phoenix-oss/llama-stack-mirror
0
0
Fork 1
mirror of https://github.com/meta-llama/llama-stack.git synced 2025-10-04 12:07:34 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

fixes

Browse source
This commit is contained in:
Ashwin Bharambe 2025-09-30 21:06:40 -07:00
parent 139320e19f
commit a78f981dbb
7 changed files with 91 additions and 199 deletions
Download patch file Download diff file Expand all files Collapse all files

6
llama_stack/apis/tools/tools.py
View file

@ -48,14 +48,16 @@ class Tool(Resource):
:param type: Type of resource, always 'tool'
:param toolgroup_id: ID of the tool group this tool belongs to
:param description: Human-readable description of what the tool does
:param parameters: List of parameters this tool accepts
:param input_schema: JSON Schema for the tool's input parameters
:param output_schema: JSON Schema for the tool's output
:param metadata: (Optional) Additional metadata about the tool
"""
type: Literal[ResourceType.tool] = ResourceType.tool
toolgroup_id: str
description: str
parameters: list[ToolParameter]
input_schema: dict[str, Any] | None = None
output_schema: dict[str, Any] | None = None
metadata: dict[str, Any] | None = None

3
llama_stack/core/routing_tables/toolgroups.py
View file

@ -83,7 +83,8 @@ class ToolGroupsRoutingTable(CommonRoutingTableImpl, ToolGroups):
identifier=t.name,
toolgroup_id=toolgroup.identifier,
description=t.description or "",
parameters=t.parameters or [],
input_schema=t.input_schema,
output_schema=t.output_schema,
metadata=t.metadata,
provider_id=toolgroup.provider_id,
)

65
llama_stack/providers/inline/agents/meta_reference/responses/streaming.py
View file

@ -65,35 +65,10 @@ def convert_tooldef_to_chat_tool(tool_def):
from llama_stack.models.llama.datatypes import ToolDefinition
from llama_stack.providers.utils.inference.openai_compat import convert_tooldef_to_openai_tool
# Build JSON Schema from tool parameters
properties = {}
required = []
for param in tool_def.parameters:
param_schema = {
"type": param.parameter_type,
"description": param.description,
}
if param.default is not None:
param_schema["default"] = param.default
if param.items is not None:
param_schema["items"] = param.items
properties[param.name] = param_schema
if param.required:
required.append(param.name)
input_schema = {
"type": "object",
"properties": properties,
"required": required,
}
internal_tool_def = ToolDefinition(
tool_name=tool_def.name,
description=tool_def.description,
input_schema=input_schema,
input_schema=tool_def.input_schema,
)
return convert_tooldef_to_openai_tool(internal_tool_def)
@ -546,33 +521,10 @@ class StreamingResponseOrchestrator:
from llama_stack.providers.utils.inference.openai_compat import convert_tooldef_to_openai_tool
def make_openai_tool(tool_name: str, tool: Tool) -> ChatCompletionToolParam:
# Build JSON Schema from tool parameters
properties = {}
required = []
for param in tool.parameters:
param_schema = {
"type": param.parameter_type,
"description": param.description,
}
if param.default is not None:
param_schema["default"] = param.default
properties[param.name] = param_schema
if param.required:
required.append(param.name)
input_schema = {
"type": "object",
"properties": properties,
"required": required,
}
tool_def = ToolDefinition(
tool_name=tool_name,
description=tool.description,
input_schema=input_schema,
input_schema=tool.input_schema,
)
return convert_tooldef_to_openai_tool(tool_def)
@ -659,16 +611,11 @@ class StreamingResponseOrchestrator:
MCPListToolsTool(
name=t.name,
description=t.description,
input_schema={
input_schema=t.input_schema
or {
"type": "object",
"properties": {
p.name: {
"type": p.parameter_type,
"description": p.description,
}
for p in t.parameters
},
"required": [p.name for p in t.parameters if p.required],
"properties": {},
"required": [],
},
)
)

4
llama_stack/providers/inline/ios/inference/LocalInferenceImpl/SystemPrompts.swift
View file

@ -68,9 +68,7 @@ public class FunctionTagCustomToolGenerator {
{
"name": "{{t.tool_name}}",
"description": "{{t.description}}",
"parameters": {
"type": "dict",
"properties": { {{t.parameters}} }
"input_schema": { {{t.input_schema}} }
}
{{/let}}

19
llama_stack/providers/remote/inference/vllm/vllm.py
View file

@ -110,18 +110,6 @@ def _convert_to_vllm_tools_in_request(tools: list[ToolDefinition]) -> list[dict]
compat_tools = []
for tool in tools:
properties = {}
compat_required = []
if tool.parameters:
for tool_key, tool_param in tool.parameters.items():
properties[tool_key] = {"type": tool_param.param_type}
if tool_param.description:
properties[tool_key]["description"] = tool_param.description
if tool_param.default:
properties[tool_key]["default"] = tool_param.default
if tool_param.required:
compat_required.append(tool_key)
# The tool.tool_name can be a str or a BuiltinTool enum. If
# it's the latter, convert to a string.
tool_name = tool.tool_name
@ -133,10 +121,11 @@ def _convert_to_vllm_tools_in_request(tools: list[ToolDefinition]) -> list[dict]
"function": {
"name": tool_name,
"description": tool.description,
"parameters": {
"parameters": tool.input_schema
or {
"type": "object",
"properties": properties,
"required": compat_required,
"properties": {},
"required": [],
},
},
}