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Author SHA1 Message Date
github-actions[bot] b2634e47ca Release 0.9.5 (#1694)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>
2025-02-28 18:18:14 +07:00
Thuc Pham ad3c7f1ec1 fix: streaming issues with LLMAgent (#1692) 2025-02-28 18:13:36 +07:00
Alex Yang 335f2df626 chore: fix lock file 2025-02-27 12:31:11 -08:00
github-actions[bot] ee963644bf Release 0.9.4 (#1689)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
2025-02-27 12:28:48 -08:00
Alex Yang cb256f24ae feat: support gpt-4.5 (#1688) 2025-02-27 12:24:33 -08:00
Alex Yang 1ccc04ecb5 chore: fix changeset 2025-02-27 12:17:12 -08:00
Brian Lange 034639153b feat: Voyage embeddings (#1574)
Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de>
2025-02-27 10:22:33 +07:00
patryktop 1914b52708 feat: add Claude 3.7 Sonnet model to community package (#1683) 2025-02-26 14:38:14 -08:00
Alex Yang cb021e7196 feat(node-parser): support async function (#1682) 2025-02-26 08:59:51 -08:00
ratacat c2aa836b35 docs: upgrade remote ollama embeddings (#1680) 2025-02-25 11:39:16 -08:00
github-actions[bot] 3b0f55f1ea Release 0.9.3 (#1676)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>
2025-02-25 16:53:30 +07:00
Marcus Schiesser a9c6144eec feat: stream thinking tokens for claude 3.7 (#1679) 2025-02-25 16:48:12 +07:00
Marcus Schiesser 3564244ced chore: add claude 3.7 support (#1678) 2025-02-25 15:18:45 +07:00
Gunnar Holwerda d952e68ec4 Fix refine synthesizer empty source nodes behavior (#1677) 2025-02-24 10:56:21 +07:00
Tushar Sonawane 5c026e839f feat(vectorstore): adds firestore vector store support (#1600) 2025-02-21 16:23:50 +07:00
github-actions[bot] 9c1c5b4d50 Release 0.9.2 (#1673)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
2025-02-21 10:57:11 +07:00
Thuc Pham c902fcbc33 chore: bump llamacloud openapi (#1674) 2025-02-20 17:47:41 +07:00
Thuc Pham 88d776f392 fix: enhance error message in llamacloud (#1672) 2025-02-20 16:33:34 +07:00
github-actions[bot] 6fcc6bcb84 Release @llamaindex/anthropic@0.1.2 (#1671)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
2025-02-20 12:56:33 +07:00
Thuc Pham be74207945 fix: dont add empty text block to tool call (#1670) 2025-02-20 12:47:43 +07:00
Alex Yang 6be223dfad chore: bump version (#1668) 2025-02-19 19:28:12 +08:00
Alex Yang 4cbfdb5f5c ci: only run in pull request (#1669) 2025-02-19 19:11:53 +08:00
github-actions[bot] 9767d1c004 Release 0.9.1 (#1664)
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Co-authored-by: himself65 <14026360+himself65@users.noreply.github.com>
2025-02-19 18:15:41 +08:00
Alex Yang e831b28627 ci: add size limit check (#1667) 2025-02-19 18:05:28 +08:00
Alex Yang cc50c9c2d4 chore: trigger env package release 2025-02-19 17:59:38 +08:00
Thuc Pham 954140776e fix: missing document entrypoints (#1663)
Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de>
2025-02-14 17:06:23 +07:00
Savas Ziplies 6d37d440a6 refactor(agent): changed regex for tool use extraction to look for optional "Input:" prefix to comply with Cohere command-r models (#1654) 2025-02-14 15:17:03 +07:00
Alex Yang e724f7e9f2 fix: cjs module resolve esm module unexpectedly (#1662) 2025-02-14 15:52:37 +08:00
Alex Yang 1b029ae525 test: add cjs smoke test (#1660) 2025-02-14 14:28:09 +08:00
Marcus Schiesser d1db2189c9 docs: update starter to ask for api key (#1661) 2025-02-14 12:14:51 +07:00
Alex Yang 2c5b4030c9 chore: bump bunchee (#1645) 2025-02-14 09:41:32 +08:00
Alex Yang 96eb597059 fix: bundler issue default in default (#1653) 2025-02-14 09:20:39 +08:00
Marcus Schiesser 04098d55ff chore: fix pnpm lock (#1658) 2025-02-13 17:49:21 +07:00
Marcus Schiesser 335a6b9e88 chore: add pathe to examples (#1657) 2025-02-13 17:44:30 +07:00
github-actions[bot] c2a345ebb1 Release 0.9.0 (#1643)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>
2025-02-13 17:34:06 +07:00
Marcus Schiesser d3fa729a30 Cleanups before 0.9 release (#1656) 2025-02-13 17:26:22 +07:00
Thuc Pham c7c08005ec fix: fumadoc build fail (#1655) 2025-02-13 16:24:28 +07:00
Alex Yang bb0ae5e321 chore: fix pkg.pr.new issue (#1651) 2025-02-12 21:19:29 +08:00
Marcus Schiesser f4588bc770 chore: Remove readers package from llamaindex (#1649) 2025-02-12 17:16:41 +07:00
Marcus Schiesser b49037612d remove service context (#1618)
Co-authored-by: thucpn <thucsh2@gmail.com>
2025-02-12 15:10:11 +07:00
Thuc Pham a87efb91a4 docs: update chat engine docs (#1648) 2025-02-12 12:45:26 +07:00
Thuc Pham 6a4a73760b chore: remove re-exporting packages in llamaindex (#1624)
Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de>
2025-02-12 12:44:52 +07:00
Alex Yang 1564831158 ci: fix pkg-pr-new release (#1646) 2025-02-11 22:42:42 +08:00
Alex Yang 4d94f6e50d test: smoke test with cjs/esm dual package (#1644) 2025-02-11 15:02:06 +08:00
Thuc Pham 7bd5d9340c docs: update workflow doc (#1637)
Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de>
2025-02-11 13:41:11 +07:00
Thuc Pham d924c63162 feat: asChatEngine function for index (#1640) 2025-02-11 12:57:15 +07:00
github-actions[bot] 83cff1277c Release 0.8.37 (#1642)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>
2025-02-11 12:48:58 +07:00
Marcus Schiesser 1c908fd852 Revert "fix: bundle output incorrect (#1638)" (#1641) 2025-02-11 12:27:11 +07:00
github-actions[bot] 56f367f08d Release 0.8.36 (#1639)
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Co-authored-by: himself65 <14026360+himself65@users.noreply.github.com>
2025-02-10 21:49:19 +08:00
Alex Yang cb608b5d01 fix: bundle output incorrect (#1638) 2025-02-10 21:30:36 +08:00
github-actions[bot] bd55bcffff Release 0.8.35 (#1633)
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Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>
2025-02-10 16:45:42 +07:00
Thuc Pham 6d4d96f8fe chore: update import to workspace pages for examples and docs (#1626)
Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de>
2025-02-10 15:43:29 +07:00
Thuc Pham b6ea2bf964 fix(gemini): use function role for message contains tool-result (#1634) 2025-02-10 12:57:45 +07:00
Parham Saidi 15563a0f70 fix: delete temp competely from params when calling openai o3 (#1629) 2025-02-10 11:07:21 +07:00
github-actions[bot] bd940d1d43 Release 0.8.34 (#1630)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
2025-02-07 16:02:27 +07:00
Thuc Pham 9f8ad37b79 fix: missing peer deps in llamaindex (#1631) 2025-02-07 15:06:41 +07:00
Peter Goldstein 7265f74c24 Add reasoning_effort for o1 and o3 (#1628) 2025-02-07 12:01:48 +07:00
github-actions[bot] e3f1b85846 Release 0.8.33 (#1619)
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Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>
2025-02-06 15:53:47 +07:00
Peter Goldstein e38e474f86 Add Gemini 2.0 models (#1625) 2025-02-06 15:41:20 +07:00
Parham Saidi 2019a041f7 fix: o3 calls do not support temperature param (#1622) 2025-02-06 10:23:23 +07:00
Thuc Pham 067a4894fe fix: missing condition to stringify tool input (#1620) 2025-02-05 17:25:37 +07:00
clean99 21769c8ad9 Fix: update deprecated response property in examples (#1614)
Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de>
2025-02-05 11:28:32 +07:00
github-actions[bot] 89ea1e1d31 Release 0.8.32 (#1595)
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Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>
2025-02-04 12:23:47 +07:00
siquick d9bbaf95f3 chore: updated docs and examples to use correct PGVectorStore imports (#1611)
Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de>
2025-02-04 11:18:39 +07:00
Marcus Schiesser 8744796c06 update the versioon of chromadb client (#1616)
Co-authored-by: my8bit <mail@my8bit.name>
2025-02-04 10:58:04 +07:00
Ihor Pavlenko f02621e379 fix: doc links (#1610) 2025-02-04 10:46:04 +07:00
Peter Goldstein 1892e1ce1d Add O3 mini model (#1612) 2025-02-04 10:34:22 +07:00
dependabot[bot] d90d8959a5 chore(deps-dev): bump vite from 5.4.11 to 5.4.12 (#1604)
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2025-02-04 10:33:18 +07:00
Thuc Pham 4df1fe6cca chore: migrate llamaindex llms and embeddings to their own packages (#1615) 2025-02-03 17:32:19 +07:00
Thuc Pham 34faf4821a chore: move vector stores to their own packages (#1605) 2025-01-24 12:45:13 +07:00
Marcus Schiesser b24ffc6174 fix: pinecone import (#1603) 2025-01-21 12:32:05 +07:00
Thuc Pham 82e25c924c fix: remove ignore package from changeset (#1602) 2025-01-21 12:28:39 +07:00
Thuc Pham 1931bbca74 chore: move azure code to own @llamaindex/azure package (#1601) 2025-01-21 12:14:17 +07:00
Thuc Pham 94566169fb chore: move postgres storage classes to @llamaindex/postgres (#1597) 2025-01-20 12:24:44 +07:00
Alex Yang d6c270ec7a feat(cloud): support pass project and org id to llama parse reader (#1594) 2025-01-08 11:23:48 -08:00
github-actions[bot] e3a77044d5 Release 0.8.31 (#1579)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: himself65 <himself65@users.noreply.github.com>
2025-01-08 10:42:19 -08:00
Alex Yang fd9c8294e1 chore: bump llamacloud openapi (#1592) 2025-01-06 23:12:41 -08:00
Thuc Pham 0ebbfc1031 fix: clean up docstore when generating embedding fail (#1588)
Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de>
2025-01-07 11:58:09 +07:00
Alex Yang 5dec9f912a chore: bump sdk deps (#1591) 2025-01-06 17:03:15 -08:00
Alex Yang 1f53819b64 chore: bump version (#1583) 2025-01-02 07:43:17 -08:00
Erik d211b7ab13 add tool call history support in chat messages (#1565) 2024-12-22 19:09:38 -08:00
Thuc Pham 057ee146bd fix: add start command for stackblitz (#1577) 2024-12-20 23:55:33 -08:00
Thuc Pham 4a831b192c fix: docs migration issues (#1576) 2024-12-20 16:42:54 +07:00
Thuc Pham cf29ca1bf8 [WIP] feat: remove legacy docs (#1571) 2024-12-20 15:12:01 +07:00
Wassim Chegham 09b933f8da feat: add Azure AI Vector Search (#1485) 2024-12-18 11:26:53 -06:00
Thuc Pham 44c0734106 feat: migrate legacy docs (#1568) 2024-12-18 02:18:47 -08:00
github-actions[bot] a7023b4a93 Release 0.8.30 (#1570)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
2024-12-16 11:40:25 -08:00
Alex Yang 012495b5ba chore: bump llamacloud sdk (#1569) 2024-12-16 11:10:09 -08:00
github-actions[bot] a8afb9a7a7 Release 0.8.29 (#1566)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
2024-12-13 19:19:03 -08:00
Peter Goldstein dd596a0cf2 Add Gemini Flash 2.0 Experimental (#1563) 2024-12-13 12:10:46 -08:00
Alex Yang 9e648a0b4f chore: bump version (#1562) 2024-12-11 12:56:38 -08:00
github-actions[bot] bbb87f42ed Release 0.8.28 (#1559)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: himself65 <himself65@users.noreply.github.com>
2024-12-11 12:09:46 -08:00
Parham Saidi 24caf93efe fix: added inference profile mapping for nova models (#1560) 2024-12-11 11:17:40 -08:00
Thuc Pham a9b5b993fa feat: build api reference pages for new documentation site (#1551) 2024-12-11 09:21:21 -08:00
github-actions[bot] f369d3de4f Release 0.8.27 (#1545)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: himself65 <himself65@users.noreply.github.com>
2024-12-11 12:18:21 +07:00
Parham Saidi c1850ee370 feat: Amazon Nova support via Bedrock (#1548) 2024-12-10 18:56:35 -08:00
Marcus Schiesser 086a65141d Add adapter to use Vercel model providers (#1558)
Co-authored-by: Alex Yang <himself65@outlook.com>
2024-12-09 21:02:57 -08:00
Qwertic d99d598491 Update typescript.mdx (#1557) 2024-12-09 19:52:15 -08:00
Gunnar Holwerda a0e6f57d9b Pass options through to userWebpack in withLlamaIndex (#1550) 2024-12-09 19:51:52 -08:00
Gunnar Holwerda e0f6cc3be1 fix: return actual source nodes with compact and refine response synt… (#1554) 2024-12-09 11:00:12 -08:00
Jingyi Zhao 8386510d86 chore: add e2e working example for ingestion (#1543) 2024-12-04 17:36:00 -08:00
Marcus Schiesser b504303c66 fix: allow Node 18 again to make Stackblitz work (#1544) 2024-12-03 20:57:20 -08:00
Marcus Schiesser cf9a9356e0 fix: discord link (#1542) 2024-12-03 11:16:02 +07:00
github-actions[bot] 335020e242 Release 0.8.26 (#1541)
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Co-authored-by: himself65 <himself65@users.noreply.github.com>
2024-12-02 12:23:57 -08:00
Alex Yang 3d1808b5d2 chore: bump version (#1540) 2024-12-02 12:18:51 -08:00
Alex Yang a19cbc7fe0 ci: fix (#1539) 2024-12-02 10:33:44 -08:00
github-actions[bot] b8f0cbc4e0 Release 0.8.25 (#1536)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: marcusschiesser <marcusschiesser@users.noreply.github.com>
2024-12-02 03:02:36 -08:00
Marcus Schiesser 7e8230b056 fix: release missing readers package (#1537) 2024-12-02 17:54:22 +07:00
Alex Yang 8be45899a7 chore: bump version 2024-12-02 02:21:13 -08:00
github-actions[bot] c4800bcf82 Release @llamaindex/vercel@0.0.2 (#1535) 2024-12-02 14:19:40 +07:00
Thuc Pham fd38a253b7 feat: add vercel chat example (#1532)
Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de>
2024-12-02 13:56:28 +07:00
github-actions[bot] 510191cb5d Release 0.8.24 (#1531)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
2024-11-30 06:05:47 -08:00
Jingyi Zhao 7934ade092 fix: add obsidian reader to index (#1533) 2024-11-30 01:29:45 -08:00
Jingyi Zhao a6c1eab762 feat: data connector for obsidian note taking app (#1529) 2024-11-29 22:39:59 -08:00
crisjy 515f2c1e3d feat: add AzureCosmosDBMongoVectorStore (#1528) 2024-11-28 17:53:09 -08:00
github-actions[bot] dc85649ead Release 0.8.23 (#1526)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
2024-11-26 17:41:29 -08:00
Alex Yang d2b2722a30 fix: switch tokenizer in cloudflare (#1525) 2024-11-26 15:42:20 -08:00
github-actions[bot] a2bbd62399 Release 0.8.22 (#1520)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
2024-11-21 23:17:45 -08:00
Alex Yang 969365ca0a feat: add cloudflare worker full example (#1521) 2024-11-21 23:05:40 -08:00
fatmelon 819af453d6 feat: add Azure CosmosDB Mongo vCore Chat store (#1516)
Co-authored-by: root <root@CPC-yangq-FRSGK>
2024-11-21 21:25:41 -08:00
github-actions[bot] 9db36f7384 Release 0.8.21 (#1513)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
2024-11-19 18:18:35 -08:00
fatmelon efa221116f feat: integrate with azure cosmos db mongo vCore (#1500)
Co-authored-by: root <root@CPC-yangq-FRSGK>
Co-authored-by: Alex Yang <himself65@outlook.com>
2024-11-19 17:58:25 -08:00
Alex Yang 83c3897539 fix: pinecone vector store (#1512) 2024-11-19 17:51:45 -08:00
github-actions[bot] e1cbce1f80 Release 0.8.20 (#1511)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
2024-11-19 10:01:18 -08:00
Madarco 02b22da384 fix: supports vercel bundling (#1509)
Co-authored-by: Alex Yang <himself65@outlook.com>
2024-11-19 09:52:56 -08:00
677 changed files with 38082 additions and 18492 deletions
+1 -1
View File
@@ -25,4 +25,4 @@ jobs:
run: pnpm run build
- name: Pre Release
run: pnpx pkg-pr-new publish ./packages/* ./packages/providers/*
run: pnpx pkg-pr-new publish --pnpm ./packages/* ./packages/providers/* ./packages/providers/storage/*
+28 -8
View File
@@ -23,7 +23,7 @@ jobs:
strategy:
fail-fast: false
matrix:
node-version: [20.x, 22.x, 23.x]
node-version: [18.x, 20.x, 22.x, 23.x]
name: E2E on Node.js ${{ matrix.node-version }}
runs-on: ubuntu-latest
steps:
@@ -53,7 +53,7 @@ jobs:
strategy:
fail-fast: false
matrix:
node-version: [20.x, 22.x, 23.x]
node-version: [18.x, 20.x, 22.x, 23.x]
name: Test on Node.js ${{ matrix.node-version }}
runs-on: ubuntu-latest
steps:
@@ -83,11 +83,6 @@ jobs:
run: pnpm install
- name: Build
run: pnpm run build
- name: Use Build For Examples
run: |
pnpm link ../packages/llamaindex/
cd readers && pnpm link ../../packages/llamaindex/
working-directory: ./examples
- name: Run Type Check
run: pnpm run type-check
- name: Run Circular Dependency Check
@@ -103,6 +98,7 @@ jobs:
- nextjs-node-runtime
- waku-query-engine
- llama-parse-browser
- vite-import-llamaindex
runs-on: ubuntu-latest
name: Build LlamaIndex Example (${{ matrix.packages }})
steps:
@@ -121,6 +117,30 @@ jobs:
run: pnpm run build
working-directory: e2e/examples/${{ matrix.packages }}
size-limit:
runs-on: ubuntu-latest
if: github.event_name == 'pull_request'
name: Size Limit
steps:
- uses: actions/checkout@v4
- uses: pnpm/action-setup@v4
- name: Setup Node.js
uses: actions/setup-node@v4
with:
node-version-file: ".nvmrc"
cache: "pnpm"
- name: Install dependencies
run: pnpm install
- name: Build llamaindex
run: pnpm run build
- uses: andresz1/size-limit-action@94bc357df29c36c8f8d50ea497c3e225c3c95d1d
with:
github_token: ${{ secrets.GITHUB_TOKEN }}
directory: e2e/examples/vite-import-llamaindex
skip_step: "install"
build_script: build
package_manager: pnpm
typecheck-examples:
runs-on: ubuntu-latest
@@ -150,7 +170,7 @@ jobs:
done
- name: Pack provider packages
run: |
for dir in packages/providers/*; do
for dir in packages/providers/* packages/providers/storage/*; do
if [ -d "$dir" ] && [ -f "$dir/package.json" ]; then
echo "Packing $dir"
pnpm pack --pack-destination ${{ runner.temp }} -C $dir
+1 -3
View File
@@ -1,3 +1 @@
pnpm format
pnpm lint
npx lint-staged
pnpm run lint-staged
+1
View File
@@ -0,0 +1 @@
LlamaIndexTS
+2 -1
View File
@@ -14,5 +14,6 @@
"[json]": {
"editor.defaultFormatter": "esbenp.prettier-vscode"
},
"prettier.prettierPath": "./node_modules/prettier"
"prettier.prettierPath": "./node_modules/prettier",
"prettier.configPath": "prettier.config.mjs"
}
+7
View File
@@ -41,8 +41,15 @@ pnpm install
### Build the packages
You'll need Turbo to build the packages. If you don't have it, you can run it with `pnpx`.
To build all packages, run:
```shell
# Build all packages
pnpx turbo build --filter "./packages/*"
# Or if you have turbo installed, you can run:
turbo build --filter "./packages/*"
```
+8 -34
View File
@@ -63,46 +63,20 @@ yarn add llamaindex
### Setup in Node.js, Deno, Bun, TypeScript...?
See our official document: <https://ts.llamaindex.ai/docs/llamaindex/setup/getting-started>
See our official document: <https://ts.llamaindex.ai/docs/llamaindex/getting_started/>
### Tips when using in non-Node.js environments
### Adding provider packages
When you are importing `llamaindex` in a non-Node.js environment(such as Vercel Edge, Cloudflare Workers, etc.)
Some classes are not exported from top-level entry file.
In most cases, you'll also need to install provider packages to use LlamaIndexTS. These are for adding AI models, file readers for ingestion or storing documents, e.g. in vector databases.
The reason is that some classes are only compatible with Node.js runtime,(e.g. `PDFReader`) which uses Node.js specific APIs(like `fs`, `child_process`, `crypto`).
For example, to use the OpenAI LLM, you would install the following package:
If you need any of those classes, you have to import them instead directly though their file path in the package.
Here's an example for importing the `PineconeVectorStore` class:
```typescript
import { PineconeVectorStore } from "llamaindex/storage/vectorStore/PineconeVectorStore";
```shell
npm install @llamaindex/openai
pnpm install @llamaindex/openai
yarn add @llamaindex/openai
```
As the `PDFReader` is not working with the Edge runtime, here's how to use the `SimpleDirectoryReader` with the `LlamaParseReader` to load PDFs:
```typescript
import { SimpleDirectoryReader } from "llamaindex/readers/SimpleDirectoryReader";
import { LlamaParseReader } from "llamaindex/readers/LlamaParseReader";
export const DATA_DIR = "./data";
export async function getDocuments() {
const reader = new SimpleDirectoryReader();
// Load PDFs using LlamaParseReader
return await reader.loadData({
directoryPath: DATA_DIR,
fileExtToReader: {
pdf: new LlamaParseReader({ resultType: "markdown" }),
},
});
}
```
> _Note_: Reader classes have to be added explictly to the `fileExtToReader` map in the Edge version of the `SimpleDirectoryReader`.
You'll find a complete example with LlamaIndexTS here: https://github.com/run-llama/create_llama_projects/tree/main/nextjs-edge-llamaparse
## Playground
Check out our NextJS playground at https://llama-playground.vercel.app/. The source is available at https://github.com/run-llama/ts-playground
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---
"llamaindex": minor
"docs": minor
---
Add deepseek llm class
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# Dependencies
/node_modules
# Production
/build
# Generated files
.docusaurus
.cache-loader
lib
# Misc
.DS_Store
.env.local
.env.development.local
.env.test.local
.env.production.local
npm-debug.log*
yarn-debug.log*
yarn-error.log*
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# docs
## 0.0.124
### Patch Changes
- Updated dependencies [90d265c]
- llamaindex@0.8.19
## 0.0.123
### Patch Changes
- Updated dependencies [d17450f]
- llamaindex@0.8.18
## 0.0.122
### Patch Changes
- llamaindex@0.8.17
## 0.0.121
### Patch Changes
- llamaindex@0.8.16
## 0.0.120
### Patch Changes
- Updated dependencies [3d503cb]
- Updated dependencies [5dae534]
- llamaindex@0.8.15
## 0.0.119
### Patch Changes
- Updated dependencies [630b425]
- llamaindex@0.8.14
## 0.0.118
### Patch Changes
- llamaindex@0.8.13
- @llamaindex/examples@0.0.16
## 0.0.117
### Patch Changes
- @llamaindex/examples@0.0.15
## 0.0.116
### Patch Changes
- llamaindex@0.8.12
## 0.0.115
### Patch Changes
- llamaindex@0.8.11
## 0.0.114
### Patch Changes
- Updated dependencies [f066e50]
- llamaindex@0.8.10
- @llamaindex/examples@0.0.14
## 0.0.113
### Patch Changes
- Updated dependencies [4fc001c]
- Updated dependencies [4d4cd8a]
- llamaindex@0.8.9
## 0.0.112
### Patch Changes
- Updated dependencies [ad85bd0]
- llamaindex@0.8.8
- @llamaindex/examples@0.0.13
## 0.0.111
### Patch Changes
- llamaindex@0.8.7
## 0.0.110
### Patch Changes
- Updated dependencies [95a5cc6]
- llamaindex@0.8.6
## 0.0.109
### Patch Changes
- Updated dependencies [14cc9eb]
- Updated dependencies [a6db5dd]
- Updated dependencies [396b1e1]
- llamaindex@0.8.5
## 0.0.108
### Patch Changes
- Updated dependencies [35430d3]
- llamaindex@0.8.4
## 0.0.107
### Patch Changes
- llamaindex@0.8.3
## 0.0.106
### Patch Changes
- @llamaindex/examples@0.0.12
## 0.0.105
### Patch Changes
- Updated dependencies [c7a918c]
- llamaindex@0.8.2
## 0.0.104
### Patch Changes
- llamaindex@0.8.1
## 0.0.103
### Patch Changes
- Updated dependencies [359fd33]
- Updated dependencies [efb7e1b]
- Updated dependencies [98ba1e7]
- Updated dependencies [620c63c]
- llamaindex@0.8.0
- @llamaindex/examples@0.0.11
## 0.0.102
### Patch Changes
- Updated dependencies [9df9a8f]
- llamaindex@0.7.10
## 0.0.101
### Patch Changes
- Updated dependencies [691c5bc]
- llamaindex@0.7.9
## 0.0.100
### Patch Changes
- llamaindex@0.7.8
## 0.0.99
### Patch Changes
- Updated dependencies [2486bd8]
- @llamaindex/examples@0.0.10
- llamaindex@0.7.7
## 0.0.98
### Patch Changes
- Updated dependencies [534d550]
- llamaindex@0.7.6
## 0.0.97
### Patch Changes
- Updated dependencies [e9a111d]
- Updated dependencies [9f22aae]
- llamaindex@0.7.5
## 0.0.96
### Patch Changes
- llamaindex@0.7.4
## 0.0.95
### Patch Changes
- llamaindex@0.7.3
## 0.0.94
### Patch Changes
- llamaindex@0.7.2
## 0.0.93
### Patch Changes
- Updated dependencies [ae49ff4]
- Updated dependencies [4c38c1b]
- Updated dependencies [a75af83]
- Updated dependencies [a75af83]
- llamaindex@0.7.1
## 0.0.92
### Patch Changes
- Updated dependencies [1364e8e]
- Updated dependencies [3b7736f]
- Updated dependencies [96fc69c]
- llamaindex@0.7.0
- @llamaindex/examples@0.0.9
## 0.0.91
### Patch Changes
- Updated dependencies [5729bd9]
- llamaindex@0.6.22
## 0.0.90
### Patch Changes
- Updated dependencies [6f75306]
- Updated dependencies [94cb4ad]
- llamaindex@0.6.21
## 0.0.89
### Patch Changes
- Updated dependencies [6a9a7b1]
- llamaindex@0.6.20
## 0.0.88
### Patch Changes
- Updated dependencies [62cba52]
- Updated dependencies [d265e96]
- Updated dependencies [d30bbf7]
- Updated dependencies [53fd00a]
- llamaindex@0.6.19
## 0.0.87
### Patch Changes
- Updated dependencies [5f67820]
- Updated dependencies [fe08d04]
- llamaindex@0.6.18
## 0.0.86
### Patch Changes
- Updated dependencies [ee697fb]
- llamaindex@0.6.17
## 0.0.85
### Patch Changes
- Updated dependencies [63e9846]
- Updated dependencies [6f3a31c]
- llamaindex@0.6.16
## 0.0.84
### Patch Changes
- Updated dependencies [2a82413]
- llamaindex@0.6.15
## 0.0.83
### Patch Changes
- llamaindex@0.6.14
## 0.0.82
### Patch Changes
- llamaindex@0.6.13
## 0.0.81
### Patch Changes
- Updated dependencies [f7b4e94]
- Updated dependencies [78037a6]
- Updated dependencies [1d9e3b1]
- llamaindex@0.6.12
## 0.0.80
### Patch Changes
- Updated dependencies [df441e2]
- llamaindex@0.6.11
## 0.0.79
### Patch Changes
- Updated dependencies [ebc5105]
- Updated dependencies [6cce3b1]
- llamaindex@0.6.10
## 0.0.78
### Patch Changes
- llamaindex@0.6.9
## 0.0.77
### Patch Changes
- Updated dependencies [8b7fdba]
- llamaindex@0.6.8
## 0.0.76
### Patch Changes
- Updated dependencies [23bcc37]
- llamaindex@0.6.7
## 0.0.75
### Patch Changes
- Updated dependencies [d902cc3]
- Updated dependencies [025ffe6]
- Updated dependencies [a659574]
- llamaindex@0.6.6
## 0.0.74
### Patch Changes
- Updated dependencies [e9714db]
- llamaindex@0.6.5
## 0.0.73
### Patch Changes
- Updated dependencies [b48bcc3]
- llamaindex@0.6.4
## 0.0.72
### Patch Changes
- Updated dependencies [2cd1383]
- Updated dependencies [5c4badb]
- llamaindex@0.6.3
## 0.0.71
### Patch Changes
- Updated dependencies [749b43a]
- llamaindex@0.6.2
## 0.0.70
### Patch Changes
- Updated dependencies [fbd5e01]
- Updated dependencies [6b70c54]
- Updated dependencies [1a6137b]
- Updated dependencies [85c2e19]
- llamaindex@0.6.1
## 0.0.69
### Patch Changes
- Updated dependencies [11feef8]
- llamaindex@0.6.0
- @llamaindex/examples@0.0.8
## 0.0.68
### Patch Changes
- Updated dependencies [7edeb1c]
- llamaindex@0.5.27
## 0.0.67
### Patch Changes
- Updated dependencies [ffe0cd1]
- Updated dependencies [ffe0cd1]
- llamaindex@0.5.26
## 0.0.66
### Patch Changes
- Updated dependencies [4810364]
- Updated dependencies [d3bc663]
- llamaindex@0.5.25
## 0.0.65
### Patch Changes
- llamaindex@0.5.24
## 0.0.64
### Patch Changes
- llamaindex@0.5.23
## 0.0.63
### Patch Changes
- Updated dependencies [4648da6]
- llamaindex@0.5.22
## 0.0.62
### Patch Changes
- Updated dependencies [ae1149f]
- Updated dependencies [2411c9f]
- Updated dependencies [e8f229c]
- Updated dependencies [11b3856]
- Updated dependencies [83d7f41]
- Updated dependencies [0148354]
- Updated dependencies [1711f6d]
- llamaindex@0.5.21
## 0.0.61
### Patch Changes
- Updated dependencies [d9d6c56]
- Updated dependencies [22ff486]
- Updated dependencies [eed0b04]
- llamaindex@0.5.20
## 0.0.60
### Patch Changes
- Updated dependencies [fcbf183]
- llamaindex@0.5.19
## 0.0.59
### Patch Changes
- Updated dependencies [8b66cf4]
- llamaindex@0.5.18
## 0.0.58
### Patch Changes
- Updated dependencies [c654398]
- llamaindex@0.5.17
## 0.0.57
### Patch Changes
- Updated dependencies [58abc57]
- llamaindex@0.5.16
## 0.0.56
### Patch Changes
- Updated dependencies [01c184c]
- Updated dependencies [07a275f]
- llamaindex@0.5.15
## 0.0.55
### Patch Changes
- Updated dependencies [c825a2f]
- llamaindex@0.5.14
## 0.0.54
### Patch Changes
- llamaindex@0.5.13
## 0.0.53
### Patch Changes
- Updated dependencies [345300f]
- Updated dependencies [da5cfc4]
- Updated dependencies [da5cfc4]
- llamaindex@0.5.12
## 0.0.52
### Patch Changes
- 376d29a: feat: added tool calling and agent support for llama3.1 504B
- llamaindex@0.5.11
## 0.0.51
### Patch Changes
- 086b940: feat: add DeepSeek LLM
- 5d5716b: feat: add a reader for JSON data
- Updated dependencies [086b940]
- Updated dependencies [5d5716b]
- Updated dependencies [91d02a4]
- Updated dependencies [fb6db45]
- llamaindex@0.5.10
## 0.0.50
### Patch Changes
- Updated dependencies [15962b3]
- llamaindex@0.5.9
## 0.0.49
### Patch Changes
- Updated dependencies [3d5ba08]
- Updated dependencies [d917cdc]
- llamaindex@0.5.8
## 0.0.48
### Patch Changes
- Updated dependencies [ec59acd]
- llamaindex@0.5.7
## 0.0.47
### Patch Changes
- Updated dependencies [2562244]
- Updated dependencies [325aa51]
- Updated dependencies [ab700ea]
- Updated dependencies [92f0782]
- Updated dependencies [6cf6ae6]
- Updated dependencies [b7cfe5b]
- llamaindex@0.5.6
## 0.0.46
### Patch Changes
- Updated dependencies [b974eea]
- llamaindex@0.5.5
## 0.0.45
### Patch Changes
- Updated dependencies [1a65ead]
- llamaindex@0.5.4
## 0.0.44
### Patch Changes
- Updated dependencies [9bbbc67]
- Updated dependencies [b3681bf]
- llamaindex@0.5.3
## 0.0.43
### Patch Changes
- llamaindex@0.5.2
## 0.0.42
### Patch Changes
- 2774681: Add mixedbread's embeddings and reranking API
- Updated dependencies [2774681]
- Updated dependencies [a0f424e]
- llamaindex@0.5.1
## 0.0.41
### Patch Changes
- 36ddec4: fix: typo in custom page separator parameter for LlamaParse
- Updated dependencies [16ef5dd]
- Updated dependencies [16ef5dd]
- Updated dependencies [36ddec4]
- llamaindex@0.5.0
- @llamaindex/examples@0.0.7
## 0.0.40
### Patch Changes
- llamaindex@0.4.14
## 0.0.39
### Patch Changes
- Updated dependencies [e8f8bea]
- Updated dependencies [304484b]
- llamaindex@0.4.13
## 0.0.38
### Patch Changes
- Updated dependencies [f326ab8]
- llamaindex@0.4.12
## 0.0.37
### Patch Changes
- Updated dependencies [8bf5b4a]
- llamaindex@0.4.11
## 0.0.36
### Patch Changes
- Updated dependencies [7dce3d2]
- llamaindex@0.4.10
## 0.0.35
### Patch Changes
- Updated dependencies [3a96a48]
- llamaindex@0.4.9
## 0.0.34
### Patch Changes
- Updated dependencies [83ebdfb]
- llamaindex@0.4.8
## 0.0.33
### Patch Changes
- Updated dependencies [41fe871]
- Updated dependencies [321c39d]
- Updated dependencies [f7f1af0]
- llamaindex@0.4.7
## 0.0.32
### Patch Changes
- Updated dependencies [1feb23b]
- Updated dependencies [08c55ec]
- llamaindex@0.4.6
## 0.0.31
### Patch Changes
- Updated dependencies [6c3e5d0]
- llamaindex@0.4.5
## 0.0.30
### Patch Changes
- Updated dependencies [42eb73a]
- llamaindex@0.4.4
## 0.0.29
### Patch Changes
- Updated dependencies [2ef62a9]
- llamaindex@0.4.3
- @llamaindex/examples@0.0.6
## 0.0.28
### Patch Changes
- Updated dependencies [a87a4d1]
- Updated dependencies [0730140]
- llamaindex@0.4.2
## 0.0.27
### Patch Changes
- Updated dependencies [3c47910]
- Updated dependencies [ed467a9]
- Updated dependencies [cba5406]
- llamaindex@0.4.1
## 0.0.26
### Patch Changes
- b1a4a74: docs: updated Bedrock Opus region and added a basic README
- Updated dependencies [436bc41]
- Updated dependencies [a44e54f]
- Updated dependencies [a51ed8d]
- Updated dependencies [d3b635b]
- llamaindex@0.4.0
- @llamaindex/examples@0.0.5
## 0.0.25
### Patch Changes
- Updated dependencies [6bc5bdd]
- Updated dependencies [bf25ff6]
- Updated dependencies [e6d6576]
- llamaindex@0.3.17
## 0.0.24
### Patch Changes
- 631f000: feat: DeepInfra LLM implementation
- 8832669: Community bedrock support added
- a29d835: setDocumentHash should be async
- Updated dependencies [11ae926]
- Updated dependencies [631f000]
- Updated dependencies [1378ec4]
- Updated dependencies [6b1ded4]
- Updated dependencies [4d4bd85]
- Updated dependencies [24a9d1e]
- Updated dependencies [45952de]
- Updated dependencies [54230f0]
- Updated dependencies [a29d835]
- Updated dependencies [73819bf]
- llamaindex@0.3.16
## 0.0.23
### Patch Changes
- Updated dependencies [6e156ed]
- Updated dependencies [265976d]
- Updated dependencies [8e26f75]
- llamaindex@0.3.15
## 0.0.22
### Patch Changes
- Updated dependencies [6ff7576]
- Updated dependencies [94543de]
- llamaindex@0.3.14
## 0.0.21
### Patch Changes
- Updated dependencies [1b1081b]
- Updated dependencies [37525df]
- Updated dependencies [660a2b3]
- Updated dependencies [a1f2475]
- llamaindex@0.3.13
## 0.0.20
### Patch Changes
- Updated dependencies [34fb1d8]
- llamaindex@0.3.12
## 0.0.19
### Patch Changes
- Updated dependencies [e072c45]
- Updated dependencies [9e133ac]
- Updated dependencies [447105a]
- Updated dependencies [320be3f]
- llamaindex@0.3.11
## 0.0.18
### Patch Changes
- Updated dependencies [4aba02e]
- llamaindex@0.3.10
## 0.0.17
### Patch Changes
- Updated dependencies [c3747d0]
- llamaindex@0.3.9
## 0.0.16
### Patch Changes
- Updated dependencies [ce94780]
- llamaindex@0.3.8
## 0.0.15
### Patch Changes
- Updated dependencies [b6a6606]
- Updated dependencies [b6a6606]
- llamaindex@0.3.7
## 0.0.14
### Patch Changes
- Updated dependencies [efa326a]
- llamaindex@0.3.6
## 0.0.13
### Patch Changes
- Updated dependencies [bc7a11c]
- Updated dependencies [2fe2b81]
- Updated dependencies [5596e31]
- Updated dependencies [e74fe88]
- Updated dependencies [be5df5b]
- llamaindex@0.3.5
## 0.0.12
### Patch Changes
- Updated dependencies [1dce275]
- Updated dependencies [d10533e]
- Updated dependencies [2008efe]
- Updated dependencies [5e61934]
- Updated dependencies [9e74a43]
- Updated dependencies [ee719a1]
- llamaindex@0.3.4
## 0.0.11
### Patch Changes
- Updated dependencies [e8c41c5]
- llamaindex@0.3.3
## 0.0.10
### Patch Changes
- Updated dependencies [61103b6]
- llamaindex@0.3.2
## 0.0.9
### Patch Changes
- Updated dependencies [46227f2]
- llamaindex@0.3.1
## 0.0.8
### Patch Changes
- Updated dependencies [5016f21]
- llamaindex@0.3.0
## 0.0.7
### Patch Changes
- Updated dependencies [6277105]
- llamaindex@0.2.13
## 0.0.6
### Patch Changes
- Updated dependencies [d8d952d]
- llamaindex@0.2.12
## 0.0.5
### Patch Changes
- Updated dependencies [87142b2]
- Updated dependencies [5a6cc0e]
- Updated dependencies [87142b2]
- llamaindex@0.2.11
## 0.0.4
### Patch Changes
- Updated dependencies [5116ad8]
- @llamaindex/env@0.0.5
## 0.0.3
### Patch Changes
- 09bf27a: Add Groq LLM to LlamaIndex
- Updated dependencies [cf87f84]
- @llamaindex/env@0.0.4
## 0.0.2
### Patch Changes
- 0f64084: docs: update API references
## 0.0.1
### Patch Changes
- 3154f52: chore: add qdrant readme
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# Website
This website is built using [Docusaurus 2](https://docusaurus.io/), a modern static website generator.
### Installation
```
$ pnpm
```
### Local Development
```
$ pnpm start
```
This command starts a local development server and opens up a browser window. Most changes are reflected live without having to restart the server.
However, the searchbar may not function with `yarn start`. Instead, run `yarn build` and launch a server:
```
$ npx http-server ./build
```
### Build
```
$ pnpm build
```
This command generates static content into the `build` directory and can be served using any static contents hosting service.
### Deployment
Using SSH:
```
$ USE_SSH=true pnpm deploy
```
Not using SSH:
```
$ GIT_USER=<Your GitHub username> pnpm deploy
```
If you are using GitHub pages for hosting, this command is a convenient way to build the website and push to the `gh-pages` branch.
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module.exports = {
presets: [require.resolve("@docusaurus/core/lib/babel/preset")],
};
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---
title: LlamaIndexTS v0.3.0
description: This is my first post on Docusaurus.
slug: welcome-llamaindexts-v0.3
authors:
- name: Alex Yang
title: LlamaIndexTS maintainer, Node.js Member
url: https://github.com/himself65
image_url: https://github.com/himself65.png
tags: [llamaindex, agent]
hide_table_of_contents: false
---
- [What's new in LlamaIndexTS v0.3.0](#whats-new-in-llamaindexts-v030)
- [Improvement in LlamaIndexTS v0.3.0](#improvement-in-llamaindexts-v030)
- [What's the next?](#whats-the-next)
## What's new in LlamaIndexTS v0.3.0
## Agents
In this release, we've not only ported the Agent module from the LlamaIndex Python version but have significantly
enhanced it to be more powerful and user-friendly for JavaScript/TypeScript applications.
Starting from v0.3.0, we are introducing multiple agents specifically designed for RAG applications, including:
- `OpenAIAgent`
- `AnthropicAgent`
- `ReActAgent`:
```ts
import { OpenAIAgent } from "llamaindex";
import { tools } from "./tools";
const agent = new OpenAIAgent({
tools: [...tools],
});
const { response } = await agent.chat({
message: "What is weather today?",
stream: false,
});
console.log(response.message.content);
```
We are also introducing the abstract AgentRunner class, which allows you to create your own agent by simply implementing
the task handler.
```ts
import { AgentRunner, OpenAI } from "llamaindex";
class MyLLM extends OpenAI {}
export class MyAgentWorker extends AgentWorker<MyLLM> {
taskHandler = MyAgent.taskHandler;
}
export class MyAgent extends AgentRunner<MyLLM> {
constructor(params: Params) {
super({
llm: params.llm,
chatHistory: params.chatHistory ?? [],
systemPrompt: params.systemPrompt ?? null,
runner: new MyAgentWorker(),
tools:
"tools" in params
? params.tools
: params.toolRetriever.retrieve.bind(params.toolRetriever),
});
}
// create store is a function to create a store for each task, by default it only includes `messages` and `toolOutputs`
createStore = AgentRunner.defaultCreateStore;
static taskHandler: TaskHandler<Anthropic> = async (step, enqueueOutput) => {
const { llm, stream } = step.context;
// initialize the input
const response = await llm.chat({
stream,
messages: step.context.store.messages,
});
// store the response for next task step
step.context.store.messages = [
...step.context.store.messages,
response.message,
];
// your logic here to decide whether to continue the task
const shouldContinue = Math.random(); /* <-- replace with your logic here */
enqueueOutput({
taskStep: step,
output: response,
isLast: !shouldContinue,
});
if (shouldContinue) {
const content = await someHeavyFunctionCall();
// if you want to continue the task, you can insert your new context for the next task step
step.context.store.messages = [
...step.context.store.messages,
{
content,
role: "user",
},
];
}
};
}
```
### Web Stream API for Streaming response
Web Stream is a web standard utilized in many modern web frameworks and libraries (like React 19, Deno, Node 22). We
have migrated streaming responses to Web Stream to ensure broader compatibility.
For instance, you can use the streaming response in a simple HTTP Server:
```ts
import { createServer } from "http";
import { OpenAIAgent } from "llamaindex";
import { OpenAIStream, streamToResponse } from "ai";
import { tools } from "./tools";
const agent = new OpenAIAgent({
tools: [...tools],
});
const server = createServer(async (req, res) => {
const response = await agent.chat({
message: "What is weather today?",
stream: true,
});
// Transform the response into a string readable stream
const stream: ReadableStream<string> = response.pipeThrough(
new TransformStream({
transform: (chunk, controller) => {
controller.enqueue(chunk.response.delta);
},
}),
);
// Pipe the stream to the response
streamToResponse(stream, res);
});
server.listen(3000);
```
Or it can be integrated into React Server Components (RSC) in Next.js:
```tsx
// app/actions/index.tsx
"use server";
import { createStreamableUI } from "ai/rsc";
import { OpenAIAgent } from "llamaindex";
import type { ChatMessage } from "llamaindex/llm/types";
export async function chatWithAgent(
question: string,
prevMessages: ChatMessage[] = [],
) {
const agent = new OpenAIAgent({
tools: [],
});
const responseStream = await agent.chat({
stream: true,
message: question,
chatHistory: prevMessages,
});
const uiStream = createStreamableUI(<div>loading...</div>);
responseStream
.pipeTo(
new WritableStream({
start: () => {
uiStream.update("response:");
},
write: async (message) => {
uiStream.append(message.response.delta);
},
}),
)
.catch(uiStream.error);
return uiStream.value;
}
```
```tsx
// app/src/page.tsx
"use client";
import { chatWithAgent } from "@/actions";
import type { JSX } from "react";
import { useFormState } from "react-dom";
export const runtime = "edge";
export default function Home() {
const [state, action] = useFormState<JSX.Element | null>(async () => {
return chatWithAgent("hello!", []);
}, null);
return (
<main>
{state}
<form action={action}>
<button>Chat</button>
</form>
</main>
);
}
```
## Improvement in LlamaIndexTS v0.3.0
### Better TypeScript support
We have made significant improvements to the type system to ensure that all code is thoroughly checked before it is
published. This ongoing enhancement has already resulted in better module reliability and developer experience.
For example, we have improved `FunctionTool` type with generic support:
```ts
type Input = {
a: number;
b: number;
};
const sumNumbers = FunctionTool.from<Input>(
({ a, b }) => `${a + b}`, // a and b will be checked as number
// JSON schema will be an error if you type wrong.
{
name: "sumNumbers",
description: "Use this function to sum two numbers",
parameters: {
type: "object",
properties: {
a: {
type: "number",
description: "The first number",
},
b: {
type: "number",
description: "The second number",
},
},
required: ["a", "b"],
},
},
);
```
![type checking](./img/function_tool_example.png)
### Better Next.js, Deno, Cloudflare Worker, and Waku(Vite) support
In addition to Node.js, LlamaIndexTS now offers enhanced support for Next.js, Deno, and Cloudflare Workers, making it
more versatile across different platforms.
For now, you can install llamaindex and directly import it into your existing Next.js, Deno or Cloudflare Worker project
**without any extra configuration**.
#### [Deno](https://deno.com/)
You can use LlamaIndexTS in Deno by installation through JSR:
```sh
jsr add @llamaindex/core
```
#### [Cloudflare Worker](https://developers.cloudflare.com/workers/)
For Cloudflare Workers, here is a starter template:
```typescript
export default {
async fetch(
request: Request,
env: Env,
ctx: ExecutionContext,
): Promise<Response> {
const { setEnvs } = await import("@llamaindex/env");
setEnvs(env);
const { OpenAIAgent } = await import("llamaindex");
const agent = new OpenAIAgent({
tools: [],
});
const responseStream = await agent.chat({
stream: true,
message: "Hello? What is the weather today?",
});
const textEncoder = new TextEncoder();
const response = responseStream.pipeThrough(
new TransformStream({
transform: (chunk, controller) => {
controller.enqueue(textEncoder.encode(chunk.response.delta));
},
}),
);
return new Response(response);
},
};
```
### [Waku (Vite)](https://waku.gg/)
Waku powered by Vite is a minimal React framework that supports multiple JS environments, including Deno, Cloudflare, and
Node.js.
You can use LlamaIndexTS with Node.js output to enable full Node.js support with React.
```sh
npm install llamaindex
```
```ts
// file: src/actions.ts
"use server";
import { Document, VectorStoreIndex } from "llamaindex";
import { readFile } from "node:fs/promises";
const path = "node_modules/llamaindex/examples/abramov.txt";
const essay = await readFile(path, "utf-8");
// Create Document object with essay
const document = new Document({ text: essay, id_: path });
// Split text and create embeddings. Store them in a VectorStoreIndex
const index = await VectorStoreIndex.fromDocuments([document]);
const queryEngine = index.asQueryEngine();
export async function chatWithAI(question: string): Promise<string> {
const { response } = await queryEngine.query({ query: question });
return response;
}
```
```tsx
// file: src/pages/index.tsx
import { chatWithAI } from "./actions";
export default async function HomePage() {
return (
<div>
<Chat askQuestion={chatWithAI} />
</div>
);
}
```
```tsx
// file: src/components/Chat.tsx
"use client";
export type ChatProps = {
askQuestion: (question: string) => Promise<string>;
};
export const Chat = (props: ChatProps) => {
const [response, setResponse] = useState<string | null>(null);
return (
<section className="border-blue-400 -mx-4 mt-4 rounded border border-dashed p-4">
<h2 className="text-lg font-bold">Chat with AI</h2>
{response ? (
<p className="text-sm text-gray-600 max-w-sm">{response}</p>
) : null}
<form
action={async (formData) => {
const question = formData.get("question") as string | null;
if (question) {
setResponse(await props.askQuestion(question));
}
}}
>
<input
type="text"
name="question"
className="border border-gray-400 rounded-sm px-2 py-0.5 text-sm"
/>
<button className="rounded-sm bg-black px-2 py-0.5 text-sm text-white">
Ask
</button>
</form>
</section>
);
};
```
```shell
waku dev # development mode
waku build # build for production
waku start # start the production server
```
Note that not all the modules are supported in all JS environments because of
lack of the file system, network API,
and incompatibility with the Node.js API by upstream dependencies.
But we are trying to make it more compatible with all the environments.
## What's the next?
As we continue to develop LlamaIndexTS, our focus remains on providing more comprehensive and powerful tools for
creating custom agents.
### Align with the Python `llama-index`
We aim to align LlamaIndexTS with the Python version to ensure API consistency and ease of use for developers familiar
with the Python ecosystem.
### Align with the Web Standard and JS development
Not all python APIs are compatible and easy to use in JavaScript/TypeScript.
We are trying to make the API more compatible with the Web Standard and JavaScript modern development.
### More Agents
Future releases will introduce more agents from the Python Llama-Index and explore APIs tailored to real-world use
cases.
### 🧪 `@llamaindex/tool`
We are exploring innovative ways to create tools for agents. The `@llamaindex/tool` library allows you to transform any
function into a tool for an agent, simplifying the development process and reducing runtime costs.
```ts
export function getWeather(city: string) {
return `The weather in ${city} is sunny.`;
}
// you don't need to worry about the shcema with different llm tools
export function getTemperature(city: string) {
return `The temperature in ${city} is 25°C.`;
}
export function getCurrentCity() {
return "New York";
}
```
These functions can be easily integrated into your applications, such as Next.js:
```ts
"use server";
import { OpenAI } from "openai";
import { getTools } from "@llamaindex/tool";
export async function chat(message: string) {
const openai = new OpenAI();
openai.chat.completions.create({
messages: [
{
role: "user",
content: "What is the weather in the current city?",
},
],
tools: getTools("openai"),
});
}
```
```ts
// next.config.js
const withTool = require("@llamaindex/tool/next");
const config = {
// Your original Next.js config
};
module.exports = withTool(config);
```
The functions are automatically transformed into tools for the agent at compile time, which eliminates any extra runtime
costs. This feature is particularly beneficial when you need to debug or deploy your assistant.
For deploying your local functions into OpenAI, you can use a simple command:
```sh
npm install -g @llamaindex/tool
mkai --tools ./src/index.llama.ts
# Successfully created assistant: asst_XXX
# chat with your assistant by `chatai --assistant asst_XXX`
chatai --assistant asst_XXX
# Open your browser and chat with your assistant
# Running at http://localhost:3000
```
This deployment process simplifies the testing and implementation of your custom tools in a live environment.
As this project is still in its early stages, we continue to explore the best ways to create and integrate tools for
agents. For more information and updates, visit the @llamaindex/tool repository.
This release of LlamaIndexTS v0.3.0 marks a significant step forward in our journey to provide developers with robust,
flexible tools for building advanced agents. We are excited to see how our community utilizes these new capabilities to
create innovative solutions and look forward to continuing to support and enhance LlamaIndexTS in future updates.
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api/
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# Agents
A built-in agent that can take decisions and reasoning based on the tools provided to it.
## OpenAI Agent
import CodeBlock from "@theme/CodeBlock";
import CodeSource from "!raw-loader!../../../../examples/agent/openai";
<CodeBlock language="ts">{CodeSource}</CodeBlock>
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# Gemini Agent
import CodeBlock from "@theme/CodeBlock";
import CodeSourceGemini from "!raw-loader!../../../../examples/gemini/agent.ts";
<CodeBlock language="ts">{CodeSourceGemini}</CodeBlock>
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---
sidebar_position: 2
---
import CodeBlock from "@theme/CodeBlock";
import CodeSource from "!raw-loader!../../../../examples/chatEngine";
# Chat Engine
Chat Engine is a class that allows you to create a chatbot from a retriever. It is a wrapper around a retriever that allows you to chat with it in a conversational manner.
<CodeBlock language="ts">{CodeSource}</CodeBlock>
@@ -1,10 +0,0 @@
---
sidebar_position: 4
---
import CodeBlock from "@theme/CodeBlock";
import CodeSource from "!raw-loader!../../../../examples/storageContext";
# Save/Load an Index
<CodeBlock language="ts">{CodeSource}</CodeBlock>
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---
sidebar_position: 3
---
import CodeBlock from "@theme/CodeBlock";
import CodeSource from "!raw-loader!../../../../examples/summaryIndex";
# Summary Index
<CodeBlock language="ts">{CodeSource}</CodeBlock>
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---
sidebar_position: 2
---
import CodeBlock from "@theme/CodeBlock";
import CodeSource from "!raw-loader!../../../../examples/vectorIndex";
# Vector Index
<CodeBlock language="ts">{CodeSource}</CodeBlock>
@@ -1,2 +0,0 @@
label: Getting Started
position: 1
@@ -1,22 +0,0 @@
---
sidebar_position: 2
---
# Environments
We support Node.JS versions 18, 20 and 22, with experimental support for Deno, Bun and Vercel Edge functions.
## NextJS
If you're using NextJS you'll need to add `withLlamaIndex` to your `next.config.js` file. This will add the necessary configuration for included 3rd-party libraries to your build:
```js
// next.config.js
const withLlamaIndex = require("llamaindex/next");
module.exports = withLlamaIndex({
// your next.js config
});
```
For details, check the latest [withLlamaIndex](https://github.com/run-llama/LlamaIndexTS/blob/main/packages/llamaindex/src/next.ts) implementation.
@@ -1,34 +0,0 @@
---
sidebar_position: 0
---
# Installation and Setup
We support Node.JS versions 18, 20 and 22, with experimental support for Deno, Bun and Vercel Edge functions.
## Installation from NPM
```bash npm2yarn
npm install llamaindex
```
### Environment variables
Our examples use OpenAI by default. You can use [other LLMs](../examples/other_llms) via their APIs; if you would prefer to use local models check out our [local LLM example](../examples/local_llm).
To use OpenAI, you'll need to [get an OpenAI API key](https://platform.openai.com/account/api-keys) and then make it available as an environment variable this way:
```bash
export OPENAI_API_KEY="sk-......" # Replace with your key
```
If you want to have it automatically loaded every time, add it to your `.zshrc/.bashrc`.
**WARNING:** do not check in your OpenAI key into version control. GitHub automatically invalidates OpenAI keys checked in by accident.
## What next?
- The easiest way to started is to [build a full-stack chat app with `create-llama`](starter_tutorial/chatbot).
- Try our other [getting started tutorials](starter_tutorial/retrieval_augmented_generation)
- Learn more about the [high level concepts](concepts) behind how LlamaIndex works
- Check out our [many examples](../examples/more_examples) of LlamaIndex.TS in action
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label: Agents
position: 1
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---
sidebar_position: 0
slug: /
---
# What is LlamaIndex?
LlamaIndex is a framework for building LLM-powered applications. LlamaIndex helps you ingest, structure, and access private or domain-specific data. It's available [as a Python package](https://docs.llamaindex.ai/en/stable/) and in TypeScript (this package). LlamaIndex.TS offers the core features of LlamaIndex for popular runtimes like Node.js (official support), Vercel Edge Functions (experimental), and Deno (experimental).
## 🚀 Why LlamaIndex.TS?
LLMs offer a natural language interface between humans and inferred data. Widely available models come pre-trained on huge amounts of publicly available data, from Wikipedia and mailing lists to textbooks and source code.
Applications built on top of LLMs often require augmenting these models with private or domain-specific data. That data is often distributed across siloed applications and data stores. It's behind APIs, in SQL databases, or trapped in PDFs and slide decks.
LlamaIndex.TS helps you unlock that data and then build powerful applications with it.
## 🦙 What is LlamaIndex for?
LlamaIndex.TS handles several major use cases:
- **Structured Data Extraction**: turning complex, unstructured and semi-structured data into uniform, programmatically accessible formats.
- **Retrieval-Augmented Generation (RAG)**: answering queries across your internal data by providing LLMs with up-to-date, semantically relevant context including Question and Answer systems and chat bots.
- **Autonomous Agents**: building software that is capable of intelligently selecting and using tools to accomplish tasks in an interactive, unsupervised manner.
## 👨‍👩‍👧‍👦 Who is LlamaIndex for?
LlamaIndex targets the "AI Engineer": developers building software in any domain that can be enhanced by LLM-powered functionality, without needing to be an expert in machine learning or natural language processing.
Our high-level API allows beginner users to use LlamaIndex.TS to ingest, index, and query their data in just a few lines of code.
For more complex applications, our lower-level APIs allow advanced users to customize and extend any module—data connectors, indices, retrievers, and query engines, to fit their needs.
## Getting Started
`npm install llamaindex`
Our documentation includes [Installation Instructions](./getting_started/installation.mdx) and a [Starter Tutorial](./getting_started/starter_tutorial/retrieval_augmented_generation.mdx) to build your first application.
Once you're up and running, [High-Level Concepts](./getting_started/concepts.md) has an overview of LlamaIndex's modular architecture. For more hands-on practical examples, look through our Examples section on the sidebar.
## 🗺️ Ecosystem
To download or contribute, find LlamaIndex on:
- Github: https://github.com/run-llama/LlamaIndexTS
- NPM: https://www.npmjs.com/package/llamaindex
## Community
Need help? Have a feature suggestion? Join the LlamaIndex community:
- Twitter: https://twitter.com/llama_index
- Discord https://discord.gg/dGcwcsnxhU
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collapsed: false
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label: "Agents"
position: 10
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---
sidebar_position: 13
---
# ChatEngine
The chat engine is a quick and simple way to chat with the data in your index.
```typescript
const retriever = index.asRetriever();
const chatEngine = new ContextChatEngine({ retriever });
// start chatting
const response = await chatEngine.chat({ message: query });
```
The `chat` function also supports streaming, just add `stream: true` as an option:
```typescript
const stream = await chatEngine.chat({ message: query, stream: true });
for await (const chunk of stream) {
process.stdout.write(chunk.response);
}
```
## Api References
- [ContextChatEngine](../api/classes/ContextChatEngine.md)
- [CondenseQuestionChatEngine](../api/classes/ContextChatEngine.md)
- [SimpleChatEngine](../api/classes/SimpleChatEngine.md)
@@ -1,2 +0,0 @@
label: "Loaders"
position: 1
@@ -1,58 +0,0 @@
import CodeBlock from "@theme/CodeBlock";
import CodeSource from "!raw-loader!../../../../../examples/readers/src/simple-directory-reader";
import CodeSource2 from "!raw-loader!../../../../../examples/readers/src/custom-simple-directory-reader";
# Loader
Before you can start indexing your documents, you need to load them into memory.
All "basic" data loaders can be seen below, mapped to their respective filetypes in `SimpleDirectoryReader`. More loaders are shown in the sidebar on the left.
Additionally the following loaders exist without separate documentation:
- `AssemblyAIReader` transcribes audio using [AssemblyAI](https://www.assemblyai.com/).
- [AudioTranscriptReader](../../api/classes/AudioTranscriptReader.md): loads entire transcript as a single document.
- [AudioTranscriptParagraphsReader](../../api/classes/AudioTranscriptParagraphsReader.md): creates a document per paragraph.
- [AudioTranscriptSentencesReader](../../api/classes/AudioTranscriptSentencesReader.md): creates a document per sentence.
- [AudioSubtitlesReader](../../api/classes/AudioTranscriptParagraphsReader.md): creates a document containing the subtitles of a transcript.
- [NotionReader](../../api/classes/NotionReader.md) loads [Notion](https://www.notion.so/) pages.
- [SimpleMongoReader](../../api/classes/SimpleMongoReader) loads data from a [MongoDB](https://www.mongodb.com/).
Check the [LlamaIndexTS Github](https://github.com/run-llama/LlamaIndexTS) for the most up to date overview of integrations.
## SimpleDirectoryReader
[![Open in StackBlitz](https://developer.stackblitz.com/img/open_in_stackblitz.svg)](https://stackblitz.com/github/run-llama/LlamaIndexTS/tree/main/examples/readers?file=src/simple-directory-reader.ts&title=Simple%20Directory%20Reader)
LlamaIndex.TS supports easy loading of files from folders using the `SimpleDirectoryReader` class.
It is a simple reader that reads all files from a directory and its subdirectories.
<CodeBlock language="ts">{CodeSource}</CodeBlock>
Currently, the following readers are mapped to specific file types:
- [TextFileReader](../../api/classes/TextFileReader.md): `.txt`
- [PDFReader](../../api/classes/PDFReader.md): `.pdf`
- [PapaCSVReader](../../api/classes/PapaCSVReader.md): `.csv`
- [MarkdownReader](../../api/classes/MarkdownReader.md): `.md`
- [DocxReader](../../api/classes/DocxReader.md): `.docx`
- [HTMLReader](../../api/classes/HTMLReader.md): `.htm`, `.html`
- [ImageReader](../../api/classes/ImageReader.md): `.jpg`, `.jpeg`, `.png`, `.gif`
You can modify the reader three different ways:
- `overrideReader` overrides the reader for all file types, including unsupported ones.
- `fileExtToReader` maps a reader to a specific file type. Can override reader for existing file types or add support for new file types.
- `defaultReader` sets a fallback reader for files with unsupported extensions. By default it is `TextFileReader`.
SimpleDirectoryReader supports up to 9 concurrent requests. Use the `numWorkers` option to set the number of concurrent requests. By default it runs in sequential mode, i.e. set to 1.
### Example
<CodeBlock language="ts" showLineNumbers metastring="{8-12,17-21}">
{CodeSource2}
</CodeBlock>
## API Reference
- [SimpleDirectoryReader](../../api/classes/SimpleDirectoryReader.md)
@@ -1 +0,0 @@
label: "LlamaParse"
@@ -1,2 +0,0 @@
label: "Data Stores"
position: 2
@@ -1 +0,0 @@
label: "Chat Stores"
@@ -1,2 +0,0 @@
label: "Document Stores"
position: 2
@@ -1,14 +0,0 @@
# Document Stores
Document stores contain ingested document chunks, i.e. [Node](../../documents_and_nodes/index.md)s.
## Available Document Stores
- [SimpleDocumentStore](../../../api/classes/SimpleDocumentStore.md): A simple in-memory document store with support for [persisting](../index.md#local-storage) data to disk.
- [PostgresDocumentStore](../../../api/classes/PostgresDocumentStore.md): A PostgreSQL document store, see [PostgreSQL Storage](../index.md#postgresql-storage).
Check the [LlamaIndexTS Github](https://github.com/run-llama/LlamaIndexTS) for the most up to date overview of integrations.
## API Reference
- [BaseDocumentStore](../../../api/classes/BaseDocumentStore.md)
@@ -1,56 +0,0 @@
# Storage
Storage in LlamaIndex.TS works automatically once you've configured a
`StorageContext` object.
## Local Storage
You can configure the `persistDir` and attach it to an index.
```typescript
import {
Document,
VectorStoreIndex,
storageContextFromDefaults,
} from "llamaindex";
const storageContext = await storageContextFromDefaults({
persistDir: "./storage",
});
const document = new Document({ text: "Test Text" });
const index = await VectorStoreIndex.fromDocuments([document], {
storageContext,
});
```
## PostgreSQL Storage
You can configure the `schemaName`, `tableName`, `namespace`, and
`connectionString`. If a `connectionString` is not
provided, it will use the environment variables `PGHOST`, `PGUSER`,
`PGPASSWORD`, `PGDATABASE` and `PGPORT`.
```typescript
import {
Document,
VectorStoreIndex,
PostgresDocumentStore,
PostgresIndexStore,
storageContextFromDefaults,
} from "llamaindex";
const storageContext = await storageContextFromDefaults({
docStore: new PostgresDocumentStore(),
indexStore: new PostgresIndexStore(),
});
const document = new Document({ text: "Test Text" });
const index = await VectorStoreIndex.fromDocuments([document], {
storageContext,
});
```
## API Reference
- [StorageContext](../../api/interfaces/StorageContext.md)
@@ -1,2 +0,0 @@
label: "Index Stores"
position: 3
@@ -1,14 +0,0 @@
# Index Stores
Index stores are underlying storage components that contain metadata(i.e. information created when indexing) about the [index](../../data_index.md) itself.
## Available Index Stores
- [SimpleIndexStore](../../../api/classes/SimpleIndexStore.md): A simple in-memory index store with support for [persisting](../index.md#local-storage) data to disk.
- [PostgresIndexStore](../../../api/classes/PostgresIndexStore.md): A PostgreSQL index store, , see [PostgreSQL Storage](../index.md#postgresql-storage).
Check the [LlamaIndexTS Github](https://github.com/run-llama/LlamaIndexTS) for the most up to date overview of integrations.
## API Reference
- [BaseIndexStore](../../../api/classes/BaseIndexStore.md)
@@ -1,2 +0,0 @@
label: "Key-Value Stores"
position: 4
@@ -1,14 +0,0 @@
# Key-Value Stores
Key-Value Stores represent underlying storage components used in [Document Stores](../doc_stores/index.md) and [Index Stores](../index_stores/index.md)
## Available Key-Value Stores
- [SimpleKVStore](../../../api/classes/SimpleKVStore.md): A simple Key-Value store with support of [persisting](../index.md#local-storage) data to disk.
- [PostgresKVStore](../../../api/classes/PostgresKVStore.md): A PostgreSQL Key-Value store, see [PostgreSQL Storage](../index.md#postgresql-storage).
Check the [LlamaIndexTS Github](https://github.com/run-llama/LlamaIndexTS) for the most up to date overview of integrations.
## API Reference
- [BaseKVStore](../../../api/classes/BaseKVStore.md)
@@ -1,2 +0,0 @@
label: "Vector Stores"
position: 1
@@ -1,22 +0,0 @@
# Vector Stores
Vector stores save embedding vectors of your ingested document chunks.
## Available Vector Stores
Available Vector Stores are shown on the sidebar to the left. Additionally the following integrations exist without separate documentation:
- [SimpleVectorStore](../../../api/classes/SimpleVectorStore.md): A simple in-memory vector store with optional [persistance](../index.md#local-storage) to disk.
- [AstraDBVectorStore](../../../api/classes/AstraDBVectorStore.md): A cloud-native, scalable Database-as-a-Service built on Apache Cassandra, see [datastax.com](https://www.datastax.com/products/datastax-astra)
- [ChromaVectorStore](../../../api/classes/ChromaVectorStore.md): An open-source vector database, focused on ease of use and performance, see [trychroma.com](https://www.trychroma.com/)
- [MilvusVectorStore](../../../api/classes/MilvusVectorStore.md): An open-source, high-performance, highly scalable vector database, see [milvus.io](https://milvus.io/)
- [MongoDBAtlasVectorSearch](../../../api/classes/MongoDBAtlasVectorSearch.md): A cloud-based vector search solution for MongoDB, see [mongodb.com](https://www.mongodb.com/products/platform/atlas-vector-search)
- [PGVectorStore](../../../api/classes/PGVectorStore.md): An open-source vector store built on PostgreSQL, see [pgvector Github](https://github.com/pgvector/pgvector)
- [PineconeVectorStore](../../../api/classes/PineconeVectorStore.md): A managed, cloud-native vector database, see [pinecone.io](https://www.pinecone.io/)
- [WeaviateVectorStore](../../../api/classes/WeaviateVectorStore.md): An open-source, ai-native vector database, see [weaviate.io](https://weaviate.io/)
Check the [LlamaIndexTS Github](https://github.com/run-llama/LlamaIndexTS) for the most up to date overview of integrations.
## API Reference
- [VectorStoreBase](../../../api/classes/VectorStoreBase.md)
@@ -1,2 +0,0 @@
label: "Document / Nodes"
position: 0
@@ -1,2 +0,0 @@
label: "Embeddings"
position: 6
@@ -1 +0,0 @@
label: "Available Embeddings"
@@ -1,28 +0,0 @@
# MistralAI
To use MistralAI embeddings, you need to import `MistralAIEmbedding` from `llamaindex`.
```ts
import { MistralAIEmbedding, Settings } from "llamaindex";
// Update Embed Model
Settings.embedModel = new MistralAIEmbedding({
apiKey: "<YOUR_API_KEY>",
});
const document = new Document({ text: essay, id_: "essay" });
const index = await VectorStoreIndex.fromDocuments([document]);
const queryEngine = index.asQueryEngine();
const query = "What is the meaning of life?";
const results = await queryEngine.query({
query,
});
```
## API Reference
- [MistralAIEmbedding](../../../api/classes/MistralAIEmbedding.md)
@@ -1,25 +0,0 @@
# OpenAI
To use OpenAI embeddings, you need to import `OpenAIEmbedding` from `llamaindex`.
```ts
import { OpenAIEmbedding, Settings } from "llamaindex";
Settings.embedModel = new OpenAIEmbedding();
const document = new Document({ text: essay, id_: "essay" });
const index = await VectorStoreIndex.fromDocuments([document]);
const queryEngine = index.asQueryEngine();
const query = "What is the meaning of life?";
const results = await queryEngine.query({
query,
});
```
## API Reference
- [OpenAIEmbedding](../../../api/classes/OpenAIEmbedding.md)
@@ -1,31 +0,0 @@
# Embedding
The embedding model in LlamaIndex is responsible for creating numerical representations of text. By default, LlamaIndex will use the `text-embedding-ada-002` model from OpenAI.
This can be explicitly updated through `Settings`
```typescript
import { OpenAIEmbedding, Settings } from "llamaindex";
Settings.embedModel = new OpenAIEmbedding({
model: "text-embedding-ada-002",
});
```
## Local Embedding
For local embeddings, you can use the [HuggingFace](./available_embeddings/huggingface.md) embedding model.
## Available Embeddings
Most available embeddings are listed in the sidebar on the left.
Additionally the following integrations exist without separate documentation:
- [ClipEmbedding](../../api/classes/ClipEmbedding.md) using `@xenova/transformers`
- [FireworksEmbedding](../../api/classes/FireworksEmbedding.md) see [fireworks.ai](https://fireworks.ai/)
Check the [LlamaIndexTS Github](https://github.com/run-llama/LlamaIndexTS) for the most up to date overview of integrations.
## API Reference
- [OpenAIEmbedding](../../api/classes/OpenAIEmbedding.md)
@@ -1,2 +0,0 @@
label: "Evaluating"
position: 9
@@ -1 +0,0 @@
label: "Modules"
@@ -1,2 +0,0 @@
label: "Ingestion Pipeline"
position: 4
@@ -1,2 +0,0 @@
label: "LLMs"
position: 5
@@ -1 +0,0 @@
label: "Available LLMs"
@@ -1,2 +0,0 @@
label: "Node Postprocessors"
position: 3
@@ -1,2 +0,0 @@
label: "Prompts"
position: 7
@@ -1,2 +0,0 @@
label: "Query Engines"
position: 8
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@@ -1,23 +0,0 @@
---
sidebar_position: 14
---
# Retriever
A retriever in LlamaIndex is what is used to fetch `Node`s from an index using a query string.
- [VectorIndexRetriever](../api/classes/VectorIndexRetriever.md) will fetch the top-k most similar nodes. Ideal for dense retrieval to find most relevant nodes.
- [SummaryIndexRetriever](../api/classes/SummaryIndexRetriever.md) will fetch all nodes no matter the query. Ideal when complete context is necessary, e.g. analyzing large datasets.
- [SummaryIndexLLMRetriever](../api/classes/SummaryIndexLLMRetriever.md) utilizes an LLM to score and filter nodes based on relevancy to the query.
- [KeywordTableLLMRetriever](../api/classes/KeywordTableLLMRetriever.md) uses an LLM to extract keywords from the query and retrieve relevant nodes based on keyword matches.
- [KeywordTableSimpleRetriever](../api/classes/KeywordTableSimpleRetriever.md) uses a basic frequency-based approach to extract keywords and retrieve nodes.
- [KeywordTableRAKERetriever](../api/classes/KeywordTableRAKERetriever.md) uses the RAKE (Rapid Automatic Keyword Extraction) algorithm to extract keywords from the query, focusing on co-occurrence and context for keyword-based retrieval.
```typescript
const retriever = vectorIndex.asRetriever({
similarityTopK: 3,
});
// Fetch nodes!
const nodesWithScore = await retriever.retrieve({ query: "query string" });
```
-168
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@@ -1,168 +0,0 @@
import CodeBlock from "@theme/CodeBlock";
import CodeSource from "!raw-loader!../../../../examples/workflow/joke.ts";
# Workflows
A `Workflow` in LlamaIndexTS is an event-driven abstraction used to chain together several events. Workflows are made up of `steps`, with each step responsible for handling certain event types and emitting new events.
Workflows in LlamaIndexTS work by defining step functions that handle specific event types and emit new events.
When a step function is added to a workflow, you need to specify the input and optionally the output event types (used for validation). The specification of the input events ensures each step only runs when an accepted event is ready.
You can create a `Workflow` to do anything! Build an agent, a RAG flow, an extraction flow, or anything else you want.
## Getting Started
As an illustrative example, let's consider a naive workflow where a joke is generated and then critiqued.
<CodeBlock language="ts">{CodeSource}</CodeBlock>
There's a few moving pieces here, so let's go through this piece by piece.
### Defining Workflow Events
```typescript
export class JokeEvent extends WorkflowEvent<{ joke: string }> {}
```
Events are user-defined classes that extend `WorkflowEvent` and contain arbitrary data provided as template argument. In this case, our workflow relies on a single user-defined event, the `JokeEvent` with a `joke` attribute of type `string`.
### Setting up the Workflow Class
```typescript
const llm = new OpenAI();
...
const jokeFlow = new Workflow({ verbose: true });
```
Our workflow is implemented by initiating the `Workflow` class. For simplicity, we created a `OpenAI` llm instance.
### Workflow Entry Points
```typescript
const generateJoke = async (_context: Context, ev: StartEvent) => {
const prompt = `Write your best joke about ${ev.data.input}.`;
const response = await llm.complete({ prompt });
return new JokeEvent({ joke: response.text });
};
```
Here, we come to the entry-point of our workflow. While events are user-defined, there are two special-case events, the `StartEvent` and the `StopEvent`. Here, the `StartEvent` signifies where to send the initial workflow input.
The `StartEvent` is a bit of a special object since it can hold arbitrary attributes. Here, we accessed the topic with `ev.data.input`.
At this point, you may have noticed that we haven't explicitly told the workflow what events are handled by which steps.
To do so, we use the `addStep` method which adds a step to the workflow. The first argument is the event type that the step will handle, and the second argument is the previously defined step function:
```typescript
jokeFlow.addStep(StartEvent, generateJoke);
```
### Workflow Exit Points
```typescript
const critiqueJoke = async (_context: Context, ev: JokeEvent) => {
const prompt = `Give a thorough critique of the following joke: ${ev.data.joke}`;
const response = await llm.complete({ prompt });
return new StopEvent({ result: response.text });
};
```
Here, we have our second, and last step, in the workflow. We know its the last step because the special `StopEvent` is returned. When the workflow encounters a returned `StopEvent`, it immediately stops the workflow and returns whatever the result was.
In this case, the result is a string, but it could be a map, array, or any other object.
Don't forget to add the step to the workflow:
```typescript
jokeFlow.addStep(JokeEvent, critiqueJoke);
```
### Running the Workflow
```typescript
const result = await jokeFlow.run("pirates");
console.log(result.data.result);
```
Lastly, we run the workflow. The `.run()` method is async, so we use await here to wait for the result.
### Validating Workflows
To tell the workflow what events are produced by each step, you can optionally provide a third argument to `addStep` to specify the output event type:
```typescript
jokeFlow.addStep(StartEvent, generateJoke, { outputs: JokeEvent });
jokeFlow.addStep(JokeEvent, critiqueJoke, { outputs: StopEvent });
```
To validate a workflow, you need to call the `validate` method:
```typescript
jokeFlow.validate();
```
To automatically validate a workflow when you run it, you can set the `validate` flag to `true` at initialization:
```typescript
const jokeFlow = new Workflow({ verbose: true, validate: true });
```
## Working with Global Context/State
Optionally, you can choose to use global context between steps. For example, maybe multiple steps access the original `query` input from the user. You can store this in global context so that every step has access.
```typescript
import { Context } from "@llamaindex/core/workflow";
const query = async (context: Context, ev: MyEvent) => {
// get the query from the context
const query = context.get("query");
// do something with context and event
const val = ...
const result = ...
// store in context
context.set("key", val);
return new StopEvent({ result });
};
```
## Waiting for Multiple Events
The context does more than just hold data, it also provides utilities to buffer and wait for multiple events.
For example, you might have a step that waits for a query and retrieved nodes before synthesizing a response:
```typescript
const synthesize = async (context: Context, ev: QueryEvent | RetrieveEvent) => {
const events = context.collectEvents(ev, [QueryEvent | RetrieveEvent]);
if (!events) {
return;
}
const prompt = events
.map((event) => {
if (event instanceof QueryEvent) {
return `Answer this query using the context provided: ${event.data.query}`;
} else if (event instanceof RetrieveEvent) {
return `Context: ${event.data.context}`;
}
return "";
})
.join("\n");
const response = await llm.complete({ prompt });
return new StopEvent({ result: response.text });
};
```
Using `ctx.collectEvents()` we can buffer and wait for ALL expected events to arrive. This function will only return events (in the requested order) once all events have arrived.
## Manually Triggering Events
Normally, events are triggered by returning another event during a step. However, events can also be manually dispatched using the `ctx.sendEvent(event)` method within a workflow.
## Examples
You can find many useful examples of using workflows in the [examples folder](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/workflow).
@@ -1,2 +0,0 @@
label: Observability
position: 5
-64
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@@ -1,64 +0,0 @@
# Observability
LlamaIndex provides **one-click observability** 🔭 to allow you to build principled LLM applications in a production setting.
A key requirement for principled development of LLM applications over your data (RAG systems, agents) is being able to observe, debug, and evaluate
your system - both as a whole and for each component.
This feature allows you to seamlessly integrate the LlamaIndex library with powerful observability/evaluation tools offered by our partners.
Configure a variable once, and you'll be able to do things like the following:
- View LLM/prompt inputs/outputs
- Ensure that the outputs of any component (LLMs, embeddings) are performing as expected
- View call traces for both indexing and querying
Each provider has similarities and differences. Take a look below for the full set of guides for each one!
- [OpenLLMetry](#openllmetry)
- [Langtrace](#langtrace)
## OpenLLMetry
[OpenLLMetry](https://github.com/traceloop/openllmetry-js) is an open-source project based on OpenTelemetry for tracing and monitoring
LLM applications. It connects to [all major observability platforms](https://www.traceloop.com/docs/openllmetry/integrations/introduction) and installs in minutes.
### Usage Pattern
```bash
npm install @traceloop/node-server-sdk
```
```js
import * as traceloop from "@traceloop/node-server-sdk";
traceloop.initialize({
apiKey: process.env.TRACELOOP_API_KEY,
disableBatch: true,
});
```
## Langtrace
Enhance your observability with Langtrace, a robust open-source tool supports OpenTelemetry and is designed to trace, evaluate, and manage LLM applications seamlessly. Langtrace integrates directly with LlamaIndex, offering detailed, real-time insights into performance metrics such as accuracy, evaluations, and latency.
#### Install
- Self-host or sign-up and generate an API key using [Langtrace](https://www.langtrace.ai) Cloud
```bash
npm install @langtrase/typescript-sdk
```
#### Initialize
```js
import * as Langtrace from "@langtrase/typescript-sdk";
Langtrace.init({ api_key: "<YOUR_API_KEY>" });
```
Features:
- OpenTelemetry compliant, ensuring broad compatibility with observability platforms.
- Provides comprehensive logs and detailed traces of all components.
- Real-time monitoring of accuracy, evaluations, usage, costs, and latency.
- For more configuration options and details, visit [Langtrace Docs](https://docs.langtrace.ai/introduction).
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@@ -1,2 +0,0 @@
label: Recipes
position: 3
-170
View File
@@ -1,170 +0,0 @@
// @ts-check
// Note: type annotations allow type checking and IDEs autocompletion
// eslint-disable-next-line @typescript-eslint/no-require-imports
const renderer = require("prism-react-renderer");
const lightCodeTheme = renderer.themes.github;
const darkCodeTheme = renderer.themes.dracula;
/** @type {import('@docusaurus/types').Config} */
const config = {
title: "LlamaIndex.TS",
tagline: "Unleash the power of LLMs over your data in TypeScript",
favicon: "img/favicon.png",
// Set the production url of your site here
url: "https://ts.llamaindex.ai",
// Set the /<baseUrl>/ pathname under which your site is served
// For GitHub pages deployment, it is often '/<projectName>/'
baseUrl: "/",
// GitHub pages deployment config.
// If you aren't using GitHub pages, you don't need these.
organizationName: "run-llama", // Usually your GitHub org/user name.
projectName: "LlamaIndex.TS", // Usually your repo name.
onBrokenLinks: "warn",
onBrokenMarkdownLinks: "warn",
presets: [
[
"@docusaurus/preset-classic",
/** @type {import('@docusaurus/preset-classic').Options} */
({
docs: {
path: "docs",
routeBasePath: "/",
sidebarPath: require.resolve("./sidebars.js"),
// Please change this to your repo.
// Remove this to remove the "edit this page" links.
// editUrl:
// "https://github.com/facebook/docusaurus/tree/main/packages/create-docusaurus/templates/shared/",
remarkPlugins: [
// eslint-disable-next-line @typescript-eslint/no-require-imports
[require("@docusaurus/remark-plugin-npm2yarn"), { sync: true }],
],
},
blog: {
blogTitle: "LlamaIndexTS blog",
blogDescription: "The official blog of LlamaIndexTS",
postsPerPage: "ALL",
},
gtag: {
trackingID: "G-NB9B8LW9W5",
anonymizeIP: true,
},
}),
],
],
themeConfig:
/** @type {import('@docusaurus/preset-classic').ThemeConfig} */
({
// Replace with your project's social card
image: "img/favicon.png", // TODO change this
announcementBar: {
id: "migrate_to_next",
content:
'We are migrating to Next.js based documentation. Check it out <a href="https://ts.llamaindex.ai/docs/llamaindex">here</a>!',
isCloseable: false,
},
navbar: {
title: "LlamaIndex.TS",
logo: {
alt: "LlamaIndex.TS",
src: "img/favicon.png",
},
items: [
{
type: "docSidebar",
sidebarId: "mySidebar",
position: "left",
label: "Docs",
},
{
type: "localeDropdown",
position: "left",
},
{ to: "blog", label: "Blog", position: "right" },
{
href: "https://github.com/run-llama/LlamaIndexTS",
label: "GitHub",
position: "right",
},
],
},
footer: {
style: "dark",
links: [
{
title: "Docs",
items: [
{
label: "API",
to: "/api",
},
],
},
{
title: "Community",
items: [
{
label: "Discord",
href: "https://discord.com/invite/eN6D2HQ4aX",
},
{
label: "Twitter",
href: "https://twitter.com/LlamaIndex",
},
],
},
{
title: "More",
items: [
{
label: "GitHub",
href: "https://github.com/run-llama/LlamaIndexTS",
},
],
},
],
copyright: `Copyright © ${new Date().getFullYear()} LlamaIndex. Built with Docusaurus.`,
},
prism: {
theme: lightCodeTheme,
darkTheme: darkCodeTheme,
},
algolia: {
// The application ID provided by Algolia
appId: "DYKPM6G4CX",
// Public API key: it is safe to commit it
apiKey: "c4ff3789f20bb72a5d735082aef17719",
indexName: "ts-llamaindex",
// Optional: see doc section below
contextualSearch: true,
},
}),
plugins: [
[
"docusaurus-plugin-typedoc",
{
entryPoints: ["../../packages/llamaindex/src/index.ts"],
tsconfig: "../../tsconfig.json",
readme: "none",
sourceLinkTemplate:
"https://github.com/run-llama/LlamaIndexTS/blob/{gitRevision}/{path}#L{line}",
sidebar: {
position: 6,
},
},
],
],
markdown: {
format: "detect",
},
};
module.exports = config;
-57
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@@ -1,57 +0,0 @@
{
"name": "docs",
"version": "0.0.124",
"private": true,
"scripts": {
"docusaurus": "docusaurus",
"start": "docusaurus start",
"build": "docusaurus build",
"swizzle": "docusaurus swizzle",
"deploy": "docusaurus deploy",
"clear": "docusaurus clear",
"serve": "docusaurus serve",
"write-translations": "docusaurus write-translations",
"write-heading-ids": "docusaurus write-heading-ids",
"typecheck": "tsc"
},
"dependencies": {
"@docusaurus/core": "3.6.1",
"@docusaurus/remark-plugin-npm2yarn": "3.6.1",
"@llamaindex/examples": "workspace:*",
"@mdx-js/react": "^3.1.0",
"clsx": "^2.1.1",
"llamaindex": "workspace:*",
"postcss": "^8.4.49",
"prism-react-renderer": "^2.4.0",
"raw-loader": "^4.0.2",
"react": "^18.3.1",
"react-dom": "18.3.1"
},
"devDependencies": {
"@docusaurus/module-type-aliases": "3.6.1",
"@docusaurus/preset-classic": "3.6.1",
"@docusaurus/theme-classic": "3.6.1",
"@docusaurus/types": "3.6.1",
"@tsconfig/docusaurus": "2.0.3",
"@types/node": "^22.9.0",
"docusaurus-plugin-typedoc": "1.0.5",
"typedoc": "0.26.11",
"typedoc-plugin-markdown": "4.2.10",
"typescript": "^5.6.3"
},
"browserslist": {
"production": [
">0.5%",
"not dead",
"not op_mini all"
],
"development": [
"last 1 chrome version",
"last 1 firefox version",
"last 1 safari version"
]
},
"engines": {
"node": ">=20.0.0"
}
}
-33
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@@ -1,33 +0,0 @@
/**
* Creating a sidebar enables you to:
- create an ordered group of docs
- render a sidebar for each doc of that group
- provide next/previous navigation
The sidebars can be generated from the filesystem, or explicitly defined here.
Create as many sidebars as you want.
*/
// @ts-check
/** @type {import('@docusaurus/plugin-content-docs').SidebarsConfig} */
const sidebars = {
// By default, Docusaurus generates a sidebar from the docs folder structure
mySidebar: [{ type: "autogenerated", dirName: "." }],
// But you can create a sidebar manually
/*
tutorialSidebar: [
'intro',
'hello',
{
type: 'category',
label: 'Tutorial',
items: ['tutorial-basics/create-a-document'],
},
],
*/
};
module.exports = sidebars;
@@ -1,62 +0,0 @@
import clsx from "clsx";
import React from "react";
import styles from "./styles.module.css";
type FeatureItem = {
title: string;
Svg: React.ComponentType<React.ComponentProps<"svg">>;
description: JSX.Element;
};
const FeatureList: FeatureItem[] = [
{
title: "Data Driven",
// eslint-disable-next-line @typescript-eslint/no-require-imports
Svg: require("@site/static/img/undraw_docusaurus_mountain.svg").default,
description: <>LlamaIndex.TS is all about using your data with LLMs.</>,
},
{
title: "Typescript Native",
// eslint-disable-next-line @typescript-eslint/no-require-imports
Svg: require("@site/static/img/undraw_docusaurus_tree.svg").default,
description: <>We Typescript, and so do our users.</>,
},
{
title: "Built by the Community",
// eslint-disable-next-line @typescript-eslint/no-require-imports
Svg: require("@site/static/img/undraw_docusaurus_react.svg").default,
description: (
<>
LlamaIndex.TS is a community project, and we welcome your contributions!
</>
),
},
];
function Feature({ title, Svg, description }: FeatureItem) {
return (
<div className={clsx("col col--4")}>
<div className="text--center">
<Svg className={styles.featureSvg} role="img" />
</div>
<div className="text--center padding-horiz--md">
<h3>{title}</h3>
<p>{description}</p>
</div>
</div>
);
}
export default function HomepageFeatures(): JSX.Element {
return (
<section className={styles.features}>
<div className="container">
<div className="row">
{FeatureList.map((props, idx) => (
<Feature key={idx} {...props} />
))}
</div>
</div>
</section>
);
}
@@ -1,11 +0,0 @@
.features {
display: flex;
align-items: center;
padding: 2rem 0;
width: 100%;
}
.featureSvg {
height: 200px;
width: 200px;
}
-30
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@@ -1,30 +0,0 @@
/**
* Any CSS included here will be global. The classic template
* bundles Infima by default. Infima is a CSS framework designed to
* work well for content-centric websites.
*/
/* You can override the default Infima variables here. */
:root {
--ifm-color-primary: #2e8555;
--ifm-color-primary-dark: #29784c;
--ifm-color-primary-darker: #277148;
--ifm-color-primary-darkest: #205d3b;
--ifm-color-primary-light: #33925d;
--ifm-color-primary-lighter: #359962;
--ifm-color-primary-lightest: #3cad6e;
--ifm-code-font-size: 95%;
--docusaurus-highlighted-code-line-bg: rgba(0, 0, 0, 0.1);
}
/* For readability concerns, you should choose a lighter palette in dark mode. */
[data-theme="dark"] {
--ifm-color-primary: #25c2a0;
--ifm-color-primary-dark: #21af90;
--ifm-color-primary-darker: #1fa588;
--ifm-color-primary-darkest: #1a8870;
--ifm-color-primary-light: #29d5b0;
--ifm-color-primary-lighter: #32d8b4;
--ifm-color-primary-lightest: #4fddbf;
--docusaurus-highlighted-code-line-bg: rgba(0, 0, 0, 0.3);
}
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@@ -1,23 +0,0 @@
/**
* CSS files with the .module.css suffix will be treated as CSS modules
* and scoped locally.
*/
.heroBanner {
padding: 4rem 0;
text-align: center;
position: relative;
overflow: hidden;
}
@media screen and (max-width: 996px) {
.heroBanner {
padding: 2rem;
}
}
.buttons {
display: flex;
align-items: center;
justify-content: center;
}
-7
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@@ -1,7 +0,0 @@
---
title: Markdown page example
---
# Markdown page example
You don't need React to write simple standalone pages.
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<svg width="200" height="200" viewBox="0 0 200 200" xmlns="http://www.w3.org/2000/svg">
<g fill="none" fill-rule="evenodd">
<path fill="#FFF" d="M99 52h84v34H99z" />
<path
d="M23 163c-7.398 0-13.843-4.027-17.303-10A19.886 19.886 0 0 0 3 163c0 11.046 8.954 20 20 20h20v-20H23z"
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<path
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@@ -1,11 +0,0 @@
{
// This file is not used in compilation. It is here just for a nice editor experience.
"extends": "./node_modules/@tsconfig/docusaurus/tsconfig.json",
"compilerOptions": {
"baseUrl": ".",
"composite": true,
"incremental": true,
"outDir": "./lib",
"tsBuildInfoFile": "./lib/.tsbuildinfo"
}
}
-8
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@@ -1,8 +0,0 @@
{
"extends": ["//"],
"tasks": {
"build": {
"outputs": ["build/**", ".docusaurus/**"]
}
}
}
+1
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@@ -29,4 +29,5 @@ next-env.d.ts
# build
/src/content/docs/cloud/api
/src/content/docs/api
./types
+287
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@@ -1,5 +1,292 @@
# @llamaindex/doc
## 0.1.5
### Patch Changes
- Updated dependencies [ad3c7f1]
- @llamaindex/core@0.5.4
- @llamaindex/cloud@3.0.5
- llamaindex@0.9.5
- @llamaindex/node-parser@1.0.4
- @llamaindex/openai@0.1.56
- @llamaindex/readers@2.0.4
## 0.1.4
### Patch Changes
- Updated dependencies [cb256f2]
- Updated dependencies [cb021e7]
- @llamaindex/openai@0.1.55
- @llamaindex/core@0.5.3
- llamaindex@0.9.4
- @llamaindex/cloud@3.0.4
- @llamaindex/node-parser@1.0.3
- @llamaindex/readers@2.0.3
## 0.1.3
### Patch Changes
- Updated dependencies [d952e68]
- @llamaindex/core@0.5.2
- @llamaindex/cloud@3.0.3
- llamaindex@0.9.3
- @llamaindex/node-parser@1.0.2
- @llamaindex/openai@0.1.54
- @llamaindex/readers@2.0.2
## 0.1.2
### Patch Changes
- Updated dependencies [c902fcb]
- Updated dependencies [88d776f]
- @llamaindex/cloud@3.0.2
- llamaindex@0.9.2
## 0.1.1
### Patch Changes
- Updated dependencies [6d37d44]
- llamaindex@0.9.1
- @llamaindex/cloud@3.0.1
- @llamaindex/core@0.5.1
- @llamaindex/node-parser@1.0.1
- @llamaindex/openai@0.1.53
- @llamaindex/readers@2.0.1
- @llamaindex/workflow@0.0.11
## 0.1.0
### Minor Changes
- 6a4a737: Remove re-exports from llamaindex main package
- f4588bc: Remove readers package from llamaindex
### Patch Changes
- c7c0800: fix: fumadoc build fail
- a87efb9: docs: update chat engine docs
- 7bd5d93: docs: update workflow doc
- Updated dependencies [6a4a737]
- Updated dependencies [d924c63]
- Updated dependencies [b490376]
- Updated dependencies [f4588bc]
- llamaindex@0.9.0
- @llamaindex/core@0.5.0
- @llamaindex/cloud@3.0.0
- @llamaindex/node-parser@1.0.0
- @llamaindex/openai@0.1.52
- @llamaindex/readers@2.0.0
## 0.0.41
### Patch Changes
- Updated dependencies [1c908fd]
- @llamaindex/openai@0.1.51
- @llamaindex/node-parser@0.0.24
- @llamaindex/workflow@0.0.10
- @llamaindex/readers@1.0.25
- @llamaindex/cloud@2.0.24
- @llamaindex/core@0.4.23
- llamaindex@0.8.37
## 0.0.40
### Patch Changes
- Updated dependencies [cb608b5]
- @llamaindex/openai@0.1.50
- @llamaindex/node-parser@0.0.23
- @llamaindex/workflow@0.0.9
- @llamaindex/readers@1.0.24
- @llamaindex/cloud@2.0.23
- @llamaindex/core@0.4.22
- llamaindex@0.8.36
## 0.0.39
### Patch Changes
- 6d4d96f: chore: update examples and docs to use unified imports
- Updated dependencies [15563a0]
- @llamaindex/openai@0.1.49
- llamaindex@0.8.35
## 0.0.38
### Patch Changes
- Updated dependencies [9f8ad37]
- Updated dependencies [7265f74]
- llamaindex@0.8.34
- @llamaindex/openai@0.1.48
## 0.0.37
### Patch Changes
- Updated dependencies [2019a04]
- @llamaindex/openai@0.1.47
- llamaindex@0.8.33
## 0.0.36
### Patch Changes
- f02621e: Fix internal links between chapters
- Updated dependencies [34faf48]
- Updated dependencies [4df1fe6]
- Updated dependencies [9456616]
- Updated dependencies [d6c270e]
- Updated dependencies [1892e1c]
- Updated dependencies [1931bbc]
- llamaindex@0.8.32
- @llamaindex/core@0.4.21
- @llamaindex/cloud@2.0.22
- @llamaindex/openai@0.1.46
- @llamaindex/node-parser@0.0.22
- @llamaindex/readers@1.0.23
## 0.0.35
### Patch Changes
- Updated dependencies [5dec9f9]
- Updated dependencies [fd9c829]
- Updated dependencies [d211b7a]
- Updated dependencies [0ebbfc1]
- @llamaindex/cloud@2.0.21
- llamaindex@0.8.31
- @llamaindex/core@0.4.20
- @llamaindex/node-parser@0.0.21
- @llamaindex/openai@0.1.45
- @llamaindex/readers@1.0.22
## 0.0.34
### Patch Changes
- Updated dependencies [012495b]
- @llamaindex/cloud@2.0.20
- llamaindex@0.8.30
## 0.0.33
### Patch Changes
- Updated dependencies [dd596a0]
- llamaindex@0.8.29
## 0.0.32
### Patch Changes
- a9b5b99: feat: build api reference pages for new documentation site
- Updated dependencies [a9b5b99]
- @llamaindex/core@0.4.19
- @llamaindex/readers@1.0.21
- @llamaindex/cloud@2.0.19
- llamaindex@0.8.28
- @llamaindex/node-parser@0.0.20
- @llamaindex/openai@0.1.44
## 0.0.31
### Patch Changes
- Updated dependencies [b504303]
- Updated dependencies [e0f6cc3]
- Updated dependencies [a0e6f57]
- llamaindex@0.8.27
- @llamaindex/core@0.4.18
- @llamaindex/cloud@2.0.18
- @llamaindex/node-parser@0.0.19
- @llamaindex/openai@0.1.43
- @llamaindex/readers@1.0.20
- @llamaindex/workflow@0.0.8
## 0.0.30
### Patch Changes
- Updated dependencies [3d1808b]
- @llamaindex/core@0.4.17
- llamaindex@0.8.26
- @llamaindex/openai@0.1.42
- @llamaindex/cloud@2.0.17
- @llamaindex/node-parser@0.0.18
- @llamaindex/readers@1.0.19
## 0.0.29
### Patch Changes
- Updated dependencies [7e8230b]
- Updated dependencies [8be4589]
- @llamaindex/readers@1.0.18
- @llamaindex/cloud@2.0.16
- @llamaindex/core@0.4.16
- @llamaindex/node-parser@0.0.17
- @llamaindex/openai@0.1.41
- @llamaindex/workflow@0.0.7
- llamaindex@0.8.25
## 0.0.28
### Patch Changes
- fd38a25: Add vercel tool adapter to use query engine tool
## 0.0.27
### Patch Changes
- Updated dependencies [515f2c1]
- llamaindex@0.8.24
## 0.0.26
### Patch Changes
- @llamaindex/cloud@2.0.15
- @llamaindex/core@0.4.15
- llamaindex@0.8.23
- @llamaindex/node-parser@0.0.16
- @llamaindex/openai@0.1.40
- @llamaindex/readers@1.0.17
## 0.0.25
### Patch Changes
- Updated dependencies [819af45]
- llamaindex@0.8.22
- @llamaindex/cloud@2.0.14
- @llamaindex/core@0.4.14
- @llamaindex/node-parser@0.0.15
- @llamaindex/openai@0.1.39
- @llamaindex/readers@1.0.16
## 0.0.24
### Patch Changes
- Updated dependencies [83c3897]
- Updated dependencies [efa2211]
- llamaindex@0.8.21
## 0.0.23
### Patch Changes
- Updated dependencies [02b22da]
- llamaindex@0.8.20
## 0.0.22
### Patch Changes
+21 -15
View File
@@ -1,6 +1,6 @@
{
"name": "@llamaindex/doc",
"version": "0.0.22",
"version": "0.1.5",
"private": true,
"scripts": {
"build": "pnpm run build:docs && next build",
@@ -8,7 +8,7 @@
"start": "next start",
"postdev": "fumadocs-mdx",
"postbuild": "fumadocs-mdx && tsx scripts/post-build.mts",
"build:docs": "node ./scripts/generate-docs.mjs"
"build:docs": "cross-env NODE_OPTIONS=\"--max-old-space-size=8192\" typedoc && node ./scripts/generate-docs.mjs"
},
"dependencies": {
"@icons-pack/react-simple-icons": "^10.1.0",
@@ -28,25 +28,26 @@
"@radix-ui/react-slot": "^1.1.0",
"@radix-ui/react-tooltip": "^1.1.4",
"@vercel/functions": "^1.5.0",
"@scalar/api-client-react": "^1.1.25",
"ai": "^3.4.33",
"class-variance-authority": "^0.7.0",
"clsx": "2.1.1",
"foxact": "^0.2.41",
"framer-motion": "^11.11.17",
"fumadocs-core": "14.4.2",
"fumadocs-docgen": "^1.3.2",
"fumadocs-mdx": "^11.1.1",
"fumadocs-openapi": "^5.7.0",
"fumadocs-twoslash": "^2.0.1",
"fumadocs-typescript": "^3.0.2",
"fumadocs-ui": "14.4.2",
"fumadocs-core": "^14.7.7",
"fumadocs-docgen": "^1.3.7",
"fumadocs-mdx": "^11.5.3",
"fumadocs-openapi": "^5.12.0",
"fumadocs-twoslash": "^2.0.3",
"fumadocs-typescript": "^3.0.3",
"fumadocs-ui": "^14.7.7",
"hast-util-to-jsx-runtime": "^2.3.2",
"llamaindex": "workspace:*",
"lucide-react": "^0.460.0",
"next": "15.0.3",
"next": "15.1.7",
"next-themes": "^0.4.3",
"react": "^18.3.1",
"react-dom": "^18.3.1",
"react": "^19.0.0",
"react-dom": "^19.0.0",
"react-icons": "^5.3.0",
"react-monaco-editor": "^0.56.2",
"react-text-transition": "^3.1.0",
@@ -54,8 +55,8 @@
"rehype-katex": "^7.0.1",
"remark-math": "^6.0.0",
"rimraf": "^6.0.1",
"shiki": "^1.23.1",
"shiki-magic-move": "^0.5.0",
"shiki": "^2.3.2",
"shiki-magic-move": "^1.0.0",
"swr": "^2.2.5",
"tailwind-merge": "^2.5.2",
"tailwindcss-animate": "^1.0.7",
@@ -72,16 +73,21 @@
"@types/react": "^18.3.12",
"@types/react-dom": "^18.3.1",
"autoprefixer": "^10.4.20",
"cross-env": "^7.0.3",
"fast-glob": "^3.3.2",
"gray-matter": "^4.0.3",
"monaco-editor-webpack-plugin": "^7.1.0",
"postcss": "^8.4.49",
"raw-loader": "^4.0.2",
"remark": "^15.0.1",
"remark-gfm": "^4.0.0",
"remark-mdx": "^3.1.0",
"remark-stringify": "^11.0.0",
"tailwindcss": "^3.4.15",
"tsx": "^4.19.2",
"typescript": "^5.6.3"
"typedoc": "0.27.4",
"typedoc-plugin-markdown": "^4.3.1",
"typedoc-plugin-merge-modules": "^6.1.0",
"typescript": "^5.7.2"
}
}
+64
View File
@@ -1,8 +1,12 @@
import * as OpenAPI from "fumadocs-openapi";
import { generateFiles } from "fumadocs-typescript";
import fs from "node:fs";
import * as path from "node:path";
import { fileURLToPath } from "node:url";
import { rimrafSync } from "rimraf";
const out = "./src/content/docs/cloud/api";
const apiRefOut = "./src/content/docs/api";
// clean generated files
rimrafSync(out, {
@@ -20,3 +24,63 @@ void OpenAPI.generateFiles({
output: out,
groupBy: "tag",
});
void generateFiles({
input: ["./src/content/docs/api/**/*.mdx"],
output: (file) => path.resolve(path.dirname(file), path.basename(file)),
transformOutput,
});
function transformOutput(filePath, content) {
const fileName = path.basename(filePath);
let title = fileName.split(".")[0];
let pageContent = content;
if (title === "index") title = "LlamaIndex API Reference";
return `---\ntitle: ${title}\n---\n\n${transformAbsoluteUrl(pageContent, filePath)}`;
}
/**
* Transforms the content by converting relative MDX links to absolute docs API links
* Example: [text](../type-aliases/TaskHandler.mdx) -> [text](/docs/api/type-aliases/TaskHandler)
* [text](BaseChatEngine.mdx) -> [text](/docs/api/classes/BaseChatEngine)
* [text](BaseVectorStore.mdx#constructors) -> [text](/docs/api/classes/BaseVectorStore#constructors)
* [text](TaskStep.mdx) -> [text](/docs/api/type-aliases/TaskStep)
*/
function transformAbsoluteUrl(content, filePath) {
const group = path.dirname(filePath).split(path.sep).pop();
return content.replace(
/\]\(([^)]+)\.mdx([^)]*)\)/g,
(match, slug, anchor) => {
const slugParts = slug.split("/");
const fileName = slugParts[slugParts.length - 1];
const fileGroup = slugParts[slugParts.length - 2] ?? group;
const result = ["/docs/api", fileGroup, fileName, anchor]
.filter(Boolean)
.join("/");
return `](${result})`;
},
);
}
// append meta.json for API page
fs.writeFileSync(
path.resolve(apiRefOut, "meta.json"),
JSON.stringify(
{
title: "API Reference",
description: "LlamaIndex API Reference",
root: true,
pages: [
"index",
"classes",
"enumerations",
"functions",
"interfaces",
"type-aliases",
"variables",
],
},
null,
2,
),
);
+10 -4
View File
@@ -76,15 +76,19 @@ export default function HomePage() {
>
<MagicMove
code={[
`import { OpenAI } from "llamaindex";
`import { OpenAI } from "@llamaindex/openai";
const llm = new OpenAI();
const response = await llm.complete({ prompt: "How are you?" });`,
`import { OpenAI } from "llamaindex";
`import { OpenAI } from "@llamaindex/openai";
const llm = new OpenAI();
const response = await llm.chat({
messages: [{ content: "Tell me a joke.", role: "user" }],
});`,
`import { OpenAI, ChatMemoryBuffer } from "llamaindex";
`import { ChatMemoryBuffer } from "llamaindex";
import { OpenAI } from "@llamaindex/openai";
const llm = new OpenAI({ model: 'gpt4o-turbo' });
const buffer = new ChatMemoryBuffer({
tokenLimit: 128_000,
@@ -94,7 +98,9 @@ const response = await llm.chat({
messages: buffer.getMessages(),
stream: true
});`,
`import { OpenAIAgent, ChatMemoryBuffer } from "llamaindex";
`import { ChatMemoryBuffer } from "llamaindex";
import { OpenAIAgent } from "@llamaindex/openai";
const agent = new OpenAIAgent({
llm,
tools: [...myTools]
+24 -40
View File
@@ -1,54 +1,38 @@
import { baseOptions } from "@/app/layout.config";
import { AITrigger } from "@/components/ai-chat";
import { buttonVariants } from "@/components/ui/button";
import { LEGACY_DOCUMENT_URL } from "@/lib/const";
import { source } from "@/lib/source";
import { cn } from "@/lib/utils";
import "fumadocs-twoslash/twoslash.css";
import { Banner } from "fumadocs-ui/components/banner";
import { DocsLayout } from "fumadocs-ui/layouts/docs";
import { MessageCircle } from "lucide-react";
import type { ReactNode } from "react";
export default function Layout({ children }: { children: ReactNode }) {
return (
<>
<Banner variant="rainbow" id="welcome">
Welcome to the new LlamaIndex.TS documentation! 🎉 If you are looking
for the old documentation
<a
className="underline text-blue-500 ml-1"
target="_blank"
href={LEGACY_DOCUMENT_URL}
>
check it here
</a>
.
</Banner>
<DocsLayout
tree={source.pageTree}
{...baseOptions}
nav={{
...baseOptions.nav,
children: (
<AITrigger
className={cn(
buttonVariants({
variant: "secondary",
size: "xs",
className:
"md:flex-1 px-2 ms-2 gap-1.5 text-fd-muted-foreground rounded-full",
}),
)}
>
<MessageCircle className="size-3" />
Ask LlamaCloud
</AITrigger>
),
}}
>
{children}
</DocsLayout>
</>
<DocsLayout
tree={source.pageTree}
{...baseOptions}
nav={{
...baseOptions.nav,
children: (
<AITrigger
className={cn(
buttonVariants({
variant: "secondary",
size: "xs",
className:
"md:flex-1 px-2 ms-2 gap-1.5 text-fd-muted-foreground rounded-full",
}),
)}
>
<MessageCircle className="size-3" />
Ask LlamaCloud
</AITrigger>
),
}}
>
{children}
</DocsLayout>
);
}
+29
View File
@@ -94,4 +94,33 @@
body {
@apply bg-background text-foreground;
}
/*
* Override default styles for Markdown
*/
.prose
:where(blockquote):not(
:where([class~="not-prose"], [class~="not-prose"] *)
) {
font-style: normal !important;
}
.prose
:where(blockquote p:first-of-type):not(
:where([class~="not-prose"], [class~="not-prose"] *)
):before {
content: none !important;
}
.prose
:where(blockquote p:first-of-type):not(
:where([class~="not-prose"], [class~="not-prose"] *)
):after {
content: none !important;
}
.prose
:where(code):not(:where([class~="not-prose"], [class~="not-prose"] *)) {
@apply text-blue-600 !important;
}
}

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@@ -0,0 +1,12 @@
---
title: Agents
---
A built-in agent that can take decisions and reasoning based on the tools provided to it.
## OpenAI Agent
import { DynamicCodeBlock } from 'fumadocs-ui/components/dynamic-codeblock';
import CodeSource from "!raw-loader!../../../../../../../examples/agent/openai";
<DynamicCodeBlock lang="ts" code={CodeSource} />
@@ -0,0 +1,28 @@
---
title: Gemini Agent
---
import { DynamicCodeBlock } from 'fumadocs-ui/components/dynamic-codeblock';
import CodeSourceGemini from "!raw-loader!../../../../../../../examples/gemini/agent.ts";
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/google
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/google
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/google
```
</Tabs>
## Source
<DynamicCodeBlock lang="ts" code={CodeSourceGemini} />
@@ -0,0 +1,10 @@
---
title: Chat Engine
---
import { DynamicCodeBlock } from 'fumadocs-ui/components/dynamic-codeblock';
import CodeSource from "!raw-loader!../../../../../../../examples/chatEngine";
Chat Engine is a class that allows you to create a chatbot from a retriever. It is a wrapper around a retriever that allows you to chat with it in a conversational manner.
<DynamicCodeBlock lang="ts" code={CodeSource} />
@@ -1,9 +1,7 @@
---
sidebar_position: 14
title: Context-Aware Agent
---
# Context-Aware Agent
The Context-Aware Agent enhances the capabilities of standard LLM agents by incorporating relevant context from a retriever for each query. This allows the agent to provide more informed and specific responses based on the available information.
## Usage
@@ -14,9 +12,8 @@ Here's a simple example of how to use the Context-Aware Agent:
import {
Document,
VectorStoreIndex,
OpenAIContextAwareAgent,
OpenAI,
} from "llamaindex";
import { OpenAI, OpenAIContextAwareAgent } from "@llamaindex/openai";
async function createContextAwareAgent() {
// Create and index some documents
@@ -60,4 +57,3 @@ In this example, the Context-Aware Agent uses the retriever to fetch relevant co
## Available Context-Aware Agents
- `OpenAIContextAwareAgent`: A context-aware agent using OpenAI's models.
- `AnthropicContextAwareAgent`: A context-aware agent using Anthropic's models.
@@ -1,4 +1,8 @@
# Local LLMs
---
title: Local LLMs
---
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
LlamaIndex.TS supports OpenAI and [other remote LLM APIs](other_llms). You can also run a local LLM on your machine!
@@ -22,7 +26,23 @@ The first time you run it will also automatically download and install the model
### Switch the LLM in your code
To tell LlamaIndex to use a local LLM, use the `Settings` object:
To switch the LLM in your code, you first need to make sure to install the package for the Ollama model provider:
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install @llamaindex/ollama
```
```shell tab="yarn"
yarn add @llamaindex/ollama
```
```shell tab="pnpm"
pnpm add @llamaindex/ollama
```
</Tabs>
Then, to tell LlamaIndex to use a local LLM, use the `Settings` object:
```javascript
Settings.llm = new Ollama({
@@ -32,7 +52,25 @@ Settings.llm = new Ollama({
### Use local embeddings
If you're doing retrieval-augmented generation, LlamaIndex.TS will also call out to OpenAI to index and embed your data. To be entirely local, you can use a local embedding model like this:
If you're doing retrieval-augmented generation, LlamaIndex.TS will also call out to OpenAI to index and embed your data. To be entirely local, you can use a local embedding model from Huggingface like this:
First install the Huggingface model provider package:
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install @llamaindex/huggingface
```
```shell tab="yarn"
yarn add @llamaindex/huggingface
```
```shell tab="pnpm"
pnpm add @llamaindex/huggingface
```
</Tabs>
And then set the embedding model in your code:
```javascript
Settings.embedModel = new HuggingFaceEmbedding({
@@ -0,0 +1,15 @@
{
"title": "Examples",
"pages": [
"more_examples",
"chat_engine",
"vector_index",
"summary_index",
"save_load_index",
"context_aware_agent",
"agent",
"agent_gemini",
"local_llm",
"other_llms"
]
}
@@ -1,9 +1,7 @@
---
sidebar_position: 1
title: See all examples
---
# See all examples
Our GitHub repository has a wealth of examples to explore and try out. You can check out our [examples folder](https://github.com/run-llama/LlamaIndexTS/tree/main/examples) to see them all at once, or browse the pages in this section for some selected highlights.
## Check out all examples

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