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https://github.com/run-llama/create-llama.git
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3 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| a108911fc1 | |||
| 282eaa07fc | |||
| 80db5f7c46 |
@@ -1,5 +1,11 @@
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# create-llama
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## 0.3.13
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### Patch Changes
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- 282eaa0: Ensure that the index and document store are created when uploading a file with no available index.
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## 0.3.12
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### Patch Changes
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@@ -217,7 +217,13 @@ Otherwise, use CHROMA_HOST and CHROMA_PORT config above`,
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},
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];
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default:
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return [];
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return [
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{
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name: "STORAGE_CACHE_DIR",
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description: "The directory to store the local storage cache.",
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value: ".cache",
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},
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];
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}
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};
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+1
-1
@@ -1,6 +1,6 @@
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{
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"name": "create-llama",
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"version": "0.3.12",
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"version": "0.3.13",
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"description": "Create LlamaIndex-powered apps with one command",
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"keywords": [
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"rag",
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@@ -3,6 +3,7 @@ import {
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IngestionPipeline,
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Settings,
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SimpleNodeParser,
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storageContextFromDefaults,
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VectorStoreIndex,
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} from "llamaindex";
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@@ -28,11 +29,20 @@ export async function runPipeline(
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return documents.map((document) => document.id_);
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} else {
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// Initialize a new index with the documents
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const newIndex = await VectorStoreIndex.fromDocuments(documents);
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newIndex.storageContext.docStore.persist();
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console.log(
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"Got empty index, created new index with the uploaded documents",
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);
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const persistDir = process.env.STORAGE_CACHE_DIR;
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if (!persistDir) {
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throw new Error("STORAGE_CACHE_DIR environment variable is required!");
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}
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const storageContext = await storageContextFromDefaults({
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persistDir,
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});
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const newIndex = await VectorStoreIndex.fromDocuments(documents, {
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storageContext,
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});
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await newIndex.storageContext.docStore.persist();
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return documents.map((document) => document.id_);
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}
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}
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@@ -5,7 +5,6 @@ import * as dotenv from "dotenv";
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import { getDocuments } from "./loader";
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import { initSettings } from "./settings";
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import { STORAGE_CACHE_DIR } from "./shared";
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// Load environment variables from local .env file
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dotenv.config();
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@@ -20,9 +19,13 @@ async function getRuntime(func: any) {
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async function generateDatasource() {
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console.log(`Generating storage context...`);
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// Split documents, create embeddings and store them in the storage context
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const persistDir = process.env.STORAGE_CACHE_DIR;
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if (!persistDir) {
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throw new Error("STORAGE_CACHE_DIR environment variable is required!");
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}
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const ms = await getRuntime(async () => {
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const storageContext = await storageContextFromDefaults({
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persistDir: STORAGE_CACHE_DIR,
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persistDir,
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});
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const documents = await getDocuments();
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@@ -1,10 +1,13 @@
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import { SimpleDocumentStore, VectorStoreIndex } from "llamaindex";
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import { storageContextFromDefaults } from "llamaindex/storage/StorageContext";
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import { STORAGE_CACHE_DIR } from "./shared";
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export async function getDataSource(params?: any) {
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const persistDir = process.env.STORAGE_CACHE_DIR;
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if (!persistDir) {
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throw new Error("STORAGE_CACHE_DIR environment variable is required!");
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}
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const storageContext = await storageContextFromDefaults({
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persistDir: `${STORAGE_CACHE_DIR}`,
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persistDir,
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});
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const numberOfDocs = Object.keys(
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@@ -1 +0,0 @@
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export const STORAGE_CACHE_DIR = "./cache";
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@@ -1,2 +1,3 @@
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# TODO: You can add observability here. For templates re-start `create-llama` with `--pro` flag to generate a new project with observability.
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def init_observability():
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pass
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