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Author SHA1 Message Date
yisding f27fd93b88 add code documentation (thanks @EmanuelCampos) 2024-01-25 15:40:04 -08:00
yisding debd71dd7f copy-paste bug 2024-01-25 15:07:30 -08:00
yisding cea6b08b46 docs(changeset): add new OpenAI embeddings (with dimension reduction support) 2024-01-25 14:55:14 -08:00
yisding b51f025401 add new openai embeddings 2024-01-25 14:53:29 -08:00
yisding 05ba70881c RELEASING: Releasing 1 package(s)
Releases:
  llamaindex@0.0.50

[skip ci]
2024-01-24 23:00:50 -08:00
yisding 8a729cdd0d minor bug fixes with together AI (#440) 2024-01-24 22:59:09 -08:00
Marcus Schiesser ffe5fbcd51 RELEASING: Releasing 1 package(s)
Releases:
  llamaindex@0.0.49

[skip ci]
2024-01-25 11:09:36 +07:00
Marcus Schiesser 18cc545e16 chore: allow separate releases for create-llama and llamaindex 2024-01-25 11:09:22 +07:00
Emanuel Ferreira c818e90cfc refactor: restructure documentation (#420)
Co-authored-by: Alex Yang <himself65@outlook.com>
2024-01-25 10:22:35 +07:00
Alex Yang 570973b9d6 docs: add stackblitz playground (#439) 2024-01-24 21:00:47 -06:00
95 changed files with 838 additions and 383 deletions
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"llamaindex": patch
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feat(qdrant): Add Qdrant Vector DB
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"llamaindex": patch
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add new OpenAI embeddings (with dimension reduction support)
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"llamaindex": patch
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Preview: Add ingestion pipeline (incl. different strategies to handle doc store duplicates)
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"llamaindex": patch
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feat: use conditional exports
The benefit of conditional exports is we split the llamaindex into different files. This will improve the tree shake if you are building web apps.
This also requires node16 (see https://nodejs.org/api/packages.html#conditional-exports).
If you are seeing typescript issue `TS2724`('llamaindex' has no exported member named XXX):
1. update `moduleResolution` to `bundler` in `tsconfig.json`, more for the web applications like Next.js, and vite, but still works for ts-node or tsx.
2. consider the ES module in your project, add `"type": "module"` into `package.json` and update `moduleResolution` to `node16` or `nodenext` in `tsconfig.json`.
We still support both cjs and esm, but you should update `tsconfig.json` to make the typescript happy.
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"llamaindex": patch
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feat(extractors): add keyword extractor and base extractor
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apps/docs/i18n
apps/docs/docs/api
pnpm-lock.yaml
lib/
dist/
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Documentation: https://ts.llamaindex.ai/
Try examples online:
[![Open in Stackblitz](https://developer.stackblitz.com/img/open_in_stackblitz.svg)](https://stackblitz.com/github/run-llama/LlamaIndexTS/tree/main/examples)
## What is LlamaIndex.TS?
LlamaIndex.TS aims to be a lightweight, easy to use set of libraries to help you integrate large language models into your applications with your own data.
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sidebar_position: 4
---
# End to End Examples
We include several end-to-end examples using LlamaIndex.TS in the repository
Check out the examples below or try them out and complete them in minutes with interactive Github Codespace tutorials provided by Dev-Docs [here](https://codespaces.new/team-dev-docs/lits-dev-docs-playground?devcontainer_path=.devcontainer%2Fjavascript_ltsquickstart%2Fdevcontainer.json):
## [Chat Engine](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/chatEngine.ts)
Read a file and chat about it with the LLM.
## [Vector Index](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/vectorIndex.ts)
Create a vector index and query it. The vector index will use embeddings to fetch the top k most relevant nodes. By default, the top k is 2.
## [Summary Index](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/summaryIndex.ts)
Create a list index and query it. This example also use the `LLMRetriever`, which will use the LLM to select the best nodes to use when generating answer.
## [Save / Load an Index](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/storageContext.ts)
Create and load a vector index. Persistance to disk in LlamaIndex.TS happens automatically once a storage context object is created.
## [Customized Vector Index](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/vectorIndexCustomize.ts)
Create a vector index and query it, while also configuring the `LLM`, the `ServiceContext`, and the `similarity_top_k`.
## [OpenAI LLM](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/openai.ts)
Create an OpenAI LLM and directly use it for chat.
## [Llama2 DeuceLLM](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/llamadeuce.ts)
Create a Llama-2 LLM and directly use it for chat.
## [SubQuestionQueryEngine](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/subquestion.ts)
Uses the `SubQuestionQueryEngine`, which breaks complex queries into multiple questions, and then aggreates a response across the answers to all sub-questions.
## [Low Level Modules](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/lowlevel.ts)
This example uses several low-level components, which removes the need for an actual query engine. These components can be used anywhere, in any application, or customized and sub-classed to meet your own needs.
## [JSON Entity Extraction](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/jsonExtract.ts)
Features OpenAI's chat API (using [`json_mode`](https://platform.openai.com/docs/guides/text-generation/json-mode)) to extract a JSON object from a sales call transcript.
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label: Examples
position: 2
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sidebar_position: 1
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import CodeBlock from "@theme/CodeBlock";
import CodeSource from "!raw-loader!../../../../examples/chatEngine";
# Chat Engine
Chat Engine is a class that allows you to create a chatbot from a retriever. It is a wrapper around a retriever that allows you to chat with it in a conversational manner.
<CodeBlock language="ts">{CodeSource}</CodeBlock>
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---
sidebar_position: 5
---
# More examples
You can check out more examples in the [examples](https://github.com/run-llama/LlamaIndexTS/tree/main/examples) folder of the repository.
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---
sidebar_position: 4
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import CodeBlock from "@theme/CodeBlock";
import CodeSource from "!raw-loader!../../../../examples/storageContext";
# Save/Load an Index
<CodeBlock language="ts">{CodeSource}</CodeBlock>
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sidebar_position: 3
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import CodeBlock from "@theme/CodeBlock";
import CodeSource from "!raw-loader!../../../../examples/summaryIndex";
# Summary Index
<CodeBlock language="ts">{CodeSource}</CodeBlock>
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sidebar_position: 2
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import CodeBlock from "@theme/CodeBlock";
import CodeSource from "!raw-loader!../../../../examples/vectorIndex";
# Vector Index
<CodeBlock language="ts">{CodeSource}</CodeBlock>
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label: Getting Started
position: 1
@@ -2,7 +2,7 @@
sidebar_position: 3
---
# High-Level Concepts
# Concepts
LlamaIndex.TS helps you build LLM-powered applications (e.g. Q&A, chatbot) over custom data.
@@ -18,7 +18,7 @@ LlamaIndex uses a two stage method when using an LLM with your data:
1. **indexing stage**: preparing a knowledge base, and
2. **querying stage**: retrieving relevant context from the knowledge to assist the LLM in responding to a question
![](./_static/concepts/rag.jpg)
![](../_static/concepts/rag.jpg)
This process is also known as Retrieval Augmented Generation (RAG).
@@ -30,7 +30,7 @@ Let's explore each stage in detail.
LlamaIndex.TS help you prepare the knowledge base with a suite of data connectors and indexes.
![](./_static/concepts/indexing.jpg)
![](../_static/concepts/indexing.jpg)
[**Data Loaders**](./modules/high_level/data_loader.md):
A data connector (i.e. `Reader`) ingest data from different data sources and data formats into a simple `Document` representation (text and simple metadata).
@@ -56,7 +56,7 @@ LlamaIndex provides composable modules that help you build and integrate RAG pip
These building blocks can be customized to reflect ranking preferences, as well as composed to reason over multiple knowledge bases in a structured way.
![](./_static/concepts/querying.jpg)
![](../_static/concepts/querying.jpg)
#### Building Blocks
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# Environments
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---
sidebar_position: 1
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# Installation and Setup
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# Starter Tutorial
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Our documentation includes [Installation Instructions](./installation.mdx) and a [Starter Tutorial](./starter.md) to build your first application.
Once you're up and running, [High-Level Concepts](./concepts.md) has an overview of LlamaIndex's modular architecture. For more hands-on practical examples, look through our [End-to-End Tutorials](./end_to_end.md).
Once you're up and running, [High-Level Concepts](./getting_started/concepts.md) has an overview of LlamaIndex's modular architecture. For more hands-on practical examples, look through our [End-to-End Tutorials](./end_to_end.md).
## 🗺️ Ecosystem
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label: High-Level Modules
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label: Low-Level Modules
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label: Observability
position: 5
@@ -41,7 +41,7 @@ LlamaIndex.TS هو إطار بيانات لتطبيقات LLM لاستيعاب
تتضمن وثائقنا [تعليمات التثبيت](./installation.mdx) و[دليل البداية](./starter.md) لبناء تطبيقك الأول.
بمجرد أن تكون جاهزًا وتعمل ، يحتوي [مفاهيم عالية المستوى](./concepts.md) على نظرة عامة على الهندسة المعمارية المتعددة المستويات لـ LlamaIndex. لمزيد من الأمثلة العملية التفصيلية ، يمكنك الاطلاع على [دروس النهاية إلى النهاية](./end_to_end.md).
بمجرد أن تكون جاهزًا وتعمل ، يحتوي [مفاهيم عالية المستوى](./getting_started/concepts.md) على نظرة عامة على الهندسة المعمارية المتعددة المستويات لـ LlamaIndex. لمزيد من الأمثلة العملية التفصيلية ، يمكنك الاطلاع على [دروس النهاية إلى النهاية](./end_to_end.md).
## 🗺️ النظام البيئي
@@ -43,7 +43,7 @@ LlamaIndex.TS предоставя основен набор от инструм
Документацията ни включва [Инструкции за инсталиране](./installation.mdx) и [Урок за начинаещи](./starter.md), за да построите първото си приложение.
След като сте готови, [Високо ниво концепции](./concepts.md) представя общ преглед на модулната архитектура на LlamaIndex. За повече практически примери, разгледайте нашите [Уроци от начало до край](./end_to_end.md).
След като сте готови, [Високо ниво концепции](./getting_started/concepts.md) представя общ преглед на модулната архитектура на LlamaIndex. За повече практически примери, разгледайте нашите [Уроци от начало до край](./end_to_end.md).
## 🗺️ Екосистема
@@ -41,7 +41,7 @@ Per a aplicacions més complexes, les nostres API de nivell inferior permeten al
La nostra documentació inclou [Instruccions d'Instal·lació](./installation.mdx) i un [Tutorial d'Inici](./starter.md) per a construir la vostra primera aplicació.
Un cop tingueu tot a punt, [Conceptes de Nivell Alt](./concepts.md) ofereix una visió general de l'arquitectura modular de LlamaIndex. Per a més exemples pràctics, consulteu els nostres [Tutorials de Principi a Fi](./end_to_end.md).
Un cop tingueu tot a punt, [Conceptes de Nivell Alt](./getting_started/concepts.md) ofereix una visió general de l'arquitectura modular de LlamaIndex. Per a més exemples pràctics, consulteu els nostres [Tutorials de Principi a Fi](./end_to_end.md).
## 🗺️ Ecosistema
@@ -41,7 +41,7 @@ Pro složitější aplikace naše API na nižší úrovni umožňuje pokročilý
Naše dokumentace obsahuje [Návod k instalaci](./installation.mdx) a [Úvodní tutoriál](./starter.md) pro vytvoření vaší první aplikace.
Jakmile jste připraveni, [Vysokoúrovňové koncepty](./concepts.md) poskytují přehled o modulární architektuře LlamaIndexu. Pro více praktických příkladů se podívejte na naše [Tutoriály od začátku do konce](./end_to_end.md).
Jakmile jste připraveni, [Vysokoúrovňové koncepty](./getting_started/concepts.md) poskytují přehled o modulární architektuře LlamaIndexu. Pro více praktických příkladů se podívejte na naše [Tutoriály od začátku do konce](./end_to_end.md).
## 🗺️ Ekosystém
@@ -41,7 +41,7 @@ Til mere komplekse applikationer giver vores API'er på lavere niveau avancerede
Vores dokumentation inkluderer [Installationsinstruktioner](./installation.mdx) og en [Starter Tutorial](./starter.md) til at bygge din første applikation.
Når du er i gang, giver [Højniveaukoncepter](./concepts.md) et overblik over LlamaIndex's modulære arkitektur. For flere praktiske eksempler, kan du kigge igennem vores [End-to-End Tutorials](./end_to_end.md).
Når du er i gang, giver [Højniveaukoncepter](./getting_started/concepts.md) et overblik over LlamaIndex's modulære arkitektur. For flere praktiske eksempler, kan du kigge igennem vores [End-to-End Tutorials](./end_to_end.md).
## 🗺️ Økosystem
@@ -41,7 +41,7 @@ Für komplexere Anwendungen ermöglichen unsere APIs auf niedrigerer Ebene fortg
Unsere Dokumentation enthält [Installationsanweisungen](./installation.mdx) und ein [Einführungstutorial](./starter.md), um Ihre erste Anwendung zu erstellen.
Sobald Sie bereit sind, bietet [High-Level-Konzepte](./concepts.md) einen Überblick über die modulare Architektur von LlamaIndex. Für praktische Beispiele schauen Sie sich unsere [End-to-End-Tutorials](./end_to_end.md) an.
Sobald Sie bereit sind, bietet [High-Level-Konzepte](./getting_started/concepts.md) einen Überblick über die modulare Architektur von LlamaIndex. Für praktische Beispiele schauen Sie sich unsere [End-to-End-Tutorials](./end_to_end.md) an.
## 🗺️ Ökosystem
@@ -43,7 +43,7 @@ slug: /
Η τεκμηρίωσή μας περιλαμβάνει [Οδηγίες Εγκατάστασης](./installation.mdx) και ένα [Εισαγωγικό Εκπαιδευτικό Πρόγραμμα](./starter.md) για να δημιουργήσετε την πρώτη σας εφαρμογή.
Αφού ξεκινήσετε, οι [Υψηλού Επιπέδου Έννοιες](./concepts.md) παρέχουν μια επισκόπηση της μοντουλαρισμένης αρχιτεκτονικής του LlamaIndex. Για περισσότερα πρακτικά παραδείγματα, ρίξτε μια ματιά στα [Ολοκληρωμένα Εκπαιδευτικά Προγράμματα](./end_to_end.md).
Αφού ξεκινήσετε, οι [Υψηλού Επιπέδου Έννοιες](./getting_started/concepts.md) παρέχουν μια επισκόπηση της μοντουλαρισμένης αρχιτεκτονικής του LlamaIndex. Για περισσότερα πρακτικά παραδείγματα, ρίξτε μια ματιά στα [Ολοκληρωμένα Εκπαιδευτικά Προγράμματα](./end_to_end.md).
## 🗺️ Οικοσύστημα
@@ -41,7 +41,7 @@ Para aplicaciones más complejas, nuestras API de nivel inferior permiten a los
Nuestra documentación incluye [Instrucciones de instalación](./installation.mdx) y un [Tutorial de inicio](./starter.md) para construir tu primera aplicación.
Una vez que estés en funcionamiento, [Conceptos de alto nivel](./concepts.md) ofrece una visión general de la arquitectura modular de LlamaIndex. Para obtener ejemplos prácticos más detallados, consulta nuestros [Tutoriales de extremo a extremo](./end_to_end.md).
Una vez que estés en funcionamiento, [Conceptos de alto nivel](./getting_started/concepts.md) ofrece una visión general de la arquitectura modular de LlamaIndex. Para obtener ejemplos prácticos más detallados, consulta nuestros [Tutoriales de extremo a extremo](./end_to_end.md).
## 🗺️ Ecosistema
@@ -41,7 +41,7 @@ Täpsemate rakenduste jaoks võimaldavad meie madalama taseme API-d edasijõudnu
Meie dokumentatsioonis on [paigaldusjuhised](./installation.mdx) ja [algõpetus](./starter.md) oma esimese rakenduse loomiseks.
Kui olete valmis ja töötate, siis [kõrgtasemel kontseptsioonid](./concepts.md) annavad ülevaate LlamaIndexi moodularhitektuurist. Praktiliste näidete jaoks vaadake läbi meie [otsast lõpuni õpetused](./end_to_end.md).
Kui olete valmis ja töötate, siis [kõrgtasemel kontseptsioonid](./getting_started/concepts.md) annavad ülevaate LlamaIndexi moodularhitektuurist. Praktiliste näidete jaoks vaadake läbi meie [otsast lõpuni õpetused](./end_to_end.md).
## 🗺️ Ökosüsteem
@@ -43,7 +43,7 @@ API سطح بالای ما به کاربران مبتدی امکان استفا
مستندات ما شامل [دستورالعمل نصب](./installation.mdx) و [آموزش شروع کار](./starter.md) برای ساخت اولین برنامه شما است.
با راه اندازی و اجرا شدن، [مفاهیم سطح بالا](./concepts.md) یک نمای کلی از معماری ماژولار لاماایندکس را ارائه می دهد. برای مثال های عملی بیشتر، به [آموزش های پایان به پایان](./end_to_end.md) مراجعه کنید.
با راه اندازی و اجرا شدن، [مفاهیم سطح بالا](./getting_started/concepts.md) یک نمای کلی از معماری ماژولار لاماایندکس را ارائه می دهد. برای مثال های عملی بیشتر، به [آموزش های پایان به پایان](./end_to_end.md) مراجعه کنید.
"
@@ -43,7 +43,7 @@ Monimutkaisempiin sovelluksiin tarjoamme matalamman tason API:t, jotka mahdollis
Dokumentaatiostamme löydät [asennusohjeet](./installation.mdx) ja [aloitusopetusohjelman](./starter.md) ensimmäisen sovelluksesi rakentamiseen.
Kun olet päässyt vauhtiin, [Korkean tason käsitteet](./concepts.md) antaa yleiskuvan LlamaIndexin modulaarisesta arkkitehtuurista. Lisää käytännön esimerkkejä löydät [Päästä päähän -opetusohjelmista](./end_to_end.md).
Kun olet päässyt vauhtiin, [Korkean tason käsitteet](./getting_started/concepts.md) antaa yleiskuvan LlamaIndexin modulaarisesta arkkitehtuurista. Lisää käytännön esimerkkejä löydät [Päästä päähän -opetusohjelmista](./end_to_end.md).
## 🗺️ Ekosysteemi
@@ -43,7 +43,7 @@ API הרמה הגבוהה שלנו מאפשר למשתמשים מתחילים ל
התיעוד שלנו כולל [הוראות התקנה](./installation.mdx) ו[מדריך התחלה](./starter.md) לבניית היישום הראשון שלך.
כאשר אתה מוכן ורץ, [מושגים ברמה גבוהה](./concepts.md) מציג סקירה על ארכיטקטורה מודולרית של LlamaIndex. לדוגמאות פרקטיות יותר, עיין ב[מדריכים מתקדמים מתחילה ועד סוף](./end_to_end.md).
כאשר אתה מוכן ורץ, [מושגים ברמה גבוהה](./getting_started/concepts.md) מציג סקירה על ארכיטקטורה מודולרית של LlamaIndex. לדוגמאות פרקטיות יותר, עיין ב[מדריכים מתקדמים מתחילה ועד סוף](./end_to_end.md).
"
@@ -43,7 +43,7 @@ LlamaIndex.TS जावास्क्रिप्ट और TypeScript के
हमारी दस्तावेज़ी में [स्थापना निर्देश](./installation.mdx) और [स्टार्टर ट्यूटोरियल](./starter.md) शामिल हैं, जिनका उपयोग करके आप अपना पहला एप्लिकेशन बना सकते हैं।
एक बार जब आप शुरू हो जाएं, [उच्च स्तरीय अवधारणाएँ](./concepts.md) में LlamaIndex की मॉड्यूलर आर्किटेक्चर का अवलोकन है। अधिक हैंड्स-ऑन प्रैक्टिकल उदाहरणों के लिए, हमारे [एंड-टू-एंड ट्यूटोरियल](./end_to_end.md) को देखें।
एक बार जब आप शुरू हो जाएं, [उच्च स्तरीय अवधारणाएँ](./getting_started/concepts.md) में LlamaIndex की मॉड्यूलर आर्किटेक्चर का अवलोकन है। अधिक हैंड्स-ऑन प्रैक्टिकल उदाहरणों के लिए, हमारे [एंड-टू-एंड ट्यूटोरियल](./end_to_end.md) को देखें।
"
@@ -41,7 +41,7 @@ Za složenije aplikacije, naše API-je niže razine omogućuju naprednim korisni
Naša dokumentacija uključuje [Upute za instalaciju](./installation.mdx) i [Uvodni vodič](./starter.md) za izgradnju vaše prve aplikacije.
Kada ste spremni za rad, [Visokorazinski koncepti](./concepts.md) pružaju pregled modularne arhitekture LlamaIndex-a. Za praktične primjere, pogledajte naše [Vodiče od početka do kraja](./end_to_end.md).
Kada ste spremni za rad, [Visokorazinski koncepti](./getting_started/concepts.md) pružaju pregled modularne arhitekture LlamaIndex-a. Za praktične primjere, pogledajte naše [Vodiče od početka do kraja](./end_to_end.md).
## 🗺️ Ekosustav
@@ -41,7 +41,7 @@ A komplexebb alkalmazásokhoz a mélyebb szintű API-k lehetővé teszik a halad
A dokumentációnk tartalmazza a [Telepítési utasításokat](./installation.mdx) és egy [Kezdő útmutatót](./starter.md) az első alkalmazás létrehozásához.
Miután elindultál, a [Magas szintű fogalmak](./concepts.md) áttekintést ad a LlamaIndex moduláris architektúrájáról. További gyakorlati példákért tekintsd meg az [End-to-End útmutatóinkat](./end_to_end.md).
Miután elindultál, a [Magas szintű fogalmak](./getting_started/concepts.md) áttekintést ad a LlamaIndex moduláris architektúrájáról. További gyakorlati példákért tekintsd meg az [End-to-End útmutatóinkat](./end_to_end.md).
## 🗺️ Ökoszisztéma
@@ -41,7 +41,7 @@ Untuk aplikasi yang lebih kompleks, API tingkat lebih rendah kami memungkinkan p
Dokumentasi kami mencakup [Instruksi Instalasi](./installation.mdx) dan [Tutorial Awal](./starter.md) untuk membangun aplikasi pertama Anda.
Setelah Anda mulai, [Konsep Tingkat Tinggi](./concepts.md) memberikan gambaran tentang arsitektur modular LlamaIndex. Untuk contoh praktis yang lebih mendalam, lihat [Tutorial End-to-End](./end_to_end.md).
Setelah Anda mulai, [Konsep Tingkat Tinggi](./getting_started/concepts.md) memberikan gambaran tentang arsitektur modular LlamaIndex. Untuk contoh praktis yang lebih mendalam, lihat [Tutorial End-to-End](./end_to_end.md).
## 🗺️ Ekosistem
@@ -41,7 +41,7 @@ Per applicazioni più complesse, le nostre API di livello inferiore consentono a
La nostra documentazione include le [Istruzioni di installazione](./installation.mdx) e un [Tutorial introduttivo](./starter.md) per creare la tua prima applicazione.
Una volta che sei pronto, i [Concetti di alto livello](./concepts.md) offrono una panoramica dell'architettura modulare di LlamaIndex. Per ulteriori esempi pratici, consulta i nostri [Tutorial end-to-end](./end_to_end.md).
Una volta che sei pronto, i [Concetti di alto livello](./getting_started/concepts.md) offrono una panoramica dell'architettura modulare di LlamaIndex. Per ulteriori esempi pratici, consulta i nostri [Tutorial end-to-end](./end_to_end.md).
## 🗺️ Ecosistema
@@ -41,7 +41,7 @@ LlamaIndex.TSは、JavaScriptとTypeScriptを使用してLLMアプリを構築
私たちのドキュメントには、[インストール手順](./installation.mdx)と[スターターチュートリアル](./starter.md)が含まれており、最初のアプリケーションの構築をサポートします。
一度準備ができたら、[ハイレベルなコンセプト](./concepts.md)では、LlamaIndexのモジュラーアーキテクチャの概要を説明しています。より実践的な例については、[エンドツーエンドのチュートリアル](./end_to_end.md)を参照してください。
一度準備ができたら、[ハイレベルなコンセプト](./getting_started/concepts.md)では、LlamaIndexのモジュラーアーキテクチャの概要を説明しています。より実践的な例については、[エンドツーエンドのチュートリアル](./end_to_end.md)を参照してください。
## 🗺️ エコシステム
@@ -41,7 +41,7 @@ LlamaIndex.TS는 JavaScript와 TypeScript로 LLM 앱을 개발하는 모든 사
저희 문서에는 [설치 지침](./installation.mdx)과 [스타터 튜토리얼](./starter.md)이 포함되어 있어 첫 번째 애플리케이션을 빌드할 수 있습니다.
한 번 시작하면, [고수준 개념](./concepts.md)에서 LlamaIndex의 모듈식 아키텍처에 대한 개요를 확인할 수 있습니다. 더 많은 실전 예제를 원하신다면, [End-to-End 튜토리얼](./end_to_end.md)을 참조해주세요.
한 번 시작하면, [고수준 개념](./getting_started/concepts.md)에서 LlamaIndex의 모듈식 아키텍처에 대한 개요를 확인할 수 있습니다. 더 많은 실전 예제를 원하신다면, [End-to-End 튜토리얼](./end_to_end.md)을 참조해주세요.
"
@@ -41,7 +41,7 @@ Sudėtingesnėms programoms mūsų žemesnio lygio API leidžia pažengusiems na
Mūsų dokumentacija apima [įdiegimo instrukcijas](./installation.mdx) ir [pradžios vadovą](./starter.md), skirtą sukurti pirmąją aplikaciją.
Kai jau esate paleidę, [aukšto lygio konceptai](./concepts.md) pateikia apžvalgą apie LlamaIndex modularią architektūrą. Norėdami gauti daugiau praktinių pavyzdžių, peržiūrėkite mūsų [nuo pradžių iki pabaigos vadovus](./end_to_end.md).
Kai jau esate paleidę, [aukšto lygio konceptai](./getting_started/concepts.md) pateikia apžvalgą apie LlamaIndex modularią architektūrą. Norėdami gauti daugiau praktinių pavyzdžių, peržiūrėkite mūsų [nuo pradžių iki pabaigos vadovus](./end_to_end.md).
## 🗺️ Ekosistema
@@ -43,7 +43,7 @@ Lielākām un sarežģītākām lietojumprogrammām mūsu zemāka līmeņa API
Mūsu dokumentācijā ir iekļautas [Instalācijas instrukcijas](./installation.mdx) un [Sākuma pamācība](./starter.md), lai izveidotu savu pirmo lietojumprogrammu.
Kad esat gatavs, [Augsta līmeņa koncepti](./concepts.md) sniedz pārskatu par LlamaIndex modulāro arhitektūru. Lai iegūtu vairāk praktisku piemēru, apskatiet mūsu [Galēji līdz galam pamācības](./end_to_end.md).
Kad esat gatavs, [Augsta līmeņa koncepti](./getting_started/concepts.md) sniedz pārskatu par LlamaIndex modulāro arhitektūru. Lai iegūtu vairāk praktisku piemēru, apskatiet mūsu [Galēji līdz galam pamācības](./end_to_end.md).
## 🗺️ Ekosistēma
@@ -41,7 +41,7 @@ Voor complexere toepassingen stellen onze API's op lager niveau gevorderde gebru
Onze documentatie bevat [Installatie-instructies](./installation.mdx) en een [Starterzelfstudie](./starter.md) om uw eerste toepassing te bouwen.
Zodra u aan de slag bent, geeft [Hoog-niveau Concepten](./concepts.md) een overzicht van de modulaire architectuur van LlamaIndex. Voor meer praktische voorbeelden kunt u onze [End-to-End Tutorials](./end_to_end.md) bekijken.
Zodra u aan de slag bent, geeft [Hoog-niveau Concepten](./getting_started/concepts.md) een overzicht van de modulaire architectuur van LlamaIndex. Voor meer praktische voorbeelden kunt u onze [End-to-End Tutorials](./end_to_end.md) bekijken.
## 🗺️ Ecosysteem
@@ -41,7 +41,7 @@ For mer komplekse applikasjoner lar våre lavnivå-APIer avanserte brukere tilpa
Dokumentasjonen vår inkluderer [Installasjonsinstruksjoner](./installation.mdx) og en [Starterveiledning](./starter.md) for å bygge din første applikasjon.
Når du er oppe og kjører, gir [Høynivåkonsepter](./concepts.md) en oversikt over LlamaIndex sin modulære arkitektur. For mer praktiske eksempler, kan du se gjennom våre [End-to-End veiledninger](./end_to_end.md).
Når du er oppe og kjører, gir [Høynivåkonsepter](./getting_started/concepts.md) en oversikt over LlamaIndex sin modulære arkitektur. For mer praktiske eksempler, kan du se gjennom våre [End-to-End veiledninger](./end_to_end.md).
## 🗺️ Økosystem
@@ -41,7 +41,7 @@ Dla bardziej zaawansowanych aplikacji nasze API na niższym poziomie umożliwia
Nasza dokumentacja zawiera [Instrukcje instalacji](./installation.mdx) oraz [Samouczek dla początkujących](./starter.md), który pomoże Ci zbudować swoją pierwszą aplikację.
Gdy już będziesz gotowy, [Wysokopoziomowe koncepcje](./concepts.md) zawierają przegląd modułowej architektury LlamaIndex. Jeśli chcesz zobaczyć praktyczne przykłady, zapoznaj się z naszymi [Samouczkami od początku do końca](./end_to_end.md).
Gdy już będziesz gotowy, [Wysokopoziomowe koncepcje](./getting_started/concepts.md) zawierają przegląd modułowej architektury LlamaIndex. Jeśli chcesz zobaczyć praktyczne przykłady, zapoznaj się z naszymi [Samouczkami od początku do końca](./end_to_end.md).
## 🗺️ Ekosystem
@@ -41,7 +41,7 @@ Para aplicativos mais complexos, nossas APIs de nível inferior permitem que usu
Nossa documentação inclui [Instruções de Instalação](./installation.mdx) e um [Tutorial Inicial](./starter.md) para construir seu primeiro aplicativo.
Depois de estar pronto para começar, [Conceitos de Alto Nível](./concepts.md) oferece uma visão geral da arquitetura modular do LlamaIndex. Para exemplos práticos mais detalhados, consulte nossos [Tutoriais de Ponta a Ponta](./end_to_end.md).
Depois de estar pronto para começar, [Conceitos de Alto Nível](./getting_started/concepts.md) oferece uma visão geral da arquitetura modular do LlamaIndex. Para exemplos práticos mais detalhados, consulte nossos [Tutoriais de Ponta a Ponta](./end_to_end.md).
## 🗺️ Ecossistema
@@ -41,7 +41,7 @@ Pentru aplicații mai complexe, API-urile noastre de nivel inferior permit utili
Documentația noastră include [Instrucțiuni de instalare](./installation.mdx) și un [Tutorial de pornire](./starter.md) pentru a construi prima ta aplicație.
Odată ce ai început, [Concepte de nivel înalt](./concepts.md) oferă o prezentare generală a arhitecturii modulare a LlamaIndex. Pentru mai multe exemple practice, consultă [Tutorialele de la cap la coadă](./end_to_end.md).
Odată ce ai început, [Concepte de nivel înalt](./getting_started/concepts.md) oferă o prezentare generală a arhitecturii modulare a LlamaIndex. Pentru mai multe exemple practice, consultă [Tutorialele de la cap la coadă](./end_to_end.md).
## 🗺️ Ecosistem
@@ -41,7 +41,7 @@ LlamaIndex.TS предоставляет основной набор инстр
Наша документация включает [Инструкции по установке](./installation.mdx) и [Стартовое руководство](./starter.md) для создания вашего первого приложения.
Когда вы начнете работу, [Высокоуровневые концепции](./concepts.md) предоставляют обзор модульной архитектуры LlamaIndex. Для более практических примеров руководство [Полный цикл руководств](./end_to_end.md) будет полезно.
Когда вы начнете работу, [Высокоуровневые концепции](./getting_started/concepts.md) предоставляют обзор модульной архитектуры LlamaIndex. Для более практических примеров руководство [Полный цикл руководств](./end_to_end.md) будет полезно.
## 🗺️ Экосистема
@@ -41,7 +41,7 @@ Za složenije aplikacije, naše API-je na nižem nivou omogućavaju naprednim ko
Naša dokumentacija uključuje [Uputstva za instalaciju](./installation.mdx) i [Uvodni tutorijal](./starter.md) za izgradnju vaše prve aplikacije.
Kada ste spremni za rad, [Koncepti na visokom nivou](./concepts.md) pružaju pregled modularne arhitekture LlamaIndex-a. Za praktične primere, pogledajte naše [Vodiče od početka do kraja](./end_to_end.md).
Kada ste spremni za rad, [Koncepti na visokom nivou](./getting_started/concepts.md) pružaju pregled modularne arhitekture LlamaIndex-a. Za praktične primere, pogledajte naše [Vodiče od početka do kraja](./end_to_end.md).
## 🗺️ Ekosistem
@@ -41,7 +41,7 @@ Za bolj kompleksne aplikacije naša nizkonivojska API omogoča naprednim uporabn
Naša dokumentacija vključuje [Navodila za namestitev](./installation.mdx) in [Vodič za začetek](./starter.md), ki vam pomagata zgraditi vašo prvo aplikacijo.
Ko ste pripravljeni, [Visokonivojski koncepti](./concepts.md) ponujajo pregled modularne arhitekture LlamaIndex-a. Za več praktičnih primerov si oglejte naše [Vodiče od začetka do konca](./end_to_end.md).
Ko ste pripravljeni, [Visokonivojski koncepti](./getting_started/concepts.md) ponujajo pregled modularne arhitekture LlamaIndex-a. Za več praktičnih primerov si oglejte naše [Vodiče od začetka do konca](./end_to_end.md).
## 🗺️ Ekosistem
@@ -41,7 +41,7 @@ Pre zložitejšie aplikácie naša nižšia úroveň API umožňuje pokročilým
Naša dokumentácia obsahuje [Inštalačné pokyny](./installation.mdx) a [Úvodný tutoriál](./starter.md) pre vytvorenie vašej prvej aplikácie.
Keď už máte všetko pripravené, [Vysokoúrovňové koncepty](./concepts.md) poskytujú prehľad o modulárnej architektúre LlamaIndexu. Pre viac praktických príkladov si prečítajte naše [Tutoriály od začiatku do konca](./end_to_end.md).
Keď už máte všetko pripravené, [Vysokoúrovňové koncepty](./getting_started/concepts.md) poskytujú prehľad o modulárnej architektúre LlamaIndexu. Pre viac praktických príkladov si prečítajte naše [Tutoriály od začiatku do konca](./end_to_end.md).
## 🗺️ Ekosystém
@@ -41,7 +41,7 @@ För mer komplexa applikationer tillåter våra lägre nivå-API:er avancerade a
Vår dokumentation inkluderar [Installationsinstruktioner](./installation.mdx) och en [Starterhandledning](./starter.md) för att bygga din första applikation.
När du är igång, ger [Högnivåkoncept](./concepts.md) en översikt över LlamaIndex modulära arkitektur. För mer praktiska exempel, titta igenom våra [Steg-för-steg handledningar](./end_to_end.md).
När du är igång, ger [Högnivåkoncept](./getting_started/concepts.md) en översikt över LlamaIndex modulära arkitektur. För mer praktiska exempel, titta igenom våra [Steg-för-steg handledningar](./end_to_end.md).
## 🗺️ Ekosystem
@@ -41,7 +41,7 @@ API ระดับสูงของเราช่วยให้ผู้ใ
เอกสารของเราประกอบด้วย[คำแนะนำการติดตั้ง](./installation.mdx)และ[บทแนะนำเบื้องต้น](./starter.md)เพื่อสร้างแอปพลิเคชันครั้งแรกของคุณ
เมื่อคุณเริ่มใช้งานแล้ว [แนวคิดระดับสูง](./concepts.md) มีภาพรวมของสถาปัตยกรรมแบบโมดูลของ LlamaIndex สำหรับตัวอย่างที่เป็นปฏิบัติจริงมากขึ้น โปรดดูที่ [บทแนะนำจบสู่จบ](./end_to_end.md) เพื่อตัวอย่างที่ใช้งานได้จริง
เมื่อคุณเริ่มใช้งานแล้ว [แนวคิดระดับสูง](./getting_started/concepts.md) มีภาพรวมของสถาปัตยกรรมแบบโมดูลของ LlamaIndex สำหรับตัวอย่างที่เป็นปฏิบัติจริงมากขึ้น โปรดดูที่ [บทแนะนำจบสู่จบ](./end_to_end.md) เพื่อตัวอย่างที่ใช้งานได้จริง
"
@@ -43,7 +43,7 @@ Daha karmaşık uygulamalar için, düşük seviyeli API'larımız, gelişmiş k
Dökümantasyonumuz, [Kurulum Talimatları](./installation.mdx) ve ilk uygulamanızı oluşturmanız için bir [Başlangıç Kılavuzu](./starter.md) içerir.
Çalışmaya başladıktan sonra, [Yüksek Düzeyli Kavramlar](./concepts.md) LlamaIndex'in modüler mimarisinin bir genel bakışını sunar. Daha fazla pratik örnek için [Uçtan Uca Öğreticilerimize](./end_to_end.md) göz atabilirsiniz.
Çalışmaya başladıktan sonra, [Yüksek Düzeyli Kavramlar](./getting_started/concepts.md) LlamaIndex'in modüler mimarisinin bir genel bakışını sunar. Daha fazla pratik örnek için [Uçtan Uca Öğreticilerimize](./end_to_end.md) göz atabilirsiniz.
## 🗺️ Ekosistem
@@ -41,7 +41,7 @@ LlamaIndex.TS надає основний набір інструментів,
Наша документація містить [Інструкції з встановлення](./installation.mdx) та [Посібник для початківців](./starter.md) для створення вашої першої програми.
Після того, як ви розпочнете роботу, [Високорівневі концепції](./concepts.md) містить огляд модульної архітектури LlamaIndex. Для більш практичних прикладів роботи, перегляньте наші [Посібники з кінця в кінець](./end_to_end.md).
Після того, як ви розпочнете роботу, [Високорівневі концепції](./getting_started/concepts.md) містить огляд модульної архітектури LlamaIndex. Для більш практичних прикладів роботи, перегляньте наші [Посібники з кінця в кінець](./end_to_end.md).
## 🗺️ Екосистема
@@ -41,7 +41,7 @@ API cấp cao của chúng tôi cho phép người dùng mới bắt đầu sử
Tài liệu của chúng tôi bao gồm [Hướng dẫn cài đặt](./installation.mdx) và [Hướng dẫn bắt đầu](./starter.md) để xây dựng ứng dụng đầu tiên của bạn.
Khi bạn đã sẵn sàng, [Khái niệm cấp cao](./concepts.md) cung cấp một cái nhìn tổng quan về kiến trúc mô-đun của LlamaIndex. Để có thêm ví dụ thực tế, hãy xem qua [Hướng dẫn từ đầu đến cuối](./end_to_end.md).
Khi bạn đã sẵn sàng, [Khái niệm cấp cao](./getting_started/concepts.md) cung cấp một cái nhìn tổng quan về kiến trúc mô-đun của LlamaIndex. Để có thêm ví dụ thực tế, hãy xem qua [Hướng dẫn từ đầu đến cuối](./end_to_end.md).
## 🗺️ Hệ sinh thái
@@ -39,7 +39,7 @@ LlamaIndex.TS 提供了一套核心工具,对于任何使用JavaScript和TypeS
我们的文档包括[安装说明](./installation.mdx)和一个[入门教程](./starter.md),帮助你构建第一个应用程序。
一旦你开始运行,[高级概念](./concepts.md)有一个LlamaIndex模块化架构的概览。更多实践例子,请浏览我们的[端到端教程](./end_to_end.md)。
一旦你开始运行,[高级概念](./getting_started/concepts.md)有一个LlamaIndex模块化架构的概览。更多实践例子,请浏览我们的[端到端教程](./end_to_end.md)。
## 🗺️ 生态系统
@@ -41,7 +41,7 @@ LlamaIndex.TS 提供了一組核心工具,對於使用 JavaScript 和 TypeScri
我們的文檔包括[安裝說明](./installation.mdx)和[入門教程](./starter.md),以構建您的第一個應用程序。
一旦您開始運行,[高級概念](./concepts.md)提供了 LlamaIndex 模塊化架構的概述。如果需要更多實際的操作示例,請查看我們的[端到端教程](./end_to_end.md)。
一旦您開始運行,[高級概念](./getting_started/concepts.md)提供了 LlamaIndex 模塊化架構的概述。如果需要更多實際的操作示例,請查看我們的[端到端教程](./end_to_end.md)。
## 🗺️ 生態系統
+12 -22
View File
@@ -1,29 +1,19 @@
# Simple Examples
# LlamaIndexTS Examples
Before running any of the examples, make sure to set your OpenAI environment variable:
Before running any of the code examples,
make sure you have basic knowledge of the [LlamaIndexTS](https://ts.llamaindex.ai/).
```bash
## Usage
```shell
# export your API key
export OPENAI_API_KEY="sk-..."
npx ts-node ./chatEngine.ts
```
There are two ways to run the examples, using the latest published version of `llamaindex` or using a local build.
## Build your own RAG app
## Using the latest published version
Make sure to call `npm install` before running these examples:
```bash
npm install
```shell
npx create llama
```
Then run the examples with `ts-node`, for example `npx ts-node vectorIndex.ts`
## Using the local build
```bash
pnpm install
pnpm --filter llamaindex build
pnpm link ../packages/core
```
Then run the examples with `ts-node`, for example `pnpx ts-node vectorIndex.ts`
+1 -1
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@@ -10,7 +10,7 @@ import {
VectorStoreIndex,
} from "llamaindex";
import essay from "./essay.js";
import essay from "./essay";
async function main() {
const document = new Document({ text: essay });
+1 -1
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@@ -3,7 +3,7 @@ import {
KeywordTableIndex,
KeywordTableRetrieverMode,
} from "llamaindex";
import essay from "./essay.js";
import essay from "./essay";
async function main() {
const document = new Document({ text: essay, id_: "essay" });
+1 -2
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@@ -1,7 +1,6 @@
{
"version": "0.0.3",
"private": true,
"name": "examples",
"private": true,
"dependencies": {
"@datastax/astra-db-ts": "^0.1.2",
"@notionhq/client": "^2.2.14",
+1 -1
View File
@@ -6,7 +6,7 @@ import {
VectorStoreIndex,
serviceContextFromDefaults,
} from "llamaindex";
import essay from "./essay.js";
import essay from "./essay";
async function main() {
const document = new Document({ text: essay, id_: "essay" });
+1 -1
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@@ -3,7 +3,7 @@ import {
storageContextFromDefaults,
VectorStoreIndex,
} from "llamaindex";
import essay from "./essay.js";
import essay from "./essay";
async function main() {
// Create Document object with essay
+1 -1
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@@ -1,6 +1,6 @@
import { Document, SubQuestionQueryEngine, VectorStoreIndex } from "llamaindex";
import essay from "./essay.js";
import essay from "./essay";
(async () => {
const document = new Document({ text: essay, id_: essay });
+1 -1
View File
@@ -5,7 +5,7 @@ import {
SummaryRetrieverMode,
serviceContextFromDefaults,
} from "llamaindex";
import essay from "./essay.js";
import essay from "./essay";
async function main() {
const serviceContext = serviceContextFromDefaults({
+1
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@@ -23,6 +23,7 @@ const together = new TogetherLLM({
for await (const message of generator) {
process.stdout.write(message.delta);
}
console.log();
const embedding = new TogetherEmbedding();
const vector = await embedding.getTextEmbedding("Hello world!");
console.log("vector:", vector);
+13 -1
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@@ -1,5 +1,17 @@
{
"extends": "../tsconfig.json",
"compilerOptions": {
"target": "es2016",
"module": "esnext",
"moduleResolution": "bundler",
"esModuleInterop": true,
"forceConsistentCasingInFileNames": true,
"strict": true,
"skipLibCheck": true,
"outDir": "./lib",
"tsBuildInfoFile": "./lib/.tsbuildinfo",
"incremental": true,
"composite": true,
},
"ts-node": {
"files": true,
"compilerOptions": {
+1 -1
View File
@@ -6,7 +6,7 @@ import {
SimilarityPostprocessor,
VectorStoreIndex,
} from "llamaindex";
import essay from "./essay.js";
import essay from "./essay";
// Customize retrieval and query args
async function main() {
+41
View File
@@ -0,0 +1,41 @@
import fs from "node:fs/promises";
import {
Document,
OpenAIEmbedding,
VectorStoreIndex,
serviceContextFromDefaults,
} from "llamaindex";
async function main() {
// Load essay from abramov.txt in Node
const path = "node_modules/llamaindex/examples/abramov.txt";
const essay = await fs.readFile(path, "utf-8");
// Create Document object with essay
const document = new Document({ text: essay, id_: path });
// Create service context and specify text-embedding-3-large
const embedModel = new OpenAIEmbedding({
model: "text-embedding-3-large",
dimensions: 1024,
});
const serviceContext = serviceContextFromDefaults({ embedModel });
// Split text and create embeddings. Store them in a VectorStoreIndex
const index = await VectorStoreIndex.fromDocuments([document], {
serviceContext,
});
// Query the index
const queryEngine = index.asQueryEngine();
const response = await queryEngine.query({
query: "What did the author do in college?",
});
// Output response
console.log(response.toString());
}
main().catch(console.error);
+6 -5
View File
@@ -12,12 +12,13 @@
"test": "turbo run test",
"type-check": "tsc -b --diagnostics",
"release": "pnpm run build:release && changeset publish",
"new-version": "pnpm run build:release && changeset version",
"new-snapshot": "pnpm run build:release && changeset version --snapshot"
"new-llamaindex": "pnpm run build:release && changeset version --ignore create-llama",
"new-create-llama": "pnpm run build:release && changeset version --ignore llamaindex",
"new-snapshots": "pnpm run build:release && changeset version --snapshot"
},
"devDependencies": {
"@changesets/cli": "^2.27.1",
"@turbo/gen": "^1.11.2",
"@turbo/gen": "^1.11.3",
"@types/jest": "^29.5.11",
"eslint": "^8.56.0",
"eslint-config-custom": "workspace:*",
@@ -26,8 +27,8 @@
"lint-staged": "^15.2.0",
"prettier": "^3.2.4",
"prettier-plugin-organize-imports": "^3.2.4",
"ts-jest": "^29.1.1",
"turbo": "^1.11.2",
"ts-jest": "^29.1.2",
"turbo": "^1.11.3",
"typescript": "^5.3.3"
},
"packageManager": "pnpm@8.10.5+sha256.a4bd9bb7b48214bbfcd95f264bd75bb70d100e5d4b58808f5cd6ab40c6ac21c5",
+27
View File
@@ -1,5 +1,32 @@
# llamaindex
## 0.0.50
### Patch Changes
- 8a729cd: fix bugs in Together.AI integration (thanks @Nutlope for reporting)
## 0.0.49
### Patch Changes
- eee3922: feat(qdrant): Add Qdrant Vector DB
- e2790da: Preview: Add ingestion pipeline (incl. different strategies to handle doc store duplicates)
- bff40f2: feat: use conditional exports
The benefit of conditional exports is we split the llamaindex into different files. This will improve the tree shake if you are building web apps.
This also requires node16 (see https://nodejs.org/api/packages.html#conditional-exports).
If you are seeing typescript issue `TS2724`('llamaindex' has no exported member named XXX):
1. update `moduleResolution` to `bundler` in `tsconfig.json`, more for the web applications like Next.js, and vite, but still works for ts-node or tsx.
2. consider the ES module in your project, add `"type": "module"` into `package.json` and update `moduleResolution` to `node16` or `nodenext` in `tsconfig.json`.
We still support both cjs and esm, but you should update `tsconfig.json` to make the typescript happy.
- 2d8845b: feat(extractors): add keyword extractor and base extractor
## 0.0.48
### Patch Changes
+3 -3
View File
@@ -1,6 +1,6 @@
{
"name": "llamaindex",
"version": "0.0.48",
"version": "0.0.50",
"license": "MIT",
"dependencies": {
"@anthropic-ai/sdk": "^0.9.1",
@@ -11,7 +11,7 @@
"@qdrant/js-client-rest": "^1.7.0",
"@xenova/transformers": "^2.10.0",
"assemblyai": "^4.0.0",
"chromadb": "^1.7.3",
"chromadb": "~1.7.3",
"file-type": "^18.7.0",
"js-tiktoken": "^1.0.8",
"lodash": "^4.17.21",
@@ -19,7 +19,7 @@
"md-utils-ts": "^2.0.0",
"mongodb": "^6.3.0",
"notion-md-crawler": "^0.0.2",
"openai": "^4.20.1",
"openai": "^4.26.0",
"papaparse": "^5.4.1",
"pathe": "^1.1.2",
"pdfjs-dist": "4.0.269",
-2
View File
@@ -6,6 +6,4 @@ export const DEFAULT_CHUNK_OVERLAP = 20;
export const DEFAULT_CHUNK_OVERLAP_RATIO = 0.1;
export const DEFAULT_SIMILARITY_TOP_K = 2;
// NOTE: for text-embedding-ada-002
export const DEFAULT_EMBEDDING_DIM = 1536;
export const DEFAULT_PADDING = 5;
@@ -9,28 +9,55 @@ import {
import { OpenAISession, getOpenAISession } from "../llm/openai";
import { BaseEmbedding } from "./types";
export enum OpenAIEmbeddingModelType {
TEXT_EMBED_ADA_002 = "text-embedding-ada-002",
}
export const ALL_OPENAI_EMBEDDING_MODELS = {
"text-embedding-ada-002": {
dimensions: 1536,
maxTokens: 8191,
},
"text-embedding-3-small": {
dimensions: 1536,
dimensionOptions: [512, 1536],
maxTokens: 8191,
},
"text-embedding-3-large": {
dimensions: 3072,
dimensionOptions: [256, 1024, 3072],
maxTokens: 8191,
},
};
export class OpenAIEmbedding extends BaseEmbedding {
model: OpenAIEmbeddingModelType | string;
/** embeddding model. defaults to "text-embedding-ada-002" */
model: string;
/** number of dimensions of the resulting vector, for models that support choosing fewer dimensions. undefined will default to model default */
dimensions: number | undefined;
// OpenAI session params
/** api key */
apiKey?: string = undefined;
/** maximum number of retries, default 10 */
maxRetries: number;
/** timeout in ms, default 60 seconds */
timeout?: number;
/** other session options for OpenAI */
additionalSessionOptions?: Omit<
Partial<OpenAIClientOptions>,
"apiKey" | "maxRetries" | "timeout"
>;
/** session object */
session: OpenAISession;
/**
* OpenAI Embedding
* @param init - initial parameters
*/
constructor(init?: Partial<OpenAIEmbedding> & { azure?: AzureOpenAIConfig }) {
super();
this.model = OpenAIEmbeddingModelType.TEXT_EMBED_ADA_002;
this.model = init?.model ?? "text-embedding-ada-002";
this.dimensions = init?.dimensions; // if no dimensions provided, will be undefined/not sent to OpenAI
this.maxRetries = init?.maxRetries ?? 10;
this.timeout = init?.timeout ?? 60 * 1000; // Default is 60 seconds
@@ -76,6 +103,7 @@ export class OpenAIEmbedding extends BaseEmbedding {
private async getOpenAIEmbedding(input: string) {
const { data } = await this.session.openai.embeddings.create({
model: this.model,
dimensions: this.dimensions, // only sent to OpenAI if set by user
input,
});
+18 -8
View File
@@ -1,16 +1,26 @@
import { OpenAIEmbedding } from "./OpenAIEmbedding";
export class TogetherEmbedding extends OpenAIEmbedding {
override model: string;
constructor(init?: Partial<OpenAIEmbedding>) {
const {
apiKey = process.env.TOGETHER_API_KEY,
additionalSessionOptions = {},
model = "togethercomputer/m2-bert-80M-32k-retrieval",
...rest
} = init ?? {};
if (!apiKey) {
throw new Error("Set Together Key in TOGETHER_API_KEY env variable"); // Tell user to set correct env variable, and not OPENAI_API_KEY
}
additionalSessionOptions.baseURL =
additionalSessionOptions.baseURL ?? "https://api.together.xyz/v1";
super({
apiKey: process.env.TOGETHER_API_KEY,
...init,
additionalSessionOptions: {
...init?.additionalSessionOptions,
baseURL: "https://api.together.xyz/v1",
},
apiKey,
additionalSessionOptions,
model,
...rest,
});
this.model = init?.model ?? "togethercomputer/m2-bert-80M-32k-retrieval";
}
}
+8 -1
View File
@@ -41,14 +41,21 @@ import {
export const GPT4_MODELS = {
"gpt-4": { contextWindow: 8192 },
"gpt-4-32k": { contextWindow: 32768 },
"gpt-4-32k-0613": { contextWindow: 32768 },
"gpt-4-turbo-preview": { contextWindow: 128000 },
"gpt-4-1106-preview": { contextWindow: 128000 },
"gpt-4-vision-preview": { contextWindow: 8192 },
"gpt-4-0125-preview": { contextWindow: 128000 },
"gpt-4-vision-preview": { contextWindow: 128000 },
};
// NOTE we don't currently support gpt-3.5-turbo-instruct and don't plan to in the near future
export const GPT35_MODELS = {
"gpt-3.5-turbo": { contextWindow: 4096 },
"gpt-3.5-turbo-0613": { contextWindow: 4096 },
"gpt-3.5-turbo-16k": { contextWindow: 16384 },
"gpt-3.5-turbo-16k-0613": { contextWindow: 16384 },
"gpt-3.5-turbo-1106": { contextWindow: 16384 },
"gpt-3.5-turbo-0125": { contextWindow: 16384 },
};
/**
+26 -2
View File
@@ -17,6 +17,14 @@ const ALL_AZURE_OPENAI_CHAT_MODELS = {
},
"gpt-4": { contextWindow: 8192, openAIModel: "gpt-4" },
"gpt-4-32k": { contextWindow: 32768, openAIModel: "gpt-4-32k" },
"gpt-4-vision-preview": {
contextWindow: 128000,
openAIModel: "gpt-4-vision-preview",
},
"gpt-4-1106-preview": {
contextWindow: 128000,
openAIModel: "gpt-4-1106-preview",
},
};
const ALL_AZURE_OPENAI_EMBEDDING_MODELS = {
@@ -25,13 +33,29 @@ const ALL_AZURE_OPENAI_EMBEDDING_MODELS = {
openAIModel: "text-embedding-ada-002",
maxTokens: 8191,
},
"text-embedding-3-small": {
dimensions: 1536,
dimensionOptions: [512, 1536],
openAIModel: "text-embedding-3-small",
maxTokens: 8191,
},
"text-embedding-3-large": {
dimensions: 3072,
dimensionOptions: [256, 1024, 3072],
openAIModel: "text-embedding-3-large",
maxTokens: 8191,
},
};
const ALL_AZURE_API_VERSIONS = [
"2022-12-01",
"2023-05-15",
"2023-06-01-preview",
"2023-07-01-preview",
"2023-03-15-preview", // retiring 2024-04-02
"2023-06-01-preview", // retiring 2024-04-02
"2023-07-01-preview", // retiring 2024-04-02
"2023-08-01-preview", // retiring 2024-04-02
"2023-09-01-preview",
"2023-12-01-preview",
];
const DEFAULT_API_VERSION = "2023-05-15";
+18 -6
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@@ -2,13 +2,25 @@ import { OpenAI } from "./LLM";
export class TogetherLLM extends OpenAI {
constructor(init?: Partial<OpenAI>) {
const {
apiKey = process.env.TOGETHER_API_KEY,
additionalSessionOptions = {},
model = "togethercomputer/llama-2-7b-chat",
...rest
} = init ?? {};
if (!apiKey) {
throw new Error("Set Together Key in TOGETHER_API_KEY env variable"); // Tell user to set correct env variable, and not OPENAI_API_KEY
}
additionalSessionOptions.baseURL =
additionalSessionOptions.baseURL ?? "https://api.together.xyz/v1";
super({
...init,
apiKey: process.env.TOGETHER_API_KEY,
additionalSessionOptions: {
...init?.additionalSessionOptions,
baseURL: "https://api.together.xyz/v1",
},
apiKey,
additionalSessionOptions,
model,
...rest,
});
}
}
@@ -20,6 +20,7 @@ export class PGVectorStore implements VectorStore {
private schemaName: string = PGVECTOR_SCHEMA;
private tableName: string = PGVECTOR_TABLE;
private connectionString: string | undefined = undefined;
private dimensions: number = 1536;
private db?: pg.Client;
@@ -38,15 +39,18 @@ export class PGVectorStore implements VectorStore {
* @param {string} config.schemaName - The name of the schema (optional). Defaults to PGVECTOR_SCHEMA.
* @param {string} config.tableName - The name of the table (optional). Defaults to PGVECTOR_TABLE.
* @param {string} config.connectionString - The connection string (optional).
* @param {number} config.dimensions - The dimensions of the embedding model.
*/
constructor(config?: {
schemaName?: string;
tableName?: string;
connectionString?: string;
dimensions?: number;
}) {
this.schemaName = config?.schemaName ?? PGVECTOR_SCHEMA;
this.tableName = config?.tableName ?? PGVECTOR_TABLE;
this.connectionString = config?.connectionString;
this.dimensions = config?.dimensions ?? 1536;
}
/**
@@ -108,7 +112,7 @@ export class PGVectorStore implements VectorStore {
collection VARCHAR,
document TEXT,
metadata JSONB DEFAULT '{}',
embeddings VECTOR(1536)
embeddings VECTOR(${this.dimensions})
)`;
await db.query(tbl);
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