diff --git a/README.md b/README.md index 4e8eaabef..83d4dcda7 100644 --- a/README.md +++ b/README.md @@ -289,6 +289,44 @@ print(model.model_dump_json(indent=2)) """ ``` +## Using Anthropic Models + +Install dependencies with + +```shell +poetry install -E anthropic +``` + +Usage: + +```python +import instructor +from anthropic import Anthropic + +class User(BaseModel): + name: str + age: int + +create = instructor.patch(create=anthropic.Anthropic().messages.create, mode=instructor.Mode.ANTHROPIC_TOOLS) + +resp = create( + model="claude-3-opus-20240229", + max_tokens=1024, + max_retries=0, + messages=[ + { + "role": "user", + "content": "Extract Jason is 25 years old.", + } + ], + response_model=User, +) + +assert isinstance(resp, User) +assert resp.name == "Jason" +assert resp.age == 25 +``` + ## [Evals](https://github.com/jxnl/instructor/tree/main/tests/openai/evals) We invite you to contribute to evals in `pytest` as a way to monitor the quality of the OpenAI models and the `instructor` library. To get started check out the [jxnl/instructor/tests/evals](https://github.com/jxnl/instructor/tree/main/tests/openai/evals) and contribute your own evals in the form of pytest tests. These evals will be run once a week and the results will be posted. diff --git a/docs/blog/posts/anthropic.md b/docs/blog/posts/anthropic.md new file mode 100644 index 000000000..db0428893 --- /dev/null +++ b/docs/blog/posts/anthropic.md @@ -0,0 +1,66 @@ +--- +draft: False +date: 2024-03-20 +authors: + - jxnl +--- + +# Announcing Anthropic Support + +A special shoutout to [Shreya](https://twitter.com/shreyaw_) for her contributions to the anthropic support. As of now, all features are operational with the exception of streaming support. + +For those eager to experiment, simply patch the client with `ANTHROPIC_TOOLS`, which will enable you to leverage the `anthropic` client for making requests. + +``` +pip install instructor[anthropic] +``` + +```python +from pydantic import BaseModel +from typing import List +import anthropic +import instructor + +# Patching the Anthropics client with the instructor for enhanced capabilities +anthropic_client = instructor.patch( + create=anthropic.Anthropic().messages.create, + mode=instructor.Mode.ANTHROPIC_TOOLS +) + +class Properties(BaseModel): + name: str + value: str + +class User(BaseModel): + name: str + age: int + properties: List[Properties] + +user_response = anthropic_client( + model="claude-3-haiku-20240307", + max_tokens=1024, + max_retries=0, + messages=[ + { + "role": "user", + "content": "Create a user for a model with a name, age, and properties.", + } + ], + response_model=User, +) # type: ignore + +print(user_response.model_dump_json(indent=2)) +""" +{ + "name": "John", + "age": 25, + "properties": [ + { + "key": "favorite_color", + "value": "blue" + } + ] +} +``` + +We're encountering challenges with deeply nested types and eagerly invite the community to test, provide feedback, and suggest necessary improvements as we enhance the anthropic client's support. \ No newline at end of file diff --git a/examples/anthropic/run.py b/examples/anthropic/run.py new file mode 100644 index 000000000..0dd39b3b8 --- /dev/null +++ b/examples/anthropic/run.py @@ -0,0 +1,36 @@ +from pydantic import BaseModel +from typing import List +import anthropic +import instructor + +# Patching the Anthropics client with the instructor for enhanced capabilities +anthropic_client = instructor.patch( + create=anthropic.Anthropic().messages.create, mode=instructor.Mode.ANTHROPIC_TOOLS +) + + +class Properties(BaseModel): + key: str + value: str + + +class User(BaseModel): + name: str + age: int + properties: List[Properties] + + +user_response = anthropic_client( + model="claude-3-haiku-20240307", + max_tokens=1024, + max_retries=0, + messages=[ + { + "role": "user", + "content": "Create a user for a model with a name, age, and properties.", + } + ], + response_model=User, +) # type: ignore + +print(user_response.model_dump_json(indent=2)) diff --git a/instructor/anthropic_utils.py b/instructor/anthropic_utils.py new file mode 100644 index 000000000..6bd75eee6 --- /dev/null +++ b/instructor/anthropic_utils.py @@ -0,0 +1,124 @@ +import re +import xmltodict +from pydantic import BaseModel +import xml.etree.ElementTree as ET +from typing import Type, Any, Dict, TypeVar + +T = TypeVar("T", bound=BaseModel) + + +def json_to_xml(model: Type[BaseModel]) -> str: + """Takes a Pydantic model and returns XML format for Anthropic function calling.""" + model_dict = model.model_json_schema() + + root = ET.Element("tool_description") + tool_name = ET.SubElement(root, "tool_name") + tool_name.text = model_dict.get("title", "Unknown") + description = ET.SubElement(root, "description") + description.text = ( + "This is the function that must be used to construct the response." + ) + parameters = ET.SubElement(root, "parameters") + references = model_dict.get("$defs", {}) + list_type_found = _add_params(parameters, model_dict, references) + + if list_type_found: # Need to append to system prompt for List type handling + return ( + ET.tostring(root, encoding="unicode") + + "\nFor any List[] types, include multiple <$PARAMETER_NAME>$PARAMETER_VALUE tags for each item in the list. XML tags should only contain the name of the parameter." + ) + else: + return ET.tostring(root, encoding="unicode") + + +def _add_params( + root: ET.Element, model_dict: Dict[str, Any], references: Dict[str, Any] +) -> bool: # Return value indiciates if we ever came across a param with type List + # TODO: handling of nested params with the same name + properties = model_dict.get("properties", {}) + list_found = False + + for field_name, details in properties.items(): + parameter = ET.SubElement(root, "parameter") + name = ET.SubElement(parameter, "name") + name.text = field_name + type_element = ET.SubElement(parameter, "type") + + # Get type + if "anyOf" in details: # Case where there can be multiple types + # supports: + # case 1: List type (example json: {'anyOf': [{'items': {'$ref': '#/$defs/PartialUser'}, 'type': 'array'}, {'type': 'null'}], 'default': None, 'title': 'Users'}) + # case 2: nested model (example json: {'anyOf': [{'$ref': '#/$defs/PartialDate'}, {'type': 'null'}], 'default': {}}) + field_type = " or ".join( + [ + d["type"] + if "type" in d + else (d["$ref"] if "$ref" in d else "unknown") + for d in details["anyOf"] + ] + ) + else: + field_type = details.get( + "type", "unknown" + ) # Might be better to fail here if there is no type since pydantic models require types + + # Adjust type if array + if "array" in field_type or "List" in field_type: + type_element.text = f"List[{details['title']}]" + list_found = True + else: + type_element.text = field_type + + param_description = ET.SubElement(parameter, "description") + param_description.text = details.get("description", "") + + if ( + isinstance(details, dict) and "$ref" in details + ): # Checking if there are nested params + nested_params = ET.SubElement(parameter, "parameters") + list_found |= _add_params( + nested_params, + _resolve_reference(references, details["$ref"]), + references, + ) + elif field_type == "array": # Handling for List[] type + nested_params = ET.SubElement(parameter, "parameters") + list_found |= _add_params( + nested_params, + _resolve_reference(references, details["items"]["$ref"]), + references, + ) + elif "array" in field_type: # Handling for optional List[] type + nested_params = ET.SubElement(parameter, "parameters") + list_found |= _add_params( + nested_params, + _resolve_reference( + references, details["anyOf"][0]["items"]["$ref"] + ), # CHANGE + references, + ) + + return list_found + + +def _resolve_reference(references: Dict[str, Any], reference: str) -> Dict[str, Any]: + parts = reference.split("/")[2:] # Remove "#" and "$defs" + for part in parts: + references = references[part] + return references + + +def extract_xml(content: str) -> str: # Currently assumes 1 function call only + """Extracts XML content in Anthropic's schema from a string.""" + pattern = r".*?" + matches = re.findall(pattern, content, re.DOTALL) + return "".join(matches) + + +def xml_to_model(model: Type[T], xml_string: str) -> T: + """Converts XML in Anthropic's schema to an instance of the provided class.""" + parsed_xml = xmltodict.parse(xml_string) + model_dict = parsed_xml["function_calls"]["invoke"]["parameters"] + return model( + **model_dict + ) # This sometimes fails if Anthropic's response hallucinates from the schema diff --git a/instructor/cli/cli.py b/instructor/cli/cli.py index c3b8af56e..7ff9e6f6f 100644 --- a/instructor/cli/cli.py +++ b/instructor/cli/cli.py @@ -21,4 +21,3 @@ def docs(query: str = typer.Argument(None, help="Search the documentation")) -> typer.launch(f"https://jxnl.github.io/instructor/?q={query}") else: typer.launch("https://jxnl.github.io/instructor") - diff --git a/instructor/function_calls.py b/instructor/function_calls.py index 36af25def..84a4da91b 100644 --- a/instructor/function_calls.py +++ b/instructor/function_calls.py @@ -7,6 +7,9 @@ from instructor.mode import Mode from instructor.utils import extract_json_from_codeblock import logging +import importlib + +from .anthropic_utils import json_to_xml, extract_xml, xml_to_model T = TypeVar("T") @@ -57,6 +60,11 @@ def openai_schema(cls) -> Dict[str, Any]: "parameters": parameters, } + @classmethod + @property + def anthropic_schema(cls) -> str: + return json_to_xml(cls) + @classmethod def from_response( cls, @@ -77,6 +85,17 @@ def from_response( Returns: cls (OpenAISchema): An instance of the class """ + if mode == Mode.ANTHROPIC_TOOLS: + try: + assert isinstance( + completion, + importlib.import_module("anthropic.types.message").Message, + ) + except ImportError as err: + raise ImportError("Please 'pip install anthropic' package to proceed.") from err + assert hasattr(completion, "content") + return xml_to_model(cls, extract_xml(completion.content[0].text)) # type:ignore + assert hasattr(completion, "choices") if completion.choices[0].finish_reason == "length": diff --git a/instructor/mode.py b/instructor/mode.py index f04c4a214..e53bde097 100644 --- a/instructor/mode.py +++ b/instructor/mode.py @@ -12,6 +12,7 @@ class Mode(enum.Enum): JSON = "json_mode" MD_JSON = "markdown_json_mode" JSON_SCHEMA = "json_schema_mode" + ANTHROPIC_TOOLS = "anthropic_tools" def __new__(cls, value: str) -> "Mode": member = object.__new__(cls) diff --git a/instructor/process_response.py b/instructor/process_response.py index a59e7bd67..91c75bdc0 100644 --- a/instructor/process_response.py +++ b/instructor/process_response.py @@ -281,6 +281,29 @@ def handle_response_model( # if it is, system append the schema to the end else: new_kwargs["messages"][0]["content"] += f"\n\n{message}" + elif mode == Mode.ANTHROPIC_TOOLS: + tool_descriptions = response_model.anthropic_schema + system_prompt = dedent( + f""" + In this environment you have access to a set of tools you can use to answer the user's question. + You may call them like this: + + + $TOOL_NAME + + <$PARAMETER_NAME>$PARAMETER_VALUE + ... + + + + + Here are the tools available:\n{tool_descriptions} + """ + ) + if "system" in new_kwargs: + new_kwargs["system"] = f"{system_prompt}\n{new_kwargs['system']}" + else: + new_kwargs["system"] = system_prompt else: raise ValueError(f"Invalid patch mode: {mode}") diff --git a/instructor/retry.py b/instructor/retry.py index cd3139c76..ff8f7178f 100644 --- a/instructor/retry.py +++ b/instructor/retry.py @@ -24,8 +24,15 @@ def reask_messages(response: ChatCompletion, mode: Mode, exception: Exception): - yield dump_message(response.choices[0].message) + if mode == Mode.ANTHROPIC_TOOLS: + # TODO: we need to include the original response + yield { + "role": "user", + "content": f"Validation Error found:\n{exception}\nRecall the function correctly, fix the errors", + } + return + yield dump_message(response.choices[0].message) # TODO: Give users more control on configuration if mode == Mode.TOOLS: for tool_call in response.choices[0].message.tool_calls: # type: ignore diff --git a/poetry.lock b/poetry.lock index cf4746396..c339194e3 100644 --- a/poetry.lock +++ b/poetry.lock @@ -121,6 +121,30 @@ files = [ 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+[tool.poetry.group.anthropic.dependencies] +anthropic = "^0.18.1" +xmltodict = "^0.13.0" + [tool.poetry.scripts] instructor = "instructor.cli.cli:app" @@ -48,4 +52,4 @@ tabulate = "^0.9.0" [build-system] requires = ["poetry-core"] -build-backend = "poetry.core.masonry.api" +build-backend = "poetry.core.masonry.api" \ No newline at end of file diff --git a/requirements.txt b/requirements.txt index 4f8f563c5..5abdbe79f 100644 --- a/requirements.txt +++ b/requirements.txt @@ -7,3 +7,5 @@ ruff==0.1.7 pre-commit==3.5.0 mypy==1.7.1 typer +anthropic +xmltodict \ No newline at end of file diff --git a/tests/anthropic/test_anthropic.py b/tests/anthropic/test_anthropic.py new file mode 100644 index 000000000..8bf5d94f4 --- /dev/null +++ b/tests/anthropic/test_anthropic.py @@ -0,0 +1,35 @@ +import pytest +import anthropic +import instructor +from pydantic import BaseModel +from typing import List + +create = instructor.patch( + create=anthropic.Anthropic().messages.create, mode=instructor.Mode.ANTHROPIC_TOOLS +) + +@pytest.mark.skip +def test_anthropic(): + class Properties(BaseModel): + name: str + value: List[str] + + class User(BaseModel): + name: str + age: int + properties: List[Properties] + + resp = create( + model="claude-3-haiku-20240307", + max_tokens=1024, + max_retries=0, + messages=[ + { + "role": "user", + "content": "Create a user for a model with a name, age, and properties.", + } + ], + response_model=User, + ) # type: ignore + + assert isinstance(resp, User) diff --git a/tests/anthropic/test_simple.py b/tests/anthropic/test_simple.py new file mode 100644 index 000000000..66b6e821a --- /dev/null +++ b/tests/anthropic/test_simple.py @@ -0,0 +1,92 @@ +import pytest +import anthropic +import instructor +from pydantic import BaseModel +from typing import List + +create = instructor.patch( + create=anthropic.Anthropic().messages.create, mode=instructor.Mode.ANTHROPIC_TOOLS +) + +@pytest.mark.skip +def test_simple(): + class User(BaseModel): + name: str + age: int + + resp = create( + model="claude-3-haiku-20240307", + max_tokens=1024, + max_retries=0, + messages=[ + { + "role": "user", + "content": "Extract John is 18 years old.", + } + ], + response_model=User, + ) # type: ignore + + assert isinstance(resp, User) + assert resp.name == "John" + assert resp.age == 18 + +@pytest.mark.skip +def test_nested_type(): + class Address(BaseModel): + house_number: int + street_name: str + + class User(BaseModel): + name: str + age: int + address: Address + + resp = create( + model="claude-3-haiku-20240307", + max_tokens=1024, + max_retries=0, + messages=[ + { + "role": "user", + "content": "Extract John is 18 years old and lives at 123 First Avenue.", + } + ], + response_model=User, + ) # type: ignore + + assert isinstance(resp, User) + assert resp.name == "John" + assert resp.age == 18 + + assert isinstance(resp.address, Address) + assert resp.address.house_number == 123 + assert resp.address.street_name == "First Avenue" + +@pytest.mark.skip +def test_nested_list(): + class Properties(BaseModel): + key: str + value: str + + class User(BaseModel): + name: str + age: int + properties: List[Properties] + + resp = create( + model="claude-3-opus-20240229", # Fails with claude-3-haiku-20240307 + max_tokens=1024, + max_retries=0, + messages=[ + { + "role": "user", + "content": "Create a user for a model with a name, age, and properties.", + } + ], + response_model=User, + ) # type: ignore + + assert isinstance(resp, User) + for property in resp.properties: + assert isinstance(property, Properties)