upgrade to newest langchain (#257)

Co-authored-by: Chaim Turkel <[email protected]>
Co-authored-by: Eugene Yurtsev <[email protected]>

.gitignore

@@ -128,3 +128,5 @@ dmypy.json
 
 # Pyre type checker
 .pyre/
+
+.DS_Store

README.md

@@ -102,7 +102,7 @@ schema = Object(
 )
 
 chain = create_extraction_chain(llm, schema, encoder_or_encoder_class='json')
-chain.run("play songs by paul simon and led zeppelin and the doors")['data']
+chain.invoke("play songs by paul simon and led zeppelin and the doors")['data']
 ```
 
 ```python
@@ -150,7 +150,7 @@ schema, validator = from_pydantic(MusicRequest)
 chain = create_extraction_chain(
     llm, schema, encoder_or_encoder_class="json", validator=validator
 )
-chain.run("stop the music now")["validated_data"]
+chain.invoke("stop the music now")["validated_data"]
 ```
 
 ```python

docs/source/index.md

@@ -72,7 +72,7 @@ schema = Object(
 )
 
 chain = create_extraction_chain(llm, schema, encoder_or_encoder_class='json')
-chain.run("play songs by paul simon and led zeppelin and the doors")['data']
+chain.invoke("play songs by paul simon and led zeppelin and the doors")['data']
 ```
 
 ```python
@@ -116,7 +116,7 @@ schema, validator = from_pydantic(MusicRequest)
 chain = create_extraction_chain(
     llm, schema, encoder_or_encoder_class="json", validator=validator
 )
-chain.run("stop the music now")["validated_data"]
+chain.invoke("stop the music now")["validated_data"]
 ```
 
 ```python

kor/extraction/api.py

@@ -2,9 +2,9 @@
 import asyncio
 from typing import Any, Callable, List, Optional, Sequence, Type, Union, cast
 
-from langchain import PromptTemplate
 from langchain.chains import LLMChain
 from langchain.docstore.document import Document
+from langchain.prompts import PromptTemplate
 
 from kor.extraction.parser import KorParser
 

kor/prompts.py

@@ -3,8 +3,7 @@
 
 from typing import Any, List, Optional, Tuple
 
-from langchain import BasePromptTemplate
-from langchain.prompts import PromptTemplate
+from langchain.prompts import BasePromptTemplate, PromptTemplate
 from langchain.schema import (
     AIMessage,
     BaseMessage,

pyproject.toml

@@ -9,7 +9,7 @@ repository = "https://www.github.com/eyurtsev/kor"
 
 [tool.poetry.dependencies]
 python = "^3.8.1"
-langchain = ">=0.0.205"
+langchain = ">=0.1.4"
 pandas = "^1.5.3"
 markdownify = {version = "^0.11.6", optional = false}
 pydantic = "<3"
@@ -23,6 +23,7 @@ black = { version="^23.1.0", extras=["jupyter"] }
 poethepoet = "^0.18.1"
 ruff = "^0.0.255"
 pytest-cov = "^4.0.0"
+langchain-openai = "^0.0.5"
 
 [tool.poetry.group.docs.dependencies]
 nbsphinx = "^0.8.9"

tests/extraction/test_extraction_with_chain.py

@@ -3,8 +3,8 @@
 
 import langchain
 import pytest
-from langchain import PromptTemplate
 from langchain.chains import LLMChain
+from langchain.prompts import PromptTemplate
 
 from kor.encoders import CSVEncoder, JSONEncoder
 from kor.extraction import create_extraction_chain
@@ -42,7 +42,7 @@ def test_create_extraction_chain(options: Mapping[str, Any]) -> None:
         chain = create_extraction_chain(chat_model, schema, **options)
         assert isinstance(chain, LLMChain)
         # Try to run through predict and parse
-        chain.run("some string")
+        chain.invoke("some string")  # type: ignore
 
 
 @pytest.mark.parametrize(
@@ -62,7 +62,7 @@ def test_create_extraction_chain_with_csv_encoder(options: Mapping[str, Any]) ->
     chain = create_extraction_chain(chat_model, **options)
     assert isinstance(chain, LLMChain)
     # Try to run through predict and parse
-    chain.run("some string")
+    chain.invoke("some string")  # type: ignore
 
 
 MANY_TEXT_SCHEMA = Text(

tests/integration/extraction_with_chain.py

@@ -1,4 +1,4 @@
-from langchain.chat_models import ChatOpenAI
+from langchain_openai.chat_models import ChatOpenAI
 from pydantic import BaseModel, Field
 
 from kor.adapters import from_pydantic
@@ -26,7 +26,7 @@ class Person(BaseModel):
     )
 
     chain = create_extraction_chain(llm, schema)
-    result = chain.run("My name is Bobby. My brother's name Joe.")  # type: ignore
+    result = chain.invoke("My name is Bobby. My brother's name Joe.")  # type: ignore
     data = result["data"]  # type: ignore
 
     assert "person" in data  # type: ignore