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lint fix and rename file search

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Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
This commit is contained in:
Francisco Javier Arceo 2025-10-24 20:24:03 -04:00
parent 2d9163529a
commit bb34e942d1
7 changed files with 26 additions and 25 deletions
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2
llama_stack/core/routers/tool_runtime.py
View file

@ -41,7 +41,7 @@ class ToolRuntimeRouter(ToolRuntime):
query_config: FileSearchConfig | None = None,
) -> FileSearchResult:
logger.debug(f"ToolRuntimeRouter.FileSearchToolImpl.query: {vector_store_ids}")
provider = await self.routing_table.get_provider_impl("knowledge_search")
provider = await self.routing_table.get_provider_impl("file_search")
return await provider.query(content, vector_store_ids, query_config)
async def insert(

2
llama_stack/core/routing_tables/toolgroups.py
View file

@ -18,7 +18,7 @@ logger = get_logger(name=__name__, category="core::routing_tables")
def parse_toolgroup_from_toolgroup_name_pair(toolgroup_name_with_maybe_tool_name: str) -> str | None:
# handle the funny case like "builtin::file_search/knowledge_search"
# handle the funny case like "builtin::file_search/file_search"
parts = toolgroup_name_with_maybe_tool_name.split("/")
if len(parts) == 2:
return parts[0]

4
llama_stack/providers/inline/agents/meta_reference/agent_instance.py
View file

@ -84,7 +84,7 @@ from .persistence import AgentPersistence
from .safety import SafetyException, ShieldRunnerMixin
TOOLS_ATTACHMENT_KEY_REGEX = re.compile(r"__tools_attachment__=(\{.*?\})")
MEMORY_QUERY_TOOL = "knowledge_search"
MEMORY_QUERY_TOOL = "file_search"
WEB_SEARCH_TOOL = "web_search"
RAG_TOOL_GROUP = "builtin::file_search"
@ -927,7 +927,7 @@ class ChatAgent(ShieldRunnerMixin):
"""Parse a toolgroup name into its components.
Args:
toolgroup_name: The toolgroup name to parse (e.g. "builtin::file_search/knowledge_search")
toolgroup_name: The toolgroup name to parse (e.g. "builtin::file_search/file_search")
Returns:
A tuple of (tool_type, tool_group, tool_name)

6
llama_stack/providers/inline/agents/meta_reference/responses/streaming.py
View file

@ -675,7 +675,7 @@ class StreamingResponseOrchestrator:
# Emit output_item.added event for the new function call
self.sequence_number += 1
is_mcp_tool = tool_call.function.name and tool_call.function.name in self.mcp_tool_to_server
if not is_mcp_tool and tool_call.function.name not in ["web_search", "knowledge_search"]:
if not is_mcp_tool and tool_call.function.name not in ["web_search", "file_search"]:
# for MCP tools (and even other non-function tools) we emit an output message item later
function_call_item = OpenAIResponseOutputMessageFunctionToolCall(
arguments="", # Will be filled incrementally via delta events
@ -900,7 +900,7 @@ class StreamingResponseOrchestrator:
id=matching_item_id,
status="in_progress",
)
elif tool_call.function.name == "knowledge_search":
elif tool_call.function.name == "file_search":
item = OpenAIResponseOutputMessageFileSearchToolCall(
id=matching_item_id,
status="in_progress",
@ -1019,7 +1019,7 @@ class StreamingResponseOrchestrator:
raise ValueError(f"Tool {tool_name} not found")
self.ctx.chat_tools.append(make_openai_tool(tool_name, tool))
elif input_tool.type == "file_search":
tool_name = "knowledge_search"
tool_name = "file_search"
tool = await self.tool_executor.tool_groups_api.get_tool(tool_name)
if not tool:
raise ValueError(f"Tool {tool_name} not found")

24
llama_stack/providers/inline/agents/meta_reference/responses/tool_executor.py
View file

@ -104,12 +104,12 @@ class ToolExecutor:
citation_files=result.metadata.get("citation_files") if result and result.metadata else None,
)
async def _execute_knowledge_search_via_vector_store(
async def _execute_file_search_via_vector_store(
self,
query: str,
response_file_search_tool: OpenAIResponseInputToolFileSearch,
) -> ToolInvocationResult:
"""Execute knowledge search using vector_stores.search API with filters support."""
"""Execute file search using vector_stores.search API with filters support."""
search_results = []
# Create search tasks for all vector stores
@ -139,7 +139,7 @@ class ToolExecutor:
content_items = []
content_items.append(
TextContentItem(
text=f"knowledge_search tool found {len(search_results)} chunks:\nBEGIN of knowledge_search tool results.\n"
text=f"file_search tool found {len(search_results)} chunks:\nBEGIN of file_search tool results.\n"
)
)
@ -158,7 +158,7 @@ class ToolExecutor:
content_items.append(TextContentItem(text=text_content))
unique_files.add(file_id)
content_items.append(TextContentItem(text="END of knowledge_search tool results.\n"))
content_items.append(TextContentItem(text="END of file_search tool results.\n"))
citation_instruction = ""
if unique_files:
@ -224,7 +224,7 @@ class ToolExecutor:
output_index=output_index,
sequence_number=sequence_number,
)
elif function_name == "knowledge_search":
elif function_name == "file_search":
sequence_number += 1
progress_event = OpenAIResponseObjectStreamResponseFileSearchCallInProgress(
item_id=item_id,
@ -246,7 +246,7 @@ class ToolExecutor:
yield ToolExecutionResult(stream_event=searching_event, sequence_number=sequence_number)
# For file search, emit searching event
if function_name == "knowledge_search":
if function_name == "file_search":
sequence_number += 1
searching_event = OpenAIResponseObjectStreamResponseFileSearchCallSearching(
item_id=item_id,
@ -283,17 +283,17 @@ class ToolExecutor:
tool_name=function_name,
kwargs=tool_kwargs,
)
elif function_name == "knowledge_search":
elif function_name == "file_search":
response_file_search_tool = next(
(t for t in ctx.response_tools if isinstance(t, OpenAIResponseInputToolFileSearch)),
None,
)
if response_file_search_tool:
# Use vector_stores.search API instead of knowledge_search tool
# Use vector_stores.search API instead of file_search tool
# to support filters and ranking_options
query = tool_kwargs.get("query", "")
async with tracing.span("knowledge_search", {}):
result = await self._execute_knowledge_search_via_vector_store(
async with tracing.span("file_search", {}):
result = await self._execute_file_search_via_vector_store(
query=query,
response_file_search_tool=response_file_search_tool,
)
@ -341,7 +341,7 @@ class ToolExecutor:
output_index=output_index,
sequence_number=sequence_number,
)
elif function_name == "knowledge_search":
elif function_name == "file_search":
sequence_number += 1
completion_event = OpenAIResponseObjectStreamResponseFileSearchCallCompleted(
item_id=item_id,
@ -395,7 +395,7 @@ class ToolExecutor:
)
if has_error:
message.status = "failed"
elif function.name == "knowledge_search":
elif function.name == "file_search":
message = OpenAIResponseOutputMessageFileSearchToolCall(
id=item_id,
queries=[tool_kwargs.get("query", "")],

8
llama_stack/providers/inline/tool_runtime/file_search/file_search.py
View file

@ -226,9 +226,7 @@ class FileSearchToolRuntimeImpl(ToolGroupsProtocolPrivate, ToolRuntime, FileSear
tokens = 0
picked: list[InterleavedContentItem] = [
TextContentItem(
text=f"knowledge_search tool found {len(chunks)} chunks:\nBEGIN of knowledge_search tool results.\n"
)
TextContentItem(text=f"file_search tool found {len(chunks)} chunks:\nBEGIN of file_search tool results.\n")
]
for i, chunk in enumerate(chunks):
metadata = chunk.metadata
@ -262,7 +260,7 @@ class FileSearchToolRuntimeImpl(ToolGroupsProtocolPrivate, ToolRuntime, FileSear
text_content = query_config.chunk_template.format(index=i + 1, chunk=chunk, metadata=metadata_for_context)
picked.append(TextContentItem(text=text_content))
picked.append(TextContentItem(text="END of knowledge_search tool results.\n"))
picked.append(TextContentItem(text="END of file_search tool results.\n"))
picked.append(
TextContentItem(
text=f'The above results were retrieved to help answer the user\'s query: "{interleaved_content_as_str(content)}". Use them as supporting information only in answering this query.\n',
@ -292,7 +290,7 @@ class FileSearchToolRuntimeImpl(ToolGroupsProtocolPrivate, ToolRuntime, FileSear
description="Insert documents into memory",
),
ToolDef(
name="knowledge_search",
name="file_search",
description="Search for information in a database.",
input_schema={
"type": "object",

5
llama_stack/ui/app/chat-playground/page.tsx
View file

@ -1167,7 +1167,10 @@ export default function ChatPlaygroundPage() {
// find RAG toolgroups that have vector_db_ids configured
const ragToolgroups = selectedAgentConfig.toolgroups.filter(toolgroup => {
if (typeof toolgroup === "object" && toolgroup.name?.includes("file_search")) {
if (
typeof toolgroup === "object" &&
toolgroup.name?.includes("file_search")
) {
return toolgroup.args && "vector_db_ids" in toolgroup.args;
}
return false;