Merge remote-tracking branch 'upstream/main' into strip-telem

src/llama_stack/apis/tools/rag_tool.py

@@ -5,18 +5,13 @@
 # the root directory of this source tree.
 
 from enum import Enum, StrEnum
-from typing import Annotated, Any, Literal, Protocol
+from typing import Annotated, Any, Literal
 
 from pydantic import BaseModel, Field, field_validator
-from typing_extensions import runtime_checkable
 
 from llama_stack.apis.common.content_types import URL, InterleavedContent
-from llama_stack.apis.common.tracing import trace_protocol
-from llama_stack.apis.version import LLAMA_STACK_API_V1
-from llama_stack.schema_utils import json_schema_type, register_schema, webmethod
 
 
-@json_schema_type
 class RRFRanker(BaseModel):
     """
     Reciprocal Rank Fusion (RRF) ranker configuration.
@@ -30,7 +25,6 @@ class RRFRanker(BaseModel):
     impact_factor: float = Field(default=60.0, gt=0.0)  # default of 60 for optimal performance
 
 
-@json_schema_type
 class WeightedRanker(BaseModel):
     """
     Weighted ranker configuration that combines vector and keyword scores.
@@ -55,10 +49,8 @@ Ranker = Annotated[
     RRFRanker | WeightedRanker,
     Field(discriminator="type"),
 ]
-register_schema(Ranker, name="Ranker")
 
 
-@json_schema_type
 class RAGDocument(BaseModel):
     """
     A document to be used for document ingestion in the RAG Tool.
@@ -75,7 +67,6 @@ class RAGDocument(BaseModel):
     metadata: dict[str, Any] = Field(default_factory=dict)
 
 
-@json_schema_type
 class RAGQueryResult(BaseModel):
     """Result of a RAG query containing retrieved content and metadata.
 
@@ -87,7 +78,6 @@ class RAGQueryResult(BaseModel):
     metadata: dict[str, Any] = Field(default_factory=dict)
 
 
-@json_schema_type
 class RAGQueryGenerator(Enum):
     """Types of query generators for RAG systems.
 
@@ -101,7 +91,6 @@ class RAGQueryGenerator(Enum):
     custom = "custom"
 
 
-@json_schema_type
 class RAGSearchMode(StrEnum):
     """
     Search modes for RAG query retrieval:
@@ -115,7 +104,6 @@ class RAGSearchMode(StrEnum):
     HYBRID = "hybrid"
 
 
-@json_schema_type
 class DefaultRAGQueryGeneratorConfig(BaseModel):
     """Configuration for the default RAG query generator.
 
@@ -127,7 +115,6 @@ class DefaultRAGQueryGeneratorConfig(BaseModel):
     separator: str = " "
 
 
-@json_schema_type
 class LLMRAGQueryGeneratorConfig(BaseModel):
     """Configuration for the LLM-based RAG query generator.
 
@@ -145,10 +132,8 @@ RAGQueryGeneratorConfig = Annotated[
     DefaultRAGQueryGeneratorConfig | LLMRAGQueryGeneratorConfig,
     Field(discriminator="type"),
 ]
-register_schema(RAGQueryGeneratorConfig, name="RAGQueryGeneratorConfig")
 
 
-@json_schema_type
 class RAGQueryConfig(BaseModel):
     """
     Configuration for the RAG query generation.
@@ -181,38 +166,3 @@ class RAGQueryConfig(BaseModel):
         if len(v) == 0:
             raise ValueError("chunk_template must not be empty")
         return v
-
-
-@runtime_checkable
-@trace_protocol
-class RAGToolRuntime(Protocol):
-    @webmethod(route="/tool-runtime/rag-tool/insert", method="POST", level=LLAMA_STACK_API_V1)
-    async def insert(
-        self,
-        documents: list[RAGDocument],
-        vector_store_id: str,
-        chunk_size_in_tokens: int = 512,
-    ) -> None:
-        """Index documents so they can be used by the RAG system.
-
-        :param documents: List of documents to index in the RAG system
-        :param vector_store_id: ID of the vector database to store the document embeddings
-        :param chunk_size_in_tokens: (Optional) Size in tokens for document chunking during indexing
-        """
-        ...
-
-    @webmethod(route="/tool-runtime/rag-tool/query", method="POST", level=LLAMA_STACK_API_V1)
-    async def query(
-        self,
-        content: InterleavedContent,
-        vector_store_ids: list[str],
-        query_config: RAGQueryConfig | None = None,
-    ) -> RAGQueryResult:
-        """Query the RAG system for context; typically invoked by the agent.
-
-        :param content: The query content to search for in the indexed documents
-        :param vector_store_ids: List of vector database IDs to search within
-        :param query_config: (Optional) Configuration parameters for the query operation
-        :returns: RAGQueryResult containing the retrieved content and metadata
-        """
-        ...

src/llama_stack/apis/tools/tools.py

@@ -16,8 +16,6 @@ from llama_stack.apis.resource import Resource, ResourceType
 from llama_stack.apis.version import LLAMA_STACK_API_V1
 from llama_stack.schema_utils import json_schema_type, webmethod
 
-from .rag_tool import RAGToolRuntime
-
 
 @json_schema_type
 class ToolDef(BaseModel):
@@ -195,8 +193,6 @@ class SpecialToolGroup(Enum):
 class ToolRuntime(Protocol):
     tool_store: ToolStore | None = None
 
-    rag_tool: RAGToolRuntime | None = None
-
     # TODO: This needs to be renamed once OPEN API generator name conflict issue is fixed.
     @webmethod(route="/tool-runtime/list-tools", method="GET", level=LLAMA_STACK_API_V1)
     async def list_runtime_tools(

src/llama_stack/cli/stack/run.py

@@ -253,7 +253,7 @@ class StackRun(Subcommand):
             )
             return
 
-        ui_dir = REPO_ROOT / "llama_stack" / "ui"
+        ui_dir = REPO_ROOT / "llama_stack_ui"
         logs_dir = Path("~/.llama/ui/logs").expanduser()
         try:
             # Create logs directory if it doesn't exist

src/llama_stack/core/routers/tool_runtime.py

@@ -8,14 +8,9 @@ from typing import Any
 
 from llama_stack.apis.common.content_types import (
     URL,
-    InterleavedContent,
 )
 from llama_stack.apis.tools import (
     ListToolDefsResponse,
-    RAGDocument,
-    RAGQueryConfig,
-    RAGQueryResult,
-    RAGToolRuntime,
     ToolRuntime,
 )
 from llama_stack.log import get_logger
@@ -26,36 +21,6 @@ logger = get_logger(name=__name__, category="core::routers")
 
 
 class ToolRuntimeRouter(ToolRuntime):
-    class RagToolImpl(RAGToolRuntime):
-        def __init__(
-            self,
-            routing_table: ToolGroupsRoutingTable,
-        ) -> None:
-            logger.debug("Initializing ToolRuntimeRouter.RagToolImpl")
-            self.routing_table = routing_table
-
-        async def query(
-            self,
-            content: InterleavedContent,
-            vector_store_ids: list[str],
-            query_config: RAGQueryConfig | None = None,
-        ) -> RAGQueryResult:
-            logger.debug(f"ToolRuntimeRouter.RagToolImpl.query: {vector_store_ids}")
-            provider = await self.routing_table.get_provider_impl("knowledge_search")
-            return await provider.query(content, vector_store_ids, query_config)
-
-        async def insert(
-            self,
-            documents: list[RAGDocument],
-            vector_store_id: str,
-            chunk_size_in_tokens: int = 512,
-        ) -> None:
-            logger.debug(
-                f"ToolRuntimeRouter.RagToolImpl.insert: {vector_store_id}, {len(documents)} documents, chunk_size={chunk_size_in_tokens}"
-            )
-            provider = await self.routing_table.get_provider_impl("insert_into_memory")
-            return await provider.insert(documents, vector_store_id, chunk_size_in_tokens)
-
     def __init__(
         self,
         routing_table: ToolGroupsRoutingTable,
@@ -63,11 +28,6 @@ class ToolRuntimeRouter(ToolRuntime):
         logger.debug("Initializing ToolRuntimeRouter")
         self.routing_table = routing_table
 
-        # HACK ALERT this should be in sync with "get_all_api_endpoints()"
-        self.rag_tool = self.RagToolImpl(routing_table)
-        for method in ("query", "insert"):
-            setattr(self, f"rag_tool.{method}", getattr(self.rag_tool, method))
-
     async def initialize(self) -> None:
         logger.debug("ToolRuntimeRouter.initialize")
         pass

src/llama_stack/core/server/routes.py

@@ -13,7 +13,6 @@ from aiohttp import hdrs
 from starlette.routing import Route
 
 from llama_stack.apis.datatypes import Api, ExternalApiSpec
-from llama_stack.apis.tools import RAGToolRuntime, SpecialToolGroup
 from llama_stack.core.resolver import api_protocol_map
 from llama_stack.schema_utils import WebMethod
 
@@ -25,33 +24,16 @@ RouteImpls = dict[str, PathImpl]
 RouteMatch = tuple[EndpointFunc, PathParams, str, WebMethod]
 
 
-def toolgroup_protocol_map():
-    return {
-        SpecialToolGroup.rag_tool: RAGToolRuntime,
-    }
-
-
 def get_all_api_routes(
     external_apis: dict[Api, ExternalApiSpec] | None = None,
 ) -> dict[Api, list[tuple[Route, WebMethod]]]:
     apis = {}
 
     protocols = api_protocol_map(external_apis)
-    toolgroup_protocols = toolgroup_protocol_map()
     for api, protocol in protocols.items():
         routes = []
         protocol_methods = inspect.getmembers(protocol, predicate=inspect.isfunction)
 
-        # HACK ALERT
-        if api == Api.tool_runtime:
-            for tool_group in SpecialToolGroup:
-                sub_protocol = toolgroup_protocols[tool_group]
-                sub_protocol_methods = inspect.getmembers(sub_protocol, predicate=inspect.isfunction)
-                for name, method in sub_protocol_methods:
-                    if not hasattr(method, "__webmethod__"):
-                        continue
-                    protocol_methods.append((f"{tool_group.value}.{name}", method))
-
         for name, method in protocol_methods:
             # Get all webmethods for this method (supports multiple decorators)
             webmethods = getattr(method, "__webmethods__", [])

src/llama_stack/core/stack.py

@@ -31,7 +31,7 @@ from llama_stack.apis.safety import Safety
 from llama_stack.apis.scoring import Scoring
 from llama_stack.apis.scoring_functions import ScoringFunctions
 from llama_stack.apis.shields import Shields
-from llama_stack.apis.tools import RAGToolRuntime, ToolGroups, ToolRuntime
+from llama_stack.apis.tools import ToolGroups, ToolRuntime
 from llama_stack.apis.vector_io import VectorIO
 from llama_stack.core.conversations.conversations import ConversationServiceConfig, ConversationServiceImpl
 from llama_stack.core.datatypes import Provider, SafetyConfig, StackRunConfig, VectorStoresConfig
@@ -78,7 +78,6 @@ class LlamaStack(
     Inspect,
     ToolGroups,
     ToolRuntime,
-    RAGToolRuntime,
     Files,
     Prompts,
     Conversations,

src/llama_stack/providers/inline/tool_runtime/rag/memory.py

@@ -27,7 +27,6 @@ from llama_stack.apis.tools import (
     RAGDocument,
     RAGQueryConfig,
     RAGQueryResult,
-    RAGToolRuntime,
     ToolDef,
     ToolGroup,
     ToolInvocationResult,
@@ -91,7 +90,7 @@ async def raw_data_from_doc(doc: RAGDocument) -> tuple[bytes, str]:
             return content_str.encode("utf-8"), "text/plain"
 
 
-class MemoryToolRuntimeImpl(ToolGroupsProtocolPrivate, ToolRuntime, RAGToolRuntime):
+class MemoryToolRuntimeImpl(ToolGroupsProtocolPrivate, ToolRuntime):
     def __init__(
         self,
         config: RagToolRuntimeConfig,