mirror of
https://github.com/meta-llama/llama-stack.git
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314ee09ae3
llama-models should have extremely minimal cruft. Its sole purpose should be didactic -- show the simplest implementation of the llama models and document the prompt formats, etc. This PR is the complement to https://github.com/meta-llama/llama-models/pull/279 ## Test Plan Ensure all `llama` CLI `model` sub-commands work: ```bash llama model list llama model download --model-id ... llama model prompt-format -m ... ``` Ran tests: ```bash cd tests/client-sdk LLAMA_STACK_CONFIG=fireworks pytest -s -v inference/ LLAMA_STACK_CONFIG=fireworks pytest -s -v vector_io/ LLAMA_STACK_CONFIG=fireworks pytest -s -v agents/ ``` Create a fresh venv `uv venv && source .venv/bin/activate` and run `llama stack build --template fireworks --image-type venv` followed by `llama stack run together --image-type venv` <-- the server runs Also checked that the OpenAPI generator can run and there is no change in the generated files as a result. ```bash cd docs/openapi_generator sh run_openapi_generator.sh ```
230 lines
9.4 KiB
Python
230 lines
9.4 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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import importlib
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import os
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from collections import defaultdict
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from pathlib import Path
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from typing import Optional
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from urllib.parse import urlparse
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import pytest
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from metadata import API_MAPS
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from pytest import CollectReport
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from termcolor import cprint
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from llama_stack.models.llama.datatypes import CoreModelId
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from llama_stack.models.llama.sku_list import (
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all_registered_models,
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llama3_1_instruct_models,
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llama3_2_instruct_models,
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llama3_3_instruct_models,
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llama3_instruct_models,
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safety_models,
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)
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from llama_stack.providers.datatypes import Api
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from llama_stack.providers.tests.env import get_env_or_fail
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def featured_models():
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models = [
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*llama3_instruct_models(),
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*llama3_1_instruct_models(),
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*llama3_2_instruct_models(),
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*llama3_3_instruct_models(),
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*safety_models(),
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]
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return {model.huggingface_repo: model for model in models if not model.variant}
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SUPPORTED_MODELS = {
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"ollama": set(
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[
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CoreModelId.llama3_1_8b_instruct.value,
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CoreModelId.llama3_1_8b_instruct.value,
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CoreModelId.llama3_1_70b_instruct.value,
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CoreModelId.llama3_1_70b_instruct.value,
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CoreModelId.llama3_1_405b_instruct.value,
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CoreModelId.llama3_1_405b_instruct.value,
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CoreModelId.llama3_2_1b_instruct.value,
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CoreModelId.llama3_2_1b_instruct.value,
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CoreModelId.llama3_2_3b_instruct.value,
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CoreModelId.llama3_2_3b_instruct.value,
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CoreModelId.llama3_2_11b_vision_instruct.value,
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CoreModelId.llama3_2_11b_vision_instruct.value,
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CoreModelId.llama3_2_90b_vision_instruct.value,
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CoreModelId.llama3_2_90b_vision_instruct.value,
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CoreModelId.llama3_3_70b_instruct.value,
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CoreModelId.llama_guard_3_8b.value,
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CoreModelId.llama_guard_3_1b.value,
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]
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),
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"tgi": set([model.core_model_id.value for model in all_registered_models() if model.huggingface_repo]),
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"vllm": set([model.core_model_id.value for model in all_registered_models() if model.huggingface_repo]),
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}
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class Report:
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def __init__(self, report_path: Optional[str] = None):
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if os.environ.get("LLAMA_STACK_CONFIG"):
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config_path_or_template_name = get_env_or_fail("LLAMA_STACK_CONFIG")
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if config_path_or_template_name.endswith(".yaml"):
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config_path = Path(config_path_or_template_name)
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else:
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config_path = Path(
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importlib.resources.files("llama_stack") / f"templates/{config_path_or_template_name}/run.yaml"
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)
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if not config_path.exists():
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raise ValueError(f"Config file {config_path} does not exist")
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self.output_path = Path(config_path.parent / "report.md")
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self.distro_name = None
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elif os.environ.get("LLAMA_STACK_BASE_URL"):
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url = get_env_or_fail("LLAMA_STACK_BASE_URL")
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self.distro_name = urlparse(url).netloc
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if report_path is None:
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raise ValueError("Report path must be provided when LLAMA_STACK_BASE_URL is set")
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self.output_path = Path(report_path)
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else:
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raise ValueError("LLAMA_STACK_CONFIG or LLAMA_STACK_BASE_URL must be set")
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self.report_data = defaultdict(dict)
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# test function -> test nodeid
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self.test_data = dict()
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self.test_name_to_nodeid = defaultdict(list)
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self.vision_model_id = None
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self.text_model_id = None
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self.client = None
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@pytest.hookimpl(tryfirst=True)
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def pytest_runtest_logreport(self, report):
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# This hook is called in several phases, including setup, call and teardown
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# The test is considered failed / error if any of the outcomes is not "Passed"
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outcome = self._process_outcome(report)
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if report.nodeid not in self.test_data:
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self.test_data[report.nodeid] = outcome
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elif self.test_data[report.nodeid] != outcome and outcome != "Passed":
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self.test_data[report.nodeid] = outcome
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def pytest_sessionfinish(self, session):
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report = []
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report.append(f"# Report for {self.distro_name} distribution")
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report.append("\n## Supported Models")
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header = f"| Model Descriptor | {self.distro_name} |"
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dividor = "|:---|:---|"
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report.append(header)
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report.append(dividor)
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rows = []
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if self.distro_name in SUPPORTED_MODELS:
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for model in all_registered_models():
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if ("Instruct" not in model.core_model_id.value and "Guard" not in model.core_model_id.value) or (
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model.variant
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):
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continue
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row = f"| {model.core_model_id.value} |"
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if model.core_model_id.value in SUPPORTED_MODELS[self.distro_name]:
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row += " ✅ |"
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else:
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row += " ❌ |"
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rows.append(row)
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else:
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supported_models = {m.identifier for m in self.client.models.list()}
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for hf_name, model in featured_models().items():
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row = f"| {model.core_model_id.value} |"
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if hf_name in supported_models:
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row += " ✅ |"
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else:
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row += " ❌ |"
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rows.append(row)
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report.extend(rows)
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report.append("\n## Inference")
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test_table = [
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"| Model | API | Capability | Test | Status |",
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"|:----- |:-----|:-----|:-----|:-----|",
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]
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for api, capa_map in API_MAPS[Api.inference].items():
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for capa, tests in capa_map.items():
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for test_name in tests:
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model_id = self.text_model_id if "text" in test_name else self.vision_model_id
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test_nodeids = self.test_name_to_nodeid[test_name]
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assert len(test_nodeids) > 0
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# There might be more than one parametrizations for the same test function. We take
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# the result of the first one for now. Ideally we should mark the test as failed if
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# any of the parametrizations failed.
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test_table.append(
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f"| {model_id} | /{api} | {capa} | {test_name} | {self._print_result_icon(self.test_data[test_nodeids[0]])} |"
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)
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report.extend(test_table)
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name_map = {Api.vector_io: "Vector IO", Api.agents: "Agents"}
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providers = self.client.providers.list()
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for api_group in [Api.vector_io, Api.agents]:
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api_capitalized = name_map[api_group]
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report.append(f"\n## {api_capitalized}")
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test_table = [
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"| Provider | API | Capability | Test | Status |",
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"|:-----|:-----|:-----|:-----|:-----|",
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]
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provider = [p for p in providers if p.api == str(api_group.name)]
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provider_str = provider[0].provider_type if provider else ""
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for api, capa_map in API_MAPS[api_group].items():
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for capa, tests in capa_map.items():
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for test_name in tests:
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test_nodeids = self.test_name_to_nodeid[test_name]
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assert len(test_nodeids) > 0
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test_table.append(
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f"| {provider_str} | /{api} | {capa} | {test_name} | {self._print_result_icon(self.test_data[test_nodeids[0]])} |"
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)
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report.extend(test_table)
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output_file = self.output_path
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text = "\n".join(report) + "\n"
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output_file.write_text(text)
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cprint(f"\nReport generated: {output_file.absolute()}", "green")
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def pytest_runtest_makereport(self, item, call):
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func_name = getattr(item, "originalname", item.name)
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self.test_name_to_nodeid[func_name].append(item.nodeid)
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# Get values from fixtures for report output
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if "text_model_id" in item.funcargs:
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text_model = item.funcargs["text_model_id"].split("/")[1]
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self.text_model_id = self.text_model_id or text_model
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elif "vision_model_id" in item.funcargs:
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vision_model = item.funcargs["vision_model_id"].split("/")[1]
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self.vision_model_id = self.vision_model_id or vision_model
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if self.client is None and "llama_stack_client" in item.funcargs:
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self.client = item.funcargs["llama_stack_client"]
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self.distro_name = self.distro_name or self.client.async_client.config.image_name
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def _print_result_icon(self, result):
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if result == "Passed":
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return "✅"
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elif result == "Failed" or result == "Error":
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return "❌"
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else:
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# result == "Skipped":
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return "⏭️"
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def _process_outcome(self, report: CollectReport):
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if self._is_error(report):
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return "Error"
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if hasattr(report, "wasxfail"):
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if report.outcome in ["passed", "failed"]:
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return "XPassed"
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if report.outcome == "skipped":
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return "XFailed"
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return report.outcome.capitalize()
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def _is_error(self, report: CollectReport):
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return report.when in ["setup", "teardown", "collect"] and report.outcome == "failed"
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