chore: Rename RagTool FileSearchTool

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

llama_stack/apis/tools/__init__.py

@@ -4,5 +4,5 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-from .rag_tool import *
+from .file_search_tool import *
 from .tools import *

llama_stack/apis/tools/file_search_tool.py

@@ -76,7 +76,7 @@ class RAGDocument(BaseModel):
 
 
 @json_schema_type
-class RAGQueryResult(BaseModel):
+class FileSearchResult(BaseModel):
     """Result of a RAG query containing retrieved content and metadata.
 
     :param content: (Optional) The retrieved content from the query
@@ -88,7 +88,7 @@ class RAGQueryResult(BaseModel):
 
 
 @json_schema_type
-class RAGQueryGenerator(Enum):
+class FileSearchGenerator(Enum):
     """Types of query generators for RAG systems.
 
     :cvar default: Default query generator using simple text processing
@@ -102,7 +102,7 @@ class RAGQueryGenerator(Enum):
 
 
 @json_schema_type
-class RAGSearchMode(StrEnum):
+class FileSearchMode(StrEnum):
     """
     Search modes for RAG query retrieval:
     - VECTOR: Uses vector similarity search for semantic matching
@@ -116,7 +116,7 @@ class RAGSearchMode(StrEnum):
 
 
 @json_schema_type
-class DefaultRAGQueryGeneratorConfig(BaseModel):
+class DefaultFileSearchGeneratorConfig(BaseModel):
     """Configuration for the default RAG query generator.
 
     :param type: Type of query generator, always 'default'
@@ -128,8 +128,8 @@ class DefaultRAGQueryGeneratorConfig(BaseModel):
 
 
 @json_schema_type
-class LLMRAGQueryGeneratorConfig(BaseModel):
-    """Configuration for the LLM-based RAG query generator.
+class LLMFileSearchGeneratorConfig(BaseModel):
+    """Configuration for the LLM-based File Search generator.
 
     :param type: Type of query generator, always 'llm'
     :param model: Name of the language model to use for query generation
@@ -141,15 +141,15 @@ class LLMRAGQueryGeneratorConfig(BaseModel):
     template: str
 
 
-RAGQueryGeneratorConfig = Annotated[
-    DefaultRAGQueryGeneratorConfig | LLMRAGQueryGeneratorConfig,
+FileSearchGeneratorConfig = Annotated[
+    DefaultFileSearchGeneratorConfig | LLMFileSearchGeneratorConfig,
     Field(discriminator="type"),
 ]
-register_schema(RAGQueryGeneratorConfig, name="RAGQueryGeneratorConfig")
+register_schema(FileSearchGeneratorConfig, name="FileSearchGeneratorConfig")
 
 
 @json_schema_type
-class RAGQueryConfig(BaseModel):
+class FileSearchConfig(BaseModel):
     """
     Configuration for the RAG query generation.
 
@@ -165,11 +165,11 @@ class RAGQueryConfig(BaseModel):
 
     # This config defines how a query is generated using the messages
     # for memory bank retrieval.
-    query_generator_config: RAGQueryGeneratorConfig = Field(default=DefaultRAGQueryGeneratorConfig())
+    query_generator_config: FileSearchGeneratorConfig = Field(default=DefaultFileSearchGeneratorConfig())
     max_tokens_in_context: int = 4096
     max_chunks: int = 5
     chunk_template: str = "Result {index}\nContent: {chunk.content}\nMetadata: {metadata}\n"
-    mode: RAGSearchMode | None = RAGSearchMode.VECTOR
+    mode: FileSearchMode | None = FileSearchMode.VECTOR
     ranker: Ranker | None = Field(default=None)  # Only used for hybrid mode
 
     @field_validator("chunk_template")
@@ -185,8 +185,8 @@ class RAGQueryConfig(BaseModel):
 
 @runtime_checkable
 @trace_protocol
-class RAGToolRuntime(Protocol):
-    @webmethod(route="/tool-runtime/rag-tool/insert", method="POST", level=LLAMA_STACK_API_V1)
+class FileSearchToolRuntime(Protocol):
+    @webmethod(route="/tool-runtime/file_search-tool/insert", method="POST", level=LLAMA_STACK_API_V1)
     async def insert(
         self,
         documents: list[RAGDocument],
@@ -201,18 +201,18 @@ class RAGToolRuntime(Protocol):
         """
         ...
 
-    @webmethod(route="/tool-runtime/rag-tool/query", method="POST", level=LLAMA_STACK_API_V1)
+    @webmethod(route="/tool-runtime/file_search-tool/query", method="POST", level=LLAMA_STACK_API_V1)
     async def query(
         self,
         content: InterleavedContent,
         vector_db_ids: list[str],
-        query_config: RAGQueryConfig | None = None,
-    ) -> RAGQueryResult:
+        query_config: FileSearchConfig | None = None,
+    ) -> FileSearchResult:
         """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_db_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
+        :returns: FileSearchResult containing the retrieved content and metadata
         """
         ...

llama_stack/apis/tools/tools.py

@@ -16,7 +16,7 @@ from llama_stack.apis.version import LLAMA_STACK_API_V1
 from llama_stack.core.telemetry.trace_protocol import trace_protocol
 from llama_stack.schema_utils import json_schema_type, webmethod
 
-from .rag_tool import RAGToolRuntime
+from .file_search_tool import FileSearchToolRuntime
 
 
 @json_schema_type
@@ -195,7 +195,7 @@ class SpecialToolGroup(Enum):
 class ToolRuntime(Protocol):
     tool_store: ToolStore | None = None
 
-    rag_tool: RAGToolRuntime | None = None
+    rag_tool: FileSearchToolRuntime | 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)