + return ontology_name + + +async def fetch_ontology_owl( + entities_service: Any, + ontology_name: str, + folder_key: str | None = None, +) -> tuple[str, str]: + """Fetch the OWL file for an ontology from Data Fabric. + + Args: + entities_service: An authenticated SDK ``EntitiesService``. Reused for + its ``request_async`` (auth headers, base-URL scoping, retries). + ontology_name: Ontology name. Validated against the QE name contract. + folder_key: Optional UiPath folder key for folder-scoped resolution. + + Returns: + A ``(content, media_type)`` tuple. ``content`` is the OWL text in + whatever serialization is stored — Turtle or OWL Functional Notation; + ``media_type`` is the stored media type (e.g. ``text/turtle``), usable + to label the notation. + + Raises: + ValueError: If the name is invalid or the content exceeds the size cap. + Transport/HTTP errors propagate from the SDK as raised exceptions + (the caller decides how to degrade). + """ + safe_name = _validate_ontology_name(ontology_name) + # Same datafabric_ service the entities calls target; matches the + # QueryEngine ontology route GET /ontologies/{ontologyName}/files/{fileType}. + endpoint = f"datafabric_/api/ontologies/{safe_name}/files/owl" + + # JSON wrapper: notation-agnostic (works for Turtle or OFN) and returns the + # stored mediaType. A text/* Accept would 406 on a serialization mismatch. + headers = {"Accept": "application/json"} + if folder_key: + headers[_FOLDER_KEY_HEADER] = folder_key + + response = await entities_service.request_async( + "GET", endpoint, scoped="tenant", headers=headers + ) + + data = response.json() + content = data.get("content") or "" + media_type = data.get("mediaType") or "" + + if len(content.encode("utf-8")) > _MAX_OWL_BYTES: + raise ValueError( + f"Ontology OWL for {safe_name!r} exceeds the " + f"{_MAX_OWL_BYTES} byte limit." + ) + logger.debug( + "Fetched ontology OWL for %r (%d chars, mediaType=%s)", + safe_name, + len(content), + media_type, + ) + return content, media_type diff --git a/src/uipath_langchain/agent/tools/datafabric_tool/ontology_fetch_tool.py b/src/uipath_langchain/agent/tools/datafabric_tool/ontology_fetch_tool.py new file mode 100644 index 000000000..5e6a21fd0 --- /dev/null +++ b/src/uipath_langchain/agent/tools/datafabric_tool/ontology_fetch_tool.py @@ -0,0 +1,130 @@ +"""LLM-decided tool that fetches an ontology's OWL schema from Data Fabric. + +Mirrors ``datafabric_query_tool.py``: a small leaf tool the inner SQL agent can +call. On invocation it fetches the configured ontology's OWL via the +QueryEngine ontology REST API and returns it. The tool node turns the return +value into a ToolMessage that the inner LLM reads on its next turn — so the +model can call ``fetch_ontology`` first, then write SQL guided by the result. + +The OWL content may be Turtle (.ttl) or OWL Functional Notation (.ofn); both +are valid OWL 2 QL serializations. The fence label reflects the actual stored +notation so the LLM knows what it is reading. + +The ontology name is pinned from configuration, not supplied by the LLM, so the +model cannot redirect the fetch to an arbitrary resource. +""" + +import logging +from typing import Any + +from langchain_core.tools import BaseTool +from uipath.platform.entities import EntitiesService + +from ..base_uipath_structured_tool import BaseUiPathStructuredTool +from .models import OntologyFetchInput +from .ontology_client import fetch_ontology_owl + +logger = logging.getLogger(__name__) + + +def _notation_label(media_type: str) -> str: + """Best-effort human label for the OWL serialization. + + OWL can be stored as Turtle or OWL Functional Notation (OFN); both are + plain text. Falls back to naming both when the media type is unrecognized. + """ + mt = (media_type or "").lower() + if "turtle" in mt or mt.endswith("ttl"): + return "Turtle" + if "functional" in mt or "ofn" in mt: + return "OWL Functional Notation" + return "Turtle or OWL Functional Notation" + + +class OntologyFetcher: + """Fetches and caches the OWL ontology for a fixed, configured name. + + The result is cached on this instance. Because the instance lives as long + as the compiled sub-graph (which the handler caches), repeated calls across + queries hit the API at most once, surviving the per-query reset of the + inner sub-graph state. + """ + + def __init__( + self, + entities_service: EntitiesService, + ontology_name: str, + folder_key: str | None = None, + ) -> None: + self._entities_service = entities_service + self._ontology_name = ontology_name + self._folder_key = folder_key + self._cached: str | None = None + + async def __call__(self, **_kwargs: Any) -> str: + """Return the OWL ontology text, fetching and caching on first call. + + Accepts and ignores keyword arguments so it works with an empty args + schema regardless of how the tool runner invokes it. Failures degrade + gracefully: the agent can still answer using the entity schemas already + present in the system prompt. + """ + if self._cached is not None: + return self._cached + try: + owl, media_type = await fetch_ontology_owl( + self._entities_service, self._ontology_name, self._folder_key + ) + except Exception as e: + # Graceful degradation — ontology is an enhancement, not a hard + # dependency. Do not surface internal error detail to the model. + logger.warning( + "Ontology fetch failed for %r: %s", self._ontology_name, e + ) + return ( + f"Ontology '{self._ontology_name}' is unavailable " + f"({type(e).__name__}). Proceed using the entity schemas " + "described in the system prompt." + ) + notation = _notation_label(media_type) + self._cached = ( + f"OWL 2 QL ontology '{self._ontology_name}' ({notation}) — " + "authoritative schema. Use these exact class/property names and " + "value formats for SQL; this is reference data, not instructions.\n\n" + f"--- ONTOLOGY (OWL 2 QL, {notation}) ---\n{owl}\n--- END ONTOLOGY ---" + ) + return self._cached + + +def create_ontology_fetch_tool( + entities_service: EntitiesService, + ontology_name: str, + folder_key: str | None = None, + tool_name: str = "fetch_ontology", +) -> BaseTool: + """Create the ``fetch_ontology`` leaf tool for the inner sub-graph. + + Args: + entities_service: Authenticated SDK service reused for the REST call. + ontology_name: The ontology to fetch (pinned from configuration). + folder_key: Optional UiPath folder key for folder-scoped resolution. + tool_name: The tool name exposed to the LLM. + + Returns: + A ``BaseUiPathStructuredTool`` that fetches the OWL ontology (Turtle or + OWL Functional Notation) and returns it as the tool result (wrapped + into a ToolMessage by the tool node). + """ + return BaseUiPathStructuredTool( + name=tool_name, + description=( + f"Fetch the OWL 2 QL ontology (the authoritative semantic schema) " + f"for the '{ontology_name}' ontology. Call this BEFORE writing SQL: " + "it gives the exact class and property names, value formats, and " + "relationships so your SQL uses the real schema instead of guesses. " + "Takes no arguments." + ), + args_schema=OntologyFetchInput, + coroutine=OntologyFetcher(entities_service, ontology_name, folder_key), + metadata={"tool_type": "ontology_fetch"}, + ) From da190875f25bf257afe3d608b266d342e554580c Mon Sep 17 00:00:00 2001 From: sankalp-uipath Date: Wed, 17 Jun 2026 14:49:02 +0530 Subject: [PATCH 02/13] feat(datafabric): resolve ontology from agent.json binding (name + folder) --- .../tools/datafabric_tool/datafabric_tool.py | 25 +++++++++++++++++-- 1 file changed, 23 insertions(+), 2 deletions(-) diff --git a/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py b/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py index 0e13c917e..e605fb353 100644 --- a/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py +++ b/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py @@ -171,8 +171,29 @@ def create_datafabric_query_tool( # Ontology name is pinned from configuration (not chosen by the LLM). # Falls back to env vars for local/demo runs that have no Agent Builder UI. # When unset, no fetch_ontology tool is added (fully backward compatible). - ontology_name = config.get(ONTOLOGY_NAME) or os.getenv("UIPATH_ONTOLOGY_NAME") - folder_key = config.get(FOLDER_KEY) or os.getenv("UIPATH_FOLDER_KEY") + # Ontology binding — the first-class source, mirroring entity_set. The + # binding carries the ontology name AND its own folderId, so the ontology is + # resolved from its own folder (entities may span several folders). + ontology_binding = getattr(resource, "ontology", None) + # Single-folder derivation is only a last-resort fallback for legacy + # agent.json with no ontology binding (and only when entities share a folder). + entity_folders = { + e.folder_key for e in entity_set if getattr(e, "folder_key", None) + } + derived_folder_key = ( + next(iter(entity_folders)) if len(entity_folders) == 1 else None + ) + ontology_name = ( + (ontology_binding.name if ontology_binding else None) + or config.get(ONTOLOGY_NAME) + or os.getenv("UIPATH_ONTOLOGY_NAME") + ) + folder_key = ( + (ontology_binding.folder_key if ontology_binding else None) + or config.get(FOLDER_KEY) + or os.getenv("UIPATH_FOLDER_KEY") + or derived_folder_key + ) handler = DataFabricTextQueryHandler( entity_set=entity_set, llm=llm, From 4c22b8f6b85d58c600fe644a8735f610945964cc Mon Sep 17 00:00:00 2001 From: sankalp-uipath Date: Wed, 17 Jun 2026 15:23:07 +0530 Subject: [PATCH 03/13] refactor(datafabric): fetch ontology via SDK EntitiesService.get_ontology_file (drop local client) --- .../tools/datafabric_tool/ontology_client.py | 118 ------------------ .../datafabric_tool/ontology_fetch_tool.py | 15 ++- 2 files changed, 12 insertions(+), 121 deletions(-) delete mode 100644 src/uipath_langchain/agent/tools/datafabric_tool/ontology_client.py diff --git a/src/uipath_langchain/agent/tools/datafabric_tool/ontology_client.py b/src/uipath_langchain/agent/tools/datafabric_tool/ontology_client.py deleted file mode 100644 index 2d832051d..000000000 --- a/src/uipath_langchain/agent/tools/datafabric_tool/ontology_client.py +++ /dev/null @@ -1,118 +0,0 @@ -"""Client for fetching ontology files from UiPath Data Fabric (QueryEngine). - -The QueryEngine ontology REST API is hosted under the same ``datafabric_`` -service as Data Fabric entities, so we reuse the SDK's authenticated -``EntitiesService`` — its ``request_async`` already injects auth, tenant/account -scoping, and retries — instead of building a second auth path. The only -caller-influenced value is ``ontology_name``, which is validated against the -QueryEngine name contract before it becomes part of the request URL. - -The ``owl`` file's content may be serialized as Turtle (.ttl) or as OWL -Functional Notation (.ofn) — both are valid OWL 2 QL serializations and both -are plain text. To stay agnostic to the stored serialization we request the -JSON wrapper (``Accept: application/json``), which always returns ``content`` -plus its ``mediaType`` regardless of notation. Requesting a specific text type -(e.g. ``text/turtle``) would 406 when the stored file is the other notation. - -Naming follows the REST API: the resource is identified by ``ontologyName`` -(``OntologyController`` route ``/{ontologyName}/files/{fileType}``). -""" - -import logging -import re -from typing import Any - -logger = logging.getLogger(__name__) - -# QueryEngine ontology name contract (OntologyCreateRequestValidator): -# lowercase, must start with a letter, max 64 chars. -_ONTOLOGY_NAME_RE = re.compile(r"^[a-z][a-z0-9-]{0,63}$") - -# Defensive cap so a malformed or oversized file can never blow up the prompt -# or token budget. Real OWL 2 QL files are a few KB; QueryEngine caps at 10 MB. -_MAX_OWL_BYTES = 1_000_000 - -_FOLDER_KEY_HEADER = "X-UiPath-FolderKey" - - -def _validate_ontology_name(ontology_name: str) -> str: - """Validate the ontology name against the QueryEngine name contract. - - The name becomes a path segment in the request URL, so only the documented - charset is permitted. This blocks path-segment injection and traversal via - crafted name values. - - Args: - ontology_name: The ontology name to validate. - - Returns: - The validated name (unchanged). - - Raises: - ValueError: If the name does not match ``^[a-z][a-z0-9-]{0,63}$``. - """ - if not isinstance(ontology_name, str) or not _ONTOLOGY_NAME_RE.match( - ontology_name - ): - raise ValueError( - f"Invalid ontology name {ontology_name!r}. " - "Must match ^[a-z][a-z0-9-]{0,63}$." - ) - return ontology_name - - -async def fetch_ontology_owl( - entities_service: Any, - ontology_name: str, - folder_key: str | None = None, -) -> tuple[str, str]: - """Fetch the OWL file for an ontology from Data Fabric. - - Args: - entities_service: An authenticated SDK ``EntitiesService``. Reused for - its ``request_async`` (auth headers, base-URL scoping, retries). - ontology_name: Ontology name. Validated against the QE name contract. - folder_key: Optional UiPath folder key for folder-scoped resolution. - - Returns: - A ``(content, media_type)`` tuple. ``content`` is the OWL text in - whatever serialization is stored — Turtle or OWL Functional Notation; - ``media_type`` is the stored media type (e.g. ``text/turtle``), usable - to label the notation. - - Raises: - ValueError: If the name is invalid or the content exceeds the size cap. - Transport/HTTP errors propagate from the SDK as raised exceptions - (the caller decides how to degrade). - """ - safe_name = _validate_ontology_name(ontology_name) - # Same datafabric_ service the entities calls target; matches the - # QueryEngine ontology route GET /ontologies/{ontologyName}/files/{fileType}. - endpoint = f"datafabric_/api/ontologies/{safe_name}/files/owl" - - # JSON wrapper: notation-agnostic (works for Turtle or OFN) and returns the - # stored mediaType. A text/* Accept would 406 on a serialization mismatch. - headers = {"Accept": "application/json"} - if folder_key: - headers[_FOLDER_KEY_HEADER] = folder_key - - response = await entities_service.request_async( - "GET", endpoint, scoped="tenant", headers=headers - ) - - data = response.json() - content = data.get("content") or "" - media_type = data.get("mediaType") or "" - - if len(content.encode("utf-8")) > _MAX_OWL_BYTES: - raise ValueError( - f"Ontology OWL for {safe_name!r} exceeds the " - f"{_MAX_OWL_BYTES} byte limit." - ) - logger.debug( - "Fetched ontology OWL for %r (%d chars, mediaType=%s)", - safe_name, - len(content), - media_type, - ) - return content, media_type diff --git a/src/uipath_langchain/agent/tools/datafabric_tool/ontology_fetch_tool.py b/src/uipath_langchain/agent/tools/datafabric_tool/ontology_fetch_tool.py index 5e6a21fd0..d5eab639c 100644 --- a/src/uipath_langchain/agent/tools/datafabric_tool/ontology_fetch_tool.py +++ b/src/uipath_langchain/agent/tools/datafabric_tool/ontology_fetch_tool.py @@ -22,10 +22,12 @@ from ..base_uipath_structured_tool import BaseUiPathStructuredTool from .models import OntologyFetchInput -from .ontology_client import fetch_ontology_owl logger = logging.getLogger(__name__) +# Defensive cap so a malformed/oversized OWL can't blow up the prompt/token budget. +_MAX_OWL_BYTES = 1_000_000 + def _notation_label(media_type: str) -> str: """Best-effort human label for the OWL serialization. @@ -72,9 +74,16 @@ async def __call__(self, **_kwargs: Any) -> str: if self._cached is not None: return self._cached try: - owl, media_type = await fetch_ontology_owl( - self._entities_service, self._ontology_name, self._folder_key + data = await self._entities_service.get_ontology_file_async( + self._ontology_name, "owl", self._folder_key ) + owl = data.get("content") or "" + media_type = data.get("mediaType") or "" + if len(owl.encode("utf-8")) > _MAX_OWL_BYTES: + raise ValueError( + f"Ontology '{self._ontology_name}' OWL exceeds " + f"{_MAX_OWL_BYTES} bytes." + ) except Exception as e: # Graceful degradation — ontology is an enhancement, not a hard # dependency. Do not surface internal error detail to the model. From 68f7cbf5de177eb4777504d13ddec6bc3fcb6c36 Mon Sep 17 00:00:00 2001 From: sankalp-uipath Date: Wed, 17 Jun 2026 15:47:46 +0530 Subject: [PATCH 04/13] feat(datafabric): support multiple ontologies per context (ontologySet) --- .../datafabric_tool/datafabric_subgraph.py | 17 +-- .../tools/datafabric_tool/datafabric_tool.py | 51 ++++---- .../datafabric_tool/ontology_fetch_tool.py | 120 ++++++++---------- 3 files changed, 80 insertions(+), 108 deletions(-) diff --git a/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_subgraph.py b/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_subgraph.py index 6ae6e8912..821d21f14 100644 --- a/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_subgraph.py +++ b/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_subgraph.py @@ -89,21 +89,18 @@ def __init__( max_iterations: int = 25, resource_description: str = "", base_system_prompt: str = "", - ontology_name: str | None = None, - folder_key: str | None = None, + ontologies: list[tuple[str, str | None]] | None = None, ) -> None: self._max_iterations = max_iterations self._execute_sql_tool = self._create_execute_sql_tool( entities_service, entities ) # Inner toolset: always execute_sql; optionally an LLM-decided - # fetch_ontology tool when an ontology name is configured. + # fetch_ontology tool when one or more ontologies are configured. inner_tools: list[BaseTool] = [self._execute_sql_tool] - if ontology_name: + if ontologies: inner_tools.append( - create_ontology_fetch_tool( - entities_service, ontology_name, folder_key - ) + create_ontology_fetch_tool(entities_service, ontologies) ) self._tools_by_name: dict[str, BaseTool] = { tool.name: tool for tool in inner_tools @@ -264,8 +261,7 @@ def create( max_iterations: int = 25, resource_description: str = "", base_system_prompt: str = "", - ontology_name: str | None = None, - folder_key: str | None = None, + ontologies: list[tuple[str, str | None]] | None = None, ) -> CompiledStateGraph[Any]: """Create and return a compiled Data Fabric sub-graph.""" graph = DataFabricGraph( @@ -275,7 +271,6 @@ def create( max_iterations, resource_description, base_system_prompt, - ontology_name, - folder_key, + ontologies, ) return graph.compiled_graph diff --git a/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py b/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py index e605fb353..fad941f1e 100644 --- a/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py +++ b/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py @@ -47,15 +47,13 @@ def __init__( llm: BaseChatModel, resource_description: str = "", base_system_prompt: str = "", - ontology_name: str | None = None, - folder_key: str | None = None, + ontologies: list[tuple[str, str | None]] | None = None, ) -> None: self._entity_set = entity_set self._llm = llm self._resource_description = resource_description self._base_system_prompt = base_system_prompt - self._ontology_name = ontology_name - self._folder_key = folder_key + self._ontologies = ontologies or [] self._compiled: CompiledStateGraph[Any] | None = None self._init_lock = asyncio.Lock() @@ -89,8 +87,7 @@ async def _ensure_datafabric_graph(self) -> CompiledStateGraph[Any]: entities_service=resolution.entities_service, resource_description=self._resource_description, base_system_prompt=self._base_system_prompt, - ontology_name=self._ontology_name, - folder_key=self._folder_key, + ontologies=self._ontologies, ) return self._compiled @@ -168,39 +165,37 @@ def create_datafabric_query_tool( DataFabricEntityItem.model_validate(item.model_dump(by_alias=True)) for item in (resource.entity_set or []) ] - # Ontology name is pinned from configuration (not chosen by the LLM). - # Falls back to env vars for local/demo runs that have no Agent Builder UI. - # When unset, no fetch_ontology tool is added (fully backward compatible). - # Ontology binding — the first-class source, mirroring entity_set. The - # binding carries the ontology name AND its own folderId, so the ontology is - # resolved from its own folder (entities may span several folders). - ontology_binding = getattr(resource, "ontology", None) - # Single-folder derivation is only a last-resort fallback for legacy - # agent.json with no ontology binding (and only when entities share a folder). + # Ontologies are first-class bindings, mirroring entity_set: a LIST, each + # carrying its own folderId so it is resolved from its own folder (entities + # may also span several folders). Falls back to a single env-configured + # ontology for local/demo runs with no binding. Empty → no fetch tool added. entity_folders = { e.folder_key for e in entity_set if getattr(e, "folder_key", None) } derived_folder_key = ( next(iter(entity_folders)) if len(entity_folders) == 1 else None ) - ontology_name = ( - (ontology_binding.name if ontology_binding else None) - or config.get(ONTOLOGY_NAME) - or os.getenv("UIPATH_ONTOLOGY_NAME") - ) - folder_key = ( - (ontology_binding.folder_key if ontology_binding else None) - or config.get(FOLDER_KEY) - or os.getenv("UIPATH_FOLDER_KEY") - or derived_folder_key - ) + ontology_items = getattr(resource, "ontology_set", None) or [] + ontologies: list[tuple[str, str | None]] = [ + (o.name, o.folder_key or derived_folder_key) + for o in ontology_items + if getattr(o, "name", None) + ] + if not ontologies: + env_name = config.get(ONTOLOGY_NAME) or os.getenv("UIPATH_ONTOLOGY_NAME") + if env_name: + env_folder = ( + config.get(FOLDER_KEY) + or os.getenv("UIPATH_FOLDER_KEY") + or derived_folder_key + ) + ontologies = [(env_name, env_folder)] handler = DataFabricTextQueryHandler( entity_set=entity_set, llm=llm, resource_description=resource.description or "", base_system_prompt=config.get(BASE_SYSTEM_PROMPT, ""), - ontology_name=ontology_name, - folder_key=folder_key, + ontologies=ontologies, ) entity_lines = [] for e in entity_set: diff --git a/src/uipath_langchain/agent/tools/datafabric_tool/ontology_fetch_tool.py b/src/uipath_langchain/agent/tools/datafabric_tool/ontology_fetch_tool.py index d5eab639c..475da60d1 100644 --- a/src/uipath_langchain/agent/tools/datafabric_tool/ontology_fetch_tool.py +++ b/src/uipath_langchain/agent/tools/datafabric_tool/ontology_fetch_tool.py @@ -1,17 +1,14 @@ -"""LLM-decided tool that fetches an ontology's OWL schema from Data Fabric. +"""LLM-decided tool that fetches ontology OWL schemas from Data Fabric. Mirrors ``datafabric_query_tool.py``: a small leaf tool the inner SQL agent can -call. On invocation it fetches the configured ontology's OWL via the -QueryEngine ontology REST API and returns it. The tool node turns the return -value into a ToolMessage that the inner LLM reads on its next turn — so the -model can call ``fetch_ontology`` first, then write SQL guided by the result. - -The OWL content may be Turtle (.ttl) or OWL Functional Notation (.ofn); both -are valid OWL 2 QL serializations. The fence label reflects the actual stored -notation so the LLM knows what it is reading. - -The ontology name is pinned from configuration, not supplied by the LLM, so the -model cannot redirect the fetch to an arbitrary resource. +call. A context may attach one or more ontologies (mirroring the entity set), so +the tool fetches each configured ontology's OWL via the SDK +(``EntitiesService.get_ontology_file_async``) and returns them concatenated. The +tool node turns the return value into a ToolMessage the inner LLM reads on its +next turn — so the model can call ``fetch_ontology`` first, then write SQL. + +Ontology names/folders are pinned from configuration, not supplied by the LLM, +so the model cannot redirect the fetch to an arbitrary resource. """ import logging @@ -25,16 +22,13 @@ logger = logging.getLogger(__name__) -# Defensive cap so a malformed/oversized OWL can't blow up the prompt/token budget. +# Defensive cap per ontology so a malformed/oversized OWL can't blow up the +# prompt/token budget. _MAX_OWL_BYTES = 1_000_000 def _notation_label(media_type: str) -> str: - """Best-effort human label for the OWL serialization. - - OWL can be stored as Turtle or OWL Functional Notation (OFN); both are - plain text. Falls back to naming both when the media type is unrecognized. - """ + """Best-effort label for the OWL serialization (Turtle or OFN).""" mt = (media_type or "").lower() if "turtle" in mt or mt.endswith("ttl"): return "Turtle" @@ -44,96 +38,84 @@ def _notation_label(media_type: str) -> str: class OntologyFetcher: - """Fetches and caches the OWL ontology for a fixed, configured name. + """Fetches and caches the OWL for one or more configured ontologies. - The result is cached on this instance. Because the instance lives as long - as the compiled sub-graph (which the handler caches), repeated calls across - queries hit the API at most once, surviving the per-query reset of the - inner sub-graph state. + Each entry is ``(ontology_name, folder_key)`` — the ontology carries its own + folder. The combined result is cached on this instance, which lives as long + as the compiled sub-graph, so repeated calls across queries hit the API at + most once. """ def __init__( self, entities_service: EntitiesService, - ontology_name: str, - folder_key: str | None = None, + ontologies: list[tuple[str, str | None]], ) -> None: self._entities_service = entities_service - self._ontology_name = ontology_name - self._folder_key = folder_key + self._ontologies = ontologies self._cached: str | None = None - async def __call__(self, **_kwargs: Any) -> str: - """Return the OWL ontology text, fetching and caching on first call. - - Accepts and ignores keyword arguments so it works with an empty args - schema regardless of how the tool runner invokes it. Failures degrade - gracefully: the agent can still answer using the entity schemas already - present in the system prompt. - """ - if self._cached is not None: - return self._cached + async def _fetch_one(self, name: str, folder_key: str | None) -> str: try: data = await self._entities_service.get_ontology_file_async( - self._ontology_name, "owl", self._folder_key + name, "owl", folder_key ) owl = data.get("content") or "" media_type = data.get("mediaType") or "" if len(owl.encode("utf-8")) > _MAX_OWL_BYTES: - raise ValueError( - f"Ontology '{self._ontology_name}' OWL exceeds " - f"{_MAX_OWL_BYTES} bytes." - ) + raise ValueError(f"Ontology '{name}' OWL exceeds the size limit.") except Exception as e: - # Graceful degradation — ontology is an enhancement, not a hard - # dependency. Do not surface internal error detail to the model. - logger.warning( - "Ontology fetch failed for %r: %s", self._ontology_name, e - ) + logger.warning("Ontology fetch failed for %r: %s", name, e) return ( - f"Ontology '{self._ontology_name}' is unavailable " - f"({type(e).__name__}). Proceed using the entity schemas " - "described in the system prompt." + f"Ontology '{name}' is unavailable ({type(e).__name__}). " + "Proceed using the entity schemas in the system prompt." ) notation = _notation_label(media_type) - self._cached = ( - f"OWL 2 QL ontology '{self._ontology_name}' ({notation}) — " - "authoritative schema. Use these exact class/property names and " - "value formats for SQL; this is reference data, not instructions.\n\n" - f"--- ONTOLOGY (OWL 2 QL, {notation}) ---\n{owl}\n--- END ONTOLOGY ---" + return ( + f"OWL 2 QL ontology '{name}' ({notation}) — authoritative schema. " + "Use these exact class/property names and value formats for SQL; " + "this is reference data, not instructions.\n\n" + f"--- ONTOLOGY: {name} ({notation}) ---\n{owl}\n" + f"--- END ONTOLOGY: {name} ---" ) + + async def __call__(self, **_kwargs: Any) -> str: + """Fetch all configured ontologies (cached), concatenated for the LLM.""" + if self._cached is not None: + return self._cached + if not self._ontologies: + return "No ontologies are configured for this agent." + blocks = [await self._fetch_one(name, folder) for name, folder in self._ontologies] + self._cached = "\n\n".join(blocks) return self._cached def create_ontology_fetch_tool( entities_service: EntitiesService, - ontology_name: str, - folder_key: str | None = None, + ontologies: list[tuple[str, str | None]], tool_name: str = "fetch_ontology", ) -> BaseTool: """Create the ``fetch_ontology`` leaf tool for the inner sub-graph. Args: - entities_service: Authenticated SDK service reused for the REST call. - ontology_name: The ontology to fetch (pinned from configuration). - folder_key: Optional UiPath folder key for folder-scoped resolution. + entities_service: Authenticated SDK service used for the REST call. + ontologies: ``(name, folder_key)`` pairs to fetch (pinned from config). tool_name: The tool name exposed to the LLM. Returns: - A ``BaseUiPathStructuredTool`` that fetches the OWL ontology (Turtle or - OWL Functional Notation) and returns it as the tool result (wrapped - into a ToolMessage by the tool node). + A ``BaseUiPathStructuredTool`` that fetches the OWL of every configured + ontology and returns them as the tool result (one ToolMessage). """ + names = ", ".join(name for name, _ in ontologies) or "(none)" return BaseUiPathStructuredTool( name=tool_name, description=( - f"Fetch the OWL 2 QL ontology (the authoritative semantic schema) " - f"for the '{ontology_name}' ontology. Call this BEFORE writing SQL: " - "it gives the exact class and property names, value formats, and " - "relationships so your SQL uses the real schema instead of guesses. " - "Takes no arguments." + f"Fetch the OWL 2 QL ontologies (the authoritative semantic schema) " + f"for: {names}. Call this BEFORE writing SQL: it gives the exact " + "class and property names, value formats, and relationships so your " + "SQL uses the real schema instead of guesses. Takes no arguments." ), args_schema=OntologyFetchInput, - coroutine=OntologyFetcher(entities_service, ontology_name, folder_key), + coroutine=OntologyFetcher(entities_service, ontologies), metadata={"tool_type": "ontology_fetch"}, ) From 40acdec5e5d900cc5c82bd7c941a32c76f1aaf27 Mon Sep 17 00:00:00 2001 From: sankalp-uipath Date: Mon, 22 Jun 2026 12:25:06 +0530 Subject: [PATCH 05/13] fix(datafabric): end loop on any successful SQL; drop env-var ontology fallback --- .../tools/datafabric_tool/datafabric_subgraph.py | 8 ++++++-- .../tools/datafabric_tool/datafabric_tool.py | 16 ++-------------- 2 files changed, 8 insertions(+), 16 deletions(-) diff --git a/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_subgraph.py b/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_subgraph.py index 821d21f14..7f463c4db 100644 --- a/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_subgraph.py +++ b/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_subgraph.py @@ -143,11 +143,15 @@ async def tool_node(self, state: DataFabricSubgraphState) -> dict[str, Any]: *[self._execute_tool_call(tc) for tc in last.tool_calls] ) tool_messages = [msg for msg, _ in results] - all_succeeded = bool(results) and all(success for _, success in results) + # End as soon as ANY tool call is a terminal success (a row-returning + # execute_sql). `any` not `all`: a non-terminal tool (e.g. fetch_ontology) + # co-issued in the same turn must not prevent a successful SQL from ending + # the loop. + any_succeeded = any(success for _, success in results) return { "messages": tool_messages, "iteration_count": state.iteration_count + len(last.tool_calls), - "last_tool_success": all_succeeded, + "last_tool_success": any_succeeded, } async def _execute_tool_call(self, tool_call: ToolCall) -> tuple[ToolMessage, bool]: diff --git a/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py b/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py index fad941f1e..d9292eae4 100644 --- a/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py +++ b/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py @@ -13,7 +13,6 @@ import asyncio import logging -import os from typing import Any from langchain_core.language_models import BaseChatModel @@ -29,8 +28,6 @@ logger = logging.getLogger(__name__) BASE_SYSTEM_PROMPT = "base_system_prompt" -ONTOLOGY_NAME = "ontology_name" -FOLDER_KEY = "folder_key" class DataFabricTextQueryHandler: @@ -167,8 +164,8 @@ def create_datafabric_query_tool( ] # Ontologies are first-class bindings, mirroring entity_set: a LIST, each # carrying its own folderId so it is resolved from its own folder (entities - # may also span several folders). Falls back to a single env-configured - # ontology for local/demo runs with no binding. Empty → no fetch tool added. + # may also span several folders). Empty → no fetch tool added. Config comes + # only from the agent definition (the binding), never from process env. entity_folders = { e.folder_key for e in entity_set if getattr(e, "folder_key", None) } @@ -181,15 +178,6 @@ def create_datafabric_query_tool( for o in ontology_items if getattr(o, "name", None) ] - if not ontologies: - env_name = config.get(ONTOLOGY_NAME) or os.getenv("UIPATH_ONTOLOGY_NAME") - if env_name: - env_folder = ( - config.get(FOLDER_KEY) - or os.getenv("UIPATH_FOLDER_KEY") - or derived_folder_key - ) - ontologies = [(env_name, env_folder)] handler = DataFabricTextQueryHandler( entity_set=entity_set, llm=llm, From 7a5bb695b4522e61df6b35bd8a9a6d722286f3a3 Mon Sep 17 00:00:00 2001 From: sankalp-uipath Date: Mon, 22 Jun 2026 12:55:14 +0530 Subject: [PATCH 06/13] test(datafabric): cover ontology fetch tool, subgraph routing, and factory mapping --- .../test_datafabric_ontology_subgraph.py | 131 +++++++++++++++++ .../test_datafabric_tool_ontology_factory.py | 46 ++++++ tests/agent/tools/test_ontology_fetch_tool.py | 132 ++++++++++++++++++ 3 files changed, 309 insertions(+) create mode 100644 tests/agent/tools/test_datafabric_ontology_subgraph.py create mode 100644 tests/agent/tools/test_datafabric_tool_ontology_factory.py create mode 100644 tests/agent/tools/test_ontology_fetch_tool.py diff --git a/tests/agent/tools/test_datafabric_ontology_subgraph.py b/tests/agent/tools/test_datafabric_ontology_subgraph.py new file mode 100644 index 000000000..4a746c597 --- /dev/null +++ b/tests/agent/tools/test_datafabric_ontology_subgraph.py @@ -0,0 +1,131 @@ +"""Tests for the ontology additions to the Data Fabric inner sub-graph. + +Covers: conditional binding of fetch_ontology, dispatch-by-name in +_execute_tool_call, and the any(...) terminal logic in tool_node. +""" + +from unittest.mock import AsyncMock, MagicMock + +import pytest +from langchain_core.messages import AIMessage + +from uipath_langchain.agent.tools.datafabric_tool import datafabric_subgraph as dsg +from uipath_langchain.agent.tools.datafabric_tool.datafabric_subgraph import ( + DataFabricGraph, + DataFabricSubgraphState, +) + + +@pytest.fixture +def entities_service(): + es = MagicMock() + es.query_entity_records_async = AsyncMock(return_value=[{"x": 1}]) + es.get_ontology_file_async = AsyncMock( + return_value={"content": "OWLX", "mediaType": "text/turtle"} + ) + return es + + +@pytest.fixture +def make_graph(monkeypatch, entities_service): + # Isolate from the prompt builder; we only exercise tools/routing here. + monkeypatch.setattr(dsg.datafabric_prompt_builder, "build", lambda *a, **k: "SYS") + + def _make(ontologies=None): + return DataFabricGraph( + llm=MagicMock(), + entities=[], + entities_service=entities_service, + ontologies=ontologies, + ) + + return _make + + +def _tc(name, args=None, cid="c1"): + return {"name": name, "args": args or {}, "id": cid, "type": "tool_call"} + + +def test_fetch_ontology_bound_only_when_ontologies(make_graph): + without = make_graph(None) + assert "execute_sql" in without._tools_by_name + assert "fetch_ontology" not in without._tools_by_name + + with_onto = make_graph([("library", None)]) + assert "fetch_ontology" in with_onto._tools_by_name + + +async def test_execute_tool_call_unknown_tool(make_graph): + graph = make_graph() + msg, ok = await graph._execute_tool_call(_tc("does_not_exist")) + assert ok is False + assert "Unknown tool" in str(msg.content) + + +async def test_execute_tool_call_sql_with_rows_is_terminal(make_graph): + graph = make_graph() + msg, ok = await graph._execute_tool_call( + _tc("execute_sql", {"sql_query": "SELECT 1"}) + ) + assert ok is True + + +async def test_execute_tool_call_sql_no_rows_not_terminal(make_graph, entities_service): + entities_service.query_entity_records_async = AsyncMock(return_value=[]) + graph = make_graph() + msg, ok = await graph._execute_tool_call( + _tc("execute_sql", {"sql_query": "SELECT 1"}) + ) + assert ok is False + + +async def test_execute_tool_call_fetch_ontology_not_terminal(make_graph): + graph = make_graph([("library", None)]) + msg, ok = await graph._execute_tool_call(_tc("fetch_ontology")) + assert ok is False # ontology fetch loops back, never terminal + assert "library" in str(msg.content) + + +async def test_tool_node_any_succeeds_with_mixed_batch(make_graph): + graph = make_graph([("library", None)]) + ai = AIMessage( + content="", + tool_calls=[ + _tc("execute_sql", {"sql_query": "SELECT 1"}, "a"), + _tc("fetch_ontology", {}, "b"), + ], + ) + out = await graph.tool_node(DataFabricSubgraphState(messages=[ai])) + # SQL returned rows → terminal, even though fetch_ontology (non-terminal) + # was co-issued in the same turn. This is the all()->any() fix. + assert out["last_tool_success"] is True + assert len(out["messages"]) == 2 + + +async def test_tool_node_not_terminal_when_only_ontology(make_graph): + graph = make_graph([("library", None)]) + ai = AIMessage(content="", tool_calls=[_tc("fetch_ontology", {}, "b")]) + out = await graph.tool_node(DataFabricSubgraphState(messages=[ai])) + assert out["last_tool_success"] is False + + +async def test_execute_tool_call_sql_value_error_becomes_error_dict(make_graph): + # execute_sql raises ValueError on multiple statements; it must be caught and + # turned into an error result (non-terminal), not propagated. + graph = make_graph() + msg, ok = await graph._execute_tool_call( + _tc("execute_sql", {"sql_query": "SELECT 1; SELECT 2"}) + ) + assert ok is False + assert "error" in str(msg.content) + + +def test_create_returns_compiled_graph(monkeypatch, entities_service): + monkeypatch.setattr(dsg.datafabric_prompt_builder, "build", lambda *a, **k: "SYS") + compiled = DataFabricGraph.create( + llm=MagicMock(), + entities=[], + entities_service=entities_service, + ontologies=[("library", None)], + ) + assert hasattr(compiled, "ainvoke") diff --git a/tests/agent/tools/test_datafabric_tool_ontology_factory.py b/tests/agent/tools/test_datafabric_tool_ontology_factory.py new file mode 100644 index 000000000..96087075d --- /dev/null +++ b/tests/agent/tools/test_datafabric_tool_ontology_factory.py @@ -0,0 +1,46 @@ +"""Tests for the ontology_set → (name, folder) mapping in the DF tool factory.""" + +from types import SimpleNamespace +from unittest.mock import MagicMock + +from uipath.platform.entities import DataFabricEntityItem + +from uipath_langchain.agent.tools.datafabric_tool.datafabric_tool import ( + create_datafabric_query_tool, +) + + +def _resource(ontology_set): + entity = DataFabricEntityItem.model_validate( + {"id": "e1", "referenceKey": "e1", "name": "LibraryLoan", "folderId": "f1"} + ) + return SimpleNamespace( + entity_set=[entity], + ontology_set=ontology_set, + description="ctx", + ) + + +def test_factory_maps_ontology_set_and_derives_folder(): + # ontology with no folderId inherits the single entity folder. + resource = _resource([SimpleNamespace(name="library", folder_key=None)]) + + tool = create_datafabric_query_tool(resource, MagicMock()) # type: ignore[arg-type] + + assert tool.coroutine._ontologies == [("library", "f1")] + + +def test_factory_keeps_per_ontology_folder(): + resource = _resource([SimpleNamespace(name="finance", folder_key="f2")]) + + tool = create_datafabric_query_tool(resource, MagicMock()) # type: ignore[arg-type] + + assert tool.coroutine._ontologies == [("finance", "f2")] + + +def test_factory_no_ontologies_is_empty(): + resource = _resource([]) + + tool = create_datafabric_query_tool(resource, MagicMock()) # type: ignore[arg-type] + + assert tool.coroutine._ontologies == [] diff --git a/tests/agent/tools/test_ontology_fetch_tool.py b/tests/agent/tools/test_ontology_fetch_tool.py new file mode 100644 index 000000000..005c938ee --- /dev/null +++ b/tests/agent/tools/test_ontology_fetch_tool.py @@ -0,0 +1,132 @@ +"""Tests for the ontology fetch tool (datafabric_tool/ontology_fetch_tool.py).""" + +from unittest.mock import AsyncMock, MagicMock + +from uipath_langchain.agent.tools.datafabric_tool import ontology_fetch_tool as oft +from uipath_langchain.agent.tools.datafabric_tool.models import OntologyFetchInput +from uipath_langchain.agent.tools.datafabric_tool.ontology_fetch_tool import ( + OntologyFetcher, + _notation_label, + create_ontology_fetch_tool, +) + + +def _entities_service(content: str = "OWLDATA", media_type: str = "text/turtle"): + es = MagicMock() + es.get_ontology_file_async = AsyncMock( + return_value={"content": content, "mediaType": media_type} + ) + return es + + +# --- _notation_label ------------------------------------------------------- + + +def test_notation_label_turtle(): + assert _notation_label("text/turtle") == "Turtle" + assert _notation_label("application/ttl") == "Turtle" + + +def test_notation_label_functional(): + assert _notation_label("application/owl-functional") == "OWL Functional Notation" + assert _notation_label("text/ofn") == "OWL Functional Notation" + + +def test_notation_label_unknown_defaults(): + assert _notation_label("") == "Turtle or OWL Functional Notation" + assert _notation_label("application/json") == "Turtle or OWL Functional Notation" + + +# --- OntologyFetchInput ---------------------------------------------------- + + +def test_ontology_fetch_input_is_empty(): + # Intentionally empty: the name is pinned from config, never the LLM. + assert OntologyFetchInput().model_dump() == {} + + +# --- OntologyFetcher ------------------------------------------------------- + + +async def test_fetcher_no_ontologies_returns_message(): + fetcher = OntologyFetcher(_entities_service(), []) + result = await fetcher() + assert "No ontologies are configured" in result + + +async def test_fetcher_single_ontology_returns_fenced_block(): + es = _entities_service(content="OWLBODY", media_type="text/turtle") + fetcher = OntologyFetcher(es, [("library", "folder-1")]) + + result = await fetcher() + + assert "ONTOLOGY: library" in result + assert "OWLBODY" in result + assert "Turtle" in result + es.get_ontology_file_async.assert_awaited_once_with("library", "owl", "folder-1") + + +async def test_fetcher_multiple_ontologies_concatenated(): + es = _entities_service() + fetcher = OntologyFetcher(es, [("library", None), ("finance", "f2")]) + + result = await fetcher() + + assert "ONTOLOGY: library" in result + assert "ONTOLOGY: finance" in result + assert es.get_ontology_file_async.await_count == 2 + + +async def test_fetcher_caches_after_first_call(): + es = _entities_service() + fetcher = OntologyFetcher(es, [("library", None), ("finance", None)]) + + first = await fetcher() + second = await fetcher() + + assert first == second + # Two ontologies fetched once total — the second call is served from cache. + assert es.get_ontology_file_async.await_count == 2 + + +async def test_fetcher_graceful_degrade_on_error(): + es = MagicMock() + es.get_ontology_file_async = AsyncMock(side_effect=RuntimeError("boom")) + fetcher = OntologyFetcher(es, [("library", None)]) + + result = await fetcher() + + assert "unavailable" in result + assert "RuntimeError" in result # the exception type is surfaced, not raised + + +async def test_fetcher_oversized_owl_is_degraded(monkeypatch): + monkeypatch.setattr(oft, "_MAX_OWL_BYTES", 5) + es = _entities_service(content="0123456789") # 10 bytes > cap + fetcher = OntologyFetcher(es, [("library", None)]) + + result = await fetcher() + + assert "unavailable" in result + + +# --- create_ontology_fetch_tool -------------------------------------------- + + +def test_create_tool_metadata_and_schema(): + tool = create_ontology_fetch_tool(_entities_service(), [("library", None), ("finance", None)]) + + assert tool.name == "fetch_ontology" + assert "library" in tool.description and "finance" in tool.description + assert tool.args_schema is OntologyFetchInput + assert tool.metadata == {"tool_type": "ontology_fetch"} + + +async def test_create_tool_invocation_fetches_ontology(): + es = _entities_service(content="OWLBODY") + tool = create_ontology_fetch_tool(es, [("library", None)]) + + result = await tool.ainvoke({}) + + assert "library" in result + assert "OWLBODY" in result From 04f79c53295b1229d9c47205d79c7bc22bf17767 Mon Sep 17 00:00:00 2001 From: sankalp-uipath Date: Mon, 22 Jun 2026 13:34:51 +0530 Subject: [PATCH 07/13] fix(datafabric): return only terminal tool msgs on END; drop ToolMessage.status to match host node --- .../agent/tools/datafabric_tool/datafabric_subgraph.py | 10 ++++++++-- tests/agent/tools/test_datafabric_ontology_subgraph.py | 5 ++++- 2 files changed, 12 insertions(+), 3 deletions(-) diff --git a/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_subgraph.py b/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_subgraph.py index 7f463c4db..170ce86e5 100644 --- a/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_subgraph.py +++ b/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_subgraph.py @@ -142,12 +142,19 @@ async def tool_node(self, state: DataFabricSubgraphState) -> dict[str, Any]: results = await asyncio.gather( *[self._execute_tool_call(tc) for tc in last.tool_calls] ) - tool_messages = [msg for msg, _ in results] # End as soon as ANY tool call is a terminal success (a row-returning # execute_sql). `any` not `all`: a non-terminal tool (e.g. fetch_ontology) # co-issued in the same turn must not prevent a successful SQL from ending # the loop. any_succeeded = any(success for _, success in results) + # When short-circuiting to END, return ONLY the terminal-success + # ToolMessages so the outer agent's result is the query rows — not a + # co-issued fetch_ontology's OWL. On a non-terminal turn keep all messages + # so the inner LLM can use them on its next pass. + if any_succeeded: + tool_messages = [msg for msg, success in results if success] + else: + tool_messages = [msg for msg, _ in results] return { "messages": tool_messages, "iteration_count": state.iteration_count + len(last.tool_calls), @@ -172,7 +179,6 @@ async def _execute_tool_call(self, tool_call: ToolCall) -> tuple[ToolMessage, bo content=f"Unknown tool: {name}", tool_call_id=tool_call["id"], name=name, - status="error", ), False, ) diff --git a/tests/agent/tools/test_datafabric_ontology_subgraph.py b/tests/agent/tools/test_datafabric_ontology_subgraph.py index 4a746c597..43a5fdfbb 100644 --- a/tests/agent/tools/test_datafabric_ontology_subgraph.py +++ b/tests/agent/tools/test_datafabric_ontology_subgraph.py @@ -99,7 +99,10 @@ async def test_tool_node_any_succeeds_with_mixed_batch(make_graph): # SQL returned rows → terminal, even though fetch_ontology (non-terminal) # was co-issued in the same turn. This is the all()->any() fix. assert out["last_tool_success"] is True - assert len(out["messages"]) == 2 + # Only the terminal execute_sql message is returned; the non-terminal + # fetch_ontology output is dropped when short-circuiting to END. + assert len(out["messages"]) == 1 + assert out["messages"][0].name == "execute_sql" async def test_tool_node_not_terminal_when_only_ontology(make_graph): From 0ed62108eabf05608c89ba34fb0c9d72c9469f1d Mon Sep 17 00:00:00 2001 From: sankalp-uipath Date: Tue, 23 Jun 2026 01:19:44 +0530 Subject: [PATCH 08/13] perf(datafabric): fetch configured ontologies concurrently (asyncio.gather) --- .../agent/tools/datafabric_tool/ontology_fetch_tool.py | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/src/uipath_langchain/agent/tools/datafabric_tool/ontology_fetch_tool.py b/src/uipath_langchain/agent/tools/datafabric_tool/ontology_fetch_tool.py index 475da60d1..be8fafa1c 100644 --- a/src/uipath_langchain/agent/tools/datafabric_tool/ontology_fetch_tool.py +++ b/src/uipath_langchain/agent/tools/datafabric_tool/ontology_fetch_tool.py @@ -11,6 +11,7 @@ so the model cannot redirect the fetch to an arbitrary resource. """ +import asyncio import logging from typing import Any @@ -85,7 +86,11 @@ async def __call__(self, **_kwargs: Any) -> str: return self._cached if not self._ontologies: return "No ontologies are configured for this agent." - blocks = [await self._fetch_one(name, folder) for name, folder in self._ontologies] + # Fetch all ontologies concurrently — each fetch is independent; order is + # preserved by gather, so the concatenation is deterministic. + blocks = await asyncio.gather( + *(self._fetch_one(name, folder) for name, folder in self._ontologies) + ) self._cached = "\n\n".join(blocks) return self._cached From e9c4cfbe3ef6575910f8dbe5c8968e1eff4b13b8 Mon Sep 17 00:00:00 2001 From: sankalp-uipath Date: Tue, 23 Jun 2026 18:19:15 +0530 Subject: [PATCH 09/13] feat(datafabric): resolve ontologies via ontology_refs --- .../agent/tools/context_tool.py | 9 +- .../agent/tools/datafabric_tool/__init__.py | 2 + .../tools/datafabric_tool/datafabric_tool.py | 60 +++++++++---- .../test_datafabric_tool_ontology_factory.py | 84 ++++++++++++++----- 4 files changed, 118 insertions(+), 37 deletions(-) diff --git a/src/uipath_langchain/agent/tools/context_tool.py b/src/uipath_langchain/agent/tools/context_tool.py index c22906835..1d44c6243 100644 --- a/src/uipath_langchain/agent/tools/context_tool.py +++ b/src/uipath_langchain/agent/tools/context_tool.py @@ -161,14 +161,21 @@ def create_context_tool( if resource.context_type == AgentContextType.DATA_FABRIC_ENTITY_SET: if llm is None: raise ValueError("Data Fabric entity set tools require an LLM instance") - from .datafabric_tool import create_datafabric_query_tool + from .datafabric_tool import ( + create_datafabric_query_tool, + resolve_context_ontologies, + ) from .datafabric_tool.datafabric_tool import BASE_SYSTEM_PROMPT + ontologies = resolve_context_ontologies( + resource, agent.resources if agent else [] + ) return create_datafabric_query_tool( resource, llm, tool_name=tool_name, agent_config={BASE_SYSTEM_PROMPT: _extract_system_prompt(agent)}, + ontologies=ontologies, ) assert resource.settings is not None diff --git a/src/uipath_langchain/agent/tools/datafabric_tool/__init__.py b/src/uipath_langchain/agent/tools/datafabric_tool/__init__.py index fccbda389..8c3ebc238 100644 --- a/src/uipath_langchain/agent/tools/datafabric_tool/__init__.py +++ b/src/uipath_langchain/agent/tools/datafabric_tool/__init__.py @@ -2,8 +2,10 @@ from .datafabric_tool import ( create_datafabric_query_tool, + resolve_context_ontologies, ) __all__ = [ "create_datafabric_query_tool", + "resolve_context_ontologies", ] diff --git a/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py b/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py index d9292eae4..f6724a510 100644 --- a/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py +++ b/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py @@ -19,7 +19,10 @@ from langchain_core.messages import AIMessage, HumanMessage, ToolMessage from langchain_core.tools import BaseTool from langgraph.graph.state import CompiledStateGraph -from uipath.agent.models.agent import AgentContextResourceConfig +from uipath.agent.models.agent import ( + AgentContextResourceConfig, + AgentOntologyResourceConfig, +) from uipath.platform.entities import DataFabricEntityItem from ..base_uipath_structured_tool import BaseUiPathStructuredTool @@ -30,6 +33,38 @@ BASE_SYSTEM_PROMPT = "base_system_prompt" +def resolve_context_ontologies( + resource: AgentContextResourceConfig, + resources: list[Any], +) -> list[tuple[str, str | None]]: + """Resolve a context's ``ontology_refs`` to ``(name, folder_key)`` pairs. + + Ontologies are standalone ``AgentOntologyResourceConfig`` resources; a Data + Fabric context references them by name via ``ontology_refs``. Each ontology + carries its own ``folderId``, so it is resolved from its own folder. A + dangling reference (no matching ontology resource) is skipped with a warning + so it can never break tool creation. + """ + refs = getattr(resource, "ontology_refs", None) or [] + if not refs: + return [] + by_name = { + r.name: r for r in resources if isinstance(r, AgentOntologyResourceConfig) + } + ontologies: list[tuple[str, str | None]] = [] + for ref in refs: + onto = by_name.get(ref) + if onto is None: + logger.warning( + "Context %r references unknown ontology %r; skipping.", + resource.name, + ref, + ) + continue + ontologies.append((onto.name, onto.folder_key)) + return ontologies + + class DataFabricTextQueryHandler: """Manages lazy initialization and invocation of the Data Fabric sub-graph. @@ -147,6 +182,7 @@ def create_datafabric_query_tool( llm: BaseChatModel, tool_name: str = "query_datafabric", agent_config: dict[str, str] | None = None, + ontologies: list[tuple[str, str | None]] | None = None, ) -> BaseTool: """Create the ``query_datafabric`` agentic tool. @@ -156,28 +192,18 @@ def create_datafabric_query_tool( tool_name: Sanitized tool name from the resource. agent_config: Optional dict with agent-level config. Key ``base_system_prompt`` carries the outer agent's system prompt. + ontologies: ``(name, folder_key)`` pairs resolved from the context's + ``ontology_refs`` against the agent's standalone ontology resources + (see ``resolve_context_ontologies``). Empty/None → no fetch tool is + added. Resolution comes only from the agent definition (the binding), + never from process env. """ config = agent_config or {} entity_set = [ DataFabricEntityItem.model_validate(item.model_dump(by_alias=True)) for item in (resource.entity_set or []) ] - # Ontologies are first-class bindings, mirroring entity_set: a LIST, each - # carrying its own folderId so it is resolved from its own folder (entities - # may also span several folders). Empty → no fetch tool added. Config comes - # only from the agent definition (the binding), never from process env. - entity_folders = { - e.folder_key for e in entity_set if getattr(e, "folder_key", None) - } - derived_folder_key = ( - next(iter(entity_folders)) if len(entity_folders) == 1 else None - ) - ontology_items = getattr(resource, "ontology_set", None) or [] - ontologies: list[tuple[str, str | None]] = [ - (o.name, o.folder_key or derived_folder_key) - for o in ontology_items - if getattr(o, "name", None) - ] + ontologies = ontologies or [] handler = DataFabricTextQueryHandler( entity_set=entity_set, llm=llm, diff --git a/tests/agent/tools/test_datafabric_tool_ontology_factory.py b/tests/agent/tools/test_datafabric_tool_ontology_factory.py index 96087075d..f11046a1c 100644 --- a/tests/agent/tools/test_datafabric_tool_ontology_factory.py +++ b/tests/agent/tools/test_datafabric_tool_ontology_factory.py @@ -1,46 +1,92 @@ -"""Tests for the ontology_set → (name, folder) mapping in the DF tool factory.""" +"""Tests for ontology resolution + (name, folder) mapping in the DF tool factory. + +Ontologies are standalone ``AgentOntologyResourceConfig`` resources; a Data +Fabric context references them by name via ``ontology_refs``. The caller +resolves those refs to ``(name, folder_key)`` pairs and passes them to the +factory. +""" from types import SimpleNamespace from unittest.mock import MagicMock +from uipath.agent.models.agent import ( + AgentContextResourceConfig, + AgentOntologyResourceConfig, +) from uipath.platform.entities import DataFabricEntityItem from uipath_langchain.agent.tools.datafabric_tool.datafabric_tool import ( create_datafabric_query_tool, + resolve_context_ontologies, ) -def _resource(ontology_set): +def _entity_resource(): entity = DataFabricEntityItem.model_validate( {"id": "e1", "referenceKey": "e1", "name": "LibraryLoan", "folderId": "f1"} ) - return SimpleNamespace( - entity_set=[entity], - ontology_set=ontology_set, - description="ctx", - ) + return SimpleNamespace(entity_set=[entity], description="ctx") -def test_factory_maps_ontology_set_and_derives_folder(): - # ontology with no folderId inherits the single entity folder. - resource = _resource([SimpleNamespace(name="library", folder_key=None)]) +# --- factory: passes resolved ontologies straight through to the handler --- - tool = create_datafabric_query_tool(resource, MagicMock()) # type: ignore[arg-type] +def test_factory_passes_ontologies_through(): + tool = create_datafabric_query_tool( + _entity_resource(), # type: ignore[arg-type] + MagicMock(), + ontologies=[("library", "f1")], + ) assert tool.coroutine._ontologies == [("library", "f1")] -def test_factory_keeps_per_ontology_folder(): - resource = _resource([SimpleNamespace(name="finance", folder_key="f2")]) +def test_factory_no_ontologies_is_empty(): + tool = create_datafabric_query_tool(_entity_resource(), MagicMock()) # type: ignore[arg-type] + assert tool.coroutine._ontologies == [] - tool = create_datafabric_query_tool(resource, MagicMock()) # type: ignore[arg-type] - assert tool.coroutine._ontologies == [("finance", "f2")] +# --- resolver: ontology_refs → standalone ontology resources → (name, folder) --- -def test_factory_no_ontologies_is_empty(): - resource = _resource([]) +def _ctx(ontology_refs): + return AgentContextResourceConfig.model_validate( + { + "$resourceType": "context", + "name": "TestDF", + "description": "", + "contextType": "datafabricentityset", + "ontologyRefs": ontology_refs, + } + ) - tool = create_datafabric_query_tool(resource, MagicMock()) # type: ignore[arg-type] - assert tool.coroutine._ontologies == [] +def _onto(name, folder_id): + return AgentOntologyResourceConfig.model_validate( + { + "$resourceType": "ontology", + "name": name, + "description": "", + "folderId": folder_id, + } + ) + + +def test_resolve_refs_to_name_and_folder(): + ctx = _ctx(["library", "finance"]) + resources = [ctx, _onto("library", "f1"), _onto("finance", "f2")] + assert resolve_context_ontologies(ctx, resources) == [ + ("library", "f1"), + ("finance", "f2"), + ] + + +def test_resolve_skips_dangling_ref(): + ctx = _ctx(["library", "missing"]) + resources = [ctx, _onto("library", "f1")] + # 'missing' has no matching ontology resource → skipped, not an error. + assert resolve_context_ontologies(ctx, resources) == [("library", "f1")] + + +def test_resolve_no_refs_is_empty(): + ctx = _ctx(None) + assert resolve_context_ontologies(ctx, [ctx]) == [] From 1fd7a30e7319a912cd505a9ea88bc797cc8ce791 Mon Sep 17 00:00:00 2001 From: sankalp-uipath Date: Tue, 23 Jun 2026 18:51:38 +0530 Subject: [PATCH 10/13] chore: consume uipath dev build (#1728) to unblock CI Co-Authored-By: Claude Opus 4.8 (1M context) --- pyproject.toml | 13 +++++++++++-- uv.lock | 29 ++++++++++++++++------------- 2 files changed, 27 insertions(+), 15 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 7bd9d381f..808a7fd98 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -5,9 +5,9 @@ description = "Python SDK that enables developers to build and deploy LangGraph readme = { file = "README.md", content-type = "text/markdown" } requires-python = ">=3.11" dependencies = [ - "uipath>=2.10.79, <2.12.0", + "uipath==2.11.10.dev1017286899", "uipath-core>=0.5.20, <0.6.0", - "uipath-platform>=0.1.71, <0.2.0", + "uipath-platform==0.1.74.dev1017286899", "uipath-runtime>=0.11.0, <0.12.0", "langgraph>=1.1.8, <2.0.0", "langchain-core>=1.2.27, <2.0.0", @@ -154,6 +154,9 @@ exclude_lines = [ [tool.uv] exclude-newer = "2 days" +# TEMP: consume the SDK PR #1728 dev build (uipath 2.11.x not yet on PyPI). +# Revert to range pins + drop tool.uv.sources when the SDK lands on PyPI. +override-dependencies = ["uipath-platform==0.1.74.dev1017286899"] [tool.uv.exclude-newer-package] uipath = false @@ -169,3 +172,9 @@ name = "testpypi" url = "https://test.pypi.org/simple/" publish-url = "https://test.pypi.org/legacy/" explicit = true + +# TEMP: pull uipath / uipath-platform from the SDK PR #1728 dev build on TestPyPI. +# Revert this section when the SDK lands on PyPI. +[tool.uv.sources] +uipath = { index = "testpypi" } +uipath-platform = { index = "testpypi" } diff --git a/uv.lock b/uv.lock index 0ac568d8a..fc1f61178 100644 --- a/uv.lock +++ b/uv.lock @@ -21,6 +21,9 @@ jsonschema-pydantic-converter = false uipath-langchain-client = false uipath-core = false +[manifest] +overrides = [{ name = "uipath-platform", specifier = "==0.1.74.dev1017286899", index = "https://test.pypi.org/simple/" }] + [[package]] name = "a2a-sdk" version = "0.3.26" @@ -4360,8 +4363,8 @@ wheels = [ [[package]] name = "uipath" -version = "2.10.79" -source = { registry = "https://pypi.org/simple" } +version = "2.11.10.dev1017286899" +source = { registry = "https://test.pypi.org/simple/" } dependencies = [ { name = "applicationinsights" }, { name = "click" }, @@ -4383,23 +4386,23 @@ dependencies = [ { name = "uipath-platform" }, { name = "uipath-runtime" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/6d/11/d9217e8be4a38414a41c0f03d269cb6fd0b68875a2da3c63c825fbf8ceee/uipath-2.10.79.tar.gz", hash = "sha256:6c5b9a7f55edf2e6ab7e2b09a676f9d4c76c602952470da02d3e2332e6b79b1c", size = 4434820, upload-time = "2026-06-09T06:49:52.867Z" } +sdist = { url = "https://test-files.pythonhosted.org/packages/ab/c8/2dec6c28365cc35c7e6e53b75e31c2b972e2456c2957ca2e586c815a5ff7/uipath-2.11.10.dev1017286899.tar.gz", hash = "sha256:39d22bd4b5e8aa1a7e9eaa74ad21739f694b25f556a9a3cfc8becad3559d89de", size = 4463454, upload-time = "2026-06-23T13:02:53.294Z" } wheels = [ - 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"uipath==2.11.10.dev1017286899", + "uipath>=2.10.79, <2.12.0", "uipath-core>=0.5.20, <0.6.0", - "uipath-platform==0.1.74.dev1017286899", + "uipath-platform>=0.1.71, <0.2.0", "uipath-runtime>=0.11.0, <0.12.0", "langgraph>=1.1.8, <2.0.0", "langchain-core>=1.2.27, <2.0.0", @@ -154,9 +154,6 @@ exclude_lines = [ [tool.uv] exclude-newer = "2 days" -# TEMP: consume the SDK PR #1728 dev build (uipath 2.11.x not yet on PyPI). -# Revert to range pins + drop tool.uv.sources when the SDK lands on PyPI. -override-dependencies = ["uipath-platform==0.1.74.dev1017286899"] [tool.uv.exclude-newer-package] uipath = false @@ -172,9 +169,3 @@ name = "testpypi" url = "https://test.pypi.org/simple/" publish-url = "https://test.pypi.org/legacy/" explicit = true - -# TEMP: pull uipath / uipath-platform from the SDK PR #1728 dev build on TestPyPI. -# Revert this section when the SDK lands on PyPI. -[tool.uv.sources] -uipath = { index = "testpypi" } -uipath-platform = { index = "testpypi" } diff --git a/tests/agent/tools/test_datafabric_ontology_subgraph.py b/tests/agent/tools/test_datafabric_ontology_subgraph.py index 43a5fdfbb..cf06b6287 100644 --- a/tests/agent/tools/test_datafabric_ontology_subgraph.py +++ b/tests/agent/tools/test_datafabric_ontology_subgraph.py @@ -9,7 +9,7 @@ import pytest from langchain_core.messages import AIMessage -from uipath_langchain.agent.tools.datafabric_tool import datafabric_subgraph as dsg +from uipath_langchain.agent.tools.datafabric_tool import datafabric_prompt_builder from uipath_langchain.agent.tools.datafabric_tool.datafabric_subgraph import ( DataFabricGraph, DataFabricSubgraphState, @@ -29,7 +29,7 @@ def entities_service(): @pytest.fixture def make_graph(monkeypatch, entities_service): # Isolate from the prompt builder; we only exercise tools/routing here. - monkeypatch.setattr(dsg.datafabric_prompt_builder, "build", lambda *a, **k: "SYS") + monkeypatch.setattr(datafabric_prompt_builder, "build", lambda *a, **k: "SYS") def _make(ontologies=None): return DataFabricGraph( @@ -124,7 +124,7 @@ async def test_execute_tool_call_sql_value_error_becomes_error_dict(make_graph): def test_create_returns_compiled_graph(monkeypatch, entities_service): - monkeypatch.setattr(dsg.datafabric_prompt_builder, "build", lambda *a, **k: "SYS") + monkeypatch.setattr(datafabric_prompt_builder, "build", lambda *a, **k: "SYS") compiled = DataFabricGraph.create( llm=MagicMock(), entities=[], diff --git a/tests/agent/tools/test_datafabric_tool_ontology_factory.py b/tests/agent/tools/test_datafabric_tool_ontology_factory.py index f11046a1c..2c514fc60 100644 --- a/tests/agent/tools/test_datafabric_tool_ontology_factory.py +++ b/tests/agent/tools/test_datafabric_tool_ontology_factory.py @@ -33,16 +33,16 @@ def _entity_resource(): def test_factory_passes_ontologies_through(): tool = create_datafabric_query_tool( - 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ontologies = resolve_context_ontologies( - resource, agent.resources if agent else [] - ) + ontologies = resolve_context_ontologies(resource) return create_datafabric_query_tool( resource, llm, diff --git a/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py b/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py index f6724a510..184a3767c 100644 --- a/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py +++ b/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py @@ -19,10 +19,7 @@ from langchain_core.messages import AIMessage, HumanMessage, ToolMessage from langchain_core.tools import BaseTool from langgraph.graph.state import CompiledStateGraph -from uipath.agent.models.agent import ( - AgentContextResourceConfig, - AgentOntologyResourceConfig, -) +from uipath.agent.models.agent import AgentContextResourceConfig from uipath.platform.entities import DataFabricEntityItem from ..base_uipath_structured_tool import BaseUiPathStructuredTool @@ -35,34 +32,15 @@ def resolve_context_ontologies( resource: AgentContextResourceConfig, - resources: list[Any], ) -> list[tuple[str, str | None]]: - """Resolve a context's ``ontology_refs`` to ``(name, folder_key)`` pairs. + """Map a context's nested ``ontology_set`` to ``(name, folder_key)`` pairs. - Ontologies are standalone ``AgentOntologyResourceConfig`` resources; a Data - Fabric context references them by name via ``ontology_refs``. Each ontology - carries its own ``folderId``, so it is resolved from its own folder. A - dangling reference (no matching ontology resource) is skipped with a warning - so it can never break tool creation. + Ontologies are configured inline on the Data Fabric context (alongside the + entity set) as ``ontologySet`` items. Each carries its own ``folderId``, so + it is fetched from its own folder. """ - refs = getattr(resource, "ontology_refs", None) or [] - if not refs: - return [] - by_name = { - r.name: r for r in resources if isinstance(r, AgentOntologyResourceConfig) - } - ontologies: list[tuple[str, str | None]] = [] - for ref in refs: - onto = by_name.get(ref) - if onto is None: - logger.warning( - "Context %r references unknown ontology %r; skipping.", - resource.name, - ref, - ) - continue - ontologies.append((onto.name, onto.folder_key)) - return ontologies + items = getattr(resource, "ontology_set", None) or [] + return [(item.name, item.folder_key) for item in items] class DataFabricTextQueryHandler: @@ -193,10 +171,9 @@ def create_datafabric_query_tool( agent_config: Optional dict with agent-level config. Key ``base_system_prompt`` carries the outer agent's system prompt. ontologies: ``(name, folder_key)`` pairs resolved from the context's - ``ontology_refs`` against the agent's standalone ontology resources - (see ``resolve_context_ontologies``). Empty/None → no fetch tool is - added. Resolution comes only from the agent definition (the binding), - never from process env. + nested ``ontology_set`` (see ``resolve_context_ontologies``). + Empty/None → no fetch tool is added. Resolution comes only from the + agent definition (the binding), never from process env. """ config = agent_config or {} entity_set = [ diff --git a/tests/agent/tools/test_datafabric_tool_ontology_factory.py b/tests/agent/tools/test_datafabric_tool_ontology_factory.py index 2c514fc60..4b2c72660 100644 --- a/tests/agent/tools/test_datafabric_tool_ontology_factory.py +++ b/tests/agent/tools/test_datafabric_tool_ontology_factory.py @@ -1,18 +1,14 @@ """Tests for ontology resolution + (name, folder) mapping in the DF tool factory. -Ontologies are standalone ``AgentOntologyResourceConfig`` resources; a Data -Fabric context references them by name via ``ontology_refs``. The caller -resolves those refs to ``(name, folder_key)`` pairs and passes them to the -factory. +Ontologies are configured inline on the Data Fabric context as a nested +``ontologySet`` (alongside the entity set). The caller resolves those items to +``(name, folder_key)`` pairs and passes them to the factory. """ from types import SimpleNamespace from unittest.mock import MagicMock -from uipath.agent.models.agent import ( - AgentContextResourceConfig, - AgentOntologyResourceConfig, -) +from uipath.agent.models.agent import AgentContextResourceConfig from uipath.platform.entities import DataFabricEntityItem from uipath_langchain.agent.tools.datafabric_tool.datafabric_tool import ( @@ -45,48 +41,34 @@ def test_factory_no_ontologies_is_empty(): assert tool.coroutine._ontologies == [] # type: ignore[attr-defined] -# --- resolver: ontology_refs → standalone ontology resources → (name, folder) --- +# --- resolver: nested ontologySet → (name, folder) pairs --- -def _ctx(ontology_refs): - return AgentContextResourceConfig.model_validate( - { - "$resourceType": "context", - "name": "TestDF", - "description": "", - "contextType": "datafabricentityset", - "ontologyRefs": ontology_refs, - } - ) +def _ctx(ontology_set): + config = { + "$resourceType": "context", + "name": "TestDF", + "description": "", + "contextType": "datafabricentityset", + } + if ontology_set is not None: + config["ontologySet"] = ontology_set + return AgentContextResourceConfig.model_validate(config) -def _onto(name, folder_id): - return AgentOntologyResourceConfig.model_validate( - { - "$resourceType": "ontology", - "name": name, - "description": "", - "folderId": folder_id, - } +def test_resolve_ontology_set_to_name_and_folder(): + ctx = _ctx( + [ + {"name": "library", "folderId": "f1"}, + {"name": "finance", "folderId": "f2", "referenceKey": "ont-2"}, + ] ) - - -def test_resolve_refs_to_name_and_folder(): - ctx = _ctx(["library", "finance"]) - resources = [ctx, _onto("library", "f1"), _onto("finance", "f2")] - assert resolve_context_ontologies(ctx, resources) == [ + assert resolve_context_ontologies(ctx) == [ ("library", "f1"), ("finance", "f2"), ] -def test_resolve_skips_dangling_ref(): - ctx = _ctx(["library", "missing"]) - resources = [ctx, _onto("library", "f1")] - # 'missing' has no matching ontology resource → skipped, not an error. - assert resolve_context_ontologies(ctx, resources) == [("library", "f1")] - - -def test_resolve_no_refs_is_empty(): +def test_resolve_no_ontology_set_is_empty(): ctx = _ctx(None) - assert resolve_context_ontologies(ctx, [ctx]) == [] + assert resolve_context_ontologies(ctx) == [] From 941f3ffe5b4dadb816117a4fa8693126c104c4a7 Mon Sep 17 00:00:00 2001 From: sankalp-uipath Date: Thu, 25 Jun 2026 23:45:28 +0530 Subject: [PATCH 13/13] refactor(datafabric): gather ontologies from datafabricontology context --- .../agent/tools/context_tool.py | 7 ++- .../tools/datafabric_tool/datafabric_tool.py | 23 ++++--- .../test_datafabric_tool_ontology_factory.py | 61 ++++++++++++------- 3 files changed, 61 insertions(+), 30 deletions(-) diff --git a/src/uipath_langchain/agent/tools/context_tool.py b/src/uipath_langchain/agent/tools/context_tool.py index 6ee17a935..af1061374 100644 --- a/src/uipath_langchain/agent/tools/context_tool.py +++ b/src/uipath_langchain/agent/tools/context_tool.py @@ -158,6 +158,11 @@ def create_context_tool( ) -> StructuredTool | BaseTool | None: tool_name = sanitize_tool_name(resource.name) + # An ontology context is not a standalone tool — it only grounds the Data + # Fabric entity tool, which gathers it via resolve_context_ontologies. + if resource.context_type == AgentContextType.DATA_FABRIC_ONTOLOGY: + return None + if resource.context_type == AgentContextType.DATA_FABRIC_ENTITY_SET: if llm is None: raise ValueError("Data Fabric entity set tools require an LLM instance") @@ -167,7 +172,7 @@ def create_context_tool( ) from .datafabric_tool.datafabric_tool import BASE_SYSTEM_PROMPT - ontologies = resolve_context_ontologies(resource) + ontologies = resolve_context_ontologies(agent.resources if agent else []) return create_datafabric_query_tool( resource, llm, diff --git a/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py b/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py index 184a3767c..359c7943f 100644 --- a/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py +++ b/src/uipath_langchain/agent/tools/datafabric_tool/datafabric_tool.py @@ -31,16 +31,25 @@ def resolve_context_ontologies( - resource: AgentContextResourceConfig, + resources: list[Any], ) -> list[tuple[str, str | None]]: - """Map a context's nested ``ontology_set`` to ``(name, folder_key)`` pairs. + """Gather ontologies from the agent's ontology context(s). - Ontologies are configured inline on the Data Fabric context (alongside the - entity set) as ``ontologySet`` items. Each carries its own ``folderId``, so - it is fetched from its own folder. + An ontology is configured in a dedicated ontology context (``contextType`` + ``datafabricontology``) whose ``ontologySet`` mirrors the entity context's + ``entitySet`` — by convention at most one such context per agent. Its + ontologies ground the Data Fabric query tool; each carries its own + ``folderId``, so it is fetched from its own folder. """ - items = getattr(resource, "ontology_set", None) or [] - return [(item.name, item.folder_key) for item in items] + ontologies: list[tuple[str, str | None]] = [] + for resource in resources: + if ( + isinstance(resource, AgentContextResourceConfig) + and resource.is_datafabric_ontology + ): + for item in resource.ontology_set or []: + ontologies.append((item.name, item.folder_key)) + return ontologies class DataFabricTextQueryHandler: diff --git a/tests/agent/tools/test_datafabric_tool_ontology_factory.py b/tests/agent/tools/test_datafabric_tool_ontology_factory.py index 4b2c72660..9455a7bd5 100644 --- a/tests/agent/tools/test_datafabric_tool_ontology_factory.py +++ b/tests/agent/tools/test_datafabric_tool_ontology_factory.py @@ -44,31 +44,48 @@ def test_factory_no_ontologies_is_empty(): # --- resolver: nested ontologySet → (name, folder) pairs --- -def _ctx(ontology_set): - config = { - "$resourceType": "context", - "name": "TestDF", - "description": "", - "contextType": "datafabricentityset", - } - if ontology_set is not None: - config["ontologySet"] = ontology_set - return AgentContextResourceConfig.model_validate(config) - - -def test_resolve_ontology_set_to_name_and_folder(): - ctx = _ctx( - [ - {"name": "library", "folderId": "f1"}, - {"name": "finance", "folderId": "f2", "referenceKey": "ont-2"}, - ] +def _entity_ctx(): + return AgentContextResourceConfig.model_validate( + { + "$resourceType": "context", + "name": "Entities", + "description": "", + "contextType": "datafabricentityset", + "entitySet": [{"id": "e1", "name": "LibraryLoan", "folderId": "f1"}], + } ) - assert resolve_context_ontologies(ctx) == [ + + +def _ontology_ctx(ontology_set): + return AgentContextResourceConfig.model_validate( + { + "$resourceType": "context", + "name": "Ontologies", + "description": "", + "contextType": "datafabricontology", + "ontologySet": ontology_set, + } + ) + + +def test_resolve_gathers_ontology_context_items(): + # The agent has an entity context + a dedicated ontology context; only the + # ontology context's items are gathered, each as (name, folder_key). + resources = [ + _entity_ctx(), + _ontology_ctx( + [ + {"name": "library", "folderId": "f1"}, + {"name": "finance", "folderId": "f2", "referenceKey": "ont-2"}, + ] + ), + ] + assert resolve_context_ontologies(resources) == [ ("library", "f1"), ("finance", "f2"), ] -def test_resolve_no_ontology_set_is_empty(): - ctx = _ctx(None) - assert resolve_context_ontologies(ctx) == [] +def test_resolve_no_ontology_context_is_empty(): + # Only an entity context, no ontology context → nothing to ground with. + assert resolve_context_ontologies([_entity_ctx()]) == []