RELEASING: Releasing 5 package(s)

Releases:
  llamaindex@0.2.0
  examples@0.0.4
  @llamaindex/core-test@0.0.2
  llamaindex-loader-example@null
  @llamaindex/experimental@0.0.3

[skip ci]

.changeset/clever-doors-invite.md

@@ -1,5 +0,0 @@
----
-"llamaindex": patch
----
-
-feat: experimental package + json query engine

.changeset/eight-dogs-burn.md

@@ -1,12 +0,0 @@
----
-"llamaindex": patch
-"@llamaindex/core-test": patch
----
-
-- Add missing exports:
-  - `IndexStructType`,
-  - `IndexDict`,
-  - `jsonToIndexStruct`,
-  - `IndexList`,
-  - `IndexStruct`
-- Fix `IndexDict.toJson()` method

.changeset/khaki-rivers-unite.md

@@ -1,5 +0,0 @@
----
-"llamaindex": patch
----
-
-Add streaming to agents

.changeset/strange-waves-sit.md

@@ -1,5 +0,0 @@
----
-"llamaindex": minor
----
-
-Use parameter object for retrieve function of Retriever (to align usage with query function of QueryEngine)

.github/workflows/e2e.yml

@@ -1,68 +0,0 @@
-name: E2E Tests
-on:
-  push:
-    branches: [main]
-  pull_request:
-    paths:
-      - "packages/create-llama/**"
-      - ".github/workflows/e2e.yml"
-    branches: [main]
-
-env:
-  POETRY_VERSION: "1.6.1"
-
-jobs:
-  e2e:
-    name: create-llama
-    timeout-minutes: 60
-    strategy:
-      fail-fast: true
-      matrix:
-        node-version: [18, 20]
-        python-version: ["3.11"]
-        os: [macos-latest, windows-latest]
-    defaults:
-      run:
-        shell: bash
-    runs-on: ${{ matrix.os }}
-    steps:
-      - uses: actions/checkout@v4
-      - name: Set up python ${{ matrix.python-version }}
-        uses: actions/setup-python@v4
-        with:
-          python-version: ${{ matrix.python-version }}
-      - name: Install Poetry
-        uses: snok/install-poetry@v1
-        with:
-          version: ${{ env.POETRY_VERSION }}
-      - uses: pnpm/action-setup@v2
-      - name: Setup Node.js ${{ matrix.node-version }}
-        uses: actions/setup-node@v4
-        with:
-          node-version: ${{ matrix.node-version }}
-          cache: "pnpm"
-      - name: Install dependencies
-        run: pnpm install
-      - name: Install Playwright Browsers
-        run: pnpm exec playwright install --with-deps
-        working-directory: ./packages/create-llama
-      - name: Build create-llama
-        run: pnpm run build
-        working-directory: ./packages/create-llama
-      - name: Pack
-        run: pnpm pack --pack-destination ./output
-        working-directory: ./packages/create-llama
-      - name: Extract Pack
-        run: tar -xvzf ./output/*.tgz -C ./output
-        working-directory: ./packages/create-llama
-      - name: Run Playwright tests
-        run: pnpm exec playwright test
-        env:
-          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
-        working-directory: ./packages/create-llama
-      - uses: actions/upload-artifact@v3
-        if: always()
-        with:
-          name: playwright-report
-          path: ./packages/create-llama/playwright-report/
-          retention-days: 30

.gitignore

@@ -45,7 +45,6 @@ playwright-report/
 blob-report/
 playwright/.cache/
 .tsbuildinfo
-packages/create-llama/e2e/cache
 
 # intellij
 **/.idea

.prettierignore

@@ -4,4 +4,3 @@ pnpm-lock.yaml
 lib/
 dist/
 .docusaurus/
-packages/create-llama/e2e/cache/

CONTRIBUTING.md

@@ -84,8 +84,7 @@ Any changes you make should be reflected in the browser. If you need to regenera
 To publish a new version of the library, run
 
 ```shell
-pnpm new-llamaindex
-pnpm new-create-llama
+pnpm new-version
 pnpm release
 git push # push to the main branch
 git push --tags

README.md

@@ -121,6 +121,42 @@ const nextConfig = {
 module.exports = nextConfig;
 ```
 
+### NextJS with Milvus:
+
+As proto files are not loaded per default in NextJS, you'll need to add the following to your next.config.js to have it load the proto files.
+
+```js
+const path = require("path");
+const CopyWebpackPlugin = require("copy-webpack-plugin");
+
+// next.config.js
+/** @type {import('next').NextConfig} */
+const nextConfig = {
+  webpack: (config, { isServer }) => {
+    if (isServer) {
+      // Copy the proto files to the server build directory
+      config.plugins.push(
+        new CopyWebpackPlugin({
+          patterns: [
+            {
+              from: path.join(
+                __dirname,
+                "node_modules/@zilliz/milvus2-sdk-node/dist",
+              ),
+              to: path.join(__dirname, ".next"),
+            },
+          ],
+        }),
+      );
+    }
+    // Important: return the modified config
+    return config;
+  },
+};
+
+module.exports = nextConfig;
+```
+
 ## Supported LLMs:
 
 - OpenAI GPT-3.5-turbo and GPT-4

examples/CHANGELOG.md

@@ -0,0 +1,14 @@
+# examples
+
+## 0.0.4
+
+### Patch Changes
+
+- d2e8d0c: add support for Milvus vector store
+- Updated dependencies [d2e8d0c]
+- Updated dependencies [aefc326]
+- Updated dependencies [484a710]
+- Updated dependencies [d766bd0]
+- Updated dependencies [dd95927]
+- Updated dependencies [bf583a7]
+  - llamaindex@0.2.0

examples/anthropic/haiku.ts

@@ -0,0 +1,19 @@
+import { Anthropic } from "llamaindex";
+
+(async () => {
+  const anthropic = new Anthropic({
+    apiKey: process.env.ANTHROPIC_API_KEY,
+    model: "claude-3-haiku",
+  });
+  const result = await anthropic.chat({
+    messages: [
+      { content: "You want to talk in rhymes.", role: "system" },
+      {
+        content:
+          "How much wood would a woodchuck chuck if a woodchuck could chuck wood?",
+        role: "user",
+      },
+    ],
+  });
+  console.log(result);
+})();

examples/astradb/README.md

@@ -32,10 +32,10 @@ run `ts-node astradb/example`
 
 This sample loads the same dataset of movie reviews as the Astra Portal sample dataset. (Feel free to load the data in your the Astra Data Explorer to compare)
 
-run `ts-node astradb/load`
+run `npx ts-node astradb/load`
 
 ### Use RAG to Query the data
 
 Check out your data in the Astra Data Explorer and change the sample query as you see fit.
 
-run `ts-node astradb/query`
+run `npx ts-node astradb/query`

examples/milvus/README.md

@@ -0,0 +1,34 @@
+# Milvus Vector Store
+
+Here are two sample scripts which work with loading and querying data from a Milvus Vector Store.
+
+## Prerequisites
+
+- An Milvus Vector Database
+  - Hosted https://milvus.io/
+  - Self Hosted https://milvus.io/docs/install_standalone-docker.md
+- An OpenAI API Key
+
+## Setup
+
+1. Set your env variables:
+
+- `MILVUS_ADDRESS`: Address of your Milvus Vector Store (like localhost:19530)
+- `MILVUS_USERNAME`: empty or username for your Milvus Vector Store
+- `MILVUS_PASSWORD`: empty or password for your Milvus Vector Store
+- `OPENAI_API_KEY`: Your OpenAI key
+
+2. `cd` Into the `examples` directory
+3. run `npm i`
+
+## Load the data
+
+This sample loads the same dataset of movie reviews as sample dataset. You can install https://github.com/zilliztech/attu to inspect the loaded data.
+
+run `npx ts-node milvus/load`
+
+## Use RAG to Query the data
+
+Check out your data in Attu and change the sample query as you see fit.
+
+run `npx ts-node milvus/query`

examples/milvus/data/movie_reviews.csv

@@ -0,0 +1,101 @@
+title,reviewid,creationdate,criticname,originalscore,reviewstate,reviewtext
+Beavers,1145982,2003-05-23,Ivan M. Lincoln,3.5/4,fresh,"Timed to be just long enough for most youngsters' brief attention spans -- and it's packed with plenty of interesting activity, both on land and under the water."
+Blood Mask,1636744,2007-06-02,The Foywonder,1/5,rotten,"It doesn't matter if a movie costs 300 million or only 300 dollars; good is good and bad is bad, and Bloodmask: The Possession of Nicole Lameroux is just plain bad."
+City Hunter: Shinjuku Private Eyes,2590987,2019-05-28,Reuben Baron,,fresh,"The choreography is so precise and lifelike at points one might wonder whether the movie was rotoscoped, but no live-action reference footage was used. The quality is due to the skill of the animators and Kodama's love for professional wrestling."
+City Hunter: Shinjuku Private Eyes,2558908,2019-02-14,Matt Schley,2.5/5,rotten,The film's out-of-touch attempts at humor may find them hunting for the reason the franchise was so popular in the first place.
+Dangerous Men,2504681,2018-08-29,Pat Padua,,fresh,Its clumsy determination is endearing and sometimes wildly entertaining
+Dangerous Men,2299284,2015-12-13,Eric Melin,4/5,fresh,"With every new minute, there's another head-scratching choice that's bound to elicit some amazing out-loud responses, so this feels like a true party flick."
+Dangerous Men,2295858,2015-11-22,Matt Donato,7/10,fresh,"Emotionless reaction shots, zero characterization, guns that have absolutely no special effects when blasted - Dangerous Men is rare winning dish from a one star restaurant."
+Dangerous Men,2295338,2015-11-19,Peter Keough,0.5/4,rotten,"Conceivably, it could serve as a primer for students on how not to make a movie, and perhaps as a deconstruction of filmic conventions for the more theoretical minded."
+Dangerous Men,2294641,2015-11-16,Jason Wilson,3/10,rotten,"If you're not a fan of garbage cinema, even for the fun of it, Dangerous Men is best to be avoided."
+Dangerous Men,2294129,2015-11-12,Soren Andersen,0/4,rotten,"""Dangerous Men,"" the picture's production notes inform, took 26 years to reach the big screen. After having seen it, I wonder: What was the rush?"
+Dangerous Men,2293902,2015-11-12,Maitland McDonagh,,rotten,Will entertain some viewers and infuriate others with its clunky mix of feminist fury and awkward action sequences.
+Dangerous Men,2293900,2015-11-12,Marjorie Baumgarten,1.5/5,rotten,"This is a bad movie, but one that awakens your senses every so often with flashes of originality and abundant self-belief."
+Dangerous Men,2293815,2015-11-12,Katie Rife,B+,fresh,"Ridiculous, artless, and wildly entertaining, Dangerous Men is more than the sum of its fascinatingly misguided parts, although it will take a special sort of moviegoer to truly appreciate (or endure, depending on your perspective) its charms."
+Dangerous Men,2293605,2015-11-11,Amy Nicholson,C,fresh,To sit through it feels like honoring the dreamers of the world who at least get shit done. Is it terrible? Of course. Is there belly-dancing? Duh.
+Small Town Wisconsin,102711819,2022-07-22,Peter Gray,,fresh,Small Town Wisconsin could hit some home truths for viewers, and though being faced with the truth isn’t always pleasant, it feels necessary in growing towards a happier fruition.
+Small Town Wisconsin,102711545,2022-07-22,Tim Grierson,,fresh,"This low-key drama has lovely interludes and some nicely understated performances, although director Niels Mueller doesn’t glean too many new insights from Jason Naczek’s familiar story..."
+Small Town Wisconsin,102700937,2022-06-16,Sumner Forbes,8.5/10,fresh,"Small Town Wisconsin is a success in almost every regard, and if you can see over the legions of cheeseheads in the rows ahead of you, it shouldn’t be missed."
+Small Town Wisconsin,102699897,2022-06-14,Tara McNamara,3/5,fresh,Just like Wayne, Small Town Wisconsin has flaws, but the poignancy of the story will stick with you for a long time.
+Small Town Wisconsin,102698744,2022-06-10,Rob Thomas,3/4,fresh,It’s a movie with its heart in the right place, and does both small town and big city Wisconsin proud.
+Small Town Wisconsin,102698639,2022-06-10,Todd Jorgenson,,rotten,Despite some intriguing character dynamics and performances that generate sympathy for this fractured family, the film stumbles when it veers into melodrama without the narrative dexterity to tackle its weightier ambitions.
+Small Town Wisconsin,102698482,2022-06-10,Jackie K. Cooper,7/10,fresh,This is the kind of movie that draws you so deeply into its story you are reluctant to let it end.
+Small Town Wisconsin,102698164,2022-06-09,Glenn Kenny,,fresh,"Mueller’s direction is patient and sensitive, the cast is accomplished and committed, and the picture’s comedic aspects sometimes earn a chuckle."
+Small Town Wisconsin,102697854,2022-06-08,Brian Orndorf,B+,fresh,Naczek isn't interested in making a soap opera with this examination of fallibility, going somewhere much more authentic when exploring character aches and pains.
+Small Town Wisconsin,102695788,2022-06-02,Eddie Harrison,4/5,fresh,…a warm-hearted story of everyday life that’s easy to recommend for those who like films about people rather than portals and vortexes…
+Small Town Wisconsin,102695250,2022-05-31,Laura Clifford,C,rotten,Debuting screenwriter Jason Naczek has concocted a manchild redemption story using metaphors as heavy as a hammer and a fairy godmother who makes everything alright with a seeming flip of the switch.
+Small Town Wisconsin,2733251,2020-10-12,Jared Mobarak,B,fresh,Small Town Wisconsin is always proving itself to be more than its familiar premise thanks to Naczek's ability to infuse a lot more drama into the mix than one custody battle.
+Tejano,2564925,2019-03-07,Joe Friar,3/4,fresh,The story of a South Texas ranch hand who gets mixed up with a Mexican cartel moves with pulse-pounding velocity and features top performances from a talented cast of actors with Texas roots.
+Tejano,2557738,2019-02-12,Cary Darling,4/5,fresh,"An entertaining blast of Texas noir that nods toward the work of the Coen brothers, Quentin Tarantino and fellow Austinite Greg Kwedar's 2016 low-budget thriller ""Transpecos"" as well as ""Breaking Bad."""
+Tejano,2547231,2019-01-10,Danielle White,3/5,fresh,The story itself slithers with twists and turns and unexpected betrayals. It's almost ridiculous how many characters die in this film.
+Tejano,2530119,2018-11-08,Chris Salce,9/10,fresh,"Tejano is one of those films that can be described as a hidden gem as it sneaks under the radar and will have you talking, telling your friends about it, and wanting to watch it again."
+Death of a Salesman,2770637,2021-02-23,Michael Dougan,,fresh,"Miller has taken a small, intimate tale and expanded it into a treatise on larger themes, primarily the abuse of the American Dream."
+Death of a Salesman,1950734,2011-01-02,Randy White,5/5,fresh,A classic American tragedy.
+Death of a Salesman,1422415,2005-08-04,Jules Brenner,4/5,fresh,
+Death of a Salesman,1409415,2005-07-05,Emanuel Levy,3/5,fresh,
+Death of a Salesman,839546,2003-02-06,Frederic and Mary Ann Brussat,,fresh,"Death of a Salesman, directed by Volker Schlondorff, draws out the multiple meanings of this Pulitzer Prize-winning play by Arthur Miller about change, family and fatherhood, work and love."
+Death of a Salesman,788410,2002-09-29,Dan Lybarger,4/5,fresh,"Schlndorff's artificial settings and some amazing performances help keep this from looking like a typical ""filmed play."""
+Death of a Salesman,751951,2002-08-08,Cory Cheney,4/5,fresh,
+Death of a Salesman,743794,2002-07-26,Bob Grimm,5/5,fresh,
+Death of a Salesman,743291,2002-07-26,Scott Weinberg,5/5,fresh,They MAKE you watch it in English class for a good reason!
+Sahara,1137710,2003-05-13,Dragan Antulov,5/10,fresh,
+The Debt,2628192,2019-09-20,Diego Batlle,,fresh,A Bresson-esque movie that is always enigmatic. [Full Review in Spanish]
+The Debt,2627988,2019-09-20,Gaspar Zimerman,,fresh,The story [Director Gustavo Fontán] tells is an excuse to give way to the exploration of feelings and sensations that avoid verbality. [Full review in Spanish]
+Peppermint Candy,2725008,2020-09-16,A.S. Hamrah,,fresh,"South Korean political history of the previous twenty years, Peppermint Candy is not tempered by its hysterical edge, which adds unpredictable violence to its vignettes of romantic, domestic, and business failure."
+Peppermint Candy,2541271,2018-12-16,Panos Kotzathanasis,,fresh,"Lee Chang-dong presents a melodrama that stands apart from the plethora of similar productions due to its intense political element, because it doesn't lose its seriousness at any point and because it doesn't become hyperbolic in his effort to draw tears"
+Peppermint Candy,1883708,2010-05-11,Anton Bitel,,fresh,"This is Korea's millennial elegy, filtering its search for times past through a confection no less bittersweet than Proust's madeleine."
+Peppermint Candy,1706014,2008-01-29,Beth Accomando,9/10,fresh,The film offers a heartbreaking drama told in reverse chronology and spanning twenty years in both the life of the main character and the political history of Korea.
+Peppermint Candy,1231988,2003-12-22,Greg Muskewitz,2/5,rotten,
+Peppermint Candy,1187104,2003-08-14,Joshua Tanzer,4/4,fresh,"It's a story about the original sin of a nation as well as one character. There has rarely been a better film made, ever"
+Prison Girls,2475348,2018-05-03,Roger Ebert,,rotten,Prison Girls didn't have a lot of prison sets because it was a big-budget exploitation movie. Maybe.
+Gimme the Power,2575688,2019-04-09,Afroxander,,fresh,"Rubio's film shows ambition where none is required, making Gimme the Power a lot like Molotov's music: politically engaged without having to take itself too seriously."
+Paa,2673089,2020-02-27,Nikhat Kazmi,3.5/5,fresh,"The film, which peters off into vague sub-plots about slum redevelopment and unwarranted media-bashing in the first half, suddenly picks up and scales new heights in the second half."
+Paa,2578129,2019-04-17,Shubhra Gupta,2/5,rotten,"Disappointingly, Paa is not as out-of-the-box as it could have been."
+Paa,2429810,2017-10-24,Anil Sinanan,3/5,rotten,Will Auro survive to know his Pa and reunite his parents? Forget about the disease: this is a vanity vehicle designed to showcase the Big B's versatility.
+Paa,1860476,2009-12-14,Frank Lovece,,rotten,This would-be tearjerker without the musical numbers of typical Bollywood fare is for die-hard Amitabh Bachchan fans only.
+Paa,1860473,2009-12-14,David Chute,,fresh,"The film owes much of its interest to the alertness and sincerity of the younger Bachchan and the luminous Vidya Balan as the anguished parents, and to the soft wash of the tasteful playback songs supplied by Ilaiyaraaja."
+Paa,1858964,2009-12-05,Avi Offer,5.85/10,rotten,"Well-acted, funny and occasionally witty with terrific make-up design. However, it's often convoluted, awkwardly paced and too uneven as a whole."
+Paa,1858853,2009-12-04,Frank Lovece,,fresh,"A would-be tearjerker without the singing-dancing musical numbers of typical Bollywood fare seen in the U.S., the lackluster Paa is for die-hard Amitabh Bachchan fans only%u2014of which there is no small number."
+Paa,1858816,2009-12-04,Rachel Saltz,3/5,fresh,Odd and sometimes oddly affecting.
+Alraune (A Daughter of Destiny) (Mandrake) (Unholy Love),2835964,2021-10-30,Erich Hellmund-Waldow,,fresh,"The acting is not only artistic, it is also as realistic as can be possible in such a film."
+Alraune (A Daughter of Destiny) (Mandrake) (Unholy Love),2357086,2016-10-17,C. Hooper Trask,,fresh,"Aimed straight for the gooseflesh, it strikes directly into the centre of the target."
+Toorbos,2760593,2021-01-29,Neil Young,,fresh,Built around a luminous and intriguing central performance by dancer-actor Elani Dekker.
+Toorbos,2752827,2020-12-21,Guy Lodge,,fresh,"A satisfying marriage of folky period romance and environmental parable from the misty, mossy depths of South Africa's Knysna forest region..."
+Connors' War,1555113,2006-11-09,David Nusair,1.5/4,rotten,"...although Criss does show some potential as a performer, his efforts to step into the shoes of a blind character are laughable."
+Connors' War,1539106,2006-09-19,Scott Weinberg,2/5,rotten,"Standard cable fodder all the way, with only a few solid action scenes and maybe one colorful performance in the whole thing."
+Born to Kill,2710947,2020-08-05,Mike Massie,10/10,fresh,"One of the most acerbic of all films noir, boasting essentially no redeemable characters (or a wealth of deliciously evil villains) while also being utterly enthralling."
+Born to Kill,2340106,2016-07-15,David Nusair,3/4,fresh,...a fairly typical film-noir premise that's employed to watchable yet entirely unmemorable effect by Robert Wise...
+Born to Kill,1507021,2006-05-16,Nick Schager,B,fresh,Competent if slightly too tame for a supposedly sleazy story.
+Born to Kill,1501617,2006-05-01,Fernando F. Croce,,fresh,"The usually meek Robert Wise trades his chameleonic tastefulness for full-on, jazzy misanthropy in this nasty melodrama."
+Born to Kill,1433953,2005-09-09,Jeffrey M. Anderson,3/4,fresh,"Hard to watch, but effective and alluring nonetheless."
+Born to Kill,1123980,2003-04-02,Dennis Schwartz,C,rotten,A revolting B film noir...
+The Soong Sisters,1402087,2005-06-15,Emanuel Levy,3/5,fresh,
+La Sapienza,102772380,2023-01-24,Vadim Rizov,,fresh,"Sapienza is a pretty lovely film. Symmetricities are everywhere, starting with that opening architectural showreel, which deliberately avoids perfect symmetricity..."
+La Sapienza,2767839,2021-02-14,Dustin Chang,,fresh,Their sincere expression of these thoughts rings true and melts away its artificiality in its presentation soon enough. This is the beauty of La Sapienza and Green films in general.
+La Sapienza,2598336,2019-06-18,C.J. Prince,,fresh,"It's a nice entry point into a peculiar cinematic universe, and those willing to open themselves to it will find a lot to enjoy."
+La Sapienza,2503963,2018-08-28,Charles Mudede,,fresh,"If architecture aspires to the condition of music, the acting in La Sapienza aspires to the condition of architecture. You will love the ending of this very original and elegant and arty work."
+La Sapienza,2314368,2016-03-12,Forrest Cardamenis,B,fresh,This startling architectural juxtaposition feels like a wake-up call.
+La Sapienza,2275677,2015-08-03,Nicole Armour,,fresh,"While Green's film is dense with historical fact and theory, it's not averse to plumbing life's mysteries. Suffused with warmth, it expresses a potent admiration for human striving and accomplishment."
+La Sapienza,2273804,2015-07-23,Norman Wilner,2/5,rotten,"The uncomplicated narrative resists stylization; Green's presentation turns everyone into mannequins, rendering their emotions theoretical. That may well be his point, but it didn't work for me."
+La Sapienza,2269287,2015-06-26,Sam Lubell,,fresh,"On the surface, writer-director Eugne Green's film ""La Sapienza"" is slow, strange and awkward - but stick with it and it may win you over."
+La Sapienza,2265997,2015-06-05,Rob Garratt,4/5,fresh,"Layered with reels of swirling shots of Rome's most beautiful buildings -- all crucially shot from the ground upwards, staring at the heavens-- La Sapienza is visually stunning."
+La Sapienza,2265990,2015-06-05,Boyd van Hoeij,,fresh,"The Sapience juxtaposes insights on how people are emotionally connected with ruminations on the buildings and spaces through which they move, in which they live and, in Alexandre's case, which they also create."
+La Sapienza,2265989,2015-06-05,Robert Horton,3/4,fresh,"If you can groove into this non-realistic mode, the film casts a spell."
+La Sapienza,2265790,2015-06-04,Tom Keogh,3.5/4,fresh,A beautiful space for people and light.
+La Sapienza,2255621,2015-04-09,Wesley Morris,,rotten,This kind of formalism needs to do more than walk through classical wonders. It should want to create cinema that can stand near or beside them. This movie defensively consecrates what's already there. You don't need a film to do that.
+La Sapienza,2255195,2015-04-08,Scott Foundas,,fresh,"An exquisite rumination on life, love and art that tickles the heart and mind in equal measure."
+La Sapienza,2252858,2015-03-23,Richard Brody,,fresh,"Green's richly textured, painterly images fuse with the story to evoke the essence of humane urbanity and the relationships that it fosters, whether educational, familial, or erotic."
+La Sapienza,2252553,2015-03-20,Ignatiy Vishnevetsky,B+,fresh,"Green doesn't so much use his characters as mouthpieces as emotionally invest them in art, turning opinions into feelings."
+La Sapienza,2252541,2015-03-20,Godfrey Cheshire,4/4,fresh,"""La Sapienza"" strikes this reviewer as easily the most astonishing and important movie to emerge from France in quite some time."
+La Sapienza,2252452,2015-03-19,A.O. Scott,,fresh,The movie is an unapologetically rarefied undertaking and at the same time a gracious and inviting film.
+La Sapienza,2252301,2015-03-19,David Noh,,rotten,"Pretentious, stuffy and slow. There's some beautiful scenery here but oh, what you must put up with to earn it!"
+La Sapienza,2252028,2015-03-18,Noel Murray,3/5,fresh,"While La Sapienza is unsatisfying as drama, it's frequently beautiful just as a tour through architecturally significant Italian buildings."
+La Sapienza,2251985,2015-03-17,David Ehrlich,3/5,fresh,La Sapienza  alternately feels like a self-reflexive love story or a haunted history lesson -- its best scenes play like both.
+La Sapienza,2251926,2015-03-17,Zachary Wigon,,fresh,A picture that balances heart and mind with nuance.
+La Sapienza,2251650,2015-03-14,Harvey S. Karten,B+,fresh,"As in ""Who's Afraid of Virginia Woolf,"" both the younger couple and their older mentors are changed from a relationship."
+La Sapienza,2250991,2015-03-12,Ben Sachs,,fresh,"This recalls Manoel de Oliveira and Eric Rohmer in its poker-faced style, deliberately archaic storytelling, and magisterial epiphanies."
+La Sapienza,2225361,2014-09-28,Donald J. Levit,,fresh,"Although a love-fiction crossed with documentary lecture and superb Raphael O'Byrne cinematography, 'La Sapienza' is as close as celluloid can approach to architecture."
+La Sapienza,2222032,2014-09-10,Carson Lund,3/4,fresh,"Eugne Green's mannered direction doesn't work for every situation it's homogenously applied to, but at its most effective it inspires an enhanced sensitivity to the import of every gesture, visual or verbal."
+Uncle Tom,2713732,2020-08-14,Megan Basham,,fresh,Uncle Tom suffers from an overreliance on pundits. Its most compelling insights come from people who've never been quoted in a Twitter or Facebook battle.
+Uncle Tom,2706229,2020-07-19,Matthew Pejkovic,4/5,fresh,"An incredibly relevant and insightful documentary that delves into the past, present, and future of the black American conservative movement."
+Uncle Tom,2698525,2020-06-24,Dante James,7/10,fresh,"It's a little misleading in some areas, especially if you know the players involved in this doc, but there are a lot of interesting historical facts about the breakdown of the Black family and how the whole welfare system targeted the Black community."

examples/milvus/load.ts

@@ -0,0 +1,65 @@
+import { DataType } from "@zilliz/milvus2-sdk-node";
+import {
+  MilvusVectorStore,
+  PapaCSVReader,
+  storageContextFromDefaults,
+  VectorStoreIndex,
+} from "llamaindex";
+
+const collectionName = "movie_reviews";
+
+async function main() {
+  try {
+    const reader = new PapaCSVReader(false);
+    const docs = await reader.loadData("./data/movie_reviews.csv");
+
+    const vectorStore = new MilvusVectorStore({
+      contentKey: "content",
+    });
+
+    const milvus = vectorStore.client();
+
+    await milvus.createCollection({
+      collection_name: collectionName,
+      fields: [
+        {
+          name: "id",
+          data_type: DataType.VarChar,
+          is_primary_key: true,
+          max_length: 200,
+        },
+        {
+          name: "embedding",
+          data_type: DataType.FloatVector,
+          dim: 1536,
+        },
+        {
+          name: "content",
+          data_type: DataType.VarChar,
+          max_length: 9000,
+        },
+        {
+          name: "metadata",
+          data_type: DataType.JSON,
+        },
+      ],
+    });
+    await milvus.createIndex({
+      collection_name: collectionName,
+      field_name: "embedding",
+      index_type: "HNSW",
+      params: { efConstruction: 10, M: 4 },
+      metric_type: "L2",
+    });
+    await vectorStore.connect(collectionName);
+
+    const ctx = await storageContextFromDefaults({ vectorStore });
+    const index = await VectorStoreIndex.fromDocuments(docs, {
+      storageContext: ctx,
+    });
+  } catch (e) {
+    console.error(e);
+  }
+}
+
+main();

examples/milvus/query.ts

@@ -0,0 +1,33 @@
+import {
+  MilvusVectorStore,
+  serviceContextFromDefaults,
+  VectorStoreIndex,
+} from "llamaindex";
+
+const collectionName = "movie_reviews";
+
+async function main() {
+  try {
+    const milvus = new MilvusVectorStore({
+      contentKey: "content",
+    });
+    await milvus.connect(collectionName);
+
+    const ctx = serviceContextFromDefaults();
+    const index = await VectorStoreIndex.fromVectorStore(milvus, ctx);
+
+    const retriever = await index.asRetriever({ similarityTopK: 20 });
+
+    const queryEngine = await index.asQueryEngine({ retriever });
+
+    const results = await queryEngine.query({
+      query: "What is the best reviewed movie?",
+    });
+
+    console.log(results.response);
+  } catch (e) {
+    console.error(e);
+  }
+}
+
+main();

examples/package.json

@@ -1,16 +1,19 @@
 {
   "name": "examples",
   "private": true,
-  "version": "0.0.3",
+  "version": "0.0.4",
   "dependencies": {
+    "@aws-crypto/sha256-js": "^5.2.0",
     "@datastax/astra-db-ts": "^0.1.4",
     "@notionhq/client": "^2.2.14",
     "@pinecone-database/pinecone": "^1.1.3",
+    "@zilliz/milvus2-sdk-node": "^2.3.5",
     "chromadb": "^1.8.1",
     "commander": "^11.1.0",
     "dotenv": "^16.4.1",
-    "llamaindex": "latest",
-    "mongodb": "^6.2.0"
+    "llamaindex": "workspace:*",
+    "mongodb": "^6.2.0",
+    "pathe": "^1.1.2"
   },
   "devDependencies": {
     "@types/node": "^18.19.10",

examples/readers/CHANGELOG.md

@@ -0,0 +1,13 @@
+# llamaindex-loader-example
+
+## null
+
+### Patch Changes
+
+- Updated dependencies [d2e8d0c]
+- Updated dependencies [aefc326]
+- Updated dependencies [484a710]
+- Updated dependencies [d766bd0]
+- Updated dependencies [dd95927]
+- Updated dependencies [bf583a7]
+  - llamaindex@0.2.0

examples/readers/package.json

@@ -12,11 +12,12 @@
     "start:llamaparse": "node --loader ts-node/esm ./src/llamaparse.ts"
   },
   "dependencies": {
-    "llamaindex": "latest"
+    "llamaindex": "workspace:*"
   },
   "devDependencies": {
     "@types/node": "^20.11.14",
     "ts-node": "^10.9.2",
     "typescript": "^5.3.3"
-  }
+  },
+  "version": null
 }

package.json

@@ -12,9 +12,7 @@
     "test": "turbo run test",
     "type-check": "tsc -b --diagnostics",
     "release": "pnpm run build:release && changeset publish",
-    "new-llamaindex": "pnpm run build:release && changeset version --ignore create-llama",
-    "new-create-llama": "pnpm run build:release && changeset version --ignore llamaindex --ignore @llamaindex/core-test",
-    "new-experimental": "pnpm run build:release && changeset version --ignore create-llama"
+    "new-version": "pnpm run build:release && changeset version"
   },
   "devDependencies": {
     "@changesets/cli": "^2.27.1",

packages/core/CHANGELOG.md

@@ -1,5 +1,25 @@
 # llamaindex
 
+## 0.2.0
+
+### Minor Changes
+
+- bf583a7: Use parameter object for retrieve function of Retriever (to align usage with query function of QueryEngine)
+
+### Patch Changes
+
+- d2e8d0c: add support for Milvus vector store
+- aefc326: feat: experimental package + json query engine
+- 484a710: - Add missing exports:
+  - `IndexStructType`,
+  - `IndexDict`,
+  - `jsonToIndexStruct`,
+  - `IndexList`,
+  - `IndexStruct`
+  - Fix `IndexDict.toJson()` method
+- d766bd0: Add streaming to agents
+- dd95927: add Claude Haiku support and update anthropic SDK
+
 ## 0.1.21
 
 ### Patch Changes

packages/core/package.json

@@ -1,12 +1,13 @@
 {
   "name": "llamaindex",
-  "version": "0.1.21",
+  "version": "0.2.0",
   "license": "MIT",
   "type": "module",
   "dependencies": {
-    "@anthropic-ai/sdk": "^0.15.0",
+    "@anthropic-ai/sdk": "^0.18.0",
     "@aws-crypto/sha256-js": "^5.2.0",
     "@datastax/astra-db-ts": "^0.1.4",
+    "@grpc/grpc-js": "^1.10.2",
     "@llamaindex/cloud": "0.0.4",
     "@llamaindex/env": "workspace:*",
     "@mistralai/mistralai": "^0.0.10",
@@ -18,6 +19,7 @@
     "@types/papaparse": "^5.3.14",
     "@types/pg": "^8.11.0",
     "@xenova/transformers": "^2.15.0",
+    "@zilliz/milvus2-sdk-node": "^2.3.5",
     "assemblyai": "^4.2.2",
     "chromadb": "~1.7.3",
     "cohere-ai": "^7.7.5",

packages/core/src/llm/LLM.ts

@@ -620,6 +620,7 @@ export const ALL_AVAILABLE_ANTHROPIC_LEGACY_MODELS = {
 export const ALL_AVAILABLE_V3_MODELS = {
   "claude-3-opus": { contextWindow: 200000 },
   "claude-3-sonnet": { contextWindow: 200000 },
+  "claude-3-haiku": { contextWindow: 200000 },
 };
 
 export const ALL_AVAILABLE_ANTHROPIC_MODELS = {
@@ -630,6 +631,7 @@ export const ALL_AVAILABLE_ANTHROPIC_MODELS = {
 const AVAILABLE_ANTHROPIC_MODELS_WITHOUT_DATE: { [key: string]: string } = {
   "claude-3-opus": "claude-3-opus-20240229",
   "claude-3-sonnet": "claude-3-sonnet-20240229",
+  "claude-3-haiku": "claude-3-haiku-20240307",
 } as { [key in keyof typeof ALL_AVAILABLE_ANTHROPIC_MODELS]: string };
 
 /**

packages/core/src/storage/index.ts

@@ -11,6 +11,7 @@ export { SimpleKVStore } from "./kvStore/SimpleKVStore.js";
 export * from "./kvStore/types.js";
 export { AstraDBVectorStore } from "./vectorStore/AstraDBVectorStore.js";
 export { ChromaVectorStore } from "./vectorStore/ChromaVectorStore.js";
+export { MilvusVectorStore } from "./vectorStore/MilvusVectorStore.js";
 export { MongoDBAtlasVectorSearch } from "./vectorStore/MongoDBAtlasVectorStore.js";
 export { PGVectorStore } from "./vectorStore/PGVectorStore.js";
 export { PineconeVectorStore } from "./vectorStore/PineconeVectorStore.js";

packages/core/src/storage/vectorStore/MilvusVectorStore.ts

@@ -0,0 +1,160 @@
+/* eslint-disable turbo/no-undeclared-env-vars */
+import type { ChannelOptions } from "@grpc/grpc-js";
+import {
+  MilvusClient,
+  type ClientConfig,
+  type DeleteReq,
+  type RowData,
+} from "@zilliz/milvus2-sdk-node";
+import { BaseNode, Document, MetadataMode, type Metadata } from "../../Node.js";
+import type {
+  VectorStore,
+  VectorStoreQuery,
+  VectorStoreQueryResult,
+} from "./types.js";
+
+export class MilvusVectorStore implements VectorStore {
+  public storesText: boolean = true;
+  public isEmbeddingQuery?: boolean;
+
+  private milvusClient: MilvusClient;
+  private collection: string = "";
+
+  private idKey: string;
+  private contentKey: string | undefined; // if undefined the entirety of the node aside from the id and embedding will be stored as content
+  private metadataKey: string;
+  private embeddingKey: string;
+
+  constructor(
+    init?: Partial<{ milvusClient: MilvusClient }> & {
+      params?: {
+        configOrAddress: ClientConfig | string;
+        ssl?: boolean;
+        username?: string;
+        password?: string;
+        channelOptions?: ChannelOptions;
+      };
+      idKey?: string;
+      contentKey?: string;
+      metadataKey?: string;
+      embeddingKey?: string;
+    },
+  ) {
+    if (init?.milvusClient) {
+      this.milvusClient = init.milvusClient;
+    } else {
+      const configOrAddress =
+        init?.params?.configOrAddress ?? process.env.MILVUS_ADDRESS;
+      const ssl = init?.params?.ssl ?? process.env.MILVUS_SSL === "true";
+      const username = init?.params?.username ?? process.env.MILVUS_USERNAME;
+      const password = init?.params?.password ?? process.env.MILVUS_PASSWORD;
+
+      if (!configOrAddress) {
+        throw new Error("Must specify MILVUS_ADDRESS via env variable.");
+      }
+      this.milvusClient = new MilvusClient(
+        configOrAddress,
+        ssl,
+        username,
+        password,
+        init?.params?.channelOptions,
+      );
+    }
+
+    this.idKey = init?.idKey ?? "id";
+    this.contentKey = init?.contentKey;
+    this.metadataKey = init?.metadataKey ?? "metadata";
+    this.embeddingKey = init?.embeddingKey ?? "embedding";
+  }
+
+  public client(): MilvusClient {
+    return this.milvusClient;
+  }
+
+  public async connect(collection: string): Promise<void> {
+    await this.milvusClient.connectPromise;
+    await this.milvusClient.loadCollectionSync({
+      collection_name: collection,
+    });
+
+    this.collection = collection;
+  }
+
+  public async add(nodes: BaseNode<Metadata>[]): Promise<string[]> {
+    if (!this.collection) {
+      throw new Error("Must connect to collection before adding.");
+    }
+
+    const result = await this.milvusClient.insert({
+      collection_name: this.collection,
+      data: nodes.map((node) => {
+        const entry: RowData = {
+          [this.idKey]: node.id_,
+          [this.embeddingKey]: node.getEmbedding(),
+          [this.metadataKey]: node.metadata ?? {},
+        };
+
+        if (this.contentKey) {
+          entry[this.contentKey] = String(node.getContent(MetadataMode.NONE));
+        }
+
+        return entry;
+      }),
+    });
+
+    if (!result.IDs) {
+      return [];
+    }
+
+    if ("int_id" in result.IDs) {
+      return result.IDs.int_id.data.map((i) => String(i));
+    }
+
+    return result.IDs.str_id.data.map((s) => String(s));
+  }
+
+  public async delete(
+    refDocId: string,
+    deleteOptions?: Omit<DeleteReq, "ids">,
+  ): Promise<void> {
+    await this.milvusClient.delete({
+      ids: [refDocId],
+      collection_name: this.collection,
+      ...deleteOptions,
+    });
+  }
+
+  public async query(
+    query: VectorStoreQuery,
+    _options?: any,
+  ): Promise<VectorStoreQueryResult> {
+    if (!this.collection) {
+      throw new Error("Must connect to collection before querying.");
+    }
+
+    const found = await this.milvusClient.search({
+      collection_name: this.collection,
+      limit: query.similarityTopK,
+      vector: query.queryEmbedding,
+    });
+
+    return {
+      nodes: found.results.map((result) => {
+        return new Document({
+          id_: result[this.idKey],
+          metadata: result[this.metadataKey] ?? {},
+          text: this.contentKey
+            ? result[this.contentKey]
+            : JSON.stringify(result),
+          embedding: result[this.embeddingKey],
+        });
+      }),
+      similarities: found.results.map((result) => result.score),
+      ids: found.results.map((result) => String(result.id)),
+    };
+  }
+
+  public async persist() {
+    // no need to do anything
+  }
+}

packages/core/tests/CHANGELOG.md

@@ -0,0 +1,13 @@
+# @llamaindex/core-test
+
+## 0.0.2
+
+### Patch Changes
+
+- 484a710: - Add missing exports:
+  - `IndexStructType`,
+  - `IndexDict`,
+  - `jsonToIndexStruct`,
+  - `IndexList`,
+  - `IndexStruct`
+  - Fix `IndexDict.toJson()` method

packages/core/tests/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/core-test",
   "private": true,
-  "version": "0.0.1",
+  "version": "0.0.2",
   "type": "module",
   "scripts": {
     "test": "vitest run"

packages/create-llama/.eslintrc

@@ -1,20 +0,0 @@
-{
-  "root": false,
-  "rules": {
-    "turbo/no-undeclared-env-vars": [
-      "error",
-      {
-        "allowList": [
-          "OPENAI_API_KEY",
-          "LLAMA_CLOUD_API_KEY",
-          "npm_config_user_agent",
-          "http_proxy",
-          "https_proxy",
-          "MODEL",
-          "NEXT_PUBLIC_CHAT_API",
-          "NEXT_PUBLIC_MODEL"
-        ]
-      }
-    ]
-  }
-}

packages/create-llama/CHANGELOG.md

@@ -1,175 +0,0 @@
-# create-llama
-
-## 0.0.28
-
-### Patch Changes
-
-- 89a49f4: Add more config variables to .env file
-- fdf48dd: Add "Start in VSCode" option to postInstallAction
-- fdf48dd: Add devcontainers to generated code
-
-## 0.0.27
-
-### Patch Changes
-
-- 2d29350: Add LlamaParse option when selecting a pdf file or a folder (FastAPI only)
-- b354f23: Add embedding model option to create-llama (FastAPI only)
-
-## 0.0.26
-
-### Patch Changes
-
-- 09d532e: feat: generate llama pack project from llama index
-- cfdd6db: feat: add pinecone support to create llama
-- ef25d69: upgrade llama-index package to version v0.10.7 for create-llama app
-- 50dfd7b: update fastapi for CVE-2024-24762
-
-## 0.0.25
-
-### Patch Changes
-
-- d06a85b: Add option to create an agent by selecting tools (Google, Wikipedia)
-- 7b7329b: Added latest turbo models for GPT-3.5 and GPT 4
-
-## 0.0.24
-
-### Patch Changes
-
-- ba95ca3: Use condense plus context chat engine for FastAPI as default
-
-## 0.0.23
-
-### Patch Changes
-
-- c680af6: Fixed issues with locating templates path
-
-## 0.0.22
-
-### Patch Changes
-
-- 6dd401e: Add an option to provide an URL and chat with the website data (FastAPI only)
-- e9b87ef: Select a folder as data source and support more file types (.pdf, .doc, .docx, .xls, .xlsx, .csv)
-
-## 0.0.20
-
-### Patch Changes
-
-- 27d55fd: Add an option to provide an URL and chat with the website data
-
-## 0.0.19
-
-### Patch Changes
-
-- 3a29a80: Add node_modules to gitignore in Express backends
-- fe03aaa: feat: generate llama pack example
-
-## 0.0.18
-
-### Patch Changes
-
-- 88d3b41: fix packaging
-
-## 0.0.17
-
-### Patch Changes
-
-- fa17f7e: Add an option that allows the user to run the generated app
-- 9e5d8e1: Add an option to select a local PDF file as data source
-
-## 0.0.16
-
-### Patch Changes
-
-- a73942d: Fix: Bundle mongo dependency with NextJS
-- 9492cc6: Feat: Added option to automatically install dependencies (for Python and TS)
-- f74dea5: Feat: Show images in chat messages using GPT4 Vision (Express and NextJS only)
-
-## 0.0.15
-
-### Patch Changes
-
-- 8e124e5: feat: support showing image on chat message
-
-## 0.0.14
-
-### Patch Changes
-
-- 2e6b36e: fix: re-organize file structure
-- 2b356c8: fix: relative path incorrect
-
-## 0.0.13
-
-### Patch Changes
-
-- Added PostgreSQL vector store (for Typescript and Python)
-- Improved async handling in FastAPI
-
-## 0.0.12
-
-### Patch Changes
-
-- 9c5e22a: Added cross-env so frontends with Express/FastAPI backends are working under Windows
-- 5ab65eb: Bring Python templates with TS templates to feature parity
-- 9c5e22a: Added vector DB selector to create-llama (starting with MongoDB support)
-
-## 0.0.11
-
-### Patch Changes
-
-- 2aeb341: - Added option to create a new project based on community templates
-  - Added OpenAI model selector for NextJS projects
-  - Added GPT4 Vision support (and file upload)
-
-## 0.0.10
-
-### Patch Changes
-
-- Bugfixes (thanks @marcusschiesser)
-
-## 0.0.9
-
-### Patch Changes
-
-- acfe232: Deployment fixes (thanks @seldo)
-
-## 0.0.8
-
-### Patch Changes
-
-- 8cdb07f: Fix Next deployment (thanks @seldo and @marcusschiesser)
-
-## 0.0.7
-
-### Patch Changes
-
-- 9f9f293: Added more to README and made it easier to switch models (thanks @seldo)
-
-## 0.0.6
-
-### Patch Changes
-
-- 4431ec7: Label bug fix (thanks @marcusschiesser)
-
-## 0.0.5
-
-### Patch Changes
-
-- 25257f4: Fix issue where it doesn't find OpenAI Key when running npm run generate (#182) (thanks @RayFernando1337)
-
-## 0.0.4
-
-### Patch Changes
-
-- 031e926: Update create-llama readme (thanks @logan-markewich)
-
-## 0.0.3
-
-### Patch Changes
-
-- 91b42a3: change version (thanks @marcusschiesser)
-
-## 0.0.2
-
-### Patch Changes
-
-- e2a6805: Hello Create Llama (thanks @marcusschiesser)

packages/create-llama/LICENSE.md

@@ -1,9 +0,0 @@
-The MIT License (MIT)
-
-Copyright (c) 2023 LlamaIndex, Vercel, Inc.
-
-Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

packages/create-llama/README.md

@@ -1,126 +0,0 @@
-# Create LlamaIndex App
-
-The easiest way to get started with [LlamaIndex](https://www.llamaindex.ai/) is by using `create-llama`. This CLI tool enables you to quickly start building a new LlamaIndex application, with everything set up for you.
-
-Just run
-
-```bash
-npx create-llama@latest
-```
-
-to get started, or see below for more options. Once your app is generated, run
-
-```bash
-npm run dev
-```
-
-to start the development server. You can then visit [http://localhost:3000](http://localhost:3000) to see your app.
-
-## What you'll get
-
-- A Next.js-powered front-end. The app is set up as a chat interface that can answer questions about your data (see below)
-  - You can style it with HTML and CSS, or you can optionally use components from [shadcn/ui](https://ui.shadcn.com/)
-- Your choice of 3 back-ends:
-  - **Next.js**: if you select this option, you’ll have a full stack Next.js application that you can deploy to a host like [Vercel](https://vercel.com/) in just a few clicks. This uses [LlamaIndex.TS](https://www.npmjs.com/package/llamaindex), our TypeScript library.
-  - **Express**: if you want a more traditional Node.js application you can generate an Express backend. This also uses LlamaIndex.TS.
-  - **Python FastAPI**: if you select this option you’ll get a backend powered by the [llama-index python package](https://pypi.org/project/llama-index/), which you can deploy to a service like Render or fly.io.
-- The back-end has a single endpoint that allows you to send the state of your chat and receive additional responses
-- You can choose whether you want a streaming or non-streaming back-end (if you're not sure, we recommend streaming)
-- You can choose whether you want to use `ContextChatEngine` or `SimpleChatEngine`
-  - `SimpleChatEngine` will just talk to the LLM directly without using your data
-  - `ContextChatEngine` will use your data to answer questions (see below).
-- The app uses OpenAI by default, so you'll need an OpenAI API key, or you can customize it to use any of the dozens of LLMs we support.
-
-## Using your data
-
-If you've enabled `ContextChatEngine`, you can supply your own data and the app will index it and answer questions. Your generated app will have a folder called `data`:
-
-- With the Next.js backend this is `./data`
-- With the Express or Python backend this is in `./backend/data`
-
-The app will ingest any supported files you put in this directory. Your Next.js and Express apps use LlamaIndex.TS so they will be able to ingest any PDF, text, CSV, Markdown, Word and HTML files. The Python backend can read even more types, including video and audio files.
-
-Before you can use your data, you need to index it. If you're using the Next.js or Express apps, run:
-
-```bash
-npm run generate
-```
-
-Then re-start your app. Remember you'll need to re-run `generate` if you add new files to your `data` folder. If you're using the Python backend, you can trigger indexing of your data by deleting the `./storage` folder and re-starting the app.
-
-## Don't want a front-end?
-
-It's optional! If you've selected the Python or Express back-ends, just delete the `frontend` folder and you'll get an API without any front-end code.
-
-## Customizing the LLM
-
-By default the app will use OpenAI's gpt-3.5-turbo model. If you want to use GPT-4, you can modify this by editing a file:
-
-- In the Next.js backend, edit `./app/api/chat/route.ts` and replace `gpt-3.5-turbo` with `gpt-4`
-- In the Express backend, edit `./backend/src/controllers/chat.controller.ts` and likewise replace `gpt-3.5-turbo` with `gpt-4`
-- In the Python backend, edit `./backend/app/utils/index.py` and once again replace `gpt-3.5-turbo` with `gpt-4`
-
-You can also replace OpenAI with one of our [dozens of other supported LLMs](https://docs.llamaindex.ai/en/stable/module_guides/models/llms/modules.html).
-
-## Example
-
-The simplest thing to do is run `create-llama` in interactive mode:
-
-```bash
-npx create-llama@latest
-# or
-npm create llama@latest
-# or
-yarn create llama
-# or
-pnpm create llama@latest
-```
-
-You will be asked for the name of your project, along with other configuration options, something like this:
-
-```bash
->> npm create llama@latest
-Need to install the following packages:
-  create-llama@latest
-Ok to proceed? (y) y
-✔ What is your project named? … my-app
-✔ Which template would you like to use? › Chat with streaming
-✔ Which framework would you like to use? › NextJS
-✔ Which UI would you like to use? › Just HTML
-✔ Which chat engine would you like to use? › ContextChatEngine
-✔ Please provide your OpenAI API key (leave blank to skip): …
-✔ Would you like to use ESLint? … No / Yes
-Creating a new LlamaIndex app in /home/my-app.
-```
-
-### Running non-interactively
-
-You can also pass command line arguments to set up a new project
-non-interactively. See `create-llama --help`:
-
-```bash
-create-llama <project-directory> [options]
-
-Options:
-  -V, --version                      output the version number
-
-  --use-npm
-
-    Explicitly tell the CLI to bootstrap the app using npm
-
-  --use-pnpm
-
-    Explicitly tell the CLI to bootstrap the app using pnpm
-
-  --use-yarn
-
-    Explicitly tell the CLI to bootstrap the app using Yarn
-
-```
-
-## LlamaIndex Documentation
-
-- [TS/JS docs](https://ts.llamaindex.ai/)
-- [Python docs](https://docs.llamaindex.ai/en/stable/)
-
-Inspired by and adapted from [create-next-app](https://github.com/vercel/next.js/tree/canary/packages/create-next-app)

packages/create-llama/create-app.ts

@@ -1,147 +0,0 @@
-/* eslint-disable import/no-extraneous-dependencies */
-import path from "path";
-import { green, yellow } from "picocolors";
-import { tryGitInit } from "./helpers/git";
-import { isFolderEmpty } from "./helpers/is-folder-empty";
-import { getOnline } from "./helpers/is-online";
-import { isWriteable } from "./helpers/is-writeable";
-import { makeDir } from "./helpers/make-dir";
-
-import fs from "fs";
-import terminalLink from "terminal-link";
-import type { InstallTemplateArgs } from "./helpers";
-import { installTemplate } from "./helpers";
-import { writeDevcontainer } from "./helpers/devcontainer";
-import { templatesDir } from "./helpers/dir";
-import { toolsRequireConfig } from "./helpers/tools";
-
-export type InstallAppArgs = Omit<
-  InstallTemplateArgs,
-  "appName" | "root" | "isOnline" | "customApiPath"
-> & {
-  appPath: string;
-  frontend: boolean;
-};
-
-export async function createApp({
-  template,
-  framework,
-  engine,
-  ui,
-  appPath,
-  packageManager,
-  eslint,
-  frontend,
-  openAiKey,
-  llamaCloudKey,
-  model,
-  embeddingModel,
-  communityProjectPath,
-  llamapack,
-  vectorDb,
-  externalPort,
-  postInstallAction,
-  dataSource,
-  tools,
-}: InstallAppArgs): Promise<void> {
-  const root = path.resolve(appPath);
-
-  if (!(await isWriteable(path.dirname(root)))) {
-    console.error(
-      "The application path is not writable, please check folder permissions and try again.",
-    );
-    console.error(
-      "It is likely you do not have write permissions for this folder.",
-    );
-    process.exit(1);
-  }
-
-  const appName = path.basename(root);
-
-  await makeDir(root);
-  if (!isFolderEmpty(root, appName)) {
-    process.exit(1);
-  }
-
-  const useYarn = packageManager === "yarn";
-  const isOnline = !useYarn || (await getOnline());
-
-  console.log(`Creating a new LlamaIndex app in ${green(root)}.`);
-  console.log();
-
-  const args = {
-    appName,
-    root,
-    template,
-    framework,
-    engine,
-    ui,
-    packageManager,
-    isOnline,
-    eslint,
-    openAiKey,
-    llamaCloudKey,
-    model,
-    embeddingModel,
-    communityProjectPath,
-    llamapack,
-    vectorDb,
-    externalPort,
-    postInstallAction,
-    dataSource,
-    tools,
-  };
-
-  if (frontend) {
-    // install backend
-    const backendRoot = path.join(root, "backend");
-    await makeDir(backendRoot);
-    await installTemplate({ ...args, root: backendRoot, backend: true });
-    // install frontend
-    const frontendRoot = path.join(root, "frontend");
-    await makeDir(frontendRoot);
-    await installTemplate({
-      ...args,
-      root: frontendRoot,
-      framework: "nextjs",
-      customApiPath: `http://localhost:${externalPort ?? 8000}/api/chat`,
-      backend: false,
-    });
-    // copy readme for fullstack
-    await fs.promises.copyFile(
-      path.join(templatesDir, "README-fullstack.md"),
-      path.join(root, "README.md"),
-    );
-  } else {
-    await installTemplate({ ...args, backend: true });
-  }
-
-  process.chdir(root);
-  if (tryGitInit(root)) {
-    console.log("Initialized a git repository.");
-    console.log();
-  }
-
-  await writeDevcontainer(root, templatesDir, framework, frontend);
-
-  if (toolsRequireConfig(tools)) {
-    console.log(
-      yellow(
-        `You have selected tools that require configuration. Please configure them in the ${terminalLink(
-          "tools_config.json",
-          `file://${root}/tools_config.json`,
-        )} file.`,
-      ),
-    );
-  }
-  console.log("");
-  console.log(`${green("Success!")} Created ${appName} at ${appPath}`);
-
-  console.log(
-    `Now have a look at the ${terminalLink(
-      "README.md",
-      `file://${root}/README.md`,
-    )} and learn how to get started.`,
-  );
-  console.log();
-}

packages/create-llama/e2e/basic.spec.ts

@@ -1,145 +0,0 @@
-/* eslint-disable turbo/no-undeclared-env-vars */
-import { expect, test } from "@playwright/test";
-import { ChildProcess } from "child_process";
-import fs from "fs";
-import path from "path";
-import type {
-  TemplateEngine,
-  TemplateFramework,
-  TemplatePostInstallAction,
-  TemplateType,
-  TemplateUI,
-} from "../helpers";
-import { createTestDir, runCreateLlama, type AppType } from "./utils";
-
-const templateTypes: TemplateType[] = ["streaming", "simple"];
-const templateFrameworks: TemplateFramework[] = [
-  "nextjs",
-  "express",
-  "fastapi",
-];
-const templateEngines: TemplateEngine[] = ["simple", "context"];
-const templateUIs: TemplateUI[] = ["shadcn", "html"];
-const templatePostInstallActions: TemplatePostInstallAction[] = [
-  "none",
-  "runApp",
-];
-
-for (const templateType of templateTypes) {
-  for (const templateFramework of templateFrameworks) {
-    for (const templateEngine of templateEngines) {
-      for (const templateUI of templateUIs) {
-        for (const templatePostInstallAction of templatePostInstallActions) {
-          if (templateFramework === "nextjs" && templateType === "simple") {
-            // nextjs doesn't support simple templates - skip tests
-            continue;
-          }
-          const appType: AppType =
-            templateFramework === "express" || templateFramework === "fastapi"
-              ? templateType === "simple"
-                ? "--no-frontend" // simple templates don't have frontends
-                : "--frontend"
-              : "";
-          if (appType === "--no-frontend" && templateUI !== "html") {
-            // if there's no frontend, don't iterate over UIs
-            continue;
-          }
-          test.describe(`try create-llama ${templateType} ${templateFramework} ${templateEngine} ${templateUI} ${appType} ${templatePostInstallAction}`, async () => {
-            let port: number;
-            let externalPort: number;
-            let cwd: string;
-            let name: string;
-            let appProcess: ChildProcess;
-            // Only test without using vector db for now
-            const vectorDb = "none";
-
-            test.beforeAll(async () => {
-              port = Math.floor(Math.random() * 10000) + 10000;
-              externalPort = port + 1;
-              cwd = await createTestDir();
-              const result = await runCreateLlama(
-                cwd,
-                templateType,
-                templateFramework,
-                templateEngine,
-                templateUI,
-                vectorDb,
-                appType,
-                port,
-                externalPort,
-                templatePostInstallAction,
-              );
-              name = result.projectName;
-              appProcess = result.appProcess;
-            });
-
-            test("App folder should exist", async () => {
-              const dirExists = fs.existsSync(path.join(cwd, name));
-              expect(dirExists).toBeTruthy();
-            });
-            test("Frontend should have a title", async ({ page }) => {
-              test.skip(templatePostInstallAction !== "runApp");
-              test.skip(appType === "--no-frontend");
-              await page.goto(`http://localhost:${port}`);
-              await expect(page.getByText("Built by LlamaIndex")).toBeVisible();
-            });
-
-            test("Frontend should be able to submit a message and receive a response", async ({
-              page,
-            }) => {
-              test.skip(templatePostInstallAction !== "runApp");
-              test.skip(appType === "--no-frontend");
-              await page.goto(`http://localhost:${port}`);
-              await page.fill("form input", "hello");
-              const [response] = await Promise.all([
-                page.waitForResponse(
-                  (res) => {
-                    return (
-                      res.url().includes("/api/chat") && res.status() === 200
-                    );
-                  },
-                  {
-                    timeout: 1000 * 60,
-                  },
-                ),
-                page.click("form button[type=submit]"),
-              ]);
-              const text = await response.text();
-              console.log("AI response when submitting message: ", text);
-              expect(response.ok()).toBeTruthy();
-            });
-
-            test("Backend should response when calling API", async ({
-              request,
-            }) => {
-              test.skip(templatePostInstallAction !== "runApp");
-              test.skip(appType !== "--no-frontend");
-              const backendPort = appType === "" ? port : externalPort;
-              const response = await request.post(
-                `http://localhost:${backendPort}/api/chat`,
-                {
-                  data: {
-                    messages: [
-                      {
-                        role: "user",
-                        content: "Hello",
-                      },
-                    ],
-                  },
-                },
-              );
-              const text = await response.text();
-              console.log("AI response when calling API: ", text);
-              expect(response.ok()).toBeTruthy();
-            });
-
-            // clean processes
-            test.afterAll(async () => {
-              appProcess?.kill();
-            });
-          });
-        }
-      }
-    }
-  }
-}

packages/create-llama/e2e/tsconfig.json

@@ -1,16 +0,0 @@
-{
-  "compilerOptions": {
-    "target": "es2019",
-    "module": "esnext",
-    "moduleResolution": "node",
-    "strict": true,
-    "resolveJsonModule": true,
-    "skipLibCheck": true,
-    "declaration": false,
-    "esModuleInterop": true,
-    "forceConsistentCasingInFileNames": true,
-    "incremental": true,
-    "tsBuildInfoFile": "./lib/.tsbuildinfo"
-  },
-  "include": ["./**/*.ts"]
-}

packages/create-llama/e2e/utils.ts

@@ -1,181 +0,0 @@
-import { ChildProcess, exec } from "child_process";
-import crypto from "node:crypto";
-import { mkdir } from "node:fs/promises";
-import * as path from "path";
-import waitPort from "wait-port";
-import {
-  TemplateEngine,
-  TemplateFramework,
-  TemplatePostInstallAction,
-  TemplateType,
-  TemplateUI,
-  TemplateVectorDB,
-} from "../helpers";
-
-export type AppType = "--frontend" | "--no-frontend" | "";
-const MODEL = "gpt-3.5-turbo";
-const EMBEDDING_MODEL = "text-embedding-ada-002";
-export type CreateLlamaResult = {
-  projectName: string;
-  appProcess: ChildProcess;
-};
-
-// eslint-disable-next-line max-params
-export async function checkAppHasStarted(
-  frontend: boolean,
-  framework: TemplateFramework,
-  port: number,
-  externalPort: number,
-  timeout: number,
-) {
-  if (frontend) {
-    await Promise.all([
-      waitPort({
-        host: "localhost",
-        port: port,
-        timeout,
-      }),
-      waitPort({
-        host: "localhost",
-        port: externalPort,
-        timeout,
-      }),
-    ]).catch((err) => {
-      console.error(err);
-      throw err;
-    });
-  } else {
-    let wPort: number;
-    if (framework === "nextjs") {
-      wPort = port;
-    } else {
-      wPort = externalPort;
-    }
-    await waitPort({
-      host: "localhost",
-      port: wPort,
-      timeout,
-    }).catch((err) => {
-      console.error(err);
-      throw err;
-    });
-  }
-}
-
-// eslint-disable-next-line max-params
-export async function runCreateLlama(
-  cwd: string,
-  templateType: TemplateType,
-  templateFramework: TemplateFramework,
-  templateEngine: TemplateEngine,
-  templateUI: TemplateUI,
-  vectorDb: TemplateVectorDB,
-  appType: AppType,
-  port: number,
-  externalPort: number,
-  postInstallAction: TemplatePostInstallAction,
-): Promise<CreateLlamaResult> {
-  const createLlama = path.join(
-    __dirname,
-    "..",
-    "output",
-    "package",
-    "dist",
-    "index.js",
-  );
-
-  const name = [
-    templateType,
-    templateFramework,
-    templateEngine,
-    templateUI,
-    appType,
-  ].join("-");
-  const command = [
-    "node",
-    createLlama,
-    name,
-    "--template",
-    templateType,
-    "--framework",
-    templateFramework,
-    "--engine",
-    templateEngine,
-    "--ui",
-    templateUI,
-    "--vector-db",
-    vectorDb,
-    "--model",
-    MODEL,
-    "--embedding-model",
-    EMBEDDING_MODEL,
-    "--open-ai-key",
-    process.env.OPENAI_API_KEY || "testKey",
-    appType,
-    "--eslint",
-    "--use-npm",
-    "--port",
-    port,
-    "--external-port",
-    externalPort,
-    "--post-install-action",
-    postInstallAction,
-    "--tools",
-    "none",
-    "--no-llama-parse",
-  ].join(" ");
-  console.log(`running command '${command}' in ${cwd}`);
-  const appProcess = exec(command, {
-    cwd,
-    env: {
-      ...process.env,
-    },
-  });
-  appProcess.stderr?.on("data", (data) => {
-    console.log(data.toString());
-  });
-  appProcess.on("exit", (code) => {
-    if (code !== 0 && code !== null) {
-      throw new Error(`create-llama command was failed!`);
-    }
-  });
-
-  // Wait for app to start
-  if (postInstallAction === "runApp") {
-    await checkAppHasStarted(
-      appType === "--frontend",
-      templateFramework,
-      port,
-      externalPort,
-      1000 * 60 * 5,
-    );
-  } else {
-    // wait create-llama to exit
-    // we don't test install dependencies for now, so just set timeout for 10 seconds
-    await new Promise((resolve, reject) => {
-      const timeout = setTimeout(() => {
-        reject(new Error("create-llama timeout error"));
-      }, 1000 * 10);
-      appProcess.on("exit", (code) => {
-        if (code !== 0 && code !== null) {
-          clearTimeout(timeout);
-          reject(new Error("create-llama command was failed!"));
-        } else {
-          clearTimeout(timeout);
-          resolve(undefined);
-        }
-      });
-    });
-  }
-
-  return {
-    projectName: name,
-    appProcess,
-  };
-}
-
-export async function createTestDir() {
-  const cwd = path.join(__dirname, "cache", crypto.randomUUID());
-  await mkdir(cwd, { recursive: true });
-  return cwd;
-}

packages/create-llama/helpers/constant.ts

@@ -1,6 +0,0 @@
-export const COMMUNITY_OWNER = "run-llama";
-export const COMMUNITY_REPO = "create_llama_projects";
-export const LLAMA_PACK_OWNER = "run-llama";
-export const LLAMA_PACK_REPO = "llama_index";
-export const LLAMA_PACK_FOLDER = "llama-index-packs";
-export const LLAMA_PACK_FOLDER_PATH = `${LLAMA_PACK_OWNER}/${LLAMA_PACK_REPO}/main/${LLAMA_PACK_FOLDER}`;

packages/create-llama/helpers/copy.ts

@@ -1,50 +0,0 @@
-/* eslint-disable import/no-extraneous-dependencies */
-import { async as glob } from "fast-glob";
-import fs from "fs";
-import path from "path";
-
-interface CopyOption {
-  cwd?: string;
-  rename?: (basename: string) => string;
-  parents?: boolean;
-}
-
-const identity = (x: string) => x;
-
-export const copy = async (
-  src: string | string[],
-  dest: string,
-  { cwd, rename = identity, parents = true }: CopyOption = {},
-) => {
-  const source = typeof src === "string" ? [src] : src;
-
-  if (source.length === 0 || !dest) {
-    throw new TypeError("`src` and `dest` are required");
-  }
-
-  const sourceFiles = await glob(source, {
-    cwd,
-    dot: true,
-    absolute: false,
-    stats: false,
-  });
-
-  const destRelativeToCwd = cwd ? path.resolve(cwd, dest) : dest;
-
-  return Promise.all(
-    sourceFiles.map(async (p) => {
-      const dirname = path.dirname(p);
-      const basename = rename(path.basename(p));
-
-      const from = cwd ? path.resolve(cwd, p) : p;
-      const to = parents
-        ? path.join(destRelativeToCwd, dirname, basename)
-        : path.join(destRelativeToCwd, basename);
-
-      // Ensure the destination directory exists
-      await fs.promises.mkdir(path.dirname(to), { recursive: true });
-
-      return fs.promises.copyFile(from, to);
-    }),
-  );
-};

packages/create-llama/helpers/devcontainer.ts

@@ -1,61 +0,0 @@
-import fs from "fs";
-import path from "path";
-import { TemplateFramework } from "./types";
-
-function renderDevcontainerContent(
-  templatesDir: string,
-  framework: TemplateFramework,
-  frontend: boolean,
-) {
-  const devcontainerJson: any = JSON.parse(
-    fs.readFileSync(path.join(templatesDir, "devcontainer.json"), "utf8"),
-  );
-
-  // Modify postCreateCommand
-  if (frontend) {
-    devcontainerJson.postCreateCommand =
-      framework === "fastapi"
-        ? "cd backend && poetry install && cd ../frontend && npm install"
-        : "cd backend && npm install && cd ../frontend && npm install";
-  } else {
-    devcontainerJson.postCreateCommand =
-      framework === "fastapi" ? "poetry install" : "npm install";
-  }
-
-  // Modify containerEnv
-  if (framework === "fastapi") {
-    if (frontend) {
-      devcontainerJson.containerEnv = {
-        ...devcontainerJson.containerEnv,
-        PYTHONPATH: "${PYTHONPATH}:${workspaceFolder}/backend",
-      };
-    } else {
-      devcontainerJson.containerEnv = {
-        ...devcontainerJson.containerEnv,
-        PYTHONPATH: "${PYTHONPATH}:${workspaceFolder}",
-      };
-    }
-  }
-
-  return JSON.stringify(devcontainerJson, null, 2);
-}
-
-export const writeDevcontainer = async (
-  root: string,
-  templatesDir: string,
-  framework: TemplateFramework,
-  frontend: boolean,
-) => {
-  console.log("Adding .devcontainer");
-  const devcontainerContent = renderDevcontainerContent(
-    templatesDir,
-    framework,
-    frontend,
-  );
-  const devcontainerDir = path.join(root, ".devcontainer");
-  fs.mkdirSync(devcontainerDir);
-  await fs.promises.writeFile(
-    path.join(devcontainerDir, "devcontainer.json"),
-    devcontainerContent,
-  );
-};

packages/create-llama/helpers/dir.ts

@@ -1,3 +0,0 @@
-import path from "path";
-
-export const templatesDir = path.join(__dirname, "..", "templates");

packages/create-llama/helpers/env-variables.ts

@@ -1,241 +0,0 @@
-import fs from "fs/promises";
-import path from "path";
-import {
-  FileSourceConfig,
-  TemplateDataSource,
-  TemplateFramework,
-  TemplateVectorDB,
-} from "./types";
-
-type EnvVar = {
-  name?: string;
-  description?: string;
-  value?: string;
-};
-
-const renderEnvVar = (envVars: EnvVar[]): string => {
-  return envVars.reduce(
-    (prev, env) =>
-      prev +
-      (env.description
-        ? `# ${env.description.replaceAll("\n", "\n# ")}\n`
-        : "") +
-      (env.name
-        ? env.value
-          ? `${env.name}=${env.value}\n\n`
-          : `# ${env.name}=\n\n`
-        : ""),
-    "",
-  );
-};
-
-const getVectorDBEnvs = (vectorDb: TemplateVectorDB) => {
-  switch (vectorDb) {
-    case "mongo":
-      return [
-        {
-          name: "MONGO_URI",
-          description:
-            "For generating a connection URI, see https://docs.timescale.com/use-timescale/latest/services/create-a-service\nThe MongoDB connection URI.",
-        },
-        {
-          name: "MONGODB_DATABASE",
-        },
-        {
-          name: "MONGODB_VECTORS",
-        },
-        {
-          name: "MONGODB_VECTOR_INDEX",
-        },
-      ];
-    case "pg":
-      return [
-        {
-          name: "PG_CONNECTION_STRING",
-          description:
-            "For generating a connection URI, see https://docs.timescale.com/use-timescale/latest/services/create-a-service\nThe PostgreSQL connection string.",
-        },
-      ];
-
-    case "pinecone":
-      return [
-        {
-          name: "PINECONE_API_KEY",
-          description:
-            "Configuration for Pinecone vector store\nThe Pinecone API key.",
-        },
-        {
-          name: "PINECONE_ENVIRONMENT",
-        },
-        {
-          name: "PINECONE_INDEX_NAME",
-        },
-      ];
-    default:
-      return [];
-  }
-};
-
-const getDataSourceEnvs = (dataSource: TemplateDataSource) => {
-  switch (dataSource.type) {
-    case "web":
-      return [
-        {
-          name: "BASE_URL",
-          description: "The base URL to start web scraping.",
-        },
-        {
-          name: "URL_PREFIX",
-          description: "The prefix of the URL to start web scraping.",
-        },
-        {
-          name: "MAX_DEPTH",
-          description: "The maximum depth to scrape.",
-        },
-      ];
-    default:
-      return [];
-  }
-};
-
-export const createBackendEnvFile = async (
-  root: string,
-  opts: {
-    openAiKey?: string;
-    llamaCloudKey?: string;
-    vectorDb?: TemplateVectorDB;
-    model?: string;
-    embeddingModel?: string;
-    framework?: TemplateFramework;
-    dataSource?: TemplateDataSource;
-    port?: number;
-  },
-) => {
-  // Init env values
-  const envFileName = ".env";
-  const defaultEnvs = [
-    {
-      render: true,
-      name: "MODEL",
-      description: "The name of LLM model to use.",
-      value: opts.model || "gpt-3.5-turbo",
-    },
-    {
-      render: true,
-      name: "OPENAI_API_KEY",
-      description: "The OpenAI API key to use.",
-      value: opts.openAiKey,
-    },
-    // Add vector database environment variables
-    ...(opts.vectorDb ? getVectorDBEnvs(opts.vectorDb) : []),
-    // Add data source environment variables
-    ...(opts.dataSource ? getDataSourceEnvs(opts.dataSource) : []),
-  ];
-  let envVars: EnvVar[] = [];
-  if (opts.framework === "fastapi") {
-    envVars = [
-      ...defaultEnvs,
-      ...[
-        {
-          name: "APP_HOST",
-          description: "The address to start the backend app.",
-          value: "0.0.0.0",
-        },
-        {
-          name: "APP_PORT",
-          description: "The port to start the backend app.",
-          value: opts.port?.toString() || "8000",
-        },
-        {
-          name: "EMBEDDING_MODEL",
-          description: "Name of the embedding model to use.",
-          value: opts.embeddingModel,
-        },
-        {
-          name: "EMBEDDING_DIM",
-          description: "Dimension of the embedding model to use.",
-        },
-        {
-          name: "LLM_TEMPERATURE",
-          description: "Temperature for sampling from the model.",
-        },
-        {
-          name: "LLM_MAX_TOKENS",
-          description: "Maximum number of tokens to generate.",
-        },
-        {
-          name: "TOP_K",
-          description:
-            "The number of similar embeddings to return when retrieving documents.",
-          value: "3",
-        },
-        {
-          name: "SYSTEM_PROMPT",
-          description: `Custom system prompt.
-Example:
-SYSTEM_PROMPT="
-We have provided context information below.
----------------------
-{context_str}
----------------------
-Given this information, please answer the question: {query_str}
-"`,
-        },
-        (opts?.dataSource?.config as FileSourceConfig).useLlamaParse
-          ? {
-              name: "LLAMA_CLOUD_API_KEY",
-              description: `The Llama Cloud API key.`,
-              value: opts.llamaCloudKey,
-            }
-          : {},
-      ],
-    ];
-  } else {
-    envVars = [
-      ...defaultEnvs,
-      ...[
-        opts.framework === "nextjs"
-          ? {
-              name: "NEXT_PUBLIC_MODEL",
-              description:
-                "The LLM model to use (hardcode to front-end artifact).",
-            }
-          : {},
-      ],
-    ];
-  }
-  // Render and write env file
-  const content = renderEnvVar(envVars);
-  await fs.writeFile(path.join(root, envFileName), content);
-  console.log(`Created '${envFileName}' file. Please check the settings.`);
-};
-
-export const createFrontendEnvFile = async (
-  root: string,
-  opts: {
-    customApiPath?: string;
-    model?: string;
-  },
-) => {
-  const defaultFrontendEnvs = [
-    {
-      name: "MODEL",
-      description: "The OpenAI model to use.",
-      value: opts.model,
-    },
-    {
-      name: "NEXT_PUBLIC_MODEL",
-      description: "The OpenAI model to use (hardcode to front-end artifact).",
-      value: opts.model,
-    },
-    {
-      name: "NEXT_PUBLIC_CHAT_API",
-      description: "The backend API for chat endpoint.",
-      value: opts.customApiPath
-        ? opts.customApiPath
-        : "http://localhost:8000/api/chat",
-    },
-  ];
-  const content = renderEnvVar(defaultFrontendEnvs);
-  await fs.writeFile(path.join(root, ".env"), content);
-};

packages/create-llama/helpers/get-pkg-manager.ts

@@ -1,15 +0,0 @@
-export type PackageManager = "npm" | "pnpm" | "yarn";
-
-export function getPkgManager(): PackageManager {
-  const userAgent = process.env.npm_config_user_agent || "";
-
-  if (userAgent.startsWith("yarn")) {
-    return "yarn";
-  }
-
-  if (userAgent.startsWith("pnpm")) {
-    return "pnpm";
-  }
-
-  return "npm";
-}

packages/create-llama/helpers/git.ts

@@ -1,58 +0,0 @@
-/* eslint-disable import/no-extraneous-dependencies */
-import { execSync } from "child_process";
-import fs from "fs";
-import path from "path";
-
-function isInGitRepository(): boolean {
-  try {
-    execSync("git rev-parse --is-inside-work-tree", { stdio: "ignore" });
-    return true;
-  } catch (_) {}
-  return false;
-}
-
-function isInMercurialRepository(): boolean {
-  try {
-    execSync("hg --cwd . root", { stdio: "ignore" });
-    return true;
-  } catch (_) {}
-  return false;
-}
-
-function isDefaultBranchSet(): boolean {
-  try {
-    execSync("git config init.defaultBranch", { stdio: "ignore" });
-    return true;
-  } catch (_) {}
-  return false;
-}
-
-export function tryGitInit(root: string): boolean {
-  let didInit = false;
-  try {
-    execSync("git --version", { stdio: "ignore" });
-    if (isInGitRepository() || isInMercurialRepository()) {
-      return false;
-    }
-
-    execSync("git init", { stdio: "ignore" });
-    didInit = true;
-
-    if (!isDefaultBranchSet()) {
-      execSync("git checkout -b main", { stdio: "ignore" });
-    }
-
-    execSync("git add -A", { stdio: "ignore" });
-    execSync('git commit -m "Initial commit from Create Llama"', {
-      stdio: "ignore",
-    });
-    return true;
-  } catch (e) {
-    if (didInit) {
-      try {
-        fs.rmSync(path.join(root, ".git"), { recursive: true, force: true });
-      } catch (_) {}
-    }
-    return false;
-  }
-}

packages/create-llama/helpers/index.ts

@@ -1,192 +0,0 @@
-import { copy } from "./copy";
-import { callPackageManager } from "./install";
-
-import fs from "fs/promises";
-import path from "path";
-import { cyan } from "picocolors";
-
-import { COMMUNITY_OWNER, COMMUNITY_REPO } from "./constant";
-import { templatesDir } from "./dir";
-import { createBackendEnvFile, createFrontendEnvFile } from "./env-variables";
-import { PackageManager } from "./get-pkg-manager";
-import { installLlamapackProject } from "./llama-pack";
-import { isHavingPoetryLockFile, tryPoetryRun } from "./poetry";
-import { installPythonTemplate } from "./python";
-import { downloadAndExtractRepo } from "./repo";
-import {
-  FileSourceConfig,
-  InstallTemplateArgs,
-  TemplateDataSource,
-  TemplateFramework,
-  TemplateVectorDB,
-} from "./types";
-import { installTSTemplate } from "./typescript";
-
-// eslint-disable-next-line max-params
-async function generateContextData(
-  framework: TemplateFramework,
-  packageManager?: PackageManager,
-  openAiKey?: string,
-  vectorDb?: TemplateVectorDB,
-  dataSource?: TemplateDataSource,
-  llamaCloudKey?: string,
-) {
-  if (packageManager) {
-    const runGenerate = `${cyan(
-      framework === "fastapi"
-        ? "poetry run python app/engine/generate.py"
-        : `${packageManager} run generate`,
-    )}`;
-    const openAiKeyConfigured = openAiKey || process.env["OPENAI_API_KEY"];
-    const llamaCloudKeyConfigured = (dataSource?.config as FileSourceConfig)
-      ?.useLlamaParse
-      ? llamaCloudKey || process.env["LLAMA_CLOUD_API_KEY"]
-      : true;
-    const hasVectorDb = vectorDb && vectorDb !== "none";
-    if (framework === "fastapi") {
-      if (
-        openAiKeyConfigured &&
-        llamaCloudKeyConfigured &&
-        !hasVectorDb &&
-        isHavingPoetryLockFile()
-      ) {
-        console.log(`Running ${runGenerate} to generate the context data.`);
-        const result = tryPoetryRun("python app/engine/generate.py");
-        if (!result) {
-          console.log(`Failed to run ${runGenerate}.`);
-          process.exit(1);
-        }
-        console.log(`Generated context data`);
-        return;
-      }
-    } else {
-      if (openAiKeyConfigured && vectorDb === "none") {
-        console.log(`Running ${runGenerate} to generate the context data.`);
-        await callPackageManager(packageManager, true, ["run", "generate"]);
-        return;
-      }
-    }
-
-    const settings = [];
-    if (!openAiKeyConfigured) settings.push("your OpenAI key");
-    if (!llamaCloudKeyConfigured) settings.push("your Llama Cloud key");
-    if (hasVectorDb) settings.push("your Vector DB environment variables");
-    const settingsMessage =
-      settings.length > 0 ? `After setting ${settings.join(" and ")}, ` : "";
-    const generateMessage = `run ${runGenerate} to generate the context data.`;
-    console.log(`\n${settingsMessage}${generateMessage}\n\n`);
-  }
-}
-
-const copyContextData = async (
-  root: string,
-  dataSource?: TemplateDataSource,
-) => {
-  const destPath = path.join(root, "data");
-
-  const dataSourceConfig = dataSource?.config as FileSourceConfig;
-
-  // Copy file
-  if (dataSource?.type === "file") {
-    if (dataSourceConfig.path) {
-      console.log(`\nCopying file to ${cyan(destPath)}\n`);
-      await fs.mkdir(destPath, { recursive: true });
-      await fs.copyFile(
-        dataSourceConfig.path,
-        path.join(destPath, path.basename(dataSourceConfig.path)),
-      );
-    } else {
-      console.log("Missing file path in config");
-      process.exit(1);
-    }
-    return;
-  }
-
-  // Copy folder
-  if (dataSource?.type === "folder") {
-    const srcPath =
-      dataSourceConfig.path ?? path.join(templatesDir, "components", "data");
-    console.log(`\nCopying data to ${cyan(destPath)}\n`);
-    await copy("**", destPath, {
-      parents: true,
-      cwd: srcPath,
-    });
-    return;
-  }
-};
-
-const installCommunityProject = async ({
-  root,
-  communityProjectPath,
-}: Pick<InstallTemplateArgs, "root" | "communityProjectPath">) => {
-  console.log("\nInstalling community project:", communityProjectPath!);
-  await downloadAndExtractRepo(root, {
-    username: COMMUNITY_OWNER,
-    name: COMMUNITY_REPO,
-    branch: "main",
-    filePath: communityProjectPath!,
-  });
-};
-
-export const installTemplate = async (
-  props: InstallTemplateArgs & { backend: boolean },
-) => {
-  process.chdir(props.root);
-
-  if (props.template === "community" && props.communityProjectPath) {
-    await installCommunityProject(props);
-    return;
-  }
-
-  if (props.template === "llamapack" && props.llamapack) {
-    await installLlamapackProject(props);
-    return;
-  }
-
-  if (props.framework === "fastapi") {
-    await installPythonTemplate(props);
-  } else {
-    await installTSTemplate(props);
-  }
-
-  if (props.backend) {
-    // This is a backend, so we need to copy the test data and create the env file.
-
-    // Copy the environment file to the target directory.
-    await createBackendEnvFile(props.root, {
-      openAiKey: props.openAiKey,
-      llamaCloudKey: props.llamaCloudKey,
-      vectorDb: props.vectorDb,
-      model: props.model,
-      embeddingModel: props.embeddingModel,
-      framework: props.framework,
-      dataSource: props.dataSource,
-      port: props.externalPort,
-    });
-
-    if (props.engine === "context") {
-      await copyContextData(props.root, props.dataSource);
-      if (
-        props.postInstallAction === "runApp" ||
-        props.postInstallAction === "dependencies"
-      ) {
-        await generateContextData(
-          props.framework,
-          props.packageManager,
-          props.openAiKey,
-          props.vectorDb,
-          props.dataSource,
-          props.llamaCloudKey,
-        );
-      }
-    }
-  } else {
-    // this is a frontend for a full-stack app, create .env file with model information
-    createFrontendEnvFile(props.root, {
-      model: props.model,
-      customApiPath: props.customApiPath,
-    });
-  }
-};
-
-export * from "./types";

packages/create-llama/helpers/install.ts

@@ -1,50 +0,0 @@
-/* eslint-disable import/no-extraneous-dependencies */
-import spawn from "cross-spawn";
-import { yellow } from "picocolors";
-import type { PackageManager } from "./get-pkg-manager";
-
-/**
- * Spawn a package manager installation based on user preference.
- *
- * @returns A Promise that resolves once the installation is finished.
- */
-export async function callPackageManager(
-  /** Indicate which package manager to use. */
-  packageManager: PackageManager,
-  /** Indicate whether there is an active Internet connection.*/
-  isOnline: boolean,
-  args: string[] = ["install"],
-): Promise<void> {
-  if (!isOnline) {
-    console.log(
-      yellow("You appear to be offline.\nFalling back to the local cache."),
-    );
-    args.push("--offline");
-  }
-  /**
-   * Return a Promise that resolves once the installation is finished.
-   */
-  return new Promise((resolve, reject) => {
-    /**
-     * Spawn the installation process.
-     */
-    const child = spawn(packageManager, args, {
-      stdio: "inherit",
-      env: {
-        ...process.env,
-        ADBLOCK: "1",
-        // we set NODE_ENV to development as pnpm skips dev
-        // dependencies when production
-        NODE_ENV: "development",
-        DISABLE_OPENCOLLECTIVE: "1",
-      },
-    });
-    child.on("close", (code) => {
-      if (code !== 0) {
-        reject({ command: `${packageManager} ${args.join(" ")}` });
-        return;
-      }
-      resolve();
-    });
-  });
-}

packages/create-llama/helpers/is-folder-empty.ts

@@ -1,62 +0,0 @@
-/* eslint-disable import/no-extraneous-dependencies */
-import fs from "fs";
-import path from "path";
-import { blue, green } from "picocolors";
-
-export function isFolderEmpty(root: string, name: string): boolean {
-  const validFiles = [
-    ".DS_Store",
-    ".git",
-    ".gitattributes",
-    ".gitignore",
-    ".gitlab-ci.yml",
-    ".hg",
-    ".hgcheck",
-    ".hgignore",
-    ".idea",
-    ".npmignore",
-    ".travis.yml",
-    "LICENSE",
-    "Thumbs.db",
-    "docs",
-    "mkdocs.yml",
-    "npm-debug.log",
-    "yarn-debug.log",
-    "yarn-error.log",
-    "yarnrc.yml",
-    ".yarn",
-  ];
-
-  const conflicts = fs
-    .readdirSync(root)
-    .filter((file) => !validFiles.includes(file))
-    // Support IntelliJ IDEA-based editors
-    .filter((file) => !/\.iml$/.test(file));
-
-  if (conflicts.length > 0) {
-    console.log(
-      `The directory ${green(name)} contains files that could conflict:`,
-    );
-    console.log();
-    for (const file of conflicts) {
-      try {
-        const stats = fs.lstatSync(path.join(root, file));
-        if (stats.isDirectory()) {
-          console.log(`  ${blue(file)}/`);
-        } else {
-          console.log(`  ${file}`);
-        }
-      } catch {
-        console.log(`  ${file}`);
-      }
-    }
-    console.log();
-    console.log(
-      "Either try using a new directory name, or remove the files listed above.",
-    );
-    console.log();
-    return false;
-  }
-
-  return true;
-}

packages/create-llama/helpers/is-online.ts

@@ -1,40 +0,0 @@
-import { execSync } from "child_process";
-import dns from "dns";
-import url from "url";
-
-function getProxy(): string | undefined {
-  if (process.env.https_proxy) {
-    return process.env.https_proxy;
-  }
-
-  try {
-    const httpsProxy = execSync("npm config get https-proxy").toString().trim();
-    return httpsProxy !== "null" ? httpsProxy : undefined;
-  } catch (e) {
-    return;
-  }
-}
-
-export function getOnline(): Promise<boolean> {
-  return new Promise((resolve) => {
-    dns.lookup("registry.yarnpkg.com", (registryErr) => {
-      if (!registryErr) {
-        return resolve(true);
-      }
-
-      const proxy = getProxy();
-      if (!proxy) {
-        return resolve(false);
-      }
-
-      const { hostname } = url.parse(proxy);
-      if (!hostname) {
-        return resolve(false);
-      }
-
-      dns.lookup(hostname, (proxyErr) => {
-        resolve(proxyErr == null);
-      });
-    });
-  });
-}

packages/create-llama/helpers/is-url.ts

@@ -1,8 +0,0 @@
-export function isUrl(url: string): boolean {
-  try {
-    new URL(url);
-    return true;
-  } catch (error) {
-    return false;
-  }
-}

packages/create-llama/helpers/is-writeable.ts

@@ -1,10 +0,0 @@
-import fs from "fs";
-
-export async function isWriteable(directory: string): Promise<boolean> {
-  try {
-    await fs.promises.access(directory, (fs.constants || fs).W_OK);
-    return true;
-  } catch (err) {
-    return false;
-  }
-}

packages/create-llama/helpers/llama-pack.ts

@@ -1,148 +0,0 @@
-import fs from "fs/promises";
-import got from "got";
-import path from "path";
-import { parse } from "smol-toml";
-import {
-  LLAMA_PACK_FOLDER,
-  LLAMA_PACK_FOLDER_PATH,
-  LLAMA_PACK_OWNER,
-  LLAMA_PACK_REPO,
-} from "./constant";
-import { copy } from "./copy";
-import { templatesDir } from "./dir";
-import { addDependencies, installPythonDependencies } from "./python";
-import { getRepoRawContent } from "./repo";
-import { InstallTemplateArgs } from "./types";
-
-const getLlamaPackFolderSHA = async () => {
-  const url = `https://api.github.com/repos/${LLAMA_PACK_OWNER}/${LLAMA_PACK_REPO}/contents`;
-  const response = await got(url, {
-    responseType: "json",
-  });
-  const data = response.body as any[];
-  const llamaPackFolder = data.find((item) => item.name === LLAMA_PACK_FOLDER);
-  return llamaPackFolder.sha;
-};
-
-const getLLamaPackFolderTree = async (
-  sha: string,
-): Promise<
-  Array<{
-    path: string;
-  }>
-> => {
-  const url = `https://api.github.com/repos/${LLAMA_PACK_OWNER}/${LLAMA_PACK_REPO}/git/trees/${sha}?recursive=1`;
-  const response = await got(url, {
-    responseType: "json",
-  });
-  return (response.body as any).tree;
-};
-
-export async function getAvailableLlamapackOptions(): Promise<
-  {
-    name: string;
-    folderPath: string;
-  }[]
-> {
-  const EXAMPLE_RELATIVE_PATH = "/examples/example.py";
-  const PACK_FOLDER_SUBFIX = "llama-index-packs";
-
-  const llamaPackFolderSHA = await getLlamaPackFolderSHA();
-  const llamaPackTree = await getLLamaPackFolderTree(llamaPackFolderSHA);
-
-  // Return options that have example files
-  const exampleFiles = llamaPackTree.filter((item) =>
-    item.path.endsWith(EXAMPLE_RELATIVE_PATH),
-  );
-  const options = exampleFiles.map((file) => {
-    const packFolder = file.path.substring(
-      0,
-      file.path.indexOf(EXAMPLE_RELATIVE_PATH),
-    );
-    const packName = packFolder.substring(PACK_FOLDER_SUBFIX.length + 1);
-    return {
-      name: packName,
-      folderPath: packFolder,
-    };
-  });
-  return options;
-}
-
-const copyLlamapackEmptyProject = async ({
-  root,
-}: Pick<InstallTemplateArgs, "root">) => {
-  const templatePath = path.join(
-    templatesDir,
-    "components/sample-projects/llamapack",
-  );
-  await copy("**", root, {
-    parents: true,
-    cwd: templatePath,
-  });
-};
-
-const copyData = async ({
-  root,
-}: Pick<InstallTemplateArgs, "root" | "llamapack">) => {
-  const dataPath = path.join(templatesDir, "components/data");
-  await copy("**", path.join(root, "data"), {
-    parents: true,
-    cwd: dataPath,
-  });
-};
-
-const installLlamapackExample = async ({
-  root,
-  llamapack,
-}: Pick<InstallTemplateArgs, "root" | "llamapack">) => {
-  const exampleFileName = "example.py";
-  const readmeFileName = "README.md";
-  const projectTomlFileName = "pyproject.toml";
-  const exampleFilePath = `${LLAMA_PACK_FOLDER_PATH}/${llamapack}/examples/${exampleFileName}`;
-  const readmeFilePath = `${LLAMA_PACK_FOLDER_PATH}/${llamapack}/${readmeFileName}`;
-  const projectTomlFilePath = `${LLAMA_PACK_FOLDER_PATH}/${llamapack}/${projectTomlFileName}`;
-
-  // Download example.py from llamapack and save to root
-  const exampleContent = await getRepoRawContent(exampleFilePath);
-  await fs.writeFile(path.join(root, exampleFileName), exampleContent);
-
-  // Download README.md from llamapack and combine with README-template.md,
-  // save to root and then delete template file
-  const readmeContent = await getRepoRawContent(readmeFilePath);
-  const readmeTemplateContent = await fs.readFile(
-    path.join(root, "README-template.md"),
-    "utf-8",
-  );
-  await fs.writeFile(
-    path.join(root, readmeFileName),
-    `${readmeContent}\n${readmeTemplateContent}`,
-  );
-  await fs.unlink(path.join(root, "README-template.md"));
-
-  // Download pyproject.toml from llamapack, parse it to get package name and version,
-  // then add it as a dependency to current toml file in the project
-  const projectTomlContent = await getRepoRawContent(projectTomlFilePath);
-  const fileParsed = parse(projectTomlContent) as any;
-  const packageName = fileParsed.tool.poetry.name;
-  const packageVersion = fileParsed.tool.poetry.version;
-  await addDependencies(root, [
-    {
-      name: packageName,
-      version: packageVersion,
-    },
-  ]);
-};
-
-export const installLlamapackProject = async ({
-  root,
-  llamapack,
-  postInstallAction,
-}: Pick<InstallTemplateArgs, "root" | "llamapack" | "postInstallAction">) => {
-  console.log("\nInstalling Llamapack project:", llamapack!);
-  await copyLlamapackEmptyProject({ root });
-  await copyData({ root });
-  await installLlamapackExample({ root, llamapack });
-  if (postInstallAction === "runApp" || postInstallAction === "dependencies") {
-    installPythonDependencies({ noRoot: true });
-  }
-};

packages/create-llama/helpers/make-dir.ts

@@ -1,8 +0,0 @@
-import fs from "fs";
-
-export function makeDir(
-  root: string,
-  options = { recursive: true },
-): Promise<string | undefined> {
-  return fs.promises.mkdir(root, options);
-}

packages/create-llama/helpers/poetry.ts

@@ -1,36 +0,0 @@
-/* eslint-disable import/no-extraneous-dependencies */
-import { execSync } from "child_process";
-import fs from "fs";
-
-export function isPoetryAvailable(): boolean {
-  try {
-    execSync("poetry --version", { stdio: "ignore" });
-    return true;
-  } catch (_) {}
-  return false;
-}
-
-export function tryPoetryInstall(noRoot: boolean): boolean {
-  try {
-    execSync(`poetry install${noRoot ? " --no-root" : ""}`, {
-      stdio: "inherit",
-    });
-    return true;
-  } catch (_) {}
-  return false;
-}
-
-export function tryPoetryRun(command: string): boolean {
-  try {
-    execSync(`poetry run ${command}`, { stdio: "inherit" });
-    return true;
-  } catch (_) {}
-  return false;
-}
-
-export function isHavingPoetryLockFile(): boolean {
-  try {
-    return fs.existsSync("poetry.lock");
-  } catch (_) {}
-  return false;
-}

packages/create-llama/helpers/python.ts

@@ -1,272 +0,0 @@
-import fs from "fs/promises";
-import path from "path";
-import { cyan, red } from "picocolors";
-import { parse, stringify } from "smol-toml";
-import terminalLink from "terminal-link";
-import { copy } from "./copy";
-import { templatesDir } from "./dir";
-import { isPoetryAvailable, tryPoetryInstall } from "./poetry";
-import { Tool } from "./tools";
-import {
-  FileSourceConfig,
-  InstallTemplateArgs,
-  TemplateDataSource,
-  TemplateVectorDB,
-} from "./types";
-
-interface Dependency {
-  name: string;
-  version?: string;
-  extras?: string[];
-}
-
-const getAdditionalDependencies = (
-  vectorDb?: TemplateVectorDB,
-  dataSource?: TemplateDataSource,
-  tools?: Tool[],
-) => {
-  const dependencies: Dependency[] = [];
-
-  // Add vector db dependencies
-  switch (vectorDb) {
-    case "mongo": {
-      dependencies.push({
-        name: "llama-index-vector-stores-mongodb",
-        version: "^0.1.3",
-      });
-      break;
-    }
-    case "pg": {
-      dependencies.push({
-        name: "llama-index-vector-stores-postgres",
-        version: "^0.1.1",
-      });
-    }
-    case "pinecone": {
-      dependencies.push({
-        name: "llama-index-vector-stores-pinecone",
-        version: "^0.1.3",
-      });
-      break;
-    }
-  }
-
-  // Add data source dependencies
-  const dataSourceType = dataSource?.type;
-  if (dataSourceType === "file" || dataSourceType === "folder") {
-    // llama-index-readers-file (pdf, excel, csv) is already included in llama_index package
-    dependencies.push({
-      name: "docx2txt",
-      version: "^0.8",
-    });
-  } else if (dataSourceType === "web") {
-    dependencies.push({
-      name: "llama-index-readers-web",
-      version: "^0.1.6",
-    });
-  }
-
-  // Add tools dependencies
-  tools?.forEach((tool) => {
-    tool.dependencies?.forEach((dep) => {
-      dependencies.push(dep);
-    });
-  });
-
-  return dependencies;
-};
-
-const mergePoetryDependencies = (
-  dependencies: Dependency[],
-  existingDependencies: Record<string, Omit<Dependency, "name">>,
-) => {
-  for (const dependency of dependencies) {
-    let value = existingDependencies[dependency.name] ?? {};
-
-    // default string value is equal to attribute "version"
-    if (typeof value === "string") {
-      value = { version: value };
-    }
-
-    value.version = dependency.version ?? value.version;
-    value.extras = dependency.extras ?? value.extras;
-
-    if (value.version === undefined) {
-      throw new Error(
-        `Dependency "${dependency.name}" is missing attribute "version"!`,
-      );
-    }
-
-    existingDependencies[dependency.name] = value;
-  }
-};
-
-export const addDependencies = async (
-  projectDir: string,
-  dependencies: Dependency[],
-) => {
-  if (dependencies.length === 0) return;
-
-  const FILENAME = "pyproject.toml";
-  try {
-    // Parse toml file
-    const file = path.join(projectDir, FILENAME);
-    const fileContent = await fs.readFile(file, "utf8");
-    const fileParsed = parse(fileContent);
-
-    // Modify toml dependencies
-    const tool = fileParsed.tool as any;
-    const existingDependencies = tool.poetry.dependencies;
-    mergePoetryDependencies(dependencies, existingDependencies);
-
-    // Write toml file
-    const newFileContent = stringify(fileParsed);
-    await fs.writeFile(file, newFileContent);
-
-    const dependenciesString = dependencies.map((d) => d.name).join(", ");
-    console.log(`\nAdded ${dependenciesString} to ${cyan(FILENAME)}\n`);
-  } catch (error) {
-    console.log(
-      `Error while updating dependencies for Poetry project file ${FILENAME}\n`,
-      error,
-    );
-  }
-};
-
-export const installPythonDependencies = (
-  { noRoot }: { noRoot: boolean } = { noRoot: false },
-) => {
-  if (isPoetryAvailable()) {
-    console.log(
-      `Installing python dependencies using poetry. This may take a while...`,
-    );
-    const installSuccessful = tryPoetryInstall(noRoot);
-    if (!installSuccessful) {
-      console.error(
-        red(
-          "Installing dependencies using poetry failed. Please check error log above and try running create-llama again.",
-        ),
-      );
-      process.exit(1);
-    }
-  } else {
-    console.error(
-      red(
-        `Poetry is not available in the current environment. Please check ${terminalLink(
-          "Poetry Installation",
-          `https://python-poetry.org/docs/#installation`,
-        )} to install poetry first, then run create-llama again.`,
-      ),
-    );
-    process.exit(1);
-  }
-};
-
-export const installPythonTemplate = async ({
-  root,
-  template,
-  framework,
-  engine,
-  vectorDb,
-  dataSource,
-  tools,
-  postInstallAction,
-}: Pick<
-  InstallTemplateArgs,
-  | "root"
-  | "framework"
-  | "template"
-  | "engine"
-  | "vectorDb"
-  | "dataSource"
-  | "tools"
-  | "postInstallAction"
->) => {
-  console.log("\nInitializing Python project with template:", template, "\n");
-  const templatePath = path.join(templatesDir, "types", template, framework);
-  await copy("**", root, {
-    parents: true,
-    cwd: templatePath,
-    rename(name) {
-      switch (name) {
-        case "gitignore": {
-          return `.${name}`;
-        }
-        // README.md is ignored by webpack-asset-relocator-loader used by ncc:
-        // https://github.com/vercel/webpack-asset-relocator-loader/blob/e9308683d47ff507253e37c9bcbb99474603192b/src/asset-relocator.js#L227
-        case "README-template.md": {
-          return "README.md";
-        }
-        default: {
-          return name;
-        }
-      }
-    },
-  });
-
-  if (engine === "context") {
-    const enginePath = path.join(root, "app", "engine");
-    const compPath = path.join(templatesDir, "components");
-
-    const vectorDbDirName = vectorDb ?? "none";
-    const VectorDBPath = path.join(
-      compPath,
-      "vectordbs",
-      "python",
-      vectorDbDirName,
-    );
-    await copy("**", enginePath, {
-      parents: true,
-      cwd: VectorDBPath,
-    });
-
-    // Copy engine code
-    if (tools !== undefined && tools.length > 0) {
-      await copy("**", enginePath, {
-        parents: true,
-        cwd: path.join(compPath, "engines", "python", "agent"),
-      });
-      // Write tools_config.json
-      const configContent: Record<string, any> = {};
-      tools.forEach((tool) => {
-        configContent[tool.name] = tool.config ?? {};
-      });
-      const configFilePath = path.join(root, "tools_config.json");
-      await fs.writeFile(
-        configFilePath,
-        JSON.stringify(configContent, null, 2),
-      );
-    } else {
-      await copy("**", enginePath, {
-        parents: true,
-        cwd: path.join(compPath, "engines", "python", "chat"),
-      });
-    }
-
-    const dataSourceType = dataSource?.type;
-    if (dataSourceType !== undefined && dataSourceType !== "none") {
-      let loaderFolder: string;
-      if (dataSourceType === "file" || dataSourceType === "folder") {
-        const dataSourceConfig = dataSource?.config as FileSourceConfig;
-        loaderFolder = dataSourceConfig.useLlamaParse ? "llama_parse" : "file";
-      } else {
-        loaderFolder = dataSourceType;
-      }
-      await copy("**", enginePath, {
-        parents: true,
-        cwd: path.join(compPath, "loaders", "python", loaderFolder),
-      });
-    }
-  }
-
-  const addOnDependencies = getAdditionalDependencies(
-    vectorDb,
-    dataSource,
-    tools,
-  );
-  await addDependencies(root, addOnDependencies);
-
-  if (postInstallAction === "runApp" || postInstallAction === "dependencies") {
-    installPythonDependencies();
-  }
-};

packages/create-llama/helpers/repo.ts

@@ -1,71 +0,0 @@
-import { createWriteStream, promises } from "fs";
-import got from "got";
-import { tmpdir } from "os";
-import { join } from "path";
-import { Stream } from "stream";
-import tar from "tar";
-import { promisify } from "util";
-import { makeDir } from "./make-dir";
-
-export type RepoInfo = {
-  username: string;
-  name: string;
-  branch: string;
-  filePath: string;
-};
-
-const pipeline = promisify(Stream.pipeline);
-
-async function downloadTar(url: string) {
-  const tempFile = join(tmpdir(), `next.js-cna-example.temp-${Date.now()}`);
-  await pipeline(got.stream(url), createWriteStream(tempFile));
-  return tempFile;
-}
-
-export async function downloadAndExtractRepo(
-  root: string,
-  { username, name, branch, filePath }: RepoInfo,
-) {
-  await makeDir(root);
-
-  const tempFile = await downloadTar(
-    `https://codeload.github.com/${username}/${name}/tar.gz/${branch}`,
-  );
-
-  await tar.x({
-    file: tempFile,
-    cwd: root,
-    strip: filePath ? filePath.split("/").length + 1 : 1,
-    filter: (p) =>
-      p.startsWith(
-        `${name}-${branch.replace(/\//g, "-")}${
-          filePath ? `/${filePath}/` : "/"
-        }`,
-      ),
-  });
-
-  await promises.unlink(tempFile);
-}
-
-export async function getRepoRootFolders(
-  owner: string,
-  repo: string,
-): Promise<string[]> {
-  const url = `https://api.github.com/repos/${owner}/${repo}/contents`;
-
-  const response = await got(url, {
-    responseType: "json",
-  });
-
-  const data = response.body as any[];
-  const folders = data.filter((item) => item.type === "dir");
-  return folders.map((item) => item.name);
-}
-
-export async function getRepoRawContent(repoFilePath: string) {
-  const url = `https://raw.githubusercontent.com/${repoFilePath}`;
-  const response = await got(url, {
-    responseType: "text",
-  });
-  return response.body;
-}

packages/create-llama/helpers/run-app.ts

@@ -1,88 +0,0 @@
-import { ChildProcess, SpawnOptions, spawn } from "child_process";
-import path from "path";
-import { TemplateFramework } from "./types";
-
-const createProcess = (
-  command: string,
-  args: string[],
-  options: SpawnOptions,
-) => {
-  return spawn(command, args, {
-    ...options,
-    shell: true,
-  })
-    .on("exit", function (code) {
-      if (code !== 0) {
-        console.log(`Child process exited with code=${code}`);
-        process.exit(1);
-      }
-    })
-    .on("error", function (err) {
-      console.log("Error when running chill process: ", err);
-      process.exit(1);
-    });
-};
-
-// eslint-disable-next-line max-params
-export async function runApp(
-  appPath: string,
-  frontend: boolean,
-  framework: TemplateFramework,
-  port?: number,
-  externalPort?: number,
-): Promise<any> {
-  let backendAppProcess: ChildProcess;
-  let frontendAppProcess: ChildProcess | undefined;
-  const frontendPort = port || 3000;
-  let backendPort = externalPort || 8000;
-
-  // Callback to kill app processes
-  process.on("exit", () => {
-    console.log("Killing app processes...");
-    backendAppProcess.kill();
-    frontendAppProcess?.kill();
-  });
-
-  let backendCommand = "";
-  let backendArgs: string[];
-  if (framework === "fastapi") {
-    backendCommand = "poetry";
-    backendArgs = [
-      "run",
-      "uvicorn",
-      "main:app",
-      "--host=0.0.0.0",
-      "--port=" + backendPort,
-    ];
-  } else if (framework === "nextjs") {
-    backendCommand = "npm";
-    backendArgs = ["run", "dev"];
-    backendPort = frontendPort;
-  } else {
-    backendCommand = "npm";
-    backendArgs = ["run", "dev"];
-  }
-
-  if (frontend) {
-    return new Promise((resolve, reject) => {
-      backendAppProcess = createProcess(backendCommand, backendArgs, {
-        stdio: "inherit",
-        cwd: path.join(appPath, "backend"),
-        env: { ...process.env, PORT: `${backendPort}` },
-      });
-      frontendAppProcess = createProcess("npm", ["run", "dev"], {
-        stdio: "inherit",
-        cwd: path.join(appPath, "frontend"),
-        env: { ...process.env, PORT: `${frontendPort}` },
-      });
-    });
-  } else {
-    return new Promise((resolve, reject) => {
-      backendAppProcess = createProcess(backendCommand, backendArgs, {
-        stdio: "inherit",
-        cwd: path.join(appPath),
-        env: { ...process.env, PORT: `${backendPort}` },
-      });
-    });
-  }
-}

packages/create-llama/helpers/tools.ts

@@ -1,71 +0,0 @@
-import { red } from "picocolors";
-
-export type Tool = {
-  display: string;
-  name: string;
-  config?: Record<string, any>;
-  dependencies?: ToolDependencies[];
-};
-export type ToolDependencies = {
-  name: string;
-  version?: string;
-};
-
-export const supportedTools: Tool[] = [
-  {
-    display: "Google Search (configuration required after installation)",
-    name: "google.GoogleSearchToolSpec",
-    config: {
-      engine:
-        "Your search engine id, see https://developers.google.com/custom-search/v1/overview#prerequisites",
-      key: "Your search api key",
-      num: 2,
-    },
-    dependencies: [
-      {
-        name: "llama-index-tools-google",
-        version: "0.1.2",
-      },
-    ],
-  },
-  {
-    display: "Wikipedia",
-    name: "wikipedia.WikipediaToolSpec",
-    dependencies: [
-      {
-        name: "llama-index-tools-wikipedia",
-        version: "0.1.2",
-      },
-    ],
-  },
-];
-
-export const getTool = (toolName: string): Tool | undefined => {
-  return supportedTools.find((tool) => tool.name === toolName);
-};
-
-export const getTools = (toolsName: string[]): Tool[] => {
-  const tools: Tool[] = [];
-  for (const toolName of toolsName) {
-    const tool = getTool(toolName);
-    if (!tool) {
-      console.log(
-        red(
-          `Error: Tool '${toolName}' is not supported. Supported tools are: ${supportedTools
-            .map((t) => t.name)
-            .join(", ")}`,
-        ),
-      );
-      process.exit(1);
-    }
-    tools.push(tool);
-  }
-  return tools;
-};
-
-export const toolsRequireConfig = (tools?: Tool[]): boolean => {
-  if (tools) {
-    return tools?.some((tool) => Object.keys(tool.config || {}).length > 0);
-  }
-  return false;
-};

packages/create-llama/helpers/types.ts

@@ -1,52 +0,0 @@
-import { PackageManager } from "../helpers/get-pkg-manager";
-import { Tool } from "./tools";
-
-export type TemplateType = "simple" | "streaming" | "community" | "llamapack";
-export type TemplateFramework = "nextjs" | "express" | "fastapi";
-export type TemplateEngine = "simple" | "context";
-export type TemplateUI = "html" | "shadcn";
-export type TemplateVectorDB = "none" | "mongo" | "pg" | "pinecone";
-export type TemplatePostInstallAction =
-  | "none"
-  | "VSCode"
-  | "dependencies"
-  | "runApp";
-export type TemplateDataSource = {
-  type: TemplateDataSourceType;
-  config: TemplateDataSourceConfig;
-};
-export type TemplateDataSourceType = "none" | "file" | "folder" | "web";
-// Config for both file and folder
-export type FileSourceConfig = {
-  path?: string;
-  useLlamaParse?: boolean;
-};
-export type WebSourceConfig = {
-  baseUrl?: string;
-  depth?: number;
-};
-export type TemplateDataSourceConfig = FileSourceConfig | WebSourceConfig;
-
-export interface InstallTemplateArgs {
-  appName: string;
-  root: string;
-  packageManager: PackageManager;
-  isOnline: boolean;
-  template: TemplateType;
-  framework: TemplateFramework;
-  engine: TemplateEngine;
-  ui: TemplateUI;
-  dataSource?: TemplateDataSource;
-  eslint: boolean;
-  customApiPath?: string;
-  openAiKey?: string;
-  llamaCloudKey?: string;
-  model: string;
-  embeddingModel: string;
-  communityProjectPath?: string;
-  llamapack?: string;
-  vectorDb?: TemplateVectorDB;
-  externalPort?: number;
-  postInstallAction?: TemplatePostInstallAction;
-  tools?: Tool[];
-}

packages/create-llama/helpers/typescript.ts

@@ -1,227 +0,0 @@
-import fs from "fs/promises";
-import os from "os";
-import path from "path";
-import { bold, cyan } from "picocolors";
-import { version } from "../../core/package.json";
-import { copy } from "../helpers/copy";
-import { callPackageManager } from "../helpers/install";
-import { templatesDir } from "./dir";
-import { PackageManager } from "./get-pkg-manager";
-import { InstallTemplateArgs } from "./types";
-
-const rename = (name: string) => {
-  switch (name) {
-    case "gitignore":
-    case "eslintrc.json": {
-      return `.${name}`;
-    }
-    // README.md is ignored by webpack-asset-relocator-loader used by ncc:
-    // https://github.com/vercel/webpack-asset-relocator-loader/blob/e9308683d47ff507253e37c9bcbb99474603192b/src/asset-relocator.js#L227
-    case "README-template.md": {
-      return "README.md";
-    }
-    default: {
-      return name;
-    }
-  }
-};
-
-export const installTSDependencies = async (
-  packageJson: any,
-  packageManager: PackageManager,
-  isOnline: boolean,
-): Promise<void> => {
-  console.log("\nInstalling dependencies:");
-  for (const dependency in packageJson.dependencies)
-    console.log(`- ${cyan(dependency)}`);
-
-  console.log("\nInstalling devDependencies:");
-  for (const dependency in packageJson.devDependencies)
-    console.log(`- ${cyan(dependency)}`);
-
-  console.log();
-
-  await callPackageManager(packageManager, isOnline).catch((error) => {
-    console.error("Failed to install TS dependencies. Exiting...");
-    process.exit(1);
-  });
-};
-
-/**
- * Install a LlamaIndex internal template to a given `root` directory.
- */
-export const installTSTemplate = async ({
-  appName,
-  root,
-  packageManager,
-  isOnline,
-  template,
-  framework,
-  engine,
-  ui,
-  eslint,
-  customApiPath,
-  vectorDb,
-  postInstallAction,
-  backend,
-}: InstallTemplateArgs & { backend: boolean }) => {
-  console.log(bold(`Using ${packageManager}.`));
-
-  /**
-   * Copy the template files to the target directory.
-   */
-  console.log("\nInitializing project with template:", template, "\n");
-  const templatePath = path.join(templatesDir, "types", template, framework);
-  const copySource = ["**"];
-  if (!eslint) copySource.push("!eslintrc.json");
-
-  await copy(copySource, root, {
-    parents: true,
-    cwd: templatePath,
-    rename,
-  });
-
-  /**
-   * If next.js is not used as a backend, update next.config.js to use static site generation.
-   */
-  if (framework === "nextjs" && !backend) {
-    // update next.config.json for static site generation
-    const nextConfigJsonFile = path.join(root, "next.config.json");
-    const nextConfigJson: any = JSON.parse(
-      await fs.readFile(nextConfigJsonFile, "utf8"),
-    );
-    nextConfigJson.output = "export";
-    nextConfigJson.images = { unoptimized: true };
-    await fs.writeFile(
-      nextConfigJsonFile,
-      JSON.stringify(nextConfigJson, null, 2) + os.EOL,
-    );
-  }
-
-  /**
-   * Copy the selected chat engine files to the target directory and reference it.
-   */
-  let relativeEngineDestPath;
-  const compPath = path.join(templatesDir, "components");
-  if (engine && (framework === "express" || framework === "nextjs")) {
-    console.log("\nUsing chat engine:", engine, "\n");
-
-    let vectorDBFolder: string = engine;
-
-    if (engine !== "simple" && vectorDb) {
-      console.log("\nUsing vector DB:", vectorDb, "\n");
-      vectorDBFolder = vectorDb;
-    }
-
-    const VectorDBPath = path.join(
-      compPath,
-      "vectordbs",
-      "typescript",
-      vectorDBFolder,
-    );
-    relativeEngineDestPath =
-      framework === "nextjs"
-        ? path.join("app", "api", "chat")
-        : path.join("src", "controllers");
-    await copy("**", path.join(root, relativeEngineDestPath, "engine"), {
-      parents: true,
-      cwd: VectorDBPath,
-    });
-  }
-
-  /**
-   * Copy the selected UI files to the target directory and reference it.
-   */
-  if (framework === "nextjs" && ui !== "shadcn") {
-    console.log("\nUsing UI:", ui, "\n");
-    const uiPath = path.join(compPath, "ui", ui);
-    const destUiPath = path.join(root, "app", "components", "ui");
-    // remove the default ui folder
-    await fs.rm(destUiPath, { recursive: true });
-    // copy the selected ui folder
-    await copy("**", destUiPath, {
-      parents: true,
-      cwd: uiPath,
-      rename,
-    });
-  }
-
-  /**
-   * Update the package.json scripts.
-   */
-  const packageJsonFile = path.join(root, "package.json");
-  const packageJson: any = JSON.parse(
-    await fs.readFile(packageJsonFile, "utf8"),
-  );
-  packageJson.name = appName;
-  packageJson.version = "0.1.0";
-
-  packageJson.dependencies = {
-    ...packageJson.dependencies,
-    llamaindex: version,
-  };
-
-  if (framework === "nextjs" && customApiPath) {
-    console.log(
-      "\nUsing external API with custom API path:",
-      customApiPath,
-      "\n",
-    );
-    // remove the default api folder
-    const apiPath = path.join(root, "app", "api");
-    await fs.rm(apiPath, { recursive: true });
-    // modify the dev script to use the custom api path
-  }
-
-  if (engine === "context" && relativeEngineDestPath) {
-    // add generate script if using context engine
-    packageJson.scripts = {
-      ...packageJson.scripts,
-      generate: `node ${path.join(
-        relativeEngineDestPath,
-        "engine",
-        "generate.mjs",
-      )}`,
-    };
-  }
-
-  if (framework === "nextjs" && ui === "html") {
-    // remove shadcn dependencies if html ui is selected
-    packageJson.dependencies = {
-      ...packageJson.dependencies,
-      "tailwind-merge": undefined,
-      "@radix-ui/react-slot": undefined,
-      "class-variance-authority": undefined,
-      clsx: undefined,
-      "lucide-react": undefined,
-      remark: undefined,
-      "remark-code-import": undefined,
-      "remark-gfm": undefined,
-      "remark-math": undefined,
-      "react-markdown": undefined,
-      "react-syntax-highlighter": undefined,
-    };
-
-    packageJson.devDependencies = {
-      ...packageJson.devDependencies,
-      "@types/react-syntax-highlighter": undefined,
-    };
-  }
-
-  if (!eslint) {
-    // Remove packages starting with "eslint" from devDependencies
-    packageJson.devDependencies = Object.fromEntries(
-      Object.entries(packageJson.devDependencies).filter(
-        ([key]) => !key.startsWith("eslint"),
-      ),
-    );
-  }
-  await fs.writeFile(
-    packageJsonFile,
-    JSON.stringify(packageJson, null, 2) + os.EOL,
-  );
-
-  if (postInstallAction === "runApp" || postInstallAction === "dependencies") {
-    await installTSDependencies(packageJson, packageManager, isOnline);
-  }
-};

packages/create-llama/helpers/validate-pkg.ts

@@ -1,20 +0,0 @@
-// eslint-disable-next-line import/no-extraneous-dependencies
-import validateProjectName from "validate-npm-package-name";
-
-export function validateNpmName(name: string): {
-  valid: boolean;
-  problems?: string[];
-} {
-  const nameValidation = validateProjectName(name);
-  if (nameValidation.validForNewPackages) {
-    return { valid: true };
-  }
-
-  return {
-    valid: false,
-    problems: [
-      ...(nameValidation.errors || []),
-      ...(nameValidation.warnings || []),
-    ],
-  };
-}

packages/create-llama/index.ts

@@ -1,383 +0,0 @@
-#!/usr/bin/env node
-/* eslint-disable import/no-extraneous-dependencies */
-import { execSync } from "child_process";
-import Commander from "commander";
-import Conf from "conf";
-import fs from "fs";
-import path from "path";
-import { bold, cyan, green, red, yellow } from "picocolors";
-import prompts from "prompts";
-import terminalLink from "terminal-link";
-import checkForUpdate from "update-check";
-import { createApp } from "./create-app";
-import { getPkgManager } from "./helpers/get-pkg-manager";
-import { isFolderEmpty } from "./helpers/is-folder-empty";
-import { runApp } from "./helpers/run-app";
-import { getTools } from "./helpers/tools";
-import { validateNpmName } from "./helpers/validate-pkg";
-import packageJson from "./package.json";
-import { QuestionArgs, askQuestions, onPromptState } from "./questions";
-
-let projectPath: string = "";
-
-const handleSigTerm = () => process.exit(0);
-
-process.on("SIGINT", handleSigTerm);
-process.on("SIGTERM", handleSigTerm);
-
-const program = new Commander.Command(packageJson.name)
-  .version(packageJson.version)
-  .arguments("<project-directory>")
-  .usage(`${green("<project-directory>")} [options]`)
-  .action((name) => {
-    projectPath = name;
-  })
-  .option(
-    "--eslint",
-    `
-
-  Initialize with eslint config.
-`,
-  )
-  .option(
-    "--use-npm",
-    `
-
-  Explicitly tell the CLI to bootstrap the application using npm
-`,
-  )
-  .option(
-    "--use-pnpm",
-    `
-
-  Explicitly tell the CLI to bootstrap the application using pnpm
-`,
-  )
-  .option(
-    "--use-yarn",
-    `
-
-  Explicitly tell the CLI to bootstrap the application using Yarn
-`,
-  )
-  .option(
-    "--reset-preferences",
-    `
-
-  Explicitly tell the CLI to reset any stored preferences
-`,
-  )
-  .option(
-    "--template <template>",
-    `
-
-  Select a template to bootstrap the application with.
-`,
-  )
-  .option(
-    "--engine <engine>",
-    `
-
-  Select a chat engine to bootstrap the application with.
-`,
-  )
-  .option(
-    "--framework <framework>",
-    `
-
-  Select a framework to bootstrap the application with.
-`,
-  )
-  .option(
-    "--files <path>",
-    `
-  
-    Specify the path to a local file or folder for chatting.
-`,
-  )
-  .option(
-    "--open-ai-key <key>",
-    `
-
-  Provide an OpenAI API key.
-`,
-  )
-  .option(
-    "--ui <ui>",
-    `
-
-  Select a UI to bootstrap the application with.
-`,
-  )
-  .option(
-    "--frontend",
-    `
-
-  Whether to generate a frontend for your backend.
-`,
-  )
-  .option(
-    "--model <model>",
-    `
-
-  Select OpenAI model to use. E.g. gpt-3.5-turbo.
-`,
-  )
-  .option(
-    "--embedding-model <embeddingModel>",
-    `
-  Select OpenAI embedding model to use. E.g. text-embedding-ada-002.
-`,
-  )
-  .option(
-    "--port <port>",
-    `
-
-  Select UI port.
-`,
-  )
-  .option(
-    "--external-port <external>",
-    `
-
-  Select external port.
-`,
-  )
-  .option(
-    "--post-install-action <action>",
-    `
-
-  Choose an action after installation. For example, 'runApp' or 'dependencies'. The default option is just to generate the app.
-`,
-  )
-  .option(
-    "--vector-db <vectorDb>",
-    `
-
-  Select which vector database you would like to use, such as 'none', 'pg' or 'mongo'. The default option is not to use a vector database and use the local filesystem instead ('none').
-`,
-  )
-  .option(
-    "--tools <tools>",
-    `
-
-  Specify the tools you want to use by providing a comma-separated list. For example, 'wikipedia.WikipediaToolSpec,google.GoogleSearchToolSpec'. Use 'none' to not using any tools.
-`,
-  )
-  .option(
-    "--llama-parse",
-    `
-    Enable LlamaParse.
-`,
-  )
-  .option(
-    "--llama-cloud-key <key>",
-    `
-  Provide a LlamaCloud API key.
-`,
-  )
-  .allowUnknownOption()
-  .parse(process.argv);
-if (process.argv.includes("--no-frontend")) {
-  program.frontend = false;
-}
-if (process.argv.includes("--no-eslint")) {
-  program.eslint = false;
-}
-if (process.argv.includes("--tools")) {
-  if (program.tools === "none") {
-    program.tools = [];
-  } else {
-    program.tools = getTools(program.tools.split(","));
-  }
-}
-if (process.argv.includes("--no-llama-parse")) {
-  program.llamaParse = false;
-}
-
-const packageManager = !!program.useNpm
-  ? "npm"
-  : !!program.usePnpm
-    ? "pnpm"
-    : !!program.useYarn
-      ? "yarn"
-      : getPkgManager();
-
-async function run(): Promise<void> {
-  const conf = new Conf({ projectName: "create-llama" });
-
-  if (program.resetPreferences) {
-    conf.clear();
-    console.log(`Preferences reset successfully`);
-    return;
-  }
-
-  if (typeof projectPath === "string") {
-    projectPath = projectPath.trim();
-  }
-
-  if (!projectPath) {
-    const res = await prompts({
-      onState: onPromptState,
-      type: "text",
-      name: "path",
-      message: "What is your project named?",
-      initial: "my-app",
-      validate: (name) => {
-        const validation = validateNpmName(path.basename(path.resolve(name)));
-        if (validation.valid) {
-          return true;
-        }
-        return "Invalid project name: " + validation.problems![0];
-      },
-    });
-
-    if (typeof res.path === "string") {
-      projectPath = res.path.trim();
-    }
-  }
-
-  if (!projectPath) {
-    console.log(
-      "\nPlease specify the project directory:\n" +
-        `  ${cyan(program.name())} ${green("<project-directory>")}\n` +
-        "For example:\n" +
-        `  ${cyan(program.name())} ${green("my-app")}\n\n` +
-        `Run ${cyan(`${program.name()} --help`)} to see all options.`,
-    );
-    process.exit(1);
-  }
-
-  const resolvedProjectPath = path.resolve(projectPath);
-  const projectName = path.basename(resolvedProjectPath);
-
-  const { valid, problems } = validateNpmName(projectName);
-  if (!valid) {
-    console.error(
-      `Could not create a project called ${red(
-        `"${projectName}"`,
-      )} because of npm naming restrictions:`,
-    );
-
-    problems!.forEach((p) => console.error(`    ${red(bold("*"))} ${p}`));
-    process.exit(1);
-  }
-
-  /**
-   * Verify the project dir is empty or doesn't exist
-   */
-  const root = path.resolve(resolvedProjectPath);
-  const appName = path.basename(root);
-  const folderExists = fs.existsSync(root);
-
-  if (folderExists && !isFolderEmpty(root, appName)) {
-    process.exit(1);
-  }
-
-  const preferences = (conf.get("preferences") || {}) as QuestionArgs;
-  await askQuestions(program as unknown as QuestionArgs, preferences);
-
-  await createApp({
-    template: program.template,
-    framework: program.framework,
-    engine: program.engine,
-    ui: program.ui,
-    appPath: resolvedProjectPath,
-    packageManager,
-    eslint: program.eslint,
-    frontend: program.frontend,
-    openAiKey: program.openAiKey,
-    llamaCloudKey: program.llamaCloudKey,
-    model: program.model,
-    embeddingModel: program.embeddingModel,
-    communityProjectPath: program.communityProjectPath,
-    llamapack: program.llamapack,
-    vectorDb: program.vectorDb,
-    externalPort: program.externalPort,
-    postInstallAction: program.postInstallAction,
-    dataSource: program.dataSource,
-    tools: program.tools,
-  });
-  conf.set("preferences", preferences);
-
-  if (program.postInstallAction === "VSCode") {
-    console.log(`Starting VSCode in ${root}...`);
-    try {
-      execSync(`code . --new-window --goto README.md`, {
-        stdio: "inherit",
-        cwd: root,
-      });
-    } catch (error) {
-      console.log(
-        red(
-          `Failed to start VSCode in ${root}. 
-Got error: ${(error as Error).message}.\n`,
-        ),
-      );
-      console.log(
-        `Make sure you have VSCode installed and added to your PATH. 
-Please check ${cyan(
-          terminalLink(
-            "This documentation",
-            `https://code.visualstudio.com/docs/setup/setup-overview`,
-          ),
-        )} for more information.`,
-      );
-    }
-  } else if (program.postInstallAction === "runApp") {
-    console.log(`Running app in ${root}...`);
-    await runApp(
-      root,
-      program.frontend,
-      program.framework,
-      program.port,
-      program.externalPort,
-    );
-  }
-}
-
-const update = checkForUpdate(packageJson).catch(() => null);
-
-async function notifyUpdate(): Promise<void> {
-  try {
-    const res = await update;
-    if (res?.latest) {
-      const updateMessage =
-        packageManager === "yarn"
-          ? "yarn global add create-llama@latest"
-          : packageManager === "pnpm"
-            ? "pnpm add -g create-llama@latest"
-            : "npm i -g create-llama@latest";
-
-      console.log(
-        yellow(bold("A new version of `create-llama` is available!")) +
-          "\n" +
-          "You can update by running: " +
-          cyan(updateMessage) +
-          "\n",
-      );
-    }
-  } catch {
-    // ignore error
-  }
-}
-
-run()
-  .then(notifyUpdate)
-  .catch(async (reason) => {
-    console.log();
-    console.log("Aborting installation.");
-    if (reason.command) {
-      console.log(`  ${cyan(reason.command)} has failed.`);
-    } else {
-      console.log(
-        red("Unexpected error. Please report it as a bug:") + "\n",
-        reason,
-      );
-    }
-    console.log();
-
-    await notifyUpdate();
-
-    process.exit(1);
-  });

packages/create-llama/package.json

@@ -1,61 +0,0 @@
-{
-  "name": "create-llama",
-  "version": "0.0.28",
-  "keywords": [
-    "rag",
-    "llamaindex",
-    "next.js"
-  ],
-  "description": "Create LlamaIndex-powered apps with one command",
-  "repository": {
-    "type": "git",
-    "url": "https://github.com/run-llama/LlamaIndexTS",
-    "directory": "packages/create-llama"
-  },
-  "license": "MIT",
-  "bin": {
-    "create-llama": "./dist/index.js"
-  },
-  "files": [
-    "dist"
-  ],
-  "scripts": {
-    "clean": "rimraf --glob ./dist ./templates/**/__pycache__ ./templates/**/node_modules ./templates/**/poetry.lock",
-    "dev": "ncc build ./index.ts -w -o dist/",
-    "build": "npm run clean && ncc build ./index.ts -o ./dist/ --minify --no-cache --no-source-map-register",
-    "lint": "eslint . --ignore-pattern dist --ignore-pattern e2e/cache",
-    "e2e": "playwright test",
-    "prepublishOnly": "cd ../../ && pnpm run build:release"
-  },
-  "devDependencies": {
-    "@playwright/test": "^1.41.1",
-    "@types/async-retry": "1.4.2",
-    "@types/ci-info": "2.0.0",
-    "@types/cross-spawn": "6.0.0",
-    "@types/node": "^20.11.7",
-    "@types/prompts": "2.0.1",
-    "@types/tar": "6.1.5",
-    "@types/validate-npm-package-name": "3.0.0",
-    "@vercel/ncc": "0.38.1",
-    "async-retry": "1.3.1",
-    "async-sema": "3.0.1",
-    "ci-info": "github:watson/ci-info#f43f6a1cefff47fb361c88cf4b943fdbcaafe540",
-    "commander": "2.20.0",
-    "conf": "10.2.0",
-    "cross-spawn": "7.0.3",
-    "fast-glob": "3.3.1",
-    "got": "10.7.0",
-    "picocolors": "1.0.0",
-    "prompts": "2.1.0",
-    "rimraf": "^5.0.5",
-    "smol-toml": "^1.1.4",
-    "tar": "6.1.15",
-    "terminal-link": "^3.0.0",
-    "update-check": "1.5.4",
-    "validate-npm-package-name": "3.0.0",
-    "wait-port": "^1.1.0"
-  },
-  "engines": {
-    "node": ">=16.14.0"
-  }
-}

packages/create-llama/playwright.config.ts

@@ -1,21 +0,0 @@
-/* eslint-disable turbo/no-undeclared-env-vars */
-import { defineConfig, devices } from "@playwright/test";
-
-export default defineConfig({
-  testDir: "./e2e",
-  fullyParallel: true,
-  forbidOnly: !!process.env.CI,
-  retries: process.env.CI ? 2 : 0,
-  workers: process.env.CI ? 1 : undefined,
-  timeout: 1000 * 60 * 5,
-  reporter: "html",
-  use: {
-    trace: "on-first-retry",
-  },
-  projects: [
-    {
-      name: "chromium",
-      use: { ...devices["Desktop Chrome"] },
-    },
-  ],
-});

packages/create-llama/questions.ts

@@ -1,747 +0,0 @@
-import { execSync } from "child_process";
-import ciInfo from "ci-info";
-import fs from "fs";
-import path from "path";
-import { blue, green, red } from "picocolors";
-import prompts from "prompts";
-import { InstallAppArgs } from "./create-app";
-import {
-  FileSourceConfig,
-  TemplateDataSourceType,
-  TemplateFramework,
-} from "./helpers";
-import { COMMUNITY_OWNER, COMMUNITY_REPO } from "./helpers/constant";
-import { templatesDir } from "./helpers/dir";
-import { getAvailableLlamapackOptions } from "./helpers/llama-pack";
-import { getRepoRootFolders } from "./helpers/repo";
-import { supportedTools, toolsRequireConfig } from "./helpers/tools";
-
-export type QuestionArgs = Omit<
-  InstallAppArgs,
-  "appPath" | "packageManager"
-> & { files?: string; llamaParse?: boolean };
-const supportedContextFileTypes = [
-  ".pdf",
-  ".doc",
-  ".docx",
-  ".xls",
-  ".xlsx",
-  ".csv",
-];
-const MACOS_FILE_SELECTION_SCRIPT = `
-osascript -l JavaScript -e '
-  a = Application.currentApplication();
-  a.includeStandardAdditions = true;
-  a.chooseFile({ withPrompt: "Please select a file to process:" }).toString()
-'`;
-const MACOS_FOLDER_SELECTION_SCRIPT = `
-osascript -l JavaScript -e '
-  a = Application.currentApplication();
-  a.includeStandardAdditions = true;
-  a.chooseFolder({ withPrompt: "Please select a folder to process:" }).toString()
-'`;
-const WINDOWS_FILE_SELECTION_SCRIPT = `
-Add-Type -AssemblyName System.Windows.Forms
-$openFileDialog = New-Object System.Windows.Forms.OpenFileDialog
-$openFileDialog.InitialDirectory = [Environment]::GetFolderPath('Desktop')
-$result = $openFileDialog.ShowDialog()
-if ($result -eq 'OK') {
-  $openFileDialog.FileName
-}
-`;
-const WINDOWS_FOLDER_SELECTION_SCRIPT = `
-Add-Type -AssemblyName System.windows.forms
-$folderBrowser = New-Object System.Windows.Forms.FolderBrowserDialog
-$dialogResult = $folderBrowser.ShowDialog()
-if ($dialogResult -eq [System.Windows.Forms.DialogResult]::OK)
-{
-    $folderBrowser.SelectedPath
-}
-`;
-
-const defaults: QuestionArgs = {
-  template: "streaming",
-  framework: "nextjs",
-  engine: "simple",
-  ui: "html",
-  eslint: true,
-  frontend: false,
-  openAiKey: "",
-  llamaCloudKey: "",
-  model: "gpt-3.5-turbo",
-  embeddingModel: "text-embedding-ada-002",
-  communityProjectPath: "",
-  llamapack: "",
-  postInstallAction: "dependencies",
-  dataSource: {
-    type: "none",
-    config: {},
-  },
-  tools: [],
-};
-
-const handlers = {
-  onCancel: () => {
-    console.error("Exiting.");
-    process.exit(1);
-  },
-};
-
-const getVectorDbChoices = (framework: TemplateFramework) => {
-  const choices = [
-    {
-      title: "No, just store the data in the file system",
-      value: "none",
-    },
-    { title: "MongoDB", value: "mongo" },
-    { title: "PostgreSQL", value: "pg" },
-    { title: "Pinecone", value: "pinecone" },
-  ];
-
-  const vectordbLang = framework === "fastapi" ? "python" : "typescript";
-  const compPath = path.join(templatesDir, "components");
-  const vectordbPath = path.join(compPath, "vectordbs", vectordbLang);
-
-  const availableChoices = fs
-    .readdirSync(vectordbPath)
-    .filter((file) => fs.statSync(path.join(vectordbPath, file)).isDirectory());
-
-  const displayedChoices = choices.filter((choice) =>
-    availableChoices.includes(choice.value),
-  );
-
-  return displayedChoices;
-};
-
-const getDataSourceChoices = (framework: TemplateFramework) => {
-  const choices = [
-    {
-      title: "No data, just a simple chat",
-      value: "simple",
-    },
-    { title: "Use an example PDF", value: "exampleFile" },
-  ];
-  if (process.platform === "win32" || process.platform === "darwin") {
-    choices.push({
-      title: `Use a local file (${supportedContextFileTypes.join(", ")})`,
-      value: "localFile",
-    });
-    choices.push({
-      title: `Use a local folder`,
-      value: "localFolder",
-    });
-  }
-  if (framework === "fastapi") {
-    choices.push({
-      title: "Use website content (requires Chrome)",
-      value: "web",
-    });
-  }
-  return choices;
-};
-
-const selectLocalContextData = async (type: TemplateDataSourceType) => {
-  try {
-    let selectedPath: string = "";
-    let execScript: string;
-    let execOpts: any = {};
-    switch (process.platform) {
-      case "win32": // Windows
-        execScript =
-          type === "file"
-            ? WINDOWS_FILE_SELECTION_SCRIPT
-            : WINDOWS_FOLDER_SELECTION_SCRIPT;
-        execOpts = { shell: "powershell.exe" };
-        break;
-      case "darwin": // MacOS
-        execScript =
-          type === "file"
-            ? MACOS_FILE_SELECTION_SCRIPT
-            : MACOS_FOLDER_SELECTION_SCRIPT;
-        break;
-      default: // Unsupported OS
-        console.log(red("Unsupported OS error!"));
-        process.exit(1);
-    }
-    selectedPath = execSync(execScript, execOpts).toString().trim();
-    if (type === "file") {
-      const fileType = path.extname(selectedPath);
-      if (!supportedContextFileTypes.includes(fileType)) {
-        console.log(
-          red(
-            `Please select a supported file type: ${supportedContextFileTypes}`,
-          ),
-        );
-        process.exit(1);
-      }
-    }
-    return selectedPath;
-  } catch (error) {
-    console.log(
-      red(
-        "Got an error when trying to select local context data! Please try again or select another data source option.",
-      ),
-    );
-    process.exit(1);
-  }
-};
-
-export const onPromptState = (state: any) => {
-  if (state.aborted) {
-    // If we don't re-enable the terminal cursor before exiting
-    // the program, the cursor will remain hidden
-    process.stdout.write("\x1B[?25h");
-    process.stdout.write("\n");
-    process.exit(1);
-  }
-};
-
-export const askQuestions = async (
-  program: QuestionArgs,
-  preferences: QuestionArgs,
-) => {
-  const getPrefOrDefault = <K extends keyof QuestionArgs>(
-    field: K,
-  ): QuestionArgs[K] => preferences[field] ?? defaults[field];
-
-  // Ask for next action after installation
-  async function askPostInstallAction() {
-    if (program.postInstallAction === undefined) {
-      if (ciInfo.isCI) {
-        program.postInstallAction = getPrefOrDefault("postInstallAction");
-      } else {
-        const actionChoices = [
-          {
-            title: "Just generate code (~1 sec)",
-            value: "none",
-          },
-          {
-            title: "Start in VSCode (~1 sec)",
-            value: "VSCode",
-          },
-          {
-            title: "Generate code and install dependencies (~2 min)",
-            value: "dependencies",
-          },
-        ];
-
-        const openAiKeyConfigured =
-          program.openAiKey || process.env["OPENAI_API_KEY"];
-        // If using LlamaParse, require LlamaCloud API key
-        const llamaCloudKeyConfigured = (
-          program.dataSource?.config as FileSourceConfig
-        )?.useLlamaParse
-          ? program.llamaCloudKey || process.env["LLAMA_CLOUD_API_KEY"]
-          : true;
-        const hasVectorDb = program.vectorDb && program.vectorDb !== "none";
-        // Can run the app if all tools do not require configuration
-        if (
-          !hasVectorDb &&
-          openAiKeyConfigured &&
-          llamaCloudKeyConfigured &&
-          !toolsRequireConfig(program.tools) &&
-          !program.llamapack
-        ) {
-          actionChoices.push({
-            title:
-              "Generate code, install dependencies, and run the app (~2 min)",
-            value: "runApp",
-          });
-        }
-
-        const { action } = await prompts(
-          {
-            type: "select",
-            name: "action",
-            message: "How would you like to proceed?",
-            choices: actionChoices,
-            initial: 1,
-          },
-          handlers,
-        );
-
-        program.postInstallAction = action;
-      }
-    }
-  }
-
-  if (!program.template) {
-    if (ciInfo.isCI) {
-      program.template = getPrefOrDefault("template");
-    } else {
-      const styledRepo = blue(
-        `https://github.com/${COMMUNITY_OWNER}/${COMMUNITY_REPO}`,
-      );
-      const { template } = await prompts(
-        {
-          type: "select",
-          name: "template",
-          message: "Which template would you like to use?",
-          choices: [
-            { title: "Chat without streaming", value: "simple" },
-            { title: "Chat with streaming", value: "streaming" },
-            {
-              title: `Community template from ${styledRepo}`,
-              value: "community",
-            },
-            {
-              title: "Example using a LlamaPack",
-              value: "llamapack",
-            },
-          ],
-          initial: 1,
-        },
-        handlers,
-      );
-      program.template = template;
-      preferences.template = template;
-    }
-  }
-
-  if (program.template === "community") {
-    const rootFolderNames = await getRepoRootFolders(
-      COMMUNITY_OWNER,
-      COMMUNITY_REPO,
-    );
-    const { communityProjectPath } = await prompts(
-      {
-        type: "select",
-        name: "communityProjectPath",
-        message: "Select community template",
-        choices: rootFolderNames.map((name) => ({
-          title: name,
-          value: name,
-        })),
-        initial: 0,
-      },
-      handlers,
-    );
-    program.communityProjectPath = communityProjectPath;
-    preferences.communityProjectPath = communityProjectPath;
-    return; // early return - no further questions needed for community projects
-  }
-
-  if (program.template === "llamapack") {
-    const availableLlamaPacks = await getAvailableLlamapackOptions();
-    const { llamapack } = await prompts(
-      {
-        type: "select",
-        name: "llamapack",
-        message: "Select LlamaPack",
-        choices: availableLlamaPacks.map((pack) => ({
-          title: pack.name,
-          value: pack.folderPath,
-        })),
-        initial: 0,
-      },
-      handlers,
-    );
-    program.llamapack = llamapack;
-    preferences.llamapack = llamapack;
-    await askPostInstallAction();
-    return; // early return - no further questions needed for llamapack projects
-  }
-
-  if (!program.framework) {
-    if (ciInfo.isCI) {
-      program.framework = getPrefOrDefault("framework");
-    } else {
-      const choices = [
-        { title: "Express", value: "express" },
-        { title: "FastAPI (Python)", value: "fastapi" },
-      ];
-      if (program.template === "streaming") {
-        // allow NextJS only for streaming template
-        choices.unshift({ title: "NextJS", value: "nextjs" });
-      }
-
-      const { framework } = await prompts(
-        {
-          type: "select",
-          name: "framework",
-          message: "Which framework would you like to use?",
-          choices,
-          initial: 0,
-        },
-        handlers,
-      );
-      program.framework = framework;
-      preferences.framework = framework;
-    }
-  }
-
-  if (
-    program.template === "streaming" &&
-    (program.framework === "express" || program.framework === "fastapi")
-  ) {
-    // if a backend-only framework is selected, ask whether we should create a frontend
-    // (only for streaming backends)
-    if (program.frontend === undefined) {
-      if (ciInfo.isCI) {
-        program.frontend = getPrefOrDefault("frontend");
-      } else {
-        const styledNextJS = blue("NextJS");
-        const styledBackend = green(
-          program.framework === "express"
-            ? "Express "
-            : program.framework === "fastapi"
-              ? "FastAPI (Python) "
-              : "",
-        );
-        const { frontend } = await prompts({
-          onState: onPromptState,
-          type: "toggle",
-          name: "frontend",
-          message: `Would you like to generate a ${styledNextJS} frontend for your ${styledBackend}backend?`,
-          initial: getPrefOrDefault("frontend"),
-          active: "Yes",
-          inactive: "No",
-        });
-        program.frontend = Boolean(frontend);
-        preferences.frontend = Boolean(frontend);
-      }
-    }
-  } else {
-    program.frontend = false;
-  }
-
-  if (program.framework === "nextjs" || program.frontend) {
-    if (!program.ui) {
-      if (ciInfo.isCI) {
-        program.ui = getPrefOrDefault("ui");
-      } else {
-        const { ui } = await prompts(
-          {
-            type: "select",
-            name: "ui",
-            message: "Which UI would you like to use?",
-            choices: [
-              { title: "Just HTML", value: "html" },
-              { title: "Shadcn", value: "shadcn" },
-            ],
-            initial: 0,
-          },
-          handlers,
-        );
-        program.ui = ui;
-        preferences.ui = ui;
-      }
-    }
-  }
-
-  if (!program.model) {
-    if (ciInfo.isCI) {
-      program.model = getPrefOrDefault("model");
-    } else {
-      const { model } = await prompts(
-        {
-          type: "select",
-          name: "model",
-          message: "Which model would you like to use?",
-          choices: [
-            { title: "gpt-3.5-turbo", value: "gpt-3.5-turbo-0125" },
-            { title: "gpt-4-turbo-preview", value: "gpt-4-turbo-preview" },
-            { title: "gpt-4", value: "gpt-4" },
-            {
-              title: "gpt-4-vision-preview",
-              value: "gpt-4-vision-preview",
-            },
-          ],
-          initial: 0,
-        },
-        handlers,
-      );
-      program.model = model;
-      preferences.model = model;
-    }
-  }
-
-  if (!program.embeddingModel && program.framework === "fastapi") {
-    if (ciInfo.isCI) {
-      program.embeddingModel = getPrefOrDefault("embeddingModel");
-    } else {
-      const { embeddingModel } = await prompts(
-        {
-          type: "select",
-          name: "embeddingModel",
-          message: "Which embedding model would you like to use?",
-          choices: [
-            {
-              title: "text-embedding-ada-002",
-              value: "text-embedding-ada-002",
-            },
-            {
-              title: "text-embedding-3-small",
-              value: "text-embedding-3-small",
-            },
-            {
-              title: "text-embedding-3-large",
-              value: "text-embedding-3-large",
-            },
-          ],
-          initial: 0,
-        },
-        handlers,
-      );
-      program.embeddingModel = embeddingModel;
-      preferences.embeddingModel = embeddingModel;
-    }
-  }
-
-  if (program.files) {
-    // If user specified files option, then the program should use context engine
-    program.engine == "context";
-    if (!fs.existsSync(program.files)) {
-      console.log("File or folder not found");
-      process.exit(1);
-    } else {
-      program.dataSource = {
-        type: fs.lstatSync(program.files).isDirectory() ? "folder" : "file",
-        config: {
-          path: program.files,
-        },
-      };
-    }
-  }
-
-  if (!program.engine) {
-    if (ciInfo.isCI) {
-      program.engine = getPrefOrDefault("engine");
-    } else {
-      const { dataSource } = await prompts(
-        {
-          type: "select",
-          name: "dataSource",
-          message: "Which data source would you like to use?",
-          choices: getDataSourceChoices(program.framework),
-          initial: 1,
-        },
-        handlers,
-      );
-      // Initialize with default config
-      program.dataSource = getPrefOrDefault("dataSource");
-      if (program.dataSource) {
-        switch (dataSource) {
-          case "simple":
-            program.engine = "simple";
-            program.dataSource = { type: "none", config: {} };
-            break;
-          case "exampleFile":
-            program.engine = "context";
-            // Treat example as a folder data source with no config
-            program.dataSource = { type: "folder", config: {} };
-            break;
-          case "localFile":
-            program.engine = "context";
-            program.dataSource = {
-              type: "file",
-              config: {
-                path: await selectLocalContextData("file"),
-              },
-            };
-            break;
-          case "localFolder":
-            program.engine = "context";
-            program.dataSource = {
-              type: "folder",
-              config: {
-                path: await selectLocalContextData("folder"),
-              },
-            };
-            break;
-          case "web":
-            program.engine = "context";
-            program.dataSource.type = "web";
-            break;
-        }
-      }
-    }
-  } else if (!program.dataSource) {
-    // Handle a case when engine is specified but dataSource is not
-    if (program.engine === "context") {
-      program.dataSource = {
-        type: "folder",
-        config: {},
-      };
-    } else if (program.engine === "simple") {
-      program.dataSource = {
-        type: "none",
-        config: {},
-      };
-    }
-  }
-
-  if (
-    (program.dataSource?.type === "file" ||
-      program.dataSource?.type === "folder") &&
-    program.framework === "fastapi"
-  ) {
-    if (ciInfo.isCI) {
-      program.llamaCloudKey = getPrefOrDefault("llamaCloudKey");
-    } else {
-      const dataSourceConfig = program.dataSource.config as FileSourceConfig;
-      dataSourceConfig.useLlamaParse = program.llamaParse;
-
-      // Is pdf file selected as data source or is it a folder data source
-      const askingLlamaParse =
-        dataSourceConfig.useLlamaParse === undefined &&
-        (program.dataSource.type === "folder"
-          ? true
-          : dataSourceConfig.path &&
-            path.extname(dataSourceConfig.path) === ".pdf");
-
-      // Ask if user wants to use LlamaParse
-      if (askingLlamaParse) {
-        const { useLlamaParse } = await prompts(
-          {
-            type: "toggle",
-            name: "useLlamaParse",
-            message:
-              "Would you like to use LlamaParse (improved parser for RAG - requires API key)?",
-            initial: true,
-            active: "yes",
-            inactive: "no",
-          },
-          handlers,
-        );
-        dataSourceConfig.useLlamaParse = useLlamaParse;
-        program.dataSource.config = dataSourceConfig;
-      }
-
-      // Ask for LlamaCloud API key
-      if (
-        dataSourceConfig.useLlamaParse &&
-        program.llamaCloudKey === undefined
-      ) {
-        const { llamaCloudKey } = await prompts(
-          {
-            type: "text",
-            name: "llamaCloudKey",
-            message:
-              "Please provide your LlamaIndex Cloud API key (leave blank to skip):",
-          },
-          handlers,
-        );
-        program.llamaCloudKey = llamaCloudKey;
-      }
-    }
-  }
-
-  if (program.dataSource?.type === "web" && program.framework === "fastapi") {
-    let { baseUrl } = await prompts(
-      {
-        type: "text",
-        name: "baseUrl",
-        message: "Please provide base URL of the website:",
-        initial: "https://www.llamaindex.ai",
-      },
-      handlers,
-    );
-    try {
-      if (!baseUrl.includes("://")) {
-        baseUrl = `https://${baseUrl}`;
-      }
-      const checkUrl = new URL(baseUrl);
-      if (checkUrl.protocol !== "https:" && checkUrl.protocol !== "http:") {
-        throw new Error("Invalid protocol");
-      }
-    } catch (error) {
-      console.log(
-        red(
-          "Invalid URL provided! Please provide a valid URL (e.g. https://www.llamaindex.ai)",
-        ),
-      );
-      process.exit(1);
-    }
-    program.dataSource.config = {
-      baseUrl: baseUrl,
-      depth: 1,
-    };
-  }
-
-  if (program.engine !== "simple" && !program.vectorDb) {
-    if (ciInfo.isCI) {
-      program.vectorDb = getPrefOrDefault("vectorDb");
-    } else {
-      const { vectorDb } = await prompts(
-        {
-          type: "select",
-          name: "vectorDb",
-          message: "Would you like to use a vector database?",
-          choices: getVectorDbChoices(program.framework),
-          initial: 0,
-        },
-        handlers,
-      );
-      program.vectorDb = vectorDb;
-      preferences.vectorDb = vectorDb;
-    }
-  }
-
-  if (
-    !program.tools &&
-    program.framework === "fastapi" &&
-    program.engine === "context"
-  ) {
-    if (ciInfo.isCI) {
-      program.tools = getPrefOrDefault("tools");
-    } else {
-      const toolChoices = supportedTools.map((tool) => ({
-        title: tool.display,
-        value: tool.name,
-      }));
-      const { toolsName } = await prompts({
-        type: "multiselect",
-        name: "toolsName",
-        message:
-          "Would you like to build an agent using tools? If so, select the tools here, otherwise just press enter",
-        choices: toolChoices,
-      });
-      const tools = toolsName?.map((tool: string) =>
-        supportedTools.find((t) => t.name === tool),
-      );
-      program.tools = tools;
-      preferences.tools = tools;
-    }
-  }
-
-  if (!program.openAiKey) {
-    const { key } = await prompts(
-      {
-        type: "text",
-        name: "key",
-        message: "Please provide your OpenAI API key (leave blank to skip):",
-      },
-      handlers,
-    );
-    program.openAiKey = key;
-    preferences.openAiKey = key;
-  }
-
-  if (program.framework !== "fastapi" && program.eslint === undefined) {
-    if (ciInfo.isCI) {
-      program.eslint = getPrefOrDefault("eslint");
-    } else {
-      const styledEslint = blue("ESLint");
-      const { eslint } = await prompts({
-        onState: onPromptState,
-        type: "toggle",
-        name: "eslint",
-        message: `Would you like to use ${styledEslint}?`,
-        initial: getPrefOrDefault("eslint"),
-        active: "Yes",
-        inactive: "No",
-      });
-      program.eslint = Boolean(eslint);
-      preferences.eslint = Boolean(eslint);
-    }
-  }
-
-  await askPostInstallAction();
-
-  // TODO: consider using zod to validate the input (doesn't work like this as not every option is required)
-  // templateUISchema.parse(program.ui);
-  // templateEngineSchema.parse(program.engine);
-  // templateFrameworkSchema.parse(program.framework);
-  // templateTypeSchema.parse(program.template);``
-};

packages/create-llama/templates/.gitignore

@@ -1,3 +0,0 @@
-__pycache__
-poetry.lock
-storage

packages/create-llama/templates/README-fullstack.md

@@ -1,18 +0,0 @@
-This is a [LlamaIndex](https://www.llamaindex.ai/) project bootstrapped with [`create-llama`](https://github.com/run-llama/LlamaIndexTS/tree/main/packages/create-llama).
-
-## Getting Started
-
-First, startup the backend as described in the [backend README](./backend/README.md).
-
-Second, run the development server of the frontend as described in the [frontend README](./frontend/README.md).
-
-Open [http://localhost:3000](http://localhost:3000) with your browser to see the result.
-
-## Learn More
-
-To learn more about LlamaIndex, take a look at the following resources:
-
-- [LlamaIndex Documentation](https://docs.llamaindex.ai) - learn about LlamaIndex (Python features).
-- [LlamaIndexTS Documentation](https://ts.llamaindex.ai) - learn about LlamaIndex (Typescript features).
-
-You can check out [the LlamaIndexTS GitHub repository](https://github.com/run-llama/LlamaIndexTS) - your feedback and contributions are welcome!

packages/create-llama/templates/components/engines/python/agent/__init__.py

@@ -1,28 +0,0 @@
-import os
-from llama_index.core.settings import Settings
-from llama_index.core.agent import AgentRunner
-from llama_index.core.tools.query_engine import QueryEngineTool
-from app.engine.tools import ToolFactory
-from app.engine.index import get_index
-
-
-def get_chat_engine():
-    system_prompt = os.getenv("SYSTEM_PROMPT")
-    top_k = os.getenv("TOP_K", "3")
-    tools = []
-
-    # Add query tool
-    index = get_index()
-    query_engine = index.as_query_engine(similarity_top_k=int(top_k))
-    query_engine_tool = QueryEngineTool.from_defaults(query_engine=query_engine)
-    tools.append(query_engine_tool)
-
-    # Add additional tools
-    tools += ToolFactory.from_env()
-
-    return AgentRunner.from_llm(
-        llm=Settings.llm,
-        tools=tools,
-        system_prompt=system_prompt,
-        verbose=True,
-    )

packages/create-llama/templates/components/engines/python/agent/tools.py

@@ -1,33 +0,0 @@
-import json
-import importlib
-
-from llama_index.core.tools.tool_spec.base import BaseToolSpec
-from llama_index.core.tools.function_tool import FunctionTool
-
-
-class ToolFactory:
-
-    @staticmethod
-    def create_tool(tool_name: str, **kwargs) -> list[FunctionTool]:
-        try:
-            tool_package, tool_cls_name = tool_name.split(".")
-            module_name = f"llama_index.tools.{tool_package}"
-            module = importlib.import_module(module_name)
-            tool_class = getattr(module, tool_cls_name)
-            tool_spec: BaseToolSpec = tool_class(**kwargs)
-            return tool_spec.to_tool_list()
-        except (ImportError, AttributeError) as e:
-            raise ValueError(f"Unsupported tool: {tool_name}") from e
-        except TypeError as e:
-            raise ValueError(
-                f"Could not create tool: {tool_name}. With config: {kwargs}"
-            ) from e
-
-    @staticmethod
-    def from_env() -> list[FunctionTool]:
-        tools = []
-        with open("tools_config.json", "r") as f:
-            tool_configs = json.load(f)
-            for name, config in tool_configs.items():
-                tools += ToolFactory.create_tool(name, **config)
-        return tools

packages/create-llama/templates/components/engines/python/chat/__init__.py

@@ -1,13 +0,0 @@
-import os
-from app.engine.index import get_index
-
-
-def get_chat_engine():
-    system_prompt = os.getenv("SYSTEM_PROMPT")
-    top_k = os.getenv("TOP_K", 3)
-
-    return get_index().as_chat_engine(
-        similarity_top_k=int(top_k),
-        system_prompt=system_prompt,
-        chat_mode="condense_plus_context",
-    )

packages/create-llama/templates/components/loaders/python/file/loader.py

@@ -1,7 +0,0 @@
-from llama_index.core.readers import SimpleDirectoryReader
-
-DATA_DIR = "data"  # directory containing the documents
-
-
-def get_documents():
-    return SimpleDirectoryReader(DATA_DIR).load_data()

packages/create-llama/templates/components/loaders/python/llama_parse/loader.py

@@ -1,17 +0,0 @@
-import os
-from llama_parse import LlamaParse
-from llama_index.core import SimpleDirectoryReader
-
-DATA_DIR = "data"  # directory containing the documents
-
-
-def get_documents():
-    if os.getenv("LLAMA_CLOUD_API_KEY") is None:
-        raise ValueError(
-            "LLAMA_CLOUD_API_KEY environment variable is not set. "
-            "Please set it in .env file or in your shell environment then run again!"
-        )
-    parser = LlamaParse(result_type="markdown", verbose=True, language="en")
-
-    reader = SimpleDirectoryReader(DATA_DIR, file_extractor={".pdf": parser})
-    return reader.load_data()

packages/create-llama/templates/components/loaders/python/web/loader.py

@@ -1,13 +0,0 @@
-import os
-from llama_index.readers.web import WholeSiteReader
-
-
-def get_documents():
-    # Initialize the scraper with a prefix URL and maximum depth
-    scraper = WholeSiteReader(
-        prefix=os.environ.get("URL_PREFIX"), max_depth=int(os.environ.get("MAX_DEPTH"))
-    )
-    # Start scraping from a base URL
-    documents = scraper.load_data(base_url=os.environ.get("BASE_URL"))
-
-    return documents

packages/create-llama/templates/components/sample-projects/llamapack/README-template.md

@@ -1,16 +0,0 @@
----
-
-## Quickstart
-
-1. Check above instructions for setting up your environment and export required environment variables
-   For example, if you are using bash, you can run the following command to set up OpenAI API key
-
-```bash
-export OPENAI_API_KEY=your_api_key
-```
-
-2. Run the example
-
-```
-poetry run python example.py
-```

packages/create-llama/templates/components/sample-projects/llamapack/pyproject.toml

@@ -1,17 +0,0 @@
-[tool.poetry]
-name = "app"
-version = "0.1.0"
-description = "Llama Pack Example"
-authors = ["Marcus Schiesser <mail@marcusschiesser.de>"]
-readme = "README.md"
-
-[tool.poetry.dependencies]
-python = "^3.11,<3.12"
-llama-index = "^0.10.6"
-llama-index-readers-file = "^0.1.3"
-python-dotenv = "^1.0.0"
-
-
-[build-system]
-requires = ["poetry-core"]
-build-backend = "poetry.core.masonry.api"

packages/create-llama/templates/components/ui/html/chat/chat-avatar.tsx

@@ -1,34 +0,0 @@
-"use client";
-
-import Image from "next/image";
-import { Message } from "./chat-messages";
-
-export default function ChatAvatar(message: Message) {
-  if (message.role === "user") {
-    return (
-      <div className="flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow bg-background">
-        <svg
-          xmlns="http://www.w3.org/2000/svg"
-          viewBox="0 0 256 256"
-          fill="currentColor"
-          className="h-4 w-4"
-        >
-          <path d="M230.92 212c-15.23-26.33-38.7-45.21-66.09-54.16a72 72 0 1 0-73.66 0c-27.39 8.94-50.86 27.82-66.09 54.16a8 8 0 1 0 13.85 8c18.84-32.56 52.14-52 89.07-52s70.23 19.44 89.07 52a8 8 0 1 0 13.85-8ZM72 96a56 56 0 1 1 56 56 56.06 56.06 0 0 1-56-56Z"></path>
-        </svg>
-      </div>
-    );
-  }
-
-  return (
-    <div className="flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border  bg-black text-white">
-      <Image
-        className="rounded-md"
-        src="/llama.png"
-        alt="Llama Logo"
-        width={24}
-        height={24}
-        priority
-      />
-    </div>
-  );
-}

packages/create-llama/templates/components/ui/html/chat/chat-input.tsx

@@ -1,43 +0,0 @@
-"use client";
-
-export interface ChatInputProps {
-  /** The current value of the input */
-  input?: string;
-  /** An input/textarea-ready onChange handler to control the value of the input */
-  handleInputChange?: (
-    e:
-      | React.ChangeEvent<HTMLInputElement>
-      | React.ChangeEvent<HTMLTextAreaElement>,
-  ) => void;
-  /** Form submission handler to automatically reset input and append a user message  */
-  handleSubmit: (e: React.FormEvent<HTMLFormElement>) => void;
-  isLoading: boolean;
-  multiModal?: boolean;
-}
-
-export default function ChatInput(props: ChatInputProps) {
-  return (
-    <>
-      <form
-        onSubmit={props.handleSubmit}
-        className="flex items-start justify-between w-full max-w-5xl p-4 bg-white rounded-xl shadow-xl gap-4"
-      >
-        <input
-          autoFocus
-          name="message"
-          placeholder="Type a message"
-          className="w-full p-4 rounded-xl shadow-inner flex-1"
-          value={props.input}
-          onChange={props.handleInputChange}
-        />
-        <button
-          disabled={props.isLoading}
-          type="submit"
-          className="p-4 text-white rounded-xl shadow-xl bg-gradient-to-r from-cyan-500 to-sky-500 disabled:opacity-50 disabled:cursor-not-allowed"
-        >
-          Send message
-        </button>
-      </form>
-    </>
-  );
-}

packages/create-llama/templates/components/ui/html/chat/chat-item.tsx

@@ -1,13 +0,0 @@
-"use client";
-
-import ChatAvatar from "./chat-avatar";
-import { Message } from "./chat-messages";
-
-export default function ChatItem(message: Message) {
-  return (
-    <div className="flex items-start gap-4 pt-5">
-      <ChatAvatar {...message} />
-      <p className="break-words">{message.content}</p>
-    </div>
-  );
-}

packages/create-llama/templates/components/ui/html/chat/chat-messages.tsx

@@ -1,48 +0,0 @@
-"use client";
-
-import { useEffect, useRef } from "react";
-import ChatItem from "./chat-item";
-
-export interface Message {
-  id: string;
-  content: string;
-  role: string;
-}
-
-export default function ChatMessages({
-  messages,
-  isLoading,
-  reload,
-  stop,
-}: {
-  messages: Message[];
-  isLoading?: boolean;
-  stop?: () => void;
-  reload?: () => void;
-}) {
-  const scrollableChatContainerRef = useRef<HTMLDivElement>(null);
-
-  const scrollToBottom = () => {
-    if (scrollableChatContainerRef.current) {
-      scrollableChatContainerRef.current.scrollTop =
-        scrollableChatContainerRef.current.scrollHeight;
-    }
-  };
-
-  useEffect(() => {
-    scrollToBottom();
-  }, [messages.length]);
-
-  return (
-    <div className="w-full max-w-5xl p-4 bg-white rounded-xl shadow-xl">
-      <div
-        className="flex flex-col gap-5 divide-y h-[50vh] overflow-auto"
-        ref={scrollableChatContainerRef}
-      >
-        {messages.map((m: Message) => (
-          <ChatItem key={m.id} {...m} />
-        ))}
-      </div>
-    </div>
-  );
-}

packages/create-llama/templates/components/ui/html/chat/index.ts

@@ -1,6 +0,0 @@
-import ChatInput from "./chat-input";
-import ChatMessages from "./chat-messages";
-
-export type { ChatInputProps } from "./chat-input";
-export type { Message } from "./chat-messages";
-export { ChatInput, ChatMessages };

packages/create-llama/templates/components/vectordbs/python/mongo/generate.py

@@ -1,43 +0,0 @@
-from dotenv import load_dotenv
-
-load_dotenv()
-
-import os
-import logging
-from llama_index.core.storage import StorageContext
-from llama_index.core.indices import VectorStoreIndex
-from llama_index.vector_stores.mongodb import MongoDBAtlasVectorSearch
-from app.settings import init_settings
-from app.engine.loader import get_documents
-
-logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger()
-
-
-def generate_datasource():
-    logger.info("Creating new index")
-    # load the documents and create the index
-    documents = get_documents()
-    store = MongoDBAtlasVectorSearch(
-        db_name=os.environ["MONGODB_DATABASE"],
-        collection_name=os.environ["MONGODB_VECTORS"],
-        index_name=os.environ["MONGODB_VECTOR_INDEX"],
-    )
-    storage_context = StorageContext.from_defaults(vector_store=store)
-    VectorStoreIndex.from_documents(
-        documents,
-        storage_context=storage_context,
-        show_progress=True,  # this will show you a progress bar as the embeddings are created
-    )
-    logger.info(
-        f"Successfully created embeddings in the MongoDB collection {os.environ['MONGODB_VECTORS']}"
-    )
-    logger.info(
-        """IMPORTANT: You can't query your index yet because you need to create a vector search index in MongoDB's UI now.
-See https://github.com/run-llama/mongodb-demo/tree/main?tab=readme-ov-file#create-a-vector-search-index"""
-    )
-
-
-if __name__ == "__main__":
-    init_settings()
-    generate_datasource()

packages/create-llama/templates/components/vectordbs/python/mongo/index.py

@@ -1,20 +0,0 @@
-import logging
-import os
-
-from llama_index.core.indices import VectorStoreIndex
-from llama_index.vector_stores.mongodb import MongoDBAtlasVectorSearch
-
-
-logger = logging.getLogger("uvicorn")
-
-
-def get_index():
-    logger.info("Connecting to index from MongoDB...")
-    store = MongoDBAtlasVectorSearch(
-        db_name=os.environ["MONGODB_DATABASE"],
-        collection_name=os.environ["MONGODB_VECTORS"],
-        index_name=os.environ["MONGODB_VECTOR_INDEX"],
-    )
-    index = VectorStoreIndex.from_vector_store(store)
-    logger.info("Finished connecting to index from MongoDB.")
-    return index

packages/create-llama/templates/components/vectordbs/python/none/constants.py

@@ -1 +0,0 @@
-STORAGE_DIR = "storage"  # directory to cache the generated index

packages/create-llama/templates/components/vectordbs/python/none/generate.py

@@ -1,32 +0,0 @@
-from dotenv import load_dotenv
-
-load_dotenv()
-
-import logging
-from llama_index.core.indices import (
-    VectorStoreIndex,
-)
-from app.engine.constants import STORAGE_DIR
-from app.engine.loader import get_documents
-from app.settings import init_settings
-
-
-logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger()
-
-
-def generate_datasource():
-    logger.info("Creating new index")
-    # load the documents and create the index
-    documents = get_documents()
-    index = VectorStoreIndex.from_documents(
-        documents,
-    )
-    # store it for later
-    index.storage_context.persist(STORAGE_DIR)
-    logger.info(f"Finished creating new index. Stored in {STORAGE_DIR}")
-
-
-if __name__ == "__main__":
-    init_settings()
-    generate_datasource()

packages/create-llama/templates/components/vectordbs/python/none/index.py

@@ -1,23 +0,0 @@
-import logging
-import os
-
-from app.engine.constants import STORAGE_DIR
-from llama_index.core.storage import StorageContext
-from llama_index.core.indices import load_index_from_storage
-
-logger = logging.getLogger("uvicorn")
-
-
-def get_index():
-    # check if storage already exists
-    if not os.path.exists(STORAGE_DIR):
-        raise Exception(
-            "StorageContext is empty - call 'python app/engine/generate.py' to generate the storage first"
-        )
-
-    # load the existing index
-    logger.info(f"Loading index from {STORAGE_DIR}...")
-    storage_context = StorageContext.from_defaults(persist_dir=STORAGE_DIR)
-    index = load_index_from_storage(storage_context)
-    logger.info(f"Finished loading index from {STORAGE_DIR}")
-    return index

packages/create-llama/templates/components/vectordbs/python/pg/constants.py

@@ -1,2 +0,0 @@
-PGVECTOR_SCHEMA = "public"
-PGVECTOR_TABLE = "llamaindex_embedding"

packages/create-llama/templates/components/vectordbs/python/pg/generate.py

@@ -1,35 +0,0 @@
-from dotenv import load_dotenv
-
-load_dotenv()
-
-import logging
-from llama_index.core.indices import VectorStoreIndex
-from llama_index.core.storage import StorageContext
-
-from app.engine.loader import get_documents
-from app.settings import init_settings
-from app.engine.utils import init_pg_vector_store_from_env
-
-logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger()
-
-
-def generate_datasource():
-    logger.info("Creating new index")
-    # load the documents and create the index
-    documents = get_documents()
-    store = init_pg_vector_store_from_env()
-    storage_context = StorageContext.from_defaults(vector_store=store)
-    VectorStoreIndex.from_documents(
-        documents,
-        storage_context=storage_context,
-        show_progress=True,  # this will show you a progress bar as the embeddings are created
-    )
-    logger.info(
-        f"Successfully created embeddings in the PG vector store, schema={store.schema_name} table={store.table_name}"
-    )
-
-
-if __name__ == "__main__":
-    init_settings()
-    generate_datasource()

packages/create-llama/templates/components/vectordbs/python/pg/index.py

@@ -1,13 +0,0 @@
-import logging
-from llama_index.core.indices.vector_store import VectorStoreIndex
-from app.engine.utils import init_pg_vector_store_from_env
-
-logger = logging.getLogger("uvicorn")
-
-
-def get_index():
-    logger.info("Connecting to index from PGVector...")
-    store = init_pg_vector_store_from_env()
-    index = VectorStoreIndex.from_vector_store(store)
-    logger.info("Finished connecting to index from PGVector.")
-    return index

packages/create-llama/templates/components/vectordbs/python/pg/utils.py

@@ -1,27 +0,0 @@
-import os
-from llama_index.vector_stores.postgres import PGVectorStore
-from urllib.parse import urlparse
-from app.engine.constants import PGVECTOR_SCHEMA, PGVECTOR_TABLE
-
-
-def init_pg_vector_store_from_env():
-    original_conn_string = os.environ.get("PG_CONNECTION_STRING")
-    if original_conn_string is None or original_conn_string == "":
-        raise ValueError("PG_CONNECTION_STRING environment variable is not set.")
-
-    # The PGVectorStore requires both two connection strings, one for psycopg2 and one for asyncpg
-    # Update the configured scheme with the psycopg2 and asyncpg schemes
-    original_scheme = urlparse(original_conn_string).scheme + "://"
-    conn_string = original_conn_string.replace(
-        original_scheme, "postgresql+psycopg2://"
-    )
-    async_conn_string = original_conn_string.replace(
-        original_scheme, "postgresql+asyncpg://"
-    )
-
-    return PGVectorStore(
-        connection_string=conn_string,
-        async_connection_string=async_conn_string,
-        schema_name=PGVECTOR_SCHEMA,
-        table_name=PGVECTOR_TABLE,
-    )

packages/create-llama/templates/components/vectordbs/python/pinecone/generate.py

@@ -1,39 +0,0 @@
-from dotenv import load_dotenv
-
-load_dotenv()
-
-import os
-import logging
-from llama_index.core.storage import StorageContext
-from llama_index.core.indices import VectorStoreIndex
-from llama_index.vector_stores.pinecone import PineconeVectorStore
-from app.settings import init_settings
-from app.engine.loader import get_documents
-
-logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger()
-
-
-def generate_datasource():
-    logger.info("Creating new index")
-    # load the documents and create the index
-    documents = get_documents()
-    store = PineconeVectorStore(
-        api_key=os.environ["PINECONE_API_KEY"],
-        index_name=os.environ["PINECONE_INDEX_NAME"],
-        environment=os.environ["PINECONE_ENVIRONMENT"],
-    )
-    storage_context = StorageContext.from_defaults(vector_store=store)
-    VectorStoreIndex.from_documents(
-        documents,
-        storage_context=storage_context,
-        show_progress=True,  # this will show you a progress bar as the embeddings are created
-    )
-    logger.info(
-        f"Successfully created embeddings and save to your Pinecone index {os.environ['PINECONE_INDEX_NAME']}"
-    )
-
-
-if __name__ == "__main__":
-    init_settings()
-    generate_datasource()

packages/create-llama/templates/components/vectordbs/python/pinecone/index.py

@@ -1,20 +0,0 @@
-import logging
-import os
-
-from llama_index.core.indices import VectorStoreIndex
-from llama_index.vector_stores.pinecone import PineconeVectorStore
-
-
-logger = logging.getLogger("uvicorn")
-
-
-def get_index():
-    logger.info("Connecting to index from Pinecone...")
-    store = PineconeVectorStore(
-        api_key=os.environ["PINECONE_API_KEY"],
-        index_name=os.environ["PINECONE_INDEX_NAME"],
-        environment=os.environ["PINECONE_ENVIRONMENT"],
-    )
-    index = VectorStoreIndex.from_vector_store(store)
-    logger.info("Finished connecting to index from Pinecone.")
-    return index

packages/create-llama/templates/components/vectordbs/typescript/mongo/generate.mjs

@@ -1,49 +0,0 @@
-/* eslint-disable turbo/no-undeclared-env-vars */
-import * as dotenv from "dotenv";
-import {
-  MongoDBAtlasVectorSearch,
-  SimpleDirectoryReader,
-  VectorStoreIndex,
-  storageContextFromDefaults,
-} from "llamaindex";
-import { MongoClient } from "mongodb";
-import { STORAGE_DIR, checkRequiredEnvVars } from "./shared.mjs";
-
-dotenv.config();
-
-const mongoUri = process.env.MONGO_URI;
-const databaseName = process.env.MONGODB_DATABASE;
-const vectorCollectionName = process.env.MONGODB_VECTORS;
-const indexName = process.env.MONGODB_VECTOR_INDEX;
-
-async function loadAndIndex() {
-  // Create a new client and connect to the server
-  const client = new MongoClient(mongoUri);
-
-  // load objects from storage and convert them into LlamaIndex Document objects
-  const documents = await new SimpleDirectoryReader().loadData({
-    directoryPath: STORAGE_DIR,
-  });
-
-  // create Atlas as a vector store
-  const vectorStore = new MongoDBAtlasVectorSearch({
-    mongodbClient: client,
-    dbName: databaseName,
-    collectionName: vectorCollectionName, // this is where your embeddings will be stored
-    indexName: indexName, // this is the name of the index you will need to create
-  });
-
-  // now create an index from all the Documents and store them in Atlas
-  const storageContext = await storageContextFromDefaults({ vectorStore });
-  await VectorStoreIndex.fromDocuments(documents, { storageContext });
-  console.log(
-    `Successfully created embeddings in the MongoDB collection ${vectorCollectionName}.`,
-  );
-  await client.close();
-}
-
-(async () => {
-  checkRequiredEnvVars();
-  await loadAndIndex();
-  console.log("Finished generating storage.");
-})();

packages/create-llama/templates/components/vectordbs/typescript/mongo/index.ts

@@ -1,37 +0,0 @@
-/* eslint-disable turbo/no-undeclared-env-vars */
-import {
-  ContextChatEngine,
-  LLM,
-  MongoDBAtlasVectorSearch,
-  serviceContextFromDefaults,
-  VectorStoreIndex,
-} from "llamaindex";
-import { MongoClient } from "mongodb";
-import { checkRequiredEnvVars, CHUNK_OVERLAP, CHUNK_SIZE } from "./shared.mjs";
-
-async function getDataSource(llm: LLM) {
-  checkRequiredEnvVars();
-  const client = new MongoClient(process.env.MONGO_URI!);
-  const serviceContext = serviceContextFromDefaults({
-    llm,
-    chunkSize: CHUNK_SIZE,
-    chunkOverlap: CHUNK_OVERLAP,
-  });
-  const store = new MongoDBAtlasVectorSearch({
-    mongodbClient: client,
-    dbName: process.env.MONGODB_DATABASE,
-    collectionName: process.env.MONGODB_VECTORS,
-    indexName: process.env.MONGODB_VECTOR_INDEX,
-  });
-
-  return await VectorStoreIndex.fromVectorStore(store, serviceContext);
-}
-
-export async function createChatEngine(llm: LLM) {
-  const index = await getDataSource(llm);
-  const retriever = index.asRetriever({ similarityTopK: 3 });
-  return new ContextChatEngine({
-    chatModel: llm,
-    retriever,
-  });
-}

packages/create-llama/templates/components/vectordbs/typescript/mongo/shared.mjs

@@ -1,27 +0,0 @@
-export const STORAGE_DIR = "./data";
-export const CHUNK_SIZE = 512;
-export const CHUNK_OVERLAP = 20;
-
-const REQUIRED_ENV_VARS = [
-  "MONGO_URI",
-  "MONGODB_DATABASE",
-  "MONGODB_VECTORS",
-  "MONGODB_VECTOR_INDEX",
-];
-
-export function checkRequiredEnvVars() {
-  const missingEnvVars = REQUIRED_ENV_VARS.filter((envVar) => {
-    return !process.env[envVar];
-  });
-
-  if (missingEnvVars.length > 0) {
-    console.log(
-      `The following environment variables are required but missing: ${missingEnvVars.join(
-        ", ",
-      )}`,
-    );
-    throw new Error(
-      `Missing environment variables: ${missingEnvVars.join(", ")}`,
-    );
-  }
-}

packages/create-llama/templates/components/vectordbs/typescript/none/constants.mjs

@@ -1,4 +0,0 @@
-export const STORAGE_DIR = "./data";
-export const STORAGE_CACHE_DIR = "./cache";
-export const CHUNK_SIZE = 512;
-export const CHUNK_OVERLAP = 20;

packages/create-llama/templates/components/vectordbs/typescript/none/generate.mjs

@@ -1,53 +0,0 @@
-import {
-  serviceContextFromDefaults,
-  SimpleDirectoryReader,
-  storageContextFromDefaults,
-  VectorStoreIndex,
-} from "llamaindex";
-
-import * as dotenv from "dotenv";
-
-import {
-  CHUNK_OVERLAP,
-  CHUNK_SIZE,
-  STORAGE_CACHE_DIR,
-  STORAGE_DIR,
-} from "./constants.mjs";
-
-// Load environment variables from local .env file
-dotenv.config();
-
-async function getRuntime(func) {
-  const start = Date.now();
-  await func();
-  const end = Date.now();
-  return end - start;
-}
-
-async function generateDatasource(serviceContext) {
-  console.log(`Generating storage context...`);
-  // Split documents, create embeddings and store them in the storage context
-  const ms = await getRuntime(async () => {
-    const storageContext = await storageContextFromDefaults({
-      persistDir: STORAGE_CACHE_DIR,
-    });
-    const documents = await new SimpleDirectoryReader().loadData({
-      directoryPath: STORAGE_DIR,
-    });
-    await VectorStoreIndex.fromDocuments(documents, {
-      storageContext,
-      serviceContext,
-    });
-  });
-  console.log(`Storage context successfully generated in ${ms / 1000}s.`);
-}
-
-(async () => {
-  const serviceContext = serviceContextFromDefaults({
-    chunkSize: CHUNK_SIZE,
-    chunkOverlap: CHUNK_OVERLAP,
-  });
-
-  await generateDatasource(serviceContext);
-  console.log("Finished generating storage.");
-})();

packages/create-llama/templates/components/vectordbs/typescript/none/index.ts

@@ -1,44 +0,0 @@
-import {
-  ContextChatEngine,
-  LLM,
-  serviceContextFromDefaults,
-  SimpleDocumentStore,
-  storageContextFromDefaults,
-  VectorStoreIndex,
-} from "llamaindex";
-import { CHUNK_OVERLAP, CHUNK_SIZE, STORAGE_CACHE_DIR } from "./constants.mjs";
-
-async function getDataSource(llm: LLM) {
-  const serviceContext = serviceContextFromDefaults({
-    llm,
-    chunkSize: CHUNK_SIZE,
-    chunkOverlap: CHUNK_OVERLAP,
-  });
-  const storageContext = await storageContextFromDefaults({
-    persistDir: `${STORAGE_CACHE_DIR}`,
-  });
-
-  const numberOfDocs = Object.keys(
-    (storageContext.docStore as SimpleDocumentStore).toDict(),
-  ).length;
-  if (numberOfDocs === 0) {
-    throw new Error(
-      `StorageContext is empty - call 'npm run generate' to generate the storage first`,
-    );
-  }
-  return await VectorStoreIndex.init({
-    storageContext,
-    serviceContext,
-  });
-}
-
-export async function createChatEngine(llm: LLM) {
-  const index = await getDataSource(llm);
-  const retriever = index.asRetriever();
-  retriever.similarityTopK = 3;
-
-  return new ContextChatEngine({
-    chatModel: llm,
-    retriever,
-  });
-}

packages/create-llama/templates/components/vectordbs/typescript/pg/generate.mjs

@@ -1,45 +0,0 @@
-/* eslint-disable turbo/no-undeclared-env-vars */
-import * as dotenv from "dotenv";
-import {
-  PGVectorStore,
-  SimpleDirectoryReader,
-  VectorStoreIndex,
-  storageContextFromDefaults,
-} from "llamaindex";
-import {
-  PGVECTOR_SCHEMA,
-  PGVECTOR_TABLE,
-  STORAGE_DIR,
-  checkRequiredEnvVars,
-} from "./shared.mjs";
-
-dotenv.config();
-
-async function loadAndIndex() {
-  // load objects from storage and convert them into LlamaIndex Document objects
-  const documents = await new SimpleDirectoryReader().loadData({
-    directoryPath: STORAGE_DIR,
-  });
-
-  // create postgres vector store
-  const vectorStore = new PGVectorStore({
-    connectionString: process.env.PG_CONNECTION_STRING,
-    schemaName: PGVECTOR_SCHEMA,
-    tableName: PGVECTOR_TABLE,
-  });
-  vectorStore.setCollection(STORAGE_DIR);
-  vectorStore.clearCollection();
-
-  // create index from all the Documents
-  console.log("Start creating embeddings...");
-  const storageContext = await storageContextFromDefaults({ vectorStore });
-  await VectorStoreIndex.fromDocuments(documents, { storageContext });
-  console.log(`Successfully created embeddings.`);
-}
-
-(async () => {
-  checkRequiredEnvVars();
-  await loadAndIndex();
-  console.log("Finished generating storage.");
-  process.exit(0);
-})();