openai¶
A module for interacting with OpenAI models.
OpenAICall
¶
Bases: BaseCall[OpenAICallResponse, OpenAICallResponseChunk, OpenAITool]
A base class for calling OpenAI's Chat Completion models.
Example:
from mirascope.openai import OpenAICall
class BookRecommender(OpenAICall):
prompt_template = "Please recommend a {genre} book"
genre: str
response = BookRecommender(genre="fantasy").call()
print(response.content)
#> There are many great books to read, it ultimately depends...
Source code in mirascope/openai/calls.py
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|
call(retries=1, **kwargs)
¶
Makes a call to the model using this OpenAICall
instance.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
retries |
Union[int, Retrying]
|
An integer for the number of times to retry the call or
a |
1
|
**kwargs |
Any
|
Additional keyword arguments parameters to pass to the call. These
will override any existing arguments in |
{}
|
Returns:
Type | Description |
---|---|
OpenAICallResponse
|
A |
Raises:
Type | Description |
---|---|
OpenAIError
|
raises any OpenAI errors, see: https://platform.openai.com/docs/guides/error-codes/api-errors |
Source code in mirascope/openai/calls.py
call_async(retries=1, **kwargs)
async
¶
Makes an asynchronous call to the model using this OpenAICall
.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
retries |
Union[int, AsyncRetrying]
|
An integer for the number of times to retry the call or
a |
1
|
**kwargs |
Any
|
Additional keyword arguments parameters to pass to the call. These
will override any existing arguments in |
{}
|
Returns:
Type | Description |
---|---|
OpenAICallResponse
|
An |
Raises:
Type | Description |
---|---|
OpenAIError
|
raises any OpenAI errors, see: https://platform.openai.com/docs/guides/error-codes/api-errors |
Source code in mirascope/openai/calls.py
messages()
¶
Returns the template as a formatted list of messages.
Source code in mirascope/openai/calls.py
stream(retries=1, **kwargs)
¶
Streams the response for a call using this OpenAICall
.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
retries |
Union[int, Retrying]
|
An integer for the number of times to retry the call or
a |
1
|
**kwargs |
Any
|
Additional keyword arguments parameters to pass to the call. These
will override any existing arguments in |
{}
|
Yields:
Type | Description |
---|---|
OpenAICallResponseChunk
|
A |
Raises:
Type | Description |
---|---|
OpenAIError
|
raises any OpenAI errors, see: https://platform.openai.com/docs/guides/error-codes/api-errors |
Source code in mirascope/openai/calls.py
stream_async(retries=1, **kwargs)
async
¶
Streams the response for an asynchronous call using this OpenAICall
.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
retries |
Union[int, AsyncRetrying]
|
An integer for the number of times to retry the call or
a |
1
|
**kwargs |
Any
|
Additional keyword arguments parameters to pass to the call. These
will override any existing arguments in |
{}
|
Yields:
Type | Description |
---|---|
AsyncGenerator[OpenAICallResponseChunk, None]
|
A |
Raises:
Type | Description |
---|---|
OpenAIError
|
raises any OpenAI errors, see: https://platform.openai.com/docs/guides/error-codes/api-errors |
Source code in mirascope/openai/calls.py
OpenAICallParams
¶
Bases: BaseCallParams[OpenAITool]
The parameters to use when calling the OpenAI API.
Source code in mirascope/openai/types.py
kwargs(tool_type=OpenAITool, exclude=None)
¶
Returns the keyword argument call parameters.
Source code in mirascope/openai/types.py
OpenAICallResponse
¶
Bases: BaseCallResponse[ChatCompletion, OpenAITool]
A convenience wrapper around the OpenAI ChatCompletion
response.
When using Mirascope's convenience wrappers to interact with OpenAI models via
OpenAICall
, responses using OpenAICall.call()
will return a
OpenAICallResponse
, whereby the implemented properties allow for simpler syntax
and a convenient developer experience.
Example:
from mirascope.openai import OpenAICall
class BookRecommender(OpenAICall):
prompt_template = "Please recommend a {genre} book"
genre: str
response = Bookrecommender(genre="fantasy").call()
print(response.content)
#> The Name of the Wind
print(response.message)
#> ChatCompletionMessage(content='The Name of the Wind', role='assistant',
# function_call=None, tool_calls=None)
print(response.choices)
#> [Choice(finish_reason='stop', index=0, logprobs=None,
# message=ChatCompletionMessage(content='The Name of the Wind', role='assistant',
# function_call=None, tool_calls=None))]
Source code in mirascope/openai/types.py
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|
choice: Choice
property
¶
Returns the 0th choice.
choices: list[Choice]
property
¶
Returns the array of chat completion choices.
content: str
property
¶
Returns the content of the chat completion for the 0th choice.
message: ChatCompletionMessage
property
¶
Returns the message of the chat completion for the 0th choice.
tool: Optional[OpenAITool]
property
¶
Returns the 0th tool for the 0th choice message.
Raises:
Type | Description |
---|---|
ValidationError
|
if the tool call doesn't match the tool's schema. |
tool_calls: Optional[list[ChatCompletionMessageToolCall]]
property
¶
Returns the tool calls for the 0th choice message.
tools: Optional[list[OpenAITool]]
property
¶
Returns the tools for the 0th choice message.
Raises:
Type | Description |
---|---|
ValidationError
|
if a tool call doesn't match the tool's schema. |
dump()
¶
Dumps the response to a dictionary.
OpenAICallResponseChunk
¶
Bases: BaseCallResponseChunk[ChatCompletionChunk, OpenAITool]
Convenience wrapper around chat completion streaming chunks.
When using Mirascope's convenience wrappers to interact with OpenAI models via
OpenAICall.stream
, responses will return an OpenAICallResponseChunk
, whereby
the implemented properties allow for simpler syntax and a convenient developer
experience.
Example:
```python from mirascope.openai import OpenAICall
class Math(OpenAICall): prompt_template = "What is 1 + 2?"
for chunk in OpenAICall().stream(): print(chunk.content)
> 1¶
+¶
2¶
equals¶
¶
3¶
.¶
Source code in mirascope/openai/types.py
choice: ChunkChoice
property
¶
Returns the 0th choice.
choices: list[ChunkChoice]
property
¶
Returns the array of chat completion choices.
content: str
property
¶
Returns the content for the 0th choice delta.
delta: ChoiceDelta
property
¶
Returns the delta for the 0th choice.
tool_calls: Optional[list[ChoiceDeltaToolCall]]
property
¶
Returns the partial tool calls for the 0th choice message.
The first list[ChoiceDeltaToolCall]
will contain the name of the tool and
index, and subsequent list[ChoiceDeltaToolCall]
s will contain the arguments
which will be strings that need to be concatenated with future
list[ChoiceDeltaToolCall]
s to form a complete JSON tool calls. The last
list[ChoiceDeltaToolCall]
will be None indicating end of stream.
OpenAIEmbedder
¶
Bases: BaseEmbedder[OpenAIEmbeddingResponse]
OpenAI Embedder
Example:
import os
from mirascope.openai import OpenAIEmbedder
os.environ["OPENAI_API_KEY"] = "YOUR_OPENAI_API_KEY"
openai_embedder = OpenAIEmbedder()
response = openai_embedder.embed(["your text to embed"])
print(response)
Source code in mirascope/openai/embedders.py
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|
__call__(input)
¶
Call the embedder with a input
Chroma expects parameter to be input
.
embed(inputs)
¶
Call the embedder with multiple inputs
Source code in mirascope/openai/embedders.py
embed_async(inputs)
async
¶
Asynchronously call the embedder with multiple inputs
Source code in mirascope/openai/embedders.py
OpenAIEmbeddingResponse
¶
Bases: BaseEmbeddingResponse[CreateEmbeddingResponse]
A convenience wrapper around the OpenAI CreateEmbeddingResponse
response.
Source code in mirascope/openai/types.py
embeddings: list[list[float]]
property
¶
Returns the raw embeddings.
OpenAIExtractor
¶
Bases: BaseExtractor[OpenAICall, OpenAITool, OpenAIToolStream, T]
, Generic[T]
A class for extracting structured information using OpenAI chat models.
Example:
from typing import Literal, Type
from mirascope.openai import OpenAIExtractor
from pydantic import BaseModel
class TaskDetails(BaseModel):
title: str
priority: Literal["low", "normal", "high"]
due_date: str
class TaskExtractor(OpenAIExtractor[TaskDetails]):
extract_schema: Type[TaskDetails] = TaskDetails
prompt_template = """
Please extract the task details:
{task}
"""
task: str
task_description = "Submit quarterly report by next Friday. Task is high priority."
task = TaskExtractor(task=task_description).extract(retries=3)
assert isinstance(task, TaskDetails)
print(task)
#> title='Submit quarterly report' priority='high' due_date='next Friday'
Source code in mirascope/openai/extractors.py
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|
extract(retries=0, **kwargs)
¶
Extracts extract_schema
from the OpenAI call response.
The extract_schema
is converted into an OpenAITool
, complete with a
description of the tool, all of the fields, and their types. This allows us to
take advantage of OpenAI's tool/function calling functionality to extract
information from a prompt according to the context provided by the BaseModel
schema.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
retries |
Union[int, Retrying]
|
The maximum number of times to retry the query on validation error. |
0
|
**kwargs |
Any
|
Additional keyword arguments parameters to pass to the call. These
will override any existing arguments in |
{}
|
Returns:
Type | Description |
---|---|
T
|
The |
Raises:
Type | Description |
---|---|
AttributeError
|
if there is no tool in the call creation. |
ValidationError
|
if the schema cannot be instantiated from the completion. |
OpenAIError
|
raises any OpenAI errors, see: https://platform.openai.com/docs/guides/error-codes/api-errors |
Source code in mirascope/openai/extractors.py
extract_async(retries=0, **kwargs)
async
¶
Asynchronously extracts extract_schema
from the OpenAI call response.
The extract_schema
is converted into an OpenAITool
, complete with a
description of the tool, all of the fields, and their types. This allows us to
take advantage of OpenAI's tool/function calling functionality to extract
information from a prompt according to the context provided by the BaseModel
schema.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
retries |
Union[int, AsyncRetrying]
|
The maximum number of times to retry the query on validation error. |
0
|
**kwargs |
Any
|
Additional keyword arguments parameters to pass to the call. These
will override any existing arguments in |
{}
|
Returns:
Type | Description |
---|---|
T
|
The |
Raises:
Type | Description |
---|---|
AttributeError
|
if there is no tool in the call creation. |
ValidationError
|
if the schema cannot be instantiated from the completion. |
OpenAIError
|
raises any OpenAI errors, see: https://platform.openai.com/docs/guides/error-codes/api-errors |
Source code in mirascope/openai/extractors.py
stream(retries=0, **kwargs)
¶
Streams partial instances of extract_schema
as the schema is streamed.
The extract_schema
is converted into a partial(OpenAITool)
, which allows for
any field (i.e.function argument) in the tool to be None
. This allows us to
stream partial results as we construct the tool from the streamed chunks.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
retries |
Union[int, Retrying]
|
The maximum number of times to retry the query on validation error. |
0
|
**kwargs |
Any
|
Additional keyword argument parameters to pass to the call. These
will override any existing arguments in |
{}
|
Yields:
Type | Description |
---|---|
T
|
The partial |
Raises:
Type | Description |
---|---|
AttributeError
|
if there is no tool in the call creation. |
ValidationError
|
if the schema cannot be instantiated from the completion. |
OpenAIError
|
raises any OpenAI errors, see: https://platform.openai.com/docs/guides/error-codes/api-errors |
Source code in mirascope/openai/extractors.py
stream_async(retries=0, **kwargs)
async
¶
Asynchronously streams partial instances of extract_schema
as streamed.
The extract_schema
is converted into a partial(OpenAITool)
, which allows for
any field (i.e.function argument) in the tool to be None
. This allows us to
stream partial results as we construct the tool from the streamed chunks.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
retries |
Union[int, AsyncRetrying]
|
The maximum number of times to retry the query on validation error. |
0
|
**kwargs |
Any
|
Additional keyword arguments parameters to pass to the call. These
will override any existing arguments in |
{}
|
Yields:
Type | Description |
---|---|
AsyncGenerator[T, None]
|
The partial |
Raises:
Type | Description |
---|---|
AttributeError
|
if there is no tool in the call creation. |
ValidationError
|
if the schema cannot be instantiated from the completion. |
OpenAIError
|
raises any OpenAI errors, see: https://platform.openai.com/docs/guides/error-codes/api-errors |
Source code in mirascope/openai/extractors.py
OpenAITool
¶
Bases: BaseTool[ChatCompletionMessageToolCall]
A base class for easy use of tools with the OpenAI Chat client.
OpenAITool
internally handles the logic that allows you to use tools with simple
calls such as OpenAICallResponse.tool
or OpenAITool.fn
, as seen in the
examples below.
Example:
from mirascope.openai import OpenAICall, OpenAICallParams
def animal_matcher(fav_food: str, fav_color: str) -> str:
"""Tells you your most likely favorite animal from personality traits.
Args:
fav_food: your favorite food.
fav_color: your favorite color.
Returns:
The animal most likely to be your favorite based on traits.
"""
return "Your favorite animal is the best one, a frog."
class AnimalMatcher(OpenAICall):
prompt_template = """
Tell me my favorite animal if my favorite food is {food} and my
favorite color is {color}.
"""
food: str
color: str
call_params = OpenAICallParams(tools=[animal_matcher])
response = AnimalMatcher(food="pizza", color="red").call
tool = response.tool
print(tool.fn(**tool.args))
#> Your favorite animal is the best one, a frog.
Source code in mirascope/openai/tools.py
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|
from_base_type(base_type)
classmethod
¶
Constructs a OpenAITool
type from a BaseType
type.
from_fn(fn)
classmethod
¶
from_model(model)
classmethod
¶
Constructs a OpenAITool
type from a BaseModel
type.
from_tool_call(tool_call, allow_partial=False)
classmethod
¶
Extracts an instance of the tool constructed from a tool call response.
Given ChatCompletionMessageToolCall
from an OpenAI chat completion response,
takes its function arguments and creates an OpenAITool
instance from it.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
tool_call |
ChatCompletionMessageToolCall
|
The |
required |
Returns:
Type | Description |
---|---|
OpenAITool
|
An instance of the tool constructed from the tool call. |
Raises:
Type | Description |
---|---|
ValidationError
|
if the tool call doesn't match the tool schema. |
Source code in mirascope/openai/tools.py
tool_schema()
classmethod
¶
Constructs a tool schema for use with the OpenAI Chat client.
A Mirascope OpenAITool
is deconstructed into a JSON schema, and relevant keys
are renamed to match the OpenAI ChatCompletionToolParam
schema used to make
function/tool calls in OpenAI API.
Returns:
Type | Description |
---|---|
ChatCompletionToolParam
|
The constructed |
Source code in mirascope/openai/tools.py
OpenAIToolStream
¶
Bases: BaseToolStream[OpenAICallResponseChunk, OpenAITool]
A base class for streaming tools from response chunks.
Source code in mirascope/openai/tool_streams.py
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|
from_async_stream(async_stream, allow_partial=False)
async
classmethod
¶
Yields partial tools from the given stream of chunks asynchronously.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
stream |
The async generator of chunks from which to stream tools. |
required | |
allow_partial |
Whether to allow partial tools. |
False
|
Raises:
Type | Description |
---|---|
RuntimeError
|
if a tool in the stream is of an unknown type. |
Source code in mirascope/openai/tool_streams.py
from_stream(stream, allow_partial=False)
classmethod
¶
Yields partial tools from the given stream of chunks.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
stream |
The generator of chunks from which to stream tools. |
required | |
allow_partial |
Whether to allow partial tools. |
False
|
Raises:
Type | Description |
---|---|
RuntimeError
|
if a tool in the stream is of an unknown type. |
Source code in mirascope/openai/tool_streams.py
openai_api_calculate_cost(usage, model='gpt-3.5-turbo-16k')
¶
Calculate the cost of a completion using the OpenAI API.
https://openai.com/pricing
Model Input Output gpt-3.5-turbo-0125 $0.50 / 1M tokens $1.50 / 1M tokens gpt-3.5-turbo-1106 $1.00 / 1M tokens $2.00 / 1M tokens gpt-4-1106-preview $10.00 / 1M tokens $30.00 / 1M tokens gpt-4 $30.00 / 1M tokens $60.00 / 1M tokens text-embedding-3-small $0.02 / 1M tokens text-embedding-3-large $0.13 / 1M tokens text-embedding-ada-0002 $0.10 / 1M tokens