.github/workflows/test.yml

@@ -25,7 +25,6 @@ jobs:
     strategy:
       matrix:
         python-version:
-          - "3.8"
           - "3.9"
           - "3.10"
           - "3.11"
@@ -43,10 +42,3 @@ jobs:
       - name: Run unit tests
         run: |
           poetry run poe test
-
-  pydantic-compatibility:
-    uses:
-      ./.github/workflows/_pydantic_compatibility.yml
-    with:
-      working-directory: .
-    secrets: inherit

README.md

@@ -5,6 +5,15 @@
 [![Open Issues](https://img.shields.io/github/issues-raw/eyurtsev/kor)](https://github.com/eyurtsev/kor/issues)
 [![](https://dcbadge.vercel.app/api/server/6adMQxSpJS?compact=true&style=flat)](https://discord.com/channels/1038097195422978059/1170024642245832774)
 
+> [!WARNING]
+> If you're using a chat model that supports a tool calling API, you should probably be using the chat models' tool calling API instead of Kor!
+>
+> Kor is best suited for old style LLMs that did not have a chat interface and did not support tool calling.
+> 
+> Read the [tool calling guide](https://python.langchain.com/docs/concepts/tool_calling/) in LangChain for more details.
+>
+> Please refer to the [chat model integration table](https://python.langchain.com/docs/integrations/chat/#featured-providers) for a list of chat models that support native tool calling.
+
 
 # Kor
 

kor/extraction/parser.py

@@ -3,7 +3,7 @@
 from typing import List, Optional
 
 from langchain_core.output_parsers import BaseOutputParser
-from pydantic import Extra
+from pydantic import ConfigDict
 
 from kor.encoders import Encoder
 from kor.exceptions import ParseError
@@ -22,6 +22,7 @@ class KorParser(BaseOutputParser[Extraction]):
     encoder: Encoder
     schema_: Object
     validator: Optional[Validator] = None
+    model_config = ConfigDict(arbitrary_types_allowed=True)
 
     @property
     def _type(self) -> str:
@@ -66,8 +67,7 @@ def parse(self, text: str) -> Extraction:
             "validated_data": validated_data,
         }
 
-    class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(
+        extra="forbid",
+        arbitrary_types_allowed=True,
+    )

kor/prompts.py

@@ -6,6 +6,7 @@
 from langchain_core.messages import AIMessage, BaseMessage, HumanMessage, SystemMessage
 from langchain_core.prompt_values import PromptValue
 from langchain_core.prompts import BasePromptTemplate, PromptTemplate
+from pydantic import ConfigDict
 
 from kor.encoders import Encoder
 from kor.encoders.encode import InputFormatter, encode_examples, format_text
@@ -14,12 +15,6 @@
 from kor.nodes import Object
 from kor.type_descriptors import TypeDescriptor
 
-try:
-    # Use pydantic v1 namespace since working with langchain
-    from pydantic.v1 import Extra  # type: ignore[assignment]
-except ImportError:
-    from pydantic import Extra  # type: ignore[assignment]
-
 from .validators import Validator
 
 DEFAULT_INSTRUCTION_TEMPLATE = PromptTemplate(
@@ -41,11 +36,10 @@ class ExtractionPromptValue(PromptValue):
     string: str
     messages: List[BaseMessage]
 
-    class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(
+        extra="forbid",
+        arbitrary_types_allowed=True,
+    )
 
     def to_string(self) -> str:
         """Format the prompt to a string."""
@@ -65,11 +59,10 @@ class ExtractionPromptTemplate(BasePromptTemplate):
     input_formatter: InputFormatter
     instruction_template: PromptTemplate
 
-    class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(
+        extra="forbid",
+        arbitrary_types_allowed=True,
+    )
 
     def format_prompt(  # type: ignore[override]
         self,