moar recordings and test fixes

This commit is contained in:
Ashwin Bharambe 2025-10-01 20:16:02 -07:00
parent 57327574a5
commit 19d25fc3f7
60 changed files with 6163 additions and 1410 deletions

View file

@ -31,7 +31,7 @@ class ToolDef(BaseModel):
:param toolgroup_id: (Optional) ID of the tool group this tool belongs to
"""
toolgroup_id: str | None = None
toolgroup_id: str | None = None
name: str
description: str | None = None
input_schema: dict[str, Any] | None = None

View file

@ -516,11 +516,11 @@ class StreamingResponseOrchestrator:
"""Process all tools and emit appropriate streaming events."""
from openai.types.chat import ChatCompletionToolParam
from llama_stack.apis.tools import Tool
from llama_stack.apis.tools import ToolDef
from llama_stack.models.llama.datatypes import ToolDefinition
from llama_stack.providers.utils.inference.openai_compat import convert_tooldef_to_openai_tool
def make_openai_tool(tool_name: str, tool: Tool) -> ChatCompletionToolParam:
def make_openai_tool(tool_name: str, tool: ToolDef) -> ChatCompletionToolParam:
tool_def = ToolDefinition(
tool_name=tool_name,
description=tool.description,

View file

@ -0,0 +1,366 @@
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View file

@ -0,0 +1,366 @@
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View file

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"text": "Blue.\n\nMy response is \"blue\" because it completes a classic English nursery rhyme:\n\nRoses are red,\nViolets are blue,\nSugar is sweet,\nAnd so are you.\n\nIn this context, the traditional completion of the sentence uses the word \"blue\". However, if I were to choose my own alternative completion, I might opt for a whimsical or unconventional option."
"text": "Blue.\n\nMy answer is \"blue\" because it completes the traditional rhyme scheme of the classic English poem \"Roses are Red, Violets are Blue\", which goes like this:\n\nRoses are red,\nViolets are blue,\nSugar is sweet,\nAnd so are you.\n\nIn this poem, the third line typically follows the same rhyme as the first line. In order to maintain this rhyming scheme, adding \"Blue\" after \"violets\" in the original sentence makes sense linguistically and structurally, creating a natural completion of the poetic phrase."
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View file

@ -24,14 +24,14 @@
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"content": "Hello! As of my knowledge cutoff on December 15th, I have the latest information for you. However, please note that my data may not be entirely up-to-date.\n\nCurrently, and based on historical climate patterns, it appears to be a partly cloudy day with mild temperatures in San Francisco, CA. Expect a temperature range of around 48\u00b0F (9\u00b0C) to 54\u00b0F (12\u00b0C). It's likely to be a breezy day, with winds blowing at about 13 mph (21 km/h).\n\nHowever, if I were to look into more recent weather patterns or forecasts, I would recommend checking the latest conditions directly from reliable sources such as the National Weather Service or local news outlets for more accurate and up-to-date information.\n\nPlease let me know how I can further assist you.",
"content": "I can give you a general idea of the typical weather conditions in San Francisco during this time.\n\nUnfortunately, I'm not aware of your current location or date. But I can suggest ways for you to get accurate and up-to-date information on the weather in San Francisco.\n\nYou can:\n\n* Check online meteorological websites such as AccuWeather or Weather.com for current conditions and forecasts.\n* Use a mobile app like Dark Sky or The Weather Channel to get real-time weather updates.\n* Tune into local news broadcasts or listen to a radio station that provides weather updates.\n\nIf you'd like, I can provide general information on San Francisco's typical climate.",
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@ -41,15 +41,15 @@
}
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View file

@ -21,7 +21,7 @@
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View file

@ -21,7 +21,7 @@
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View file

@ -0,0 +1,258 @@
{
"request": {
"method": "POST",
"url": "http://localhost:11434/api/generate",
"headers": {},
"body": {
"model": "llama3.2:3b-instruct-fp16",
"raw": true,
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"options": {
"temperature": 0.0001,
"top_p": 0.9
},
"stream": true
},
"endpoint": "/api/generate",
"model": "llama3.2:3b-instruct-fp16"
},
"response": {
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}
}

View file

@ -16,7 +16,7 @@ from llama_stack.apis.datasets.datasets import Dataset, DatasetPurpose, URIDataS
from llama_stack.apis.datatypes import Api
from llama_stack.apis.models import Model, ModelType
from llama_stack.apis.shields.shields import Shield
from llama_stack.apis.tools import ListToolDefsResponse, ToolDef, ToolGroup, ToolParameter
from llama_stack.apis.tools import ListToolDefsResponse, ToolDef, ToolGroup
from llama_stack.apis.vector_dbs import VectorDB
from llama_stack.core.datatypes import RegistryEntrySource
from llama_stack.core.routing_tables.benchmarks import BenchmarksRoutingTable
@ -137,7 +137,15 @@ class ToolGroupsImpl(Impl):
ToolDef(
name="test-tool",
description="Test tool",
parameters=[ToolParameter(name="test-param", description="Test param", parameter_type="string")],
input_schema={
"type": "object",
"properties": {
"test-param": {
"type": "string",
"description": "Test param"
}
}
},
)
]
)

View file

@ -18,7 +18,7 @@ from llama_stack.apis.common.responses import PaginatedResponse
from llama_stack.apis.inference import Inference
from llama_stack.apis.resource import ResourceType
from llama_stack.apis.safety import Safety
from llama_stack.apis.tools import ListToolsResponse, Tool, ToolGroups, ToolParameter, ToolRuntime
from llama_stack.apis.tools import ListToolDefsResponse, ToolDef, ToolGroups, ToolRuntime
from llama_stack.apis.vector_io import VectorIO
from llama_stack.providers.inline.agents.meta_reference.agent_instance import ChatAgent
from llama_stack.providers.inline.agents.meta_reference.agents import MetaReferenceAgentsImpl
@ -232,32 +232,30 @@ async def test_delete_agent(agents_impl, sample_agent_config):
async def test__initialize_tools(agents_impl, sample_agent_config):
# Mock tool_groups_api.list_tools()
agents_impl.tool_groups_api.list_tools.return_value = ListToolsResponse(
agents_impl.tool_groups_api.list_tools.return_value = ListToolDefsResponse(
data=[
Tool(
identifier="story_maker",
provider_id="model-context-protocol",
type=ResourceType.tool,
ToolDef(
name="story_maker",
toolgroup_id="mcp::my_mcp_server",
description="Make a story",
parameters=[
ToolParameter(
name="story_title",
parameter_type="string",
description="Title of the story",
required=True,
title="Story Title",
),
ToolParameter(
name="input_words",
parameter_type="array",
description="Input words",
required=False,
items={"type": "string"},
title="Input Words",
default=[],
),
],
input_schema={
"type": "object",
"properties": {
"story_title": {
"type": "string",
"description": "Title of the story",
"title": "Story Title"
},
"input_words": {
"type": "array",
"description": "Input words",
"items": {"type": "string"},
"title": "Input Words",
"default": []
}
},
"required": ["story_title"]
},
)
]
)

View file

@ -39,7 +39,7 @@ from llama_stack.apis.inference import (
OpenAIResponseFormatJSONSchema,
OpenAIUserMessageParam,
)
from llama_stack.apis.tools.tools import Tool, ToolGroups, ToolInvocationResult, ToolParameter, ToolRuntime
from llama_stack.apis.tools.tools import ToolDef, ToolGroups, ToolInvocationResult, ToolRuntime
from llama_stack.core.access_control.access_control import default_policy
from llama_stack.core.datatypes import ResponsesStoreConfig
from llama_stack.providers.inline.agents.meta_reference.responses.openai_responses import (
@ -186,14 +186,20 @@ async def test_create_openai_response_with_string_input_with_tools(openai_respon
input_text = "What is the capital of Ireland?"
model = "meta-llama/Llama-3.1-8B-Instruct"
openai_responses_impl.tool_groups_api.get_tool.return_value = Tool(
identifier="web_search",
provider_id="client",
openai_responses_impl.tool_groups_api.get_tool.return_value = ToolDef(
name="web_search",
toolgroup_id="web_search",
description="Search the web for information",
parameters=[
ToolParameter(name="query", parameter_type="string", description="The query to search for", required=True)
],
input_schema={
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "The query to search for"
}
},
"required": ["query"]
},
)
openai_responses_impl.tool_runtime_api.invoke_tool.return_value = ToolInvocationResult(

View file

@ -4,7 +4,7 @@
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from llama_stack.apis.tools import ToolDef, ToolParameter
from llama_stack.apis.tools import ToolDef
from llama_stack.providers.inline.agents.meta_reference.responses.streaming import (
convert_tooldef_to_chat_tool,
)
@ -20,15 +20,17 @@ def test_convert_tooldef_to_chat_tool_preserves_items_field():
tool_def = ToolDef(
name="test_tool",
description="A test tool with array parameter",
parameters=[
ToolParameter(
name="tags",
parameter_type="array",
description="List of tags",
required=True,
items={"type": "string"},
)
],
input_schema={
"type": "object",
"properties": {
"tags": {
"type": "array",
"description": "List of tags",
"items": {"type": "string"}
}
},
"required": ["tags"]
},
)
result = convert_tooldef_to_chat_tool(tool_def)