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feat: Increased compatibility with new and old versions for dalle (#14222)
- **Description:** Increased compatibility with all versions openai for dalle, This pr add support for openai version from 0 ~ 1.3.
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@ -1,9 +1,17 @@
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"""Utility that calls OpenAI's Dall-E Image Generator."""
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from typing import Any, Dict, Optional
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import logging
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import os
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from typing import Any, Dict, Mapping, Optional, Tuple, Union
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from langchain_core.pydantic_v1 import BaseModel, Extra, root_validator
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from langchain_core.pydantic_v1 import BaseModel, Extra, Field, root_validator
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from langchain_core.utils import (
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get_pydantic_field_names,
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)
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from langchain.utils import get_from_dict_or_env
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from langchain.utils.openai import is_openai_v1
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logger = logging.getLogger(__name__)
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class DallEAPIWrapper(BaseModel):
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@ -18,52 +26,139 @@ class DallEAPIWrapper(BaseModel):
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"""
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client: Any #: :meta private:
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openai_api_key: Optional[str] = None
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async_client: Any = Field(default=None, exclude=True) #: :meta private:
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model_name: str = Field(default="dall-e-2", alias="model")
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model_kwargs: Dict[str, Any] = Field(default_factory=dict)
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openai_api_key: Optional[str] = Field(default=None, alias="api_key")
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"""Automatically inferred from env var `OPENAI_API_KEY` if not provided."""
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openai_api_base: Optional[str] = Field(default=None, alias="base_url")
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"""Base URL path for API requests, leave blank if not using a proxy or service
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emulator."""
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openai_organization: Optional[str] = Field(default=None, alias="organization")
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"""Automatically inferred from env var `OPENAI_ORG_ID` if not provided."""
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# to support explicit proxy for OpenAI
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openai_proxy: Optional[str] = None
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request_timeout: Union[float, Tuple[float, float], Any, None] = Field(
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default=None, alias="timeout"
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)
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n: int = 1
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"""Number of images to generate"""
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size: str = "1024x1024"
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"""Size of image to generate"""
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separator: str = "\n"
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"""Separator to use when multiple URLs are returned."""
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model: Optional[str] = "dall-e-2"
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"""Model to use for image generation"""
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quality: Optional[str] = "standard"
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"""Quality of the image that will be generated"""
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max_retries: int = 2
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"""Maximum number of retries to make when generating."""
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default_headers: Union[Mapping[str, str], None] = None
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default_query: Union[Mapping[str, object], None] = None
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# Configure a custom httpx client. See the
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# [httpx documentation](https://www.python-httpx.org/api/#client) for more details.
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http_client: Union[Any, None] = None
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"""Optional httpx.Client."""
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class Config:
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"""Configuration for this pydantic object."""
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extra = Extra.forbid
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@root_validator(pre=True)
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def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:
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"""Build extra kwargs from additional params that were passed in."""
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all_required_field_names = get_pydantic_field_names(cls)
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extra = values.get("model_kwargs", {})
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for field_name in list(values):
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if field_name in extra:
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raise ValueError(f"Found {field_name} supplied twice.")
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if field_name not in all_required_field_names:
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logger.warning(
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f"""WARNING! {field_name} is not default parameter.
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{field_name} was transferred to model_kwargs.
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Please confirm that {field_name} is what you intended."""
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)
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extra[field_name] = values.pop(field_name)
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invalid_model_kwargs = all_required_field_names.intersection(extra.keys())
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if invalid_model_kwargs:
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raise ValueError(
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f"Parameters {invalid_model_kwargs} should be specified explicitly. "
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f"Instead they were passed in as part of `model_kwargs` parameter."
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)
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values["model_kwargs"] = extra
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return values
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@root_validator()
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def validate_environment(cls, values: Dict) -> Dict:
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"""Validate that api key and python package exists in environment."""
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openai_api_key = get_from_dict_or_env(
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values["openai_api_key"] = get_from_dict_or_env(
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values, "openai_api_key", "OPENAI_API_KEY"
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)
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try:
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from openai import OpenAI
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client = OpenAI(
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api_key=openai_api_key, # this is also the default, it can be omitted
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# Check OPENAI_ORGANIZATION for backwards compatibility.
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values["openai_organization"] = (
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values["openai_organization"]
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or os.getenv("OPENAI_ORG_ID")
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or os.getenv("OPENAI_ORGANIZATION")
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or None
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)
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values["openai_api_base"] = values["openai_api_base"] or os.getenv(
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"OPENAI_API_BASE"
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)
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values["openai_proxy"] = get_from_dict_or_env(
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values,
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"openai_proxy",
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"OPENAI_PROXY",
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default="",
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)
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values["client"] = client
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except ImportError as e:
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try:
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import openai
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except ImportError:
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raise ImportError(
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"Could not import openai python package. "
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"Please it install it with `pip install openai`."
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) from e
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"Please install it with `pip install openai`."
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)
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if is_openai_v1():
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client_params = {
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"api_key": values["openai_api_key"],
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"organization": values["openai_organization"],
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"base_url": values["openai_api_base"],
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"timeout": values["request_timeout"],
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"max_retries": values["max_retries"],
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"default_headers": values["default_headers"],
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"default_query": values["default_query"],
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"http_client": values["http_client"],
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}
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if not values.get("client"):
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values["client"] = openai.OpenAI(**client_params).images
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if not values.get("async_client"):
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values["async_client"] = openai.AsyncOpenAI(**client_params).images
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elif not values.get("client"):
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values["client"] = openai.Image
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else:
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pass
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return values
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def run(self, query: str) -> str:
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"""Run query through OpenAI and parse result."""
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response = self.client.images.generate(
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if is_openai_v1():
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response = self.client.generate(
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prompt=query,
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n=self.n,
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size=self.size,
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model=self.model,
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model=self.model_name,
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quality=self.quality,
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)
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image_urls = self.separator.join([item.url for item in response.data])
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else:
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response = self.client.create(
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prompt=query, n=self.n, size=self.size, model=self.model_name
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)
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image_urls = self.separator.join([item["url"] for item in response["data"]])
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return image_urls if image_urls else "No image was generated"
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