Ollama RAG Chatbot(Local Chat with multiple PDFs using Ollama and RAG) BrainSoup(Flexible native client with RAG & multi-agent automation) macai(macOS client for Ollama, ChatGPT, and other compatible API back-ends) RWKV-Runner(RWKV offline LLM deployment tool, also usable as a client for...
5)构建Retrieval链 importlogging# MultiQueryRetriever工具fromlangchain.retrievers.multi_queryimportMultiQueryRetriever# RetrievalQA链fromlangchain.chainsimportRetrievalQA# # 设置Logginglogging.basicConfig()logging.getLogger('langchain.retrievers.multi_query').setLevel(logging.INFO)# # 实例化一个大模型工具froml...
PromptTemplatefrom langchain_core.output_parsers import StrOutputParserfrom langchain_core.runnables import RunnablePassthroughfrom langchain.retrievers.multi_query import MultiQueryRetrieverfrom get_vector_db import get_vector_db
C. 代码程序 from llama_index.core import VectorStoreIndex, Document, SimpleDirectoryReader,Settings from llama_index.llms.ollama import Ollama from llama_index.embeddings.ollama import OllamaEmbedding # 指定LLM Settings.llm = Ollama(model="qwen2:7b", request_timeout=60.0) # 指定 embedding mode...
For multiline input, you can wrap text with""": >>> """Hello, ... world! ... """ I'm a basic program that prints the famous "Hello, world!" message to the console. Multimodal models >>> What's in this image? /Users/jmorgan/Desktop/smile.png The image features a yellow smi...
参阅文档:《Microsoft’s GraphRAG + AutoGen + Ollama + Chainlit = Local & Free Multi-Agent RAG Superbot》,源码:Autogen_GraphRAG_Ollama。 其它相关内容及代码请参阅前文《微软GraphRAG测试》,本篇不再重复。 1、建立测试项目。 拷贝要建立知识图谱的txt文件进input目录。
import java.util.*; public class Hello { public static void main(String[] args) { // 输出“Hello,火星生活!”的样式 System.out.println("Hello,火星生活!"); } } 要运行这段代码,请按照以下步骤操作: 确保你已经在你的项目中安装了Java开发环境(如IDE)。 将上述代码保存到一个文件中,例如Hello....
Import the open APIs of hundreds of platforms in API Hub or your own backend service interfaces as custom Agents! And use @Agent to combine different Agents in the same session to truly link everything! Inline CompletionRefactored inline completion feature using platform SDK and gpt-40-mini, ...
Import the open APIs of hundreds of platforms in API Hub or your own backend service interfaces as custom Agents! And use @Agent to combine different Agents in the same session to truly link everything! Inline CompletionRefactored inline completion feature using platform SDK and gpt-40-mini, ...
Ollama RAG Chatbot(Local Chat with multiple PDFs using Ollama and RAG) BrainSoup(Flexible native client with RAG & multi-agent automation) macai(macOS client for Ollama, ChatGPT, and other compatible API back-ends) RWKV-Runner(RWKV offline LLM deployment tool, also usable as a client for...