存储路径:~/Library/Application Support/anythingllm-desktop 2. 选择大模型 AnythingLLM默认通过Ollama来使用LLama2 7B,Mistral 7B,Gemma 2B等模型,也可以调用OpenAI、Gemini、Mistral等大模型的API服务。 此前,我已经安装了Ollama,那么只要选择Ollama,输入调用的API接口URL,再选择此前已经下载的Gemma模型即可。 3. ...
存储路径:~/Library/Application Support/anythingllm-desktop 2. 选择大模型 AnythingLLM默认通过Ollama来使用LLama2 7B,Mistral 7B,Gemma 2B等模型,也可以调用OpenAI、Gemini、Mistral等大模型的API服务。 此前,我已经安装了Ollama,那么只要选择Ollama,输入调用的API接口URL,再选择此前已经下载的Gemma模型即可。
ollama serve 配置AnythingLLM 下载AnythingLLM AnythingLLM是一个基于RAG(Retrieval-Augmented Generation)方案构建的开源、高效、可定制的私有知识库解决方案。本文使用的AnythingLLM的Desktop版本,首先从官网(https://useanything.com/)下载安装包: 下载后直接点击即可安装。 安装完毕后点击Get started开始配置: 配置LLM ...
from pydantic import BaseModelfrom typing import Any, Optionalfrom unstructured.partition.pdf import partition_pdf# Load path = "/Users/rlm/Desktop/IH-Unstructured/"file = "IH_Policy_Doc.pdf"# Get elementsraw_pdf_elements = partition_pdf( filename=path+file, extract_images_in_pdf=False,...
LLM大模型推理测试 & AI PC选型指南 (1)》中的体验类似,集成Intel Arc显卡的Core Ultra H系列CPU,...
(LLMs) are quickly gaining popularity from both individuals and companies as people are finding new emerging capabilities and opportunities to greatly improve their productivity. An especially powerful recent development has been the popularization of retrieval-based LLM systems that can hold informed ...
The all-in-one Desktop & Docker AI application with full RAG and AI Agent capabilities. - venhow/anything-llm
When you access the web UI for the first time, it will dowload the default LLM (llama3) and the embedding model (mxbai-embed-large). Tip If you are on Ubuntu Desktop, a frameless Chromium window will pop up to access the web app, to make it look like an independent application. You...
2.Custom Embeddable Chat Widget: Enhances user engagement by embedding a customizable chat widget on your website, offering seamless access to document-based conversations. 3.Multiple Document Type Support: AnythingLLM accommodates various document formats, from PDFs to DOCX files,...
最近,围绕着利用 LLM(Language Model)和知识图谱(KG,Knowledge Graphs)构建RAG(Retrieval Augmented Generation)流程引起了很多关注。 在本文中,让我们通过利用LlamaIndex和NebulaGraph为费城费城人队(Philadelphia Phillies)构建一个RAG流程,深入探讨知识图谱。