LlamaIndex offers a selection of data connectors on LlamaHub, simplifying data access by supporting direct ingestion from native sources without conversion. LangChain uses document loaders as data connectors to fetch and convert information from various sources into a format it can process. LlamaIndex...
} from "llamaindex" import 'dotenv/config' import fs from "node:fs/promises" async function main() { const PARSING_CACHE = "./cache.json" // set LLM and the embedding model Settings.llm = new OpenAI({ apiKey: process.env.OPENAI_API_KEY, model: "gpt-4o", }) Settings.embedModel ...
// create a query engine from our documents const index = await VectorStoreIndex.fromDocuments( documents, {vectorStore} ) In 5_qdrant you can see that we have also implemented a very naive caching mechanism to avoid re-parsing the PDF each time we run the agent: // load cache.json and...
Trying to decide between LlamaIndex and Langchain? Gain an overview and understand the key differences between the two most trending frameworks in the era of…
model. The goal of this repository is to provide examples to quickly get started with fine-tuning for domain adaptation and how to run inference for the fine-tuned models. For ease of use, the examples use Hugging Face converted versions of the models. See steps for conversion of the model...
Insert the embeddings, texts, titles and question id’s in milvus DB. Then Create an index on ...
Model conversion to Hugging Face The recipes and notebooks in this folder are using the Llama 2 model definition provided by Hugging Face's transformers library. Given that the original checkpoint resides under models/7B you can install all requirements and convert the checkpoint with: ...
See steps for conversion of the model here. In addition, we also provide a number of demo apps, to showcase the Llama 2 usage along with other ecosystem solutions to run Llama 2 locally, in the cloud, and on-prem. Llama 2 is a new technology that carries potential risks with use. ...
" 'filename': '2408.09869.pdf'}}),\n", " ('With Docling , we open-source a very capable and efficient document conversion tool which builds on the powerful, specialized AI models and datasets for layout analysis and table structure recognition we developed and presented in the recent past...
model. The goal of this repository is to provide examples to quickly get started with fine-tuning for domain adaptation and how to run inference for the fine-tuned models. For ease of use, the examples use Hugging Face converted versions of the models. See steps for conversion of the model...