Migrate to UV

.github/workflows/pyright.yml

@@ -21,29 +21,13 @@ jobs:
     steps:
       - name: Checkout code
         uses: actions/checkout@v3
-
-      - name: Set up Python
-        uses: actions/setup-python@v4
-        with:
-          python-version: ${{ matrix.python-version }}
-
-      - name: Cache Poetry virtualenv
-        uses: actions/cache@v2
-        with:
-          path: ~/.cache/pypoetry/virtualenvs
-          key: ${{ runner.os }}-poetry-${{ hashFiles('**/poetry.lock') }}
-          restore-keys: |
-            ${{ runner.os }}-poetry-
-
-      - name: Install Poetry
-        uses: snok/install-poetry@v1.3.1
-
-      - name: Install dependencies
-        run: poetry install --with dev,anthropic
-
-      - name: Add poetry to PATH
-        run: echo "$(poetry env info --path)/bin" >> $GITHUB_PATH
-
-      - uses: jakebailey/pyright-action@v2
+      - name: Install uv
+        uses: astral-sh/setup-uv@v4
         with:
-          version: 1.1.373
+          enable-cache: true
+      - name: Set up Python
+        run: uv python install ${{ matrix.python-version }}
+      - name: Install the project
+        run: uv sync --all-extras
+      - name: Run pyright
+        run: uv run pyright

.github/workflows/python-publish.yml

@@ -21,21 +21,16 @@ jobs:
 
     steps:
       - uses: actions/checkout@v2
-
-      - name: Set up Python 3.10
-        uses: actions/setup-python@v4
+      - name: Install uv
+        uses: astral-sh/setup-uv@v4
         with:
-          python-version: '3.10' 
-
-      - name: Install Poetry
-        uses: snok/install-poetry@v1.3.1
-        env:
-          ACTIONS_ALLOW_UNSECURE_COMMANDS: 'true'
-
-      - name: Get release version
-        run: echo "RELEASE_VERSION=$(poetry version | awk '{print $2}')" >> $GITHUB_ENV
+          enable-cache: true
+      - name: Set up Python
+        run: uv python install 3.10
+      - name: Install the project
+        run: uv sync --all-extras
 
       - name: Build and publish Python package
-        run: poetry publish --build
+        run: uv publish
         env:
-          POETRY_PYPI_TOKEN_PYPI: ${{ secrets.PYPI_TOKEN }}
+          UV_PUBLISH_TOKEN: ${{ secrets.PYPI_TOKEN }}

.github/workflows/ruff.yml

@@ -20,16 +20,14 @@ jobs:
     steps:
       - name: Checkout code
         uses: actions/checkout@v3
-      - name: Environment setup
-        uses: actions/setup-python@v4
+      - name: Install uv
+        uses: astral-sh/setup-uv@v4
         with:
-          python-version: 3.9
-          cache: "pip"
-      - name: Install dev dependencies
-        run: |
-          python3 -m pip install --upgrade pip setuptools wheel
-          python3 -m pip install -r requirements.txt
-          python3 -m pip install -r requirements-doc.txt
+          enable-cache: true
+      - name: Set up Python
+        run: uv python install 3.9
+      - name: Install the project
+        run: uv sync --all-extras
       - name: Run Continuous Integration Action
         uses: astral-sh/ruff-action@v1
       - name: Upload Artifacts

.github/workflows/test.yml

@@ -15,45 +15,34 @@ jobs:
 
     steps:
       - uses: actions/checkout@v2
-
-      - name: Set up Python
-        uses: actions/setup-python@v4
+      - name: Install uv
+        uses: astral-sh/setup-uv@v4
         with:
-          python-version: ${{ matrix.python-version }}
-
-      - name: Cache Poetry virtualenv
-        uses: actions/cache@v2
-        with:
-          path: ~/.cache/pypoetry/virtualenvs
-          key: ${{ runner.os }}-poetry-${{ hashFiles('**/poetry.lock') }}
-          restore-keys: |
-            ${{ runner.os }}-poetry-
-
-      - name: Install Poetry
-        uses: snok/install-poetry@v1.3.1
-
-      - name: Install dependencies
-        run: poetry install --with dev,anthropic
-
+          enable-cache: true
+      - name: Set up Python
+        run: uv python install ${{ matrix.python-version }}
+      - name: Install the project
+        run: uv sync --all-extras
       - name: Run tests
         if: matrix.python-version != '3.11'
-        run: poetry run pytest tests/ -k 'not llm and not openai and not gemini and not anthropic and not cohere and not vertexai' && poetry run pytest tests/llm/test_cohere
+        run: uv run pytest tests/ -k 'not llm and not openai and not gemini and not anthropic and not cohere and not vertexai'
         env:
           OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
           ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
           COHERE_API_KEY: ${{ secrets.COHERE_API_KEY }}
 
       - name: Run Gemini Tests
-        run: poetry run pytest tests/llm/test_gemini
+        if: matrix.python-version == '3.11'
+        run: uv run pytest tests/llm/test_gemini
         env:
           GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }}
 
       - name: Generate coverage report
         if: matrix.python-version == '3.11'
         run: |
-          poetry run coverage run -m pytest tests/ -k "not docs and not anthropic and not gemini and not cohere and not vertexai and not fireworks"
-          poetry run coverage report
-          poetry run coverage html
+          uv run coverage run -m pytest tests/ -k "not docs and not anthropic and not gemini and not cohere and not vertexai and not fireworks"
+          uv run coverage report
+          uv run coverage html
         env:
           OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
           ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}

.github/workflows/test_docs.yml

@@ -28,18 +28,10 @@ jobs:
         with:
           python-version: ${{ matrix.python-version }}
           cache: "poetry"
-
-      - name: Cache Poetry virtualenv
-        uses: actions/cache@v2
-        with:
-          path: ~/.cache/pypoetry/virtualenvs
-          key: ${{ runner.os }}-poetry-${{ hashFiles('**/poetry.lock') }}
-          restore-keys: |
-            ${{ runner.os }}-poetry-
-
-      - name: Install dependencies
-        run: poetry install --with dev,docs,test-docs,anthropic,google-generativeai
-
+      - name: Install uv
+        uses: astral-sh/setup-uv@v4
+      - name: Install the project
+        run: uv sync --all-extras
       - name: Run tests
         run: poetry run pytest tests/llm/test_openai/docs
         env:

README.md

@@ -1,6 +1,6 @@
 # Instructor, The Most Popular Library for Simple Structured Outputs
 
-Instructor is the most popular Python library for working with structured outputs from large language models (LLMs), boasting over 600,000 monthly downloads. Built on top of Pydantic, it provides a simple, transparent, and user-friendly API to manage validation, retries, and streaming responses. Get ready to supercharge your LLM workflows with the community's top choice!
+Instructor is the most popular Python library for working with structured outputs from large language models (LLMs), boasting over 1 million monthly downloads. Built on top of Pydantic, it provides a simple, transparent, and user-friendly API to manage validation, retries, and streaming responses. Get ready to supercharge your LLM workflows with the community's top choice!
 
 [![Twitter Follow](https://img.shields.io/twitter/follow/jxnlco?style=social)](https://twitter.com/jxnlco)
 [![Discord](https://img.shields.io/discord/1192334452110659664?label=discord)](https://discord.gg/bD9YE9JArw)
@@ -131,9 +131,10 @@ user_info = client.chat.completions.create(
 
 print(f"Name: {user_info.name}, Age: {user_info.age}")
 #> Name: John, Age: 20
-``` 
+```
 
 This example demonstrates:
+
 1. A pre-execution hook that logs all kwargs passed to the function.
 2. An exception hook that logs any exceptions that occur during execution.
 
@@ -513,6 +514,14 @@ We invite you to contribute to evals in `pytest` as a way to monitor the quality
 
 If you want to help, checkout some of the issues marked as `good-first-issue` or `help-wanted` found [here](https://github.com/jxnl/instructor/labels/good%20first%20issue). They could be anything from code improvements, a guest blog post, or a new cookbook.
 
+Here's a quick list of commands that you can run to get started. We're using `uv` to manage our dependencies so make sure you have that installed.
+
+1. `uv sync --all-extras --group <dependency groups you'd like to install>`: This should install all the dependencies for the project using `uv`, make sure to install the specific dependencies that you'd like to install
+
+2. `uv run pytest` : This runs the tests in `pytest`. If you're pushing up a new PR, make sure that you've written some tests and that they're passing locally for you
+
+We use `ruff` and `pyright` for linting and type checking so make sure those are passing when you push up a PR. You can check pyright by running `uv run pyright` and ruff with `uv run ruff check` locally.
+
 ## CLI
 
 We also provide some added CLI functionality for easy convenience:

docs/concepts/prompt_caching.md

@@ -17,23 +17,16 @@ This optimization is especially useful for applications making multiple API call
 
 Prompt Caching is enabled for the following models:
 
-* gpt-4o
-* gpt-4o-mini
-* o1-preview
-* o1-mini
+- gpt-4o
+- gpt-4o-mini
+- o1-preview
+- o1-mini
 
 Caching is based on prefix matching, so if you're using a system prompt that contains a common set of instructions, you're likely to see a cache hit as long as you move all variable parts of the prompt to the end of the message when possible.
 
-
 ## Prompt Caching in Anthropic
 
-The `anthropic.beta.prompt_caching.messages.create` method enables you to:
-
-1. Cache specific prompt portions
-2. Reuse cached content in subsequent calls
-3. Reduce processed data per request
-
-By implementing prompt caching, you can potentially enhance efficiency and reduce costs, especially when dealing with large, shared contexts across multiple API interactions.
+Prompt Caching is now generally avaliable for Anthropic. This enables you to cache specific prompt portions, reuse cached content in subsequent calls, and reduce processed data per request.
 
 ??? note "Source Text"
 
@@ -182,18 +175,11 @@ By implementing prompt caching, you can potentially enhance efficiency and reduc
     ```
 
 ```python
-from instructor import Instructor, Mode, patch
+import instructor
 from anthropic import Anthropic
 from pydantic import BaseModel
 
-client = Instructor(  # (1)!
-    client=Anthropic(),
-    create=patch(
-        create=Anthropic().beta.prompt_caching.messages.create,
-        mode=Mode.ANTHROPIC_TOOLS,
-    ),
-    mode=Mode.ANTHROPIC_TOOLS,
-)
+client = instructor.from_anthropic(Anthropic())
 
 
 class Character(BaseModel):
@@ -204,16 +190,16 @@ class Character(BaseModel):
 with open("./book.txt") as f:
     book = f.read()
 
-resp = client.chat.completions.create(
-    model="claude-3-haiku-20240307",
+resp, completion = client.chat.completions.create_with_completion(
+    model="claude-3-5-sonnet-20240620",
     messages=[
         {
             "role": "user",
             "content": [
                 {
                     "type": "text",
                     "text": "<book>" + book + "</book>",
-                    "cache_control": {"type": "ephemeral"},  # (2)!
+                    "cache_control": {"type": "ephemeral"}, #(1)!
                 },
                 {
                     "type": "text",
@@ -225,11 +211,33 @@ resp = client.chat.completions.create(
     response_model=Character,
     max_tokens=1000,
 )
-```
 
-1. Since the feature is still in beta, we need to manually pass in the function that we're looking to patch.
+print(completion)
+# Message(
+#     id='msg_01QcqjktYc1PXL8nk7y5hkMV',
+#     content=[
+#         ToolUseBlock(
+#             id='toolu_019wABRzQxtSbXeuuRwvJo15',
+#             input={
+#                 'name': 'Jane Austen',
+#                 'description': 'A renowned English novelist of the early 19th century, known for her wit, humor, and keen observations of human nature. She is the author of
+# several classic novels including "Pride and Prejudice," "Emma," "Sense and Sensibility," and "Mansfield Park." Austen\'s writing is characterized by its subtlety, delicate touch,
+# and ability to create memorable characters. Her work often involves social commentary and explores themes of love, marriage, and societal expectations in Regency-era England.'
+#             },
+#             name='Character',
+#             type='tool_use'
+#         )
+#     ],
+#     model='claude-3-5-sonnet-20240620',
+#     role='assistant',
+#     stop_reason='tool_use',
+#     stop_sequence=None,
+#     type='message',
+#     usage=Usage(cache_creation_input_tokens=2777, cache_read_input_tokens=0, input_tokens=30, output_tokens=161)
+# )
+```
 
-2. Anthropic requires that you explicitly pass in the `cache_control` parameter to indicate that you want to cache the content.
+1. Anthropic requires that you explicitly pass in the `cache_control` parameter to indicate that you want to cache the content.
 
 !!! Warning "Caching Considerations"
 

instructor/client.py

@@ -373,7 +373,7 @@ def __init__(
         self.provider = provider
         self.hooks = hooks or Hooks()
 
-    async def create(
+    async def create(  # type: ignore[override]
         self,
         response_model: type[T] | None,
         messages: list[ChatCompletionMessageParam],
@@ -395,7 +395,7 @@ async def create(
             **kwargs,
         )
 
-    async def create_partial(
+    async def create_partial(  # type: ignore[override]
         self,
         response_model: type[T],
         messages: list[ChatCompletionMessageParam],
@@ -419,7 +419,7 @@ async def create_partial(
         ):
             yield item
 
-    async def create_iterable(
+    async def create_iterable(  # type: ignore[override]
         self,
         messages: list[ChatCompletionMessageParam],
         response_model: type[T],
@@ -443,7 +443,7 @@ async def create_iterable(
         ):
             yield item
 
-    async def create_with_completion(
+    async def create_with_completion(  # type: ignore[override]
         self,
         messages: list[ChatCompletionMessageParam],
         response_model: type[T],

instructor/client_anthropic.py

@@ -12,7 +12,6 @@ def from_anthropic(
         anthropic.Anthropic | anthropic.AnthropicBedrock | anthropic.AnthropicVertex
     ),
     mode: instructor.Mode = instructor.Mode.ANTHROPIC_TOOLS,
-    enable_prompt_caching: bool = False,
     beta: bool = False,
     **kwargs: Any,
 ) -> instructor.Instructor: ...
@@ -26,7 +25,6 @@ def from_anthropic(
         | anthropic.AsyncAnthropicVertex
     ),
     mode: instructor.Mode = instructor.Mode.ANTHROPIC_TOOLS,
-    enable_prompt_caching: bool = False,
     beta: bool = False,
     **kwargs: Any,
 ) -> instructor.AsyncInstructor: ...
@@ -42,7 +40,6 @@ def from_anthropic(
         | anthropic.AnthropicVertex
     ),
     mode: instructor.Mode = instructor.Mode.ANTHROPIC_TOOLS,
-    enable_prompt_caching: bool = False,
     beta: bool = False,
     **kwargs: Any,
 ) -> instructor.Instructor | instructor.AsyncInstructor:
@@ -82,14 +79,7 @@ def from_anthropic(
         ),
     ), "Client must be an instance of {anthropic.Anthropic, anthropic.AsyncAnthropic, anthropic.AnthropicBedrock, anthropic.AsyncAnthropicBedrock,  anthropic.AnthropicVertex, anthropic.AsyncAnthropicVertex}"
 
-    if enable_prompt_caching:
-        if isinstance(client, (anthropic.Anthropic, anthropic.AsyncAnthropic)):
-            create = client.beta.prompt_caching.messages.create
-        else:
-            raise TypeError(
-                "Client must be an instance of {anthropic.Anthropic, anthropic.AsyncAnthropic} to enable prompt caching"
-            )
-    elif beta:
+    if beta:
         create = client.beta.messages.create
     else:
         create = client.messages.create