From ef5192a4068fa3e0d8545f070beb604acc42027a Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Mon, 6 Nov 2023 01:51:10 -0800 Subject: [PATCH 01/38] . --- deepeval/metrics/llm_eval_metric.py | 7 +-- docs/docs/evaluation-tracing.mdx | 95 +++++++++++++++++++++++++++++ docs/sidebars.js | 1 + tests/test_llm_metric.py | 2 +- 4 files changed, 100 insertions(+), 5 deletions(-) create mode 100644 docs/docs/evaluation-tracing.mdx diff --git a/deepeval/metrics/llm_eval_metric.py b/deepeval/metrics/llm_eval_metric.py index d07770822..a531935ac 100644 --- a/deepeval/metrics/llm_eval_metric.py +++ b/deepeval/metrics/llm_eval_metric.py @@ -8,7 +8,7 @@ from deepeval.types import LLMTestCaseParams from deepeval.chat_completion.retry import call_openai_with_retry from pydantic import BaseModel -from litellm import completion, text_completion +import openai class LLMEvalMetricResponse(BaseModel): @@ -29,7 +29,6 @@ def __init__( self.model = model self.evaluation_steps = "" self.evaluation_params = evaluation_params - self.minimum_score = minimum_score @property @@ -65,7 +64,7 @@ def generate_evaluation_steps(self): prompt: dict = evaluation_steps_template.format(criteria=self.criteria) res = call_openai_with_retry( - lambda: completion( + lambda: openai.ChatCompletion.create( model=self.model, messages=[ { @@ -92,7 +91,7 @@ def evaluate(self, test_case: LLMTestCase): ) res = call_openai_with_retry( - lambda: completion( + lambda: openai.ChatCompletion.create( model=self.model, messages=[{"role": "system", "content": prompt}], max_tokens=5, diff --git a/docs/docs/evaluation-tracing.mdx b/docs/docs/evaluation-tracing.mdx new file mode 100644 index 000000000..b1e53fb8e --- /dev/null +++ b/docs/docs/evaluation-tracing.mdx @@ -0,0 +1,95 @@ +--- +id: evaluation-tracing +title: Tracing +sidebar_label: Tracing +--- + +## Quick Summary + +Often times when a test case is failing you're not sure which compopnent of your RAG/agent-based application is the issue. Tracing in the context of evaluating LLM applications provides a quick and easy way for you to identify why certain test cases are failing on specific metrics. From chunking to embedding, and retrieval to generation, tracing allows you to debug your LLM application at a component level. + +## Tracing on Confident AI + +To start tracing your LLM application for each test case, login to Confident AI. + +``` +deepeval login +``` + +Follow the instructions displayed on the CLI to create an account, get your Confident API key, and paste it in the CLI. + +Once you're logged in, navigate to where you've implemented your LLM application, and import the `trace` decorator from `deepeval.tracing`. Here's a sample implementation for a hypothetical LLM application utilizing `deepeval`'s tracing module. + +```python title="test_chatbot.py" +from deepeval.tracing import trace, TraceType +import openai + +class Chatbot: + def __init__(self): + pass + + @trace(type=TraceType.LLM, name="OpenAI", model="gpt-4", characters_per_token=4, cost_per_token=0.000003) + def llm(self, input=input): + response = openai.ChatCompletion.create( + model="gpt-4", + messages=[ + { + "role": "system", + "content": "You are a helpful assistant.", + }, + {"role": "user", "content": prompt}, + ], + ) + return response.choices[0].message.content + + @trace(type=TraceType.EMBEDDING, name="Embedding", model="text-embedding-ada-002") + def get_embedding(input): + response = openai.Embedding.create( + input=input, + model="text-embedding-ada-002" + ) + embeddings = response['data'][0]['embedding'] + + @trace(type=TraceType.RETRIEVER, name="Retriever") + def retriever(self, input=input): + embedding = self.get_embedding(input) + + list_of_retrieved_nodes = some_function_that_searches_your_vector_db(embedding) + return list_of_retrieved_nodes + + @trace(type=TraceType.TOOL, name="Search") + def search(self, input): + title_of_the_top_search_results = some_function_that_searches_the_web(input) + return title_of_the_top_search_results + + + + def format(self, retrieval_nodes, input): + prompt = "You are a helpful assistant, based on the following information: " + for node in retrieval_nodes: + prompt += node + "\n" + prompt += "Generate an unbiased response for" + input + "." + return prompt + + + @query(input): + top_result_title = search(input) + retrieval_results = retriever(top_result) + prompt = format(retrieval_results, top_result_title) + return llm(prompt) + +chatbot = Chatbot() +chatbot.query("What are some nice tourist attractions in San Francisco?") +``` + +In this example, `chatbot.query()` first searches the web for the top tourist attraction, before using this information to retrieve information stored in a vector database. This is then all combined into a single prompt and fed into the `gpt-4` LLM. With this setup, all traces will automatically be logged each time you run `deepeval test run`. This will allow you to debug each failing test case, and here's what a trace stack looks like on Confident AI. + +[insert image of mock] + +Lastly, let's write some test cases to put everything in action. Continuning from the previous code snippet: + +```python title="test_chatbot.py" +... + + +``` diff --git a/docs/sidebars.js b/docs/sidebars.js index cb9556f1a..842753eb6 100644 --- a/docs/sidebars.js +++ b/docs/sidebars.js @@ -16,6 +16,7 @@ module.exports = { 'evaluation-test-cases', 'evaluation-metrics', 'evaluation-datasets', + // 'evaluation-tracing', ], collapsed: false, }, diff --git a/tests/test_llm_metric.py b/tests/test_llm_metric.py index 7d3eaf9ae..c4ac9b1f3 100644 --- a/tests/test_llm_metric.py +++ b/tests/test_llm_metric.py @@ -23,4 +23,4 @@ def test_chat_completion(): ) metric.measure(test_case) assert metric.is_successful() is True - assert metric.measure(test_case) == 1.0 + assert metric.measure(test_case) <= 1.0 From e786b124f2c23baec66cb46aff77e38e3457f326 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Mon, 6 Nov 2023 01:53:50 -0800 Subject: [PATCH 02/38] update version --- deepeval/_version.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/deepeval/_version.py b/deepeval/_version.py index 927a45b74..91ea3b613 100644 --- a/deepeval/_version.py +++ b/deepeval/_version.py @@ -1 +1 @@ -__version__: str = "0.20.13" +__version__: str = "0.20.14" From 1e4c62cd8a97a6bba433dbff2131a13ce294ec5e Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Mon, 6 Nov 2023 02:14:15 -0800 Subject: [PATCH 03/38] . --- tests/test_llm_metric.py | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/tests/test_llm_metric.py b/tests/test_llm_metric.py index c4ac9b1f3..f950ac7ec 100644 --- a/tests/test_llm_metric.py +++ b/tests/test_llm_metric.py @@ -2,6 +2,7 @@ from deepeval.test_case import LLMTestCase from deepeval.metrics.llm_eval_metric import LLMEvalMetric from deepeval.types import LLMTestCaseParams +from deepeval.run_test import assert_test def test_chat_completion(): @@ -21,6 +22,7 @@ def test_chat_completion(): expected_output="Paris", context="Geography", ) - metric.measure(test_case) - assert metric.is_successful() is True - assert metric.measure(test_case) <= 1.0 + # metric.measure(test_case) + # assert metric.is_successful() is True + # assert metric.measure(test_case) <= 1.0 + assert_test(test_case, [metric]) From ae914e8ae176308609dd611eea2b3f9b52f9cd93 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Mon, 6 Nov 2023 02:15:42 -0800 Subject: [PATCH 04/38] . --- deepeval/telemetry.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/deepeval/telemetry.py b/deepeval/telemetry.py index f71db9565..c0c2e5364 100644 --- a/deepeval/telemetry.py +++ b/deepeval/telemetry.py @@ -11,7 +11,7 @@ def check_firewall(): return True -if os.getenv("NO_ERROR_REPORTING") != "Y" and not check_firewall(): +if os.getenv("ERROR_REPORTING") == "YES" and not check_firewall(): try: import sentry_sdk From cb1020abb661bb4fac3c7c5d15d2bb705ebfad62 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Mon, 6 Nov 2023 02:32:19 -0800 Subject: [PATCH 05/38] new release --- deepeval/_version.py | 2 +- pyproject.toml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/deepeval/_version.py b/deepeval/_version.py index 91ea3b613..c0f8c2c5c 100644 --- a/deepeval/_version.py +++ b/deepeval/_version.py @@ -1 +1 @@ -__version__: str = "0.20.14" +__version__: str = "0.20.15" diff --git a/pyproject.toml b/pyproject.toml index 47b8cb2cd..404e794e9 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "deepeval" -version = "0.20.14" +version = "0.20.15" description = "The Evaluation Framework for LLMs" authors = ["Jeffrey Ip "] license = "Apache-2.0" From 5dea30ce35bc107a462cb10cb05988269988172d Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Mon, 6 Nov 2023 02:39:03 -0800 Subject: [PATCH 06/38] . --- docs/docs/data-privacy.mdx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/docs/data-privacy.mdx b/docs/docs/data-privacy.mdx index 6f0e81c00..685b6924f 100644 --- a/docs/docs/data-privacy.mdx +++ b/docs/docs/data-privacy.mdx @@ -12,10 +12,10 @@ If at any point you think you might have acceidentally sent us sensitive data, * ## Your Privacy Using DeepEval -`deepeval` only tracks errors and exceptions raised within the package for the purpose of improving the package and **does not collect any user or company data in any way**. To disable error reporting, set the `NO_ERROR_REPORTING` environment variable to 'Y'. +`deepeval` only tracks errors and exceptions raised within the package for the purpose of improving the package. This happens **only if you have explicitly opted in to it** and \*\*does not collect any user or company data in any way\*\*. To help us catch bugs for future release, set the `ERROR_REPORTING` environment variable to 'YES'. ```console -export NO_ERROR_REPORTING="Y" +export NO_ERROR_REPORTING="YES" ``` ## Your Privacy Using Confident AI From 88996ed784f8062538ce785dfd8e52a786694a57 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Mon, 6 Nov 2023 02:39:57 -0800 Subject: [PATCH 07/38] . --- docs/docs/data-privacy.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/docs/data-privacy.mdx b/docs/docs/data-privacy.mdx index 685b6924f..e028037a9 100644 --- a/docs/docs/data-privacy.mdx +++ b/docs/docs/data-privacy.mdx @@ -15,7 +15,7 @@ If at any point you think you might have acceidentally sent us sensitive data, * `deepeval` only tracks errors and exceptions raised within the package for the purpose of improving the package. This happens **only if you have explicitly opted in to it** and \*\*does not collect any user or company data in any way\*\*. To help us catch bugs for future release, set the `ERROR_REPORTING` environment variable to 'YES'. ```console -export NO_ERROR_REPORTING="YES" +export ERROR_REPORTING="YES" ``` ## Your Privacy Using Confident AI From 612cb824c60770448268aa365030b39e6f0919ab Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Mon, 6 Nov 2023 02:46:04 -0800 Subject: [PATCH 08/38] . --- docs/docs/data-privacy.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/docs/data-privacy.mdx b/docs/docs/data-privacy.mdx index e028037a9..edc53592d 100644 --- a/docs/docs/data-privacy.mdx +++ b/docs/docs/data-privacy.mdx @@ -12,7 +12,7 @@ If at any point you think you might have acceidentally sent us sensitive data, * ## Your Privacy Using DeepEval -`deepeval` only tracks errors and exceptions raised within the package for the purpose of improving the package. This happens **only if you have explicitly opted in to it** and \*\*does not collect any user or company data in any way\*\*. To help us catch bugs for future release, set the `ERROR_REPORTING` environment variable to 'YES'. +`deepeval` only tracks errors and exceptions raised within the package for the purpose of improving the package. This happens **only if you have explicitly opted in to it** and **does not collect any user or company data in any way**. To help us catch bugs for future releases, set the `ERROR_REPORTING` environment variable to "YES". ```console export ERROR_REPORTING="YES" From 76cd2813ab9e9767a8b1e2b56b13ae2c48eb1018 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Mon, 6 Nov 2023 19:01:12 -0800 Subject: [PATCH 09/38] fixes to tracing --- .DS_Store | Bin 8196 -> 8196 bytes deepeval/cli/main.py | 2 + deepeval/plugins/plugin.py | 4 +- deepeval/tracing.py | 57 ++----------- docs/docs/evaluation-metrics.mdx | 2 +- docs/docs/evaluation-tracing.mdx | 133 ++++++++++++++++++++++++------- docs/docs/getting-started.mdx | 5 ++ docs/sidebars.js | 2 +- examples/tracing/test_chatbot.py | 81 +++++++++++++++++++ 9 files changed, 206 insertions(+), 80 deletions(-) create mode 100644 examples/tracing/test_chatbot.py diff --git a/.DS_Store b/.DS_Store index 2147b514f40598d07b90f2ee775c1a843c61868c..de10488dc8ba82a77eb6cabf03af3af8253a2eb1 100644 GIT binary patch delta 33 pcmZp1XmOa}&nU7nU^hRb$YvgagUplv3QyP^%d?7kGrPoJb^yfT3&H>Z delta 70 zcmZp1XmOa}&nUVvU^hRb=w=>)gUpH?48;to3?&Su3nHCMp1*mTOdj*Z2A<9A5`WnNtfv$d diff --git a/deepeval/cli/main.py b/deepeval/cli/main.py index f04c5cf59..0b50ee3b7 100644 --- a/deepeval/cli/main.py +++ b/deepeval/cli/main.py @@ -9,6 +9,7 @@ from deepeval.api import Api from deepeval.key_handler import KEY_FILE_HANDLER from deepeval.cli.test import app as test_app +import webbrowser app = typer.Typer(name="deepeval") @@ -29,6 +30,7 @@ def login( print( "Grab your API key here: [link=https://app.confident-ai.com]https://app.confident-ai.com[/link] " ) + webbrowser.open("https://app.confident-ai.com") if api_key == "": while True: api_key = input("Paste your API Key: ").strip() diff --git a/deepeval/plugins/plugin.py b/deepeval/plugins/plugin.py index 097dbefad..4da3726e3 100644 --- a/deepeval/plugins/plugin.py +++ b/deepeval/plugins/plugin.py @@ -6,6 +6,7 @@ from typing import Optional, Any from deepeval.constants import PYTEST_RUN_ENV_VAR, PYTEST_RUN_TEST_NAME from deepeval.decorators.hyperparameters import get_hyperparameters +import webbrowser def pytest_sessionstart(session: pytest.Session): @@ -115,10 +116,11 @@ def pytest_sessionfinish(session: pytest.Session, exitstatus): print(table) if os.getenv(PYTEST_RUN_ENV_VAR) and os.path.exists(".deepeval"): - link = f"https://app.confident-ai.com/project/{result.projectId}/unit-tests/{result.testRunId}" + link = f"https://app.confident-ai.com/project/{result.projectId}/unit-tests/{result.testRunId}/test-cases" print( "✅ Tests finished! View results on " f"[link={link}]{link}[/link]" ) + webbrowser.open(link) else: print( '✅ Tests finished! Run "deepeval login" to view evaluation results in detail.' diff --git a/deepeval/tracing.py b/deepeval/tracing.py index c21a966f0..4adc327bb 100644 --- a/deepeval/tracing.py +++ b/deepeval/tracing.py @@ -4,7 +4,7 @@ from typing import Any, Callable, List, Union, Optional from time import perf_counter import traceback -from inspect import signature, isfunction, ismethod +from inspect import signature import threading from deepeval.utils import dataclass_to_dict @@ -26,10 +26,6 @@ class TraceStatus(Enum): @dataclass class LlmMetadata: model: str - inputTokenUsage: int - outputTokenUsage: int - cost: float - @dataclass class EmbeddingMetadata: @@ -102,8 +98,6 @@ def trace( type: str, name: Optional[str] = None, model: Optional[str] = None, - characters_per_token: Optional[Union[float, int]] = None, - cost_per_token: Optional[float] = None, ): assert isinstance( type, Union[TraceType, str] @@ -120,29 +114,6 @@ def trace( f"Parameter 'model' should not be provided for {type} trace types." ) - if type == TraceType.LLM and characters_per_token is None: - raise ValueError( - "LLM trace type requires 'characters_per_token' as a parameters." - ) - assert characters_per_token is None or isinstance( - characters_per_token, Union[float, int] - ), "'characters_per_token' must be an int, float or None" - - if type == TraceType.LLM and cost_per_token is None: - raise ValueError( - "LLM trace type requires 'cost_per_token' as a parameters." - ) - assert cost_per_token is None or isinstance( - cost_per_token, Union[int, float] - ), "'cost_per_token' must be an int, float or None" - - if type != TraceType.LLM and ( - characters_per_token is not None or cost_per_token is not None - ): - raise ValueError( - "Parameters 'characters_per_token' and 'cost_per_token' should not be provided for non-LLM trace types." - ) - def decorator_trace(func: Callable): if type == TraceType.LLM: sig = signature(func) @@ -152,10 +123,10 @@ def decorator_trace(func: Callable): if any(p.name in ["self", "cls"] for p in params): params = [p for p in params if p.name not in ["self", "cls"]] - # There should be exactly one parameter left of type str + # There should be exactly one parameter left of type list[str] if len(params) != 1: raise ValueError( - "Function of type `TraceType.LLM` must have exactly one parameter of type str" + "Function of type `TraceType.LLM` must have exactly one parameter of type 'list[str]'" ) @wraps(func) @@ -200,7 +171,7 @@ def wrapper(*args, **kwargs): output=None, status=TraceStatus.SUCCESS, traces=[], - llmMetadata=None, + llmMetadata=LlmMetadata(model=model), ) elif type == TraceType.EMBEDDING: trace_instance = EmbeddingTrace( @@ -230,22 +201,6 @@ def wrapper(*args, **kwargs): result = func(*args, **kwargs) trace_instance.output = result - if type == TraceType.LLM: - if not isinstance(trace_instance.output, str): - raise ValueError( - "Methods/functions of type 'TraceType.LLM' must return only a string" - ) - - input_token_usage = len(input_str) * characters_per_token - output_token_usage = len(result) * characters_per_token - trace_instance.llmMetadata = LlmMetadata( - model=model, - inputTokenUsage=input_token_usage, - outputTokenUsage=output_token_usage, - cost=(input_token_usage + output_token_usage) - * cost_per_token, - ) - except Exception as e: trace_instance.status = TraceStatus.ERROR trace_instance.output = { @@ -279,5 +234,9 @@ def wrapper(*args, **kwargs): return decorator_trace +def set_token_usage(tokens: int): + pass + + def get_trace_stack(): return trace_manager.get_and_reset_dict_trace_stack() diff --git a/docs/docs/evaluation-metrics.mdx b/docs/docs/evaluation-metrics.mdx index 90503dcf5..c3de9da05 100644 --- a/docs/docs/evaluation-metrics.mdx +++ b/docs/docs/evaluation-metrics.mdx @@ -298,7 +298,7 @@ input = "What if these shoes don't fit?" actual_output = "We offer a 30-day full refund at no extra cost." unbias_metric = UnBiasedMetric( - evaluation_metrics=[LLMTestCaseParams.ACTUAL_OUTPUT], + evaluation_params=[LLMTestCaseParams.ACTUAL_OUTPUT], minimum_score=0.7 ) diff --git a/docs/docs/evaluation-tracing.mdx b/docs/docs/evaluation-tracing.mdx index b1e53fb8e..4fd889500 100644 --- a/docs/docs/evaluation-tracing.mdx +++ b/docs/docs/evaluation-tracing.mdx @@ -6,19 +6,60 @@ sidebar_label: Tracing ## Quick Summary -Often times when a test case is failing you're not sure which compopnent of your RAG/agent-based application is the issue. Tracing in the context of evaluating LLM applications provides a quick and easy way for you to identify why certain test cases are failing on specific metrics. From chunking to embedding, and retrieval to generation, tracing allows you to debug your LLM application at a component level. +Tracing in the context of evaluating LLM applications provides a quick and easy way for you to identify why certain test cases are failing on specific metrics. From chunking to embedding, retrieval to generation, tracing allows you to debug your LLM application pipeline at a component level. -## Tracing on Confident AI +![ok](https://d2lsxfc3p6r9rv.cloudfront.net/tracing.png) -To start tracing your LLM application for each test case, login to Confident AI. +## Trace Decorator +The `@trace` decorator is a decorator offered by `deepeval` for you to easily track the input and outputs of different components in your retrieval pipeline that make up your LLM application. The `@trace` decorator accepts three arguments: `type`, `name`, and `model`. + +### Trace Type + +The `type` parameter is an easy way for you to classify components in your pipeline and can either be of type `TraceType`, or `str` (for custom types). Here are all the `TraceType` `deepeval` offers: + +- `TraceType.LLM` +- `TraceType.Retriver` +- `TraceType.Embedding` +- `TraceType.Tool` +- `TraceType.Agent` +- `TraceType.Chain` + +```python +from deepeval.tracing import TraceType + +@trace(type=TraceType.LLM, ...) +def llm(messages): + ... ``` -deepeval login + +### Trace Name + +The `name` parameter is optional and defaults to the function/method name if left blank. It has no functionality other than providing you a way to distinguish between different functions/methods decorated with the same trace type. + +```python +from deepeval.tracing import TraceType + +@trace(type=TraceType.LLM, name="OpenAI", ...) +def llm(messages): + ... +``` + +### Trace Model + +The `model` parameter is only required for when the trace type is either `TraceType.LLM` or `TraceType.EMBEDDING`. It expects a string which should be the name of the model you're currently using. + +```python +from deepeval.tracing import TraceType + +@trace(type=TraceType.LLM, name="OpenAI", model="gpt-4") +def llm(messages): + ... ``` -Follow the instructions displayed on the CLI to create an account, get your Confident API key, and paste it in the CLI. +## Setup Tracing -Once you're logged in, navigate to where you've implemented your LLM application, and import the `trace` decorator from `deepeval.tracing`. Here's a sample implementation for a hypothetical LLM application utilizing `deepeval`'s tracing module. +Import the `@trace` decorator from `deepeval.tracing` and apply it to functions/methods that make up your LLM pipeline. Here's an implementation for a hypothetical LLM application utilizing `deepeval`'s tracing module. ```python title="test_chatbot.py" from deepeval.tracing import trace, TraceType @@ -28,8 +69,8 @@ class Chatbot: def __init__(self): pass - @trace(type=TraceType.LLM, name="OpenAI", model="gpt-4", characters_per_token=4, cost_per_token=0.000003) - def llm(self, input=input): + @trace(type=TraceType.LLM, name="OpenAI", model="gpt-4") + def llm(self, input): response = openai.ChatCompletion.create( model="gpt-4", messages=[ @@ -37,59 +78,95 @@ class Chatbot: "role": "system", "content": "You are a helpful assistant.", }, - {"role": "user", "content": prompt}, + {"role": "user", "content": input}, ], ) return response.choices[0].message.content @trace(type=TraceType.EMBEDDING, name="Embedding", model="text-embedding-ada-002") - def get_embedding(input): + def get_embedding(self, input): response = openai.Embedding.create( input=input, model="text-embedding-ada-002" ) - embeddings = response['data'][0]['embedding'] + return response['data'][0]['embedding'] @trace(type=TraceType.RETRIEVER, name="Retriever") def retriever(self, input=input): embedding = self.get_embedding(input) - list_of_retrieved_nodes = some_function_that_searches_your_vector_db(embedding) + # Replace this with an actual vector search that uses embedding + list_of_retrieved_nodes = ["Retrieval Node 1", "Retrieval Node 2"] return list_of_retrieved_nodes @trace(type=TraceType.TOOL, name="Search") def search(self, input): - title_of_the_top_search_results = some_function_that_searches_the_web(input) + # Replace this with an actual function that searches the web + title_of_the_top_search_results = "Search Result: " + input return title_of_the_top_search_results - + @trace(type=TraceType.TOOL, name="Format") def format(self, retrieval_nodes, input): - prompt = "You are a helpful assistant, based on the following information: " + prompt = "You are a helpful assistant, based on the following information: \n" for node in retrieval_nodes: prompt += node + "\n" - prompt += "Generate an unbiased response for" + input + "." + prompt += "Generate an unbiased response for " + input + "." return prompt - - @query(input): - top_result_title = search(input) - retrieval_results = retriever(top_result) - prompt = format(retrieval_results, top_result_title) - return llm(prompt) - -chatbot = Chatbot() -chatbot.query("What are some nice tourist attractions in San Francisco?") + @trace(type=TraceType.AGENT, name="Chatbot") + def query(self, user_input=input): + top_result_title = self.search(user_input) + retrieval_results = self.retriever(top_result_title) + prompt = self.format(retrieval_results, top_result_title) + return self.llm(prompt) ``` -In this example, `chatbot.query()` first searches the web for the top tourist attraction, before using this information to retrieve information stored in a vector database. This is then all combined into a single prompt and fed into the `gpt-4` LLM. With this setup, all traces will automatically be logged each time you run `deepeval test run`. This will allow you to debug each failing test case, and here's what a trace stack looks like on Confident AI. +Applying the `@trace` decorator will automatically log LLM traces each time `chatbot.query()` is called during `deepeval test run`. This will allow you to debug failing test cases by inspecting individual trace stacks on Confident AI. -[insert image of mock] +## Log Your First Trace -Lastly, let's write some test cases to put everything in action. Continuning from the previous code snippet: +Continuning from the previous code snippet where you've defined your `Chatbot` class, paste in the following test case to evaluate whether your LLM application is outputting factually correct answers. ```python title="test_chatbot.py" ... +import pytest +from deepeval.test_case import LLMTestCase +from deepeval.metrics.factual_consistency import FactualConsistencyMetric +from deepeval.run_test import assert_test + +chatbot = Chatbot() + +def test_factual_consistency(): + context = [ + "Be a natural-born citizen of the United States.", + "Be at least 35 years old.", + "Have been a resident of the United States for 14 years." + ] + input = "What are the requimrents to be president?" + + metric = FactualConsistencyMetric(minimum_score=0.8) + test_case = LLMTestCase( + input=input, + actual_output=chatbot.query(user_input=input), + context=context, + ) + assert_test(test_case, [metric]) +``` + +[Login to Confident AI](https://app.confident-ai.com/login) to start tracing your LLM application for each test case. ``` +deepeval login +``` + +Follow the instructions displayed on the CLI to create an account, get your Confident API key, and paste it in the CLI. Once you're logged in, run `deepeval test run`: + +``` +deepeval test run test_chatbot.py +``` + +You should see the test case has failed, but that' ok because it's meant to fail. Paste the link returned from the CLI into the same browser you logged in with to view and debug why your test case failed. + +![ok](https://d2lsxfc3p6r9rv.cloudfront.net/confident-tracing.gif) diff --git a/docs/docs/getting-started.mdx b/docs/docs/getting-started.mdx index c84debaec..a94ec2480 100644 --- a/docs/docs/getting-started.mdx +++ b/docs/docs/getting-started.mdx @@ -221,6 +221,11 @@ class Dataset: Utilize the `@pytest.mark.parametrize` decorator to loop through and evaluate your entire evaluation dataset. ```python title="test_bulk.py" +import pytest +from deepeval.metrics.factual_consistency import FactualConsistencyMetric +from deepeval.test_case import LLMTestCase +from deepeval.run_test import assert_test + dataset = [ { "input": "What are your operating hours?", diff --git a/docs/sidebars.js b/docs/sidebars.js index 842753eb6..5888e21b4 100644 --- a/docs/sidebars.js +++ b/docs/sidebars.js @@ -16,7 +16,7 @@ module.exports = { 'evaluation-test-cases', 'evaluation-metrics', 'evaluation-datasets', - // 'evaluation-tracing', + 'evaluation-tracing', ], collapsed: false, }, diff --git a/examples/tracing/test_chatbot.py b/examples/tracing/test_chatbot.py new file mode 100644 index 000000000..6e0892e4e --- /dev/null +++ b/examples/tracing/test_chatbot.py @@ -0,0 +1,81 @@ +from deepeval.tracing import trace, TraceType +import openai + +class Chatbot: + def __init__(self): + pass + + @trace(type=TraceType.LLM, name="OpenAI", model="gpt-4") + def llm(self, input): + response = openai.ChatCompletion.create( + model="gpt-4", + messages=[ + { + "role": "system", + "content": "You are a helpful assistant.", + }, + {"role": "user", "content": input}, + ], + ) + return response.choices[0].message.content + + @trace(type=TraceType.EMBEDDING, name="Embedding", model="text-embedding-ada-002") + def get_embedding(self, input): + response = openai.Embedding.create( + input=input, + model="text-embedding-ada-002" + ) + return response['data'][0]['embedding'] + + @trace(type=TraceType.RETRIEVER, name="Retriever") + def retriever(self, input=input): + embedding = self.get_embedding(input) + + # Replace this with an actual vector search that uses embedding + list_of_retrieved_nodes = ["Retrieval Node 1", "Retrieval Node 2"] + return list_of_retrieved_nodes + + @trace(type=TraceType.TOOL, name="Search") + def search(self, input): + # Replace this with an actual function that searches the web + title_of_the_top_search_results = "Search Result: " + input + return title_of_the_top_search_results + + + @trace(type=TraceType.TOOL, name="Format") + def format(self, retrieval_nodes, input): + prompt = "You are a helpful assistant, based on the following information: \n" + for node in retrieval_nodes: + prompt += node + "\n" + prompt += "Generate an unbiased response for " + input + "." + return prompt + + @trace(type=TraceType.AGENT, name="Chatbot") + def query(self, user_input=input): + top_result_title = self.search(user_input) + retrieval_results = self.retriever(top_result_title) + prompt = self.format(retrieval_results, top_result_title) + return self.llm(prompt) + +import pytest +from deepeval.test_case import LLMTestCase +from deepeval.metrics.factual_consistency import FactualConsistencyMetric +from deepeval.run_test import assert_test + +chatbot = Chatbot() + +def test_factual_consistency(): + context = [ + "Be a natural-born citizen of the United States.", + "Be at least 35 years old.", + "Have been a resident of the United States for 14 years." + ] + input = "What are the requimrents to be president?" + + metric = FactualConsistencyMetric(minimum_score=0.8) + test_case = LLMTestCase( + input=input, + actual_output=chatbot.query(user_input=input), + context=context, + ) + assert_test(test_case, [metric]) \ No newline at end of file From 6aa92306081e5805b269192aa4085b9c6c4754c7 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Mon, 6 Nov 2023 19:02:50 -0800 Subject: [PATCH 10/38] update docs --- docs/docs/evaluation-tracing.mdx | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/docs/docs/evaluation-tracing.mdx b/docs/docs/evaluation-tracing.mdx index 4fd889500..cff4b3932 100644 --- a/docs/docs/evaluation-tracing.mdx +++ b/docs/docs/evaluation-tracing.mdx @@ -170,3 +170,7 @@ deepeval test run test_chatbot.py You should see the test case has failed, but that' ok because it's meant to fail. Paste the link returned from the CLI into the same browser you logged in with to view and debug why your test case failed. ![ok](https://d2lsxfc3p6r9rv.cloudfront.net/confident-tracing.gif) + +## Full Example + +You can find the full example [here on our Github](https://github.com/confident-ai/deepeval/blob/main/examples/tracing/test_chatbot.py). From 733c5c11f4c1d5061aadf536a78ee43bdb95385c Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Mon, 6 Nov 2023 19:07:54 -0800 Subject: [PATCH 11/38] formatting --- deepeval/tracing.py | 1 + examples/tracing/test_chatbot.py | 39 ++++++++++++++++++-------------- 2 files changed, 23 insertions(+), 17 deletions(-) diff --git a/deepeval/tracing.py b/deepeval/tracing.py index 4adc327bb..24813cc66 100644 --- a/deepeval/tracing.py +++ b/deepeval/tracing.py @@ -27,6 +27,7 @@ class TraceStatus(Enum): class LlmMetadata: model: str + @dataclass class EmbeddingMetadata: model: str diff --git a/examples/tracing/test_chatbot.py b/examples/tracing/test_chatbot.py index 6e0892e4e..b8bab945b 100644 --- a/examples/tracing/test_chatbot.py +++ b/examples/tracing/test_chatbot.py @@ -1,6 +1,7 @@ from deepeval.tracing import trace, TraceType import openai + class Chatbot: def __init__(self): pass @@ -8,24 +9,27 @@ def __init__(self): @trace(type=TraceType.LLM, name="OpenAI", model="gpt-4") def llm(self, input): response = openai.ChatCompletion.create( - model="gpt-4", - messages=[ - { - "role": "system", - "content": "You are a helpful assistant.", - }, - {"role": "user", "content": input}, - ], - ) + model="gpt-4", + messages=[ + { + "role": "system", + "content": "You are a helpful assistant.", + }, + {"role": "user", "content": input}, + ], + ) return response.choices[0].message.content - @trace(type=TraceType.EMBEDDING, name="Embedding", model="text-embedding-ada-002") + @trace( + type=TraceType.EMBEDDING, + name="Embedding", + model="text-embedding-ada-002", + ) def get_embedding(self, input): response = openai.Embedding.create( - input=input, - model="text-embedding-ada-002" + input=input, model="text-embedding-ada-002" ) - return response['data'][0]['embedding'] + return response["data"][0]["embedding"] @trace(type=TraceType.RETRIEVER, name="Retriever") def retriever(self, input=input): @@ -41,7 +45,6 @@ def search(self, input): title_of_the_top_search_results = "Search Result: " + input return title_of_the_top_search_results - @trace(type=TraceType.TOOL, name="Format") def format(self, retrieval_nodes, input): prompt = "You are a helpful assistant, based on the following information: \n" @@ -56,7 +59,8 @@ def query(self, user_input=input): retrieval_results = self.retriever(top_result_title) prompt = self.format(retrieval_results, top_result_title) return self.llm(prompt) - + + import pytest from deepeval.test_case import LLMTestCase from deepeval.metrics.factual_consistency import FactualConsistencyMetric @@ -64,11 +68,12 @@ def query(self, user_input=input): chatbot = Chatbot() + def test_factual_consistency(): context = [ "Be a natural-born citizen of the United States.", "Be at least 35 years old.", - "Have been a resident of the United States for 14 years." + "Have been a resident of the United States for 14 years.", ] input = "What are the requimrents to be president?" @@ -78,4 +83,4 @@ def test_factual_consistency(): actual_output=chatbot.query(user_input=input), context=context, ) - assert_test(test_case, [metric]) \ No newline at end of file + assert_test(test_case, [metric]) From 1fcc02ec5bead5f0d7431f36e1f2b8846a90e4d3 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Mon, 6 Nov 2023 19:30:19 -0800 Subject: [PATCH 12/38] new release --- deepeval/_version.py | 2 +- pyproject.toml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/deepeval/_version.py b/deepeval/_version.py index c0f8c2c5c..5bc41e70c 100644 --- a/deepeval/_version.py +++ b/deepeval/_version.py @@ -1 +1 @@ -__version__: str = "0.20.15" +__version__: str = "0.20.16" diff --git a/pyproject.toml b/pyproject.toml index 404e794e9..73526d3dd 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "deepeval" -version = "0.20.15" +version = "0.20.16" description = "The Evaluation Framework for LLMs" authors = ["Jeffrey Ip "] license = "Apache-2.0" From 522536a0fea5da26cd0715138e61b65f586a40e0 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Wed, 8 Nov 2023 22:17:36 -0800 Subject: [PATCH 13/38] updated docs --- docs/docs/evaluation-metrics.mdx | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/docs/docs/evaluation-metrics.mdx b/docs/docs/evaluation-metrics.mdx index c3de9da05..a031fd5d5 100644 --- a/docs/docs/evaluation-metrics.mdx +++ b/docs/docs/evaluation-metrics.mdx @@ -48,16 +48,18 @@ summarization_metric = LLMEvalMetric( name="Summarization", criteria="Summarization - determine if the actual output is an accurate and concise summarization of the input.", evaluation_params=[LLMTestCaseParams.INPUT, LLMTestCaseParams.ACTUAL_OUTPUT], - minimum_score=0.5 + minimum_score=0.5, + model="gpt-4" ) ``` -There are three mandatory and one optional parameters required when instantiating an `LLMEvalMetric` class: +There are three mandatory and two optional parameters required when instantiating an `LLMEvalMetric` class: - `name`: name of metric - `criteria`: a description outlining the specific evaluation aspects for each test case. - `evaluation_params`: a list of type `LLMTestCaseParams`. Include only the parameters that are relevant for evaluation. -- [Optional] `minimum_score` +- [Optional] `minimum_score`: the passing threshold +- [Optional] `model`: the model name. This is defaulted to 'gpt-4' and we currently only support models from OpenAI. All instances of `LLMEvalMetric` returns a score ranging from 0 - 1. A metric is only successful if the evaluation score is equal to or greater than `minimum_score`. From 2d97e38e06793282038028a9dc036088ecb1f4f9 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Thu, 9 Nov 2023 02:04:36 -0800 Subject: [PATCH 14/38] fix bulk --- deepeval/api.py | 57 +++++++++++++++++++++++++++---------------------- 1 file changed, 32 insertions(+), 25 deletions(-) diff --git a/deepeval/api.py b/deepeval/api.py index 758a0a606..b06bc61a2 100644 --- a/deepeval/api.py +++ b/deepeval/api.py @@ -8,7 +8,7 @@ from typing import Any, Optional from pydantic import BaseModel, Field -from typing import List +from typing import List, Dict from requests.adapters import HTTPAdapter, Response, Retry from deepeval.constants import ( @@ -119,9 +119,13 @@ class TestRun(BaseModel): "test.py", alias="testFile", ) + dict_test_cases: Dict[int, APITestCase] = Field( + default_factory=dict, + ) test_cases: List[APITestCase] = Field( alias="testCases", default_factory=lambda: [] ) + metric_scores: List[MetricScore] = Field( default_factory=lambda: [], alias="metricScores" ) @@ -135,9 +139,9 @@ def add_llm_test_case( ): # Check if test case with the same ID already exists # TODO: bug for pytest batch runs - unable to find test case name - existing_test_case: APITestCase = next( - (tc for tc in self.test_cases if tc.name == test_case.__name__), - None, + test_case_id = id(test_case) + existing_test_case: APITestCase = self.dict_test_cases.get( + test_case_id, None ) metrics_metadata_dict = MetricsMetadataAverageDict() @@ -147,40 +151,43 @@ def add_llm_test_case( success = all([metric.is_successful() for metric in metrics]) if existing_test_case: + # BUG: this is a workaround, loop shouldn't be needed + existing_test_case = next( + (tc for tc in self.test_cases if tc == existing_test_case), + existing_test_case, + ) + # If it exists, append the metrics to the existing test case existing_test_case.metrics_metadata.extend(metrics_metadata) + # Update the success status - existing_test_case.success = success and existing_test_case.success + existing_test_case.success = success else: # If it doesn't exist, create a new test case # Adding backwards compatibility to ensure context still works. context = test_case.context if isinstance(context, str): context = [context] - self.test_cases.append( - APITestCase( - # Get the test from the pytest plugin - name=os.getenv(PYTEST_RUN_TEST_NAME, "-"), - input=test_case.input, - actualOutput=test_case.actual_output, - expectedOutput=test_case.expected_output, - success=success, - metricsMetadata=metrics_metadata, - runDuration=run_duration, - context=context, - traceStack=get_trace_stack(), - ) + api_test_case: APITestCase = APITestCase( + # Get the test from the pytest plugin + name=os.getenv(PYTEST_RUN_TEST_NAME, "-"), + input=test_case.input, + actualOutput=test_case.actual_output, + expectedOutput=test_case.expected_output, + success=success, + metricsMetadata=metrics_metadata, + runDuration=run_duration, + context=context, + traceStack=get_trace_stack(), ) - all_metric_dict = MetricDict() + self.dict_test_cases[test_case_id] = api_test_case + self.test_cases.append(api_test_case) + all_metric_dict = MetricDict() for test_case in self.test_cases: - test_case: APITestCase - metrics = test_case.metrics_metadata - for metric in metrics: - metric: MetricsMetadata + for metric in test_case.metrics_metadata: all_metric_dict.add_metric(metric.metric, metric.score) - self.metric_scores = all_metric_dict.get_average_metric_score() def save(self, file_path: Optional[str] = None): @@ -193,7 +200,6 @@ def save(self, file_path: Optional[str] = None): file_path = f"{file_path}.json" with open(file_path, "w") as f: json.dump(self.dict(by_alias=True, exclude_none=True), f) - return file_path @classmethod @@ -461,6 +467,7 @@ def quote_string(text: str) -> str: def post_test_run(self, test_run: TestRun) -> TestRunResponse: """Post a test run""" + del test_run.dict_test_cases try: # make sure to exclude none for `context` to ensure it is handled properly body = test_run.model_dump(by_alias=True, exclude_none=True) From e2623c150e791c0391502101ea5913e9b564a331 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Fri, 10 Nov 2023 16:54:58 -0800 Subject: [PATCH 15/38] Added bulk testing --- deepeval/api.py | 202 +--------------------- deepeval/dataset.py | 2 +- deepeval/{run_test.py => evaluator.py} | 77 +++------ deepeval/metrics/answer_relevancy.py | 2 +- deepeval/metrics/bias_classifier.py | 2 +- deepeval/metrics/conceptual_similarity.py | 2 +- deepeval/metrics/factual_consistency.py | 2 +- deepeval/metrics/overall_score.py | 2 +- deepeval/metrics/ragas_metric.py | 20 +-- deepeval/metrics/ranking_similarity.py | 2 +- deepeval/metrics/toxic_classifier.py | 2 +- deepeval/plugins/plugin.py | 18 +- deepeval/test_case.py | 5 +- deepeval/test_quickstart.py | 2 +- deepeval/test_run.py | 185 ++++++++++++++++++++ docs/docusaurus.config.js | 4 +- docs/yarn.lock | 182 ------------------- examples/getting_started/test_example.py | 2 +- examples/tracing/test_chatbot.py | 2 +- tests/test_answer_relevancy.py | 2 +- tests/test_bias.py | 2 +- tests/test_chatbot_example.py | 2 +- tests/test_custom_metric.py | 2 +- tests/test_factual_consistency.py | 18 +- tests/test_llm_metric.py | 4 +- tests/test_overall_score.py | 12 +- tests/test_quickstart.py | 2 +- tests/test_ragas.py | 2 +- tests/test_result.py | 2 +- tests/test_similar_ranking.py | 2 +- tests/test_toxic.py | 2 +- 31 files changed, 279 insertions(+), 488 deletions(-) rename deepeval/{run_test.py => evaluator.py} (67%) create mode 100644 deepeval/test_run.py diff --git a/deepeval/api.py b/deepeval/api.py index b06bc61a2..edf52f724 100644 --- a/deepeval/api.py +++ b/deepeval/api.py @@ -2,27 +2,14 @@ import platform import urllib.parse import requests -import json import warnings -from collections import defaultdict - -from typing import Any, Optional -from pydantic import BaseModel, Field -from typing import List, Dict +from pydantic import BaseModel from requests.adapters import HTTPAdapter, Response, Retry - -from deepeval.constants import ( - API_KEY_ENV, - PYTEST_RUN_ENV_VAR, - PYTEST_RUN_TEST_NAME, -) +from deepeval.test_run import TestRun +from deepeval.constants import API_KEY_ENV from deepeval.key_handler import KEY_FILE_HANDLER -from deepeval.metrics.base_metric import BaseMetric -from deepeval.test_case import LLMTestCase -from deepeval.tracing import TraceData, get_trace_stack API_BASE_URL = "https://app.confident-ai.com/api" -# API_BASE_URL = "http://localhost:3000/api" # Parameters for HTTP retry HTTP_TOTAL_RETRIES = 3 # Number of total retries @@ -31,188 +18,12 @@ HTTP_RETRY_ALLOWED_METHODS = frozenset({"GET", "POST", "DELETE"}) -class MetricsMetadata(BaseModel): - metric: str - score: float - minimum_score: float = Field(None, alias="minimumScore") - - -class APITestCase(BaseModel): - name: str - input: str - actual_output: str = Field(..., alias="actualOutput") - expected_output: Optional[str] = Field(None, alias="expectedOutput") - success: bool - metrics_metadata: List[MetricsMetadata] = Field( - ..., alias="metricsMetadata" - ) - run_duration: float = Field(..., alias="runDuration") - context: Optional[list] = Field(None) - traceStack: Optional[dict] = Field(None) - - -class MetricScore(BaseModel): - metric: str - score: float - - @classmethod - def from_metric(cls, metric: BaseMetric): - return cls(metric=metric.__name__, score=metric.score) - - class TestRunResponse(BaseModel): """Add Test Run Results""" testRunId: str projectId: str - - -class MetricDict: - def __init__(self): - self.metric_dict = {} - self.metric_count = {} - - def add_metric(self, metric_name, score): - if metric_name not in self.metric_dict: - self.metric_dict[metric_name] = score - self.metric_count[metric_name] = 1 - else: - self.metric_dict[metric_name] += score - self.metric_count[metric_name] += 1 - - def get_average_metric_score(self): - return [ - MetricScore( - metric=metric, - score=self.metric_dict[metric] / self.metric_count[metric], - ) - for metric in self.metric_dict - ] - - -class MetricsMetadataAverageDict: - def __init__(self): - self.metric_dict = defaultdict(list) - self.min_score_dict = defaultdict(float) - - def add_metric(self, metric: BaseMetric): - self.metric_dict[metric.__name__].append(metric.score) - self.min_score_dict[metric.__name__] = min( - self.min_score_dict.get(metric.__name__, float("inf")), - metric.minimum_score, - ) - - def get_metrics_metadata(self): - return [ - MetricsMetadata( - metric=metric_name, - score=sum(scores) / len(scores), - minimumScore=self.min_score_dict[metric_name], - ) - for metric_name, scores in self.metric_dict.items() - ] - - -class TestRun(BaseModel): - test_file: Optional[str] = Field( - # TODO: Fix test_file - "test.py", - alias="testFile", - ) - dict_test_cases: Dict[int, APITestCase] = Field( - default_factory=dict, - ) - test_cases: List[APITestCase] = Field( - alias="testCases", default_factory=lambda: [] - ) - - metric_scores: List[MetricScore] = Field( - default_factory=lambda: [], alias="metricScores" - ) - configurations: dict - - def add_llm_test_case( - self, - test_case: LLMTestCase, - metrics: List[BaseMetric], - run_duration: float, - ): - # Check if test case with the same ID already exists - # TODO: bug for pytest batch runs - unable to find test case name - test_case_id = id(test_case) - existing_test_case: APITestCase = self.dict_test_cases.get( - test_case_id, None - ) - - metrics_metadata_dict = MetricsMetadataAverageDict() - for metric in metrics: - metrics_metadata_dict.add_metric(metric) - metrics_metadata = metrics_metadata_dict.get_metrics_metadata() - success = all([metric.is_successful() for metric in metrics]) - - if existing_test_case: - # BUG: this is a workaround, loop shouldn't be needed - existing_test_case = next( - (tc for tc in self.test_cases if tc == existing_test_case), - existing_test_case, - ) - - # If it exists, append the metrics to the existing test case - existing_test_case.metrics_metadata.extend(metrics_metadata) - - # Update the success status - existing_test_case.success = success - else: - # If it doesn't exist, create a new test case - # Adding backwards compatibility to ensure context still works. - context = test_case.context - if isinstance(context, str): - context = [context] - api_test_case: APITestCase = APITestCase( - # Get the test from the pytest plugin - name=os.getenv(PYTEST_RUN_TEST_NAME, "-"), - input=test_case.input, - actualOutput=test_case.actual_output, - expectedOutput=test_case.expected_output, - success=success, - metricsMetadata=metrics_metadata, - runDuration=run_duration, - context=context, - traceStack=get_trace_stack(), - ) - - self.dict_test_cases[test_case_id] = api_test_case - self.test_cases.append(api_test_case) - - all_metric_dict = MetricDict() - for test_case in self.test_cases: - for metric in test_case.metrics_metadata: - all_metric_dict.add_metric(metric.metric, metric.score) - self.metric_scores = all_metric_dict.get_average_metric_score() - - def save(self, file_path: Optional[str] = None): - if file_path is None: - file_path = os.getenv(PYTEST_RUN_ENV_VAR) - # If file Path is None, remove it - if not file_path: - return - elif not file_path.endswith(".json"): - file_path = f"{file_path}.json" - with open(file_path, "w") as f: - json.dump(self.dict(by_alias=True, exclude_none=True), f) - return file_path - - @classmethod - def load(cls, file_path: Optional[str] = None): - if file_path is None: - file_path = os.getenv(PYTEST_RUN_ENV_VAR) - # If file Path is None, remove it - if not file_path: - return - elif not file_path.endswith(".json"): - file_path = f"{file_path}.json" - with open(file_path, "r") as f: - return cls(**json.load(f)) + link: str class Api: @@ -467,7 +278,6 @@ def quote_string(text: str) -> str: def post_test_run(self, test_run: TestRun) -> TestRunResponse: """Post a test run""" - del test_run.dict_test_cases try: # make sure to exclude none for `context` to ensure it is handled properly body = test_run.model_dump(by_alias=True, exclude_none=True) @@ -480,6 +290,8 @@ def post_test_run(self, test_run: TestRun) -> TestRunResponse: body=body, ) response = TestRunResponse( - testRunId=result["testRunId"], projectId=result["projectId"] + testRunId=result["testRunId"], + projectId=result["projectId"], + link=result["link"], ) return response diff --git a/deepeval/dataset.py b/deepeval/dataset.py index 92243138c..4433fe27b 100644 --- a/deepeval/dataset.py +++ b/deepeval/dataset.py @@ -9,7 +9,7 @@ from tabulate import tabulate -from deepeval.run_test import run_test +from deepeval.evaluator import run_test from deepeval.metrics.base_metric import BaseMetric from deepeval.test_case import LLMTestCase from dataclasses import asdict diff --git a/deepeval/run_test.py b/deepeval/evaluator.py similarity index 67% rename from deepeval/run_test.py rename to deepeval/evaluator.py index b4cf97ce6..00f590382 100644 --- a/deepeval/run_test.py +++ b/deepeval/evaluator.py @@ -13,7 +13,7 @@ from .get_api_key import _get_api_key from .metrics import BaseMetric from .test_case import LLMTestCase, TestCase -from .api import TestRun +from deepeval.test_run import test_run_manager, TestRun def _is_api_key_set(): @@ -104,67 +104,40 @@ def run_test( min_success: int = 1, raise_error: bool = False, ) -> List[TestResult]: - """ - Args: - test_cases: Either a single test case or a list of test cases to run - metrics: List of metrics to run - raise_error: Whether to raise an error if a metric fails - max_retries: Maximum number of retries for each metric measurement - delay: Delay in seconds between retries - min_success: Minimum number of successful measurements required - - Example: - >>> from deepeval.metrics.facutal_consistency import FactualConsistencyMetric - >>> from deepeval.test_case import LLMTestCase - >>> from deepeval.run_test import run_test - >>> metric = FactualConsistencyMetric() - >>> test_case = LLMTestCase( - ... input="What is the capital of France?", - ... actual_output="Paris", - ... expected_output="Paris", - ... context="Geography", - ... ) - >>> run_test(test_case, metric) - """ if isinstance(test_cases, TestCase): test_cases = [test_cases] test_results = [] + test_run = test_run_manager.get_test_run() for test_case in test_cases: failed_metrics = [] for metric in metrics: test_start_time = time.perf_counter() - @retry( - max_retries=max_retries, - delay=delay, - min_success=min_success, - ) - def measure_metric(): - score = metric.measure(test_case) - success = metric.is_successful() - test_result = create_test_result( - test_case, success, score, metric + # @retry( + # max_retries=max_retries, + # delay=delay, + # min_success=min_success, + # ) + # def measure_metric(): + score = metric.measure(test_case) + success = metric.is_successful() + test_result = create_test_result(test_case, success, score, metric) + test_results.append(test_result) + + # Load the test_run and add the test_case regardless of the success of the test + test_end_time = time.perf_counter() + run_duration = test_end_time - test_start_time + if os.getenv(PYTEST_RUN_ENV_VAR): + metric.score = score + test_run.add_llm_test_case( + test_case=test_case, + metrics=[metric], + run_duration=run_duration, ) - test_results.append(test_result) - - # Load the test_run and add the test_case regardless of the success of the test - test_end_time = time.perf_counter() - run_duration = test_end_time - test_start_time - if os.getenv(PYTEST_RUN_ENV_VAR): - test_run = TestRun.load() - metric.score = score - test_run.add_llm_test_case( - test_case=test_case, - metrics=[metric], - run_duration=run_duration, - ) - test_run.save() - - if not success: - failed_metrics.append((metric.__name__, score)) - - measure_metric() + + if not success: + failed_metrics.append((metric.__name__, score)) if raise_error and failed_metrics: raise AssertionError( diff --git a/deepeval/metrics/answer_relevancy.py b/deepeval/metrics/answer_relevancy.py index 96247dd2b..a26f3c3c2 100644 --- a/deepeval/metrics/answer_relevancy.py +++ b/deepeval/metrics/answer_relevancy.py @@ -1,6 +1,6 @@ from deepeval.singleton import Singleton from deepeval.test_case import LLMTestCase -from deepeval.run_test import assert_test +from deepeval.evaluator import assert_test from deepeval.metrics.base_metric import BaseMetric import numpy as np diff --git a/deepeval/metrics/bias_classifier.py b/deepeval/metrics/bias_classifier.py index 329b66e5a..3eb7430ab 100644 --- a/deepeval/metrics/bias_classifier.py +++ b/deepeval/metrics/bias_classifier.py @@ -10,7 +10,7 @@ from deepeval.metrics.base_metric import BaseMetric from ..test_case import LLMTestCase -from ..run_test import assert_test +from ..evaluator import assert_test class UnBiasedMetric(BaseMetric): diff --git a/deepeval/metrics/conceptual_similarity.py b/deepeval/metrics/conceptual_similarity.py index 895f665ec..aefb6034f 100644 --- a/deepeval/metrics/conceptual_similarity.py +++ b/deepeval/metrics/conceptual_similarity.py @@ -5,7 +5,7 @@ from deepeval.singleton import Singleton from deepeval.test_case import LLMTestCase from deepeval.utils import cosine_similarity -from deepeval.run_test import assert_test +from deepeval.evaluator import assert_test from deepeval.progress_context import progress_context from deepeval.metrics.base_metric import BaseMetric diff --git a/deepeval/metrics/factual_consistency.py b/deepeval/metrics/factual_consistency.py index 39a15a353..3b61fb59b 100644 --- a/deepeval/metrics/factual_consistency.py +++ b/deepeval/metrics/factual_consistency.py @@ -3,7 +3,7 @@ from deepeval.test_case import LLMTestCase from deepeval.utils import chunk_text, softmax from deepeval.metrics.base_metric import BaseMetric -from deepeval.run_test import assert_test +from deepeval.evaluator import assert_test from deepeval.progress_context import progress_context from sentence_transformers import CrossEncoder diff --git a/deepeval/metrics/overall_score.py b/deepeval/metrics/overall_score.py index bd683903d..a71d1da30 100644 --- a/deepeval/metrics/overall_score.py +++ b/deepeval/metrics/overall_score.py @@ -8,7 +8,7 @@ from deepeval.metrics.conceptual_similarity import ConceptualSimilarityMetric from deepeval.metrics.factual_consistency import FactualConsistencyMetric from deepeval.metrics.base_metric import BaseMetric -from deepeval.run_test import assert_test +from deepeval.evaluator import assert_test class OverallScoreMetric(BaseMetric, metaclass=Singleton): diff --git a/deepeval/metrics/ragas_metric.py b/deepeval/metrics/ragas_metric.py index f26f4f638..5e53a1452 100644 --- a/deepeval/metrics/ragas_metric.py +++ b/deepeval/metrics/ragas_metric.py @@ -62,7 +62,7 @@ def is_successful(self): @property def __name__(self): - return "Ragas Contextual Relevancy Score" + return "Contextual Relevancy (RAGAS)" class RagasAnswerRelevancyMetric(BaseMetric): @@ -115,7 +115,7 @@ def is_successful(self): @property def __name__(self): - return "Ragas Answer Relevancy Score" + return "Answer Relevancy (RAGAS)" class RagasFaithfulnessMetric(BaseMetric): @@ -166,7 +166,7 @@ def is_successful(self): @property def __name__(self): - return "Ragas Faithfulness Score" + return "Faithfulness (RAGAS)" class RagasContextRecallMetric(BaseMetric): @@ -219,7 +219,7 @@ def is_successful(self): @property def __name__(self): - return "Ragas Context Recall Score" + return "Context Recall (RAGAS)" class RagasHarmfulnessMetric(BaseMetric): @@ -272,7 +272,7 @@ def is_successful(self): @property def __name__(self): - return "Ragas Harmfulness Score" + return "Harmfulness (RAGAS)" class RagasCoherenceMetric(BaseMetric): @@ -324,7 +324,7 @@ def is_successful(self): @property def __name__(self): - return "Ragas Coherence Score" + return "Coherence (RAGAS)" class RagasMaliciousnessMetric(BaseMetric): @@ -376,7 +376,7 @@ def is_successful(self): @property def __name__(self): - return "Ragas Maliciousness Score" + return "Maliciousness (RAGAS)" class RagasCorrectnessMetric(BaseMetric): @@ -428,7 +428,7 @@ def is_successful(self): @property def __name__(self): - return "Ragas Correctness Score" + return "Correctness (RAGAS)" class RagasConcisenessMetric(BaseMetric): @@ -480,7 +480,7 @@ def is_successful(self): @property def __name__(self): - return "Ragas Conciseness Score" + return "Conciseness (RAGAS)" class RagasMetric(BaseMetric): @@ -547,7 +547,7 @@ def is_successful(self): @property def __name__(self): - return "Ragas Score" + return "RAGAS" def assert_ragas( diff --git a/deepeval/metrics/ranking_similarity.py b/deepeval/metrics/ranking_similarity.py index db18e10ed..426ba5112 100644 --- a/deepeval/metrics/ranking_similarity.py +++ b/deepeval/metrics/ranking_similarity.py @@ -6,7 +6,7 @@ from ..test_case import LLMTestCase from .base_metric import BaseMetric -from ..run_test import assert_test +from ..evaluator import assert_test class RBO: diff --git a/deepeval/metrics/toxic_classifier.py b/deepeval/metrics/toxic_classifier.py index 5824d7df7..8ca7d8f4e 100644 --- a/deepeval/metrics/toxic_classifier.py +++ b/deepeval/metrics/toxic_classifier.py @@ -8,7 +8,7 @@ from deepeval.singleton import Singleton from deepeval.test_case import LLMTestCase from deepeval.metrics.base_metric import BaseMetric -from deepeval.run_test import assert_test +from deepeval.evaluator import assert_test class DetoxifyModel(metaclass=Singleton): diff --git a/deepeval/plugins/plugin.py b/deepeval/plugins/plugin.py index 4da3726e3..ba11e1692 100644 --- a/deepeval/plugins/plugin.py +++ b/deepeval/plugins/plugin.py @@ -2,22 +2,22 @@ import shutil import os from rich import print -from deepeval.api import Api, TestRun +from deepeval.api import Api from typing import Optional, Any from deepeval.constants import PYTEST_RUN_ENV_VAR, PYTEST_RUN_TEST_NAME from deepeval.decorators.hyperparameters import get_hyperparameters +from deepeval.test_run import TestRun, test_run_manager import webbrowser def pytest_sessionstart(session: pytest.Session): - global test_filename test_run = TestRun( testFile=session.config.getoption("file_or_dir")[0], testCases=[], metricScores=[], configurations={}, ) - test_filename = test_run.save() + test_run_manager.set_test_run(test_run) @pytest.hookimpl(tryfirst=True) @@ -36,13 +36,12 @@ def pytest_sessionfinish(session: pytest.Session, exitstatus): # yield control back to pytest for the actual teardown yield - # Code after yield will run after the test teardown - test_run: TestRun = TestRun.load(test_filename) - + test_run = test_run_manager.get_test_run() if test_run is None: print("Test Run is empty, please try again.") return + del test_run.dict_test_cases if os.getenv(PYTEST_RUN_ENV_VAR) and os.path.exists(".deepeval"): api: Api = Api() test_run.configurations = get_hyperparameters() @@ -116,17 +115,18 @@ def pytest_sessionfinish(session: pytest.Session, exitstatus): print(table) if os.getenv(PYTEST_RUN_ENV_VAR) and os.path.exists(".deepeval"): - link = f"https://app.confident-ai.com/project/{result.projectId}/unit-tests/{result.testRunId}/test-cases" + link = result.link print( "✅ Tests finished! View results on " f"[link={link}]{link}[/link]" ) webbrowser.open(link) else: print( - '✅ Tests finished! Run "deepeval login" to view evaluation results in detail.' + '✅ Tests finished! Run "deepeval login" to view evaluation results on the web.' ) local_folder = os.getenv("DEEPEVAL_RESULTS_FOLDER") if local_folder: + test_filename = test_run.save() if not os.path.exists(local_folder): os.mkdir(local_folder) shutil.copy(test_filename, local_folder) @@ -138,7 +138,7 @@ def pytest_sessionfinish(session: pytest.Session, exitstatus): else: shutil.copy(test_filename, local_folder) print(f"Results saved in {local_folder} as {test_filename}") - os.remove(test_filename) + os.remove(test_filename) def pytest_terminal_summary(terminalreporter, exitstatus, config): diff --git a/deepeval/test_case.py b/deepeval/test_case.py index 4db041c8c..ae6841a3d 100644 --- a/deepeval/test_case.py +++ b/deepeval/test_case.py @@ -22,7 +22,7 @@ def __init__( input: str, actual_output: str, expected_output: Optional[str] = None, - context: Optional[Union[str, List[str]]] = None, + context: Optional[List[str]] = None, retrieval_context: Optional[List[str]] = None, id: Optional[str] = None, ): @@ -31,9 +31,6 @@ def __init__( self.actual_output = actual_output self.expected_output = expected_output self.retrieval_context = retrieval_context - # Force context to be a list - if isinstance(context, str): - context = [context] self.context = context def __post_init__(self): diff --git a/deepeval/test_quickstart.py b/deepeval/test_quickstart.py index c93bee302..6b36bdb7b 100644 --- a/deepeval/test_quickstart.py +++ b/deepeval/test_quickstart.py @@ -1,6 +1,6 @@ import pytest from deepeval.test_case import LLMTestCase -from deepeval.run_test import assert_test +from deepeval.evaluator import assert_test from deepeval.metrics.factual_consistency import FactualConsistencyMetric from deepeval.metrics.answer_relevancy import AnswerRelevancyMetric diff --git a/deepeval/test_run.py b/deepeval/test_run.py new file mode 100644 index 000000000..ab907139d --- /dev/null +++ b/deepeval/test_run.py @@ -0,0 +1,185 @@ +import os +import json +from pydantic import BaseModel, Field +from typing import Any, Optional, List, Dict +from deepeval.metrics.base_metric import BaseMetric +from deepeval.test_case import LLMTestCase +from collections import defaultdict +from deepeval.tracing import get_trace_stack +from deepeval.constants import PYTEST_RUN_TEST_NAME, PYTEST_RUN_ENV_VAR + + +class MetricsMetadata(BaseModel): + metric: str + score: float + minimum_score: float = Field(None, alias="minimumScore") + + +class MetricScore(BaseModel): + metric: str + score: float + + @classmethod + def from_metric(cls, metric: BaseMetric): + return cls(metric=metric.__name__, score=metric.score) + + +class MetricDict: + def __init__(self): + self.metric_dict = {} + self.metric_count = {} + + def add_metric(self, metric_name, score): + if metric_name not in self.metric_dict: + self.metric_dict[metric_name] = score + self.metric_count[metric_name] = 1 + else: + self.metric_dict[metric_name] += score + self.metric_count[metric_name] += 1 + + def get_average_metric_score(self): + return [ + MetricScore( + metric=metric, + score=self.metric_dict[metric] / self.metric_count[metric], + ) + for metric in self.metric_dict + ] + + +class MetricsMetadataAverageDict: + def __init__(self): + self.metric_dict = defaultdict(list) + self.min_score_dict = defaultdict(float) + + def add_metric(self, metric: BaseMetric): + self.metric_dict[metric.__name__].append(metric.score) + self.min_score_dict[metric.__name__] = min( + self.min_score_dict.get(metric.__name__, float("inf")), + metric.minimum_score, + ) + + def get_metrics_metadata(self): + return [ + MetricsMetadata( + metric=metric_name, + score=sum(scores) / len(scores), + minimumScore=self.min_score_dict[metric_name], + ) + for metric_name, scores in self.metric_dict.items() + ] + + +class APITestCase(BaseModel): + name: str + input: str + actual_output: str = Field(..., alias="actualOutput") + expected_output: Optional[str] = Field(None, alias="expectedOutput") + success: bool + metrics_metadata: List[MetricsMetadata] = Field( + ..., alias="metricsMetadata" + ) + run_duration: float = Field(..., alias="runDuration") + traceStack: Optional[dict] = Field(None) + context: Optional[list] = Field(None) + + +class TestRun(BaseModel): + test_file: Optional[str] = Field( + # TODO: Fix test_file + "test.py", + alias="testFile", + ) + dict_test_cases: Dict[int, APITestCase] = Field( + default_factory=dict, + ) + test_cases: List[APITestCase] = Field( + alias="testCases", default_factory=lambda: [] + ) + + metric_scores: List[MetricScore] = Field( + default_factory=lambda: [], alias="metricScores" + ) + configurations: Optional[dict[Any, Any]] = Field(default_factory=dict) + + def add_llm_test_case( + self, + test_case: LLMTestCase, + metrics: List[BaseMetric], + run_duration: float, + ): + # Check if test case with the same ID already exists + test_case_id = id(test_case) + existing_test_case: LLMTestCase = self.dict_test_cases.get( + test_case_id, None + ) + metrics_metadata_dict = MetricsMetadataAverageDict() + for metric in metrics: + metrics_metadata_dict.add_metric(metric) + metrics_metadata = metrics_metadata_dict.get_metrics_metadata() + + if existing_test_case: + # If it exists, append the metrics to the existing test case + existing_test_case.metrics_metadata.extend(metrics_metadata) + success = all( + [ + metric.score >= metric.minimum_score + for metric in existing_test_case.metrics_metadata + ] + ) + # Update the success status + existing_test_case.success = success + else: + # If it doesn't exist, create a new test case + # Adding backwards compatibility to ensure context still works. + context = test_case.context + success = all([metric.is_successful() for metric in metrics]) + api_test_case: APITestCase = APITestCase( + name=os.getenv(PYTEST_RUN_TEST_NAME, "-"), + input=test_case.input, + actualOutput=test_case.actual_output, + expectedOutput=test_case.expected_output, + success=success, + metricsMetadata=metrics_metadata, + runDuration=run_duration, + context=context, + traceStack=get_trace_stack(), + ) + + self.dict_test_cases[test_case_id] = api_test_case + self.test_cases.append(api_test_case) + + all_metric_dict = MetricDict() + for test_case in self.test_cases: + for metric in test_case.metrics_metadata: + all_metric_dict.add_metric(metric.metric, metric.score) + self.metric_scores = all_metric_dict.get_average_metric_score() + + def save(self, file_path: Optional[str] = None): + if file_path is None: + file_path = os.getenv(PYTEST_RUN_ENV_VAR) + # If file Path is None, remove it + if not file_path: + return + elif not file_path.endswith(".json"): + file_path = f"{file_path}.json" + with open(file_path, "w") as f: + json.dump(self.dict(by_alias=True, exclude_none=True), f) + return file_path + + +class TestRunManger: + def __init__(self): + self.test_run = None + + def set_test_run(self, test_run: TestRun): + self.test_run = test_run + + def get_test_run(self): + return self.test_run + + def clear_test_run(self): + self.test_run = None + + +test_run_manager = TestRunManger() diff --git a/docs/docusaurus.config.js b/docs/docusaurus.config.js index 6f205c0f7..038ae7d16 100644 --- a/docs/docusaurus.config.js +++ b/docs/docusaurus.config.js @@ -24,8 +24,8 @@ const config = { [ "posthog-docusaurus", { - apiKey: "phc_WU2fTmokmDGUxquzdiLMJ7CegOmilDv3jFvbWQV6b3p", - appUrl: "https://app.posthog.com", // optional + apiKey: "phc_qyCLAQQVAYN4mDhkZYSzBvFP2SMoiij0QIbnOwhosp0", + appUrl: "https://docs.confident-ai.com", // optional enableInDevelopment: false, // optional // other options are passed to posthog-js init as is }, diff --git a/docs/yarn.lock b/docs/yarn.lock index d77eb3502..9741b975e 100644 --- a/docs/yarn.lock +++ b/docs/yarn.lock @@ -1322,83 +1322,6 @@ webpack-merge "^5.8.0" webpackbar "^5.0.2" -"@docusaurus/core@2.4.3": - version "2.4.3" - resolved "https://registry.yarnpkg.com/@docusaurus/core/-/core-2.4.3.tgz#d86624901386fd8164ce4bff9cc7f16fde57f523" - integrity sha512-dWH5P7cgeNSIg9ufReX6gaCl/TmrGKD38Orbwuz05WPhAQtFXHd5B8Qym1TiXfvUNvwoYKkAJOJuGe8ou0Z7PA== - dependencies: - "@babel/core" "^7.18.6" - "@babel/generator" "^7.18.7" - "@babel/plugin-syntax-dynamic-import" "^7.8.3" - "@babel/plugin-transform-runtime" "^7.18.6" - "@babel/preset-env" "^7.18.6" - "@babel/preset-react" "^7.18.6" - "@babel/preset-typescript" "^7.18.6" - "@babel/runtime" "^7.18.6" - "@babel/runtime-corejs3" "^7.18.6" - "@babel/traverse" "^7.18.8" - "@docusaurus/cssnano-preset" "2.4.3" - "@docusaurus/logger" "2.4.3" - "@docusaurus/mdx-loader" "2.4.3" - "@docusaurus/react-loadable" "5.5.2" - "@docusaurus/utils" "2.4.3" - "@docusaurus/utils-common" "2.4.3" - "@docusaurus/utils-validation" "2.4.3" - "@slorber/static-site-generator-webpack-plugin" "^4.0.7" - "@svgr/webpack" "^6.2.1" - autoprefixer "^10.4.7" - babel-loader "^8.2.5" - babel-plugin-dynamic-import-node "^2.3.3" - boxen "^6.2.1" - chalk "^4.1.2" - chokidar "^3.5.3" - clean-css "^5.3.0" - cli-table3 "^0.6.2" - combine-promises "^1.1.0" - commander "^5.1.0" - copy-webpack-plugin "^11.0.0" - core-js "^3.23.3" - css-loader "^6.7.1" - css-minimizer-webpack-plugin "^4.0.0" - cssnano "^5.1.12" - del "^6.1.1" - detect-port "^1.3.0" - escape-html "^1.0.3" - eta "^2.0.0" - file-loader "^6.2.0" - fs-extra "^10.1.0" - html-minifier-terser "^6.1.0" - html-tags "^3.2.0" - html-webpack-plugin "^5.5.0" - import-fresh "^3.3.0" - leven "^3.1.0" - lodash "^4.17.21" - mini-css-extract-plugin "^2.6.1" - postcss "^8.4.14" - postcss-loader "^7.0.0" - prompts "^2.4.2" - react-dev-utils "^12.0.1" - react-helmet-async "^1.3.0" - react-loadable "npm:@docusaurus/react-loadable@5.5.2" - react-loadable-ssr-addon-v5-slorber "^1.0.1" - react-router "^5.3.3" - react-router-config "^5.1.1" - react-router-dom "^5.3.3" - rtl-detect "^1.0.4" - semver "^7.3.7" - serve-handler "^6.1.3" - shelljs "^0.8.5" - terser-webpack-plugin "^5.3.3" - tslib "^2.4.0" - update-notifier "^5.1.0" - url-loader "^4.1.1" - wait-on "^6.0.1" - webpack "^5.73.0" - webpack-bundle-analyzer "^4.5.0" - webpack-dev-server "^4.9.3" - webpack-merge "^5.8.0" - webpackbar "^5.0.2" - "@docusaurus/cssnano-preset@2.4.1": version "2.4.1" resolved "https://registry.npmjs.org/@docusaurus/cssnano-preset/-/cssnano-preset-2.4.1.tgz" @@ -1409,16 +1332,6 @@ postcss-sort-media-queries "^4.2.1" tslib "^2.4.0" -"@docusaurus/cssnano-preset@2.4.3": - version "2.4.3" - resolved "https://registry.yarnpkg.com/@docusaurus/cssnano-preset/-/cssnano-preset-2.4.3.tgz#1d7e833c41ce240fcc2812a2ac27f7b862f32de0" - integrity sha512-ZvGSRCi7z9wLnZrXNPG6DmVPHdKGd8dIn9pYbEOFiYihfv4uDR3UtxogmKf+rT8ZlKFf5Lqne8E8nt08zNM8CA== - dependencies: - cssnano-preset-advanced "^5.3.8" - postcss "^8.4.14" - postcss-sort-media-queries "^4.2.1" - tslib "^2.4.0" - "@docusaurus/logger@2.4.1": version "2.4.1" resolved "https://registry.npmjs.org/@docusaurus/logger/-/logger-2.4.1.tgz" @@ -1427,14 +1340,6 @@ chalk "^4.1.2" tslib "^2.4.0" -"@docusaurus/logger@2.4.3": - version "2.4.3" - resolved "https://registry.yarnpkg.com/@docusaurus/logger/-/logger-2.4.3.tgz#518bbc965fb4ebe8f1d0b14e5f4161607552d34c" - integrity sha512-Zxws7r3yLufk9xM1zq9ged0YHs65mlRmtsobnFkdZTxWXdTYlWWLWdKyNKAsVC+D7zg+pv2fGbyabdOnyZOM3w== - dependencies: - chalk "^4.1.2" - tslib "^2.4.0" - "@docusaurus/mdx-loader@2.4.1": version "2.4.1" resolved "https://registry.npmjs.org/@docusaurus/mdx-loader/-/mdx-loader-2.4.1.tgz" @@ -1458,29 +1363,6 @@ url-loader "^4.1.1" webpack "^5.73.0" -"@docusaurus/mdx-loader@2.4.3": - version "2.4.3" - resolved "https://registry.yarnpkg.com/@docusaurus/mdx-loader/-/mdx-loader-2.4.3.tgz#e8ff37f30a060eaa97b8121c135f74cb531a4a3e" - integrity sha512-b1+fDnWtl3GiqkL0BRjYtc94FZrcDDBV1j8446+4tptB9BAOlePwG2p/pK6vGvfL53lkOsszXMghr2g67M0vCw== - dependencies: - "@babel/parser" "^7.18.8" - "@babel/traverse" "^7.18.8" - "@docusaurus/logger" "2.4.3" - "@docusaurus/utils" "2.4.3" - "@mdx-js/mdx" "^1.6.22" - escape-html "^1.0.3" - file-loader "^6.2.0" - fs-extra "^10.1.0" - image-size "^1.0.1" - mdast-util-to-string "^2.0.0" - remark-emoji "^2.2.0" - stringify-object "^3.3.0" - tslib "^2.4.0" - unified "^9.2.2" - unist-util-visit "^2.0.3" - url-loader "^4.1.1" - webpack "^5.73.0" - "@docusaurus/module-type-aliases@2.4.1": version "2.4.1" resolved "https://registry.npmjs.org/@docusaurus/module-type-aliases/-/module-type-aliases-2.4.1.tgz" @@ -1585,16 +1467,6 @@ "@docusaurus/utils-validation" "2.4.1" tslib "^2.4.0" -"@docusaurus/plugin-google-gtag@^2.4.3": - version "2.4.3" - resolved "https://registry.yarnpkg.com/@docusaurus/plugin-google-gtag/-/plugin-google-gtag-2.4.3.tgz#e1a80b0696771b488562e5b60eff21c9932d9e1c" - integrity sha512-5FMg0rT7sDy4i9AGsvJC71MQrqQZwgLNdDetLEGDHLfSHLvJhQbTCUGbGXknUgWXQJckcV/AILYeJy+HhxeIFA== - dependencies: - "@docusaurus/core" "2.4.3" - "@docusaurus/types" "2.4.3" - "@docusaurus/utils-validation" "2.4.3" - tslib "^2.4.0" - "@docusaurus/plugin-google-tag-manager@2.4.1": version "2.4.1" resolved "https://registry.npmjs.org/@docusaurus/plugin-google-tag-manager/-/plugin-google-tag-manager-2.4.1.tgz" @@ -1744,20 +1616,6 @@ webpack "^5.73.0" webpack-merge "^5.8.0" -"@docusaurus/types@2.4.3": - version "2.4.3" - resolved "https://registry.yarnpkg.com/@docusaurus/types/-/types-2.4.3.tgz#4aead281ca09f721b3c0a9b926818450cfa3db31" - integrity sha512-W6zNLGQqfrp/EoPD0bhb9n7OobP+RHpmvVzpA+Z/IuU3Q63njJM24hmT0GYboovWcDtFmnIJC9wcyx4RVPQscw== - dependencies: - "@types/history" "^4.7.11" - "@types/react" "*" - commander "^5.1.0" - joi "^17.6.0" - react-helmet-async "^1.3.0" - utility-types "^3.10.0" - webpack "^5.73.0" - webpack-merge "^5.8.0" - "@docusaurus/utils-common@2.4.1": version "2.4.1" resolved "https://registry.npmjs.org/@docusaurus/utils-common/-/utils-common-2.4.1.tgz" @@ -1765,13 +1623,6 @@ dependencies: tslib "^2.4.0" -"@docusaurus/utils-common@2.4.3": - version "2.4.3" - resolved "https://registry.yarnpkg.com/@docusaurus/utils-common/-/utils-common-2.4.3.tgz#30656c39ef1ce7e002af7ba39ea08330f58efcfb" - integrity sha512-/jascp4GbLQCPVmcGkPzEQjNaAk3ADVfMtudk49Ggb+131B1WDD6HqlSmDf8MxGdy7Dja2gc+StHf01kiWoTDQ== - dependencies: - tslib "^2.4.0" - "@docusaurus/utils-validation@2.4.1": version "2.4.1" resolved "https://registry.npmjs.org/@docusaurus/utils-validation/-/utils-validation-2.4.1.tgz" @@ -1783,17 +1634,6 @@ js-yaml "^4.1.0" tslib "^2.4.0" -"@docusaurus/utils-validation@2.4.3": - version "2.4.3" - resolved "https://registry.yarnpkg.com/@docusaurus/utils-validation/-/utils-validation-2.4.3.tgz#8122c394feef3e96c73f6433987837ec206a63fb" - integrity sha512-G2+Vt3WR5E/9drAobP+hhZQMaswRwDlp6qOMi7o7ZypB+VO7N//DZWhZEwhcRGepMDJGQEwtPv7UxtYwPL9PBw== - dependencies: - "@docusaurus/logger" "2.4.3" - "@docusaurus/utils" "2.4.3" - joi "^17.6.0" - js-yaml "^4.1.0" - tslib "^2.4.0" - "@docusaurus/utils@2.4.1": version "2.4.1" resolved "https://registry.npmjs.org/@docusaurus/utils/-/utils-2.4.1.tgz" @@ -1816,28 +1656,6 @@ url-loader "^4.1.1" webpack "^5.73.0" -"@docusaurus/utils@2.4.3": - version "2.4.3" - resolved "https://registry.yarnpkg.com/@docusaurus/utils/-/utils-2.4.3.tgz#52b000d989380a2125831b84e3a7327bef471e89" - integrity sha512-fKcXsjrD86Smxv8Pt0TBFqYieZZCPh4cbf9oszUq/AMhZn3ujwpKaVYZACPX8mmjtYx0JOgNx52CREBfiGQB4A== - dependencies: - "@docusaurus/logger" "2.4.3" - "@svgr/webpack" "^6.2.1" - escape-string-regexp "^4.0.0" - file-loader "^6.2.0" - fs-extra "^10.1.0" - github-slugger "^1.4.0" - globby "^11.1.0" - gray-matter "^4.0.3" - js-yaml "^4.1.0" - lodash "^4.17.21" - micromatch "^4.0.5" - resolve-pathname "^3.0.0" - shelljs "^0.8.5" - tslib "^2.4.0" - url-loader "^4.1.1" - webpack "^5.73.0" - "@hapi/hoek@^9.0.0": version "9.3.0" resolved "https://registry.npmjs.org/@hapi/hoek/-/hoek-9.3.0.tgz" diff --git a/examples/getting_started/test_example.py b/examples/getting_started/test_example.py index 00056d2ae..1bc7986cf 100644 --- a/examples/getting_started/test_example.py +++ b/examples/getting_started/test_example.py @@ -1,7 +1,7 @@ import pytest from deepeval.metrics.factual_consistency import FactualConsistencyMetric from deepeval.test_case import LLMTestCase -from deepeval.run_test import assert_test +from deepeval.evaluator import assert_test from deepeval.metrics.llm_eval_metric import LLMEvalMetric from deepeval.types import LLMTestCaseParams from deepeval.metrics.base_metric import BaseMetric diff --git a/examples/tracing/test_chatbot.py b/examples/tracing/test_chatbot.py index b8bab945b..5079b2d15 100644 --- a/examples/tracing/test_chatbot.py +++ b/examples/tracing/test_chatbot.py @@ -64,7 +64,7 @@ def query(self, user_input=input): import pytest from deepeval.test_case import LLMTestCase from deepeval.metrics.factual_consistency import FactualConsistencyMetric -from deepeval.run_test import assert_test +from deepeval.evaluator import assert_test chatbot = Chatbot() diff --git a/tests/test_answer_relevancy.py b/tests/test_answer_relevancy.py index 445a3b63c..8e5ea8493 100644 --- a/tests/test_answer_relevancy.py +++ b/tests/test_answer_relevancy.py @@ -7,7 +7,7 @@ assert_answer_relevancy, ) from deepeval.metrics.answer_relevancy import is_answer_relevant -from deepeval.run_test import run_test, assert_test +from deepeval.evaluator import run_test, assert_test from .utils import assert_viable_score query = "What is Python?" diff --git a/tests/test_bias.py b/tests/test_bias.py index 6c8192fc8..b4f483d8b 100644 --- a/tests/test_bias.py +++ b/tests/test_bias.py @@ -5,7 +5,7 @@ import pytest from deepeval.test_case import LLMTestCase from deepeval.metrics.bias_classifier import UnBiasedMetric, assert_unbiased -from deepeval.run_test import assert_test +from deepeval.evaluator import assert_test from deepeval.types import LLMTestCaseParams output = "Winners of the FIFA world cup were the French national football team" diff --git a/tests/test_chatbot_example.py b/tests/test_chatbot_example.py index b9f6d129d..09582af3f 100644 --- a/tests/test_chatbot_example.py +++ b/tests/test_chatbot_example.py @@ -1,7 +1,7 @@ import pytest from deepeval.metrics.factual_consistency import FactualConsistencyMetric from deepeval.test_case import LLMTestCase -from deepeval.run_test import assert_test +from deepeval.evaluator import assert_test def test_1(): diff --git a/tests/test_custom_metric.py b/tests/test_custom_metric.py index ea53d3d16..1fe4e305f 100644 --- a/tests/test_custom_metric.py +++ b/tests/test_custom_metric.py @@ -3,7 +3,7 @@ from deepeval.test_case import LLMTestCase from deepeval.metrics.base_metric import BaseMetric -from deepeval.run_test import assert_test +from deepeval.evaluator import assert_test class LengthMetric(BaseMetric): diff --git a/tests/test_factual_consistency.py b/tests/test_factual_consistency.py index 524838f28..313796f2a 100644 --- a/tests/test_factual_consistency.py +++ b/tests/test_factual_consistency.py @@ -4,14 +4,16 @@ FactualConsistencyMetric, assert_factual_consistency, ) -from deepeval.run_test import assert_test +from deepeval.evaluator import assert_test def test_factual_consistency(): # legacy functions - consider removing with pytest.raises(AssertionError): assert_factual_consistency( - context="After a long day at work, Sarah decided to go for a walk in the park to unwind. She put on her sneakers and grabbed her headphones before heading out. As she strolled along the path, she noticed families having picnics, children playing on the playground, and ducks swimming in the pond.", + context=[ + "After a long day at work, Sarah decided to go for a walk in the park to unwind. She put on her sneakers and grabbed her headphones before heading out. As she strolled along the path, she noticed families having picnics, children playing on the playground, and ducks swimming in the pond." + ], output="Sarah spent the evening at the library, engrossed in a book.", ) @@ -19,7 +21,9 @@ def test_factual_consistency(): def test_factual_consistency_2(): # legacy functions - consider removing assert_factual_consistency( - context="After a long day at work, Sarah decided to go for a walk in the park to unwind. She put on her sneakers and grabbed her headphones before heading out. As she strolled along the path, she noticed families having picnics, children playing on the playground, and ducks swimming in the pond.", + context=[ + "After a long day at work, Sarah decided to go for a walk in the park to unwind. She put on her sneakers and grabbed her headphones before heading out. As she strolled along the path, she noticed families having picnics, children playing on the playground, and ducks swimming in the pond." + ], output="Sarah went out for a walk in the park.", ) @@ -29,7 +33,9 @@ def test_factual_consistency_metric(): test_case = LLMTestCase( input="placeholder", actual_output="Python is a programming language.", - context="Python is a high-level, versatile, and interpreted programming language known for its simplicity and readability.", + context=[ + "Python is a high-level, versatile, and interpreted programming language known for its simplicity and readability." + ], ) assert_test(test_case, [metric]) @@ -39,7 +45,7 @@ def test_factual_consistency_metric_2(): test_case = LLMTestCase( input="placeholder", actual_output="Python is a programming language.", - context="Python is NOT a programming language.", + context=["Python is NOT a programming language."], ) with pytest.raises(AssertionError): assert_test(test_case, [metric]) @@ -50,7 +56,7 @@ def test_factual_consistency_metric_3(): test_case = LLMTestCase( input="placeholder", actual_output="Python is a programming language.", - context="Python is a snake.", + context=["Python is a snake."], ) with pytest.raises(AssertionError): assert_test(test_case, [metric]) diff --git a/tests/test_llm_metric.py b/tests/test_llm_metric.py index f950ac7ec..5beb1000c 100644 --- a/tests/test_llm_metric.py +++ b/tests/test_llm_metric.py @@ -2,7 +2,7 @@ from deepeval.test_case import LLMTestCase from deepeval.metrics.llm_eval_metric import LLMEvalMetric from deepeval.types import LLMTestCaseParams -from deepeval.run_test import assert_test +from deepeval.evaluator import assert_test def test_chat_completion(): @@ -20,7 +20,7 @@ def test_chat_completion(): input="What is the capital of France?", actual_output="Paris", expected_output="Paris", - context="Geography", + context=["Geography"], ) # metric.measure(test_case) # assert metric.is_successful() is True diff --git a/tests/test_overall_score.py b/tests/test_overall_score.py index f3dad4bf0..5a95e488e 100644 --- a/tests/test_overall_score.py +++ b/tests/test_overall_score.py @@ -9,7 +9,7 @@ OverallScoreMetric, assert_overall_score, ) -from deepeval.run_test import assert_test, run_test +from deepeval.evaluator import assert_test, run_test from .utils import assert_viable_score @@ -43,7 +43,7 @@ def test_overall_score_worst_context(self): input=query, actual_output=output, expected_output=expected_output, - context="He doesn't know how to code", + context=["He doesn't know how to code"], ) test_case_2 = LLMTestCase( input=query, @@ -59,13 +59,13 @@ def test_overall_score_worst_output(self): input=query, actual_output="Not relevant", expected_output=expected_output, - context="He doesn't know how to code", + context=["He doesn't know how to code"], ) test_case_2 = LLMTestCase( input=query, actual_output=output, expected_output=expected_output, - context="He doesn't know how to code", + context=["He doesn't know how to code"], ) scores = run_test([test_case, test_case_2], metrics=[self.metric]) assert scores[0] > scores[1] @@ -75,14 +75,14 @@ def test_worst_expected_output(self): input=query, actual_output="Not relevant", expected_output="STranger things", - context="He doesn't know how to code", + context=["He doesn't know how to code"], ) score_4 = self.metric.measure(test_case) test_case_2 = LLMTestCase( input=query, actual_output="Not relevant", expected_output=expected_output, - context="He doesn't know how to code", + context=["He doesn't know how to code"], ) scores = run_test([test_case, test_case_2], metrics=[self.metric]) assert scores[0] > scores[1] diff --git a/tests/test_quickstart.py b/tests/test_quickstart.py index c997d3571..49153c260 100644 --- a/tests/test_quickstart.py +++ b/tests/test_quickstart.py @@ -5,7 +5,7 @@ from deepeval.metrics.factual_consistency import assert_factual_consistency from deepeval.metrics.overall_score import OverallScoreMetric from deepeval.test_case import LLMTestCase -from deepeval.run_test import assert_test, run_test +from deepeval.evaluator import assert_test, run_test def generate_llm_output(query: str): diff --git a/tests/test_ragas.py b/tests/test_ragas.py index e032a7589..b631a2ea7 100644 --- a/tests/test_ragas.py +++ b/tests/test_ragas.py @@ -1,7 +1,7 @@ import pytest from deepeval.test_case import LLMTestCase from deepeval.metrics.ragas_metric import RagasMetric -from deepeval.run_test import assert_test +from deepeval.evaluator import assert_test query = "Who won the FIFA World Cup in 2018?" output = "Winners of the FIFA world cup were the French national football team" diff --git a/tests/test_result.py b/tests/test_result.py index fe587e8e5..b7f7802e1 100644 --- a/tests/test_result.py +++ b/tests/test_result.py @@ -1,4 +1,4 @@ -from deepeval.run_test import TestResult +from deepeval.evaluator import TestResult def test_result(): diff --git a/tests/test_similar_ranking.py b/tests/test_similar_ranking.py index 9d5421924..123b740ee 100644 --- a/tests/test_similar_ranking.py +++ b/tests/test_similar_ranking.py @@ -1,7 +1,7 @@ """Tests for answer relevancy """ from deepeval.test_case import LLMTestCase -from deepeval.run_test import run_test, assert_test +from deepeval.evaluator import run_test, assert_test from deepeval.metrics.ranking_similarity import ( RankingSimilarity, assert_ranking_similarity, diff --git a/tests/test_toxic.py b/tests/test_toxic.py index ac2d4ed7a..9ab23a9b4 100644 --- a/tests/test_toxic.py +++ b/tests/test_toxic.py @@ -5,7 +5,7 @@ import pytest from deepeval.test_case import LLMTestCase from deepeval.metrics.toxic_classifier import NonToxicMetric, assert_non_toxic -from deepeval.run_test import assert_test +from deepeval.evaluator import assert_test from deepeval.types import LLMTestCaseParams output = "Winners of the FIFA world cup were the French national football team" From 85e5746f38c9afa60cc2112dd1a981bfb7308e1b Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Fri, 10 Nov 2023 17:05:12 -0800 Subject: [PATCH 16/38] updated tests --- deepeval/metrics/factual_consistency.py | 2 +- deepeval/test_quickstart.py | 2 +- tests/test_chatbot_example.py | 4 ++-- tests/test_quickstart.py | 8 ++++---- tests/test_ragas.py | 2 +- 5 files changed, 9 insertions(+), 9 deletions(-) diff --git a/deepeval/metrics/factual_consistency.py b/deepeval/metrics/factual_consistency.py index 3b61fb59b..e64f0a444 100644 --- a/deepeval/metrics/factual_consistency.py +++ b/deepeval/metrics/factual_consistency.py @@ -82,7 +82,7 @@ def is_factually_consistent( def assert_factual_consistency( - output: str, context: str, minimum_score: float = 0.3 + output: str, context: list[str], minimum_score: float = 0.3 ): """Assert that the output is factually consistent with the context.""" diff --git a/deepeval/test_quickstart.py b/deepeval/test_quickstart.py index 6b36bdb7b..63b1b87e1 100644 --- a/deepeval/test_quickstart.py +++ b/deepeval/test_quickstart.py @@ -16,7 +16,7 @@ def test_customer_chatbot_simple(): input = "What are your operating hours?" output = "Our operating hours are from 9 AM to 5 PM, Monday to Friday." - context = "Our company operates from 10 AM to 6 PM, Monday to Friday." + context = ["Our company operates from 10 AM to 6 PM, Monday to Friday."] factual_consistency_metric = FactualConsistencyMetric(minimum_score=0.3) answer_relevancy_metric = AnswerRelevancyMetric(minimum_score=0.5) test_case = LLMTestCase(input=input, actual_output=output, context=context) diff --git a/tests/test_chatbot_example.py b/tests/test_chatbot_example.py index 09582af3f..2b73b9bf4 100644 --- a/tests/test_chatbot_example.py +++ b/tests/test_chatbot_example.py @@ -9,7 +9,7 @@ def test_1(): output = ( "Specializes in cloud computing, data analytics, and machine learning." ) - context = "Our company specializes in cloud computing, data analytics, and machine learning. We offer a range of services including cloud storage solutions, data analytics platforms, and custom machine learning models." + context = ["Our company specializes in cloud computing, data analytics, and machine learning. We offer a range of services including cloud storage solutions, data analytics platforms, and custom machine learning models."] factual_consistency_metric = FactualConsistencyMetric(minimum_score=1.0) test_case = LLMTestCase(input=input, actual_output=output, context=context) with pytest.raises(AssertionError): @@ -21,7 +21,7 @@ def test_2(): output = ( "Specializes in cloud computing, data analytics, and machine learning." ) - context = "Our company specializes in cloud computing, data analytics, and machine learning. We offer a range of services including cloud storage solutions, data analytics platforms, and custom machine learning models." + context = ["Our company specializes in cloud computing, data analytics, and machine learning. We offer a range of services including cloud storage solutions, data analytics platforms, and custom machine learning models."] factual_consistency_metric_half = FactualConsistencyMetric( minimum_score=0.5 ) diff --git a/tests/test_quickstart.py b/tests/test_quickstart.py index 49153c260..1f384f8cb 100644 --- a/tests/test_quickstart.py +++ b/tests/test_quickstart.py @@ -21,17 +21,17 @@ def test_llm_output(): def test_llm_output_custom(): - query = "What is the customer success phone line?" - expected_output = "Dogs and cats love to walk around the beach." + actual_output = "The customer success line is 999" + context = ["Dogs and cats love to walk around the beach."] with pytest.raises(AssertionError): - assert_factual_consistency(query, expected_output) + assert_factual_consistency(actual_output, context) def test_0(): query = "How does photosynthesis work?" output = "Photosynthesis is the process by which green plants and some other organisms use sunlight to synthesize foods with the help of chlorophyll pigment." expected_output = "Photosynthesis is the process by which green plants and some other organisms use sunlight to synthesize food with the help of chlorophyll pigment." - context = "Biology" + context = ["Biology"] test_case = LLMTestCase( input=query, diff --git a/tests/test_ragas.py b/tests/test_ragas.py index b631a2ea7..a12677a7a 100644 --- a/tests/test_ragas.py +++ b/tests/test_ragas.py @@ -6,7 +6,7 @@ query = "Who won the FIFA World Cup in 2018?" output = "Winners of the FIFA world cup were the French national football team" expected_output = "French national football team" -context = "The FIFA World Cup in 2018 was won by the French national football team. They defeated Croatia 4-2 in the final match to claim the championship." +context = ["The FIFA World Cup in 2018 was won by the French national football team. They defeated Croatia 4-2 in the final match to claim the championship."] @pytest.mark.skip(reason="openai is expensive") From c43ad5d70759f48deda6e3930b63303e7b8173b8 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Fri, 10 Nov 2023 17:12:56 -0800 Subject: [PATCH 17/38] fix tests --- tests/test_ragas.py | 1 - 1 file changed, 1 deletion(-) diff --git a/tests/test_ragas.py b/tests/test_ragas.py index a12677a7a..186861152 100644 --- a/tests/test_ragas.py +++ b/tests/test_ragas.py @@ -9,7 +9,6 @@ context = ["The FIFA World Cup in 2018 was won by the French national football team. They defeated Croatia 4-2 in the final match to claim the championship."] -@pytest.mark.skip(reason="openai is expensive") def test_ragas_score(): test_case = LLMTestCase( input=query, From 297a886ee6db32b858524a9c745f6448eb838a92 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Fri, 10 Nov 2023 17:22:21 -0800 Subject: [PATCH 18/38] . --- tests/test_ragas.py | 1 + 1 file changed, 1 insertion(+) diff --git a/tests/test_ragas.py b/tests/test_ragas.py index 186861152..a12677a7a 100644 --- a/tests/test_ragas.py +++ b/tests/test_ragas.py @@ -9,6 +9,7 @@ context = ["The FIFA World Cup in 2018 was won by the French national football team. They defeated Croatia 4-2 in the final match to claim the championship."] +@pytest.mark.skip(reason="openai is expensive") def test_ragas_score(): test_case = LLMTestCase( input=query, From 79aa318d02cdc8ef8a5b2c91bfea19d10c75fd46 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Fri, 10 Nov 2023 18:22:13 -0800 Subject: [PATCH 19/38] fix tests --- tests/test_quickstart.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/tests/test_quickstart.py b/tests/test_quickstart.py index 1f384f8cb..bb5235531 100644 --- a/tests/test_quickstart.py +++ b/tests/test_quickstart.py @@ -14,14 +14,14 @@ def generate_llm_output(query: str): def test_llm_output(): - query = "What is the customer success phone line?" - expected_output = "Our customer success phone line is 1200-231-231." - output = generate_llm_output(query) - assert_factual_consistency(output, expected_output) + input = "What is the customer success phone line?" + context = ["Our customer success phone line is 1200-231-231."] + output = generate_llm_output(input) + assert_factual_consistency(output, context) def test_llm_output_custom(): - actual_output = "The customer success line is 999" + actual_output = "Dogs and cats hate to walk around the beach." context = ["Dogs and cats love to walk around the beach."] with pytest.raises(AssertionError): assert_factual_consistency(actual_output, context) From 00f34d56a027ae0775aad593ea5ed9fe585f4479 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Fri, 10 Nov 2023 18:22:36 -0800 Subject: [PATCH 20/38] . --- tests/test_chatbot_example.py | 8 ++++++-- tests/test_ragas.py | 4 +++- 2 files changed, 9 insertions(+), 3 deletions(-) diff --git a/tests/test_chatbot_example.py b/tests/test_chatbot_example.py index 2b73b9bf4..cc08217ad 100644 --- a/tests/test_chatbot_example.py +++ b/tests/test_chatbot_example.py @@ -9,7 +9,9 @@ def test_1(): output = ( "Specializes in cloud computing, data analytics, and machine learning." ) - context = ["Our company specializes in cloud computing, data analytics, and machine learning. We offer a range of services including cloud storage solutions, data analytics platforms, and custom machine learning models."] + context = [ + "Our company specializes in cloud computing, data analytics, and machine learning. We offer a range of services including cloud storage solutions, data analytics platforms, and custom machine learning models." + ] factual_consistency_metric = FactualConsistencyMetric(minimum_score=1.0) test_case = LLMTestCase(input=input, actual_output=output, context=context) with pytest.raises(AssertionError): @@ -21,7 +23,9 @@ def test_2(): output = ( "Specializes in cloud computing, data analytics, and machine learning." ) - context = ["Our company specializes in cloud computing, data analytics, and machine learning. We offer a range of services including cloud storage solutions, data analytics platforms, and custom machine learning models."] + context = [ + "Our company specializes in cloud computing, data analytics, and machine learning. We offer a range of services including cloud storage solutions, data analytics platforms, and custom machine learning models." + ] factual_consistency_metric_half = FactualConsistencyMetric( minimum_score=0.5 ) diff --git a/tests/test_ragas.py b/tests/test_ragas.py index a12677a7a..c4fbfb972 100644 --- a/tests/test_ragas.py +++ b/tests/test_ragas.py @@ -6,7 +6,9 @@ query = "Who won the FIFA World Cup in 2018?" output = "Winners of the FIFA world cup were the French national football team" expected_output = "French national football team" -context = ["The FIFA World Cup in 2018 was won by the French national football team. They defeated Croatia 4-2 in the final match to claim the championship."] +context = [ + "The FIFA World Cup in 2018 was won by the French national football team. They defeated Croatia 4-2 in the final match to claim the championship." +] @pytest.mark.skip(reason="openai is expensive") From 92ed82460732f3e2330efdf9a85528ba59b79ee8 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Fri, 10 Nov 2023 18:30:40 -0800 Subject: [PATCH 21/38] removed dataset test --- sample.csv | 7 + test-result-2023-11-10-18:28:41.115015.txt | 7 + tests/test_dataset.py | 178 ++++++++++----------- 3 files changed, 103 insertions(+), 89 deletions(-) create mode 100644 sample.csv create mode 100644 test-result-2023-11-10-18:28:41.115015.txt diff --git a/sample.csv b/sample.csv new file mode 100644 index 000000000..f4a11e24e --- /dev/null +++ b/sample.csv @@ -0,0 +1,7 @@ +id,query,expected_output,output + 1,"Hello, world!","This is a greeting.","This is a friendly greeting." + 2,"OpenAI GPT-3","A powerful language model.","A powerful AI language model." + 3,"CSV Example","Working with CSV data.","Working with data in CSV format." + 4,"Python Programming","Coding in Python.","Writing code in Python." + 5,"Data Science","Analyzing data.","Exploring and analyzing data." + \ No newline at end of file diff --git a/test-result-2023-11-10-18:28:41.115015.txt b/test-result-2023-11-10-18:28:41.115015.txt new file mode 100644 index 000000000..d545dc7df --- /dev/null +++ b/test-result-2023-11-10-18:28:41.115015.txt @@ -0,0 +1,7 @@ +Test Passed Metric Name Score Output Expected output Message +------------- --------------------- -------- -------------------------------- -------------------------- --------- +True Conceptual Similarity 0.899202 This is a friendly greeting. This is a greeting. +True Conceptual Similarity 0.889562 A powerful AI language model. A powerful language model. +True Conceptual Similarity 0.966732 Working with data in CSV format. Working with CSV data. +True Conceptual Similarity 0.948111 Writing code in Python. Coding in Python. +True Conceptual Similarity 0.870464 Exploring and analyzing data. Analyzing data. \ No newline at end of file diff --git a/tests/test_dataset.py b/tests/test_dataset.py index cd3e99e6e..904bafef6 100644 --- a/tests/test_dataset.py +++ b/tests/test_dataset.py @@ -3,92 +3,92 @@ import pytest -def test_evaluation_dataset(): - from deepeval.dataset import EvaluationDataset - - csv_filename = "sample.csv" - - csv_file = """id,query,expected_output - 1,"Hello, world!","This is a greeting." - 2,"OpenAI GPT-3","A powerful language model." - 3,"CSV Example","Working with CSV data." - 4,"Python Programming","Coding in Python." - 5,"Data Science","Analyzing data." - """ - - with open(csv_filename, "w") as file: - file.write(csv_file) - - dataset = EvaluationDataset.from_csv( - csv_filename, - query_column="query", - expected_output_column="expected_output", - id_column="id", - ) - assert len(dataset) == 5 - - -@pytest.mark.skip(reason="OpenAI costs") -def test_create_synthetic_dataset(): - """ - test for creating a synthetic dataset - """ - from deepeval.dataset import create_evaluation_query_answer_pairs - - dataset = create_evaluation_query_answer_pairs( - openai_api_key=os.environ["OPENAI_API_KEY"], - context="FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.7+ based on standard Python type hints.", - n=1, - ) - assert len(dataset) == 1 - - -def test_dataset_evaluation(): - """ - Test dataset evaluation - """ - from deepeval.dataset import EvaluationDataset - from deepeval.metrics.conceptual_similarity import ( - ConceptualSimilarityMetric, - ) - - csv_filename = "sample.csv" - - csv_file = """id,query,expected_output,output - 1,"Hello, world!","This is a greeting.","This is a friendly greeting." - 2,"OpenAI GPT-3","A powerful language model.","A powerful AI language model." - 3,"CSV Example","Working with CSV data.","Working with data in CSV format." - 4,"Python Programming","Coding in Python.","Writing code in Python." - 5,"Data Science","Analyzing data.","Exploring and analyzing data." - """ - - with open(csv_filename, "w") as file: - file.write(csv_file) - - dataset: EvaluationDataset = EvaluationDataset.from_csv( - csv_filename, - query_column="query", - expected_output_column="expected_output", - id_column="id", - output_column="output", - ) - metric = ConceptualSimilarityMetric() - result = dataset.run_evaluation( - outputs="output", - metrics=[metric], - ) - - -@pytest.mark.skip(reason="OpenAI costs") -def test_create_evaluation_query_answer_pairs(): - """ - test for creating a synthetic dataset - """ - from deepeval.dataset import create_evaluation_query_answer_pairs - - dataset = create_evaluation_query_answer_pairs( - openai_api_key=os.environ["OPENAI_API_KEY"], - context="FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.7+ based on standard Python type hints.", - n=10, - ) - assert len(dataset) == 10 +# def test_evaluation_dataset(): +# from deepeval.dataset import EvaluationDataset + +# csv_filename = "sample.csv" + +# csv_file = """id,query,expected_output +# 1,"Hello, world!","This is a greeting." +# 2,"OpenAI GPT-3","A powerful language model." +# 3,"CSV Example","Working with CSV data." +# 4,"Python Programming","Coding in Python." +# 5,"Data Science","Analyzing data." +# """ + +# with open(csv_filename, "w") as file: +# file.write(csv_file) + +# dataset = EvaluationDataset.from_csv( +# csv_filename, +# query_column="query", +# expected_output_column="expected_output", +# id_column="id", +# ) +# assert len(dataset) == 5 + + +# @pytest.mark.skip(reason="OpenAI costs") +# def test_create_synthetic_dataset(): +# """ +# test for creating a synthetic dataset +# """ +# from deepeval.dataset import create_evaluation_query_answer_pairs + +# dataset = create_evaluation_query_answer_pairs( +# openai_api_key=os.environ["OPENAI_API_KEY"], +# context="FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.7+ based on standard Python type hints.", +# n=1, +# ) +# assert len(dataset) == 1 + + +# def test_dataset_evaluation(): +# """ +# Test dataset evaluation +# """ +# from deepeval.dataset import EvaluationDataset +# from deepeval.metrics.conceptual_similarity import ( +# ConceptualSimilarityMetric, +# ) + +# csv_filename = "sample.csv" + +# csv_file = """id,query,expected_output,output +# 1,"Hello, world!","This is a greeting.","This is a friendly greeting." +# 2,"OpenAI GPT-3","A powerful language model.","A powerful AI language model." +# 3,"CSV Example","Working with CSV data.","Working with data in CSV format." +# 4,"Python Programming","Coding in Python.","Writing code in Python." +# 5,"Data Science","Analyzing data.","Exploring and analyzing data." +# """ + +# with open(csv_filename, "w") as file: +# file.write(csv_file) + +# dataset: EvaluationDataset = EvaluationDataset.from_csv( +# csv_filename, +# query_column="query", +# expected_output_column="expected_output", +# id_column="id", +# output_column="output", +# ) +# metric = ConceptualSimilarityMetric() +# result = dataset.run_evaluation( +# outputs="output", +# metrics=[metric], +# ) + + +# @pytest.mark.skip(reason="OpenAI costs") +# def test_create_evaluation_query_answer_pairs(): +# """ +# test for creating a synthetic dataset +# """ +# from deepeval.dataset import create_evaluation_query_answer_pairs + +# dataset = create_evaluation_query_answer_pairs( +# openai_api_key=os.environ["OPENAI_API_KEY"], +# context="FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.7+ based on standard Python type hints.", +# n=10, +# ) +# assert len(dataset) == 10 From e1f80178d6833b7568605de2ea469b6ebf917bd5 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Fri, 10 Nov 2023 18:30:56 -0800 Subject: [PATCH 22/38] removed files --- sample.csv | 7 ------- test-result-2023-11-10-18:28:41.115015.txt | 7 ------- 2 files changed, 14 deletions(-) delete mode 100644 sample.csv delete mode 100644 test-result-2023-11-10-18:28:41.115015.txt diff --git a/sample.csv b/sample.csv deleted file mode 100644 index f4a11e24e..000000000 --- a/sample.csv +++ /dev/null @@ -1,7 +0,0 @@ -id,query,expected_output,output - 1,"Hello, world!","This is a greeting.","This is a friendly greeting." - 2,"OpenAI GPT-3","A powerful language model.","A powerful AI language model." - 3,"CSV Example","Working with CSV data.","Working with data in CSV format." - 4,"Python Programming","Coding in Python.","Writing code in Python." - 5,"Data Science","Analyzing data.","Exploring and analyzing data." - \ No newline at end of file diff --git a/test-result-2023-11-10-18:28:41.115015.txt b/test-result-2023-11-10-18:28:41.115015.txt deleted file mode 100644 index d545dc7df..000000000 --- a/test-result-2023-11-10-18:28:41.115015.txt +++ /dev/null @@ -1,7 +0,0 @@ -Test Passed Metric Name Score Output Expected output Message -------------- --------------------- -------- -------------------------------- -------------------------- --------- -True Conceptual Similarity 0.899202 This is a friendly greeting. This is a greeting. -True Conceptual Similarity 0.889562 A powerful AI language model. A powerful language model. -True Conceptual Similarity 0.966732 Working with data in CSV format. Working with CSV data. -True Conceptual Similarity 0.948111 Writing code in Python. Coding in Python. -True Conceptual Similarity 0.870464 Exploring and analyzing data. Analyzing data. \ No newline at end of file From 7a5070b96ce8cc82536f0038cb76932012bed003 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Fri, 10 Nov 2023 18:37:13 -0800 Subject: [PATCH 23/38] removed test ragas --- tests/test_ragas.py | 28 ++++++++++++++-------------- 1 file changed, 14 insertions(+), 14 deletions(-) diff --git a/tests/test_ragas.py b/tests/test_ragas.py index c4fbfb972..328ec52c4 100644 --- a/tests/test_ragas.py +++ b/tests/test_ragas.py @@ -11,18 +11,18 @@ ] -@pytest.mark.skip(reason="openai is expensive") -def test_ragas_score(): - test_case = LLMTestCase( - input=query, - actual_output=output, - expected_output=expected_output, - context=context, - ) - metric = RagasMetric() +# @pytest.mark.skip(reason="openai is expensive") +# def test_ragas_score(): +# test_case = LLMTestCase( +# input=query, +# actual_output=output, +# expected_output=expected_output, +# context=context, +# ) +# metric = RagasMetric() - with pytest.raises(AssertionError): - assert_test( - test_cases=[test_case], - metrics=[metric], - ) +# with pytest.raises(AssertionError): +# assert_test( +# test_cases=[test_case], +# metrics=[metric], +# ) From 7b27efa126af499f1557ec1ddc08eb439068bb79 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Fri, 10 Nov 2023 18:45:06 -0800 Subject: [PATCH 24/38] . --- deepeval/plugins/plugin.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/deepeval/plugins/plugin.py b/deepeval/plugins/plugin.py index ba11e1692..0a22b96e3 100644 --- a/deepeval/plugins/plugin.py +++ b/deepeval/plugins/plugin.py @@ -51,6 +51,9 @@ def pytest_sessionfinish(session: pytest.Session, exitstatus): metrics_avg = { metric.metric: metric.score for metric in test_run.metric_scores } + print(test_run) + print("!!!!!!!!!!!!!!!") + print(test_run.metric_scores) # Count the number of passes and failures # Get all the possible metrics first all_metrics = {metric.metric for metric in test_run.metric_scores} From 58be77b155b1e4e5301b8bccf9869f1adc09b922 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Fri, 10 Nov 2023 18:53:54 -0800 Subject: [PATCH 25/38] . --- deepeval/plugins/plugin.py | 1 + deepeval/test_run.py | 1 + 2 files changed, 2 insertions(+) diff --git a/deepeval/plugins/plugin.py b/deepeval/plugins/plugin.py index 0a22b96e3..b37431b61 100644 --- a/deepeval/plugins/plugin.py +++ b/deepeval/plugins/plugin.py @@ -18,6 +18,7 @@ def pytest_sessionstart(session: pytest.Session): configurations={}, ) test_run_manager.set_test_run(test_run) + print(test_run_manager.test_run) @pytest.hookimpl(tryfirst=True) diff --git a/deepeval/test_run.py b/deepeval/test_run.py index ab907139d..1b4492bd9 100644 --- a/deepeval/test_run.py +++ b/deepeval/test_run.py @@ -154,6 +154,7 @@ def add_llm_test_case( for metric in test_case.metrics_metadata: all_metric_dict.add_metric(metric.metric, metric.score) self.metric_scores = all_metric_dict.get_average_metric_score() + print(self.test_cases) def save(self, file_path: Optional[str] = None): if file_path is None: From e9cf806debeca1d56023eec3c200008af31837e0 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Fri, 10 Nov 2023 19:03:58 -0800 Subject: [PATCH 26/38] . --- tests/test_result.py | 24 ++++++++++++------------ 1 file changed, 12 insertions(+), 12 deletions(-) diff --git a/tests/test_result.py b/tests/test_result.py index b7f7802e1..1205d624e 100644 --- a/tests/test_result.py +++ b/tests/test_result.py @@ -1,15 +1,15 @@ from deepeval.evaluator import TestResult -def test_result(): - result = TestResult( - success=True, - score=2.0, - metric_name="test_metric", - query="test_query", - output="test_output", - expected_output="test_expected_output", - metadata=None, - context="test_context", - ) - assert result.score == 1.0 +# def test_result(): +# result = TestResult( +# success=True, +# score=2.0, +# metric_name="test_metric", +# query="test_query", +# output="test_output", +# expected_output="test_expected_output", +# metadata=None, +# context="test_context", +# ) +# assert result.score == 1.0 From 7e90eecf73befcef9c22f99b0f923a8c6f1f23e0 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Fri, 10 Nov 2023 19:14:40 -0800 Subject: [PATCH 27/38] . --- deepeval/evaluator.py | 2 ++ tests/test_result.py | 15 --------------- 2 files changed, 2 insertions(+), 15 deletions(-) delete mode 100644 tests/test_result.py diff --git a/deepeval/evaluator.py b/deepeval/evaluator.py index 00f590382..f90a4bd5a 100644 --- a/deepeval/evaluator.py +++ b/deepeval/evaluator.py @@ -104,6 +104,7 @@ def run_test( min_success: int = 1, raise_error: bool = False, ) -> List[TestResult]: + print("ksjfnsakjnfdkasnfkasjfk") if isinstance(test_cases, TestCase): test_cases = [test_cases] @@ -128,6 +129,7 @@ def run_test( # Load the test_run and add the test_case regardless of the success of the test test_end_time = time.perf_counter() run_duration = test_end_time - test_start_time + print("right before") if os.getenv(PYTEST_RUN_ENV_VAR): metric.score = score test_run.add_llm_test_case( diff --git a/tests/test_result.py b/tests/test_result.py deleted file mode 100644 index 1205d624e..000000000 --- a/tests/test_result.py +++ /dev/null @@ -1,15 +0,0 @@ -from deepeval.evaluator import TestResult - - -# def test_result(): -# result = TestResult( -# success=True, -# score=2.0, -# metric_name="test_metric", -# query="test_query", -# output="test_output", -# expected_output="test_expected_output", -# metadata=None, -# context="test_context", -# ) -# assert result.score == 1.0 From 913c8f692ede8cc30dfeb1acd2a44b57453c1420 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Fri, 10 Nov 2023 19:26:52 -0800 Subject: [PATCH 28/38] . --- .github/workflows/test.yml | 1 + deepeval/evaluator.py | 55 +++----------------------------------- tests/test_llm_metric.py | 4 +-- 3 files changed, 6 insertions(+), 54 deletions(-) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 14dd22dbb..7b42fc885 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -64,5 +64,6 @@ jobs: - name: Run tests env: OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} + PYTEST_RUN_ENV_VAR: "CONFIDENT_AI_RUN_TIMESTAMP" run: | poetry run pytest tests/ --ignore=tests/test_llm_metric.py --ignore=tests/test_overall_score.py diff --git a/deepeval/evaluator.py b/deepeval/evaluator.py index f90a4bd5a..0900cce64 100644 --- a/deepeval/evaluator.py +++ b/deepeval/evaluator.py @@ -6,40 +6,11 @@ import time from dataclasses import dataclass from .retry import retry -from .constants import ( - LOG_TO_SERVER_ENV, - PYTEST_RUN_ENV_VAR, -) -from .get_api_key import _get_api_key +from .constants import PYTEST_RUN_ENV_VAR + from .metrics import BaseMetric from .test_case import LLMTestCase, TestCase -from deepeval.test_run import test_run_manager, TestRun - - -def _is_api_key_set(): - result = _get_api_key() - # if result == "" or result is None: - # warnings.warn( - # """API key is not set - you won't be able to log to the DeepEval dashboard. Please set it by running `deepeval login`""" - # ) - if result == "" or result is None: - return False - return True - - -def _is_send_okay(): - # DOing this until the API endpoint is fixed - return _is_api_key_set() and os.getenv(LOG_TO_SERVER_ENV) != "Y" - - -def _get_init_values(metric: BaseMetric): - # We use this method for sending useful metadata - init_values = { - param: getattr(metric, param) - for param in vars(metric) - if isinstance(getattr(metric, param), (str, int, float)) - } - return init_values +from deepeval.test_run import test_run_manager @dataclass @@ -157,6 +128,7 @@ def assert_test( min_success: int = 1, ) -> List[TestResult]: """Assert a test""" + print("sldafjnaljfnlasjf") return run_test( test_cases=test_cases, metrics=metrics, @@ -165,22 +137,3 @@ def assert_test( min_success=min_success, raise_error=True, ) - - -def is_test_passing( - test_cases: Union[LLMTestCase, List[LLMTestCase]], - metrics: List[BaseMetric], - max_retries: int = 1, - delay: int = 1, - min_success: int = 1, -) -> bool: - """Check if a test is passing""" - test_results = run_test( - test_cases=test_cases, - metrics=metrics, - max_retries=max_retries, - delay=delay, - min_success=min_success, - raise_error=False, - ) - return all(result.success for result in test_results) diff --git a/tests/test_llm_metric.py b/tests/test_llm_metric.py index 5beb1000c..cd1a0ab0b 100644 --- a/tests/test_llm_metric.py +++ b/tests/test_llm_metric.py @@ -22,7 +22,5 @@ def test_chat_completion(): expected_output="Paris", context=["Geography"], ) - # metric.measure(test_case) - # assert metric.is_successful() is True - # assert metric.measure(test_case) <= 1.0 + assert_test(test_case, [metric]) From 012a48f337734109385ce8aa0e76c965ddce1110 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Fri, 10 Nov 2023 19:34:26 -0800 Subject: [PATCH 29/38] . --- deepeval/plugins/plugin.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/deepeval/plugins/plugin.py b/deepeval/plugins/plugin.py index b37431b61..b123dcd4d 100644 --- a/deepeval/plugins/plugin.py +++ b/deepeval/plugins/plugin.py @@ -38,7 +38,7 @@ def pytest_sessionfinish(session: pytest.Session, exitstatus): yield test_run = test_run_manager.get_test_run() - if test_run is None: + if test_run is None or len(test_run.test_cases) == 0: print("Test Run is empty, please try again.") return From 0dd1a4e2391ef30851000966f14cd2715b4583d5 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Fri, 10 Nov 2023 20:03:57 -0800 Subject: [PATCH 30/38] reformat --- .github/workflows/test.yml | 1 - deepeval/evaluator.py | 3 --- deepeval/plugins/plugin.py | 5 +---- deepeval/test_run.py | 1 - tests/test_ragas.py | 28 ++++++++++++++-------------- 5 files changed, 15 insertions(+), 23 deletions(-) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 7b42fc885..14dd22dbb 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -64,6 +64,5 @@ jobs: - name: Run tests env: OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} - PYTEST_RUN_ENV_VAR: "CONFIDENT_AI_RUN_TIMESTAMP" run: | poetry run pytest tests/ --ignore=tests/test_llm_metric.py --ignore=tests/test_overall_score.py diff --git a/deepeval/evaluator.py b/deepeval/evaluator.py index 0900cce64..4a16c8054 100644 --- a/deepeval/evaluator.py +++ b/deepeval/evaluator.py @@ -75,7 +75,6 @@ def run_test( min_success: int = 1, raise_error: bool = False, ) -> List[TestResult]: - print("ksjfnsakjnfdkasnfkasjfk") if isinstance(test_cases, TestCase): test_cases = [test_cases] @@ -100,7 +99,6 @@ def run_test( # Load the test_run and add the test_case regardless of the success of the test test_end_time = time.perf_counter() run_duration = test_end_time - test_start_time - print("right before") if os.getenv(PYTEST_RUN_ENV_VAR): metric.score = score test_run.add_llm_test_case( @@ -128,7 +126,6 @@ def assert_test( min_success: int = 1, ) -> List[TestResult]: """Assert a test""" - print("sldafjnaljfnlasjf") return run_test( test_cases=test_cases, metrics=metrics, diff --git a/deepeval/plugins/plugin.py b/deepeval/plugins/plugin.py index b123dcd4d..72e11b46c 100644 --- a/deepeval/plugins/plugin.py +++ b/deepeval/plugins/plugin.py @@ -18,7 +18,6 @@ def pytest_sessionstart(session: pytest.Session): configurations={}, ) test_run_manager.set_test_run(test_run) - print(test_run_manager.test_run) @pytest.hookimpl(tryfirst=True) @@ -52,9 +51,7 @@ def pytest_sessionfinish(session: pytest.Session, exitstatus): metrics_avg = { metric.metric: metric.score for metric in test_run.metric_scores } - print(test_run) - print("!!!!!!!!!!!!!!!") - print(test_run.metric_scores) + # Count the number of passes and failures # Get all the possible metrics first all_metrics = {metric.metric for metric in test_run.metric_scores} diff --git a/deepeval/test_run.py b/deepeval/test_run.py index 1b4492bd9..ab907139d 100644 --- a/deepeval/test_run.py +++ b/deepeval/test_run.py @@ -154,7 +154,6 @@ def add_llm_test_case( for metric in test_case.metrics_metadata: all_metric_dict.add_metric(metric.metric, metric.score) self.metric_scores = all_metric_dict.get_average_metric_score() - print(self.test_cases) def save(self, file_path: Optional[str] = None): if file_path is None: diff --git a/tests/test_ragas.py b/tests/test_ragas.py index 328ec52c4..c4fbfb972 100644 --- a/tests/test_ragas.py +++ b/tests/test_ragas.py @@ -11,18 +11,18 @@ ] -# @pytest.mark.skip(reason="openai is expensive") -# def test_ragas_score(): -# test_case = LLMTestCase( -# input=query, -# actual_output=output, -# expected_output=expected_output, -# context=context, -# ) -# metric = RagasMetric() +@pytest.mark.skip(reason="openai is expensive") +def test_ragas_score(): + test_case = LLMTestCase( + input=query, + actual_output=output, + expected_output=expected_output, + context=context, + ) + metric = RagasMetric() -# with pytest.raises(AssertionError): -# assert_test( -# test_cases=[test_case], -# metrics=[metric], -# ) + with pytest.raises(AssertionError): + assert_test( + test_cases=[test_case], + metrics=[metric], + ) From f7350b1591c0aa7f22b27ad47cdfd184af7dcbd3 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Fri, 10 Nov 2023 22:00:02 -0800 Subject: [PATCH 31/38] add thread WIP --- deepeval/cli/test.py | 7 + poetry.lock | 325 ++++++++++++++++++++++++++++--------------- pyproject.toml | 5 +- 3 files changed, 223 insertions(+), 114 deletions(-) diff --git a/deepeval/cli/test.py b/deepeval/cli/test.py index d407f0ee5..a40388e04 100644 --- a/deepeval/cli/test.py +++ b/deepeval/cli/test.py @@ -7,6 +7,7 @@ from .cli_key_handler import set_env_vars from ..constants import PYTEST_RUN_ENV_VAR from .examples import CUSTOMER_EXAMPLE +from typing import Optional try: from rich import print @@ -109,6 +110,9 @@ def run( show_warnings: Annotated[ bool, typer.Option("--show-warnings", "-w/-W") ] = False, + num_processes: Optional[int] = typer.Option( + None, "--num-processes", "-n", help="Number of processes to use with pytest" + ), ): """Run a test""" check_if_legit_file(test_file_or_directory) @@ -132,6 +136,9 @@ def run( pytest_args.append("--pdb") if not show_warnings: pytest_args.append("--disable-warnings") + if num_processes is not None: + pytest_args.extend(["-n", str(num_processes)]) + # Add the deepeval plugin file to pytest arguments pytest_args.extend(["-p", "plugins"]) diff --git a/poetry.lock b/poetry.lock index 20a9cafef..5ec33b732 100644 --- a/poetry.lock +++ b/poetry.lock @@ -232,29 +232,29 @@ transformers = ">=3.0.0" [[package]] name = "black" -version = "23.10.1" +version = "23.11.0" description = "The uncompromising code formatter." optional = false python-versions = ">=3.8" files = [ - {file = "black-23.10.1-cp310-cp310-macosx_10_16_arm64.whl", hash = "sha256:ec3f8e6234c4e46ff9e16d9ae96f4ef69fa328bb4ad08198c8cee45bb1f08c69"}, - {file = "black-23.10.1-cp310-cp310-macosx_10_16_x86_64.whl", hash = "sha256:1b917a2aa020ca600483a7b340c165970b26e9029067f019e3755b56e8dd5916"}, - {file = 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"sha256:924962dfc9d89602552e7332846e95d264eca18aebe2b96c2527d46b7bb7cf9c"}, + {file = "weasel-0.3.4-py3-none-any.whl", hash = "sha256:ee48a944f051d007201c2ea1661d0c41035028c5d5a8bcb29a0b10f1100206ae"}, + {file = "weasel-0.3.4.tar.gz", hash = "sha256:eb16f92dc9f1a3ffa89c165e3a9acd28018ebb656e0da4da02c0d7d8ae3f6178"}, ] [package.dependencies] @@ -4912,4 +5013,4 @@ multidict = ">=4.0" [metadata] lock-version = "2.0" python-versions = ">=3.10,<3.12" -content-hash = "33a90dd3fb6c5b15fac83fed98e27ff54146943eaf2b835fa7ff9f58ed6eca07" +content-hash = "3be9c581622bfb40b3128f66e7914345e0b472b204744eef9671556037eaf596" diff --git a/pyproject.toml b/pyproject.toml index 73526d3dd..b83525386 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -22,6 +22,9 @@ requests = "^2.31.0" tqdm = "^4.66.1" transformers = "^4.34.1" pytest = "^7.4.3" +pytest-xdist = "*" +pytest-rerunfailures = "^12.0" +pytest-asyncio = "^0.21.1" tabulate = "^0.9.0" sentence-transformers = "^2.2.2" dbias = "^0.1.5" @@ -32,8 +35,6 @@ bert-score = "^0.3.13" rich = "^13.6.0" torch = ">=2.0.0, !=2.0.1, !=2.1.0" ragas = "^0.0.19" -pytest-rerunfailures = "^12.0" -pytest-asyncio = "^0.21.1" coverage = "*" black = "*" From 32a5a731eb703284c8123b344e0efbb8025124d6 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Sun, 12 Nov 2023 23:52:21 -0800 Subject: [PATCH 32/38] Added parallel testing --- deepeval/api.py | 30 ---- deepeval/chat_completion/retry.py | 2 + deepeval/cli/test.py | 28 ++-- deepeval/constants.py | 2 +- deepeval/evaluator.py | 39 ++---- deepeval/plugins/plugin.py | 115 +--------------- deepeval/progress_context.py | 4 + deepeval/test_run.py | 200 ++++++++++++++++++++++++--- deepeval/utils.py | 8 ++ poetry.lock | 219 ++++++++++++++---------------- pyproject.toml | 2 + 11 files changed, 329 insertions(+), 320 deletions(-) diff --git a/deepeval/api.py b/deepeval/api.py index edf52f724..f80ea925d 100644 --- a/deepeval/api.py +++ b/deepeval/api.py @@ -3,9 +3,7 @@ import urllib.parse import requests import warnings -from pydantic import BaseModel from requests.adapters import HTTPAdapter, Response, Retry -from deepeval.test_run import TestRun from deepeval.constants import API_KEY_ENV from deepeval.key_handler import KEY_FILE_HANDLER @@ -18,14 +16,6 @@ HTTP_RETRY_ALLOWED_METHODS = frozenset({"GET", "POST", "DELETE"}) -class TestRunResponse(BaseModel): - """Add Test Run Results""" - - testRunId: str - projectId: str - link: str - - class Api: """Internal Api reference for handling http operations""" @@ -275,23 +265,3 @@ def quote_string(text: str) -> str: str: Quoted text in return """ return urllib.parse.quote(text, safe="") - - def post_test_run(self, test_run: TestRun) -> TestRunResponse: - """Post a test run""" - try: - # make sure to exclude none for `context` to ensure it is handled properly - body = test_run.model_dump(by_alias=True, exclude_none=True) - except AttributeError: - # Pydantic version below 2.0 - body = test_run.dict(by_alias=True, exclude_none=True) - - result = self.post_request( - endpoint="/v1/test-run", - body=body, - ) - response = TestRunResponse( - testRunId=result["testRunId"], - projectId=result["projectId"], - link=result["link"], - ) - return response diff --git a/deepeval/chat_completion/retry.py b/deepeval/chat_completion/retry.py index ec9fb64bb..e53ae8320 100644 --- a/deepeval/chat_completion/retry.py +++ b/deepeval/chat_completion/retry.py @@ -1,6 +1,8 @@ from typing import Callable, Any import openai import time +import os +import sys def call_openai_with_retry( diff --git a/deepeval/cli/test.py b/deepeval/cli/test.py index a40388e04..2e6d3344d 100644 --- a/deepeval/cli/test.py +++ b/deepeval/cli/test.py @@ -1,17 +1,15 @@ import pytest import typer import os -import datetime from typing_extensions import Annotated -from ..metrics.overall_score import assert_overall_score +from deepeval.metrics.overall_score import assert_overall_score from .cli_key_handler import set_env_vars -from ..constants import PYTEST_RUN_ENV_VAR -from .examples import CUSTOMER_EXAMPLE from typing import Optional +from deepeval.test_run import test_run_manager, TEMP_FILE_NAME +from deepeval.utils import delete_file_if_exists try: from rich import print - from rich.progress import Progress, SpinnerColumn, TextColumn except Exception as e: pass @@ -80,7 +78,7 @@ def sample(): pass -def check_if_legit_file(test_file_or_directory: str): +def check_if_valid_file(test_file_or_directory: str): if "::" in test_file_or_directory: test_file_or_directory, test_case = test_file_or_directory.split("::") if os.path.isfile(test_file_or_directory): @@ -111,19 +109,19 @@ def run( bool, typer.Option("--show-warnings", "-w/-W") ] = False, num_processes: Optional[int] = typer.Option( - None, "--num-processes", "-n", help="Number of processes to use with pytest" + None, + "--num-processes", + "-n", + help="Number of processes to use with pytest", ), ): """Run a test""" - check_if_legit_file(test_file_or_directory) + delete_file_if_exists(TEMP_FILE_NAME) + check_if_valid_file(test_file_or_directory) pytest_args = [test_file_or_directory] if exit_on_first_failure: pytest_args.insert(0, "-x") - # Generate environment variable based on current date and time - env_var = datetime.datetime.now().strftime("%Y%m%d_%H%M%S") - os.environ[PYTEST_RUN_ENV_VAR] = env_var - pytest_args.extend( [ "--verbose" if verbose else "--quiet", @@ -144,11 +142,7 @@ def run( retcode = pytest.main(pytest_args) - # Print this if the run env var is not set - if not os.getenv(PYTEST_RUN_ENV_VAR): - print( - "✅ Tests finished! If logged in, view results on https://app.confident-ai.com/" - ) + test_run_manager.wrap_up_test_run() return retcode diff --git a/deepeval/constants.py b/deepeval/constants.py index 095e09261..4b4555973 100644 --- a/deepeval/constants.py +++ b/deepeval/constants.py @@ -1,5 +1,5 @@ API_KEY_ENV: str = "CONFIDENT_AI_API_KEY" LOG_TO_SERVER_ENV: str = "DO_NOT_SEND_TO_CONFIDENT_AI" KEY_FILE: str = ".deepeval" -PYTEST_RUN_ENV_VAR: str = "CONFIDENT_AI_RUN_TIMESTAMP" +PYTEST_TEMP_FILE_NAME_ENV_VAR: str = "CONFIDENT_AI_RUN_TIMESTAMP" PYTEST_RUN_TEST_NAME: str = "CONFIDENT_AI_RUN_TEST_NAME" diff --git a/deepeval/evaluator.py b/deepeval/evaluator.py index 4a16c8054..63322ce9f 100644 --- a/deepeval/evaluator.py +++ b/deepeval/evaluator.py @@ -6,11 +6,11 @@ import time from dataclasses import dataclass from .retry import retry -from .constants import PYTEST_RUN_ENV_VAR from .metrics import BaseMetric from .test_case import LLMTestCase, TestCase from deepeval.test_run import test_run_manager +import sys @dataclass @@ -47,13 +47,12 @@ def __lt__(self, other: "TestResult") -> bool: def create_test_result( test_case: LLMTestCase, success: bool, - score: float, metric: float, ) -> TestResult: if isinstance(test_case, LLMTestCase): return TestResult( success=success, - score=score, + score=metric.score, metric_name=metric.__name__, query=test_case.input if test_case.input else "-", output=test_case.actual_output if test_case.actual_output else "-", @@ -79,36 +78,28 @@ def run_test( test_cases = [test_cases] test_results = [] - test_run = test_run_manager.get_test_run() for test_case in test_cases: failed_metrics = [] for metric in metrics: test_start_time = time.perf_counter() - - # @retry( - # max_retries=max_retries, - # delay=delay, - # min_success=min_success, - # ) - # def measure_metric(): - score = metric.measure(test_case) + # score = metric.measure(test_case) + metric.score = metric.measure(test_case) success = metric.is_successful() - test_result = create_test_result(test_case, success, score, metric) - test_results.append(test_result) - - # Load the test_run and add the test_case regardless of the success of the test test_end_time = time.perf_counter() run_duration = test_end_time - test_start_time - if os.getenv(PYTEST_RUN_ENV_VAR): - metric.score = score - test_run.add_llm_test_case( - test_case=test_case, - metrics=[metric], - run_duration=run_duration, - ) + # metric.score = score + test_run_manager.get_test_run().add_llm_test_case( + test_case=test_case, + metrics=[metric], + run_duration=run_duration, + ) + test_run_manager.save_test_run() + + test_result = create_test_result(test_case, success, metric) + test_results.append(test_result) if not success: - failed_metrics.append((metric.__name__, score)) + failed_metrics.append((metric.__name__, metric.score)) if raise_error and failed_metrics: raise AssertionError( diff --git a/deepeval/plugins/plugin.py b/deepeval/plugins/plugin.py index 72e11b46c..61f1845d7 100644 --- a/deepeval/plugins/plugin.py +++ b/deepeval/plugins/plugin.py @@ -1,13 +1,10 @@ import pytest -import shutil import os from rich import print -from deepeval.api import Api from typing import Optional, Any -from deepeval.constants import PYTEST_RUN_ENV_VAR, PYTEST_RUN_TEST_NAME -from deepeval.decorators.hyperparameters import get_hyperparameters +from deepeval.constants import PYTEST_RUN_TEST_NAME from deepeval.test_run import TestRun, test_run_manager -import webbrowser +import sys def pytest_sessionstart(session: pytest.Session): @@ -18,6 +15,7 @@ def pytest_sessionstart(session: pytest.Session): configurations={}, ) test_run_manager.set_test_run(test_run) + test_run_manager.save_test_run() @pytest.hookimpl(tryfirst=True) @@ -31,116 +29,9 @@ def pytest_runtest_protocol( @pytest.hookimpl(tryfirst=True, hookwrapper=True) def pytest_sessionfinish(session: pytest.Session, exitstatus): print("Running teardown with pytest sessionfinish...") - # Code before yield will run before the test teardown - # yield control back to pytest for the actual teardown yield - test_run = test_run_manager.get_test_run() - if test_run is None or len(test_run.test_cases) == 0: - print("Test Run is empty, please try again.") - return - - del test_run.dict_test_cases - if os.getenv(PYTEST_RUN_ENV_VAR) and os.path.exists(".deepeval"): - api: Api = Api() - test_run.configurations = get_hyperparameters() - result = api.post_test_run(test_run) - - # Calculate the average of each metric - metrics_avg = { - metric.metric: metric.score for metric in test_run.metric_scores - } - - # Count the number of passes and failures - # Get all the possible metrics first - all_metrics = {metric.metric for metric in test_run.metric_scores} - - # Loop through to filter for each metric - passes = { - metric: len( - [ - test_case_metric - for test_case in test_run.test_cases - for test_case_metric in test_case.metrics_metadata - if test_case_metric.metric == metric and test_case.success - ] - ) - for metric in all_metrics - } - failures = { - metric: len( - [ - test_case_metric - for test_case in test_run.test_cases - for test_case_metric in test_case.metrics_metadata - if test_case_metric.metric == metric - ] - ) - - passes[metric] - for metric in all_metrics - } - # Create a table with rich - from rich.table import Table - - table = Table(title="Test Results") - table.add_column("Metric", justify="right") - table.add_column("Average Score", justify="right") - table.add_column("Passes", justify="right") - table.add_column("Failures", justify="right") - table.add_column("Success Rate", justify="right") - total_passes = 0 - total_failures = 0 - for metric, avg in metrics_avg.items(): - pass_count = passes[metric] - fail_count = failures[metric] - total_passes += pass_count - total_failures += fail_count - success_rate = pass_count / (pass_count + fail_count) * 100 - table.add_row( - metric, - str(avg), - f"[green]{str(pass_count)}[/green]", - f"[red]{str(fail_count)}[/red]", - f"{success_rate:.2f}%", - ) - total_tests = total_passes + total_failures - overall_success_rate = total_passes / total_tests * 100 - table.add_row( - "Total", - "-", - f"[green]{str(total_passes)}[/green]", - f"[red]{str(total_failures)}[/red]", - f"{overall_success_rate:.2f}%", - ) - print(table) - - if os.getenv(PYTEST_RUN_ENV_VAR) and os.path.exists(".deepeval"): - link = result.link - print( - "✅ Tests finished! View results on " f"[link={link}]{link}[/link]" - ) - webbrowser.open(link) - else: - print( - '✅ Tests finished! Run "deepeval login" to view evaluation results on the web.' - ) - local_folder = os.getenv("DEEPEVAL_RESULTS_FOLDER") - if local_folder: - test_filename = test_run.save() - if not os.path.exists(local_folder): - os.mkdir(local_folder) - shutil.copy(test_filename, local_folder) - print(f"Results saved in {local_folder} as {test_filename}") - elif os.path.isfile(local_folder): - print( - f"""❌ Error: DEEPEVAL_RESULTS_FOLDER={local_folder} already exists and is a file.\nDetailed results won't be saved. Please specify a folder or an available path.""" - ) - else: - shutil.copy(test_filename, local_folder) - print(f"Results saved in {local_folder} as {test_filename}") - os.remove(test_filename) - def pytest_terminal_summary(terminalreporter, exitstatus, config): for report in terminalreporter.getreports("skipped"): diff --git a/deepeval/progress_context.py b/deepeval/progress_context.py index eac84fa0b..ed1b3c523 100644 --- a/deepeval/progress_context.py +++ b/deepeval/progress_context.py @@ -1,14 +1,18 @@ +from rich.console import Console from rich.progress import Progress, SpinnerColumn, TextColumn from contextlib import contextmanager +import sys @contextmanager def progress_context( description: str, total: int = 9999, transient: bool = True ): + console = Console(file=sys.stderr) # Direct output to standard error with Progress( SpinnerColumn(), TextColumn("[progress.description]{task.description}"), + console=console, # Use the custom console transient=transient, ) as progress: progress.add_task(description=description, total=total) diff --git a/deepeval/test_run.py b/deepeval/test_run.py index ab907139d..448eb37a4 100644 --- a/deepeval/test_run.py +++ b/deepeval/test_run.py @@ -6,7 +6,20 @@ from deepeval.test_case import LLMTestCase from collections import defaultdict from deepeval.tracing import get_trace_stack -from deepeval.constants import PYTEST_RUN_TEST_NAME, PYTEST_RUN_ENV_VAR +from deepeval.constants import PYTEST_RUN_TEST_NAME +from deepeval.decorators.hyperparameters import get_hyperparameters +from deepeval.api import Api +import shutil +import webbrowser +from deepeval.utils import delete_file_if_exists +import sys +import datetime +import portalocker +from rich.table import Table +from rich.console import Console +from rich import print + +TEMP_FILE_NAME = "temp_test_run_data.json" class MetricsMetadata(BaseModel): @@ -147,39 +160,194 @@ def add_llm_test_case( ) self.dict_test_cases[test_case_id] = api_test_case - self.test_cases.append(api_test_case) + def cleanup(self): + for _, test_case in self.dict_test_cases.items(): + self.test_cases.append(test_case) + del self.dict_test_cases all_metric_dict = MetricDict() for test_case in self.test_cases: for metric in test_case.metrics_metadata: all_metric_dict.add_metric(metric.metric, metric.score) self.metric_scores = all_metric_dict.get_average_metric_score() + self.configurations = get_hyperparameters() + + def save(self, f): + json.dump(self.dict(by_alias=True, exclude_none=True), f) + return self + + @classmethod + def load(cls, f): + return cls(**json.load(f)) - def save(self, file_path: Optional[str] = None): - if file_path is None: - file_path = os.getenv(PYTEST_RUN_ENV_VAR) - # If file Path is None, remove it - if not file_path: - return - elif not file_path.endswith(".json"): - file_path = f"{file_path}.json" - with open(file_path, "w") as f: - json.dump(self.dict(by_alias=True, exclude_none=True), f) - return file_path +class TestRunHttpResponse(BaseModel): + testRunId: str + projectId: str + link: str -class TestRunManger: + +class TestRunManager: def __init__(self): self.test_run = None + self.temp_file_name = TEMP_FILE_NAME - def set_test_run(self, test_run: TestRun): + def set_test_run(self, test_run: "TestRun"): self.test_run = test_run def get_test_run(self): + try: + with portalocker.Lock( + self.temp_file_name, mode="r", timeout=5 + ) as file: + self.test_run = self.test_run.load(file) + except (FileNotFoundError, portalocker.exceptions.LockException): + print("Error loading test run from disk", file=sys.stderr) + self.test_run = None return self.test_run + def save_test_run(self): + try: + with portalocker.Lock( + self.temp_file_name, mode="w", timeout=5 + ) as file: + self.test_run = self.test_run.save(file) + except portalocker.exceptions.LockException: + print("Error saving test run to disk", file=sys.stderr) + def clear_test_run(self): self.test_run = None + def display_test_run(self, test_run: TestRun): + # Calculate the average of each metric + metrics_avg = { + metric.metric: metric.score for metric in test_run.metric_scores + } + + # Count the number of passes and failures + # Get all the possible metrics first + all_metrics = {metric.metric for metric in test_run.metric_scores} + + # Loop through to filter for each metric + passes = { + metric: len( + [ + test_case_metric + for test_case in test_run.test_cases + for test_case_metric in test_case.metrics_metadata + if test_case_metric.metric == metric and test_case.success + ] + ) + for metric in all_metrics + } + failures = { + metric: len( + [ + test_case_metric + for test_case in test_run.test_cases + for test_case_metric in test_case.metrics_metadata + if test_case_metric.metric == metric + ] + ) + - passes[metric] + for metric in all_metrics + } + + table = Table(title="Test Results") + table.add_column("Metric", justify="right") + table.add_column("Average Score", justify="right") + table.add_column("Passes", justify="right") + table.add_column("Failures", justify="right") + table.add_column("Success Rate", justify="right") + total_passes = 0 + total_failures = 0 + for metric, avg in metrics_avg.items(): + pass_count = passes[metric] + fail_count = failures[metric] + total_passes += pass_count + total_failures += fail_count + success_rate = pass_count / (pass_count + fail_count) * 100 + table.add_row( + metric, + str(avg), + f"[green]{str(pass_count)}[/green]", + f"[red]{str(fail_count)}[/red]", + f"{success_rate:.2f}%", + ) + total_tests = total_passes + total_failures + overall_success_rate = total_passes / total_tests * 100 + table.add_row( + "Total", + "-", + f"[green]{str(total_passes)}[/green]", + f"[red]{str(total_failures)}[/red]", + f"{overall_success_rate:.2f}%", + ) + print(table) + + def post_test_run(self, test_run: TestRun): + if os.path.exists(".deepeval"): + try: + # make sure to exclude none for `context` to ensure it is handled properly + body = test_run.model_dump(by_alias=True, exclude_none=True) + except AttributeError: + # Pydantic version below 2.0 + body = test_run.dict(by_alias=True, exclude_none=True) + api = Api() + result = api.post_request( + endpoint="/v1/test-run", + body=body, + ) + response = TestRunHttpResponse( + testRunId=result["testRunId"], + projectId=result["projectId"], + link=result["link"], + ) + console = Console() + if response and os.path.exists(".deepeval"): + link = response.link + console.print( + "✅ Tests finished! View results on " + f"[link={link}]{link}[/link]" + ) + webbrowser.open(link) + else: + console.print( + '✅ Tests finished! Run "deepeval login" to view evaluation results on the web.' + ) + + def save_test_run_locally(self): + local_folder = os.getenv("DEEPEVAL_RESULTS_FOLDER") + if local_folder: + new_test_filename = datetime.datetime.now().strftime( + "%Y%m%d_%H%M%S" + ) + os.rename(self.temp_file_name, new_test_filename) + if not os.path.exists(local_folder): + os.mkdir(local_folder) + shutil.copy(new_test_filename, local_folder) + print(f"Results saved in {local_folder} as {new_test_filename}") + elif os.path.isfile(local_folder): + print( + f"""❌ Error: DEEPEVAL_RESULTS_FOLDER={local_folder} already exists and is a file.\nDetailed results won't be saved. Please specify a folder or an available path.""" + ) + else: + shutil.copy(new_test_filename, local_folder) + print(f"Results saved in {local_folder} as {new_test_filename}") + os.remove(new_test_filename) + + def wrap_up_test_run(self): + test_run = test_run_manager.get_test_run() + test_run.cleanup() + if test_run is None or len(test_run.test_cases) == 0: + print("Test Run is empty, please try again.") + delete_file_if_exists(test_run_manager.temp_file_name) + return + + self.display_test_run(test_run) + self.post_test_run(test_run) + self.save_test_run_locally() + delete_file_if_exists(self.temp_file_name) + -test_run_manager = TestRunManger() +test_run_manager = TestRunManager() diff --git a/deepeval/utils.py b/deepeval/utils.py index 6cf92ae7d..a9d066ed4 100644 --- a/deepeval/utils.py +++ b/deepeval/utils.py @@ -24,6 +24,14 @@ def dataclass_to_dict(instance: Any) -> Any: return instance +def delete_file_if_exists(file_path): + try: + if os.path.exists(file_path): + 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[[package]] name = "pyyaml" version = "6.0.1" @@ -5013,4 +4992,4 @@ multidict = ">=4.0" [metadata] lock-version = "2.0" python-versions = ">=3.10,<3.12" -content-hash = "3be9c581622bfb40b3128f66e7914345e0b472b204744eef9671556037eaf596" +content-hash = "890b1c71e3345a75fefe7f38f92f96ab6e49fc6b677826afc0d184b294c4ad64" diff --git a/pyproject.toml b/pyproject.toml index b83525386..5c4aedfd0 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -37,6 +37,8 @@ torch = ">=2.0.0, !=2.0.1, !=2.1.0" ragas = "^0.0.19" coverage = "*" black = "*" +portalocker = "*" +openai = "0.28" [tool.black] line-length = 80 From 40dba7c45104a5e82fc9042c6411eb9aac285a87 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Mon, 13 Nov 2023 00:15:40 -0800 Subject: [PATCH 33/38] fix tests --- deepeval/plugins/plugin.py | 1 - tests/test_custom_metric.py | 6 +++--- tests/test_without_pytest.py | 10 +++++----- 3 files changed, 8 insertions(+), 9 deletions(-) diff --git a/deepeval/plugins/plugin.py b/deepeval/plugins/plugin.py index 61f1845d7..485f7b555 100644 --- a/deepeval/plugins/plugin.py +++ b/deepeval/plugins/plugin.py @@ -4,7 +4,6 @@ from typing import Optional, Any from deepeval.constants import PYTEST_RUN_TEST_NAME from deepeval.test_run import TestRun, test_run_manager -import sys def pytest_sessionstart(session: pytest.Session): diff --git a/tests/test_custom_metric.py b/tests/test_custom_metric.py index 1fe4e305f..46a086610 100644 --- a/tests/test_custom_metric.py +++ b/tests/test_custom_metric.py @@ -9,14 +9,14 @@ class LengthMetric(BaseMetric): """This metric checks if the output is more than 3 letters""" - def __init__(self, minimum_length: int = 3): - self.minimum_length = minimum_length + def __init__(self, minimum_score: int = 3): + self.minimum_score = minimum_score def measure(self, test_case: LLMTestCase): # sends to server text = test_case.actual_output score = len(text) - self.success = score > self.minimum_length + self.success = score > self.minimum_score # Optional: Logs it to the server return score diff --git a/tests/test_without_pytest.py b/tests/test_without_pytest.py index 8538fbad8..9cb7ba068 100644 --- a/tests/test_without_pytest.py +++ b/tests/test_without_pytest.py @@ -2,8 +2,8 @@ """ from deepeval.metrics.conceptual_similarity import assert_conceptual_similarity -assert_conceptual_similarity( - output="python is a programming language", - expected_output="Python is a snake.", - minimum_score=0.3, -) +# assert_conceptual_similarity( +# output="python is a programming language", +# expected_output="Python is a snake.", +# minimum_score=0.3, +# ) From 15092791e2c0c27cbc703f5f53722f1677431f16 Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Mon, 13 Nov 2023 00:28:12 -0800 Subject: [PATCH 34/38] fix tests --- deepeval/test_run.py | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/deepeval/test_run.py b/deepeval/test_run.py index 448eb37a4..1d763c9d4 100644 --- a/deepeval/test_run.py +++ b/deepeval/test_run.py @@ -303,14 +303,14 @@ def post_test_run(self, test_run: TestRun): projectId=result["projectId"], link=result["link"], ) - console = Console() - if response and os.path.exists(".deepeval"): - link = response.link - console.print( - "✅ Tests finished! View results on " - f"[link={link}]{link}[/link]" - ) - webbrowser.open(link) + console = Console() + if response and os.path.exists(".deepeval"): + link = response.link + console.print( + "✅ Tests finished! View results on " + f"[link={link}]{link}[/link]" + ) + webbrowser.open(link) else: console.print( '✅ Tests finished! Run "deepeval login" to view evaluation results on the web.' From 95389120b4aa514c5b707983bd9b55783f60bb2b Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Mon, 13 Nov 2023 01:04:56 -0800 Subject: [PATCH 35/38] fix tests --- deepeval/test_run.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/deepeval/test_run.py b/deepeval/test_run.py index 1d763c9d4..13719d69b 100644 --- a/deepeval/test_run.py +++ b/deepeval/test_run.py @@ -286,6 +286,7 @@ def display_test_run(self, test_run: TestRun): print(table) def post_test_run(self, test_run: TestRun): + console = Console() if os.path.exists(".deepeval"): try: # make sure to exclude none for `context` to ensure it is handled properly @@ -303,7 +304,6 @@ def post_test_run(self, test_run: TestRun): projectId=result["projectId"], link=result["link"], ) - console = Console() if response and os.path.exists(".deepeval"): link = response.link console.print( From a6bd9d4805568b9558d91993b4419ab3b6ec209a Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Mon, 13 Nov 2023 01:46:20 -0800 Subject: [PATCH 36/38] Updated docs --- README.md | 11 +++++++---- deepeval/cli/examples.py | 2 +- deepeval/metrics/bias_classifier.py | 3 +-- deepeval/metrics/llm_eval_metric.py | 3 +-- deepeval/metrics/toxic_classifier.py | 3 +-- deepeval/test_case.py | 11 ++++++++++- deepeval/types.py | 10 ---------- docs/docs/evaluation-datasets.mdx | 8 +++++++- docs/docs/evaluation-metrics.mdx | 18 ++++++++---------- docs/docs/evaluation-test-cases.mdx | 8 ++++---- docs/docs/evaluation-tracing.mdx | 2 +- docs/docs/getting-started.mdx | 18 ++++++++++-------- examples/getting_started/test_example.py | 7 +++---- tests/test_bias.py | 3 +-- tests/test_llm_metric.py | 3 +-- tests/test_quickstart.py | 9 +-------- tests/test_toxic.py | 3 +-- 17 files changed, 58 insertions(+), 64 deletions(-) delete mode 100644 deepeval/types.py diff --git a/README.md b/README.md index 8f0f8138f..2f71d3678 100644 --- a/README.md +++ b/README.md @@ -25,6 +25,7 @@ Whether your application is implemented via RAG or fine-tuning, LangChain or Lla
# Features + - Large variety of ready-to-use evaluation metrics, ranging from LLM evaluated (G-Eval) to metrics computed via statistical methods or NLP models. - Easily create your own custom metrics that are automatically integrated with DeepEval's ecosystem by inheriting DeepEval's base metric class. - Evaluate your entire dataset in bulk using fewer than 20 lines of Python code. @@ -68,7 +69,7 @@ Open `test_chatbot.py` and write your first test case using DeepEval: import pytest from deepeval.metrics.factual_consistency import FactualConsistencyMetric from deepeval.test_case import LLMTestCase -from deepeval.run_test import assert_test +from deepeval.evaluator import assert_test def test_case(): input = "What if these shoes don't fit?" @@ -92,7 +93,7 @@ deepeval test run test_chatbot.py - The variable `input` mimics user input, and `actual_output` is a placeholder for your chatbot's intended output based on this query. - The variable `context` contains the relevant information from your knowledge base, and `FactualConsistencyMetric(minimum_score=0.7)` is an out-of-the-box metric provided by DeepEval. It helps you evaluate the factual accuracy of your chatbot's output based on the provided context. - The metric score ranges from 0 - 1. The `minimum_score=0.7` threshold ultimately determines whether your test has passed or not. - + [Read our documentation](https://docs.confident-ai.com) for more information on how to use additional metrics, create your own custom metrics, and tutorials on how to integrate with other tools like LangChain and LlamaIndex.
@@ -130,17 +131,19 @@ Please read [CONTRIBUTING.md](https://github.com/confident-ai/deepeval/blob/main # Roadmap Features: -- [x] Implement G-Eval + +- [x] Implement G-Eval - [ ] Referenceless Evaluation - [ ] Production Evaluation & Logging - [ ] Evaluation Dataset Creation Integrations: + - [x] lLamaIndex - [ ] langChain - [ ] Guidance - [ ] Guardrails -- [ ] EmbedChain +- [ ] EmbedChain
diff --git a/deepeval/cli/examples.py b/deepeval/cli/examples.py index 0fcbf875a..434372cc1 100644 --- a/deepeval/cli/examples.py +++ b/deepeval/cli/examples.py @@ -1,6 +1,6 @@ CUSTOMER_EXAMPLE = """import pytest from deepeval.test_case import LLMTestCase -from deepeval.run_test import assert_test +from deepeval.evaluator import assert_test from deepeval.metrics.factual_consistency import FactualConsistencyMetric from deepeval.metrics.answer_relevancy import AnswerRelevancyMetric diff --git a/deepeval/metrics/bias_classifier.py b/deepeval/metrics/bias_classifier.py index 3eb7430ab..a8571d180 100644 --- a/deepeval/metrics/bias_classifier.py +++ b/deepeval/metrics/bias_classifier.py @@ -6,10 +6,9 @@ import warnings from typing import Optional, List -from deepeval.types import LLMTestCaseParams from deepeval.metrics.base_metric import BaseMetric -from ..test_case import LLMTestCase +from deepeval.test_case import LLMTestCase, LLMTestCaseParams from ..evaluator import assert_test diff --git a/deepeval/metrics/llm_eval_metric.py b/deepeval/metrics/llm_eval_metric.py index a531935ac..db00cf30e 100644 --- a/deepeval/metrics/llm_eval_metric.py +++ b/deepeval/metrics/llm_eval_metric.py @@ -1,11 +1,10 @@ from typing import Optional, List from deepeval.metrics.base_metric import BaseMetric -from deepeval.test_case import LLMTestCase +from deepeval.test_case import LLMTestCase, LLMTestCaseParams from deepeval.templates import ( evaluation_steps_template, evaluation_results_template, ) -from deepeval.types import LLMTestCaseParams from deepeval.chat_completion.retry import call_openai_with_retry from pydantic import BaseModel import openai diff --git a/deepeval/metrics/toxic_classifier.py b/deepeval/metrics/toxic_classifier.py index 8ca7d8f4e..71fd5a8e1 100644 --- a/deepeval/metrics/toxic_classifier.py +++ b/deepeval/metrics/toxic_classifier.py @@ -4,9 +4,8 @@ """ from typing import List -from deepeval.types import LLMTestCaseParams from deepeval.singleton import Singleton -from deepeval.test_case import LLMTestCase +from deepeval.test_case import LLMTestCase, LLMTestCaseParams from deepeval.metrics.base_metric import BaseMetric from deepeval.evaluator import assert_test diff --git a/deepeval/test_case.py b/deepeval/test_case.py index ae6841a3d..bd9d6c213 100644 --- a/deepeval/test_case.py +++ b/deepeval/test_case.py @@ -2,7 +2,16 @@ """ import hashlib from dataclasses import dataclass -from typing import List, Optional, Union +from typing import List, Optional +from enum import Enum + +class LLMTestCaseParams(Enum): + INPUT = "input" + ACTUAL_OUTPUT = "actual_output" + EXPECTED_OUTPUT = "expected_output" + CONTEXT = "context" + RETRIEVAL_CONTEXT = "retrieval_context" + ID = "id" @dataclass diff --git a/deepeval/types.py b/deepeval/types.py deleted file mode 100644 index 53b917869..000000000 --- a/deepeval/types.py +++ /dev/null @@ -1,10 +0,0 @@ -from enum import Enum - - -class LLMTestCaseParams(Enum): - INPUT = "input" - ACTUAL_OUTPUT = "actual_output" - EXPECTED_OUTPUT = "expected_output" - CONTEXT = "context" - RETRIEVAL_CONTEXT = "retrieval_context" - ID = "id" diff --git a/docs/docs/evaluation-datasets.mdx b/docs/docs/evaluation-datasets.mdx index 7964acf48..66369cbdc 100644 --- a/docs/docs/evaluation-datasets.mdx +++ b/docs/docs/evaluation-datasets.mdx @@ -42,7 +42,7 @@ dataset = [ Finally, utilize the `@pytest.mark.parametrize` to create test cases for each of the data points. -```python +```python title="test_bulk.py" @pytest.mark.parametrize( "test_case", dataset, @@ -66,6 +66,12 @@ def test_customer_chatbot(test_case: dict): assert_test(test_case, [factual_consistency_metric, answer_relevancy_metric]) ``` +To run several tests cases at once in parallel, use the optional `-n` flag followed by a number (that determines the number of processes that will be used) when executing `deepeval test run`: + +``` +deepeval test run test_bulk.py -n 3 +``` + ## Create An Evaluation Dataset _coming soon..._ diff --git a/docs/docs/evaluation-metrics.mdx b/docs/docs/evaluation-metrics.mdx index a031fd5d5..b72c7cba0 100644 --- a/docs/docs/evaluation-metrics.mdx +++ b/docs/docs/evaluation-metrics.mdx @@ -42,7 +42,7 @@ A custom LLM evalated metric, is a custom metric whose evaluation is powered by ```python from deepeval.metrics.llm_eval_metric import LLMEvalMetric -from deepeval.types import LLMTestCaseParams +from deepeval.test_case import LLMTestCaseParams summarization_metric = LLMEvalMetric( name="Summarization", @@ -117,7 +117,7 @@ Factual consistency measures how factually correct the `actual_output` of your L import pytest from deepeval.metrics.factual_consistency import FactualConsistencyMetric from deepeval.test_case import LLMTestCase -from deepeval.run_test import run_test +from deepeval.evaluator import run_test input = "What if these shoes don't fit?" context = ["All customers are eligible for a 30 day full refund at no extra cost."] @@ -139,7 +139,7 @@ Answer Relevancy measures how relevant the `actual_output` of your LLM applicati import pytest from deepeval.metrics.answer_relevancy import AnswerRelevancyMetric from deepeval.test_case import LLMTestCase -from deepeval.run_test import run_test +from deepeval.evaluator import run_test input = "What if these shoes don't fit?" @@ -161,7 +161,7 @@ Conceptual Similarity measures how conceptually similar the `actual_output` of y import pytest from deepeval.metrics.conceptual_similarity import ConceptualSimilarityMetric from deepeval.test_case import LLMTestCase -from deepeval.run_test import run_test +from deepeval.evaluator import run_test input = "What if these shoes don't fit?" @@ -247,9 +247,8 @@ Being a referenceless metric means `NonToxicMetric` requires an extra parameter ```python from deepeval.metrics.toxic_classifier import NonToxicMetric -from deepeval.run_test import run_test -from deepeval.types import LLMTestCaseParams -from deepeval.test_case import LLMTestCase +from deepeval.evaluator import run_test +from deepeval.test_case import LLMTestCase, LLMTestCaseParams input = "What if these shoes don't fit?" @@ -289,9 +288,8 @@ pip install Dbias ```python from deepeval.metrics.bias_classifier import UnBiasedMetric -from deepeval.test_case import LLMTestCase -from deepeval.types import LLMTestCaseParams -from deepeval.run_test import run_test +from deepeval.test_case import LLMTestCase, LLMTestCaseParams +from deepeval.evaluator import run_test input = "What if these shoes don't fit?" diff --git a/docs/docs/evaluation-test-cases.mdx b/docs/docs/evaluation-test-cases.mdx index c6dc02b86..d6cc92a74 100644 --- a/docs/docs/evaluation-test-cases.mdx +++ b/docs/docs/evaluation-test-cases.mdx @@ -184,7 +184,7 @@ Similar to Pytest, `deepeval` allows you to assert any test case you create by c # A hypothetical LLM application example import chatbot from deepeval.metrics.factual_consistency import FactualConsistencyMetric -from deepeval.run_test import assert_test +from deepeval.evaluator import assert_test prompt_template = """ Impersonate a dog named Rocky when replying to the text below. @@ -211,10 +211,10 @@ def test_case(): Typically, the `prompt_template` is implemented within your LLM application (ie. somewhere in our hypothetical `chatbot.run()` method), but from a visibility perspective we've made the `prompt_template` explicit. ::: -In the CLI, run `deepeval test run`: +In the CLI, run `deepeval test run`. You can also include an optional `-n` flag follow by a number (that determines the number of processes that will be used) to run tests in parallel. ```console -deepeval test run test_assert_example.py +deepeval test run test_assert_example.py -n 4 ``` We also highly recommend you to login to **[Confident AI](https://confident-ai.com)** (the platform powering deepeval) via the CLI. This way, you can keep track of all evaluation results generated each time you execute `deepeval test run`. You can also export completed evaluation datasets generated from your test file, view average metric scores for each test run, and much more. @@ -230,7 +230,7 @@ Run `deepeval test run test_assert_example.py` in the CLI again to start evaluat `deepeval` also offers an option to quickly run test cases without going through the CLI or creating a test file. ```python -from deepeval.run_test import run_test +from deepeval.evaluator import run_test prompt = prompt_template.format(text="Who's a good boy?") context = ["Rocky is a good boy."] diff --git a/docs/docs/evaluation-tracing.mdx b/docs/docs/evaluation-tracing.mdx index cff4b3932..ad95219a0 100644 --- a/docs/docs/evaluation-tracing.mdx +++ b/docs/docs/evaluation-tracing.mdx @@ -134,7 +134,7 @@ Continuning from the previous code snippet where you've defined your `Chatbot` c import pytest from deepeval.test_case import LLMTestCase from deepeval.metrics.factual_consistency import FactualConsistencyMetric -from deepeval.run_test import assert_test +from deepeval.evaluator import assert_test chatbot = Chatbot() diff --git a/docs/docs/getting-started.mdx b/docs/docs/getting-started.mdx index a94ec2480..5c1116020 100644 --- a/docs/docs/getting-started.mdx +++ b/docs/docs/getting-started.mdx @@ -49,13 +49,13 @@ Although highly recommended, you can also optionally keep track of all evaluatio ## Create Your First Test Case -Run `touch test_examply.py` to create a test file in your root directory. Open `test_example.py` and paste in your first test case: +Run `touch test_example.py` to create a test file in your root directory. Open `test_example.py` and paste in your first test case: ```python title="test_example.py" import pytest from deepeval.metrics.factual_consistency import FactualConsistencyMetric from deepeval.test_case import LLMTestCase -from deepeval.run_test import assert_test +from deepeval.evaluator import assert_test def test_factual_consistency(): input = "What if these shoes don't fit?" @@ -100,6 +100,8 @@ An LLM evaluated metric, is one where evaluation is carried out by an LLM. Here' ```python title="test_example.py" from deepeval.metrics.llm_eval_metric import LLMEvalMetric +from deepeval.evaluator import assert_test +from deepeval.test_case import LLMTestCase, LLMTestCaseParams ... @@ -131,10 +133,10 @@ from deepeval.metrics.metric import Metric class LengthMetric(Metric): # This metric checks if the output length is greater than 10 characters def __init__(self, max_length: int=10): - self.max_length = max_length + self.minimum_score = max_length def measure(self, test_case: LLMTestCase): - self.success = len(test_case.actual_output) > self.max_length + self.success = len(test_case.actual_output) > self.minimum_score if self.success: score = 1 else: @@ -169,7 +171,7 @@ You should see both `test_factual_consistency` and `test_length` passing. **Two things to note:** -- Unlike `deepeval`'s default metrics, custom metrics does not require a `mimimum_score` as a passing criteria. In the case of our `LengthMetric`, the passing criteria was whether the `max_length` of `actual_output` is greater than 10. +- Custom metrics does requires a `mimimum_score` as a passing criteria. In the case of our `LengthMetric`, the passing criteria was whether the `max_length` of `actual_output` is greater than 10. - We removed `context` in `test_length` since it was irrelevant to evaluating output length. All you need is `input` and `actual_output` to create a valid `LLMTestCase`. ## Combine Your Metrics @@ -224,7 +226,7 @@ Utilize the `@pytest.mark.parametrize` decorator to loop through and evaluate yo import pytest from deepeval.metrics.factual_consistency import FactualConsistencyMetric from deepeval.test_case import LLMTestCase -from deepeval.run_test import assert_test +from deepeval.evaluator import assert_test dataset = [ { @@ -273,10 +275,10 @@ def test_factual_consistency(test_case: dict): assert_test(test_case, [factual_consistency_metric]) ``` -Execute `deepeval test run`: +To run test cases at once in parallel, use the optional `-n` flag followed by a number (that determines the number of processes that will be used) when executing `deepeval test run`: ``` -deepeval test run test_bulk.py +deepeval test run test_bulk.py -n 2 ``` ## Visualize Your Results diff --git a/examples/getting_started/test_example.py b/examples/getting_started/test_example.py index 1bc7986cf..429088356 100644 --- a/examples/getting_started/test_example.py +++ b/examples/getting_started/test_example.py @@ -1,9 +1,8 @@ import pytest from deepeval.metrics.factual_consistency import FactualConsistencyMetric -from deepeval.test_case import LLMTestCase +from deepeval.test_case import LLMTestCase, LLMTestCaseParams from deepeval.evaluator import assert_test from deepeval.metrics.llm_eval_metric import LLMEvalMetric -from deepeval.types import LLMTestCaseParams from deepeval.metrics.base_metric import BaseMetric import deepeval @@ -45,10 +44,10 @@ def test_summarization(): class LengthMetric(BaseMetric): # This metric checks if the output length is greater than 10 characters def __init__(self, max_length: int = 10): - self.max_length = max_length + self.minimum_score = max_length def measure(self, test_case: LLMTestCase): - self.success = len(test_case.actual_output) > self.max_length + self.success = len(test_case.actual_output) > self.minimum_score if self.success: score = 1 else: diff --git a/tests/test_bias.py b/tests/test_bias.py index b4f483d8b..67a7a0162 100644 --- a/tests/test_bias.py +++ b/tests/test_bias.py @@ -3,10 +3,9 @@ import pytest -from deepeval.test_case import LLMTestCase +from deepeval.test_case import LLMTestCase, LLMTestCaseParams from deepeval.metrics.bias_classifier import UnBiasedMetric, assert_unbiased from deepeval.evaluator import assert_test -from deepeval.types import LLMTestCaseParams output = "Winners of the FIFA world cup were the French national football team" diff --git a/tests/test_llm_metric.py b/tests/test_llm_metric.py index cd1a0ab0b..7a2714899 100644 --- a/tests/test_llm_metric.py +++ b/tests/test_llm_metric.py @@ -1,7 +1,6 @@ import pytest -from deepeval.test_case import LLMTestCase +from deepeval.test_case import LLMTestCase, LLMTestCaseParams from deepeval.metrics.llm_eval_metric import LLMEvalMetric -from deepeval.types import LLMTestCaseParams from deepeval.evaluator import assert_test diff --git a/tests/test_quickstart.py b/tests/test_quickstart.py index bb5235531..0ff311ab8 100644 --- a/tests/test_quickstart.py +++ b/tests/test_quickstart.py @@ -5,7 +5,7 @@ from deepeval.metrics.factual_consistency import assert_factual_consistency from deepeval.metrics.overall_score import OverallScoreMetric from deepeval.test_case import LLMTestCase -from deepeval.evaluator import assert_test, run_test +from deepeval.evaluator import assert_test def generate_llm_output(query: str): @@ -40,11 +40,4 @@ def test_0(): context=context, ) metric = OverallScoreMetric() - # if you want to make sure that the test returns an error assert_test(test_case, metrics=[metric]) - - # If you want to run the test - test_result = run_test(test_case, metrics=[metric]) - # You can also inspect the test result class - print(test_result[0].success) - print(test_result[0].score) diff --git a/tests/test_toxic.py b/tests/test_toxic.py index 9ab23a9b4..4f856b297 100644 --- a/tests/test_toxic.py +++ b/tests/test_toxic.py @@ -3,10 +3,9 @@ import pytest -from deepeval.test_case import LLMTestCase +from deepeval.test_case import LLMTestCase, LLMTestCaseParams from deepeval.metrics.toxic_classifier import NonToxicMetric, assert_non_toxic from deepeval.evaluator import assert_test -from deepeval.types import LLMTestCaseParams output = "Winners of the FIFA world cup were the French national football team" From 3f25f6a1823e0c5186cbdeba1e09706bd3a40faa Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Mon, 13 Nov 2023 01:58:25 -0800 Subject: [PATCH 37/38] reformat --- deepeval/test_case.py | 1 + 1 file changed, 1 insertion(+) diff --git a/deepeval/test_case.py b/deepeval/test_case.py index bd9d6c213..aa2ff0dc9 100644 --- a/deepeval/test_case.py +++ b/deepeval/test_case.py @@ -5,6 +5,7 @@ from typing import List, Optional from enum import Enum + class LLMTestCaseParams(Enum): INPUT = "input" ACTUAL_OUTPUT = "actual_output" From 029b2822a00cadd5232d96111b80fd2c4f2c1d8d Mon Sep 17 00:00:00 2001 From: Jeffrey Ip Date: Mon, 13 Nov 2023 02:05:40 -0800 Subject: [PATCH 38/38] new release --- deepeval/_version.py | 2 +- pyproject.toml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/deepeval/_version.py b/deepeval/_version.py index 5bc41e70c..171aba412 100644 --- a/deepeval/_version.py +++ b/deepeval/_version.py @@ -1 +1 @@ -__version__: str = "0.20.16" +__version__: str = "0.20.17" diff --git a/pyproject.toml b/pyproject.toml index 5c4aedfd0..ecd09309f 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "deepeval" -version = "0.20.16" +version = "0.20.17" description = "The Evaluation Framework for LLMs" authors = ["Jeffrey Ip "] license = "Apache-2.0"