diff --git a/Chroma_DB_with_Langchain.ipynb b/Chroma_DB_with_Langchain.ipynb index c45aa9f..8bbd005 100644 --- a/Chroma_DB_with_Langchain.ipynb +++ b/Chroma_DB_with_Langchain.ipynb @@ -103,7 +103,7 @@ } ], "source": [ - "from langchain.document_loaders import DirectoryLoader\n", + "from langchain_community.document_loaders import DirectoryLoader\n", "\n", "directory = '/content/pets'\n", "\n", @@ -146,7 +146,7 @@ } ], "source": [ - "from langchain.text_splitter import RecursiveCharacterTextSplitter\n", + "from langchain_text_splitters import RecursiveCharacterTextSplitter\n", "\n", "def split_docs(documents,chunk_size=1000,chunk_overlap=20):\n", " text_splitter = RecursiveCharacterTextSplitter(chunk_size=chunk_size, chunk_overlap=chunk_overlap)\n", @@ -168,7 +168,7 @@ "# # import openai\n", "# from langchain.embeddings.openai import OpenAIEmbeddings\n", "# embeddings = OpenAIEmbeddings(model_name=\"ada\")\n", - "from langchain.embeddings import SentenceTransformerEmbeddings\n", + "from langchain_community.embeddings import SentenceTransformerEmbeddings\n", "embeddings = SentenceTransformerEmbeddings(model_name=\"all-MiniLM-L6-v2\")" ] }, @@ -180,7 +180,7 @@ }, "outputs": [], "source": [ - "from langchain.vectorstores import Chroma\n", + "from langchain_community.vectorstores import Chroma\n", "db = Chroma.from_documents(docs, embeddings)" ] }, @@ -380,7 +380,7 @@ }, "outputs": [], "source": [ - "from langchain.chat_models import ChatOpenAI\n", + "from langchain_openai import ChatOpenAI\n", "model_name = \"gpt-3.5-turbo\"\n", "llm = ChatOpenAI(model_name=model_name)" ] diff --git a/LangChain_Expression_Language_(LCEL)_Tutorial.ipynb b/LangChain_Expression_Language_(LCEL)_Tutorial.ipynb index 96f812c..1b324c1 100644 --- a/LangChain_Expression_Language_(LCEL)_Tutorial.ipynb +++ b/LangChain_Expression_Language_(LCEL)_Tutorial.ipynb @@ -210,9 +210,9 @@ { "cell_type": "code", "source": [ - "from langchain.chat_models import ChatOpenAI\n", + "from langchain_openai import ChatOpenAI\n", "from langchain.prompts import ChatPromptTemplate\n", - "from langchain.schema.output_parser import StrOutputParser" + "from langchain_core.output_parsers import StrOutputParser" ], "metadata": { "id": "ZQGsQtxlmUoO" @@ -558,10 +558,10 @@ { "cell_type": "code", "source": [ - "from langchain.embeddings import OpenAIEmbeddings\n", + "from langchain_openai import OpenAIEmbeddings\n", "from langchain.prompts import ChatPromptTemplate\n", - "from langchain.schema.runnable import RunnableParallel, RunnablePassthrough\n", - "from langchain.vectorstores import Chroma" + "from langchain_core.runnables import RunnableParallel, RunnablePassthrough\n", + "from langchain_community.vectorstores import Chroma" ], "metadata": { "id": "WWa6ZZGc2GKs" diff --git a/LangGraph FastAPI Integration/api/requirements.txt b/LangGraph FastAPI Integration/api/requirements.txt index d631d15..3bb70d9 100644 --- a/LangGraph FastAPI Integration/api/requirements.txt +++ b/LangGraph FastAPI Integration/api/requirements.txt @@ -1,4 +1,4 @@ -langchain +langchain>=0.1 langchain-openai langchain-core langchain_community @@ -13,3 +13,4 @@ fastapi uvicorn pydantic python-dotenv +langchain-text-splitters>=0.0.1 diff --git a/Langchain Chatbot/Langchain_Pinecone_Indexing_.ipynb b/Langchain Chatbot/Langchain_Pinecone_Indexing_.ipynb index 36cbd8a..93dcb84 100644 --- a/Langchain Chatbot/Langchain_Pinecone_Indexing_.ipynb +++ b/Langchain Chatbot/Langchain_Pinecone_Indexing_.ipynb @@ -4892,7 +4892,7 @@ { "cell_type": "code", "source": [ - "from langchain.document_loaders import DirectoryLoader\n", + "from langchain_community.document_loaders import DirectoryLoader\n", "\n", "directory = '/content/data'\n", "\n", @@ -4944,7 +4944,7 @@ { "cell_type": "code", "source": [ - "from langchain.text_splitter import RecursiveCharacterTextSplitter\n", + "from langchain_text_splitters import RecursiveCharacterTextSplitter\n", "\n", "def split_docs(documents,chunk_size=500,chunk_overlap=20):\n", " text_splitter = RecursiveCharacterTextSplitter(chunk_size=chunk_size, chunk_overlap=chunk_overlap)\n", @@ -5015,7 +5015,7 @@ "# import openai\n", "# from langchain.embeddings.openai import OpenAIEmbeddings\n", "# embeddings = OpenAIEmbeddings(model_name=\"ada\")\n", - "from langchain.embeddings import SentenceTransformerEmbeddings\n", + "from langchain_community.embeddings import SentenceTransformerEmbeddings\n", "embeddings = SentenceTransformerEmbeddings(model_name=\"all-MiniLM-L6-v2\")" ], "metadata": { @@ -5448,7 +5448,7 @@ "cell_type": "code", "source": [ "import pinecone \n", - "from langchain.vectorstores import Pinecone\n", + "from langchain_community.vectorstores import Pinecone\n", "# initialize pinecone\n", "pinecone.init(\n", " api_key=\"\", # find at app.pinecone.io\n", diff --git a/Langchain Chatbot/main.py b/Langchain Chatbot/main.py index 4380a35..2bdd955 100644 --- a/Langchain Chatbot/main.py +++ b/Langchain Chatbot/main.py @@ -1,4 +1,4 @@ -from langchain.chat_models import ChatOpenAI +from langchain_openai import ChatOpenAI from langchain.chains import ConversationChain from langchain.chains.conversation.memory import ConversationBufferWindowMemory from langchain.prompts import ( diff --git a/Langchain Chatbot/requirements.txt b/Langchain Chatbot/requirements.txt index c315b3e..f083933 100644 --- a/Langchain Chatbot/requirements.txt +++ b/Langchain Chatbot/requirements.txt @@ -1,4 +1,8 @@ streamlit streamlit_chat -langchain -sentence_transformers \ No newline at end of file +langchain>=0.1 +sentence_transformers +langchain-community>=0.0.20 +langchain-openai>=0.0.5 +langchain-text-splitters>=0.0.1 +langchain-core>=0.1 diff --git a/Langchain RAG Course 2024/LangChain_Conversational_RAG_Crash_Course_From_Basics_to_Production_Part_1.ipynb b/Langchain RAG Course 2024/LangChain_Conversational_RAG_Crash_Course_From_Basics_to_Production_Part_1.ipynb index 6047d00..6b85412 100644 --- a/Langchain RAG Course 2024/LangChain_Conversational_RAG_Crash_Course_From_Basics_to_Production_Part_1.ipynb +++ b/Langchain RAG Course 2024/LangChain_Conversational_RAG_Crash_Course_From_Basics_to_Production_Part_1.ipynb @@ -1062,7 +1062,7 @@ } ], "source": [ - "from langchain.schema.runnable import RunnablePassthrough\n", + "from langchain_core.runnables import RunnablePassthrough\n", "rag_chain = (\n", " {\"context\": retriever, \"question\": RunnablePassthrough()} | prompt\n", ")\n", diff --git a/Langchain RAG Course 2024/api/requirements.txt b/Langchain RAG Course 2024/api/requirements.txt index 5f1a463..b0a6546 100644 --- a/Langchain RAG Course 2024/api/requirements.txt +++ b/Langchain RAG Course 2024/api/requirements.txt @@ -1,4 +1,4 @@ -langchain +langchain>=0.1 langchain-openai langchain-core langchain_community @@ -6,4 +6,5 @@ docx2txt pypdf langchain_chroma python-multipart -streamlit \ No newline at end of file +streamlit +langchain-text-splitters>=0.0.1 diff --git a/Langchain_Agents_SQL_Database_Agent.ipynb b/Langchain_Agents_SQL_Database_Agent.ipynb index 8e096f9..6ba5a1c 100644 --- a/Langchain_Agents_SQL_Database_Agent.ipynb +++ b/Langchain_Agents_SQL_Database_Agent.ipynb @@ -95,7 +95,7 @@ "from langchain.agents import load_tools\n", "from langchain.agents import initialize_agent\n", "from langchain.agents import AgentType\n", - "from langchain.llms import OpenAI" + "from langchain_openai import OpenAI\n" ], "metadata": { "id": "66hNmNKMhd5n" @@ -222,7 +222,7 @@ "from langchain.agents import create_sql_agent\n", "from langchain.agents.agent_toolkits import SQLDatabaseToolkit\n", "from langchain.sql_database import SQLDatabase\n", - "from langchain.llms.openai import OpenAI\n", + "from langchain_openai import OpenAI\n", "from langchain.agents import AgentExecutor" ] }, @@ -254,7 +254,7 @@ "cell_type": "code", "source": [ "# llm=OpenAI(temperature=0)\n", - "from langchain.chat_models import ChatOpenAI\n", + "from langchain_openai import ChatOpenAI\n", "llm = ChatOpenAI(model_name=\"gpt-3.5-turbo\")\n", "# chat = ChatOpenAI(model_name=\"gpt-4\")" ], diff --git a/Langchain_Semnatic_Serach_Pinecone.ipynb b/Langchain_Semnatic_Serach_Pinecone.ipynb index ef0dec6..1c5c2ce 100644 --- a/Langchain_Semnatic_Serach_Pinecone.ipynb +++ b/Langchain_Semnatic_Serach_Pinecone.ipynb @@ -159,7 +159,7 @@ { "cell_type": "code", "source": [ - "from langchain.document_loaders import DirectoryLoader\n", + "from langchain_community.document_loaders import DirectoryLoader\n", "\n", "directory = '/content/data'\n", "\n", @@ -204,7 +204,7 @@ { "cell_type": "code", "source": [ - "from langchain.text_splitter import RecursiveCharacterTextSplitter\n", + "from langchain_text_splitters import RecursiveCharacterTextSplitter\n", "\n", "def split_docs(documents,chunk_size=1000,chunk_overlap=20):\n", " text_splitter = RecursiveCharacterTextSplitter(chunk_size=chunk_size, chunk_overlap=chunk_overlap)\n", @@ -304,7 +304,7 @@ "cell_type": "code", "source": [ "import openai\n", - "from langchain.embeddings.openai import OpenAIEmbeddings\n", + "from langchain_openai import OpenAIEmbeddings\n", "\n", "embeddings = OpenAIEmbeddings(model_name=\"ada\")\n", "\n", @@ -356,7 +356,7 @@ "cell_type": "code", "source": [ "import pinecone \n", - "from langchain.vectorstores import Pinecone\n", + "from langchain_community.vectorstores import Pinecone\n", "# initialize pinecone\n", "pinecone.init(\n", " api_key=\"f7aa89af-ac99-4619-8914-8d08740f7b38\", # find at app.pinecone.io\n", @@ -419,7 +419,7 @@ { "cell_type": "code", "source": [ - "from langchain.llms import OpenAI\n", + "from langchain_openai import OpenAI\n", "\n", "# model_name = \"text-davinci-003\"\n", "# model_name = \"gpt-3.5-turbo\"\n", diff --git a/LlamaIndex_Tutorial.ipynb b/LlamaIndex_Tutorial.ipynb index bc4ea6e..819d217 100644 --- a/LlamaIndex_Tutorial.ipynb +++ b/LlamaIndex_Tutorial.ipynb @@ -334,7 +334,7 @@ "source": [ "from llama_index import LLMPredictor, ServiceContext\n", "\n", - "from langchain.chat_models import ChatOpenAI\n", + "from langchain_openai import ChatOpenAI\n", "\n", "llm_predictor = LLMPredictor(llm=ChatOpenAI(temperature=0, model_name=\"gpt-3.5-turbo\"))\n", "\n", @@ -457,7 +457,7 @@ { "cell_type": "code", "source": [ - "from langchain.embeddings.huggingface import HuggingFaceEmbeddings\n", + "from langchain_community.embeddings.huggingface import HuggingFaceEmbeddings\n", "from llama_index import LangchainEmbedding, ServiceContext\n", "\n", "# load in HF embedding model from langchain\n",