| import langchain |
|
|
| langchain.__version__ |
|
|
| from langchain import HuggingFacePipeline |
|
|
| from langchain import PromptTemplate |
| from langchain import LLMChain |
| from langchain.document_loaders import OnlinePDFLoader |
| from langchain.text_splitter import CharacterTextSplitter |
| from langchain.embeddings import HuggingFaceEmbeddings |
| from langchain.vectorstores import Chroma |
| from langchain.chains import ConversationalRetrievalChain |
| from langchain.agents import load_tools, initialize_agent, AgentType |
|
|
| |
| llm = HuggingFacePipeline.from_model_id(model_id="OpenAssistant/stablelm-7b-sft-v7-epoch-3", |
| task="text-generation", model_kwargs={"temperature": 0.0, "max_length": 2048, 'device_map': 'auto'}) |
|
|
| template = """<|prompter|>{question}<|endoftext|><|assistant|>""" |
|
|
| prompt = PromptTemplate(template=template, input_variables=["question"]) |
|
|
| llm_chain = LLMChain(prompt=prompt, llm=llm) |
| question = "What is the meaning of life?" |
| llm_chain.run(question) |
|
|
| loader = OnlinePDFLoader("https://arxiv.org/pdf/1911.01547.pdf") |
| document = loader.load() |
| len(document[0].page_content) |
|
|
| text_splitter = CharacterTextSplitter(chunk_size=1024, chunk_overlap=64) |
|
|
| |
| documents = text_splitter.split_documents(document) |
| len(documents) |
| documents[10].page_content |
|
|
|
|
| embeddings = HuggingFaceEmbeddings() |
| query_result = embeddings.embed_query(documents[0].page_content) |
|
|
| vectorstore = Chroma.from_documents(documents, embeddings) |
| qa = ConversationalRetrievalChain.from_llm(llm, vectorstore.as_retriever(), return_source_documents=True) |
|
|
| chat_history = [] |
| query = "What is the definition of intelligence?" |
| result = qa({"question": query, "chat_history": chat_history}) |
| result["answer"] |
|
|
| result['source_documents'][0].page_content |
|
|
| tools = load_tools( |
| ["arxiv"], |
| ) |
|
|
| agent_chain = initialize_agent( |
| tools, |
| llm, |
| agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, |
| verbose=True, |
| ) |
|
|
| agent_chain.run( |
| "What's the paper On the measure of intelligence, by François Chollet, about?", |
| ) |
