🧼 isort

examples/async/expert_answer.py

@@ -1,8 +1,11 @@
-from asyncio import gather, run as _await
-from funcchain import achain, settings
-from pydantic import BaseModel
+from asyncio import gather
+from asyncio import run as _await
 from random import shuffle
 
+from pydantic import BaseModel
+
+from funcchain import achain, settings
+
 settings.temperature = 1
 settings.llm = "openai/gpt-3.5-turbo-1106"
 

examples/experiments/dynamic_model_generation.py

@@ -1,9 +1,10 @@
 from langchain.document_loaders import WebBaseLoader
-from funcchain import chain, settings
-from funcchain.parser import CodeBlock
 from pydantic import BaseModel
 from rich import print
 
+from funcchain import chain, settings
+from funcchain.parser import CodeBlock
+
 settings.llm = "gpt-4-1106-preview"
 settings.context_lenght = 4096 * 8
 

src/funcchain/_llms.py

@@ -7,14 +7,7 @@
 from langchain.callbacks.manager import CallbackManagerForLLMRun
 from langchain.chat_models.base import BaseChatModel
 from langchain.schema import ChatResult
-from langchain.schema.messages import (
-    AIMessage,
-    AIMessageChunk,
-    BaseMessage,
-    ChatMessage,
-    HumanMessage,
-    SystemMessage,
-)
+from langchain.schema.messages import AIMessage, AIMessageChunk, BaseMessage, ChatMessage, HumanMessage, SystemMessage
 from langchain.schema.output import ChatGeneration, ChatGenerationChunk
 from langchain_core.language_models import BaseLanguageModel
 from langchain_core.pydantic_v1 import Field, root_validator

src/funcchain/chain/creation.py

@@ -1,19 +1,16 @@
 from types import UnionType
 from typing import TypeVar, Union
 
-from funcchain._llms import ChatLlamaCpp
 from langchain.chat_models.base import BaseChatModel
 from langchain.prompts import ChatPromptTemplate
 from langchain.schema import AIMessage, BaseMessage, BaseOutputParser, HumanMessage
 from langchain.schema.chat_history import BaseChatMessageHistory
-from langchain.schema.runnable import (
-    RunnableSequence,
-    RunnableSerializable,
-    RunnableWithFallbacks,
-)
+from langchain.schema.runnable import RunnableSequence, RunnableSerializable, RunnableWithFallbacks
 from PIL import Image
 from pydantic import BaseModel
 
+from funcchain._llms import ChatLlamaCpp
+
 from ..parser import MultiToolParser, ParserBaseModel, PydanticFuncParser
 from ..settings import FuncchainSettings
 from ..streaming import stream_handler
@@ -24,17 +21,13 @@
     is_function_model,
     is_vision_model,
     kwargs_from_parent,
-    univeral_model_selector,
     multi_pydantic_to_functions,
     parser_for,
     pydantic_to_functions,
     pydantic_to_grammar,
+    univeral_model_selector,
 )
-from .prompt import (
-    HumanImageMessagePromptTemplate,
-    create_chat_prompt,
-    create_instruction_prompt,
-)
+from .prompt import HumanImageMessagePromptTemplate, create_chat_prompt, create_instruction_prompt
 
 ChainOutput = TypeVar("ChainOutput")
 
@@ -261,7 +254,7 @@ def _gather_llm(
         llm = settings.llm
     else:
         llm = univeral_model_selector(settings)
-    
+
     if not llm:
         raise RuntimeError(
             "No language model provided. Either set the llm environment variable or "

src/funcchain/chain/interface.py

@@ -4,8 +4,8 @@
 from langchain.schema import BaseMessage, BaseOutputParser
 from langchain.schema.chat_history import BaseChatMessageHistory
 
-from .invoke import ainvoke, invoke
 from ..settings import SettingsOverride, get_settings
+from .invoke import ainvoke, invoke
 
 ChainOutput = TypeVar("ChainOutput")
 

src/funcchain/chain/invoke.py

@@ -4,8 +4,8 @@
 from langchain.schema import BaseMessage, BaseOutputParser
 from langchain.schema.chat_history import BaseChatMessageHistory
 
-from ..utils.decorators import get_parent_frame, log_openai_callback, retry_parse
 from ..settings import FuncchainSettings
+from ..utils.decorators import get_parent_frame, log_openai_callback, retry_parse
 from .creation import create_chain
 
 T = TypeVar("T")

src/funcchain/chain/prompt.py

@@ -1,16 +1,13 @@
 from string import Formatter
-from typing import Any, Type, Optional
+from typing import Any, Optional, Type
 
-from PIL import Image
-from pydantic import BaseModel
 from langchain.prompts import ChatPromptTemplate
-from langchain.prompts.chat import (
-    BaseStringMessagePromptTemplate,
-    MessagePromptTemplateT,
-)
+from langchain.prompts.chat import BaseStringMessagePromptTemplate, MessagePromptTemplateT
 from langchain.prompts.prompt import PromptTemplate
 from langchain.schema import BaseMessage, HumanMessage, SystemMessage
 from langchain.schema.chat_history import BaseChatMessageHistory
+from PIL import Image
+from pydantic import BaseModel
 
 from ..utils import image_to_base64_url
 

src/funcchain/parser.py

@@ -3,12 +3,7 @@
 import re
 from typing import Callable, Optional, Type, TypeVar
 
-from langchain.schema import (
-    AIMessage,
-    ChatGeneration,
-    Generation,
-    OutputParserException,
-)
+from langchain.schema import AIMessage, ChatGeneration, Generation, OutputParserException
 from langchain.schema.output_parser import BaseGenerationOutputParser, BaseOutputParser
 from pydantic import BaseModel, ValidationError
 

src/funcchain/settings.py

@@ -8,8 +8,8 @@
 from langchain.chat_models.base import BaseChatModel
 from langchain.globals import set_llm_cache
 from langchain.schema.runnable import RunnableWithFallbacks
-from pydantic_settings import BaseSettings
 from pydantic import Field
+from pydantic_settings import BaseSettings
 
 set_llm_cache(InMemoryCache())
 

src/funcchain/streaming.py

@@ -86,6 +86,7 @@ def stream_to(
         ...     # your chain calls here
     """
     import builtins
+
     import rich
 
     if (fn is builtins.print or fn is rich.print) and kwargs == {}:

src/funcchain/utils/__init__.py

@@ -1,9 +1,7 @@
 from .decorators import *  # noqa: F401, F403
 from .function_frame import *  # noqa: F401, F403
+from .grammars import pydantic_to_grammar  # noqa: F401, F403
+from .grammars import schema_to_grammar  # noqa: F401, F403
 from .helpers import *  # noqa: F401, F403
 from .image import *  # noqa: F401, F403
 from .model_defaults import *  # noqa: F401, F403
-from .grammars import (
-    schema_to_grammar,  # noqa: F401, F403
-    pydantic_to_grammar,  # noqa: F401, F403
-)

src/funcchain/utils/decorators.py

@@ -11,8 +11,8 @@
 from langchain.schema.output_parser import OutputParserException
 from rich import print
 
-from ..settings import FuncchainSettings
 from ..exceptions import ParsingRetryException
+from ..settings import FuncchainSettings
 from .function_frame import get_parent_frame
 
 

src/funcchain/utils/function_frame.py

@@ -6,7 +6,6 @@
 
 from ..parser import BoolOutputParser, ParserBaseModel, PydanticOutputParser
 
-
 FUNC_DEPTH = 8
 
 

src/funcchain/utils/grammars.py

@@ -1,6 +1,7 @@
 import json
 import re
 from typing import Type
+
 from pydantic import BaseModel
 
 SPACE_RULE = '" "?'

src/funcchain/utils/model_defaults.py

@@ -1,16 +1,11 @@
+from pathlib import Path
 from typing import Any
 
-from pathlib import Path
-from langchain.chat_models import (
-    AzureChatOpenAI,
-    ChatAnthropic,
-    ChatGooglePalm,
-    ChatOpenAI,
-)
+from langchain.chat_models import AzureChatOpenAI, ChatAnthropic, ChatGooglePalm, ChatOpenAI
 from langchain.chat_models.base import BaseChatModel
 
-from ..settings import FuncchainSettings
 from .._llms import ChatLlamaCpp
+from ..settings import FuncchainSettings
 
 
 def get_gguf_model(

tests/async_test.py

@@ -1,8 +1,11 @@
-from asyncio import gather, run as _await
-from funcchain import achain, settings
-from pydantic import BaseModel
+from asyncio import gather
+from asyncio import run as _await
 from random import shuffle
 
+from pydantic import BaseModel
+
+from funcchain import achain, settings
+
 settings.temperature = 1
 settings.llm = "openai/gpt-3.5-turbo-1106"
 

tests/llamacpp_test.py

@@ -1,7 +1,8 @@
 import pytest
-from funcchain import chain, settings
 from pydantic import BaseModel
 
+from funcchain import chain, settings
+
 
 class Task(BaseModel):
     description: str

tests/openai_test.py

@@ -1,6 +1,7 @@
-from funcchain import chain, settings
 from pydantic import BaseModel, Field
 
+from funcchain import chain, settings
+
 
 class Task(BaseModel):
     name: str