txtai

AI-powered search engine (by neuml)

Stats

Basic txtai repo stats
50
1,048
9.3
17 days ago

neuml/txtai is an open source project licensed under Apache License 2.0 which is an OSI approved license.

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NOTE: The number of mentions on this list indicates mentions on common posts. Hence, a higher number means a better txtai alternative or higher similarity.

Posts

Posts where txtai has been mentioned. We have used some of these posts to build our list of alternatives and similar projects - the last one was on 2021-06-03.
  • Build and query a book similarity index
    GitHub: https://github.com/neuml/txtai Application: https://github.com/neuml/txtai/blob/master/examples/books.py
  • Txtai 3.1 released – Distributed embeddings indexes and update/delete/count
    news.ycombinator.com | 2021-05-22
  • txtai 3.1 released - Distributed embeddings indexes across multiple nodes and update/delete/count operations
  • Distributed embeddings cluster
    dev.to | 2021-05-19
  • [P] Machine learning workflows to summarize, translate, transcribe and more
    GitHub | Workflow builder | Documentation | Article
  • txtai: Machine-learning workflows to transform data and build AI-powered text indices to perform similarity search
  • https://np.reddit.com/r/rust/comments/nad9h0/txtai_30_released_machinelearning_workflows/gxuen8x/
    use std::error::Error; use txtai::segmentation::Segmentation; use txtai::summary::Summary; use txtai::textractor::Textractor; use txtai::transcription::Transcription; use txtai::translation::Translation; use txtai::workflow::Workflow; /// Example pipeline and workflow functionality. /// /// Uses files from txtai unit tests: https://github.com/neuml/txtai/releases/download/v2.0.0/tests.tar.gz pub async fn pipelines() -> Result { let service = "http://localhost:8000"; let segment = Segmentation::new(service); let sentences = "This is a test. And another test."; println!("---- Segmented Text ----"); println!("{:?}", segment.segment(sentences).await?); let textractor = Textractor::new(service); let text = textractor.textract("/tmp/txtai/article.pdf").await?; println!("\n---- Extracted Text ----"); println!("{:?}", text); let summary = Summary::new(service); let summarytext = summary.summary(text.as_string().unwrap(), None, None).await?; println!("\n---- Summary Text ----"); println!("{:?}", summarytext); let translate = Translation::new(service); let translation = translate.translate(&summarytext, Some("es"), None).await?; println!("\n---- Summary Text in Spanish ----"); println!("{:?}", translation); let workflow = Workflow::new(service); let output = workflow.workflow("sumspanish", &vec!["file:///tmp/txtai/article.pdf"]).await?; println!("\n---- Workflow [Extract Text->Summarize->Translate] ----"); println!("{:?}", output); let transcribe = Transcription::new(service); let transcription = transcribe.transcribe("/tmp/txtai/Make_huge_profits.wav").await?; println!("\n---- Transcribed Text ----"); println!("{:?}", transcription); Ok(()) }
  • https://np.reddit.com/r/javascript/comments/nad96f/txtai_30_released_machinelearning_workflows/gxuejd8/
    import {Segmentation, Textractor, Summary, Transcription, Translation, Workflow} from "txtai"; /** * Example pipeline and workflow functionality. * * Uses files from txtai unit tests: https://github.com/neuml/txtai/releases/download/v2.0.0/tests.tar.gz */ const run = async () => { try { let service = "http://localhost:8000" let segment = new Segmentation(service); let sentences = "This is a test. And another test."; console.log("---- Segmented Text ----"); console.log(await segment.segment(sentences)); let textractor = new Textractor(service); let text = await textractor.textract("/tmp/txtai/article.pdf") console.log("\n---- Extracted Text ----"); console.log(text); let summary = new Summary(service); let summarytext = await summary.summary(text); console.log("\n---- Summary Text ----"); console.log(summarytext); let translate = new Translation(service); let translation = await translate.translate(summarytext, "es"); console.log("\n---- Summary Text in Spanish ----"); console.log(translation); let workflow = new Workflow(service); let output = await workflow.workflow("sumspanish", ["file:///tmp/txtai/article.pdf"]); console.log("\n---- Workflow [Extract Text->Summarize->Translate] ----"); console.log(output); let transcribe = new Transcription(service); let transcription = await transcribe.transcribe("/tmp/txtai/Make_huge_profits.wav") console.log("\n---- Transcribed Text ----"); console.log(transcription); } catch (e) { console.trace(e); } }; run();
  • https://np.reddit.com/r/java/comments/nad8ih/txtai_30_released_machinelearning_workflows/gxuefrl/
    import java.util.Arrays; import java.util.List; import txtai.Segmentation; import txtai.Summary; import txtai.Textractor; import txtai.Transcription; import txtai.Translation; import txtai.Workflow; /** * Example pipeline and workflow functionality. * * Uses files from txtai unit tests: https://github.com/neuml/txtai/releases/download/v2.0.0/tests.tar.gz */ public class PipelinesDemo { public static void main(String[] args) { try { String service = "http://localhost:8000"; Segmentation segment = new Segmentation(service); String sentences = "This is a test. And another test."; System.out.println("---- Segmented Text ----"); System.out.println(segment.segment(sentences)); Textractor textractor = new Textractor(service); String text = (String)textractor.textract("/tmp/txtai/article.pdf"); System.out.println("\n---- Extracted Text ----"); System.out.println(text); Summary summary = new Summary(service); String summarytext = summary.summary(text, -1, -1); System.out.println("\n---- Summary Text ----"); System.out.println(summarytext); Translation translate = new Translation(service); String translation = translate.translate(summarytext, "es", null); System.out.println("\n---- Summary Text in Spanish ----"); System.out.println(translation); Workflow workflow = new Workflow(service); List output = workflow.workflow("sumspanish", Arrays.asList("file:///tmp/txtai/article.pdf")); System.out.println("\n---- Workflow [Extract Text->Summarize->Translate] ----"); System.out.println(output); Transcription transcribe = new Transcription(service); String transcription = transcribe.transcribe("/tmp/txtai/Make_huge_profits.wav"); System.out.println("\n---- Transcribed Text ----"); System.out.println(transcription); } catch (Exception ex) { ex.printStackTrace(); } } }
  • https://np.reddit.com/r/golang/comments/nad82x/txtai_30_released_machinelearning_workflows/gxue7qo/
    // Example pipeline and workflow functionality. // // Uses files from txtai unit tests: https://github.com/neuml/txtai/releases/download/v2.0.0/tests.tar.gz package main import ( "fmt" "github.com/neuml/txtai.go" ) func main() { service := "http://localhost:8000" segment := txtai.Segmentation(service) sentences := "This is a test. And another test." fmt.Println("---- Segmented Text ----") fmt.Println(segment.Segment(sentences)) textractor := txtai.Textractor(service) text := textractor.Textract("/tmp/txtai/article.pdf"); fmt.Println("\n---- Extracted Text ----") fmt.Println(text) summary := txtai.Summary(service) summarytext := summary.Summary(text.(string), -1, -1) fmt.Println("\n---- Summary Text ----") fmt.Println(summarytext) translate := txtai.Translation(service) translation := translate.Translate(summarytext, "es", "") fmt.Println("\n---- Summary Text in Spanish ----") fmt.Println(translation) workflow := txtai.Workflow(service) output := workflow.Workflow("sumspanish", []string {"file:///tmp/txtai/article.pdf"}) fmt.Println("\n---- Workflow [Extract Text->Summarize->Translate] ----") fmt.Println(output) transcribe := txtai.Transcription(service) transcription := transcribe.Transcribe("/tmp/txtai/Make_huge_profits.wav") fmt.Println("\n---- Transcribed Text ----") fmt.Println(transcription) }
  • txtai 3.0 released - Machine-learning workflows and similarity search in Python
    reddit.com/r/Python | 2021-05-11
  • txtai 3.0 released - Machine-learning workflows, similarity search and Rust support via API
    reddit.com/r/rust | 2021-05-11
  • txtai 3.0 released - Machine-learning workflows, similarity search and JavaScript support via API
  • txtai 3.0 released - Machine-learning workflows, similarity search and Java support via API
    reddit.com/r/java | 2021-05-11
    /** * Example pipeline and workflow functionality. * * Uses files from txtai unit tests: https://github.com/neuml/txtai/releases/download/v2.0.0/tests.tar.gz */ public class PipelinesDemo { public static void main(String[] args) { try { String service = "http://localhost:8000";
    reddit.com/r/java | 2021-05-11