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

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": [],
},
)
)