Release 0.4.8 (#998)

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

.github/workflows/publish.yml

@@ -1,36 +0,0 @@
-name: Publish
-on:
-  push:
-    branches:
-      - main
-
-jobs:
-  publish:
-    runs-on: ubuntu-latest
-
-    permissions:
-      contents: read
-      id-token: write
-
-    steps:
-      - uses: actions/checkout@v4
-      - uses: pnpm/action-setup@v3
-      - name: Setup Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version-file: ".nvmrc"
-          cache: "pnpm"
-      - name: Install dependencies
-        run: pnpm install
-
-      - name: Publish @llamaindex/env
-        run: npx jsr publish
-        working-directory: packages/env
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-
-      - name: Publish @llamaindex/llamaindex
-        run: npx jsr publish --allow-slow-types
-        working-directory: packages/llamaindex
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/release.yml

@@ -58,9 +58,11 @@ jobs:
 
       # Refs: https://github.com/changesets/changesets/issues/421
       - name: Update lock file
+        continue-on-error: true
         run: pnpm install --lockfile-only
 
       - name: Commit lock file
+        continue-on-error: true
         uses: stefanzweifel/git-auto-commit-action@v5
         with:
           commit_message: "chore: update lock file"

.github/workflows/test.yml

@@ -128,6 +128,12 @@ jobs:
         run: pnpm run build
       - name: Copy examples
         run: rsync -rv --exclude=node_modules ./examples ${{ runner.temp }}
+      - name: Pack @llamaindex/cloud
+        run: pnpm pack --pack-destination ${{ runner.temp }}
+        working-directory: packages/cloud
+      - name: Pack @llamaindex/core
+        run: pnpm pack --pack-destination ${{ runner.temp }}
+        working-directory: packages/core
       - name: Pack @llamaindex/env
         run: pnpm pack --pack-destination ${{ runner.temp }}
         working-directory: packages/env

.gitignore

@@ -48,3 +48,6 @@ playwright/.cache/
 
 # intellij
 **/.idea
+
+# generated API
+packages/cloud/src/client

apps/docs/CHANGELOG.md

@@ -1,5 +1,29 @@
 # docs
 
+## 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

apps/docs/docs/examples/agent_gemini.mdx

@@ -0,0 +1,6 @@
+# Gemini Agent
+
+import CodeBlock from "@theme/CodeBlock";
+import CodeSourceGemini from "!raw-loader!../../../../examples/gemini/agent.ts";
+
+<CodeBlock language="ts">{CodeSourceGemini}</CodeBlock>

apps/docs/docs/modules/agent/index.md

@@ -12,12 +12,14 @@ An “agent” is an automated reasoning and decision engine. It takes in a user
 LlamaIndex.TS comes with a few built-in agents, but you can also create your own. The built-in agents include:
 
 - OpenAI Agent
-- Anthropic Agent
+- Anthropic Agent both via Anthropic and Bedrock (in `@llamaIndex/community`)
+- Gemini Agent
 - ReACT Agent
 
 ## Examples
 
 - [OpenAI Agent](../../examples/agent.mdx)
+- [Gemini Agent](../../examples/agent_gemini.mdx)
 
 ## Api References
 

apps/docs/package.json

@@ -1,6 +1,6 @@
 {
   "name": "docs",
-  "version": "0.0.31",
+  "version": "0.0.34",
   "private": true,
   "scripts": {
     "docusaurus": "docusaurus",

examples/README.md

@@ -9,7 +9,7 @@ make sure you have basic knowledge of the [LlamaIndexTS](https://ts.llamaindex.a
 # export your API key
 export OPENAI_API_KEY="sk-..."
 
-npx ts-node ./chatEngine.ts
+npx tsx ./chatEngine.ts
 ```
 
 ## Build your own RAG app

examples/agent/azure_dynamic_session.ts

@@ -0,0 +1,54 @@
+import "dotenv/config";
+
+import {
+  DefaultAzureCredential,
+  getBearerTokenProvider,
+} from "@azure/identity";
+import { AzureDynamicSessionTool, OpenAI, ReActAgent } from "llamaindex";
+
+async function main() {
+  const credential = new DefaultAzureCredential();
+  const azureADTokenProvider = getBearerTokenProvider(
+    credential,
+    "https://cognitiveservices.azure.com/.default",
+  );
+
+  const azure = {
+    azureADTokenProvider,
+    deployment: process.env.AZURE_OPENAI_DEPLOYMENT ?? "gpt-35-turbo",
+  };
+
+  // configure LLM model
+  const llm = new OpenAI({
+    azure,
+  });
+
+  const azureDynamicSession = new AzureDynamicSessionTool();
+
+  // Create an ReActAgent with the azure dynamic session tool
+  const agent = new ReActAgent({
+    llm,
+    tools: [azureDynamicSession],
+    // verbose: true,
+    systemPrompt: `You are a Python interpreter.
+      - You are given tasks to complete and you run python code to solve them.
+      - The python code runs by the python runtime. Every time you call $(interpreter) tool, the python code is executed in a separate cell. It's okay to make multiple calls to $(interpreter).
+      - You can run any python code you want in a secure environment.
+      - For images, return the full URL, not the base64 data.
+      - Return any image content as an HTML tag with the src attribute set to the URL of the image.`,
+  });
+
+  // Chat with the agent
+  const response = await agent.chat({
+    message:
+      "plot a chart of 5 random numbers and save it to /mnt/data/chart.png",
+    stream: false,
+  });
+
+  // Print the response
+  console.log({ response });
+}
+
+void main().then(() => {
+  console.log("Done");
+});

examples/astradb/README.md

@@ -24,7 +24,7 @@ Here are two sample scripts which work well with the sample data in the Astra Po
 
 Loads and queries a simple vectorstore with some documents about Astra DB
 
-run `ts-node astradb/example`
+run `tsx astradb/example`
 
 ## Movie Reviews Example
 
@@ -32,10 +32,10 @@ run `ts-node astradb/example`
 
 This sample loads the same dataset of movie reviews as the Astra Portal sample dataset. (Feel free to load the data in your the Astra Data Explorer to compare)
 
-run `npx ts-node astradb/load`
+run `npx tsx astradb/load`
 
 ### Use RAG to Query the data
 
 Check out your data in the Astra Data Explorer and change the sample query as you see fit.
 
-run `npx ts-node astradb/query`
+run `npx tsx astradb/query`

examples/chromadb/README.md

@@ -6,7 +6,7 @@ Export your OpenAI API Key using `export OPEN_API_KEY=insert your api key here`
 
 If you haven't installed chromadb, run `pip install chromadb`. Start the server using `chroma run`.
 
-Now, open a new terminal window and inside `examples`, run `pnpm dlx ts-node chromadb/test.ts`.
+Now, open a new terminal window and inside `examples`, run `pnpm dlx tsx chromadb/test.ts`.
 
 Here's the output for the input query `Tell me about Godfrey Cheshire's rating of La Sapienza.`:
 

examples/cloud/README.md

@@ -21,7 +21,7 @@ export LLAMA_CLOUD_BASE_URL="https://api.staging.llamaindex.ai"
 This example is using the managed index named `test` from the project `default` to create a chat engine.
 
 ```shell
-pnpx ts-node cloud/chat.ts
+pnpx tsx cloud/chat.ts
 ```
 
 ## Query Engine
@@ -29,7 +29,7 @@ pnpx ts-node cloud/chat.ts
 This example shows how to use the managed index with a query engine.
 
 ```shell
-pnpx ts-node cloud/query.ts
+pnpx tsx cloud/query.ts
 ```
 
 ## Pipeline
@@ -37,5 +37,5 @@ pnpx ts-node cloud/query.ts
 This example shows how to create a managed index with a pipeline.
 
 ```shell
-pnpx ts-node cloud/pipeline.ts
+pnpx tsx cloud/pipeline.ts
 ```

examples/cloud/chat.ts

@@ -6,7 +6,7 @@ import { ContextChatEngine, LlamaCloudIndex } from "llamaindex";
 async function main() {
   const index = new LlamaCloudIndex({
     name: "test",
-    projectName: "default",
+    projectName: "Default",
     baseUrl: process.env.LLAMA_CLOUD_BASE_URL,
     apiKey: process.env.LLAMA_CLOUD_API_KEY,
   });
@@ -19,10 +19,10 @@ async function main() {
   while (true) {
     const query = await rl.question("User: ");
     const stream = await chatEngine.chat({ message: query, stream: true });
-    console.log();
     for await (const chunk of stream) {
       process.stdout.write(chunk.response);
     }
+    process.stdout.write("\n");
   }
 }
 

examples/gemini/agent.ts

@@ -0,0 +1,65 @@
+import { FunctionTool, Gemini, GEMINI_MODEL, LLMAgent } from "llamaindex";
+
+const sumNumbers = FunctionTool.from(
+  ({ a, b }: { a: number; b: number }) => `${a + b}`,
+  {
+    name: "sumNumbers",
+    description: "Use this function to sum two numbers",
+    parameters: {
+      type: "object",
+      properties: {
+        a: {
+          type: "number",
+          description: "The first number",
+        },
+        b: {
+          type: "number",
+          description: "The second number",
+        },
+      },
+      required: ["a", "b"],
+    },
+  },
+);
+
+const divideNumbers = FunctionTool.from(
+  ({ a, b }: { a: number; b: number }) => `${a / b}`,
+  {
+    name: "divideNumbers",
+    description: "Use this function to divide two numbers",
+    parameters: {
+      type: "object",
+      properties: {
+        a: {
+          type: "number",
+          description: "The dividend a to divide",
+        },
+        b: {
+          type: "number",
+          description: "The divisor b to divide by",
+        },
+      },
+      required: ["a", "b"],
+    },
+  },
+);
+
+async function main() {
+  const gemini = new Gemini({
+    model: GEMINI_MODEL.GEMINI_PRO,
+  });
+  const agent = new LLMAgent({
+    llm: gemini,
+    tools: [sumNumbers, divideNumbers],
+  });
+
+  const response = await agent.chat({
+    message: "How much is 5 + 5? then divide by 2",
+  });
+
+  console.log(response.message);
+}
+
+void main().then(() => {
+  console.log("Done");
+});

examples/milvus/README.md

@@ -25,10 +25,10 @@ Here are two sample scripts which work with loading and querying data from a Mil
 
 This sample loads the same dataset of movie reviews as sample dataset. You can install https://github.com/zilliztech/attu to inspect the loaded data.
 
-run `npx ts-node milvus/load`
+run `npx tsx milvus/load`
 
 ## Use RAG to Query the data
 
 Check out your data in Attu and change the sample query as you see fit.
 
-run `npx ts-node milvus/query`
+run `npx tsx milvus/query`

examples/mongodb/README.md

@@ -34,7 +34,7 @@ MONGODB_COLLECTION=tiny_tweets_collection
 You are now ready to import our ready-made data set into Mongo. This is the file `tinytweets.json`, a selection of approximately 1000 tweets from @seldo on Twitter in mid-2019. With your environment set up you can do this by running
 
 ```
-npx ts-node mongodb/1_import.ts
+npx tsx mongodb/1_import.ts
 ```
 
 If you don't want to use tweets, you can replace `json_file` with any other array of JSON objects, but you will need to modify some code later to make sure the correct field gets indexed. There is no LlamaIndex-specific code here; you can load your data into Mongo any way you want to.
@@ -59,7 +59,7 @@ MONGODB_VECTOR_INDEX=tiny_tweets_vector_index
 If the data you're indexing is the tweets we gave you, you're ready to go:
 
 ```bash
-npx ts-node mongodb/2_load_and_index.ts
+npx tsx mongodb/2_load_and_index.ts
 ```
 
 > Note: this script is running a couple of minutes and currently doesn't show any progress.
@@ -112,7 +112,7 @@ Now you're ready to query your data!
 You can do this by running
 
 ```bash
-npx ts-node mongodb/3_query.ts
+npx tsx mongodb/3_query.ts
 ```
 
 This sets up a connection to Atlas just like `2_load_and_index.ts` did, then it creates a [query engine](https://docs.llamaindex.ai/en/stable/understanding/querying/querying.html#getting-started) and runs a query against it.

examples/package.json

@@ -4,6 +4,7 @@
   "version": "0.0.6",
   "dependencies": {
     "@aws-crypto/sha256-js": "^5.2.0",
+    "@azure/identity": "^4.2.1",
     "@datastax/astra-db-ts": "^1.2.1",
     "@notionhq/client": "^2.2.15",
     "@pinecone-database/pinecone": "^2.2.2",
@@ -18,7 +19,6 @@
   },
   "devDependencies": {
     "@types/node": "^20.14.1",
-    "ts-node": "^10.9.2",
     "tsx": "^4.15.6",
     "typescript": "^5.5.2"
   },

examples/pg-vector-store/README.md

@@ -37,7 +37,7 @@ Read and follow the instructions in the README.md file located one directory up
 
 To import documents and save the embedding vectors to your database:
 
-> `npx ts-node pg-vector-store/load-docs.ts data`
+> `npx tsx pg-vector-store/load-docs.ts data`
 
 where data is the directory containing your input files. Using the `data` directory in the example above will read all of the files in that directory using the LlamaIndexTS default readers for each file type.
 
@@ -45,6 +45,6 @@ where data is the directory containing your input files. Using the `data` direct
 
 To query using the resulting vector store:
 
-> `npx ts-node pg-vector-store/query.ts`
+> `npx tsx pg-vector-store/query.ts`
 
 The script will prompt for a question, then process and present the answer using the PGVectorStore data and your OpenAI API key. It will continue to prompt until you enter `q`, `quit` or `exit` as the next query.

examples/pinecone-vector-store/README.md

@@ -19,7 +19,7 @@ Read and follow the instructions in the README.md file located one directory up
 
 To import documents and save the embedding vectors to your database:
 
-> `npx ts-node pinecone-vector-store/load-docs.ts data`
+> `npx tsx pinecone-vector-store/load-docs.ts data`
 
 where data is the directory containing your input files. Using the _data_ directory in the example above will read all of the files in that directory using the llamaindexTS default readers for each file type.
 
@@ -29,6 +29,6 @@ where data is the directory containing your input files. Using the _data_ direct
 
 To query using the resulting vector store:
 
-> `npx ts-node pinecone-vector-store/query.ts`
+> `npx tsx pinecone-vector-store/query.ts`
 
 The script will prompt for a question, then process and present the answer using the PineconeVectorStore data and your OpenAI API key. It will continue to prompt until you enter `q`, `quit` or `exit` as the next query.

examples/qdrantdb/README.md

@@ -8,4 +8,4 @@ Add your OpenAI API Key into a file called `.env` in the parent folder of this d
 OPEN_API_KEY=sk-you-key
 ```
 
-Now, open a new terminal window and inside `examples`, run `npx ts-node qdrantdb/preFilters.ts`.
+Now, open a new terminal window and inside `examples`, run `npx tsx qdrantdb/preFilters.ts`.

examples/readers/src/custom-simple-directory-reader.ts

@@ -7,7 +7,7 @@ import {
 import { TextFileReader } from "llamaindex/readers/TextFileReader";
 
 class ZipReader extends FileReader {
-  loadDataAsContent(fileContent: Buffer): Promise<Document<Metadata>[]> {
+  loadDataAsContent(fileContent: Uint8Array): Promise<Document<Metadata>[]> {
     throw new Error("Implement me");
   }
 }

package.json

@@ -12,10 +12,9 @@
     "e2e": "turbo run e2e",
     "test": "turbo run test",
     "type-check": "tsc -b --diagnostics",
-    "release": "pnpm run check-minor-version && pnpm run build:release && changeset publish",
-    "release-snapshot": "pnpm run check-minor-version && pnpm run build:release && changeset publish --tag snapshot",
-    "check-minor-version": "node ./scripts/check-minor-version.mjs",
-    "new-version": "changeset version && pnpm run check-minor-version && pnpm format:write && pnpm run build:release",
+    "release": "pnpm run build:release && changeset publish",
+    "release-snapshot": "pnpm run build:release && changeset publish --tag snapshot",
+    "new-version": "changeset version && pnpm format:write && pnpm run build:release",
     "new-snapshot": "pnpm run build:release && changeset version --snapshot"
   },
   "devDependencies": {
@@ -24,14 +23,14 @@
     "eslint": "^8.57.0",
     "eslint-config-next": "^14.2.4",
     "eslint-config-prettier": "^9.1.0",
-    "eslint-config-turbo": "^1.13.4",
+    "eslint-config-turbo": "^2.0.5",
     "eslint-plugin-react": "7.34.1",
     "husky": "^9.0.11",
     "lint-staged": "^15.2.7",
     "madge": "^7.0.0",
     "prettier": "^3.3.2",
     "prettier-plugin-organize-imports": "^3.2.4",
-    "turbo": "^1.13.4",
+    "turbo": "^2.0.5",
     "typescript": "^5.5.2"
   },
   "packageManager": "pnpm@9.4.0",
@@ -40,6 +39,9 @@
       "trim": "1.0.1",
       "@babel/traverse": "7.23.2",
       "protobufjs": "7.2.6"
+    },
+    "patchedDependencies": {
+      "bunchee@5.2.1": "patches/bunchee@5.2.1.patch"
     }
   },
   "lint-staged": {

packages/autotool/examples/02_nextjs/CHANGELOG.md

@@ -1,5 +1,32 @@
 # @llamaindex/autotool-02-next-example
 
+## 0.1.18
+
+### Patch Changes
+
+- Updated dependencies [83ebdfb]
+  - llamaindex@0.4.8
+  - @llamaindex/autotool@1.0.0
+
+## 0.1.17
+
+### Patch Changes
+
+- Updated dependencies [41fe871]
+- Updated dependencies [321c39d]
+- Updated dependencies [f7f1af0]
+  - llamaindex@0.4.7
+  - @llamaindex/autotool@1.0.0
+
+## 0.1.16
+
+### Patch Changes
+
+- Updated dependencies [1feb23b]
+- Updated dependencies [08c55ec]
+  - llamaindex@0.4.6
+  - @llamaindex/autotool@1.0.0
+
 ## 0.1.15
 
 ### Patch Changes

packages/autotool/examples/02_nextjs/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/autotool-02-next-example",
   "private": true,
-  "version": "0.1.15",
+  "version": "0.1.18",
   "scripts": {
     "dev": "next dev",
     "build": "next build",

packages/autotool/package.json

@@ -51,7 +51,7 @@
     "unplugin": "^1.10.1"
   },
   "peerDependencies": {
-    "llamaindex": "^0.4.5",
+    "llamaindex": "^0.4.8",
     "openai": "^4",
     "typescript": "^4"
   },

packages/cloud/CHANGELOG.md

@@ -0,0 +1,7 @@
+# @llamaindex/cloud
+
+## 0.1.1
+
+### Patch Changes
+
+- 321c39d: fix: generate api as class

packages/cloud/README.md

@@ -0,0 +1,18 @@
+# @llamaindex/cloud
+
+> LlamaCloud is a new generation of managed parsing, ingestion, and retrieval services, designed to bring production-grade context-augmentation to your LLM and RAG applications.
+
+## Usage
+
+```ts
+import { OpenAPI } from "@llamaindex/cloud/api";
+OpenAPI.TOKEN = "YOUR_API_KEY";
+OpenAPI.BASE = "https://api.cloud.llamaindex.ai/";
+// ...
+```
+
+For more information, see the [API documentation](https://docs.cloud.llamaindex.ai/).
+
+## License
+
+MIT

packages/cloud/openapi-ts.config.ts

@@ -0,0 +1,18 @@
+import { defineConfig } from "@hey-api/openapi-ts";
+
+export default defineConfig({
+  // you can download this file to get the latest version of the OpenAPI document
+  // @link https://api.cloud.llamaindex.ai/api/openapi.json
+  input: "./openapi.json",
+  output: {
+    path: "./src/client",
+    format: "prettier",
+    lint: "eslint",
+  },
+  services: {
+    asClass: true,
+  },
+  types: {
+    enums: "javascript",
+  },
+});

packages/cloud/package.json

@@ -0,0 +1,40 @@
+{
+  "name": "@llamaindex/cloud",
+  "version": "0.1.1",
+  "type": "module",
+  "license": "MIT",
+  "scripts": {
+    "generate": "pnpm dlx @hey-api/openapi-ts",
+    "build": "pnpm run generate && bunchee"
+  },
+  "files": [
+    "openapi.json",
+    "dist"
+  ],
+  "exports": {
+    "./openapi.json": "./openapi.json",
+    "./api": {
+      "require": {
+        "types": "./dist/api.d.cts",
+        "default": "./dist/api.cjs"
+      },
+      "import": {
+        "types": "./dist/api.d.ts",
+        "default": "./dist/api.js"
+      },
+      "default": {
+        "types": "./dist/api.d.ts",
+        "default": "./dist/api.js"
+      }
+    }
+  },
+  "repository": {
+    "type": "git",
+    "url": "https://github.com/himself65/LlamaIndexTS.git",
+    "directory": "packages/cloud"
+  },
+  "devDependencies": {
+    "@hey-api/openapi-ts": "^0.48.0",
+    "bunchee": "^5.2.1"
+  }
+}

packages/cloud/src/api.ts

@@ -0,0 +1 @@
+export * from "./client";

packages/cloud/tsconfig.json

@@ -0,0 +1,15 @@
+{
+  "extends": "../../tsconfig.json",
+  "compilerOptions": {
+    "rootDir": "./src",
+    "outDir": "./dist/type",
+    "tsBuildInfoFile": "./dist/.tsbuildinfo",
+    "emitDeclarationOnly": true,
+    "moduleResolution": "Bundler",
+    "skipLibCheck": true,
+    "strict": true,
+    "lib": ["DOM", "ESNext"]
+  },
+  "include": ["./src"],
+  "exclude": ["node_modules"]
+}

packages/community/CHANGELOG.md

@@ -1,5 +1,29 @@
 # @llamaindex/community
 
+## 0.0.12
+
+### Patch Changes
+
+- Updated dependencies [83ebdfb]
+  - llamaindex@0.4.8
+
+## 0.0.11
+
+### Patch Changes
+
+- Updated dependencies [41fe871]
+- Updated dependencies [321c39d]
+- Updated dependencies [f7f1af0]
+  - llamaindex@0.4.7
+
+## 0.0.10
+
+### Patch Changes
+
+- Updated dependencies [1feb23b]
+- Updated dependencies [08c55ec]
+  - llamaindex@0.4.6
+
 ## 0.0.9
 
 ### Patch Changes

packages/community/jsr.json

@@ -1,8 +0,0 @@
-{
-  "name": "@llamaindex/community",
-  "version": "0.0.5",
-  "exports": {
-    ".": "./src/index.ts",
-    "./type": "./src/type.ts"
-  }
-}

packages/community/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/community",
   "description": "Community package for LlamaIndexTS",
-  "version": "0.0.9",
+  "version": "0.0.12",
   "type": "module",
   "types": "dist/type/index.d.ts",
   "main": "dist/cjs/index.js",

packages/core/CHANGELOG.md

@@ -0,0 +1,9 @@
+# @llamaindex/core
+
+## 0.0.2
+
+### Patch Changes
+
+- f10b41d: fix: release files
+- Updated dependencies [41fe871]
+  - @llamaindex/env@0.1.7

packages/core/package.json

@@ -0,0 +1,70 @@
+{
+  "name": "@llamaindex/core",
+  "type": "module",
+  "version": "0.0.2",
+  "description": "LlamaIndex Core Module",
+  "exports": {
+    "./decorator": {
+      "require": {
+        "types": "./dist/decorator/index.d.cts",
+        "default": "./dist/decorator/index.cjs"
+      },
+      "import": {
+        "types": "./dist/decorator/index.d.ts",
+        "default": "./dist/decorator/index.js"
+      },
+      "default": {
+        "types": "./dist/decorator/index.d.ts",
+        "default": "./dist/decorator/index.js"
+      }
+    },
+    "./global": {
+      "require": {
+        "types": "./dist/global/index.d.cts",
+        "default": "./dist/global/index.cjs"
+      },
+      "import": {
+        "types": "./dist/global/index.d.ts",
+        "default": "./dist/global/index.js"
+      },
+      "default": {
+        "types": "./dist/global/index.d.ts",
+        "default": "./dist/global/index.js"
+      }
+    },
+    "./schema": {
+      "require": {
+        "types": "./dist/schema/index.d.cts",
+        "default": "./dist/schema/index.cjs"
+      },
+      "import": {
+        "types": "./dist/schema/index.d.ts",
+        "default": "./dist/schema/index.js"
+      },
+      "default": {
+        "types": "./dist/schema/index.d.ts",
+        "default": "./dist/schema/index.js"
+      }
+    }
+  },
+  "files": [
+    "dist"
+  ],
+  "scripts": {
+    "dev": "bunchee --watch",
+    "build": "bunchee"
+  },
+  "repository": {
+    "type": "git",
+    "directory": "packages/core",
+    "url": "https://github.com/himself65/LlamaIndexTS.git"
+  },
+  "devDependencies": {
+    "bunchee": "^5.2.1"
+  },
+  "dependencies": {
+    "@llamaindex/env": "workspace:*",
+    "@types/node": "^20.14.9",
+    "zod": "^3.23.8"
+  }
+}

packages/core/src/decorator/index.ts

@@ -1,11 +1,11 @@
 import { getEnv } from "@llamaindex/env";
-import type { BaseNode } from "../../Node.js";
-import { getChunkSize } from "../settings/chunk-size.js";
+import { Settings } from "../global";
+import type { BaseNode } from "../schema/node";
 
 const emitOnce = false;
 
 export function chunkSizeCheck<
-  This extends BaseNode,
+  This extends { id_: string },
   Args extends any[],
   Return,
 >(
@@ -17,7 +17,7 @@ export function chunkSizeCheck<
 ) {
   return function (this: This, ...args: Args) {
     const content = contentGetter.call(this, ...args);
-    const chunkSize = getChunkSize();
+    const chunkSize = Settings.chunkSize;
     const enableChunkSizeCheck = getEnv("ENABLE_CHUNK_SIZE_CHECK") === "true";
     if (
       enableChunkSizeCheck &&
@@ -25,7 +25,7 @@ export function chunkSizeCheck<
       content.length > chunkSize
     ) {
       console.warn(
-        `Node (${this.id_}) is larger than chunk size: ${content.length}`,
+        `Node (${this.id_}) is larger than chunk size: ${content.length} > ${chunkSize}`,
       );
       if (!emitOnce) {
         console.warn(

packages/core/src/global/index.ts

@@ -0,0 +1 @@
+export { Settings } from "./settings";

packages/core/src/global/settings.ts

@@ -0,0 +1,17 @@
+import {
+  getChunkSize,
+  setChunkSize,
+  withChunkSize,
+} from "./settings/chunk-size";
+
+export const Settings = {
+  get chunkSize(): number | undefined {
+    return getChunkSize();
+  },
+  set chunkSize(chunkSize: number | undefined) {
+    setChunkSize(chunkSize);
+  },
+  withChunkSize<Result>(chunkSize: number, fn: () => Result): Result {
+    return withChunkSize(chunkSize, fn);
+  },
+};

packages/core/src/global/settings/chunk-size.ts

@@ -1,14 +1,16 @@
 import { AsyncLocalStorage } from "@llamaindex/env";
 
 const chunkSizeAsyncLocalStorage = new AsyncLocalStorage<number | undefined>();
-const globalChunkSize: number | null = null;
+let globalChunkSize: number | null = null;
 
 export function getChunkSize(): number | undefined {
   return globalChunkSize ?? chunkSizeAsyncLocalStorage.getStore();
 }
 
 export function setChunkSize(chunkSize: number | undefined) {
-  chunkSizeAsyncLocalStorage.enterWith(chunkSize);
+  if (chunkSize !== undefined) {
+    globalChunkSize = chunkSize;
+  }
 }
 
 export function withChunkSize<Result>(

packages/core/src/index.ts

@@ -0,0 +1 @@
+export * from "./schema";

packages/core/src/schema/index.ts

@@ -0,0 +1,2 @@
+export * from "./node";
+export * from "./zod";

packages/core/src/schema/node.ts

@@ -0,0 +1,452 @@
+import { createSHA256, path, randomUUID } from "@llamaindex/env";
+import { chunkSizeCheck, lazyInitHash } from "../decorator";
+
+export enum NodeRelationship {
+  SOURCE = "SOURCE",
+  PREVIOUS = "PREVIOUS",
+  NEXT = "NEXT",
+  PARENT = "PARENT",
+  CHILD = "CHILD",
+}
+
+export enum ObjectType {
+  TEXT = "TEXT",
+  IMAGE = "IMAGE",
+  INDEX = "INDEX",
+  DOCUMENT = "DOCUMENT",
+  IMAGE_DOCUMENT = "IMAGE_DOCUMENT",
+}
+
+export enum MetadataMode {
+  ALL = "ALL",
+  EMBED = "EMBED",
+  LLM = "LLM",
+  NONE = "NONE",
+}
+
+export type Metadata = Record<string, any>;
+
+export interface RelatedNodeInfo<T extends Metadata = Metadata> {
+  nodeId: string;
+  nodeType?: ObjectType;
+  metadata: T;
+  hash?: string;
+}
+
+export type RelatedNodeType<T extends Metadata = Metadata> =
+  | RelatedNodeInfo<T>
+  | RelatedNodeInfo<T>[];
+
+export type BaseNodeParams<T extends Metadata = Metadata> = {
+  id_?: string;
+  metadata?: T;
+  excludedEmbedMetadataKeys?: string[];
+  excludedLlmMetadataKeys?: string[];
+  relationships?: Partial<Record<NodeRelationship, RelatedNodeType<T>>>;
+  hash?: string;
+  embedding?: number[];
+};
+
+/**
+ * Generic abstract class for retrievable nodes
+ */
+export abstract class BaseNode<T extends Metadata = Metadata> {
+  /**
+   * The unique ID of the Node/Document. The trailing underscore is here
+   * to avoid collisions with the id keyword in Python.
+   *
+   * Set to a UUID by default.
+   */
+  id_: string;
+  embedding?: number[];
+
+  // Metadata fields
+  metadata: T;
+  excludedEmbedMetadataKeys: string[];
+  excludedLlmMetadataKeys: string[];
+  relationships: Partial<Record<NodeRelationship, RelatedNodeType<T>>>;
+
+  @lazyInitHash
+  accessor hash: string = "";
+
+  protected constructor(init?: BaseNodeParams<T>) {
+    const {
+      id_,
+      metadata,
+      excludedEmbedMetadataKeys,
+      excludedLlmMetadataKeys,
+      relationships,
+      hash,
+      embedding,
+    } = init || {};
+    this.id_ = id_ ?? randomUUID();
+    this.metadata = metadata ?? ({} as T);
+    this.excludedEmbedMetadataKeys = excludedEmbedMetadataKeys ?? [];
+    this.excludedLlmMetadataKeys = excludedLlmMetadataKeys ?? [];
+    this.relationships = relationships ?? {};
+    this.embedding = embedding;
+  }
+
+  abstract get type(): ObjectType;
+
+  abstract getContent(metadataMode: MetadataMode): string;
+
+  abstract getMetadataStr(metadataMode: MetadataMode): string;
+
+  // todo: set value as a generic type
+  abstract setContent(value: unknown): void;
+
+  get sourceNode(): RelatedNodeInfo<T> | undefined {
+    const relationship = this.relationships[NodeRelationship.SOURCE];
+
+    if (Array.isArray(relationship)) {
+      throw new Error("Source object must be a single RelatedNodeInfo object");
+    }
+
+    return relationship;
+  }
+
+  get prevNode(): RelatedNodeInfo<T> | undefined {
+    const relationship = this.relationships[NodeRelationship.PREVIOUS];
+
+    if (Array.isArray(relationship)) {
+      throw new Error(
+        "Previous object must be a single RelatedNodeInfo object",
+      );
+    }
+
+    return relationship;
+  }
+
+  get nextNode(): RelatedNodeInfo<T> | undefined {
+    const relationship = this.relationships[NodeRelationship.NEXT];
+
+    if (Array.isArray(relationship)) {
+      throw new Error("Next object must be a single RelatedNodeInfo object");
+    }
+
+    return relationship;
+  }
+
+  get parentNode(): RelatedNodeInfo<T> | undefined {
+    const relationship = this.relationships[NodeRelationship.PARENT];
+
+    if (Array.isArray(relationship)) {
+      throw new Error("Parent object must be a single RelatedNodeInfo object");
+    }
+
+    return relationship;
+  }
+
+  get childNodes(): RelatedNodeInfo<T>[] | undefined {
+    const relationship = this.relationships[NodeRelationship.CHILD];
+
+    if (!Array.isArray(relationship)) {
+      throw new Error(
+        "Child object must be a an array of RelatedNodeInfo objects",
+      );
+    }
+
+    return relationship;
+  }
+
+  abstract generateHash(): string;
+
+  getEmbedding(): number[] {
+    if (this.embedding === undefined) {
+      throw new Error("Embedding not set");
+    }
+
+    return this.embedding;
+  }
+
+  asRelatedNodeInfo(): RelatedNodeInfo<T> {
+    return {
+      nodeId: this.id_,
+      metadata: this.metadata,
+      hash: this.hash,
+    };
+  }
+
+  /**
+   * Called by built in JSON.stringify (see https://javascript.info/json)
+   * Properties are read-only as they are not deep-cloned (not necessary for stringification).
+   * @see toMutableJSON - use to return a mutable JSON instead
+   */
+  toJSON(): Record<string, any> {
+    return {
+      ...this,
+      type: this.type,
+      // hash is an accessor property, so it's not included in the rest operator
+      hash: this.hash,
+    };
+  }
+
+  clone(): BaseNode {
+    return jsonToNode(this.toMutableJSON()) as BaseNode;
+  }
+
+  /**
+   * Converts the object to a JSON representation.
+   * Properties can be safely modified as a deep clone of the properties are created.
+   * @return {Record<string, any>} - The JSON representation of the object.
+   */
+  toMutableJSON(): Record<string, any> {
+    return structuredClone(this.toJSON());
+  }
+}
+
+export type TextNodeParams<T extends Metadata = Metadata> =
+  BaseNodeParams<T> & {
+    text?: string;
+    textTemplate?: string;
+    startCharIdx?: number;
+    endCharIdx?: number;
+    metadataSeparator?: string;
+  };
+
+/**
+ * TextNode is the default node type for text. Most common node type in LlamaIndex.TS
+ */
+export class TextNode<T extends Metadata = Metadata> extends BaseNode<T> {
+  text: string;
+  textTemplate: string;
+
+  startCharIdx?: number;
+  endCharIdx?: number;
+  // textTemplate: NOTE write your own formatter if needed
+  // metadataTemplate: NOTE write your own formatter if needed
+  metadataSeparator: string;
+
+  constructor(init: TextNodeParams<T> = {}) {
+    super(init);
+    const { text, textTemplate, startCharIdx, endCharIdx, metadataSeparator } =
+      init;
+    this.text = text ?? "";
+    this.textTemplate = textTemplate ?? "";
+    if (startCharIdx) {
+      this.startCharIdx = startCharIdx;
+    }
+    if (endCharIdx) {
+      this.endCharIdx = endCharIdx;
+    }
+    this.metadataSeparator = metadataSeparator ?? "\n";
+  }
+
+  /**
+   * Generate a hash of the text node.
+   * The ID is not part of the hash as it can change independent of content.
+   * @returns
+   */
+  generateHash() {
+    const hashFunction = createSHA256();
+    hashFunction.update(`type=${this.type}`);
+    hashFunction.update(
+      `startCharIdx=${this.startCharIdx} endCharIdx=${this.endCharIdx}`,
+    );
+    hashFunction.update(this.getContent(MetadataMode.ALL));
+    return hashFunction.digest();
+  }
+
+  get type() {
+    return ObjectType.TEXT;
+  }
+
+  @chunkSizeCheck
+  getContent(metadataMode: MetadataMode = MetadataMode.NONE): string {
+    const metadataStr = this.getMetadataStr(metadataMode).trim();
+    return `${metadataStr}\n\n${this.text}`.trim();
+  }
+
+  getMetadataStr(metadataMode: MetadataMode): string {
+    if (metadataMode === MetadataMode.NONE) {
+      return "";
+    }
+
+    const usableMetadataKeys = new Set(Object.keys(this.metadata).sort());
+    if (metadataMode === MetadataMode.LLM) {
+      for (const key of this.excludedLlmMetadataKeys) {
+        usableMetadataKeys.delete(key);
+      }
+    } else if (metadataMode === MetadataMode.EMBED) {
+      for (const key of this.excludedEmbedMetadataKeys) {
+        usableMetadataKeys.delete(key);
+      }
+    }
+
+    return [...usableMetadataKeys]
+      .map((key) => `${key}: ${this.metadata[key]}`)
+      .join(this.metadataSeparator);
+  }
+
+  setContent(value: string) {
+    this.text = value;
+    this.hash = this.generateHash();
+  }
+
+  getNodeInfo() {
+    return { start: this.startCharIdx, end: this.endCharIdx };
+  }
+
+  getText() {
+    return this.getContent(MetadataMode.NONE);
+  }
+}
+
+export type IndexNodeParams<T extends Metadata = Metadata> =
+  TextNodeParams<T> & {
+    indexId: string;
+  };
+
+export class IndexNode<T extends Metadata = Metadata> extends TextNode<T> {
+  indexId: string;
+
+  constructor(init?: IndexNodeParams<T>) {
+    super(init);
+    const { indexId } = init || {};
+    this.indexId = indexId ?? "";
+  }
+
+  get type() {
+    return ObjectType.INDEX;
+  }
+}
+
+/**
+ * A document is just a special text node with a docId.
+ */
+export class Document<T extends Metadata = Metadata> extends TextNode<T> {
+  constructor(init?: TextNodeParams<T>) {
+    super(init);
+  }
+
+  get type() {
+    return ObjectType.DOCUMENT;
+  }
+}
+
+export function jsonToNode(json: any, type?: ObjectType) {
+  if (!json.type && !type) {
+    throw new Error("Node type not found");
+  }
+  const nodeType = type || json.type;
+
+  switch (nodeType) {
+    case ObjectType.TEXT:
+      return new TextNode(json);
+    case ObjectType.INDEX:
+      return new IndexNode(json);
+    case ObjectType.DOCUMENT:
+      return new Document(json);
+    case ObjectType.IMAGE_DOCUMENT:
+      return new ImageDocument(json);
+    default:
+      throw new Error(`Invalid node type: ${nodeType}`);
+  }
+}
+
+export type ImageType = string | Blob | URL;
+
+export type ImageNodeParams<T extends Metadata = Metadata> =
+  TextNodeParams<T> & {
+    image: ImageType;
+  };
+
+export class ImageNode<T extends Metadata = Metadata> extends TextNode<T> {
+  image: ImageType; // image as blob
+
+  constructor(init: ImageNodeParams<T>) {
+    super(init);
+    const { image } = init;
+    this.image = image;
+  }
+
+  get type() {
+    return ObjectType.IMAGE;
+  }
+
+  getUrl(): URL {
+    // id_ stores the relative path, convert it to the URL of the file
+    const absPath = path.resolve(this.id_);
+    return new URL(`file://${absPath}`);
+  }
+
+  // Calculates the image part of the hash
+  private generateImageHash() {
+    const hashFunction = createSHA256();
+
+    if (this.image instanceof Blob) {
+      // TODO: ideally we should use the blob's content to calculate the hash:
+      // hashFunction.update(new Uint8Array(await this.image.arrayBuffer()));
+      // as this is async, we're using the node's ID for the time being
+      hashFunction.update(this.id_);
+    } else if (this.image instanceof URL) {
+      hashFunction.update(this.image.toString());
+    } else if (typeof this.image === "string") {
+      hashFunction.update(this.image);
+    } else {
+      throw new Error(
+        `Unknown image type: ${typeof this.image}. Can't calculate hash`,
+      );
+    }
+
+    return hashFunction.digest();
+  }
+
+  generateHash() {
+    const hashFunction = createSHA256();
+    // calculates hash based on hash of both components (image and text)
+    hashFunction.update(super.generateHash());
+    hashFunction.update(this.generateImageHash());
+
+    return hashFunction.digest();
+  }
+}
+
+export class ImageDocument<T extends Metadata = Metadata> extends ImageNode<T> {
+  constructor(init: ImageNodeParams<T>) {
+    super(init);
+  }
+
+  get type() {
+    return ObjectType.IMAGE_DOCUMENT;
+  }
+}
+
+/**
+ * A node with a similarity score
+ */
+export interface NodeWithScore<T extends Metadata = Metadata> {
+  node: BaseNode<T>;
+  score?: number;
+}
+
+export enum ModalityType {
+  TEXT = "TEXT",
+  IMAGE = "IMAGE",
+}
+
+type NodesByType = {
+  [P in ModalityType]?: BaseNode[];
+};
+
+export function splitNodesByType(nodes: BaseNode[]): NodesByType {
+  const result: NodesByType = {};
+
+  for (const node of nodes) {
+    let type: ModalityType;
+    if (node instanceof ImageNode) {
+      type = ModalityType.IMAGE;
+    } else if (node instanceof TextNode) {
+      type = ModalityType.TEXT;
+    } else {
+      throw new Error(`Unknown node type: ${node.type}`);
+    }
+    if (type in result) {
+      result[type]?.push(node);
+    } else {
+      result[type] = [node];
+    }
+  }
+  return result;
+}

packages/core/src/schema/zod.ts

@@ -0,0 +1,16 @@
+import { z } from "zod";
+
+export const toolMetadataSchema = z.object({
+  description: z.string(),
+  name: z.string(),
+  parameters: z.record(z.any()),
+});
+
+export const baseToolSchema = z.object({
+  call: z.optional(z.function()),
+  metadata: toolMetadataSchema,
+});
+
+export const baseToolWithCallSchema = baseToolSchema.extend({
+  call: z.function(),
+});

packages/core/tests/decorator.test.ts

@@ -0,0 +1,25 @@
+import { Settings } from "@llamaindex/core/global";
+import { TextNode } from "@llamaindex/core/schema";
+import { env } from "process";
+import { afterEach, describe, expect, test, vi } from "vitest";
+describe("chunkSizeCheck", () => {
+  afterEach(() => {
+    Settings.chunkSize = undefined;
+    env.ENABLE_CHUNK_SIZE_CHECK = undefined;
+  });
+
+  test("should warn when content is larger than chunk size", () => {
+    env.ENABLE_CHUNK_SIZE_CHECK = "true";
+
+    let message = "";
+    const consoleMock = vi
+      .spyOn(console, "warn")
+      .mockImplementation((msg) => (message += msg + "\n"));
+
+    Settings.chunkSize = 0;
+    const node = new TextNode();
+    expect(message).toEqual("");
+    node.setContent("a".repeat(1024));
+    expect(message).toContain("is larger than chunk size");
+  });
+});

packages/core/tests/package.json

@@ -0,0 +1,12 @@
+{
+  "name": "@llamaindex/core-tests",
+  "private": true,
+  "type": "module",
+  "scripts": {
+    "test": "vitest"
+  },
+  "devDependencies": {
+    "@llamaindex/core": "workspace:*",
+    "vitest": "^1.6.0"
+  }
+}

packages/core/tests/schema-node.test.ts

@@ -1,4 +1,4 @@
-import { Document, TextNode } from "llamaindex/Node";
+import { Document, TextNode } from "@llamaindex/core/schema";
 import { beforeEach, describe, expect, test } from "vitest";
 
 describe("Document", () => {
@@ -50,7 +50,6 @@ describe("TextNode", () => {
       `
       {
         "embedding": undefined,
-        "endCharIdx": undefined,
         "excludedEmbedMetadataKeys": [],
         "excludedLlmMetadataKeys": [],
         "hash": "Z6SWgFPlalaeblMGQGw0KS3qKgmZdEWXKfzEp/K+QN0=",
@@ -62,7 +61,6 @@ describe("TextNode", () => {
         "metadataSeparator": "
       ",
         "relationships": {},
-        "startCharIdx": undefined,
         "text": "Hello World",
         "textTemplate": "",
         "type": "TEXT",

packages/core/tests/tsconfig.json

@@ -0,0 +1,18 @@
+{
+  "extends": "../../../tsconfig.json",
+  "compilerOptions": {
+    "outDir": "./lib",
+    "module": "node16",
+    "moduleResolution": "node16",
+    "target": "ESNext"
+  },
+  "include": ["./**/*.ts"],
+  "references": [
+    {
+      "path": "../tsconfig.json"
+    },
+    {
+      "path": "../../env/tsconfig.json"
+    }
+  ]
+}

packages/core/tsconfig.json

@@ -0,0 +1,15 @@
+{
+  "extends": "../../tsconfig.json",
+  "compilerOptions": {
+    "rootDir": "./src",
+    "outDir": "./dist/type",
+    "tsBuildInfoFile": "./dist/.tsbuildinfo",
+    "emitDeclarationOnly": true,
+    "moduleResolution": "Bundler",
+    "skipLibCheck": true,
+    "strict": true,
+    "types": ["node"]
+  },
+  "include": ["./src"],
+  "exclude": ["node_modules"]
+}

packages/env/CHANGELOG.md

@@ -1,5 +1,11 @@
 # @llamaindex/env
 
+## 0.1.7
+
+### Patch Changes
+
+- 41fe871: Add support for azure dynamic session tool
+
 ## 0.1.6
 
 ### Patch Changes

packages/env/jsr.json

@@ -1,10 +0,0 @@
-{
-  "name": "@llamaindex/env",
-  "version": "0.1.6",
-  "exports": {
-    ".": "./src/index.edge-light.ts"
-  },
-  "publish": {
-    "include": ["LICENSE", "README.md", "src/**/*", "jsr.json"]
-  }
-}

packages/env/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/env",
   "description": "environment wrapper, supports all JS environment including node, deno, bun, edge runtime, and cloudflare worker",
-  "version": "0.1.6",
+  "version": "0.1.7",
   "type": "module",
   "types": "dist/type/index.d.ts",
   "main": "dist/cjs/index.js",

packages/env/src/fs/node.ts

@@ -5,6 +5,7 @@
  *
  * @module
  */
+import { createWriteStream } from "node:fs";
 import fs from "node:fs/promises";
 
-export { fs };
+export { createWriteStream, fs };

packages/env/src/index.ts

@@ -15,12 +15,14 @@ import { ok } from "node:assert";
 import { createHash, randomUUID } from "node:crypto";
 import { EOL } from "node:os";
 import path from "node:path";
+import { Readable } from "node:stream";
 import {
   ReadableStream,
   TransformStream,
   WritableStream,
 } from "node:stream/web";
-import { fs } from "./fs/node.js";
+import { fileURLToPath } from "node:url";
+import { createWriteStream, fs } from "./fs/node.js";
 import type { SHA256 } from "./polyfill.js";
 
 export function createSHA256(): SHA256 {
@@ -38,11 +40,14 @@ export function createSHA256(): SHA256 {
 export { Tokenizers, tokenizers, type Tokenizer } from "./tokenizers/node.js";
 export { AsyncLocalStorage, CustomEvent, getEnv, setEnvs } from "./utils.js";
 export {
+  createWriteStream,
   EOL,
+  fileURLToPath,
   fs,
   ok,
   path,
   randomUUID,
+  Readable,
   ReadableStream,
   TransformStream,
   WritableStream,

packages/experimental/CHANGELOG.md

@@ -1,5 +1,29 @@
 # @llamaindex/experimental
 
+## 0.0.43
+
+### Patch Changes
+
+- Updated dependencies [83ebdfb]
+  - llamaindex@0.4.8
+
+## 0.0.42
+
+### Patch Changes
+
+- Updated dependencies [41fe871]
+- Updated dependencies [321c39d]
+- Updated dependencies [f7f1af0]
+  - llamaindex@0.4.7
+
+## 0.0.41
+
+### Patch Changes
+
+- Updated dependencies [1feb23b]
+- Updated dependencies [08c55ec]
+  - llamaindex@0.4.6
+
 ## 0.0.40
 
 ### Patch Changes

packages/experimental/jsr.json

@@ -1,8 +0,0 @@
-{
-  "name": "@llamaindex/experimental",
-  "version": "0.0.5",
-  "exports": {
-    ".": "./src/index.ts",
-    "./type": "./src/type.ts"
-  }
-}

packages/experimental/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/experimental",
   "description": "Experimental package for LlamaIndexTS",
-  "version": "0.0.40",
+  "version": "0.0.43",
   "type": "module",
   "types": "dist/type/index.d.ts",
   "main": "dist/cjs/index.js",

packages/llamaindex/CHANGELOG.md

@@ -1,5 +1,32 @@
 # llamaindex
 
+## 0.4.8
+
+### Patch Changes
+
+- 83ebdfb: fix: next.js build error
+
+## 0.4.7
+
+### Patch Changes
+
+- 41fe871: Add support for azure dynamic session tool
+- 321c39d: fix: generate api as class
+- f7f1af0: fix: throw error when no pipeline found
+- Updated dependencies [41fe871]
+- Updated dependencies [f10b41d]
+- Updated dependencies [321c39d]
+  - @llamaindex/env@0.1.7
+  - @llamaindex/core@0.0.2
+  - @llamaindex/cloud@0.1.1
+
+## 0.4.6
+
+### Patch Changes
+
+- 1feb23b: feat: Gemini tool calling for agent support
+- 08c55ec: Add metadata to PDFs and use Uint8Array for readers content
+
 ## 0.4.5
 
 ### Patch Changes

packages/llamaindex/e2e/examples/cloudflare-worker-agent/CHANGELOG.md

@@ -1,5 +1,29 @@
 # @llamaindex/cloudflare-worker-agent-test
 
+## 0.0.27
+
+### Patch Changes
+
+- Updated dependencies [83ebdfb]
+  - llamaindex@0.4.8
+
+## 0.0.26
+
+### Patch Changes
+
+- Updated dependencies [41fe871]
+- Updated dependencies [321c39d]
+- Updated dependencies [f7f1af0]
+  - llamaindex@0.4.7
+
+## 0.0.25
+
+### Patch Changes
+
+- Updated dependencies [1feb23b]
+- Updated dependencies [08c55ec]
+  - llamaindex@0.4.6
+
 ## 0.0.24
 
 ### Patch Changes

packages/llamaindex/e2e/examples/cloudflare-worker-agent/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/cloudflare-worker-agent-test",
-  "version": "0.0.24",
+  "version": "0.0.27",
   "type": "module",
   "private": true,
   "scripts": {

packages/llamaindex/e2e/examples/nextjs-agent/CHANGELOG.md

@@ -1,5 +1,29 @@
 # @llamaindex/next-agent-test
 
+## 0.1.27
+
+### Patch Changes
+
+- Updated dependencies [83ebdfb]
+  - llamaindex@0.4.8
+
+## 0.1.26
+
+### Patch Changes
+
+- Updated dependencies [41fe871]
+- Updated dependencies [321c39d]
+- Updated dependencies [f7f1af0]
+  - llamaindex@0.4.7
+
+## 0.1.25
+
+### Patch Changes
+
+- Updated dependencies [1feb23b]
+- Updated dependencies [08c55ec]
+  - llamaindex@0.4.6
+
 ## 0.1.24
 
 ### Patch Changes

packages/llamaindex/e2e/examples/nextjs-agent/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/next-agent-test",
-  "version": "0.1.24",
+  "version": "0.1.27",
   "private": true,
   "scripts": {
     "dev": "next dev",

packages/llamaindex/e2e/examples/nextjs-edge-runtime/CHANGELOG.md

@@ -1,5 +1,29 @@
 # test-edge-runtime
 
+## 0.1.26
+
+### Patch Changes
+
+- Updated dependencies [83ebdfb]
+  - llamaindex@0.4.8
+
+## 0.1.25
+
+### Patch Changes
+
+- Updated dependencies [41fe871]
+- Updated dependencies [321c39d]
+- Updated dependencies [f7f1af0]
+  - llamaindex@0.4.7
+
+## 0.1.24
+
+### Patch Changes
+
+- Updated dependencies [1feb23b]
+- Updated dependencies [08c55ec]
+  - llamaindex@0.4.6
+
 ## 0.1.23
 
 ### Patch Changes

packages/llamaindex/e2e/examples/nextjs-edge-runtime/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/nextjs-edge-runtime-test",
-  "version": "0.1.23",
+  "version": "0.1.26",
   "private": true,
   "scripts": {
     "dev": "next dev",

packages/llamaindex/e2e/examples/nextjs-node-runtime/CHANGELOG.md

@@ -1,5 +1,30 @@
 # @llamaindex/next-node-runtime
 
+## 0.0.8
+
+### Patch Changes
+
+- 83ebdfb: fix: next.js build error
+- Updated dependencies [83ebdfb]
+  - llamaindex@0.4.8
+
+## 0.0.7
+
+### Patch Changes
+
+- Updated dependencies [41fe871]
+- Updated dependencies [321c39d]
+- Updated dependencies [f7f1af0]
+  - llamaindex@0.4.7
+
+## 0.0.6
+
+### Patch Changes
+
+- Updated dependencies [1feb23b]
+- Updated dependencies [08c55ec]
+  - llamaindex@0.4.6
+
 ## 0.0.5
 
 ### Patch Changes

packages/llamaindex/e2e/examples/nextjs-node-runtime/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/next-node-runtime-test",
-  "version": "0.0.5",
+  "version": "0.0.8",
   "private": true,
   "scripts": {
     "dev": "next dev",

packages/llamaindex/e2e/examples/nextjs-node-runtime/src/actions/openai.ts

@@ -0,0 +1,68 @@
+"use server";
+import {
+  OpenAI,
+  OpenAIAgent,
+  QueryEngineTool,
+  Settings,
+  VectorStoreIndex,
+} from "llamaindex";
+import { HuggingFaceEmbedding } from "llamaindex/embeddings/HuggingFaceEmbedding";
+import { SimpleDirectoryReader } from "llamaindex/readers/SimpleDirectoryReader";
+
+Settings.llm = new OpenAI({
+  // eslint-disable-next-line turbo/no-undeclared-env-vars
+  apiKey: process.env.NEXT_PUBLIC_OPENAI_KEY ?? "FAKE_KEY_TO_PASS_TESTS",
+  model: "gpt-4o",
+});
+Settings.embedModel = new HuggingFaceEmbedding({
+  modelType: "BAAI/bge-small-en-v1.5",
+  quantized: false,
+});
+Settings.callbackManager.on("llm-tool-call", (event) => {
+  console.log(event.detail.payload);
+});
+Settings.callbackManager.on("llm-tool-result", (event) => {
+  console.log(event.detail.payload);
+});
+
+export async function getOpenAIModelRequest(query: string) {
+  try {
+    const currentDir = __dirname;
+
+    // load our data and create a query engine
+    const reader = new SimpleDirectoryReader();
+    const documents = await reader.loadData(currentDir);
+    const index = await VectorStoreIndex.fromDocuments(documents);
+    const retriever = index.asRetriever({
+      similarityTopK: 10,
+    });
+    const queryEngine = index.asQueryEngine({
+      retriever,
+    });
+
+    // define the query engine as a tool
+    const tools = [
+      new QueryEngineTool({
+        queryEngine: queryEngine,
+        metadata: {
+          name: "deployment_details_per_env",
+          description: `This tool can answer detailed questions about deployments happened in various environments.`,
+        },
+      }),
+    ];
+    // create the agent
+    const agent = new OpenAIAgent({ tools });
+
+    const { response } = await agent.chat({
+      message: query,
+    });
+    return {
+      message: response,
+    };
+  } catch (err) {
+    console.error(err);
+    return {
+      errors: "Error Calling OpenAI Model",
+    };
+  }
+}

packages/llamaindex/e2e/examples/nextjs-node-runtime/src/app/api/openai/route.ts

@@ -0,0 +1,10 @@
+import { getOpenAIModelRequest } from "@/actions/openai";
+import { NextRequest, NextResponse } from "next/server";
+
+// POST /api/openai
+export async function POST(request: NextRequest) {
+  const body = await request.json();
+  const content = await getOpenAIModelRequest(body.query);
+
+  return NextResponse.json(content, { status: 200 });
+}

packages/llamaindex/e2e/examples/waku-query-engine/CHANGELOG.md

@@ -1,5 +1,29 @@
 # @llamaindex/waku-query-engine-test
 
+## 0.0.27
+
+### Patch Changes
+
+- Updated dependencies [83ebdfb]
+  - llamaindex@0.4.8
+
+## 0.0.26
+
+### Patch Changes
+
+- Updated dependencies [41fe871]
+- Updated dependencies [321c39d]
+- Updated dependencies [f7f1af0]
+  - llamaindex@0.4.7
+
+## 0.0.25
+
+### Patch Changes
+
+- Updated dependencies [1feb23b]
+- Updated dependencies [08c55ec]
+  - llamaindex@0.4.6
+
 ## 0.0.24
 
 ### Patch Changes

packages/llamaindex/e2e/examples/waku-query-engine/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/waku-query-engine-test",
-  "version": "0.0.24",
+  "version": "0.0.27",
   "type": "module",
   "private": true,
   "scripts": {

packages/llamaindex/jsr.json

@@ -1,11 +0,0 @@
-{
-  "name": "@llamaindex/llamaindex",
-  "version": "0.4.5",
-  "exports": "./src/index.ts",
-  "imports": {
-    "@llamaindex/env": "jsr:@llamaindex/env@0.1.6"
-  },
-  "publish": {
-    "include": ["LICENSE", "README.md", "src/**/*", "jsr.json"]
-  }
-}

packages/llamaindex/package.json

@@ -1,6 +1,6 @@
 {
   "name": "llamaindex",
-  "version": "0.4.5",
+  "version": "0.4.8",
   "license": "MIT",
   "type": "module",
   "keywords": [
@@ -22,17 +22,20 @@
   "dependencies": {
     "@anthropic-ai/sdk": "^0.21.1",
     "@aws-crypto/sha256-js": "^5.2.0",
+    "@azure/identity": "^4.2.1",
     "@datastax/astra-db-ts": "^1.2.1",
     "@google-cloud/vertexai": "^1.2.0",
     "@google/generative-ai": "^0.12.0",
     "@grpc/grpc-js": "^1.10.8",
     "@huggingface/inference": "^2.7.0",
-    "@llamaindex/cloud": "0.0.7",
+    "@llamaindex/cloud": "workspace:*",
+    "@llamaindex/core": "workspace:*",
     "@llamaindex/env": "workspace:*",
     "@mistralai/mistralai": "^0.4.0",
     "@pinecone-database/pinecone": "^2.2.2",
     "@qdrant/js-client-rest": "^1.9.0",
-    "@types/lodash": "^4.17.5",
+    "@types/lodash": "^4.17.4",
+    "@types/node": "^20.14.5",
     "@types/papaparse": "^5.3.14",
     "@types/pg": "^8.11.6",
     "@xenova/transformers": "^2.17.2",
@@ -60,7 +63,8 @@
     "tiktoken": "^1.0.15",
     "unpdf": "^0.10.1",
     "wikipedia": "^2.1.2",
-    "wink-nlp": "^2.3.0"
+    "wink-nlp": "^2.3.0",
+    "zod": "^3.23.8"
   },
   "peerDependencies": {
     "@notionhq/client": "^2.2.15"
@@ -148,7 +152,7 @@
   "repository": {
     "type": "git",
     "url": "https://github.com/run-llama/LlamaIndexTS.git",
-    "directory": "packages/core"
+    "directory": "packages/llamaindex"
   },
   "scripts": {
     "lint": "eslint .",

packages/llamaindex/src/EngineResponse.ts

@@ -1,4 +1,4 @@
-import type { NodeWithScore } from "./Node.js";
+import type { NodeWithScore } from "@llamaindex/core/schema";
 import type {
   ChatMessage,
   ChatResponse,

packages/llamaindex/src/Node.ts

@@ -1,448 +1,6 @@
-import { createSHA256, path, randomUUID } from "@llamaindex/env";
-import { chunkSizeCheck, lazyInitHash } from "./internal/decorator/node.js";
+console.warn(
+  'Package "llamaindex/Node" is deprecated, and will be removed in the next major release.',
+);
+console.warn("Please import from the @llamaindex/core/schema package instead.");
 
-export enum NodeRelationship {
-  SOURCE = "SOURCE",
-  PREVIOUS = "PREVIOUS",
-  NEXT = "NEXT",
-  PARENT = "PARENT",
-  CHILD = "CHILD",
-}
-
-export enum ObjectType {
-  TEXT = "TEXT",
-  IMAGE = "IMAGE",
-  INDEX = "INDEX",
-  DOCUMENT = "DOCUMENT",
-  IMAGE_DOCUMENT = "IMAGE_DOCUMENT",
-}
-
-export enum MetadataMode {
-  ALL = "ALL",
-  EMBED = "EMBED",
-  LLM = "LLM",
-  NONE = "NONE",
-}
-
-export type Metadata = Record<string, any>;
-
-export interface RelatedNodeInfo<T extends Metadata = Metadata> {
-  nodeId: string;
-  nodeType?: ObjectType;
-  metadata: T;
-  hash?: string;
-}
-
-export type RelatedNodeType<T extends Metadata = Metadata> =
-  | RelatedNodeInfo<T>
-  | RelatedNodeInfo<T>[];
-
-export type BaseNodeParams<T extends Metadata = Metadata> = {
-  id_?: string;
-  metadata?: T;
-  excludedEmbedMetadataKeys?: string[];
-  excludedLlmMetadataKeys?: string[];
-  relationships?: Partial<Record<NodeRelationship, RelatedNodeType<T>>>;
-  hash?: string;
-  embedding?: number[];
-};
-
-/**
- * Generic abstract class for retrievable nodes
- */
-export abstract class BaseNode<T extends Metadata = Metadata> {
-  /**
-   * The unique ID of the Node/Document. The trailing underscore is here
-   * to avoid collisions with the id keyword in Python.
-   *
-   * Set to a UUID by default.
-   */
-  id_: string;
-  embedding?: number[];
-
-  // Metadata fields
-  metadata: T;
-  excludedEmbedMetadataKeys: string[];
-  excludedLlmMetadataKeys: string[];
-  relationships: Partial<Record<NodeRelationship, RelatedNodeType<T>>>;
-
-  @lazyInitHash
-  accessor hash: string = "";
-
-  protected constructor(init?: BaseNodeParams<T>) {
-    const {
-      id_,
-      metadata,
-      excludedEmbedMetadataKeys,
-      excludedLlmMetadataKeys,
-      relationships,
-      hash,
-      embedding,
-    } = init || {};
-    this.id_ = id_ ?? randomUUID();
-    this.metadata = metadata ?? ({} as T);
-    this.excludedEmbedMetadataKeys = excludedEmbedMetadataKeys ?? [];
-    this.excludedLlmMetadataKeys = excludedLlmMetadataKeys ?? [];
-    this.relationships = relationships ?? {};
-    this.embedding = embedding;
-  }
-
-  abstract get type(): ObjectType;
-
-  abstract getContent(metadataMode: MetadataMode): string;
-  abstract getMetadataStr(metadataMode: MetadataMode): string;
-  // todo: set value as a generic type
-  abstract setContent(value: unknown): void;
-
-  get sourceNode(): RelatedNodeInfo<T> | undefined {
-    const relationship = this.relationships[NodeRelationship.SOURCE];
-
-    if (Array.isArray(relationship)) {
-      throw new Error("Source object must be a single RelatedNodeInfo object");
-    }
-
-    return relationship;
-  }
-
-  get prevNode(): RelatedNodeInfo<T> | undefined {
-    const relationship = this.relationships[NodeRelationship.PREVIOUS];
-
-    if (Array.isArray(relationship)) {
-      throw new Error(
-        "Previous object must be a single RelatedNodeInfo object",
-      );
-    }
-
-    return relationship;
-  }
-
-  get nextNode(): RelatedNodeInfo<T> | undefined {
-    const relationship = this.relationships[NodeRelationship.NEXT];
-
-    if (Array.isArray(relationship)) {
-      throw new Error("Next object must be a single RelatedNodeInfo object");
-    }
-
-    return relationship;
-  }
-
-  get parentNode(): RelatedNodeInfo<T> | undefined {
-    const relationship = this.relationships[NodeRelationship.PARENT];
-
-    if (Array.isArray(relationship)) {
-      throw new Error("Parent object must be a single RelatedNodeInfo object");
-    }
-
-    return relationship;
-  }
-
-  get childNodes(): RelatedNodeInfo<T>[] | undefined {
-    const relationship = this.relationships[NodeRelationship.CHILD];
-
-    if (!Array.isArray(relationship)) {
-      throw new Error(
-        "Child object must be a an array of RelatedNodeInfo objects",
-      );
-    }
-
-    return relationship;
-  }
-
-  abstract generateHash(): string;
-
-  getEmbedding(): number[] {
-    if (this.embedding === undefined) {
-      throw new Error("Embedding not set");
-    }
-
-    return this.embedding;
-  }
-
-  asRelatedNodeInfo(): RelatedNodeInfo<T> {
-    return {
-      nodeId: this.id_,
-      metadata: this.metadata,
-      hash: this.hash,
-    };
-  }
-
-  /**
-   * Called by built in JSON.stringify (see https://javascript.info/json)
-   * Properties are read-only as they are not deep-cloned (not necessary for stringification).
-   * @see toMutableJSON - use to return a mutable JSON instead
-   */
-  toJSON(): Record<string, any> {
-    return {
-      ...this,
-      type: this.type,
-      // hash is an accessor property, so it's not included in the rest operator
-      hash: this.hash,
-    };
-  }
-
-  clone(): BaseNode {
-    return jsonToNode(this.toMutableJSON()) as BaseNode;
-  }
-
-  /**
-   * Converts the object to a JSON representation.
-   * Properties can be safely modified as a deep clone of the properties are created.
-   * @return {Record<string, any>} - The JSON representation of the object.
-   */
-  toMutableJSON(): Record<string, any> {
-    return structuredClone(this.toJSON());
-  }
-}
-
-export type TextNodeParams<T extends Metadata = Metadata> =
-  BaseNodeParams<T> & {
-    text?: string;
-    textTemplate?: string;
-    startCharIdx?: number;
-    endCharIdx?: number;
-    metadataSeparator?: string;
-  };
-
-/**
- * TextNode is the default node type for text. Most common node type in LlamaIndex.TS
- */
-export class TextNode<T extends Metadata = Metadata> extends BaseNode<T> {
-  text: string;
-  textTemplate: string;
-
-  startCharIdx?: number;
-  endCharIdx?: number;
-  // textTemplate: NOTE write your own formatter if needed
-  // metadataTemplate: NOTE write your own formatter if needed
-  metadataSeparator: string;
-
-  constructor(init: TextNodeParams<T> = {}) {
-    super(init);
-    const { text, textTemplate, startCharIdx, endCharIdx, metadataSeparator } =
-      init;
-    this.text = text ?? "";
-    this.textTemplate = textTemplate ?? "";
-    if (startCharIdx) {
-      this.startCharIdx = startCharIdx;
-    }
-    this.endCharIdx = endCharIdx;
-    this.metadataSeparator = metadataSeparator ?? "\n";
-  }
-
-  /**
-   * Generate a hash of the text node.
-   * The ID is not part of the hash as it can change independent of content.
-   * @returns
-   */
-  generateHash() {
-    const hashFunction = createSHA256();
-    hashFunction.update(`type=${this.type}`);
-    hashFunction.update(
-      `startCharIdx=${this.startCharIdx} endCharIdx=${this.endCharIdx}`,
-    );
-    hashFunction.update(this.getContent(MetadataMode.ALL));
-    return hashFunction.digest();
-  }
-
-  get type() {
-    return ObjectType.TEXT;
-  }
-
-  @chunkSizeCheck
-  getContent(metadataMode: MetadataMode = MetadataMode.NONE): string {
-    const metadataStr = this.getMetadataStr(metadataMode).trim();
-    return `${metadataStr}\n\n${this.text}`.trim();
-  }
-
-  getMetadataStr(metadataMode: MetadataMode): string {
-    if (metadataMode === MetadataMode.NONE) {
-      return "";
-    }
-
-    const usableMetadataKeys = new Set(Object.keys(this.metadata).sort());
-    if (metadataMode === MetadataMode.LLM) {
-      for (const key of this.excludedLlmMetadataKeys) {
-        usableMetadataKeys.delete(key);
-      }
-    } else if (metadataMode === MetadataMode.EMBED) {
-      for (const key of this.excludedEmbedMetadataKeys) {
-        usableMetadataKeys.delete(key);
-      }
-    }
-
-    return [...usableMetadataKeys]
-      .map((key) => `${key}: ${this.metadata[key]}`)
-      .join(this.metadataSeparator);
-  }
-
-  setContent(value: string) {
-    this.text = value;
-    this.hash = this.generateHash();
-  }
-
-  getNodeInfo() {
-    return { start: this.startCharIdx, end: this.endCharIdx };
-  }
-
-  getText() {
-    return this.getContent(MetadataMode.NONE);
-  }
-}
-
-export type IndexNodeParams<T extends Metadata = Metadata> =
-  TextNodeParams<T> & {
-    indexId: string;
-  };
-
-export class IndexNode<T extends Metadata = Metadata> extends TextNode<T> {
-  indexId: string;
-
-  constructor(init?: IndexNodeParams<T>) {
-    super(init);
-    const { indexId } = init || {};
-    this.indexId = indexId ?? "";
-  }
-
-  get type() {
-    return ObjectType.INDEX;
-  }
-}
-
-/**
- * A document is just a special text node with a docId.
- */
-export class Document<T extends Metadata = Metadata> extends TextNode<T> {
-  constructor(init?: TextNodeParams<T>) {
-    super(init);
-  }
-
-  get type() {
-    return ObjectType.DOCUMENT;
-  }
-}
-
-export function jsonToNode(json: any, type?: ObjectType) {
-  if (!json.type && !type) {
-    throw new Error("Node type not found");
-  }
-  const nodeType = type || json.type;
-
-  switch (nodeType) {
-    case ObjectType.TEXT:
-      return new TextNode(json);
-    case ObjectType.INDEX:
-      return new IndexNode(json);
-    case ObjectType.DOCUMENT:
-      return new Document(json);
-    case ObjectType.IMAGE_DOCUMENT:
-      return new ImageDocument(json);
-    default:
-      throw new Error(`Invalid node type: ${nodeType}`);
-  }
-}
-
-export type ImageType = string | Blob | URL;
-
-export type ImageNodeParams<T extends Metadata = Metadata> =
-  TextNodeParams<T> & {
-    image: ImageType;
-  };
-
-export class ImageNode<T extends Metadata = Metadata> extends TextNode<T> {
-  image: ImageType; // image as blob
-
-  constructor(init: ImageNodeParams<T>) {
-    super(init);
-    const { image } = init;
-    this.image = image;
-  }
-
-  get type() {
-    return ObjectType.IMAGE;
-  }
-
-  getUrl(): URL {
-    // id_ stores the relative path, convert it to the URL of the file
-    const absPath = path.resolve(this.id_);
-    return new URL(`file://${absPath}`);
-  }
-
-  // Calculates the image part of the hash
-  private generateImageHash() {
-    const hashFunction = createSHA256();
-
-    if (this.image instanceof Blob) {
-      // TODO: ideally we should use the blob's content to calculate the hash:
-      // hashFunction.update(new Uint8Array(await this.image.arrayBuffer()));
-      // as this is async, we're using the node's ID for the time being
-      hashFunction.update(this.id_);
-    } else if (this.image instanceof URL) {
-      hashFunction.update(this.image.toString());
-    } else if (typeof this.image === "string") {
-      hashFunction.update(this.image);
-    } else {
-      throw new Error(
-        `Unknown image type: ${typeof this.image}. Can't calculate hash`,
-      );
-    }
-
-    return hashFunction.digest();
-  }
-
-  generateHash() {
-    const hashFunction = createSHA256();
-    // calculates hash based on hash of both components (image and text)
-    hashFunction.update(super.generateHash());
-    hashFunction.update(this.generateImageHash());
-
-    return hashFunction.digest();
-  }
-}
-
-export class ImageDocument<T extends Metadata = Metadata> extends ImageNode<T> {
-  constructor(init: ImageNodeParams<T>) {
-    super(init);
-  }
-
-  get type() {
-    return ObjectType.IMAGE_DOCUMENT;
-  }
-}
-
-/**
- * A node with a similarity score
- */
-export interface NodeWithScore<T extends Metadata = Metadata> {
-  node: BaseNode<T>;
-  score?: number;
-}
-
-export enum ModalityType {
-  TEXT = "TEXT",
-  IMAGE = "IMAGE",
-}
-
-type NodesByType = {
-  [P in ModalityType]?: BaseNode[];
-};
-
-export function splitNodesByType(nodes: BaseNode[]): NodesByType {
-  const result: NodesByType = {};
-
-  for (const node of nodes) {
-    let type: ModalityType;
-    if (node instanceof ImageNode) {
-      type = ModalityType.IMAGE;
-    } else if (node instanceof TextNode) {
-      type = ModalityType.TEXT;
-    } else {
-      throw new Error(`Unknown node type: ${node.type}`);
-    }
-    if (type in result) {
-      result[type]?.push(node);
-    } else {
-      result[type] = [node];
-    }
-  }
-  return result;
-}
+export * from "@llamaindex/core/schema";

packages/llamaindex/src/Retriever.ts

@@ -1,4 +1,4 @@
-import type { NodeWithScore } from "./Node.js";
+import type { NodeWithScore } from "@llamaindex/core/schema";
 import type { ServiceContext } from "./ServiceContext.js";
 import type { MessageContent } from "./index.edge.js";
 

packages/llamaindex/src/Settings.ts

@@ -1,3 +1,4 @@
+import { Settings as CoreSettings } from "@llamaindex/core/global";
 import { CallbackManager } from "./callbacks/CallbackManager.js";
 import { OpenAI } from "./llm/openai.js";
 
@@ -17,11 +18,6 @@ import {
   setEmbeddedModel,
   withEmbeddedModel,
 } from "./internal/settings/EmbedModel.js";
-import {
-  getChunkSize,
-  setChunkSize,
-  withChunkSize,
-} from "./internal/settings/chunk-size.js";
 import type { LLM } from "./llm/types.js";
 import type { NodeParser } from "./nodeParsers/types.js";
 
@@ -148,15 +144,15 @@ class GlobalSettings implements Config {
   }
 
   set chunkSize(chunkSize: number | undefined) {
-    setChunkSize(chunkSize);
+    CoreSettings.chunkSize = chunkSize;
   }
 
   get chunkSize(): number | undefined {
-    return getChunkSize();
+    return CoreSettings.chunkSize;
   }
 
   withChunkSize<Result>(chunkSize: number, fn: () => Result): Result {
-    return withChunkSize(chunkSize, fn);
+    return CoreSettings.withChunkSize(chunkSize, fn);
   }
 
   get chunkOverlap(): number | undefined {

packages/llamaindex/src/agent/base.ts

@@ -12,6 +12,7 @@ import { consoleLogger, emptyLogger } from "../internal/logger.js";
 import { getCallbackManager } from "../internal/settings/CallbackManager.js";
 import { isAsyncIterable } from "../internal/utils.js";
 import type { ChatMessage, LLM, MessageContent } from "../llm/index.js";
+import { ObjectRetriever } from "../objects/index.js";
 import type { BaseToolWithCall, ToolOutput } from "../types.js";
 import type {
   AgentTaskContext,
@@ -126,12 +127,21 @@ export type AgentParamsBase<
   >
     ? AdditionalMessageOptions
     : never,
-> = {
-  llm?: AI;
-  chatHistory?: ChatMessage<AdditionalMessageOptions>[];
-  systemPrompt?: MessageContent;
-  verbose?: boolean;
-};
+> =
+  | {
+      llm?: AI;
+      chatHistory?: ChatMessage<AdditionalMessageOptions>[];
+      systemPrompt?: MessageContent;
+      verbose?: boolean;
+      tools: BaseToolWithCall[];
+    }
+  | {
+      llm?: AI;
+      chatHistory?: ChatMessage<AdditionalMessageOptions>[];
+      systemPrompt?: MessageContent;
+      verbose?: boolean;
+      toolRetriever: ObjectRetriever<BaseToolWithCall>;
+    };
 
 /**
  * Worker will schedule tasks and handle the task execution

packages/llamaindex/src/agent/llm.ts

@@ -3,6 +3,7 @@ import { ObjectRetriever } from "../objects/index.js";
 import { Settings } from "../Settings.js";
 import type { BaseToolWithCall } from "../types.js";
 import { AgentRunner, AgentWorker, type AgentParamsBase } from "./base.js";
+import { validateAgentParams } from "./utils.js";
 
 type LLMParamsBase = AgentParamsBase<LLM>;
 
@@ -22,6 +23,7 @@ export class LLMAgentWorker extends AgentWorker<LLM> {
 
 export class LLMAgent extends AgentRunner<LLM> {
   constructor(params: LLMAgentParams) {
+    validateAgentParams(params);
     const llm = params.llm ?? (Settings.llm ? (Settings.llm as LLM) : null);
     if (!llm)
       throw new Error(

packages/llamaindex/src/agent/react.ts

@@ -11,35 +11,18 @@ import {
   type LLM,
 } from "../llm/index.js";
 import { extractText } from "../llm/utils.js";
-import { ObjectRetriever } from "../objects/index.js";
 import { Settings } from "../Settings.js";
-import type {
-  BaseTool,
-  BaseToolWithCall,
-  JSONObject,
-  JSONValue,
-} from "../types.js";
+import type { BaseTool, JSONObject, JSONValue } from "../types.js";
 import { AgentRunner, AgentWorker, type AgentParamsBase } from "./base.js";
 import type { TaskHandler } from "./types.js";
 import {
   callTool,
   consumeAsyncIterable,
   createReadableStream,
+  validateAgentParams,
 } from "./utils.js";
 
-type ReACTAgentParamsBase = AgentParamsBase<LLM>;
-
-type ReACTAgentParamsWithTools = ReACTAgentParamsBase & {
-  tools: BaseToolWithCall[];
-};
-
-type ReACTAgentParamsWithToolRetriever = ReACTAgentParamsBase & {
-  toolRetriever: ObjectRetriever<BaseToolWithCall>;
-};
-
-export type ReACTAgentParams =
-  | ReACTAgentParamsWithTools
-  | ReACTAgentParamsWithToolRetriever;
+export type ReACTAgentParams = AgentParamsBase<LLM>;
 
 type BaseReason = {
   type: unknown;
@@ -342,9 +325,8 @@ export class ReACTAgentWorker extends AgentWorker<LLM, ReACTAgentStore> {
 }
 
 export class ReActAgent extends AgentRunner<LLM, ReACTAgentStore> {
-  constructor(
-    params: ReACTAgentParamsWithTools | ReACTAgentParamsWithToolRetriever,
-  ) {
+  constructor(params: ReACTAgentParams) {
+    validateAgentParams(params);
     super({
       llm: params.llm ?? Settings.llm,
       chatHistory: params.chatHistory ?? [],

packages/llamaindex/src/agent/utils.ts

@@ -1,4 +1,6 @@
+import { baseToolWithCallSchema } from "@llamaindex/core/schema";
 import { ReadableStream } from "@llamaindex/env";
+import { z } from "zod";
 import type { Logger } from "../internal/logger.js";
 import { getCallbackManager } from "../internal/settings/CallbackManager.js";
 import {
@@ -17,6 +19,7 @@ import type {
   ToolCallLLMMessageOptions,
 } from "../llm/index.js";
 import type { BaseTool, JSONObject, JSONValue, ToolOutput } from "../types.js";
+import type { AgentParamsBase } from "./base.js";
 import type { TaskHandler } from "./types.js";
 
 type StepToolsResponseParams<Model extends LLM> = {
@@ -61,6 +64,7 @@ export async function stepToolsStreaming<Model extends LLM>({
   // check if first chunk has tool calls, if so, this is a function call
   // otherwise, it's a regular message
   const hasToolCall = !!(value.options && "toolCall" in value.options);
+
   enqueueOutput({
     taskStep: step,
     output: finalStream,
@@ -78,6 +82,14 @@ export async function stepToolsStreaming<Model extends LLM>({
         });
       }
     }
+
+    // If there are toolCalls but they didn't get read into the stream, used for Gemini
+    if (!toolCalls.size && value.options && "toolCall" in value.options) {
+      value.options.toolCall.forEach((toolCall) => {
+        toolCalls.set(toolCall.id, toolCall);
+      });
+    }
+
     step.context.store.messages = [
       ...step.context.store.messages,
       {
@@ -288,3 +300,13 @@ export function createReadableStream<T>(
     },
   });
 }
+
+export function validateAgentParams<AI extends LLM>(
+  params: AgentParamsBase<AI>,
+) {
+  if ("tools" in params) {
+    z.array(baseToolWithCallSchema).parse(params.tools);
+  } else {
+    // todo: check `params.toolRetriever` when migrate to @llamaindex/core
+  }
+}

packages/llamaindex/src/callbacks/CallbackManager.ts

@@ -1,6 +1,6 @@
 import type { Anthropic } from "@anthropic-ai/sdk";
+import type { NodeWithScore } from "@llamaindex/core/schema";
 import { CustomEvent } from "@llamaindex/env";
-import type { NodeWithScore } from "../Node.js";
 import type { AgentEndEvent, AgentStartEvent } from "../agent/types.js";
 import {
   EventCaller,

packages/llamaindex/src/cloud/LlamaCloudIndex.ts

@@ -1,4 +1,4 @@
-import type { Document } from "../Node.js";
+import type { Document } from "@llamaindex/core/schema";
 import type { BaseRetriever } from "../Retriever.js";
 import { RetrieverQueryEngine } from "../engines/query/RetrieverQueryEngine.js";
 import type { TransformComponent } from "../ingestion/types.js";
@@ -8,10 +8,12 @@ import type { QueryEngine } from "../types.js";
 import type { CloudRetrieveParams } from "./LlamaCloudRetriever.js";
 import { LlamaCloudRetriever } from "./LlamaCloudRetriever.js";
 import { getPipelineCreate } from "./config.js";
-import type { CloudConstructorParams } from "./types.js";
-import { getAppBaseUrl, getClient } from "./utils.js";
+import type { CloudConstructorParams } from "./constants.js";
+import { getAppBaseUrl, initService } from "./utils.js";
 
+import { PipelinesService, ProjectsService } from "@llamaindex/cloud/api";
 import { getEnv } from "@llamaindex/env";
+import { Settings } from "../Settings.js";
 import { OpenAIEmbedding } from "../embeddings/OpenAIEmbedding.js";
 import { SimpleNodeParser } from "../nodeParsers/SimpleNodeParser.js";
 
@@ -20,10 +22,11 @@ export class LlamaCloudIndex {
 
   constructor(params: CloudConstructorParams) {
     this.params = params;
+    initService(this.params);
   }
 
   private async waitForPipelineIngestion(
-    verbose = false,
+    verbose = Settings.debug,
     raiseOnError = false,
   ): Promise<void> {
     const pipelineId = await this.getPipelineId(
@@ -31,18 +34,17 @@ export class LlamaCloudIndex {
       this.params.projectName,
     );
 
-    const client = await getClient({
-      ...this.params,
-      baseUrl: this.params.baseUrl,
-    });
-
     if (verbose) {
       console.log("Waiting for pipeline ingestion: ");
     }
 
     while (true) {
       const pipelineStatus =
-        await client.pipelines.getPipelineStatus(pipelineId);
+        await PipelinesService.getPipelineStatusApiV1PipelinesPipelineIdStatusGet(
+          {
+            pipelineId,
+          },
+        );
 
       if (pipelineStatus.status === "SUCCESS") {
         if (verbose) {
@@ -71,7 +73,7 @@ export class LlamaCloudIndex {
 
   private async waitForDocumentIngestion(
     docIds: string[],
-    verbose = false,
+    verbose = Settings.debug,
     raiseOnError = false,
   ): Promise<void> {
     const pipelineId = await this.getPipelineId(
@@ -79,11 +81,6 @@ export class LlamaCloudIndex {
       this.params.projectName,
     );
 
-    const client = await getClient({
-      ...this.params,
-      baseUrl: this.params.baseUrl,
-    });
-
     if (verbose) {
       console.log("Loading data: ");
     }
@@ -94,10 +91,10 @@ export class LlamaCloudIndex {
       const docsToRemove = new Set<string>();
 
       for (const doc of pendingDocs) {
-        const { status } = await client.pipelines.getPipelineDocumentStatus(
-          pipelineId,
-          doc,
-        );
+        const { status } =
+          await PipelinesService.getPipelineDocumentStatusApiV1PipelinesPipelineIdDocumentsDocumentIdStatusGet(
+            { pipelineId, documentId: doc },
+          );
 
         if (status === "NOT_STARTED" || status === "IN_PROGRESS") {
           continue;
@@ -140,12 +137,7 @@ export class LlamaCloudIndex {
     name: string,
     projectName: string,
   ): Promise<string> {
-    const client = await getClient({
-      ...this.params,
-      baseUrl: this.params.baseUrl,
-    });
-
-    const pipelines = await client.pipelines.searchPipelines({
+    const pipelines = await PipelinesService.searchPipelinesApiV1PipelinesGet({
       projectName,
       pipelineName: name,
     });
@@ -166,10 +158,7 @@ export class LlamaCloudIndex {
         apiKey: getEnv("OPENAI_API_KEY"),
       }),
     ];
-
-    const appUrl = getAppBaseUrl(params.baseUrl);
-
-    const client = await getClient({ ...params, baseUrl: appUrl });
+    const apiUrl = getAppBaseUrl();
 
     const pipelineCreateParams = await getPipelineCreate({
       pipelineName: params.name,
@@ -178,21 +167,23 @@ export class LlamaCloudIndex {
       transformations: params.transformations ?? defaultTransformations,
     });
 
-    const project = await client.projects.upsertProject({
-      name: params.projectName ?? "default",
+    const project = await ProjectsService.upsertProjectApiV1ProjectsPut({
+      requestBody: {
+        name: params.projectName ?? "default",
+      },
     });
 
     if (!project.id) {
       throw new Error("Project ID should be defined");
     }
 
-    const pipeline = await client.pipelines.upsertPipeline({
+    const pipeline = await PipelinesService.upsertPipelineApiV1PipelinesPut({
       projectId: project.id,
-      body: {
+      requestBody: {
         name: params.name,
-        configuredTransformations:
-          pipelineCreateParams.configuredTransformations,
-        pipelineType: pipelineCreateParams.pipelineType,
+        configured_transformations:
+          pipelineCreateParams.configured_transformations,
+        pipeline_type: pipelineCreateParams.pipeline_type,
       },
     });
 
@@ -204,21 +195,26 @@ export class LlamaCloudIndex {
       console.log(`Created pipeline ${pipeline.id} with name ${params.name}`);
     }
 
-    await client.pipelines.upsertBatchPipelineDocuments(
-      pipeline.id,
-      params.documents.map((doc) => ({
-        metadata: doc.metadata,
-        text: doc.text,
-        excludedEmbedMetadataKeys: doc.excludedLlmMetadataKeys,
-        excludedLlmMetadataKeys: doc.excludedEmbedMetadataKeys,
-        id: doc.id_,
-      })),
+    await PipelinesService.upsertBatchPipelineDocumentsApiV1PipelinesPipelineIdDocumentsPut(
+      {
+        pipelineId: pipeline.id,
+        requestBody: params.documents.map((doc) => ({
+          metadata: doc.metadata,
+          text: doc.text,
+          excluded_embed_metadata_keys: doc.excludedEmbedMetadataKeys,
+          excluded_llm_metadata_keys: doc.excludedEmbedMetadataKeys,
+          id: doc.id_,
+        })),
+      },
     );
 
     while (true) {
-      const pipelineStatus = await client.pipelines.getPipelineStatus(
-        pipeline.id,
-      );
+      const pipelineStatus =
+        await PipelinesService.getPipelineStatusApiV1PipelinesPipelineIdStatusGet(
+          {
+            pipelineId: pipeline.id,
+          },
+        );
 
       if (pipelineStatus.status === "SUCCESS") {
         console.info(
@@ -229,14 +225,14 @@ export class LlamaCloudIndex {
 
       if (pipelineStatus.status === "ERROR") {
         console.error(
-          `Some documents failed to ingest, check your pipeline logs at ${appUrl}/project/${project.id}/deploy/${pipeline.id}`,
+          `Some documents failed to ingest, check your pipeline logs at ${apiUrl}/project/${project.id}/deploy/${pipeline.id}`,
         );
         throw new Error("Some documents failed to ingest");
       }
 
       if (pipelineStatus.status === "PARTIAL_SUCCESS") {
         console.info(
-          `Documents ingestion partially succeeded, to check a more complete status check your pipeline at ${appUrl}/project/${project.id}/deploy/${pipeline.id}`,
+          `Documents ingestion partially succeeded, to check a more complete status check your pipeline at ${apiUrl}/project/${project.id}/deploy/${pipeline.id}`,
         );
         break;
       }
@@ -250,7 +246,7 @@ export class LlamaCloudIndex {
 
     if (params.verbose) {
       console.info(
-        `Ingestion completed, find your index at ${appUrl}/project/${project.id}/deploy/${pipeline.id}`,
+        `Ingestion completed, find your index at ${apiUrl}/project/${project.id}/deploy/${pipeline.id}`,
       );
     }
 
@@ -281,10 +277,6 @@ export class LlamaCloudIndex {
   }
 
   async insert(document: Document) {
-    const appUrl = getAppBaseUrl(this.params.baseUrl);
-
-    const client = await getClient({ ...this.params, baseUrl: appUrl });
-
     const pipelineId = await this.getPipelineId(
       this.params.name,
       this.params.projectName,
@@ -294,24 +286,25 @@ export class LlamaCloudIndex {
       throw new Error("We couldn't find the pipeline ID for the given name");
     }
 
-    await client.pipelines.createBatchPipelineDocuments(pipelineId, [
+    await PipelinesService.createBatchPipelineDocumentsApiV1PipelinesPipelineIdDocumentsPost(
       {
-        metadata: document.metadata,
-        text: document.text,
-        excludedEmbedMetadataKeys: document.excludedLlmMetadataKeys,
-        excludedLlmMetadataKeys: document.excludedEmbedMetadataKeys,
-        id: document.id_,
+        pipelineId: pipelineId,
+        requestBody: [
+          {
+            metadata: document.metadata,
+            text: document.text,
+            excluded_embed_metadata_keys: document.excludedLlmMetadataKeys,
+            excluded_llm_metadata_keys: document.excludedEmbedMetadataKeys,
+            id: document.id_,
+          },
+        ],
       },
-    ]);
+    );
 
     await this.waitForDocumentIngestion([document.id_]);
   }
 
   async delete(document: Document) {
-    const appUrl = getAppBaseUrl(this.params.baseUrl);
-
-    const client = await getClient({ ...this.params, baseUrl: appUrl });
-
     const pipelineId = await this.getPipelineId(
       this.params.name,
       this.params.projectName,
@@ -321,16 +314,17 @@ export class LlamaCloudIndex {
       throw new Error("We couldn't find the pipeline ID for the given name");
     }
 
-    await client.pipelines.deletePipelineDocument(pipelineId, document.id_);
+    await PipelinesService.deletePipelineDocumentApiV1PipelinesPipelineIdDocumentsDocumentIdDelete(
+      {
+        pipelineId,
+        documentId: document.id_,
+      },
+    );
 
     await this.waitForPipelineIngestion();
   }
 
   async refreshDoc(document: Document) {
-    const appUrl = getAppBaseUrl(this.params.baseUrl);
-
-    const client = await getClient({ ...this.params, baseUrl: appUrl });
-
     const pipelineId = await this.getPipelineId(
       this.params.name,
       this.params.projectName,
@@ -340,15 +334,20 @@ export class LlamaCloudIndex {
       throw new Error("We couldn't find the pipeline ID for the given name");
     }
 
-    await client.pipelines.upsertBatchPipelineDocuments(pipelineId, [
+    await PipelinesService.upsertBatchPipelineDocumentsApiV1PipelinesPipelineIdDocumentsPut(
       {
-        metadata: document.metadata,
-        text: document.text,
-        excludedEmbedMetadataKeys: document.excludedLlmMetadataKeys,
-        excludedLlmMetadataKeys: document.excludedEmbedMetadataKeys,
-        id: document.id_,
+        pipelineId,
+        requestBody: [
+          {
+            metadata: document.metadata,
+            text: document.text,
+            excluded_embed_metadata_keys: document.excludedLlmMetadataKeys,
+            excluded_llm_metadata_keys: document.excludedEmbedMetadataKeys,
+            id: document.id_,
+          },
+        ],
       },
-    ]);
+    );
 
     await this.waitForDocumentIngestion([document.id_]);
   }

packages/llamaindex/src/cloud/LlamaCloudRetriever.ts

@@ -1,30 +1,33 @@
-import type { LlamaCloudApi, LlamaCloudApiClient } from "@llamaindex/cloud";
-import type { NodeWithScore } from "../Node.js";
-import { ObjectType, jsonToNode } from "../Node.js";
+import {
+  type MetadataFilters,
+  PipelinesService,
+  type RetrievalParams,
+  type TextNodeWithScore,
+} from "@llamaindex/cloud/api";
+import type { NodeWithScore } from "@llamaindex/core/schema";
+import { jsonToNode, ObjectType } from "@llamaindex/core/schema";
 import type { BaseRetriever, RetrieveParams } from "../Retriever.js";
 import { wrapEventCaller } from "../internal/context/EventCaller.js";
-import { getCallbackManager } from "../internal/settings/CallbackManager.js";
 import { extractText } from "../llm/utils.js";
-import type { ClientParams, CloudConstructorParams } from "./types.js";
-import { DEFAULT_PROJECT_NAME } from "./types.js";
-import { getClient } from "./utils.js";
+import type { ClientParams, CloudConstructorParams } from "./constants.js";
+import { DEFAULT_PROJECT_NAME } from "./constants.js";
+import { initService } from "./utils.js";
 
 export type CloudRetrieveParams = Omit<
-  LlamaCloudApi.RetrievalParams,
+  RetrievalParams,
   "query" | "searchFilters" | "className" | "denseSimilarityTopK"
 > & { similarityTopK?: number };
 
 export class LlamaCloudRetriever implements BaseRetriever {
-  client?: LlamaCloudApiClient;
   clientParams: ClientParams;
   retrieveParams: CloudRetrieveParams;
   projectName: string = DEFAULT_PROJECT_NAME;
   pipelineName: string;
 
   private resultNodesToNodeWithScore(
-    nodes: LlamaCloudApi.TextNodeWithScore[],
+    nodes: TextNodeWithScore[],
   ): NodeWithScore[] {
-    return nodes.map((node: LlamaCloudApi.TextNodeWithScore) => {
+    return nodes.map((node: TextNodeWithScore) => {
       return {
         // Currently LlamaCloud only supports text nodes
         node: jsonToNode(node.node, ObjectType.TEXT),
@@ -35,6 +38,7 @@ export class LlamaCloudRetriever implements BaseRetriever {
 
   constructor(params: CloudConstructorParams & CloudRetrieveParams) {
     this.clientParams = { apiKey: params.apiKey, baseUrl: params.baseUrl };
+    initService(this.clientParams);
     this.retrieveParams = params;
     this.pipelineName = params.name;
     if (params.projectName) {
@@ -42,32 +46,26 @@ export class LlamaCloudRetriever implements BaseRetriever {
     }
   }
 
-  private async getClient(): Promise<LlamaCloudApiClient> {
-    if (!this.client) {
-      this.client = await getClient(this.clientParams);
-    }
-    return this.client;
-  }
-
   @wrapEventCaller
   async retrieve({
     query,
     preFilters,
   }: RetrieveParams): Promise<NodeWithScore[]> {
-    const client = await this.getClient();
-
-    const pipelines = await client?.pipelines.searchPipelines({
+    const pipelines = await PipelinesService.searchPipelinesApiV1PipelinesGet({
       projectName: this.projectName,
       pipelineName: this.pipelineName,
     });
 
-    if (!pipelines) {
+    if (pipelines.length === 0 || !pipelines[0].id) {
       throw new Error(
         `No pipeline found with name ${this.pipelineName} in project ${this.projectName}`,
       );
     }
 
-    const pipeline = await client?.pipelines.getPipeline(pipelines[0].id);
+    const pipeline =
+      await PipelinesService.getPipelineApiV1PipelinesPipelineIdGet({
+        pipelineId: pipelines[0].id,
+      });
 
     if (!pipeline) {
       throw new Error(
@@ -75,19 +73,16 @@ export class LlamaCloudRetriever implements BaseRetriever {
       );
     }
 
-    const results = await client?.pipelines.runSearch(pipeline.id, {
-      ...this.retrieveParams,
-      query: extractText(query),
-      searchFilters: preFilters as LlamaCloudApi.MetadataFilters,
-    });
+    const results =
+      await PipelinesService.runSearchApiV1PipelinesPipelineIdRetrievePost({
+        pipelineId: pipeline.id,
+        requestBody: {
+          ...this.retrieveParams,
+          query: extractText(query),
+          search_filters: preFilters as MetadataFilters,
+        },
+      });
 
-    const nodes = this.resultNodesToNodeWithScore(results.retrievalNodes);
-
-    getCallbackManager().dispatchEvent("retrieve", {
-      query,
-      nodes,
-    });
-
-    return nodes;
+    return this.resultNodesToNodeWithScore(results.retrieval_nodes);
   }
 }

packages/llamaindex/src/cloud/config.ts

@@ -1,24 +1,27 @@
-import { LlamaCloudApi } from "@llamaindex/cloud";
-import { BaseNode } from "../Node.js";
+import type {
+  ConfiguredTransformationItem,
+  PipelineCreate,
+  PipelineType,
+} from "@llamaindex/cloud/api";
+import { BaseNode } from "@llamaindex/core/schema";
 import { OpenAIEmbedding } from "../embeddings/OpenAIEmbedding.js";
 import type { TransformComponent } from "../ingestion/types.js";
 import { SimpleNodeParser } from "../nodeParsers/SimpleNodeParser.js";
 
 export type GetPipelineCreateParams = {
   pipelineName: string;
-  pipelineType: any; // TODO: PlatformApi.PipelineType is not exported
+  pipelineType: PipelineType;
   transformations?: TransformComponent[];
   inputNodes?: BaseNode[];
 };
 
 function getTransformationConfig(
   transformation: TransformComponent,
-): LlamaCloudApi.ConfiguredTransformationItem {
+): ConfiguredTransformationItem {
   if (transformation instanceof SimpleNodeParser) {
     return {
-      configurableTransformationType: "SENTENCE_AWARE_NODE_PARSER",
+      configurable_transformation_type: "SENTENCE_AWARE_NODE_PARSER",
       component: {
-        // TODO: API doesnt accept camelCase
         chunk_size: transformation.textSplitter.chunkSize, // TODO: set to public in SentenceSplitter
         chunk_overlap: transformation.textSplitter.chunkOverlap, // TODO: set to public in SentenceSplitter
         include_metadata: transformation.includeMetadata,
@@ -28,9 +31,8 @@ function getTransformationConfig(
   }
   if (transformation instanceof OpenAIEmbedding) {
     return {
-      configurableTransformationType: "OPENAI_EMBEDDING",
+      configurable_transformation_type: "OPENAI_EMBEDDING",
       component: {
-        // TODO: API doesnt accept camelCase
         model: transformation.model,
         api_key: transformation.apiKey,
         embed_batch_size: transformation.embedBatchSize,
@@ -43,12 +45,12 @@ function getTransformationConfig(
 
 export async function getPipelineCreate(
   params: GetPipelineCreateParams,
-): Promise<LlamaCloudApi.PipelineCreate> {
+): Promise<PipelineCreate> {
   const { pipelineName, pipelineType, transformations = [] } = params;
 
   return {
     name: pipelineName,
-    configuredTransformations: transformations.map(getTransformationConfig),
-    pipelineType: pipelineType,
+    configured_transformations: transformations.map(getTransformationConfig),
+    pipeline_type: pipelineType,
   };
 }

packages/llamaindex/src/cloud/constants.ts

@@ -1,6 +1,5 @@
 import type { ServiceContext } from "../ServiceContext.js";
 
-export const DEFAULT_PIPELINE_NAME = "default";
 export const DEFAULT_PROJECT_NAME = "Default";
 export const DEFAULT_BASE_URL = "https://api.cloud.llamaindex.ai";
 

packages/llamaindex/src/cloud/index.ts

@@ -1,6 +1,6 @@
+export type { CloudConstructorParams } from "./constants.js";
 export { LlamaCloudIndex } from "./LlamaCloudIndex.js";
 export {
   LlamaCloudRetriever,
   type CloudRetrieveParams,
 } from "./LlamaCloudRetriever.js";
-export type { CloudConstructorParams } from "./types.js";

packages/llamaindex/src/cloud/utils.ts

@@ -1,36 +1,22 @@
-import type { LlamaCloudApiClient } from "@llamaindex/cloud";
+import { OpenAPI } from "@llamaindex/cloud/api";
 import { getEnv } from "@llamaindex/env";
-import type { ClientParams } from "./types.js";
-import { DEFAULT_BASE_URL } from "./types.js";
+import type { ClientParams } from "./constants.js";
+import { DEFAULT_BASE_URL } from "./constants.js";
 
 function getBaseUrl(baseUrl?: string): string {
   return baseUrl ?? getEnv("LLAMA_CLOUD_BASE_URL") ?? DEFAULT_BASE_URL;
 }
 
-export function getAppBaseUrl(baseUrl?: string): string {
-  return getBaseUrl(baseUrl).replace(/api\./, "");
+export function getAppBaseUrl(): string {
+  return OpenAPI.BASE.replace(/api\./, "");
 }
 
-export async function getClient({
-  apiKey,
-  baseUrl,
-}: ClientParams = {}): Promise<LlamaCloudApiClient> {
-  const { LlamaCloudApiClient } = await import("@llamaindex/cloud");
-
-  // Get the environment variables or use defaults
-  baseUrl = getBaseUrl(baseUrl);
-  apiKey = apiKey ?? getEnv("LLAMA_CLOUD_API_KEY");
-
-  if (!apiKey) {
+export function initService({ apiKey, baseUrl }: ClientParams = {}) {
+  OpenAPI.TOKEN = apiKey ?? getEnv("LLAMA_CLOUD_API_KEY");
+  OpenAPI.BASE = getBaseUrl(baseUrl);
+  if (!OpenAPI.TOKEN) {
     throw new Error(
       "API Key is required for LlamaCloudIndex. Please pass the apiKey parameter",
     );
   }
-
-  const client = new LlamaCloudApiClient({
-    token: apiKey,
-    environment: baseUrl,
-  });
-
-  return client;
 }

packages/llamaindex/src/embeddings/ClipEmbedding.ts

@@ -1,5 +1,5 @@
+import type { ImageType } from "@llamaindex/core/schema";
 import _ from "lodash";
-import type { ImageType } from "../Node.js";
 import { lazyLoadTransformers } from "../internal/deps/transformers.js";
 import { MultiModalEmbedding } from "./MultiModalEmbedding.js";
 // only import type, to avoid bundling error

packages/llamaindex/src/embeddings/CloudflareWorkerEmbedding.ts

@@ -1,4 +1,4 @@
-import type { ImageType } from "../Node.js";
+import type { ImageType } from "@llamaindex/core/schema";
 import { MultiModalEmbedding } from "./MultiModalEmbedding.js";
 
 /**

packages/llamaindex/src/embeddings/MultiModalEmbedding.ts

@@ -5,7 +5,7 @@ import {
   splitNodesByType,
   type BaseNode,
   type ImageType,
-} from "../Node.js";
+} from "@llamaindex/core/schema";
 import type { MessageContentDetail } from "../llm/types.js";
 import { extractImage, extractSingleText } from "../llm/utils.js";
 import { BaseEmbedding, batchEmbeddings } from "./types.js";

packages/llamaindex/src/embeddings/types.ts

@@ -1,6 +1,6 @@
+import type { BaseNode } from "@llamaindex/core/schema";
+import { MetadataMode } from "@llamaindex/core/schema";
 import { type Tokenizers } from "@llamaindex/env";
-import type { BaseNode } from "../Node.js";
-import { MetadataMode } from "../Node.js";
 import type { TransformComponent } from "../ingestion/types.js";
 import type { MessageContentDetail } from "../llm/types.js";
 import { extractSingleText } from "../llm/utils.js";

packages/llamaindex/src/embeddings/utils.ts

@@ -1,7 +1,7 @@
+import type { ImageType } from "@llamaindex/core/schema";
 import { fs } from "@llamaindex/env";
 import _ from "lodash";
 import { filetypemime } from "magic-bytes.js";
-import type { ImageType } from "../Node.js";
 import { DEFAULT_SIMILARITY_TOP_K } from "../constants.js";
 import type { VectorStoreQueryMode } from "../storage/vectorStore/types.js";
 

packages/llamaindex/src/engines/chat/DefaultContextGenerator.ts

@@ -1,4 +1,4 @@
-import { type NodeWithScore } from "../../Node.js";
+import { type NodeWithScore } from "@llamaindex/core/schema";
 import type { ContextSystemPrompt } from "../../Prompt.js";
 import { defaultContextSystemPrompt } from "../../Prompt.js";
 import type { BaseRetriever } from "../../Retriever.js";

packages/llamaindex/src/engines/chat/types.ts

@@ -1,6 +1,6 @@
+import type { NodeWithScore } from "@llamaindex/core/schema";
 import type { ChatHistory } from "../../ChatHistory.js";
 import type { EngineResponse } from "../../EngineResponse.js";
-import type { NodeWithScore } from "../../Node.js";
 import type { ChatMessage } from "../../llm/index.js";
 import type { MessageContent } from "../../llm/types.js";
 

packages/llamaindex/src/engines/query/RetrieverQueryEngine.ts

@@ -1,5 +1,5 @@
+import type { NodeWithScore } from "@llamaindex/core/schema";
 import type { EngineResponse } from "../../EngineResponse.js";
-import type { NodeWithScore } from "../../Node.js";
 import type { BaseRetriever } from "../../Retriever.js";
 import { wrapEventCaller } from "../../internal/context/EventCaller.js";
 import type { BaseNodePostprocessor } from "../../postprocessors/index.js";

packages/llamaindex/src/engines/query/RouterQueryEngine.ts

@@ -1,5 +1,5 @@
+import type { NodeWithScore } from "@llamaindex/core/schema";
 import { EngineResponse } from "../../EngineResponse.js";
-import type { NodeWithScore } from "../../Node.js";
 import type { ServiceContext } from "../../ServiceContext.js";
 import { llmFromSettingsOrContext } from "../../Settings.js";
 import { PromptMixin } from "../../prompts/index.js";

packages/llamaindex/src/engines/query/SubQuestionQueryEngine.ts

@@ -1,6 +1,6 @@
+import type { NodeWithScore } from "@llamaindex/core/schema";
+import { TextNode } from "@llamaindex/core/schema";
 import type { EngineResponse } from "../../EngineResponse.js";
-import type { NodeWithScore } from "../../Node.js";
-import { TextNode } from "../../Node.js";
 import { LLMQuestionGenerator } from "../../QuestionGenerator.js";
 import type { ServiceContext } from "../../ServiceContext.js";
 import { PromptMixin } from "../../prompts/Mixin.js";