diff --git a/.github/workflows/code_checks.yml b/.github/workflows/code_checks.yml index 8891144..1adcaeb 100644 --- a/.github/workflows/code_checks.yml +++ b/.github/workflows/code_checks.yml @@ -59,9 +59,7 @@ jobs: # has an issue with tests: # https://github.com/streamlit/streamlit/issues/12566 # GHSA-5239-wwwm-4pmq: issue with pygments 2.19.12 that can't be upgraded because it breaks the docs build - # PYSEC-2026-2132: Click cannot be upgraded to 8.3.3 because of inspectai ignore-vulns: | GHSA-7p48-42j8-8846 GHSA-5239-wwwm-4pmq PYSEC-2026-212 - PYSEC-2026-2132 diff --git a/.gitignore b/.gitignore index bd1085b..bac052e 100644 --- a/.gitignore +++ b/.gitignore @@ -9,6 +9,9 @@ wheels/ # Virtual environments .venv +# Spec / task skill local state +.specs_skill_state/ + # Lint & Test .mypy_cache/ .pytest_cache/ diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 492e686..4213167 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -85,10 +85,17 @@ endpoint that takes a form data with the following fields: - An `api_key` to access the models - A file upload `systematized_concepts_file`, which can be downloaded after answering all the questions from the main app. -- (Optional) The model to use for the evaluation. Default is `openai/gpt-4o`. Possible values -are `openai/gpt-4o`, `openai/gpt-5.5`, `openai/gpt-5.4-mini`, `google/gemini-3.1-pro-preview`, -`google/gemini-3-flash-preview`, `google/gemini-3.1-flash-lite`, `anthropic/claude-opus-4-7`, -`anthropic/claude-sonnet-4-6` and `anthropic/claude-haiku-4-5-20251001`. +- (Optional) The model to use for the evaluation. Default is `gpt-4o`. Possible values +are `gpt-4o`, `gpt-5.5`, `gpt-5.4-mini`, `gemini-3.1-pro-preview`, +`gemini-3-flash-preview`, `claude-opus-4-7`, and `claude-sonnet-4-6`. To see the full documentation for the available endpoints, you can access `http://localhost:8000/docs` on your browser. + +### 🔑 LLM API keys (Vector proxy) + +LLM calls go through Vector's OpenAI-compatible proxy at +`https://proxy.vectorinstitute.ai/v1`. Use a Vector proxy API key when prompted in the +UI/API (`api_key`). For local manual tests, set `ASPIS_API_KEY` or `OPENAI_API_KEY` to +that proxy key. Do not rely on writing provider keys into the process environment for +request auth. diff --git a/README.md b/README.md index 5e72c40..67a4eed 100644 --- a/README.md +++ b/README.md @@ -85,10 +85,15 @@ endpoint that takes a form data with the following fields: - An `api_key` to access the models - A file upload `systematized_concepts_file`, which can be downloaded after answering all the questions from the main app. -- (Optional) The model to use for the evaluation. Default is `openai/gpt-4o`. Possible values -are `openai/gpt-4o`, `openai/gpt-5.5`, `openai/gpt-5.4-mini`, `google/gemini-3.1-pro-preview`, -`google/gemini-3-flash-preview`, `google/gemini-3.1-flash-lite`, `anthropic/claude-opus-4-7`, -`anthropic/claude-sonnet-4-6` and `anthropic/claude-haiku-4-5-20251001`. +- (Optional) The model to use for the evaluation. Default is `gpt-4o`. Possible values +are `gpt-4o`, `gpt-5.5`, `gpt-5.4-mini`, `gemini-3.1-pro-preview`, +`gemini-3-flash-preview`, `claude-opus-4-7`, and `claude-sonnet-4-6`. To see the full documentation for the available endpoints, you can access `http://localhost:8080/api/docs` on your browser. + +### 🔑 LLM API keys (Vector proxy) + +LLM calls are routed through Vector's OpenAI-compatible proxy at +`https://proxy.vectorinstitute.ai/v1`. Pass a Vector proxy API key as `api_key` in the +UI or API (not a provider-specific key written into process environment variables). diff --git a/plans/2026-08-10-replace-inspectai-with-openai-proxy.md b/plans/2026-08-10-replace-inspectai-with-openai-proxy.md new file mode 100644 index 0000000..1245735 --- /dev/null +++ b/plans/2026-08-10-replace-inspectai-with-openai-proxy.md @@ -0,0 +1,71 @@ +# Plan: Replace InspectAI with OpenAI SDK via Vector Proxy + +**Date:** 2026-08-10 +**Branch:** `replace-inspectai-with-openai-proxy` +**Status:** complete + +## Goal + +Replace InspectAI-based LLM calls with the official OpenAI SDK, routed through `https://proxy.vectorinstitute.ai/v1`, while keeping multi-provider models and safe concurrent API-key handling. + +## Decisions (from clarification) + +1. **Multi-provider:** Keep Gemini/Claude/OpenAI models; the Vector proxy supports all of them via the OpenAI-compatible API. +2. **Auth:** Keep the existing pattern of passing `api_key` into call sites (UI/API). Do **not** write keys into process `os.environ` (unsafe under concurrency). Prefer per-call `OpenAI(api_key=..., base_url=...)` clients. +3. **Client:** Official `openai` SDK (not `langchain-openai`). +4. **Threading:** Remove `ThreadPoolExecutor` unless verification shows Streamlit still requires it. The old thread pool existed for InspectAI + Streamlit main-thread issues. +5. **Lockfile:** After `pyproject.toml` dependency changes, regenerate `uv.lock` with `uv` (e.g. `uv lock` / `uv sync`). **Never hand-edit `uv.lock`.** + +## Steps + +### 1. Branch + +- Work on `replace-inspectai-with-openai-proxy` (created from `main`). + +### 2. New LLM client layer (`inferencer.py` core) + +- Add an OpenAI client factory that always creates a **new per-call client**: + - `OpenAI(api_key=, base_url="https://proxy.vectorinstitute.ai/v1")` + - Never set `os.environ` for keys. +- Replace InspectAI `Task` / `eval` / `generate` / `model_graded_qa` with `client.chat.completions.create(...)`. +- Replace InspectAI `Sample` inputs with prompt strings. +- Keep `ModelInfo` and multi-provider model IDs; send those model IDs to the proxy. +- Adapt `extract_string_output` to OpenAI response content shapes as needed. +- Drop `ThreadPoolExecutor` if direct sync OpenAI calls are safe with Streamlit. + +### 3. Call sites / API surface + +- Update `systematization.py`, API, UI, and helpers for the new sample/client path. +- Preserve “pass `api_key` into the function” from UI form + API form. + +### 4. Dependencies + +- Add official `openai` SDK. +- Remove `inspect-ai`. +- Remove now-unused provider SDKs only if nothing else imports them after the switch (`anthropic`, `google-genai` are candidates to audit). +- Regenerate `uv.lock` via `uv` from `pyproject.toml` changes (no manual lock edits). +- Update CI notes that mention InspectAI (e.g. click pin comment in code checks). + +### 5. Tests + +- Rewrite tests that mock `inspect_ai_eval` to mock the OpenAI client instead. +- Remove InspectAI imports from tests. +- Cover that API keys are passed into the client constructor (not env), so concurrent calls cannot share/override keys. + +### 6. Docs / misc + +- Light README/CONTRIBUTING updates if they describe InspectAI or key setup incorrectly. +- Leave `.env` alone (secrets); wire default base URL in code (optional non-secret env override if useful). + +### 7. Quality gate + +- Coding agent implements + runs project checks/tests. +- Separate code-review agent reviews. +- Commit only after a clean review. +- Verify clean `git status` and summarize. + +## Non-goals + +- No InspectAI proxy workaround. +- No shared global client / env-based key for request auth. +- No full project re-spec; this is a `/spec task`. diff --git a/pyproject.toml b/pyproject.toml index d3b8cfc..d808b75 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -7,12 +7,9 @@ authors = [ {name = "Vector AI Engineering", email = "ai_engineering@vectorinsti license = "Apache-2.0" requires-python = ">=3.12" dependencies = [ - "anthropic>=0.102.0", "fastapi[standard]>=0.121.0", - "google-genai>=2.2.0", - "inspect-ai>=0.3.160", "langchain>=1.3.9", - "langchain-openai>=1.1.14", + "openai>=1.40.0", "pydantic>=2.11.7", "pyyaml>=6.0.2", "streamlit>=1.48.1", diff --git a/src/aspis/api/main.py b/src/aspis/api/main.py index 755c9fe..8e1e206 100644 --- a/src/aspis/api/main.py +++ b/src/aspis/api/main.py @@ -1,5 +1,6 @@ """Functions for the programmatic API of the Aspis application.""" +import asyncio import datetime from typing import Any @@ -45,11 +46,10 @@ async def evaluate( text_to_evaluate: The text to evaluate. api_key: The API key to use to connect to the model. model: The model to use for this evaluation. Optional, - defaults to `openai/gpt-4o`. Allowed values are `openai/gpt-4o`, - `openai/gpt-5.5`, `openai/gpt-5.4-mini`, `google/gemini-3.1-pro-preview`, - `google/gemini-3-flash-preview`, `google/gemini-3.1-flash-lite`, - `anthropic/claude-opus-4-7`, `anthropic/claude-sonnet-4-6` - and `anthropic/claude-haiku-4-5-20251001`. + defaults to `gpt-4o`. Allowed values are `gpt-4o`, + `gpt-5.5`, `gpt-5.4-mini`, `gemini-3.1-pro-preview`, + `gemini-3-flash-preview`, `claude-opus-4-7`, and + `claude-sonnet-4-6`. systematized_concepts_file: The file containing the systematized concepts. It must be a `.yaml` file that contains a `systematized_concepts` key with a list of systematized concepts. Each systematized concept must @@ -87,7 +87,8 @@ async def evaluate( logger.info("%s: Evaluating input text against all concepts...", datetime.datetime.now()) - results = evaluate_text(text_to_evaluate, prompt_templates, model, api_key) + # Offload the synchronous OpenAI SDK call so the event loop stays responsive. + results = await asyncio.to_thread(evaluate_text, text_to_evaluate, prompt_templates, model, api_key) evaluation_responses = [] for i in range(len(systematized_concepts)): diff --git a/src/aspis/inferencer.py b/src/aspis/inferencer.py index 88ec41a..4d2b4bd 100644 --- a/src/aspis/inferencer.py +++ b/src/aspis/inferencer.py @@ -1,25 +1,21 @@ -"""Scorer for applications using Aspis as anLLM-as-a-judge.""" +"""Scorer for applications using Aspis as an LLM-as-a-judge.""" import json import os -from concurrent.futures import ThreadPoolExecutor from enum import Enum -from tempfile import TemporaryDirectory -from threading import Lock from typing import Any, Self -from inspect_ai import Task -from inspect_ai import eval as inspect_ai_eval -from inspect_ai.dataset import MemoryDataset, Sample -from inspect_ai.log import EvalLog -from inspect_ai.scorer import model_graded_qa -from inspect_ai.solver import generate +from openai import OpenAI -from aspis.logging import get_logger_level, logger +from aspis.logging import logger from aspis.utils import clean_model_output -_INSPECTAI_EVAL_LOCK = Lock() +DEFAULT_PROXY_BASE_URL = "https://proxy.vectorinstitute.ai/v1" +DEFAULT_OPENAI_TIMEOUT_SECONDS = 120.0 + +# Content part types that are reasoning / thinking (not the final answer). +_REASONING_PART_TYPES = frozenset({"reasoning", "thinking", "reasoning_content"}) class ModelInfo(str, Enum): @@ -27,31 +23,16 @@ class ModelInfo(str, Enum): model_id: str friendly_name: str - api_key_name: str - - OPENAI_GPT_4O = ("openai/gpt-4o", "GPT-4o (OpenAI)", "OPENAI_API_KEY") - OPENAI_GPT_5_5 = ("openai/gpt-5.5", "GPT-5.5 (OpenAI)", "OPENAI_API_KEY") - OPENAI_GPT_5_4_MINI = ("openai/gpt-5.4-mini", "GPT-5.4-mini (OpenAI)", "OPENAI_API_KEY") - GOOGLE_GEMINI_3_1_PRO_PREVIEW = ( - "google/gemini-3.1-pro-preview", - "Gemini 3.1 Pro Preview (Google)", - "GOOGLE_API_KEY", - ) - GOOGLE_GEMINI_3_FLASH_PREVIEW = ( - "google/gemini-3-flash-preview", - "Gemini 3 Flash Preview (Google)", - "GOOGLE_API_KEY", - ) - GOOGLE_GEMINI_3_1_FLASH_LITE = ("google/gemini-3.1-flash-lite", "Gemini 3.1 Flash Lite (Google)", "GOOGLE_API_KEY") - ANTHROPIC_CLAUDE_4_7_OPUS = ("anthropic/claude-opus-4-7", "Claude Opus 4.7 (Anthropic)", "ANTHROPIC_API_KEY") - ANTHROPIC_CLAUDE_4_6_SONNET = ("anthropic/claude-sonnet-4-6", "Claude Sonnet 4.6 (Anthropic)", "ANTHROPIC_API_KEY") - ANTHROPIC_CLAUDE_4_5_HAIKU = ( - "anthropic/claude-haiku-4-5-20251001", - "Claude Haiku 4.5(Anthropic)", - "ANTHROPIC_API_KEY", - ) - def __new__(cls, model_id: str, friendly_name: str, api_key_name: str) -> Self: + OPENAI_GPT_4O = ("gpt-4o", "GPT-4o (OpenAI)") + OPENAI_GPT_5_5 = ("gpt-5.5", "GPT-5.5 (OpenAI)") + OPENAI_GPT_5_4_MINI = ("gpt-5.4-mini", "GPT-5.4-mini (OpenAI)") + GOOGLE_GEMINI_3_1_PRO_PREVIEW = ("gemini-3.1-pro-preview", "Gemini 3.1 Pro Preview (Google)") + GOOGLE_GEMINI_3_FLASH_PREVIEW = ("gemini-3-flash-preview", "Gemini 3 Flash Preview (Google)") + ANTHROPIC_CLAUDE_4_7_OPUS = ("claude-opus-4-7", "Claude Opus 4.7 (Anthropic)") + ANTHROPIC_CLAUDE_4_6_SONNET = ("claude-sonnet-4-6", "Claude Sonnet 4.6 (Anthropic)") + + def __new__(cls, model_id: str, friendly_name: str) -> Self: """Make a new ModelInfo enum object. The value of the enum will be the model ID. @@ -59,13 +40,11 @@ def __new__(cls, model_id: str, friendly_name: str, api_key_name: str) -> Self: Args: model_id: The ID of the model. friendly_name: The friendly name of the model (displayed in the UI). - api_key_name: The name of the API key to use to connect to the model. """ obj = str.__new__(cls, model_id) obj._value_ = model_id obj.model_id = model_id obj.friendly_name = friendly_name - obj.api_key_name = api_key_name return obj def __str__(self) -> str: @@ -77,44 +56,67 @@ def __str__(self) -> str: return self.friendly_name -def execute_samples_against_model(samples: list[Sample], model_info: ModelInfo, api_key: str) -> list[str]: - """Executes a list of samples against a model and returns the model outputs. +def get_proxy_base_url() -> str: + """Return the OpenAI-compatible proxy base URL. + + Returns: + The proxy base URL, overridable via ``ASPIS_OPENAI_BASE_URL``. + """ + return os.environ.get("ASPIS_OPENAI_BASE_URL", DEFAULT_PROXY_BASE_URL) + + +def create_openai_client(api_key: str) -> OpenAI: + """Create a new OpenAI client for a single request. + + The API key is passed only to this client instance and is never written to + process environment variables, so concurrent callers cannot override each + other's credentials. Args: - samples: The list of samples to execute against the model. - model_info: The information about the model to execute the samples against. - api_key: The API key to use to execute the samples against the model. + api_key: The caller-provided API key. Returns: - The model outputs. + A new ``OpenAI`` client pointed at the Vector proxy. """ - logger.info(f"Making API call to model {model_info.model_id}...") + return OpenAI( + api_key=api_key, + base_url=get_proxy_base_url(), + timeout=DEFAULT_OPENAI_TIMEOUT_SECONDS, + ) - # Executing this in a synchronous thread pool executor to make InspectAI - # work well with streamlit's main thread - with ThreadPoolExecutor() as executor: - result = executor.submit(run_eval, samples, model_info, api_key).result() - assert len(result) == 1, "Expected exactly one result" +def execute_samples_against_model(prompts: list[str], model_info: ModelInfo, api_key: str) -> list[str]: + """Executes a list of prompts against a model and returns the model outputs. - if result[0].status != "success": - logger.error("Evaluation error: %s", result[0].error) - logger.debug("Full evaluation result: %s", result[0]) - raise ValueError("Error during evaluation.") + Args: + prompts: The list of prompt strings to execute against the model. + model_info: The information about the model to execute the prompts against. + api_key: The API key to use to execute the prompts against the model. - assert result[0].samples is not None, "Expected samples to be not None" - assert len(result[0].samples) == len(samples), ( - "Expected number of samples to be the same as the number of samples in the task" - ) + Returns: + The model outputs. + """ + logger.info(f"Making API call to model {model_info.model_id}...") model_outputs = [] - for sample in result[0].samples: - message_content = extract_string_output( - sample.output.choices[0].message.content, - model_info, - ) - assert isinstance(message_content, str), "Expected message content to be a string" - model_outputs.append(message_content) + with create_openai_client(api_key) as client: + for prompt in prompts: + try: + response = client.chat.completions.create( + model=model_info.model_id, + messages=[{"role": "user", "content": prompt}], + ) + except Exception as e: + logger.exception("Error during model evaluation for model %s", model_info.model_id) + raise ValueError("Error during evaluation.") from e + + if not response.choices: + raise ValueError("Expected at least one choice in the model response") + + message_content = extract_string_output(response.choices[0].message.content) + if not isinstance(message_content, str): + raise ValueError("Expected message content to be a string") + model_outputs.append(message_content) return model_outputs @@ -136,12 +138,8 @@ def evaluate_text( Returns: The inferred output from the model, parsed from a json to a dictionary. """ - samples = [] - for prompt_template in prompt_templates: - input_prompt = get_inference_prompt(input_text, prompt_template) - samples.append(Sample(input=input_prompt, target="")) - - model_outputs = execute_samples_against_model(samples, model_info, api_key) + prompts = [get_inference_prompt(input_text, prompt_template) for prompt_template in prompt_templates] + model_outputs = execute_samples_against_model(prompts, model_info, api_key) parsed_model_outputs = [] for model_output in model_outputs: @@ -158,35 +156,6 @@ def evaluate_text( return parsed_model_outputs -def run_eval(samples: list[Sample], model_info: ModelInfo, api_key: str) -> list[EvalLog]: - """Helper function to run eval on a list of samples with a specific API key. - - Args: - samples: The list of samples to run the eval on. - model_info: The information about the model to use for the evaluation. - api_key: The API key to use to run the eval. - - Returns: - The result of the eval. - """ - task = Task( - dataset=MemoryDataset(samples), - solver=[generate()], - scorer=model_graded_qa(), - ) - with TemporaryDirectory() as temp_dir, _INSPECTAI_EVAL_LOCK: - try: - os.environ[model_info.api_key_name] = api_key - result = inspect_ai_eval(task, model=model_info.model_id, log_dir=temp_dir) - finally: - os.environ.pop(model_info.api_key_name, None) - # Reset the logger level to the default level since - # inspectai sets it to WARNING - logger.setLevel(get_logger_level()) - - return result - - def get_inference_prompt(input_text: str, prompt: str) -> str: """Get the inference prompt to be used as input to the model. @@ -203,29 +172,51 @@ def get_inference_prompt(input_text: str, prompt: str) -> str: return prompt.replace("", f"{input_text}") -def extract_string_output(model_output: Any, model_info: ModelInfo) -> str: - """Extract the string output from the model output given the model info. +def _part_type(part: Any) -> str | None: + """Return the content-part type string when available.""" + if isinstance(part, dict): + part_type = part.get("type") + return str(part_type) if part_type is not None else None + part_type = getattr(part, "type", None) + return str(part_type) if part_type is not None else None + + +def _part_text(part: Any) -> str | None: + """Return text from a content part, if present.""" + if isinstance(part, str): + return part + if isinstance(part, dict): + text = part.get("text") + return str(text) if text is not None else None + text = getattr(part, "text", None) + return str(text) if text is not None else None + + +def extract_string_output(model_output: Any) -> str: + """Extract the answer string from an OpenAI chat completion message content. + + For multi-part content (e.g. reasoning + answer), skips known reasoning part + types and returns the final remaining text part so JSON parsing is not broken + by reasoning prefixes. Args: - model_output: The model output. - model_info: The model info. + model_output: The message content from the model response. Returns: The string output. """ - if model_info == ModelInfo.OPENAI_GPT_4O: + if isinstance(model_output, str): return model_output - if model_info in [ - ModelInfo.OPENAI_GPT_5_5, - ModelInfo.GOOGLE_GEMINI_3_1_PRO_PREVIEW, - ModelInfo.GOOGLE_GEMINI_3_FLASH_PREVIEW, - ModelInfo.GOOGLE_GEMINI_3_1_FLASH_LITE, - ]: - # first output is the reasoning, second output is the answer - return model_output[1].text - - if model_info == ModelInfo.OPENAI_GPT_5_4_MINI: - return model_output[0].text - - raise ValueError(f"Model info {model_info} not supported") + if isinstance(model_output, list): + answer_parts: list[str] = [] + for part in model_output: + if _part_type(part) in _REASONING_PART_TYPES: + continue + text = _part_text(part) + if text is not None: + answer_parts.append(text) + if answer_parts: + return answer_parts[-1] + + raise ValueError(f"Unsupported model output content type: {type(model_output)}") diff --git a/src/aspis/systematization.py b/src/aspis/systematization.py index 21f76d5..edc8fc6 100644 --- a/src/aspis/systematization.py +++ b/src/aspis/systematization.py @@ -4,7 +4,6 @@ from dataclasses import dataclass from pathlib import Path -from inspect_ai.dataset import Sample from langchain_core.prompts import ChatPromptTemplate from aspis.inferencer import ModelInfo, execute_samples_against_model @@ -102,16 +101,13 @@ def get_systematization_questions( """ logger.info("Querying model for systematization questions") - sample = Sample( - input=SYSTEMATIZATION_PROMPT.format( - product_description=product_description, - risk_description=risk_description, - systematization_paper=SYSTEMATIZATION_PAPER_PATH.read_text(), - ), - target="", + prompt = SYSTEMATIZATION_PROMPT.format( + product_description=product_description, + risk_description=risk_description, + systematization_paper=SYSTEMATIZATION_PAPER_PATH.read_text(), ) - model_outputs = execute_samples_against_model([sample], model_info, api_key) + model_outputs = execute_samples_against_model([prompt], model_info, api_key) assert len(model_outputs) == 1, "Expected exactly one model output" model_output = model_outputs[0] @@ -170,12 +166,9 @@ def get_systematized_concepts( # Format questions and answers for the prompt logger.info("Querying model for systematized concepts") - sample = Sample( - input=get_systematized_concepts_prompt(product_description, risk_description, questions, answers), - target="", - ) + prompt = get_systematized_concepts_prompt(product_description, risk_description, questions, answers) - model_outputs = execute_samples_against_model([sample], model_info, api_key) + model_outputs = execute_samples_against_model([prompt], model_info, api_key) assert len(model_outputs) == 1, "Expected exactly one model output" model_output = model_outputs[0] diff --git a/tests/aspis/api/test_main.py b/tests/aspis/api/test_main.py index f7f9d97..0863ffe 100644 --- a/tests/aspis/api/test_main.py +++ b/tests/aspis/api/test_main.py @@ -2,29 +2,30 @@ import json from io import BytesIO -from unittest.mock import ANY, Mock, patch +from unittest.mock import Mock, patch import pytest import yaml from fastapi.testclient import TestClient -from inspect_ai.scorer import model_graded_qa -from inspect_ai.solver import generate from aspis.api.main import app -from aspis.inferencer import ModelInfo +from aspis.inferencer import DEFAULT_OPENAI_TIMEOUT_SECONDS, DEFAULT_PROXY_BASE_URL, ModelInfo from aspis.utils import clean_model_output +def _mock_completion(content: str) -> Mock: + return Mock(choices=[Mock(message=Mock(content=content))]) + + @pytest.mark.integration_test -@patch("aspis.inferencer.inspect_ai_eval") -def test_evaluate_from_file_success(mock_inspect_ai_eval: Mock) -> None: +@patch("aspis.inferencer.OpenAI") +def test_evaluate_from_file_success(mock_openai: Mock) -> None: test_scores = ['{"score": "test score 1"}', '```json{"score": "test score 2"}```', "not a valid json test score"] - mock_inspect_ai_eval.return_value = [ - Mock( - status="success", - samples=[Mock(output=Mock(choices=[Mock(message=Mock(content=test_score))])) for test_score in test_scores], - ), - ] + mock_client = Mock() + mock_openai.return_value = mock_client + mock_client.__enter__ = Mock(return_value=mock_client) + mock_client.__exit__ = Mock(return_value=False) + mock_client.chat.completions.create.side_effect = [_mock_completion(score) for score in test_scores] with TestClient(app) as client: test_text_to_evaluate = "Test text" @@ -77,20 +78,25 @@ def test_evaluate_from_file_success(mock_inspect_ai_eval: Mock) -> None: assert json_response[i]["result"] == expected_result assert json_response[i]["prompt"] == expected_prompts[i] - mock_inspect_ai_eval.assert_called_once_with(ANY, model=ModelInfo.OPENAI_GPT_4O.model_id, log_dir=ANY) - - inspect_call_args = mock_inspect_ai_eval.call_args_list[0][0][0] - assert expected_prompts == [s.input for s in inspect_call_args.dataset.samples] - assert len(inspect_call_args.solver) == 1 - assert inspect_call_args.solver[0].__qualname__ == generate().__qualname__ - assert len(inspect_call_args.scorer) == 1 - assert inspect_call_args.scorer[0].__qualname__ == model_graded_qa().__qualname__ + mock_openai.assert_called_once_with( + api_key=test_api_key, base_url=DEFAULT_PROXY_BASE_URL, timeout=DEFAULT_OPENAI_TIMEOUT_SECONDS + ) + assert mock_client.chat.completions.create.call_count == len(test_systematized_concepts) + for expected_prompt in expected_prompts: + mock_client.chat.completions.create.assert_any_call( + model=ModelInfo.OPENAI_GPT_4O.model_id, + messages=[{"role": "user", "content": expected_prompt}], + ) @pytest.mark.integration_test -@patch("aspis.inferencer.inspect_ai_eval") -def test_evaluate_from_file_failure_evaluation_error(mock_inspect_ai_eval: Mock) -> None: - mock_inspect_ai_eval.return_value = [Mock(status="error", error="Test error")] +@patch("aspis.inferencer.OpenAI") +def test_evaluate_from_file_failure_evaluation_error(mock_openai: Mock) -> None: + mock_client = Mock() + mock_openai.return_value = mock_client + mock_client.__enter__ = Mock(return_value=mock_client) + mock_client.__exit__ = Mock(return_value=False) + mock_client.chat.completions.create.side_effect = RuntimeError("Test error") with TestClient(app) as client: test_systematized_concepts = [ @@ -140,29 +146,28 @@ def test_evaluate_from_file_failure_bad_format() -> None: @pytest.mark.integration_test -@patch("aspis.inferencer.inspect_ai_eval") -def test_evaluate_from_file_with_model_success(mock_inspect_ai_eval: Mock) -> None: +@patch("aspis.inferencer.OpenAI") +def test_evaluate_from_file_with_model_success(mock_openai: Mock) -> None: test_systematized_concepts = [ {"title": "Test concept 1", "prompt_template": "Test template 1 text"} ] file_content = yaml.safe_dump({"systematized_concepts": test_systematized_concepts}).encode("utf-8") - test_scores = [[{}, Mock(text='{"score": "test score 1"}')]] - mock_inspect_ai_eval.return_value = [ - Mock( - status="success", - samples=[Mock(output=Mock(choices=[Mock(message=Mock(content=test_score))])) for test_score in test_scores], - ), - ] + mock_client = Mock() + mock_openai.return_value = mock_client + mock_client.__enter__ = Mock(return_value=mock_client) + mock_client.__exit__ = Mock(return_value=False) + mock_client.chat.completions.create.return_value = _mock_completion('{"score": "test score 1"}') test_model_id = ModelInfo.GOOGLE_GEMINI_3_1_PRO_PREVIEW.model_id + test_api_key = "test api key" with TestClient(app) as client: response = client.post( "/evaluate_from_file", data={ "text_to_evaluate": "Test text", - "api_key": "test api key", + "api_key": test_api_key, "model": test_model_id, }, files={ @@ -175,7 +180,18 @@ def test_evaluate_from_file_with_model_success(mock_inspect_ai_eval: Mock) -> No ) assert response.status_code == 200 - mock_inspect_ai_eval.assert_called_once_with(ANY, model=test_model_id, log_dir=ANY) + mock_openai.assert_called_once_with( + api_key=test_api_key, base_url=DEFAULT_PROXY_BASE_URL, timeout=DEFAULT_OPENAI_TIMEOUT_SECONDS + ) + mock_client.chat.completions.create.assert_called_once_with( + model=test_model_id, + messages=[ + { + "role": "user", + "content": "Test template 1 Test text text", + } + ], + ) @pytest.mark.integration_test @@ -203,7 +219,7 @@ def test_evaluate_from_file_invalid_model() -> None: ) assert response.status_code == 422 - assert "Input should be 'openai/" in response.json()["detail"][0]["msg"] + assert "Input should be 'gpt-4o'" in response.json()["detail"][0]["msg"] @pytest.mark.integration_test @@ -237,30 +253,28 @@ def test_evaluate_from_file_failure_missing_fields() -> None: @pytest.mark.integration_test -@patch("aspis.inferencer.inspect_ai_eval") -def test_evaluate_from_file_failure_assertions(mock_inspect_ai_eval: Mock) -> None: - return_values_and_error_messages = [ - ([], "Expected exactly one result"), - (["a", "b"], "Expected exactly one result"), - ([Mock(status="success", samples=None)], "Expected samples to be not None"), - ( - [Mock(status="success", samples=[])], - "Expected number of samples to be the same as the number of samples in the task", - ), +@patch("aspis.inferencer.OpenAI") +def test_evaluate_from_file_failure_assertions(mock_openai: Mock) -> None: + return_values_and_expectations = [ ( - [Mock(status="success", samples=["a", "b"])], - "Expected number of samples to be the same as the number of samples in the task", + Mock(choices=[]), + 500, + "Evaluation failed: Expected at least one choice in the model response", ), ( - [Mock(status="success", samples=[Mock(output=Mock(choices=[Mock(message=Mock(content=123))]))])], - "Expected message content to be a string", + Mock(choices=[Mock(message=Mock(content=123))]), + 500, + "Evaluation failed: Unsupported model output content type: ", ), ] - for return_value, error_message in return_values_and_error_messages: - mock_inspect_ai_eval.return_value = return_value + for return_value, expected_status, error_message in return_values_and_expectations: + mock_client = Mock() + mock_openai.return_value = mock_client + mock_client.__enter__ = Mock(return_value=mock_client) + mock_client.__exit__ = Mock(return_value=False) + mock_client.chat.completions.create.return_value = return_value - """Test the API main module.""" with TestClient(app) as client: file_content = yaml.safe_dump( { @@ -288,7 +302,7 @@ def test_evaluate_from_file_failure_assertions(mock_inspect_ai_eval: Mock) -> No }, ) - assert response.status_code == 422 + assert response.status_code == expected_status assert response.json()["detail"] == error_message - mock_inspect_ai_eval.reset_mock() + mock_openai.reset_mock() diff --git a/tests/aspis/manual_test_inferencer.py b/tests/aspis/manual_test_inferencer.py index 2df5122..fd0e6ad 100644 --- a/tests/aspis/manual_test_inferencer.py +++ b/tests/aspis/manual_test_inferencer.py @@ -2,27 +2,23 @@ import os -from inspect_ai.dataset import Sample - from aspis.inferencer import ModelInfo, execute_samples_against_model from aspis.systematization import SYSTEMATIZATION_PAPER_PATH, SYSTEMATIZATION_PROMPT def run_inferencer_manual_test() -> None: """Run the inferencer manual test.""" - model_info = ModelInfo.GOOGLE_GEMINI_3_1_FLASH_LITE - api_key = os.getenv(model_info.api_key_name) - - sample = Sample( - input=SYSTEMATIZATION_PROMPT.format( - product_description="this is my product", - risk_description="this is my risk", - systematization_paper=SYSTEMATIZATION_PAPER_PATH.read_text(), - ), - target="", + model_info = ModelInfo.GOOGLE_GEMINI_3_FLASH_PREVIEW + api_key = os.getenv("ASPIS_API_KEY") or os.getenv("OPENAI_API_KEY") + assert api_key is not None, "Set ASPIS_API_KEY or OPENAI_API_KEY before running this manual test" + + prompt = SYSTEMATIZATION_PROMPT.format( + product_description="this is my product", + risk_description="this is my risk", + systematization_paper=SYSTEMATIZATION_PAPER_PATH.read_text(), ) - model_outputs = execute_samples_against_model([sample], model_info, api_key) + model_outputs = execute_samples_against_model([prompt], model_info, api_key) print(model_outputs) diff --git a/tests/aspis/test_inferencer.py b/tests/aspis/test_inferencer.py index e5733a4..8457cef 100644 --- a/tests/aspis/test_inferencer.py +++ b/tests/aspis/test_inferencer.py @@ -1,20 +1,121 @@ """Tests for the inferencer module.""" -from unittest.mock import Mock +from types import SimpleNamespace +from unittest.mock import Mock, patch -from aspis.inferencer import ModelInfo, extract_string_output +import pytest + +from aspis.inferencer import ( + DEFAULT_OPENAI_TIMEOUT_SECONDS, + DEFAULT_PROXY_BASE_URL, + ModelInfo, + create_openai_client, + execute_samples_against_model, + extract_string_output, +) def test_extract_string_output() -> None: test_cases = [ - (ModelInfo.OPENAI_GPT_4O, "test score", "test score"), - (ModelInfo.OPENAI_GPT_5_5, [{}, Mock(text="test score")], "test score"), - (ModelInfo.OPENAI_GPT_5_4_MINI, [Mock(text="test score")], "test score"), - (ModelInfo.GOOGLE_GEMINI_3_1_PRO_PREVIEW, [{}, Mock(text="test score")], "test score"), - (ModelInfo.GOOGLE_GEMINI_3_FLASH_PREVIEW, [{}, Mock(text="test score")], "test score"), - (ModelInfo.GOOGLE_GEMINI_3_1_FLASH_LITE, [{}, Mock(text="test score")], "test score"), + ("test score", "test score"), + (["part1", "part2"], "part2"), + ([Mock(text="test score")], "test score"), + ([{"text": "test score"}], "test score"), + # Reasoning then answer: take the final non-reasoning text part. + ([SimpleNamespace(text="reasoning"), SimpleNamespace(text="answer")], "answer"), + ( + [ + SimpleNamespace(type="reasoning", text="thinking..."), + SimpleNamespace(type="text", text='{"score": 1}'), + ], + '{"score": 1}', + ), + ( + [ + {"type": "thinking", "text": "step by step"}, + {"type": "text", "text": "final answer"}, + ], + "final answer", + ), ] - for test_case in test_cases: - model_info, model_output, expected_output = test_case - assert extract_string_output(model_output, model_info) == expected_output + for model_output, expected_output in test_cases: + assert extract_string_output(model_output) == expected_output + + +def test_extract_string_output_unsupported() -> None: + with pytest.raises(ValueError, match="Unsupported model output content type"): + extract_string_output(123) + + +@patch("aspis.inferencer.OpenAI") +def test_create_openai_client_passes_api_key_and_proxy(mock_openai: Mock) -> None: + api_key = "test-api-key" + create_openai_client(api_key) + + mock_openai.assert_called_once_with( + api_key=api_key, base_url=DEFAULT_PROXY_BASE_URL, timeout=DEFAULT_OPENAI_TIMEOUT_SECONDS + ) + + +@patch("aspis.inferencer.OpenAI") +def test_execute_samples_against_model_uses_per_call_client(mock_openai: Mock) -> None: + api_key = "caller-api-key" + model_info = ModelInfo.OPENAI_GPT_4O + prompts = ["prompt one", "prompt two"] + + mock_client = Mock() + mock_openai.return_value = mock_client + mock_client.__enter__ = Mock(return_value=mock_client) + mock_client.__exit__ = Mock(return_value=False) + mock_client.chat.completions.create.side_effect = [ + Mock(choices=[Mock(message=Mock(content="output one"))]), + Mock(choices=[Mock(message=Mock(content="output two"))]), + ] + + outputs = execute_samples_against_model(prompts, model_info, api_key) + + assert outputs == ["output one", "output two"] + mock_openai.assert_called_once_with( + api_key=api_key, base_url=DEFAULT_PROXY_BASE_URL, timeout=DEFAULT_OPENAI_TIMEOUT_SECONDS + ) + assert mock_client.chat.completions.create.call_count == 2 + mock_client.chat.completions.create.assert_any_call( + model=model_info.model_id, + messages=[{"role": "user", "content": "prompt one"}], + ) + mock_client.chat.completions.create.assert_any_call( + model=model_info.model_id, + messages=[{"role": "user", "content": "prompt two"}], + ) + mock_client.__exit__.assert_called_once() + + +@patch("aspis.inferencer.OpenAI") +def test_execute_samples_against_model_raises_on_api_error(mock_openai: Mock) -> None: + mock_client = Mock() + mock_openai.return_value = mock_client + mock_client.__enter__ = Mock(return_value=mock_client) + mock_client.__exit__ = Mock(return_value=False) + mock_client.chat.completions.create.side_effect = RuntimeError("boom") + + with pytest.raises(ValueError, match="Error during evaluation") as exc_info: + execute_samples_against_model(["prompt"], ModelInfo.OPENAI_GPT_4O, "key") + + assert isinstance(exc_info.value.__cause__, RuntimeError) + mock_openai.assert_called_once_with( + api_key="key", base_url=DEFAULT_PROXY_BASE_URL, timeout=DEFAULT_OPENAI_TIMEOUT_SECONDS + ) + mock_client.__exit__.assert_called_once() + + +@patch("aspis.inferencer.OpenAI") +def test_execute_samples_against_model_raises_on_empty_choices(mock_openai: Mock) -> None: + mock_client = Mock() + mock_openai.return_value = mock_client + mock_client.__enter__ = Mock(return_value=mock_client) + mock_client.__exit__ = Mock(return_value=False) + mock_client.chat.completions.create.return_value = Mock(choices=[]) + + with pytest.raises(ValueError, match="Expected at least one choice"): + execute_samples_against_model(["prompt"], ModelInfo.OPENAI_GPT_4O, "key") diff --git a/tests/aspis/test_systematization.py b/tests/aspis/test_systematization.py index 641b9d3..4e1cf7e 100644 --- a/tests/aspis/test_systematization.py +++ b/tests/aspis/test_systematization.py @@ -3,8 +3,6 @@ import json from unittest.mock import Mock, patch -from inspect_ai.dataset import Sample - from aspis.inferencer import ModelInfo from aspis.systematization import ( SYSTEMATIZATION_PAPER_PATH, @@ -43,12 +41,7 @@ def test_get_systematization_questions_success(mock_execute_samples: Mock) -> No assert questions == ["test question 1", "test question 2"] mock_execute_samples.assert_called_once_with( - [ - Sample( - input=get_systematization_questions_prompt(test_product_description, test_risk_description), - target="", - ) - ], + [get_systematization_questions_prompt(test_product_description, test_risk_description)], test_model_info, test_openai_api_key, ) @@ -84,12 +77,7 @@ def test_get_systematization_questions_failure_invalid_results(mock_execute_samp assert questions is None mock_execute_samples.assert_called_once_with( - [ - Sample( - input=get_systematization_questions_prompt(test_product_description, test_risk_description), - target="", - ) - ], + [get_systematization_questions_prompt(test_product_description, test_risk_description)], test_model_info, test_openai_api_key, ) @@ -136,14 +124,11 @@ def test_get_systematized_concepts_success(mock_execute_samples: Mock) -> None: mock_execute_samples.assert_called_once_with( [ - Sample( - input=get_systematized_concepts_prompt( - test_product_description, - test_risk_description, - test_questions, - test_answers, - ), - target="", + get_systematized_concepts_prompt( + test_product_description, + test_risk_description, + test_questions, + test_answers, ) ], test_model_info, @@ -187,14 +172,11 @@ def test_get_systematized_concepts_failure_invalid_results(mock_execute_samples: assert systematized_concepts is None mock_execute_samples.assert_called_once_with( [ - Sample( - input=get_systematized_concepts_prompt( - test_product_description, - test_risk_description, - test_questions, - test_answers, - ), - target="", + get_systematized_concepts_prompt( + test_product_description, + test_risk_description, + test_questions, + test_answers, ) ], test_model_info, diff --git a/tests/aspis/ui/test_main.py b/tests/aspis/ui/test_main.py index d59ac59..650eefb 100644 --- a/tests/aspis/ui/test_main.py +++ b/tests/aspis/ui/test_main.py @@ -1,7 +1,6 @@ """Test for the main module.""" import json -import os from copy import deepcopy from dataclasses import asdict from io import BytesIO @@ -10,10 +9,9 @@ import pytest import yaml -from inspect_ai.dataset import Sample from streamlit.testing.v1 import AppTest -from aspis.inferencer import ModelInfo +from aspis.inferencer import DEFAULT_OPENAI_TIMEOUT_SECONDS, DEFAULT_PROXY_BASE_URL, ModelInfo from aspis.systematization import ( SystematizedConcept, get_systematization_questions_prompt, @@ -21,24 +19,26 @@ ) -def make_inspect_ai_side_effect(model_info: ModelInfo, api_key: str, return_value: Any) -> Callable[[...], list[Mock]]: - side_effect_return = [ - Mock( - status="success", - samples=[Mock(output=Mock(choices=[Mock(message=Mock(content=json.dumps(return_value)))]))], - ), - ] +def make_openai_side_effect(api_key: str, return_value: Any) -> Callable[..., Mock]: + def side_effect(*args: Any, **kwargs: Any) -> Mock: + assert kwargs.get("api_key") == api_key + assert kwargs.get("base_url") == DEFAULT_PROXY_BASE_URL + assert kwargs.get("timeout") == DEFAULT_OPENAI_TIMEOUT_SECONDS - def side_effect(*args: Any, **kwargs: Any) -> list[Mock]: - assert os.environ[model_info.api_key_name] == api_key - return side_effect_return + mock_client = Mock() + mock_client.__enter__ = Mock(return_value=mock_client) + mock_client.__exit__ = Mock(return_value=False) + mock_client.chat.completions.create.return_value = Mock( + choices=[Mock(message=Mock(content=json.dumps(return_value)))] + ) + return mock_client return side_effect @pytest.mark.integration_test -@patch("aspis.inferencer.inspect_ai_eval") -def test_main_render_inputs_when_empty(mock_inspect_ai_eval: Mock) -> None: +@patch("aspis.inferencer.OpenAI") +def test_main_render_inputs_when_empty(mock_openai: Mock) -> None: app = AppTest.from_file("src/aspis/ui/main.py") app.run() @@ -48,7 +48,7 @@ def test_main_render_inputs_when_empty(mock_inspect_ai_eval: Mock) -> None: assert "risk_description" not in app.session_state assert "product_description" not in app.session_state - mock_inspect_ai_eval.assert_not_called() + mock_openai.assert_not_called() assert app.selectbox("model_info_input").label == "Select the model you want to use:" assert app.selectbox("model_info_input").options == [model.friendly_name for model in list(ModelInfo)] assert app.selectbox("model_info_input").index == 0 @@ -61,15 +61,30 @@ def test_main_render_inputs_when_empty(mock_inspect_ai_eval: Mock) -> None: @pytest.mark.integration_test -@patch("aspis.inferencer.inspect_ai_eval") -def test_main_ask_for_questions_when_inputs_are_set(mock_inspect_ai_eval: Mock) -> None: +@patch("aspis.inferencer.OpenAI") +def test_main_ask_for_questions_when_inputs_are_set(mock_openai: Mock) -> None: test_questions = ["test question"] test_api_key = "test api key" test_model_info = ModelInfo.OPENAI_GPT_4O test_risk_description = "test risk description" test_product_description = "test product description" - mock_inspect_ai_eval.side_effect = make_inspect_ai_side_effect(test_model_info, test_api_key, test_questions) + created_clients: list[Mock] = [] + + def side_effect(*args: Any, **kwargs: Any) -> Mock: + assert kwargs.get("api_key") == test_api_key + assert kwargs.get("base_url") == DEFAULT_PROXY_BASE_URL + assert kwargs.get("timeout") == DEFAULT_OPENAI_TIMEOUT_SECONDS + mock_client = Mock() + mock_client.__enter__ = Mock(return_value=mock_client) + mock_client.__exit__ = Mock(return_value=False) + mock_client.chat.completions.create.return_value = Mock( + choices=[Mock(message=Mock(content=json.dumps(test_questions)))] + ) + created_clients.append(mock_client) + return mock_client + + mock_openai.side_effect = side_effect app = AppTest.from_file("src/aspis/ui/main.py") @@ -80,25 +95,30 @@ def test_main_ask_for_questions_when_inputs_are_set(mock_inspect_ai_eval: Mock) app.run() - assert mock_inspect_ai_eval.call_count == 1 - mock_inspect_ai_eval.assert_called_once_with(ANY, model=test_model_info.model_id, log_dir=ANY) - task = mock_inspect_ai_eval.call_args_list[0][0][0] - expected_sample = Sample( - input=get_systematization_questions_prompt(test_product_description, test_risk_description), - target="", + assert mock_openai.call_count == 1 + mock_openai.assert_called_once_with( + api_key=test_api_key, base_url=DEFAULT_PROXY_BASE_URL, timeout=DEFAULT_OPENAI_TIMEOUT_SECONDS + ) + assert len(created_clients) == 1 + created_clients[0].chat.completions.create.assert_called_once_with( + model=test_model_info.model_id, + messages=[ + { + "role": "user", + "content": get_systematization_questions_prompt(test_product_description, test_risk_description), + } + ], ) - assert task.dataset[0] == expected_sample - assert os.environ.get(test_model_info.api_key_name, None) is None @pytest.mark.integration_test -@patch("aspis.inferencer.inspect_ai_eval") -def test_main_render_error_messages_when_inputs_are_not_set(mock_inspect_ai_eval: Mock) -> None: +@patch("aspis.inferencer.OpenAI") +def test_main_render_error_messages_when_inputs_are_not_set(mock_openai: Mock) -> None: test_api_key = "test api key" test_risk_description = "test risk description" test_product_description = "test product description" test_model_info = ModelInfo.OPENAI_GPT_4O - mock_inspect_ai_eval.side_effect = make_inspect_ai_side_effect(test_model_info, test_api_key, ["test question"]) + mock_openai.side_effect = make_openai_side_effect(test_api_key, ["test question"]) # Empty API key app = AppTest.from_file("src/aspis/ui/main.py") @@ -156,17 +176,21 @@ def test_main_render_error_messages_when_inputs_are_not_set(mock_inspect_ai_eval assert app.session_state.model_info == test_model_info assert app.session_state.risk_description == test_risk_description assert app.session_state.product_description == test_product_description - mock_inspect_ai_eval.assert_called() + mock_openai.assert_called_once_with( + api_key=test_api_key, + base_url=DEFAULT_PROXY_BASE_URL, + timeout=DEFAULT_OPENAI_TIMEOUT_SECONDS, + ) @pytest.mark.integration_test -@patch("aspis.inferencer.inspect_ai_eval") -def test_main_render_error_when_questions_are_none(mock_inspect_ai_eval: Mock) -> None: +@patch("aspis.inferencer.OpenAI") +def test_main_render_error_when_questions_are_none(mock_openai: Mock) -> None: test_api_key = "test api key" test_risk_description = "test risk description" test_product_description = "test product description" test_model_info = ModelInfo.OPENAI_GPT_4O - mock_inspect_ai_eval.side_effect = make_inspect_ai_side_effect(test_model_info, test_api_key, None) + mock_openai.side_effect = make_openai_side_effect(test_api_key, None) app = AppTest.from_file("src/aspis/ui/main.py") app.run() @@ -179,28 +203,38 @@ def test_main_render_error_when_questions_are_none(mock_inspect_ai_eval: Mock) - app.button("generate_questions_button").click() app.run() - assert mock_inspect_ai_eval.call_count == 1 - mock_inspect_ai_eval.assert_called_once_with(ANY, model=test_model_info.model_id, log_dir=ANY) - task = mock_inspect_ai_eval.call_args_list[0][0][0] - expected_sample = Sample( - input=get_systematization_questions_prompt(test_product_description, test_risk_description), - target="", + assert mock_openai.call_count == 1 + mock_openai.assert_called_once_with( + api_key=test_api_key, base_url=DEFAULT_PROXY_BASE_URL, timeout=DEFAULT_OPENAI_TIMEOUT_SECONDS ) - assert task.dataset[0] == expected_sample - assert os.environ.get(test_model_info.api_key_name, None) is None assert app.error[0].value == "Error generating questions. Please try again." @pytest.mark.integration_test -@patch("aspis.inferencer.inspect_ai_eval") -def test_main_render_questions_on_success(mock_inspect_ai_eval: Mock) -> None: +@patch("aspis.inferencer.OpenAI") +def test_main_render_questions_on_success(mock_openai: Mock) -> None: test_questions = ["test question 1", "test question 2"] test_api_key = "test api key" test_model_info = ModelInfo.OPENAI_GPT_4O test_product_description = "test product description" test_risk_description = "test risk description" - mock_inspect_ai_eval.side_effect = make_inspect_ai_side_effect(test_model_info, test_api_key, test_questions) + created_clients: list[Mock] = [] + + def side_effect(*args: Any, **kwargs: Any) -> Mock: + assert kwargs.get("api_key") == test_api_key + assert kwargs.get("base_url") == DEFAULT_PROXY_BASE_URL + assert kwargs.get("timeout") == DEFAULT_OPENAI_TIMEOUT_SECONDS + mock_client = Mock() + mock_client.__enter__ = Mock(return_value=mock_client) + mock_client.__exit__ = Mock(return_value=False) + mock_client.chat.completions.create.return_value = Mock( + choices=[Mock(message=Mock(content=json.dumps(test_questions)))] + ) + created_clients.append(mock_client) + return mock_client + + mock_openai.side_effect = side_effect app = AppTest.from_file("src/aspis/ui/main.py") app.run() @@ -213,28 +247,33 @@ def test_main_render_questions_on_success(mock_inspect_ai_eval: Mock) -> None: app.button("generate_questions_button").click() app.run() - mock_inspect_ai_eval.assert_called_once_with(ANY, model=test_model_info.model_id, log_dir=ANY) - task = mock_inspect_ai_eval.call_args_list[0][0][0] - expected_sample = Sample( - input=get_systematization_questions_prompt(test_product_description, test_risk_description), - target="", + mock_openai.assert_called_once_with( + api_key=test_api_key, base_url=DEFAULT_PROXY_BASE_URL, timeout=DEFAULT_OPENAI_TIMEOUT_SECONDS + ) + assert len(created_clients) == 1 + created_clients[0].chat.completions.create.assert_called_once_with( + model=test_model_info.model_id, + messages=[ + { + "role": "user", + "content": get_systematization_questions_prompt(test_product_description, test_risk_description), + } + ], ) - assert task.dataset[0] == expected_sample - assert os.environ.get(test_model_info.api_key_name, None) is None for i in range(len(test_questions)): assert app.text_area(f"answer_input_{i + 1}").label == rf"{i + 1}\. {test_questions[i]}" @pytest.mark.integration_test -@patch("aspis.inferencer.inspect_ai_eval") -def test_main_error_when_answers_are_empty(mock_inspect_ai_eval: Mock) -> None: +@patch("aspis.inferencer.OpenAI") +def test_main_error_when_answers_are_empty(mock_openai: Mock) -> None: test_questions = ["test question 1", "test question 2"] test_api_key = "test api key" test_risk_description = "test risk description" test_product_description = "test product description" test_model_info = ModelInfo.OPENAI_GPT_4O - mock_inspect_ai_eval.side_effect = make_inspect_ai_side_effect(test_model_info, test_api_key, test_questions) + mock_openai.side_effect = make_openai_side_effect(test_api_key, test_questions) app = AppTest.from_file("src/aspis/ui/main.py") @@ -253,14 +292,26 @@ def test_main_error_when_answers_are_empty(mock_inspect_ai_eval: Mock) -> None: @pytest.mark.integration_test -@patch("aspis.inferencer.inspect_ai_eval") -def test_main_saves_answers_on_success(mock_inspect_ai_eval: Mock) -> None: +@patch("aspis.inferencer.OpenAI") +def test_main_saves_answers_on_success(mock_openai: Mock) -> None: test_api_key = "test api key" test_model_info = ModelInfo.OPENAI_GPT_4O test_risk_description = "test risk description" test_product_description = "test product description" test_questions = ["test question 1", "test question 2"] test_answers = ["test answer to question 1", "test answer to question 2"] + test_systematized_concepts = [ + { + "title": "test concept 1", + "body": "test body 1", + "prompt_template": "test prompt template 1", + }, + { + "title": "test concept 2", + "body": "test body 2", + "prompt_template": "test prompt template 2", + }, + ] app = AppTest.from_file("src/aspis/ui/main.py") @@ -275,7 +326,7 @@ def test_main_saves_answers_on_success(mock_inspect_ai_eval: Mock) -> None: app.text_area("answer_input_1").set_value(test_answers[0]) app.text_area("answer_input_2").set_value(test_answers[1]) - mock_inspect_ai_eval.side_effect = make_inspect_ai_side_effect(test_model_info, test_api_key, test_answers) + mock_openai.side_effect = make_openai_side_effect(test_api_key, test_systematized_concepts) app.button("submit_answers_button").click() app.run() @@ -284,8 +335,8 @@ def test_main_saves_answers_on_success(mock_inspect_ai_eval: Mock) -> None: @pytest.mark.integration_test -@patch("aspis.inferencer.inspect_ai_eval") -def test_main_render_results_when_answers_are_set(mock_inspect_ai_eval: Mock) -> None: +@patch("aspis.inferencer.OpenAI") +def test_main_render_results_when_answers_are_set(mock_openai: Mock) -> None: test_product_description = "test product description" test_risk_description = "test risk description" test_api_key = "test api key" @@ -306,6 +357,21 @@ def test_main_render_results_when_answers_are_set(mock_inspect_ai_eval: Mock) -> }, ] + created_clients: list[Mock] = [] + + def side_effect(*args: Any, **kwargs: Any) -> Mock: + assert kwargs.get("api_key") == test_api_key + assert kwargs.get("base_url") == DEFAULT_PROXY_BASE_URL + assert kwargs.get("timeout") == DEFAULT_OPENAI_TIMEOUT_SECONDS + mock_client = Mock() + mock_client.__enter__ = Mock(return_value=mock_client) + mock_client.__exit__ = Mock(return_value=False) + mock_client.chat.completions.create.return_value = Mock( + choices=[Mock(message=Mock(content=json.dumps(test_systematized_concepts)))] + ) + created_clients.append(mock_client) + return mock_client + app = AppTest.from_file("src/aspis/ui/main.py") app.session_state.model_info = test_model_info @@ -319,9 +385,7 @@ def test_main_render_results_when_answers_are_set(mock_inspect_ai_eval: Mock) -> app.text_area("answer_input_1").set_value(test_answers[0]) app.text_area("answer_input_2").set_value(test_answers[1]) - mock_inspect_ai_eval.side_effect = make_inspect_ai_side_effect( - test_model_info, test_api_key, test_systematized_concepts - ) + mock_openai.side_effect = side_effect app.button("submit_answers_button").click() app.run() @@ -333,26 +397,30 @@ def test_main_render_results_when_answers_are_set(mock_inspect_ai_eval: Mock) -> assert app.markdown[9].value == test_systematized_concepts[1]["body"] assert app.code[1].value == test_systematized_concepts[1]["prompt_template"] - assert mock_inspect_ai_eval.call_count == 1 - mock_inspect_ai_eval.assert_called_with(ANY, model=test_model_info.model_id, log_dir=ANY) - task = mock_inspect_ai_eval.call_args_list[0][0][0] - expected_sample = Sample( - input=get_systematized_concepts_prompt( - test_product_description, - test_risk_description, - test_questions, - test_answers, - ), - target="", + assert mock_openai.call_count == 1 + mock_openai.assert_called_with( + api_key=test_api_key, base_url=DEFAULT_PROXY_BASE_URL, timeout=DEFAULT_OPENAI_TIMEOUT_SECONDS + ) + assert len(created_clients) == 1 + created_clients[0].chat.completions.create.assert_called_once_with( + model=test_model_info.model_id, + messages=[ + { + "role": "user", + "content": get_systematized_concepts_prompt( + test_product_description, + test_risk_description, + test_questions, + test_answers, + ), + } + ], ) - assert task.dataset[0] == expected_sample - - assert os.environ.get(test_model_info.api_key_name, None) is None @pytest.mark.integration_test -@patch("aspis.inferencer.inspect_ai_eval") -def test_main_render_error_when_systematized_concepts_are_none(mock_inspect_ai_eval: Mock) -> None: +@patch("aspis.inferencer.OpenAI") +def test_main_render_error_when_systematized_concepts_are_none(mock_openai: Mock) -> None: test_product_description = "test product description" test_risk_description = "test risk description" test_api_key = "test api key" @@ -374,25 +442,14 @@ def test_main_render_error_when_systematized_concepts_are_none(mock_inspect_ai_e app.text_area("answer_input_1").set_value(test_answers[0]) app.text_area("answer_input_2").set_value(test_answers[1]) - mock_inspect_ai_eval.side_effect = make_inspect_ai_side_effect(test_model_info, test_api_key, None) + mock_openai.side_effect = make_openai_side_effect(test_api_key, None) app.button("submit_answers_button").click() app.run() - mock_inspect_ai_eval.assert_called_once_with(ANY, model=test_model_info.model_id, log_dir=ANY) - task = mock_inspect_ai_eval.call_args_list[0][0][0] - expected_sample = Sample( - input=get_systematized_concepts_prompt( - test_product_description, - test_risk_description, - test_questions, - test_answers, - ), - target="", + mock_openai.assert_called_once_with( + api_key=test_api_key, base_url=DEFAULT_PROXY_BASE_URL, timeout=DEFAULT_OPENAI_TIMEOUT_SECONDS ) - assert task.dataset[0] == expected_sample - - assert os.environ.get(test_model_info.api_key_name, None) is None assert app.error[0].value == "Error generating systematized concepts. 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