use api_enum method on GooeyEnum class, use it with LargeLanguageModels

daras_ai_v2/base.py

@@ -138,6 +138,9 @@ class BasePage:
     )
 
     class RequestModel(BaseModel):
+        class Config:
+            use_enum_values = True
+
         functions: list[RecipeFunction] | None = Field(
             title="🧩 Developer Tools and Functions",
         )

daras_ai_v2/custom_enum.py

@@ -23,6 +23,29 @@ def from_db(cls, db_value) -> typing_extensions.Self:
     def api_choices(cls):
         return typing.Literal[tuple(e.name for e in cls)]
 
+    @classmethod
+    @property
+    def api_enum(cls):
+        """
+        Enum that is useful as a type in API requests.
+
+        Maps `name`->`name` for all values.
+        The title (same as the Enum class name) will be
+        used as the new Enum's title. This will be passed
+        on to the OpenAPI schema and the generated SDK.
+        """
+        # this cache is a hack to get around a bug where
+        # dynamic Enums with the same name crash when
+        # generating the OpenAPI spec
+        if not hasattr(cls, "_cached_api_enum"):
+            cls._cached_api_enum = {}
+        if cls.__name__ not in cls._cached_api_enum:
+            cls._cached_api_enum[cls.__name__] = Enum(
+                cls.__name__, {e.name: e.name for e in cls}
+            )
+
+        return cls._cached_api_enum[cls.__name__]
+
     @classmethod
     def from_api(cls, name: str) -> typing_extensions.Self:
         for e in cls:

daras_ai_v2/language_model.py

@@ -25,6 +25,7 @@
 
 from daras_ai.image_input import gs_url_to_uri, bytes_to_cv2_img, cv2_img_to_bytes
 from daras_ai_v2.asr import get_google_auth_session
+from daras_ai_v2.custom_enum import GooeyEnum
 from daras_ai_v2.exceptions import raise_for_status, UserError
 from daras_ai_v2.gpu_server import call_celery_task
 from daras_ai_v2.text_splitter import (
@@ -72,7 +73,7 @@ class LLMSpec(typing.NamedTuple):
     supports_json: bool = False
 
 
-class LargeLanguageModels(Enum):
+class LargeLanguageModels(GooeyEnum):
     # https://platform.openai.com/docs/models/gpt-4o
     gpt_4_o = LLMSpec(
         label="GPT-4o (openai)",

recipes/BulkEval.py

@@ -186,9 +186,7 @@ class RequestModelBase(BasePage.RequestModel):
             """,
         )
 
-        selected_model: (
-            typing.Literal[tuple(e.name for e in LargeLanguageModels)] | None
-        )
+        selected_model: LargeLanguageModels.api_enum | None
 
     class RequestModel(LanguageModelSettings, RequestModelBase):
         pass

recipes/CompareLLM.py

@@ -44,17 +44,13 @@ class CompareLLMPage(BasePage):
 
     class RequestModelBase(BasePage.RequestModel):
         input_prompt: str | None
-        selected_models: list[
-            typing.Literal[tuple(e.name for e in LargeLanguageModels)]
-        ]
+        selected_models: list[LargeLanguageModels.api_enum] | None
 
     class RequestModel(LanguageModelSettings, RequestModelBase):
         pass
 
     class ResponseModel(BaseModel):
-        output_text: dict[
-            typing.Literal[tuple(e.name for e in LargeLanguageModels)], list[str]
-        ]
+        output_text: dict[LargeLanguageModels.api_choices, list[str]]
 
     def preview_image(self, state: dict) -> str | None:
         return DEFAULT_COMPARE_LM_META_IMG

recipes/DocExtract.py

@@ -105,9 +105,7 @@ class RequestModelBase(BasePage.RequestModel):
 
         task_instructions: str | None
 
-        selected_model: (
-            typing.Literal[tuple(e.name for e in LargeLanguageModels)] | None
-        )
+        selected_model: LargeLanguageModels.api_enum | None
 
     class RequestModel(LanguageModelSettings, RequestModelBase):
         pass

recipes/DocSearch.py

@@ -2,7 +2,7 @@
 import typing
 
 from furl import furl
-from pydantic import BaseModel
+from pydantic import BaseModel, Field
 
 import gooey_gui as gui
 from bots.models import Workflow
@@ -72,9 +72,7 @@ class RequestModelBase(DocSearchRequest, BasePage.RequestModel):
         task_instructions: str | None
         query_instructions: str | None
 
-        selected_model: (
-            typing.Literal[tuple(e.name for e in LargeLanguageModels)] | None
-        )
+        selected_model: LargeLanguageModels.api_enum | None
 
         citation_style: typing.Literal[tuple(e.name for e in CitationStyles)] | None
 

recipes/DocSummary.py

@@ -2,7 +2,7 @@
 from enum import Enum
 
 from daras_ai_v2.pydantic_validation import FieldHttpUrl
-from pydantic import BaseModel, Field
+from pydantic import BaseModel
 
 import gooey_gui as gui
 from bots.models import Workflow
@@ -16,7 +16,6 @@
     LargeLanguageModels,
     run_language_model,
     calc_gpt_tokens,
-    ResponseFormatType,
 )
 from daras_ai_v2.language_model_settings_widgets import (
     language_model_settings,
@@ -69,9 +68,7 @@ class RequestModelBase(BasePage.RequestModel):
         task_instructions: str | None
         merge_instructions: str | None
 
-        selected_model: (
-            typing.Literal[tuple(e.name for e in LargeLanguageModels)] | None
-        )
+        selected_model: LargeLanguageModels.api_enum | None
 
         chain_type: typing.Literal[tuple(e.name for e in CombineDocumentsChains)] | None
 

recipes/GoogleGPT.py

@@ -1,7 +1,7 @@
 import typing
 
 from furl import furl
-from pydantic import BaseModel
+from pydantic import BaseModel, Field
 
 import gooey_gui as gui
 from bots.models import Workflow
@@ -82,9 +82,7 @@ class RequestModelBase(BasePage.RequestModel):
         task_instructions: str | None
         query_instructions: str | None
 
-        selected_model: (
-            typing.Literal[tuple(e.name for e in LargeLanguageModels)] | None
-        )
+        selected_model: LargeLanguageModels.api_enum | None
 
         max_search_urls: int | None
 

recipes/SEOSummary.py

@@ -100,9 +100,7 @@ class RequestModelBase(BaseModel):
 
         enable_html: bool | None
 
-        selected_model: (
-            typing.Literal[tuple(e.name for e in LargeLanguageModels)] | None
-        )
+        selected_model: LargeLanguageModels.api_enum | None
 
         max_search_urls: int | None
 

recipes/SmartGPT.py

@@ -1,7 +1,7 @@
 import typing
 
 import jinja2.sandbox
-from pydantic import BaseModel
+from pydantic import BaseModel, Field
 
 import gooey_gui as gui
 from bots.models import Workflow
@@ -39,9 +39,7 @@ class RequestModelBase(BasePage.RequestModel):
         reflexion_prompt: str | None
         dera_prompt: str | None
 
-        selected_model: (
-            typing.Literal[tuple(e.name for e in LargeLanguageModels)] | None
-        )
+        selected_model: LargeLanguageModels.api_enum | None
 
     class RequestModel(LanguageModelSettings, RequestModelBase):
         pass

recipes/SocialLookupEmail.py

@@ -2,7 +2,7 @@
 import typing
 
 import requests
-from pydantic import BaseModel
+from pydantic import BaseModel, Field
 
 import gooey_gui as gui
 from bots.models import Workflow
@@ -55,9 +55,7 @@ class RequestModelBase(BasePage.RequestModel):
         # domain: str | None
         # key_words: str | None
 
-        selected_model: (
-            typing.Literal[tuple(e.name for e in LargeLanguageModels)] | None
-        )
+        selected_model: LargeLanguageModels.api_enum | None
 
     class RequestModel(LanguageModelSettings, RequestModelBase):
         pass

recipes/VideoBots.py

@@ -197,9 +197,7 @@ class RequestModelBase(BasePage.RequestModel):
         bot_script: str | None
 
         # llm model
-        selected_model: (
-            typing.Literal[tuple(e.name for e in LargeLanguageModels)] | None
-        )
+        selected_model: LargeLanguageModels.api_enum | None
         document_model: str | None = Field(
             title="🩻 Photo / Document Intelligence",
             description="When your copilot users upload a photo or pdf, what kind of document are they mostly likely to upload? "