langchain to langchain_community

playground/demos/langchain_example/langchain_example.py

@@ -1,7 +1,7 @@
 import os
 from dotenv import load_dotenv
 from swarms import Agent
-from langchain.llms import OpenAIChat
+from langchain_communityllms import OpenAIChat
 
 # Loading environment variables from .env file
 load_dotenv()

playground/memory/qdrant/usage_example.py

@@ -1,4 +1,4 @@
-from langchain.document_loaders import CSVLoader
+from langchain_communitydocument_loaders import CSVLoader
 from swarms.memory import qdrant
 
 loader = CSVLoader(

playground/structs/debate_example.py

@@ -2,10 +2,10 @@ from typing import Callable, List
 
 import numpy as np
 import tenacity
-from langchain.chat_models import ChatOpenAI
-from langchain.output_parsers import RegexParser
-from langchain.prompts import PromptTemplate
-from langchain.schema import (
+from langchain_communitychat_models import ChatOpenAI
+from langchain_communityoutput_parsers import RegexParser
+from langchain_communityprompts import PromptTemplate
+from langchain_communityschema import (
     HumanMessage,
     SystemMessage,
 )

pyproject.toml

@@ -32,6 +32,7 @@ asyncio = "3.4.3"
 einops = "0.7.0"
 google-generativeai = "0.3.1"
 langchain-experimental = "0.0.10"
+langchain-community = "0.0.20"
 tensorflow = "*"
 weaviate-client = "3.25.3"
 opencv-python-headless = "4.8.1.78"

requirements.txt

@@ -3,6 +3,7 @@ transformers
 pandas==1.5.3
 langchain==0.0.333
 langchain-experimental==0.0.10
+langchain-community==0.0.20
 httpx==0.24.1
 Pillow==9.4.0
 faiss-cpu==1.7.4

swarms/agents/omni_modal_agent.py

@@ -1,4 +1,4 @@
-from langchain.base_language import BaseLanguageModel
+from langchain_communitybase_language import BaseLanguageModel
 from langchain_experimental.autonomous_agents.hugginggpt.repsonse_generator import (
     load_response_generator,
 )

swarms/agents/worker_agent.py

@@ -2,9 +2,9 @@ import os
 from typing import Any, List
 
 import faiss
-from langchain.docstore import InMemoryDocstore
-from langchain.embeddings import OpenAIEmbeddings
-from langchain.vectorstores import FAISS
+from langchain_communitydocstore import InMemoryDocstore
+from langchain_communityembeddings import OpenAIEmbeddings
+from langchain_communityvectorstores import FAISS
 from langchain_experimental.autonomous_agents import AutoGPT
 
 from swarms.utils.decorators import error_decorator, timing_decorator

swarms/models/anthropic.py

@@ -19,16 +19,16 @@ from typing import (
     Union,
 )
 
-from langchain.callbacks.manager import (
+from langchain_communitycallbacks.manager import (
     AsyncCallbackManagerForLLMRun,
     CallbackManagerForLLMRun,
 )
-from langchain.llms.base import LLM
+from langchain_communityllms.base import LLM
 from pydantic import Field, SecretStr, root_validator
-from langchain.schema.language_model import BaseLanguageModel
-from langchain.schema.output import GenerationChunk
-from langchain.schema.prompt import PromptValue
-from langchain.utils import (
+from langchain_communityschema.language_model import BaseLanguageModel
+from langchain_communityschema.output import GenerationChunk
+from langchain_communityschema.prompt import PromptValue
+from langchain_communityutils import (
     get_from_dict_or_env,
 )
 from packaging.version import parse
@@ -360,7 +360,7 @@ class Anthropic(LLM, _AnthropicCommon):
         .. code-block:: python
 
             import anthropic
-            from langchain.llms import Anthropic
+            from langchain_communityllms import Anthropic
 
             model = Anthropic(model="<model_name>", anthropic_api_key="my-api-key")
 
@@ -386,7 +386,7 @@ class Anthropic(LLM, _AnthropicCommon):
         """Raise warning that this class is deprecated."""
         warnings.warn(
             "This Anthropic LLM is deprecated. Please use `from"
-            " langchain.chat_models import ChatAnthropic` instead"
+            " langchain_communitychat_models import ChatAnthropic` instead"
         )
         return values
 

swarms/models/cohere_chat.py

@@ -9,15 +9,15 @@ from tenacity import (
     wait_exponential,
 )
 
-from langchain.callbacks.manager import (
+from langchain_communitycallbacks.manager import (
     AsyncCallbackManagerForLLMRun,
     CallbackManagerForLLMRun,
 )
-from langchain.llms.base import LLM
-from langchain.llms.utils import enforce_stop_tokens
-from langchain.load.serializable import Serializable
+from langchain_communityllms.base import LLM
+from langchain_communityllms.utils import enforce_stop_tokens
+from langchain_communityload.serializable import Serializable
 from pydantic import Extra, Field, root_validator
-from langchain.utils import get_from_dict_or_env
+from langchain_communityutils import get_from_dict_or_env
 
 logger = logging.getLogger(__name__)
 
@@ -119,7 +119,7 @@ class Cohere(LLM, BaseCohere):
     Example:
         .. code-block:: python
 
-            from langchain.llms import Cohere
+            from langchain_communityllms import Cohere
 
             cohere = Cohere(model="gptd-instruct-tft", cohere_api_key="my-api-key")
     """

swarms/models/eleven_labs.py

@@ -2,7 +2,7 @@ import tempfile
 from enum import Enum
 from typing import Any, Dict, Union
 
-from langchain.utils import get_from_dict_or_env
+from langchain_communityutils import get_from_dict_or_env
 from pydantic import root_validator
 
 from swarms.tools.tool import BaseTool

swarms/models/openai_embeddings.py

@@ -155,7 +155,7 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
     Example:
         .. code-block:: python
 
-            from langchain.embeddings import OpenAIEmbeddings
+            from langchain_communityembeddings import OpenAIEmbeddings
             openai = OpenAIEmbeddings(openai_api_key="my-api-key")
 
     In order to use the library with Microsoft Azure endpoints, you need to set
@@ -174,7 +174,7 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
             os.environ["OPENAI_API_VERSION"] = "2023-05-15"
             os.environ["OPENAI_PROXY"] = "http://your-corporate-proxy:8080"
 
-            from langchain.embeddings.openai import OpenAIEmbeddings
+            from langchain_communityembeddings.openai import OpenAIEmbeddings
             embeddings = OpenAIEmbeddings(
                 deployment="your-embeddings-deployment-name",
                 model="your-embeddings-model-name",

swarms/models/openai_models.py

@@ -22,19 +22,19 @@ from typing import (
     Union,
 )
 
-from langchain.callbacks.manager import (
+from langchain_communitycallbacks.manager import (
     AsyncCallbackManagerForLLMRun,
     CallbackManagerForLLMRun,
 )
-from langchain.llms.base import BaseLLM
-from langchain.pydantic_v1 import Field, root_validator
-from langchain.schema import Generation, LLMResult
-from langchain.schema.output import GenerationChunk
-from langchain.utils import (
+from langchain_communityllms.base import BaseLLM
+from langchain_communitypydantic_v1 import Field, root_validator
+from langchain_communityschema import Generation, LLMResult
+from langchain_communityschema.output import GenerationChunk
+from langchain_communityutils import (
     get_from_dict_or_env,
     get_pydantic_field_names,
 )
-from langchain.utils.utils import build_extra_kwargs
+from langchain_communityutils.utils import build_extra_kwargs
 from tenacity import (
     RetryCallState,
     before_sleep_log,
@@ -796,7 +796,7 @@ class OpenAI(BaseOpenAI):
     Example:
         .. code-block:: python
 
-            from langchain.llms import OpenAI
+            from langchain_communityllms import OpenAI
             openai = OpenAI(model_name="text-davinci-003")
     """
 
@@ -820,7 +820,7 @@ class AzureOpenAI(BaseOpenAI):
     Example:
         .. code-block:: python
 
-            from langchain.llms import AzureOpenAI
+            from langchain_communityllms import AzureOpenAI
             openai = AzureOpenAI(model_name="text-davinci-003")
     """
 
@@ -897,7 +897,7 @@ class OpenAIChat(BaseLLM):
     Example:
         .. code-block:: python
 
-            from langchain.llms import OpenAIChat
+            from langchain_communityllms import OpenAIChat
             openaichat = OpenAIChat(model_name="gpt-3.5-turbo")
     """
 

swarms/models/palm.py

@@ -3,11 +3,11 @@ from __future__ import annotations
 import logging
 from typing import Any, Callable, Dict, List, Optional
 
-from langchain.callbacks.manager import CallbackManagerForLLMRun
-from langchain.llms import BaseLLM
-from langchain.pydantic_v1 import BaseModel, root_validator
-from langchain.schema import Generation, LLMResult
-from langchain.utils import get_from_dict_or_env
+from langchain_communitycallbacks.manager import CallbackManagerForLLMRun
+from langchain_communityllms import BaseLLM
+from langchain_communitypydantic_v1 import BaseModel, root_validator
+from langchain_communityschema import Generation, LLMResult
+from langchain_communityutils import get_from_dict_or_env
 from tenacity import (
     before_sleep_log,
     retry,

swarms/prompts/base.py

@@ -8,7 +8,7 @@ from pydantic import Field
 from swarms.utils.serializable import Serializable
 
 if TYPE_CHECKING:
-    from langchain.prompts.chat import ChatPromptTemplate
+    from langchain_communityprompts.chat import ChatPromptTemplate
 
 
 def get_buffer_string(
@@ -29,7 +29,7 @@ def get_buffer_string(
     Example:
         .. code-block:: python
 
-            from langchain.schema import AIMessage, HumanMessage
+            from langchain_communityschema import AIMessage, HumanMessage
 
             messages = [
                 HumanMessage(content="Hi, how are you?"),
@@ -86,7 +86,7 @@ class BaseMessage(Serializable):
         return True
 
     def __add__(self, other: Any) -> ChatPromptTemplate:
-        from langchain.prompts.chat import ChatPromptTemplate
+        from langchain_communityprompts.chat import ChatPromptTemplate
 
         prompt = ChatPromptTemplate(messages=[self])
         return prompt + other

swarms/structs/document.py

@@ -5,7 +5,7 @@ from abc import ABC, abstractmethod
 from functools import partial
 from typing import Any, Literal, Sequence
 
-from langchain.load.serializable import Serializable
+from langchain_communityload.serializable import Serializable
 from pydantic import Field
 
 

swarms/structs/multi_agent_collab.py

@@ -3,7 +3,7 @@ import random
 from typing import List
 
 import tenacity
-from langchain.output_parsers import RegexParser
+from langchain_communityoutput_parsers import RegexParser
 
 from swarms.structs.agent import Agent
 from swarms.utils.logger import logger

swarms/tools/exec_tool.py

@@ -3,7 +3,7 @@ import re
 from abc import abstractmethod
 from typing import Dict, List, NamedTuple
 
-from langchain.schema import BaseOutputParser
+from langchain_communityschema import BaseOutputParser
 from pydantic import ValidationError
 
 from swarms.tools.tool import BaseTool

swarms/tools/tool.py

@@ -19,8 +19,8 @@ from typing import (
     Union,
 )
 
-from langchain.callbacks.base import BaseCallbackManager
-from langchain.callbacks.manager import (
+from langchain_communitycallbacks.base import BaseCallbackManager
+from langchain_communitycallbacks.manager import (
     AsyncCallbackManager,
     AsyncCallbackManagerForToolRun,
     CallbackManager,
@@ -28,7 +28,7 @@ from langchain.callbacks.manager import (
     Callbacks,
 )
 
-from langchain.load.serializable import Serializable
+from langchain_communityload.serializable import Serializable
 from pydantic import (
     BaseModel,
     Extra,
@@ -37,7 +37,7 @@ from pydantic import (
     root_validator,
     validate_arguments,
 )
-from langchain.schema.runnable import (
+from langchain_communityschema.runnable import (
     Runnable,
     RunnableConfig,
     RunnableSerializable,

swarms/utils/README.md

@@ -100,9 +100,9 @@ Here's the pseudocode algorithm for a `WorkerNode` class that includes a vector
 In Python, this could look something like:
 
 ```python
-from langchain.vectorstores import FAISS
-from langchain.docstore import InMemoryDocstore
-from langchain.embeddings import OpenAIEmbeddings
+from langchain_communityvectorstores import FAISS
+from langchain_communitydocstore import InMemoryDocstore
+from langchain_communityembeddings import OpenAIEmbeddings
 import faiss
 from swarms.workers.auto_agent import AutoGPT
 from collections import deque

tests/models/test_elevenlab.py

@@ -47,7 +47,7 @@ def test_stream_speech(eleven_labs_tool):
 # Testing fixture and environment variables
 def test_api_key_validation(eleven_labs_tool):
     with patch(
-        "langchain.utils.get_from_dict_or_env", return_value=API_KEY
+        "langchain_communityutils.get_from_dict_or_env", return_value=API_KEY
     ):
         values = {"eleven_api_key": None}
         validated_values = eleven_labs_tool.validate_environment(