feat(instructor): introduce new client with support for different providers and sync/async operations #546
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👍 Looks good to me!
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1. instructor/client.py:30:
- Assessed confidence :
50% - Comment:
The 'ANYSCALE' and 'TOGETHER' providers are defined in the Provider Enum but are not used anywhere in the code. If these are not intended to be used, consider removing them to avoid confusion. - Reasoning:
The new client.py file introduces a new class 'Instructor' and 'AsyncInstructor' which seem to be wrappers around the OpenAI and Anthropic clients. The classes provide methods for creating, creating partial, creating iterable, and creating with response. The methods seem to be handling the kwargs properly and the assertions for the provider not supporting certain features are in place. The 'from_openai' and 'from_anthropic' functions are overloaded to handle both synchronous and asynchronous clients. The test cases in test_new_client.py seem to be covering all the new methods introduced in the Instructor classes. However, I noticed that the 'ANYSCALE' and 'TOGETHER' providers are defined in the Provider Enum but are not used anywhere in the code. This could potentially be a future plan or an oversight.
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Deploying instructor with
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| Latest commit: |
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| Status: | ✅ Deploy successful! |
| Preview URL: | https://931e05b5.instructor.pages.dev |
| Branch Preview URL: | https://v1-attempt2.instructor.pages.dev |
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1. instructor/client.py:15:
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TheInstructorandAsyncInstructorclasses have a lot of repeated code. The methodscreate,create_partial,create_iterable, andcreate_with_responseare almost identical in both classes. This violates the DRY (Don't Repeat Yourself) principle. We should consider refactoring this to avoid code duplication. - Reasoning:
TheInstructorandAsyncInstructorclasses have a lot of repeated code. The methodscreate,create_partial,create_iterable, andcreate_with_responseare almost identical in both classes. This violates the DRY (Don't Repeat Yourself) principle. We should consider refactoring this to avoid code duplication.
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👍 Looks good to me!
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1. instructor/client.py:68:
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The removal of *args from the method signatures could potentially break existing code that uses positional arguments. Please ensure that these methods are not called with positional arguments anywhere in the codebase. - Reasoning:
The PR removed the *args parameter from several methods in the Instructor and AsyncInstructor classes. This could potentially break existing code that uses positional arguments when calling these methods. However, it's not clear from the PR description why this change was made. I'll need to check the rest of the codebase to see if these methods are called with positional arguments anywhere.
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❌ Changes requested.
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| class Instructor: | ||
| client: openai.OpenAI | anthropic.Anthropic | None |
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The client parameter is now optional and can be None. Please ensure that all usages of client in the Instructor and AsyncInstructor classes are properly checked to avoid NoneType errors.
| **kwargs, | ||
| ) -> Instructor | AsyncInstructor: | ||
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| is_async = inspect.isawaitable(completion) |
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The inspect.isawaitable function checks if an object is an instance of an awaitable class, not if a function returns an awaitable object. This could lead to incorrect behavior if a synchronous function that returns an awaitable object is passed as the completion parameter. Consider using inspect.iscoroutinefunction instead.
| @@ -59,6 +71,13 @@ def patch( | |||
| ) -> InstructorChatCompletionCreate: ... | |||
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| @overload | |||
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The overload of the patch function that takes an Awaitable as the create parameter returns InstructorChatCompletionCreate, which is a protocol for synchronous functions. This could lead to type errors if an asynchronous function is passed as the create parameter. Consider returning AsyncInstructorChatCompletionCreate instead.
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1. instructor/client.py:163:
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Theproviderattribute is not defined in theAsyncInstructorclass and is not passed as an argument to its constructor. This could lead to an AttributeError when thecreate_partialandcreate_iterablemethods are called on an instance ofAsyncInstructor. Consider adding aproviderattribute to theAsyncInstructorclass and passing it as an argument to its constructor. - Reasoning:
Thecreate_partialandcreate_iterablemethods in bothInstructorandAsyncInstructorclasses have assertions that check if the provider is notAnthropic. However, theproviderattribute is not defined in theAsyncInstructorclass and is not passed as an argument to its constructor. This could lead to an AttributeError when these methods are called on an instance ofAsyncInstructor.
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| def from_anthropic( | ||
| client: anthropic.Anthropic | anthropic.AsyncAnthropic, | ||
| mode: instructor.Mode = instructor.Mode.ANTHROPIC_JSON, |
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The from_anthropic function has two overloads but the actual function implementation does not match the overloads. The overloads suggest that the mode parameter can have different default values depending on the type of the client parameter. However, in the actual function implementation, the mode parameter has a single default value regardless of the client type. Consider updating the function implementation to match the overloads.
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👍 Looks good to me!
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1. instructor/client.py:91:
- Assessed confidence :
100% - Grade:
0% - Comment:
The PR introduces significant changes to the instructor module, including new classes and methods. However, the PR description does not mention any updates to the documentation or tests to reflect these changes. Please ensure that the documentation and tests are updated accordingly. - Reasoning:
The PR introduces new classes and methods in the instructor module, removes the *args parameter from several methods, includes a new test file for validation, introduces a new protocol, and overloads a function to support Awaitable. The changes seem to be well implemented and there are no clear violations of best practices, logical bugs, performance bugs, or security bugs. However, the PR description does not mention any updates to the documentation or tests to reflect these changes. I will comment on this.
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👍 Looks good to me!
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1. README.md:39:
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The changes in the README.md file are correct and consistent with the changes made in the code. The examples provided are clear and easy to understand. - Reasoning:
The README.md file has been updated to reflect the changes in the code. The examples provided in the README.md file are consistent with the changes made in the code. The examples are clear and easy to understand. The changes made in the README.md file are correct and do not require any modifications.
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…e new client with support for different providers and sync/async operations);
…547) Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
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@ellipsis_dev can you update everything in /docs to use |
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I was in the process of checking all the .md files in the /docs directory and its subdirectories for Responding to this comment by @jxnl. For more information about Ellipsis, check the documentation. |
…ew client with support for different providers and sync/async operations);
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👍 Looks good to me!
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1. examples/avail/run_mixtral.py:71:
- Assessed confidence :
80% - Comment:
This function used to return anIterable[AvailabilityResponse]. The change to return an iterable might cause issues if the function's return value is expected to be an iterable ofAvailabilityResponseobjects elsewhere in the code. Consider reverting this change.
def parse_availability(text: str) -> Iterable[AvailabilityResponse]:
- Reasoning:
The functionparse_availabilityinrun_mixtral.pyhas been changed to return an iterable instead of anIterable[AvailabilityResponse]. This change might cause issues if the function's return value is expected to be an iterable ofAvailabilityResponseobjects elsewhere in the code. I'll suggest reverting this change.
2. examples/batch-classification/run_langsmith.py:61:
- Assessed confidence :
80% - Comment:
This function used to return aQuestionClassification. The change to return aNonetype might cause issues if the function's return value is expected to be aQuestionClassificationobject elsewhere in the code. Consider reverting this change.
async def classify(data: str) -> QuestionClassification:
- Reasoning:
The functionclassifyinrun_langsmith.pyhas been changed to return aNonetype instead of aQuestionClassification. This change might cause issues if the function's return value is expected to be aQuestionClassificationobject elsewhere in the code. I'll suggest reverting this change.
3. examples/vision/run_table.py:59:
- Assessed confidence :
80% - Comment:
This function used to return anIterable[Table]. The change to return an iterable might cause issues if the function's return value is expected to be an iterable ofTableobjects elsewhere in the code. Consider reverting this change.
def extract_table(url: str) -> Iterable[Table]:
- Reasoning:
The functionextract_tableinrun_table.pyhas been changed to return an iterable instead of anIterable[Table]. This change might cause issues if the function's return value is expected to be an iterable ofTableobjects elsewhere in the code. I'll suggest reverting this change.
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👍 Looks good to me!
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❌ Changes requested.
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1. instructor/dsl/validators.py:6:
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0% - Comment:
Good job updating the import statement for the Instructor class to import from the correct location. - Reasoning:
The import statement for the Instructor class has been updated to import from the correct location. This is a good change as it fixes a potential ImportError.
2. instructor/client.py:24:
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0% - Comment:
Good job updating the import statement for the Partial class to import from the correct location. - Reasoning:
The import statement for the Partial class has been updated to import from the correct location. This is a good change as it fixes a potential ImportError.
3. instructor/client.py:5:
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0% - Comment:
Good job updating the import statement for the Provider enum and get_provider function to import from the correct location. - Reasoning:
The import statement for the Provider enum and get_provider function has been updated to import from the correct location. This is a good change as it fixes a potential ImportError.
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| mode: instructor.Mode = instructor.Mode.ANTHROPIC_JSON, | ||
| **kwargs, | ||
| ) -> Instructor | AsyncInstructor: | ||
| assert mode in { |
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The assertion error message is not formatted correctly. The variables instructor.Mode.ANTHROPIC_JSON and instructor.Mode.ANTHROPIC_TOOLS are not being interpolated into the string. Consider using an f-string to format the error message correctly.
| assert mode in { | |
| assert mode in {instructor.Mode.ANTHROPIC_JSON, instructor.Mode.ANTHROPIC_TOOLS}, f"Mode must be one of {{instructor.Mode.ANTHROPIC_JSON}}, {{instructor.Mode.ANTHROPIC_TOOLS}}" |
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| def test_client_chat_completions_create_with_response(): | ||
| client = instructor.from_openai(openai.OpenAI(), model="gpt-3.5-turbo") | ||
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| user, completion = client.chat.completions.create_with_completion( |
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The function name in the test case does not match the function being called. Consider renaming the test case to 'test_client_chat_completions_create_with_completion' to match the function being called.
| user, completion = client.chat.completions.create_with_completion( | |
| def test_client_chat_completions_create_with_completion(): |
| client = openai.AsyncOpenAI() | ||
| instructor_client = instructor.from_openai(client, model="gpt-3.5-turbo") | ||
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| user, response = await instructor_client.chat.completions.create_with_completion( |
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The function name in the test case does not match the function being called. Consider renaming the test case to 'test_async_client_chat_completions_create_with_completion' to match the function being called.
| user, response = await instructor_client.chat.completions.create_with_completion( | |
| async def test_async_client_chat_completions_create_with_completion(): |
| model="claude-3-haiku-20240307", | ||
| ) | ||
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| user, response = client.messages.create_with_completion( |
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The function name in the test case does not match the function being called. Consider renaming the test case to 'test_client_from_anthropic_with_completion' to match the function being called.
| user, response = client.messages.create_with_completion( | |
| def test_client_from_anthropic_with_completion(): |
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👍 Looks good to me!
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1. /tests/llm/test_openai/test_validators.py:25:
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50% - Comment:
The changes in this test file seem to reflect the updates to the client correctly. The client is now created using thefrom_openaifunction, which is expected to handle different providers and modes. Thellm_validatorfunction now takes the newclientas a parameter instead of theopenai_client. This seems to be a logical change given the updates to the client. However, I would need to check the implementation of these functions to confirm that they are correctly handling the new client. - Reasoning:
The PR introduces a new client with support for different providers and sync/async operations. The changes in the test file seem to reflect these changes correctly. The client is now created using thefrom_openaifunction, which is expected to handle different providers and modes. Thellm_validatorfunction now takes the newclientas a parameter instead of theopenai_client. This seems to be a logical change given the updates to the client. However, I would need to check the implementation of these functions to confirm that they are correctly handling the new client.
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👍 Looks good to me!
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1. instructor/dsl/validators.py:32:
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50% - Comment:
Theclientparameter type has been changed fromOpenAItoInstructor. Please ensure that theInstructorclass has all the necessary methods and attributes that were previously available in theOpenAIclass. - Reasoning:
Thellm_validatorfunction has been updated to use theInstructorclass instead ofOpenAI. This is a significant change as it means the function will now be using the newInstructorclient which supports different providers and sync/async operations. This change seems to be in line with the PR's intent of enhancing theinstructormodule with support for different providers and sync/async operations. However, I need to check if theInstructorclass has all the necessary methods and attributes that were previously available in theOpenAIclass.
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1. instructor/client.py:291:
- Assessed confidence :
50% - Comment:
Please ensure that the newmdfile is added tomkdocs.ymland that all assertions have well-formatted error messages. - Reasoning:
The PR introduces a new client with support for different providers and sync/async operations. It also updates theinstructormodule, introduces new protocols, and overloads functions to supportAwaitable. TheProviderenum andInstructorclasses are updated to handle different providers. A new test file is added for validation. The documentation is updated with examples of using the new classes with different providers. Theclientparameter type in thellm_validatorfunction is changed fromOpenAItoInstructor. The PR seems to follow best practices and doesn't appear to introduce any new bugs. However, I'll need to check if the newmdfile is added tomkdocs.ymland if the assertions have well-formatted error messages.
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❌ Changes requested.
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👍 Looks good to me!
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1. pyproject.toml:57:
- Assessed confidence :
50% - Comment:
New dependenciespydantic_extra_types,litellm, andanthropichave been added. Please ensure that these are being used in the code and are necessary. Also, check if these dependencies have any known security vulnerabilities. - Reasoning:
The PR introduces new dependencies in the pyproject.toml file. It's important to ensure that these new dependencies are actually used in the code and are necessary. Also, it's crucial to check if these new dependencies have any known security vulnerabilities.
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👍 Looks good to me!
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1. /tests/llm/test_openai/util.py:6:
- Assessed confidence :
80% - Comment:
It seems likeinstructor.Mode.MD_JSONhas been removed from themodeslist. This mode might still be necessary for testing theinstructormodule's functionality. Consider adding it back unless there's a specific reason for its removal.
modes = [
instructor.Mode.TOOLS,
instructor.Mode.MD_JSON,
]
- Reasoning:
The PR description mentions that theinstructormodule has been enhanced with support for different providers and sync/async operations. However, in the diff, I see that theinstructor.Mode.MD_JSONhas been removed from themodeslist in thetests/llm/test_openai/util.pyfile. This could potentially lead to incomplete testing of theinstructormodule's functionality. I need to suggest adding it back.
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1. poetry.lock:1397:
- Assessed confidence :
50% - Comment:
This PR introduces a new dependency 'litellm'. Please ensure that this library is necessary and well-maintained. Also, check if the version used is the latest stable version. - Reasoning:
The PR introduces a new dependency 'litellm'. I need to check if this library is necessary and if it's a well-maintained and trusted library. Also, I need to check if the version used is the latest stable version.
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1. .github/workflows/test.yml:39:
- Assessed confidence :
50% - Comment:
The 'docs' are excluded from the tests and coverage report. If there are any tests in the 'docs' directory, they will be skipped. Please confirm if this is the intended behavior. - Reasoning:
The changes in the test.yml file are excluding the 'docs' from the tests and coverage report. This might be intentional if the 'docs' do not contain any testable code. However, it's worth noting that if there are any tests in the 'docs' directory, they will be skipped. The changes in the test_hub.py file are adding 'contact' to the list of excluded sources. This seems fine if 'contact' is indeed a source that is not supported in testing.
2. tests/llm/test_openai/docs/test_hub.py:13:
- Assessed confidence :
50% - Comment:
The 'contact' source is added to the excluded sources. Any tests related to the 'contact' source will be skipped. Please confirm if this is the intended behavior. - Reasoning:
The 'contact' source is added to the list of excluded sources in the test_hub.py file. This seems fine if 'contact' is indeed a source that is not supported in testing. However, it's worth noting that any tests related to the 'contact' source will be skipped.
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❌ Changes requested.
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| @@ -36,15 +36,15 @@ jobs: | |||
| run: poetry install --with dev,anthropic | |||
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| - name: Run tests | |||
| run: poetry run pytest tests/ -k "not openai and not anthropic and not evals" | |||
| run: poetry run pytest tests/ -k "not openai and not anthropic and not evals and not docs" | |||
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The test exclusion pattern in the 'Generate coverage report' step should also be updated to exclude 'docs' for consistency with the 'Run tests' step. Please ensure this change is made to maintain consistency in test results and coverage reports.
Summary:
This PR enhances the
instructormodule, introduces new protocols and function overloading, updates classes and functions, adds a new test file, updates the documentation, adds a new blog post, removesinstructor.Mode.MD_JSONfrommodeslist, adds new dependencies topoetry.lock, and updates test configurations.Key points:
instructormodule with support for different providers and sync/async operations.instructor/patch.py.Providerenum inutils.pyandInstructorandAsyncInstructorclasses inclient.py.tests/test_new_client.py.docs/blog/posts/version-1.md.clientparameter type inllm_validatorfunction ininstructor/dsl/validators.py.instructor.Mode.MD_JSONfrommodeslist intests/llm/test_openai/util.py.poetry.lock..github/workflows/test.ymlto exclude 'docs' from the test run.tests/llm/test_openai/docs/test_hub.pyto include 'contact' in the list of excluded sources for testing.Generated with ❤️ by ellipsis.dev