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chore: correct langchain-community references (#33827)

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fix docstrings that referenced community versions of now-native packages
This commit is contained in:
Mason Daugherty
2025-11-04 17:01:35 -05:00
committed by GitHub
parent 915c446c48
commit ee0bdaeb79
35 changed files with 51 additions and 49 deletions
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6
SECURITY.md
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@@ -55,10 +55,10 @@ All out of scope targets defined by huntr as well as:
* **langchain-experimental**: This repository is for experimental code and is not
eligible for bug bounties (see [package warning](https://pypi.org/project/langchain-experimental/)), bug reports to it will be marked as interesting or waste of
time and published with no bounty attached.
* **tools**: Tools in either langchain or langchain-community are not eligible for bug
* **tools**: Tools in either `langchain` or `langchain-community` are not eligible for bug
bounties. This includes the following directories
* libs/langchain/langchain/tools
* libs/community/langchain_community/tools
* `libs/langchain/langchain/tools`
* `libs/community/langchain_community/tools`
* Please review the [Best Practices](#best-practices)
for more details, but generally tools interact with the real world. Developers are
expected to understand the security implications of their code and are responsible

4
libs/core/langchain_core/runnables/base.py
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@@ -774,7 +774,7 @@ class Runnable(ABC, Generic[Input, Output]):
"""Assigns new fields to the `dict` output of this `Runnable`.
```python
from langchain_community.llms.fake import FakeStreamingListLLM
from langchain_core.language_models.fake import FakeStreamingListLLM
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import SystemMessagePromptTemplate
from langchain_core.runnables import Runnable
@@ -5766,7 +5766,7 @@ class RunnableBinding(RunnableBindingBase[Input, Output]): # type: ignore[no-re
```python
# Create a Runnable binding that invokes the chat model with the
# additional kwarg `stop=['-']` when running it.
from langchain_community.chat_models import ChatOpenAI
from langchain_openai import ChatOpenAI
model = ChatOpenAI()
model.invoke('Say "Parrot-MAGIC"', stop=["-"]) # Should return `Parrot`

2
libs/core/langchain_core/runnables/history.py
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@@ -122,7 +122,7 @@ class RunnableWithMessageHistory(RunnableBindingBase): # type: ignore[no-redef]
```python
from typing import Optional
from langchain_community.chat_models import ChatAnthropic
from langchain_anthropic import ChatAnthropic
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
from langchain_core.runnables.history import RunnableWithMessageHistory

16
libs/langchain/langchain_classic/_api/module_import.py
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@@ -26,7 +26,7 @@ def create_importer(
imports to new imports.
The function will raise deprecation warning on loops using
deprecated_lookups or fallback_module.
`deprecated_lookups` or `fallback_module`.
Module lookups will import without deprecation warnings (used to speed
up imports from large namespaces like llms or chat models).
@@ -37,18 +37,20 @@ def create_importer(
loss of type information, IDE support for going to definition etc).
Args:
package: current package. Use __package__
module_lookup: maps name of object to the module where it is defined.
package: Current package. Use `__package__`
module_lookup: Maps name of object to the module where it is defined.
e.g.,
```json
{
"MyDocumentLoader": (
"langchain_community.document_loaders.my_document_loader"
)
}
deprecated_lookups: same as module look up, but will raise
```
deprecated_lookups: Same as module look up, but will raise
deprecation warnings.
fallback_module: module to import from if the object is not found in
module_lookup or if module_lookup is not provided.
fallback_module: Module to import from if the object is not found in
`module_lookup` or if `module_lookup` is not provided.
Returns:
A function that imports objects from the specified modules.
@@ -56,7 +58,7 @@ def create_importer(
all_module_lookup = {**(deprecated_lookups or {}), **(module_lookup or {})}
def import_by_name(name: str) -> Any:
"""Import stores from langchain_community."""
"""Import stores from `langchain_community`."""
# If not in interactive env, raise warning.
if all_module_lookup and name in all_module_lookup:
new_module = all_module_lookup[name]

2
libs/langchain/langchain_classic/agents/json_chat/base.py
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@@ -50,7 +50,7 @@ def create_json_chat_agent(
Example:
```python
from langchain_classic import hub
from langchain_community.chat_models import ChatOpenAI
from langchain_openai import ChatOpenAI
from langchain_classic.agents import AgentExecutor, create_json_chat_agent
prompt = hub.pull("hwchase17/react-chat-json")

2
libs/langchain/langchain_classic/agents/openai_functions_agent/base.py
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@@ -310,7 +310,7 @@ def create_openai_functions_agent(
Creating an agent with no memory
```python
from langchain_community.chat_models import ChatOpenAI
from langchain_openai import ChatOpenAI
from langchain_classic.agents import (
AgentExecutor,
create_openai_functions_agent,

2
libs/langchain/langchain_classic/agents/openai_tools/base.py
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@@ -40,7 +40,7 @@ def create_openai_tools_agent(
Example:
```python
from langchain_classic import hub
from langchain_community.chat_models import ChatOpenAI
from langchain_openai import ChatOpenAI
from langchain_classic.agents import (
AgentExecutor,
create_openai_tools_agent,

2
libs/langchain/langchain_classic/agents/react/agent.py
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@@ -59,7 +59,7 @@ def create_react_agent(
Examples:
```python
from langchain_classic import hub
from langchain_community.llms import OpenAI
from langchain_openai import OpenAI
from langchain_classic.agents import AgentExecutor, create_react_agent
prompt = hub.pull("hwchase17/react")

2
libs/langchain/langchain_classic/agents/self_ask_with_search/base.py
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@@ -116,7 +116,7 @@ def create_self_ask_with_search_agent(
Examples:
```python
from langchain_classic import hub
from langchain_community.chat_models import ChatAnthropic
from langchain_anthropic import ChatAnthropic
from langchain_classic.agents import (
AgentExecutor,
create_self_ask_with_search_agent,

2
libs/langchain/langchain_classic/agents/structured_chat/base.py
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@@ -195,7 +195,7 @@ def create_structured_chat_agent(
Examples:
```python
from langchain_classic import hub
from langchain_community.chat_models import ChatOpenAI
from langchain_openai import ChatOpenAI
from langchain_classic.agents import (
AgentExecutor,
create_structured_chat_agent,

2
libs/langchain/langchain_classic/agents/xml/base.py
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@@ -146,7 +146,7 @@ def create_xml_agent(
Example:
```python
from langchain_classic import hub
from langchain_community.chat_models import ChatAnthropic
from langchain_anthropic import ChatAnthropic
from langchain_classic.agents import AgentExecutor, create_xml_agent
prompt = hub.pull("hwchase17/xml-agent-convo")

2
libs/langchain/langchain_classic/chains/combine_documents/map_reduce.py
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@@ -44,7 +44,7 @@ class MapReduceDocumentsChain(BaseCombineDocumentsChain):
MapReduceDocumentsChain,
)
from langchain_core.prompts import PromptTemplate
from langchain_community.llms import OpenAI
from langchain_openai import OpenAI
# This controls how each document will be formatted. Specifically,
# it will be passed to `format_document` - see that function for more

2
libs/langchain/langchain_classic/chains/combine_documents/map_rerank.py
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@@ -38,7 +38,7 @@ class MapRerankDocumentsChain(BaseCombineDocumentsChain):
```python
from langchain_classic.chains import MapRerankDocumentsChain, LLMChain
from langchain_core.prompts import PromptTemplate
from langchain_community.llms import OpenAI
from langchain_openai import OpenAI
from langchain_classic.output_parsers.regex import RegexParser
document_variable_name = "context"

2
libs/langchain/langchain_classic/chains/combine_documents/reduce.py
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@@ -163,7 +163,7 @@ class ReduceDocumentsChain(BaseCombineDocumentsChain):
ReduceDocumentsChain,
)
from langchain_core.prompts import PromptTemplate
from langchain_community.llms import OpenAI
from langchain_openai import OpenAI
# This controls how each document will be formatted. Specifically,
# it will be passed to `format_document` - see that function for more

2
libs/langchain/langchain_classic/chains/combine_documents/refine.py
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@@ -46,7 +46,7 @@ class RefineDocumentsChain(BaseCombineDocumentsChain):
```python
from langchain_classic.chains import RefineDocumentsChain, LLMChain
from langchain_core.prompts import PromptTemplate
from langchain_community.llms import OpenAI
from langchain_openai import OpenAI
# This controls how each document will be formatted. Specifically,
# it will be passed to `format_document` - see that function for more

6
libs/langchain/langchain_classic/chains/combine_documents/stuff.py
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@@ -56,9 +56,9 @@ def create_stuff_documents_chain(
Example:
```python
# pip install -U langchain langchain-community
# pip install -U langchain langchain-openai
from langchain_community.chat_models import ChatOpenAI
from langchain_openai import ChatOpenAI
from langchain_core.documents import Document
from langchain_core.prompts import ChatPromptTemplate
from langchain_classic.chains.combine_documents import (
@@ -123,7 +123,7 @@ class StuffDocumentsChain(BaseCombineDocumentsChain):
```python
from langchain_classic.chains import StuffDocumentsChain, LLMChain
from langchain_core.prompts import PromptTemplate
from langchain_community.llms import OpenAI
from langchain_openai import OpenAI
# This controls how each document will be formatted. Specifically,
# it will be passed to `format_document` - see that function for more

2
libs/langchain/langchain_classic/chains/constitutional_ai/base.py
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@@ -165,7 +165,7 @@ class ConstitutionalChain(Chain):
Example:
```python
from langchain_community.llms import OpenAI
from langchain_openai import OpenAI
from langchain_classic.chains import LLMChain, ConstitutionalChain
from langchain_classic.chains.constitutional_ai.models \
import ConstitutionalPrinciple

2
libs/langchain/langchain_classic/chains/conversation/base.py
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@@ -97,7 +97,7 @@ class ConversationChain(LLMChain):
Example:
```python
from langchain_classic.chains import ConversationChain
from langchain_community.llms import OpenAI
from langchain_openai import OpenAI
conversation = ConversationChain(llm=OpenAI())
```

2
libs/langchain/langchain_classic/chains/conversational_retrieval/base.py
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@@ -357,7 +357,7 @@ class ConversationalRetrievalChain(BaseConversationalRetrievalChain):
ConversationalRetrievalChain,
)
from langchain_core.prompts import PromptTemplate
from langchain_community.llms import OpenAI
from langchain_openai import OpenAI
combine_docs_chain = StuffDocumentsChain(...)
vectorstore = ...

2
libs/langchain/langchain_classic/chains/elasticsearch_database/base.py
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@@ -31,7 +31,7 @@ class ElasticsearchDatabaseChain(Chain):
Example:
```python
from langchain_classic.chains import ElasticsearchDatabaseChain
from langchain_community.llms import OpenAI
from langchain_openai import OpenAI
from elasticsearch import Elasticsearch
database = Elasticsearch("http://localhost:9200")

2
libs/langchain/langchain_classic/chains/history_aware_retriever.py
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@@ -33,7 +33,7 @@ def create_history_aware_retriever(
```python
# pip install -U langchain langchain-community
from langchain_community.chat_models import ChatOpenAI
from langchain_openai import ChatOpenAI
from langchain_classic.chains import create_history_aware_retriever
from langchain_classic import hub

2
libs/langchain/langchain_classic/chains/llm.py
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@@ -64,7 +64,7 @@ class LLMChain(Chain):
Example:
```python
from langchain_classic.chains import LLMChain
from langchain_community.llms import OpenAI
from langchain_openai import OpenAI
from langchain_core.prompts import PromptTemplate
prompt_template = "Tell me a {adjective} joke"

2
libs/langchain/langchain_classic/chains/llm_checker/base.py
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@@ -77,7 +77,7 @@ class LLMCheckerChain(Chain):
Example:
```python
from langchain_community.llms import OpenAI
from langchain_openai import OpenAI
from langchain_classic.chains import LLMCheckerChain
model = OpenAI(temperature=0.7)

2
libs/langchain/langchain_classic/chains/llm_math/base.py
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@@ -145,7 +145,7 @@ class LLMMathChain(Chain):
Example:
```python
from langchain_classic.chains import LLMMathChain
from langchain_community.llms import OpenAI
from langchain_openai import OpenAI
llm_math = LLMMathChain.from_llm(OpenAI())
```

2
libs/langchain/langchain_classic/chains/llm_summarization_checker/base.py
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@@ -80,7 +80,7 @@ class LLMSummarizationCheckerChain(Chain):
Example:
```python
from langchain_community.llms import OpenAI
from langchain_openai import OpenAI
from langchain_classic.chains import LLMSummarizationCheckerChain
model = OpenAI(temperature=0.0)

4
libs/langchain/langchain_classic/chains/openai_functions/base.py
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@@ -85,7 +85,7 @@ def create_openai_fn_chain(
from typing import Optional
from langchain_classic.chains.openai_functions import create_openai_fn_chain
from langchain_community.chat_models import ChatOpenAI
from langchain_openai import ChatOpenAI
from langchain_core.prompts import ChatPromptTemplate
from pydantic import BaseModel, Field
@@ -179,7 +179,7 @@ def create_structured_output_chain(
from typing import Optional
from langchain_classic.chains.openai_functions import create_structured_output_chain
from langchain_community.chat_models import ChatOpenAI
from langchain_openai import ChatOpenAI
from langchain_core.prompts import ChatPromptTemplate
from pydantic import BaseModel, Field

4
libs/langchain/langchain_classic/chains/retrieval.py
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@@ -36,9 +36,9 @@ def create_retrieval_chain(
Example:
```python
# pip install -U langchain langchain-community
# pip install -U langchain langchain-openai
from langchain_community.chat_models import ChatOpenAI
from langchain_openai import ChatOpenAI
from langchain_classic.chains.combine_documents import (
create_stuff_documents_chain,
)

2
libs/langchain/langchain_classic/chains/retrieval_qa/base.py
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@@ -259,7 +259,7 @@ class RetrievalQA(BaseRetrievalQA):
Example:
```python
from langchain_community.llms import OpenAI
from langchain_openai import OpenAI
from langchain_classic.chains import RetrievalQA
from langchain_community.vectorstores import FAISS
from langchain_core.vectorstores import VectorStoreRetriever

2
libs/langchain/langchain_classic/embeddings/cache.py
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@@ -122,7 +122,7 @@ class CacheBackedEmbeddings(Embeddings):
```python
from langchain_classic.embeddings import CacheBackedEmbeddings
from langchain_classic.storage import LocalFileStore
from langchain_community.embeddings import OpenAIEmbeddings
from langchain_openai import OpenAIEmbeddings
store = LocalFileStore("./my_cache")

2
libs/langchain/langchain_classic/evaluation/agents/trajectory_eval_chain.py
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@@ -104,7 +104,7 @@ class TrajectoryEvalChain(AgentTrajectoryEvaluator, LLMEvalChain):
Example:
```python
from langchain_classic.agents import AgentType, initialize_agent
from langchain_community.chat_models import ChatOpenAI
from langchain_openai import ChatOpenAI
from langchain_classic.evaluation import TrajectoryEvalChain
from langchain_classic.tools import tool

2
libs/langchain/langchain_classic/evaluation/comparison/__init__.py
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@@ -6,7 +6,7 @@ preferences, measuring similarity / semantic equivalence between outputs,
or any other comparison task.
Example:
>>> from langchain_community.chat_models import ChatOpenAI
>>> from langchain_openai import ChatOpenAI
>>> from langchain_classic.evaluation.comparison import PairwiseStringEvalChain
>>> llm = ChatOpenAI(temperature=0)
>>> chain = PairwiseStringEvalChain.from_llm(llm=llm)

2
libs/langchain/langchain_classic/evaluation/comparison/eval_chain.py
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@@ -163,7 +163,7 @@ class PairwiseStringEvalChain(PairwiseStringEvaluator, LLMEvalChain, LLMChain):
output_parser (BaseOutputParser): The output parser for the chain.
Example:
>>> from langchain_community.chat_models import ChatOpenAI
>>> from langchain_openai import ChatOpenAI
>>> from langchain_classic.evaluation.comparison import PairwiseStringEvalChain
>>> model = ChatOpenAI(
... temperature=0, model_name="gpt-4", model_kwargs={"random_seed": 42}

4
libs/langchain/langchain_classic/evaluation/criteria/__init__.py
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@@ -12,7 +12,7 @@ chain against specified criteria.
Examples:
--------
Using a predefined criterion:
>>> from langchain_community.llms import OpenAI
>>> from langchain_openai import OpenAI
>>> from langchain_classic.evaluation.criteria import CriteriaEvalChain
>>> model = OpenAI()
@@ -26,7 +26,7 @@ Using a predefined criterion:
Using a custom criterion:
>>> from langchain_community.llms import OpenAI
>>> from langchain_openai import OpenAI
>>> from langchain_classic.evaluation.criteria import LabeledCriteriaEvalChain
>>> model = OpenAI()

2
libs/langchain/langchain_classic/evaluation/scoring/__init__.py
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@@ -5,7 +5,7 @@ be they LLMs, Chains, or otherwise. This can be based on a variety of
criteria and or a reference answer.
Example:
>>> from langchain_community.chat_models import ChatOpenAI
>>> from langchain_openai import ChatOpenAI
>>> from langchain_classic.evaluation.scoring import ScoreStringEvalChain
>>> model = ChatOpenAI(temperature=0, model_name="gpt-4")
>>> chain = ScoreStringEvalChain.from_llm(llm=model)

2
libs/langchain/langchain_classic/evaluation/scoring/eval_chain.py
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@@ -154,7 +154,7 @@ class ScoreStringEvalChain(StringEvaluator, LLMEvalChain, LLMChain):
output_parser (BaseOutputParser): The output parser for the chain.
Example:
>>> from langchain_community.chat_models import ChatOpenAI
>>> from langchain_openai import ChatOpenAI
>>> from langchain_classic.evaluation.scoring import ScoreStringEvalChain
>>> model = ChatOpenAI(temperature=0, model_name="gpt-4")
>>> chain = ScoreStringEvalChain.from_llm(llm=model)