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Author SHA1 Message Date
Emanuel Ferreira 0e61df60f7 chore: remove query engine 2024-02-27 07:43:16 -03:00
67 changed files with 251 additions and 898 deletions
-5
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@@ -1,5 +0,0 @@
---
"create-llama": patch
---
Add LlamaParse option when selecting a pdf file or a folder
-5
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@@ -1,5 +0,0 @@
---
"llamaindex": patch
---
Add quantized parameter to HuggingFaceEmbedding
-1
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@@ -44,7 +44,6 @@ test-results/
playwright-report/
blob-report/
playwright/.cache/
.tsbuildinfo
# intellij
**/.idea
-7
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@@ -1,12 +1,5 @@
# docs
## 0.0.4
### Patch Changes
- Updated dependencies [5116ad8]
- @llamaindex/env@0.0.5
## 0.0.3
### Patch Changes
@@ -23,15 +23,3 @@ const results = await queryEngine.query({
query,
});
```
Per default, `HuggingFaceEmbedding` is using the `Xenova/all-MiniLM-L6-v2` model. You can change the model by passing the `modelType` parameter to the constructor.
If you're not using a quantized model, set the `quantized` parameter to `false`.
For example, to use the not quantized `BAAI/bge-small-en-v1.5` model, you can use the following code:
```
const embedModel = new HuggingFaceEmbedding({
modelType: "BAAI/bge-small-en-v1.5",
quantized: false,
});
```
+1 -1
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@@ -1,6 +1,6 @@
{
"name": "docs",
"version": "0.0.4",
"version": "0.0.3",
"private": true,
"scripts": {
"docusaurus": "docusaurus",
@@ -8,7 +8,7 @@ import {
async function main() {
// Load the documents
const documents = await new SimpleDirectoryReader().loadData({
directoryPath: "node_modules/llamaindex/examples",
directoryPath: "node_modules/llamaindex/examples/",
});
// Create a vector index from the documents
@@ -32,31 +32,13 @@ async function main() {
verbose: true,
});
const task = agent.createTask("What was his salary?");
// Chat with the agent
const response = await agent.chat({
message: "What was his salary?",
});
let count = 0;
while (true) {
const stepOutput = await agent.runStep(task.taskId);
console.log(`Runnning step ${count++}`);
console.log(`======== OUTPUT ==========`);
if (stepOutput.output.response) {
console.log(stepOutput.output.response);
} else {
console.log(stepOutput.output.sources);
}
console.log(`==========================`);
if (stepOutput.isLast) {
const finalResponse = await agent.finalizeResponse(
task.taskId,
stepOutput,
);
console.log({ finalResponse });
break;
}
}
// Print the response
console.log(String(response));
}
main().then(() => {
+1 -1
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@@ -8,7 +8,7 @@ import {
async function main() {
// Load the documents
const documents = await new SimpleDirectoryReader().loadData({
directoryPath: "node_modules/llamaindex/examples",
directoryPath: "node_modules/llamaindex/examples/",
});
// Create a vector index from the documents
-95
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@@ -1,95 +0,0 @@
import { FunctionTool, OpenAIAgent } from "llamaindex";
// Define a function to sum two numbers
function sumNumbers({ a, b }: { a: number; b: number }): number {
return a + b;
}
// Define a function to divide two numbers
function divideNumbers({ a, b }: { a: number; b: number }): number {
return a / b;
}
// Define the parameters of the sum function as a JSON schema
const sumJSON = {
type: "object",
properties: {
a: {
type: "number",
description: "The first number",
},
b: {
type: "number",
description: "The second number",
},
},
required: ["a", "b"],
};
const divideJSON = {
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() {
// Create a function tool from the sum function
const functionTool = new FunctionTool(sumNumbers, {
name: "sumNumbers",
description: "Use this function to sum two numbers",
parameters: sumJSON,
});
// Create a function tool from the divide function
const functionTool2 = new FunctionTool(divideNumbers, {
name: "divideNumbers",
description: "Use this function to divide two numbers",
parameters: divideJSON,
});
// Create an OpenAIAgent with the function tools
const agent = new OpenAIAgent({
tools: [functionTool, functionTool2],
verbose: true,
});
// Create a task to sum and divide numbers
const task = agent.createTask("How much is 5 + 5? then divide by 2");
let count = 0;
while (true) {
const stepOutput = await agent.runStep(task.taskId);
console.log(`Runnning step ${count++}`);
console.log(`======== OUTPUT ==========`);
if (stepOutput.output.response) {
console.log(stepOutput.output.response);
} else {
console.log(stepOutput.output.sources);
}
console.log(`==========================`);
if (stepOutput.isLast) {
const finalResponse = await agent.finalizeResponse(
task.taskId,
stepOutput,
);
console.log({ finalResponse });
break;
}
}
}
main().then(() => {
console.log("Done");
});
-90
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@@ -1,90 +0,0 @@
import { FunctionTool, ReActAgent } from "llamaindex";
// Define a function to sum two numbers
function sumNumbers({ a, b }: { a: number; b: number }): number {
return a + b;
}
// Define a function to divide two numbers
function divideNumbers({ a, b }: { a: number; b: number }): number {
return a / b;
}
// Define the parameters of the sum function as a JSON schema
const sumJSON = {
type: "object",
properties: {
a: {
type: "number",
description: "The first number",
},
b: {
type: "number",
description: "The second number",
},
},
required: ["a", "b"],
};
const divideJSON = {
type: "object",
properties: {
a: {
type: "number",
description: "The dividend",
},
b: {
type: "number",
description: "The divisor",
},
},
required: ["a", "b"],
};
async function main() {
// Create a function tool from the sum function
const functionTool = new FunctionTool(sumNumbers, {
name: "sumNumbers",
description: "Use this function to sum two numbers",
parameters: sumJSON,
});
// Create a function tool from the divide function
const functionTool2 = new FunctionTool(divideNumbers, {
name: "divideNumbers",
description: "Use this function to divide two numbers",
parameters: divideJSON,
});
// Create an OpenAIAgent with the function tools
const agent = new ReActAgent({
tools: [functionTool, functionTool2],
verbose: true,
});
const task = agent.createTask("Divide 16 by 2 then add 20");
let count = 0;
while (true) {
const stepOutput = await agent.runStep(task.taskId);
console.log(`Runnning step ${count++}`);
console.log(`======== OUTPUT ==========`);
console.log(stepOutput.output);
console.log(`==========================`);
if (stepOutput.isLast) {
const finalResponse = await agent.finalizeResponse(
task.taskId,
stepOutput,
);
console.log({ finalResponse });
break;
}
}
}
main().then(() => {
console.log("Done");
});
@@ -3,7 +3,6 @@ import { Anthropic } from "llamaindex";
(async () => {
const anthropic = new Anthropic({
apiKey: process.env.ANTHROPIC_API_KEY,
model: "claude-3-opus",
});
const result = await anthropic.chat({
messages: [
-34
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@@ -1,34 +0,0 @@
import { Anthropic, SimpleChatEngine, SimpleChatHistory } from "llamaindex";
import { stdin as input, stdout as output } from "node:process";
import readline from "node:readline/promises";
(async () => {
const llm = new Anthropic({
apiKey: process.env.ANTHROPIC_API_KEY,
model: "claude-3-opus",
});
// chatHistory will store all the messages in the conversation
const chatHistory = new SimpleChatHistory({
messages: [
{
content: "You want to talk in rhymes.",
role: "system",
},
],
});
const chatEngine = new SimpleChatEngine({
llm,
chatHistory,
});
const rl = readline.createInterface({ input, output });
while (true) {
const query = await rl.question("User: ");
process.stdout.write("Assistant: ");
const stream = await chatEngine.chat({ message: query, stream: true });
for await (const chunk of stream) {
process.stdout.write(chunk.response);
}
process.stdout.write("\n");
}
})();
-23
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@@ -1,23 +0,0 @@
import { Anthropic } from "llamaindex";
(async () => {
const anthropic = new Anthropic({
apiKey: process.env.ANTHROPIC_API_KEY,
model: "claude-instant-1.2",
});
const stream = await anthropic.chat({
messages: [
{ content: "You want to talk in rhymes.", role: "system" },
{
content:
"How much wood would a woodchuck chuck if a woodchuck could chuck wood?",
role: "user",
},
],
stream: true,
});
for await (const chunk of stream) {
process.stdout.write(chunk.delta);
}
})();
+1 -7
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@@ -1,4 +1,4 @@
import { OpenAI, OpenAIEmbedding } from "llamaindex";
import { OpenAI } from "llamaindex";
(async () => {
const llm = new OpenAI({ model: "gpt-4-1106-preview", temperature: 0.1 });
@@ -12,10 +12,4 @@ import { OpenAI, OpenAIEmbedding } from "llamaindex";
messages: [{ content: "Tell me a joke.", role: "user" }],
});
console.log(response2.message.content);
// embeddings
const embedModel = new OpenAIEmbedding();
const texts = ["hello", "world"];
const embeddings = await embedModel.getTextEmbeddingsBatch(texts);
console.log(`\nWe have ${embeddings.length} embeddings`);
})();
+2 -3
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@@ -7,9 +7,8 @@ There are two scripts available here: load-docs.ts and query.ts
You'll need a Pinecone account, project, and index. Pinecone does not allow automatic creation of indexes on the free plan,
so this vector store does not check and create the index (unlike, e.g., the PGVectorStore)
Set the **PINECONE_API_KEY** and **PINECONE_ENVIRONMENT** environment variables to match your specific values.
You will likely also need to set **PINECONE_INDEX_NAME**, unless your index is the default value "llama".
By default, all operations take place inside the default namespace '', but you can set **PINECONE_NAMESPACE** to a different value if you need to.
Set the **PINECONE_API_KEY** and **PINECONE_ENVIRONMENT** environment variables to match your specific values. You will likely also need to set **PINECONE_INDEX_NAME**, unless your
index is the default value "llama".
You'll also need a value for OPENAI_API_KEY in your environment.
-2
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@@ -1,3 +1 @@
.turbo
README.md
LICENSE
-17
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@@ -1,22 +1,5 @@
# llamaindex
## 0.1.20
### Patch Changes
- 64683a5: fix: prefix messages always true
- 698cd9c: fix: step wise agent + examples
- 7257751: fixed removeRefDocNode and persist store on delete
- 5116ad8: fix: compatibility issue with Deno
- Updated dependencies [5116ad8]
- @llamaindex/env@0.0.5
## 0.1.19
### Patch Changes
- 026d068: feat: enhance pinecone usage
## 0.1.18
### Patch Changes
-8
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@@ -1,8 +0,0 @@
{
"name": "@llamaindex/core",
"version": "0.1.20",
"exports": "./src/index.ts",
"imports": {
"@llamaindex/env": "jsr:@llamaindex/env@0.0.5"
}
}
+8 -9
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@@ -1,22 +1,22 @@
{
"name": "llamaindex",
"version": "0.1.20",
"version": "0.1.18",
"license": "MIT",
"type": "module",
"dependencies": {
"@anthropic-ai/sdk": "^0.15.0",
"@anthropic-ai/sdk": "^0.13.0",
"@aws-crypto/sha256-js": "^5.2.0",
"@datastax/astra-db-ts": "^0.1.4",
"@llamaindex/cloud": "0.0.4",
"@types/lodash": "^4.14.202",
"@types/node": "^18.19.14",
"@types/papaparse": "^5.3.14",
"@types/pg": "^8.11.0",
"@llamaindex/cloud": "^0.0.1",
"@llamaindex/env": "workspace:*",
"@mistralai/mistralai": "^0.0.10",
"@notionhq/client": "^2.2.14",
"@pinecone-database/pinecone": "^2.0.1",
"@qdrant/js-client-rest": "^1.7.0",
"@types/lodash": "^4.14.202",
"@types/node": "^18.19.14",
"@types/papaparse": "^5.3.14",
"@types/pg": "^8.11.0",
"@xenova/transformers": "^2.15.0",
"assemblyai": "^4.2.2",
"chromadb": "~1.7.3",
@@ -95,8 +95,7 @@
"build:esm": "swc src -d dist --strip-leading-paths --config-file .swcrc",
"build:cjs": "swc src -d dist/cjs --strip-leading-paths --config-file .cjs.swcrc",
"build:type": "pnpm run -w type-check",
"copy": "cp -r ../../README.md ../../LICENSE .",
"postbuild": "pnpm run copy && node -e \"require('fs').writeFileSync('./dist/cjs/package.json', JSON.stringify({ type: 'commonjs' }))\"",
"postbuild": "node -e \"require('fs').writeFileSync('./dist/cjs/package.json', JSON.stringify({ type: 'commonjs' }))\"",
"circular-check": "madge -c ./src/index.ts",
"dev": "concurrently \"pnpm run build:esm --watch\" \"pnpm run build:cjs --watch\" \"pnpm run build:type --watch\""
}
+2
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@@ -37,6 +37,8 @@ export class OpenAIAgent extends AgentRunner {
toolRetriever,
systemPrompt,
}: OpenAIAgentParams) {
prefixMessages = prefixMessages || [];
llm = llm ?? new OpenAI({ model: "gpt-3.5-turbo-0613" });
if (systemPrompt) {
+2 -3
View File
@@ -14,7 +14,7 @@ import { AgentState, BaseAgentRunner, TaskState } from "./types.js";
const validateStepFromArgs = (
taskId: string,
input?: string | null,
input: string,
step?: any,
kwargs?: any,
): TaskStep | undefined => {
@@ -24,7 +24,6 @@ const validateStepFromArgs = (
}
return step;
} else {
if (!input) return;
return new TaskStep(taskId, step, input, kwargs);
}
};
@@ -195,7 +194,7 @@ export class AgentRunner extends BaseAgentRunner {
*/
async runStep(
taskId: string,
input?: string | null,
input: string,
step?: TaskStep,
kwargs: any = {},
): Promise<TaskStepOutput> {
+2 -2
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@@ -161,13 +161,13 @@ export class TaskStep implements ITaskStep {
* @param isLast: isLast
*/
export class TaskStepOutput {
output: any;
output: unknown;
taskStep: TaskStep;
nextSteps: TaskStep[];
isLast: boolean;
constructor(
output: any,
output: unknown,
taskStep: TaskStep,
nextSteps: TaskStep[],
isLast: boolean = false,
+2 -3
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@@ -1,5 +1,4 @@
import type { PlatformApiClient } from "@llamaindex/cloud";
import { getEnv } from "@llamaindex/env";
import type { ClientParams } from "./types.js";
import { DEFAULT_BASE_URL } from "./types.js";
@@ -8,8 +7,8 @@ export async function getClient({
baseUrl,
}: ClientParams = {}): Promise<PlatformApiClient> {
// Get the environment variables or use defaults
baseUrl = baseUrl ?? getEnv("LLAMA_CLOUD_BASE_URL") ?? DEFAULT_BASE_URL;
apiKey = apiKey ?? getEnv("LLAMA_CLOUD_API_KEY");
baseUrl = baseUrl ?? process.env.LLAMA_CLOUD_BASE_URL ?? DEFAULT_BASE_URL;
apiKey = apiKey ?? process.env.LLAMA_CLOUD_API_KEY;
const { PlatformApiClient } = await import("@llamaindex/cloud");
@@ -20,7 +20,6 @@ export enum HuggingFaceEmbeddingModelType {
*/
export class HuggingFaceEmbedding extends BaseEmbedding {
modelType: string = HuggingFaceEmbeddingModelType.XENOVA_ALL_MINILM_L6_V2;
quantized: boolean = true;
private extractor: any;
@@ -32,9 +31,7 @@ export class HuggingFaceEmbedding extends BaseEmbedding {
async getExtractor() {
if (!this.extractor) {
const { pipeline } = await import("@xenova/transformers");
this.extractor = await pipeline("feature-extraction", this.modelType, {
quantized: this.quantized,
});
this.extractor = await pipeline("feature-extraction", this.modelType);
}
return this.extractor;
}
+1 -2
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@@ -1,10 +1,9 @@
import { getEnv } from "@llamaindex/env";
import { OpenAIEmbedding } from "./OpenAIEmbedding.js";
export class FireworksEmbedding extends OpenAIEmbedding {
constructor(init?: Partial<OpenAIEmbedding>) {
const {
apiKey = getEnv("FIREWORKS_API_KEY"),
apiKey = process.env.FIREWORKS_API_KEY,
additionalSessionOptions = {},
model = "nomic-ai/nomic-embed-text-v1.5",
...rest
+1 -2
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@@ -1,10 +1,9 @@
import { getEnv } from "@llamaindex/env";
import { OpenAIEmbedding } from "./OpenAIEmbedding.js";
export class TogetherEmbedding extends OpenAIEmbedding {
constructor(init?: Partial<OpenAIEmbedding>) {
const {
apiKey = getEnv("TOGETHER_API_KEY"),
apiKey = process.env.TOGETHER_API_KEY,
additionalSessionOptions = {},
model = "togethercomputer/m2-bert-80M-32k-retrieval",
...rest
+47 -81
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@@ -1,6 +1,7 @@
import type OpenAILLM from "openai";
import type { ClientOptions as OpenAIClientOptions } from "openai";
import type {
AnthropicStreamToken,
CallbackManager,
Event,
EventType,
@@ -12,7 +13,11 @@ import type { ChatCompletionMessageParam } from "openai/resources/index.js";
import type { LLMOptions } from "portkey-ai";
import { Tokenizers, globalsHelper } from "../GlobalsHelper.js";
import type { AnthropicSession } from "./anthropic.js";
import { getAnthropicSession } from "./anthropic.js";
import {
ANTHROPIC_AI_PROMPT,
ANTHROPIC_HUMAN_PROMPT,
getAnthropicSession,
} from "./anthropic.js";
import type { AzureOpenAIConfig } from "./azure.js";
import {
getAzureBaseUrl,
@@ -255,7 +260,7 @@ export class OpenAI extends BaseLLM {
stream: false,
});
const content = response.choices[0].message?.content ?? null;
const content = response.choices[0].message?.content ?? "";
const kwargsOutput: Record<string, any> = {};
@@ -608,30 +613,12 @@ If a question does not make any sense, or is not factually coherent, explain why
}
}
export const ALL_AVAILABLE_ANTHROPIC_LEGACY_MODELS = {
"claude-2.1": {
contextWindow: 200000,
},
"claude-instant-1.2": {
contextWindow: 100000,
},
};
export const ALL_AVAILABLE_V3_MODELS = {
"claude-3-opus": { contextWindow: 200000 },
"claude-3-sonnet": { contextWindow: 200000 },
};
export const ALL_AVAILABLE_ANTHROPIC_MODELS = {
...ALL_AVAILABLE_ANTHROPIC_LEGACY_MODELS,
...ALL_AVAILABLE_V3_MODELS,
// both models have 100k context window, see https://docs.anthropic.com/claude/reference/selecting-a-model
"claude-2": { contextWindow: 200000 },
"claude-instant-1": { contextWindow: 100000 },
};
const AVAILABLE_ANTHROPIC_MODELS_WITHOUT_DATE: { [key: string]: string } = {
"claude-3-opus": "claude-3-opus-20240229",
"claude-3-sonnet": "claude-3-sonnet-20240229",
} as { [key in keyof typeof ALL_AVAILABLE_ANTHROPIC_MODELS]: string };
/**
* Anthropic LLM implementation
*/
@@ -653,7 +640,7 @@ export class Anthropic extends BaseLLM {
constructor(init?: Partial<Anthropic>) {
super();
this.model = init?.model ?? "claude-3-opus";
this.model = init?.model ?? "claude-2";
this.temperature = init?.temperature ?? 0.1;
this.topP = init?.topP ?? 0.999; // Per Ben Mann
this.maxTokens = init?.maxTokens ?? undefined;
@@ -687,24 +674,21 @@ export class Anthropic extends BaseLLM {
};
}
getModelName = (model: string): string => {
if (Object.keys(AVAILABLE_ANTHROPIC_MODELS_WITHOUT_DATE).includes(model)) {
return AVAILABLE_ANTHROPIC_MODELS_WITHOUT_DATE[model];
}
return model;
};
formatMessages(messages: ChatMessage[]) {
return messages.map((message) => {
if (message.role !== "user" && message.role !== "assistant") {
throw new Error("Unsupported Anthropic role");
}
return {
content: message.content,
role: message.role,
};
});
mapMessagesToPrompt(messages: ChatMessage[]) {
return (
messages.reduce((acc, message) => {
return (
acc +
`${
message.role === "system"
? ""
: message.role === "assistant"
? ANTHROPIC_AI_PROMPT + " "
: ANTHROPIC_HUMAN_PROMPT + " "
}${message.content.trim()}`
);
}, "") + ANTHROPIC_AI_PROMPT
);
}
chat(
@@ -714,67 +698,49 @@ export class Anthropic extends BaseLLM {
async chat(
params: LLMChatParamsNonStreaming | LLMChatParamsStreaming,
): Promise<ChatResponse | AsyncIterable<ChatResponseChunk>> {
let { messages } = params;
const { parentEvent, stream } = params;
let systemPrompt: string | null = null;
const systemMessages = messages.filter(
(message) => message.role === "system",
);
if (systemMessages.length > 0) {
systemPrompt = systemMessages
.map((message) => message.content)
.join("\n");
messages = messages.filter((message) => message.role !== "system");
}
const { messages, parentEvent, stream } = params;
//Streaming
if (stream) {
return this.streamChat(messages, parentEvent, systemPrompt);
return this.streamChat(messages, parentEvent);
}
//Non-streaming
const response = await this.session.anthropic.messages.create({
model: this.getModelName(this.model),
messages: this.formatMessages(messages),
max_tokens: this.maxTokens ?? 4096,
const response = await this.session.anthropic.completions.create({
model: this.model,
prompt: this.mapMessagesToPrompt(messages),
max_tokens_to_sample: this.maxTokens ?? 100000,
temperature: this.temperature,
top_p: this.topP,
...(systemPrompt && { system: systemPrompt }),
});
return {
message: { content: response.content[0].text, role: "assistant" },
message: { content: response.completion.trimStart(), role: "assistant" },
//^ We're trimming the start because Anthropic often starts with a space in the response
// That space will be re-added when we generate the next prompt.
};
}
protected async *streamChat(
messages: ChatMessage[],
parentEvent?: Event | undefined,
systemPrompt?: string | null,
): AsyncIterable<ChatResponseChunk> {
const stream = await this.session.anthropic.messages.create({
model: this.getModelName(this.model),
messages: this.formatMessages(messages),
max_tokens: this.maxTokens ?? 4096,
temperature: this.temperature,
top_p: this.topP,
stream: true,
...(systemPrompt && { system: systemPrompt }),
});
// AsyncIterable<AnthropicStreamToken>
const stream: AsyncIterable<AnthropicStreamToken> =
await this.session.anthropic.completions.create({
model: this.model,
prompt: this.mapMessagesToPrompt(messages),
max_tokens_to_sample: this.maxTokens ?? 100000,
temperature: this.temperature,
top_p: this.topP,
stream: true,
});
let idx_counter: number = 0;
for await (const part of stream) {
const content =
part.type === "content_block_delta" ? part.delta.text : null;
if (typeof content !== "string") continue;
//TODO: LLM Stream Callback, pending re-work.
idx_counter++;
yield { delta: content };
yield { delta: part.completion };
}
return;
}
+3 -2
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@@ -1,6 +1,5 @@
import type { ClientOptions } from "@anthropic-ai/sdk";
import Anthropic, { AI_PROMPT, HUMAN_PROMPT } from "@anthropic-ai/sdk";
import { getEnv } from "@llamaindex/env";
import _ from "lodash";
export class AnthropicSession {
@@ -8,7 +7,9 @@ export class AnthropicSession {
constructor(options: ClientOptions = {}) {
if (!options.apiKey) {
options.apiKey = getEnv("ANTHROPIC_API_KEY");
if (typeof process !== undefined) {
options.apiKey = process.env.ANTHROPIC_API_KEY;
}
}
if (!options.apiKey) {
+14 -16
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@@ -1,5 +1,3 @@
import { getEnv } from "@llamaindex/env";
export interface AzureOpenAIConfig {
apiKey?: string;
endpoint?: string;
@@ -69,24 +67,24 @@ export function getAzureConfigFromEnv(
return {
apiKey:
init?.apiKey ??
getEnv("AZURE_OPENAI_KEY") ?? // From Azure docs
getEnv("OPENAI_API_KEY") ?? // Python compatible
getEnv("AZURE_OPENAI_API_KEY"), // LCJS compatible
process.env.AZURE_OPENAI_KEY ?? // From Azure docs
process.env.OPENAI_API_KEY ?? // Python compatible
process.env.AZURE_OPENAI_API_KEY, // LCJS compatible
endpoint:
init?.endpoint ??
getEnv("AZURE_OPENAI_ENDPOINT") ?? // From Azure docs
getEnv("OPENAI_API_BASE") ?? // Python compatible
getEnv("AZURE_OPENAI_API_INSTANCE_NAME"), // LCJS compatible
process.env.AZURE_OPENAI_ENDPOINT ?? // From Azure docs
process.env.OPENAI_API_BASE ?? // Python compatible
process.env.AZURE_OPENAI_API_INSTANCE_NAME, // LCJS compatible
apiVersion:
init?.apiVersion ??
getEnv("AZURE_OPENAI_API_VERSION") ?? // From Azure docs
getEnv("OPENAI_API_VERSION") ?? // Python compatible
getEnv("AZURE_OPENAI_API_VERSION") ?? // LCJS compatible
process.env.AZURE_OPENAI_API_VERSION ?? // From Azure docs
process.env.OPENAI_API_VERSION ?? // Python compatible
process.env.AZURE_OPENAI_API_VERSION ?? // LCJS compatible
DEFAULT_API_VERSION,
deploymentName:
init?.deploymentName ??
getEnv("AZURE_OPENAI_DEPLOYMENT") ?? // From Azure docs
getEnv("AZURE_OPENAI_API_DEPLOYMENT_NAME") ?? // LCJS compatible
process.env.AZURE_OPENAI_DEPLOYMENT ?? // From Azure docs
process.env.AZURE_OPENAI_API_DEPLOYMENT_NAME ?? // LCJS compatible
init?.model, // Fall back to model name, Python compatible
};
}
@@ -115,8 +113,8 @@ export function getAzureModel(openAIModel: string) {
export function shouldUseAzure() {
return (
getEnv("AZURE_OPENAI_ENDPOINT") ||
getEnv("AZURE_OPENAI_API_INSTANCE_NAME") ||
getEnv("OPENAI_API_TYPE") === "azure"
process.env.AZURE_OPENAI_ENDPOINT ||
process.env.AZURE_OPENAI_API_INSTANCE_NAME ||
process.env.OPENAI_API_TYPE === "azure"
);
}
+1 -2
View File
@@ -1,10 +1,9 @@
import { getEnv } from "@llamaindex/env";
import { OpenAI } from "./LLM.js";
export class FireworksLLM extends OpenAI {
constructor(init?: Partial<OpenAI>) {
const {
apiKey = getEnv("FIREWORKS_API_KEY"),
apiKey = process.env.FIREWORKS_API_KEY,
additionalSessionOptions = {},
model = "accounts/fireworks/models/mixtral-8x7b-instruct",
...rest
+1 -2
View File
@@ -1,10 +1,9 @@
import { getEnv } from "@llamaindex/env";
import { OpenAI } from "./LLM.js";
export class Groq extends OpenAI {
constructor(init?: Partial<OpenAI>) {
const {
apiKey = getEnv("GROQ_API_KEY"),
apiKey = process.env.GROQ_API_KEY,
additionalSessionOptions = {},
model = "mixtral-8x7b-32768",
...rest
+3 -2
View File
@@ -1,4 +1,3 @@
import { getEnv } from "@llamaindex/env";
import type {
CallbackManager,
Event,
@@ -28,7 +27,9 @@ export class MistralAISession {
if (init?.apiKey) {
this.apiKey = init?.apiKey;
} else {
this.apiKey = getEnv("MISTRAL_API_KEY");
if (typeof process !== undefined) {
this.apiKey = process.env.MISTRAL_API_KEY;
}
}
if (!this.apiKey) {
throw new Error("Set Mistral API key in MISTRAL_API_KEY env variable"); // Overriding MistralAI package's error message
-5
View File
@@ -37,18 +37,14 @@ export class Ollama extends BaseEmbedding implements LLM {
additionalChatOptions?: Record<string, unknown>;
callbackManager?: CallbackManager;
protected modelMetadata: Partial<LLMMetadata>;
constructor(
init: Partial<Ollama> & {
// model is required
model: string;
modelMetadata?: Partial<LLMMetadata>;
},
) {
super();
this.model = init.model;
this.modelMetadata = init.modelMetadata ?? {};
Object.assign(this, init);
}
@@ -60,7 +56,6 @@ export class Ollama extends BaseEmbedding implements LLM {
maxTokens: undefined,
contextWindow: this.contextWindow,
tokenizer: undefined,
...this.modelMetadata,
};
}
+3 -2
View File
@@ -1,4 +1,3 @@
import { getEnv } from "@llamaindex/env";
import _ from "lodash";
import type { ClientOptions } from "openai";
import OpenAI from "openai";
@@ -14,7 +13,9 @@ export class OpenAISession {
constructor(options: ClientOptions & { azure?: boolean } = {}) {
if (!options.apiKey) {
options.apiKey = getEnv("OPENAI_API_KEY");
if (typeof process !== undefined) {
options.apiKey = process.env.OPENAI_API_KEY;
}
}
if (!options.apiKey) {
+12 -3
View File
@@ -1,8 +1,17 @@
import { getEnv } from "@llamaindex/env";
import _ from "lodash";
import type { LLMOptions } from "portkey-ai";
import { Portkey } from "portkey-ai";
export const readEnv = (
env: string,
default_val?: string,
): string | undefined => {
if (typeof process !== "undefined") {
return process.env?.[env] ?? default_val;
}
return default_val;
};
interface PortkeyOptions {
apiKey?: string;
baseURL?: string;
@@ -15,11 +24,11 @@ export class PortkeySession {
constructor(options: PortkeyOptions = {}) {
if (!options.apiKey) {
options.apiKey = getEnv("PORTKEY_API_KEY");
options.apiKey = readEnv("PORTKEY_API_KEY");
}
if (!options.baseURL) {
options.baseURL = getEnv("PORTKEY_BASE_URL") ?? "https://api.portkey.ai";
options.baseURL = readEnv("PORTKEY_BASE_URL", "https://api.portkey.ai");
}
this.portkey = new Portkey({});
+2 -3
View File
@@ -1,4 +1,3 @@
import { getEnv } from "@llamaindex/env";
import Replicate from "replicate";
export class ReplicateSession {
@@ -8,8 +7,8 @@ export class ReplicateSession {
constructor(replicateKey: string | null = null) {
if (replicateKey) {
this.replicateKey = replicateKey;
} else if (getEnv("REPLICATE_API_TOKEN")) {
this.replicateKey = getEnv("REPLICATE_API_TOKEN") as string;
} else if (process.env.REPLICATE_API_TOKEN) {
this.replicateKey = process.env.REPLICATE_API_TOKEN;
} else {
throw new Error(
"Set Replicate token in REPLICATE_API_TOKEN env variable",
+1 -2
View File
@@ -1,10 +1,9 @@
import { getEnv } from "@llamaindex/env";
import { OpenAI } from "./LLM.js";
export class TogetherLLM extends OpenAI {
constructor(init?: Partial<OpenAI>) {
const {
apiKey = getEnv("TOGETHER_API_KEY"),
apiKey = process.env.TOGETHER_API_KEY,
additionalSessionOptions = {},
model = "togethercomputer/llama-2-7b-chat",
...rest
@@ -1,4 +1,3 @@
import { getEnv } from "@llamaindex/env";
import type {
BaseServiceParams,
SubtitleFormat,
@@ -29,7 +28,7 @@ abstract class AssemblyAIReader implements BaseReader {
options = {};
}
if (!options.apiKey) {
options.apiKey = getEnv("ASSEMBLYAI_API_KEY");
options.apiKey = process.env.ASSEMBLYAI_API_KEY;
}
if (!options.apiKey) {
throw new Error(
@@ -1,4 +1,5 @@
import { defaultFS, getEnv, type GenericFileSystem } from "@llamaindex/env";
import type { GenericFileSystem } from "@llamaindex/env";
import { defaultFS } from "@llamaindex/env";
import { Document } from "../Node.js";
import type { FileReader } from "./type.js";
@@ -23,7 +24,7 @@ export class LlamaParseReader implements FileReader {
constructor(params: Partial<LlamaParseReader> = {}) {
Object.assign(this, params);
params.apiKey = params.apiKey ?? getEnv("LLAMA_CLOUD_API_KEY");
params.apiKey = params.apiKey ?? process.env.LLAMA_CLOUD_API_KEY;
if (!params.apiKey) {
throw new Error(
"API Key is required for LlamaParseReader. Please pass the apiKey parameter or set the LLAMA_CLOUD_API_KEY environment variable.",
@@ -1,4 +1,4 @@
import _ from "lodash";
import _, * as lodash from "lodash";
import type { BaseNode } from "../../Node.js";
import { ObjectType } from "../../Node.js";
import { DEFAULT_NAMESPACE } from "../constants.js";
@@ -123,10 +123,10 @@ export class KVDocumentStore extends BaseDocumentStore {
const refDocInfo = await this.kvstore.get(refDocId, this.refDocCollection);
if (!_.isNil(refDocInfo)) {
!_.pull(refDocInfo.nodeIds, docId);
lodash.pull(refDocInfo.docIds, docId);
if (refDocInfo.nodeIds.length > 0) {
this.kvstore.put(refDocId, refDocInfo, this.refDocCollection);
if (refDocInfo.docIds.length > 0) {
this.kvstore.put(refDocId, refDocInfo.toDict(), this.refDocCollection);
}
this.kvstore.delete(refDocId, this.metadataCollection);
}
@@ -54,9 +54,6 @@ export class SimpleKVStore extends BaseKVStore {
): Promise<boolean> {
if (key in this.data[collection]) {
delete this.data[collection][key];
if (this.persistPath) {
await this.persist(this.persistPath, this.fs);
}
return true;
}
return false;
@@ -1,6 +1,5 @@
import { AstraDB } from "@datastax/astra-db-ts";
import type { Collection } from "@datastax/astra-db-ts/dist/collections";
import { getEnv } from "@llamaindex/env";
import type { BaseNode } from "../../Node.js";
import { MetadataMode } from "../../Node.js";
import type {
@@ -35,8 +34,9 @@ export class AstraDBVectorStore implements VectorStore {
if (init?.astraDBClient) {
this.astraDBClient = init.astraDBClient;
} else {
const token = init?.params?.token ?? getEnv("ASTRA_DB_APPLICATION_TOKEN");
const endpoint = init?.params?.endpoint ?? getEnv("ASTRA_DB_ENDPOINT");
const token =
init?.params?.token ?? process.env.ASTRA_DB_APPLICATION_TOKEN;
const endpoint = init?.params?.endpoint ?? process.env.ASTRA_DB_ENDPOINT;
if (!token) {
throw new Error(
@@ -48,7 +48,7 @@ export class AstraDBVectorStore implements VectorStore {
}
const namespace =
init?.params?.namespace ??
getEnv("ASTRA_DB_NAMESPACE") ??
process.env.ASTRA_DB_NAMESPACE ??
"default_keyspace";
this.astraDBClient = new AstraDB(token, endpoint, namespace);
}
@@ -1,4 +1,3 @@
import { getEnv } from "@llamaindex/env";
import type { BulkWriteOptions, Collection } from "mongodb";
import { MongoClient } from "mongodb";
import type { BaseNode } from "../../Node.js";
@@ -45,7 +44,7 @@ export class MongoDBAtlasVectorSearch implements VectorStore {
if (init.mongodbClient) {
this.mongodbClient = init.mongodbClient;
} else {
const mongoUri = getEnv("MONGODB_URI");
const mongoUri = process.env.MONGODB_URI;
if (!mongoUri) {
throw new Error(
"Must specify MONGODB_URI via env variable if not directly passing in client.",
@@ -1,4 +1,5 @@
import type pg from "pg";
import pg from "pg";
import pgvector from "pgvector/pg";
import type {
VectorStore,
@@ -82,18 +83,16 @@ export class PGVectorStore implements VectorStore {
private async getDb(): Promise<pg.Client> {
if (!this.db) {
try {
const { Client } = await import("pg");
const { registerType } = await import("pgvector/pg");
// Create DB connection
// Read connection params from env - see comment block above
const db = new Client({
const db = new pg.Client({
connectionString: this.connectionString,
});
await db.connect();
// Check vector extension
db.query("CREATE EXTENSION IF NOT EXISTS vector");
await registerType(db);
await pgvector.registerType(db);
// Check schema, table(s), index(es)
await this.checkSchema(db);
@@ -6,21 +6,19 @@ import type {
VectorStoreQueryResult,
} from "./types.js";
import { getEnv, type GenericFileSystem } from "@llamaindex/env";
import type { GenericFileSystem } from "@llamaindex/env";
import type {
FetchResponse,
Index,
ScoredPineconeRecord,
} from "@pinecone-database/pinecone";
import { type Pinecone } from "@pinecone-database/pinecone";
import { Pinecone } from "@pinecone-database/pinecone";
import type { BaseNode, Metadata } from "../../Node.js";
import { metadataDictToNode, nodeToMetadata } from "./utils.js";
type PineconeParams = {
indexName?: string;
chunkSize?: number;
namespace?: string;
textKey?: string;
};
/**
@@ -39,23 +37,18 @@ export class PineconeVectorStore implements VectorStore {
*/
db?: Pinecone;
indexName: string;
namespace: string;
chunkSize: number;
textKey: string;
constructor(params?: PineconeParams) {
this.indexName =
params?.indexName ?? getEnv("PINECONE_INDEX_NAME") ?? "llama";
this.namespace = params?.namespace ?? getEnv("PINECONE_NAMESPACE") ?? "";
params?.indexName ?? process.env.PINECONE_INDEX_NAME ?? "llama";
this.chunkSize =
params?.chunkSize ??
Number.parseInt(getEnv("PINECONE_CHUNK_SIZE") ?? "100");
this.textKey = params?.textKey ?? "text";
Number.parseInt(process.env.PINECONE_CHUNK_SIZE ?? "100");
}
private async getDb(): Promise<Pinecone> {
if (!this.db) {
const { Pinecone } = await import("@pinecone-database/pinecone");
this.db = await new Pinecone();
}
@@ -155,23 +148,24 @@ export class PineconeVectorStore implements VectorStore {
};
const idx = await this.index();
const results = await idx.namespace(this.namespace).query(options);
const results = await idx.query(options);
const idList = results.matches.map((row) => row.id);
const records: FetchResponse<any> = await idx
.namespace(this.namespace)
.fetch(idList);
const records: FetchResponse<any> = await idx.fetch(idList);
const rows = Object.values(records.records);
const nodes = rows.map((row) => {
const node = metadataDictToNode(row.metadata, {
const metadata = this.metaWithoutText(row.metadata);
const text = this.textFromResultRow(row);
const node = metadataDictToNode(metadata, {
fallback: {
id: row.id,
text: this.textFromResultRow(row),
metadata: this.metaWithoutText(row.metadata),
text,
metadata,
embedding: row.values,
},
});
node.setContent(text);
return node;
});
@@ -205,12 +199,12 @@ export class PineconeVectorStore implements VectorStore {
}
textFromResultRow(row: ScoredPineconeRecord<Metadata>): string {
return row.metadata?.[this.textKey] ?? "";
return row.metadata?.text ?? "";
}
metaWithoutText(meta: Metadata): any {
return Object.keys(meta)
.filter((key) => key != this.textKey)
.filter((key) => key != "text")
.reduce((acc: any, key: string) => {
acc[key] = meta[key];
return acc;
@@ -82,9 +82,6 @@ export class SimpleVectorStore implements VectorStore {
delete this.data.embeddingDict[textId];
delete this.data.textIdToRefDocId[textId];
}
if (this.persistPath) {
await this.persist(this.persistPath, this.fs);
}
return Promise.resolve();
}
+1 -9
View File
@@ -6,13 +6,5 @@
"moduleResolution": "node16",
"target": "ESNext"
},
"include": ["./**/*.ts"],
"references": [
{
"path": "../../core/tsconfig.json"
},
{
"path": "../../env/tsconfig.json"
}
]
"include": ["./**/*.ts"]
}
+1 -7
View File
@@ -3,7 +3,6 @@
"compilerOptions": {
"rootDir": "./src",
"outDir": "./dist/type",
"tsBuildInfoFile": "./dist/.tsbuildinfo",
"emitDeclarationOnly": true,
"module": "node16",
"moduleResolution": "node16",
@@ -11,10 +10,5 @@
"strict": true
},
"include": ["./src"],
"exclude": ["node_modules"],
"references": [
{
"path": "../env/tsconfig.json"
}
]
"exclude": ["node_modules"]
}
-2
View File
@@ -32,7 +32,6 @@ export async function createApp({
eslint,
frontend,
openAiKey,
llamaCloudKey,
model,
communityProjectPath,
llamapack,
@@ -78,7 +77,6 @@ export async function createApp({
isOnline,
eslint,
openAiKey,
llamaCloudKey,
model,
communityProjectPath,
llamapack,
-6
View File
@@ -26,7 +26,6 @@ const createEnvLocalFile = async (
root: string,
opts?: {
openAiKey?: string;
llamaCloudKey?: string;
vectorDb?: TemplateVectorDB;
model?: string;
framework?: TemplateFramework;
@@ -47,10 +46,6 @@ const createEnvLocalFile = async (
content += `OPENAI_API_KEY=${opts?.openAiKey}\n`;
}
if (opts?.llamaCloudKey) {
content += `LLAMA_CLOUD_API_KEY=${opts?.llamaCloudKey}\n`;
}
switch (opts?.vectorDb) {
case "mongo": {
content += `# For generating a connection URI, see https://www.mongodb.com/docs/guides/atlas/connection-string\n`;
@@ -210,7 +205,6 @@ export const installTemplate = async (
// Copy the environment file to the target directory.
await createEnvLocalFile(props.root, {
openAiKey: props.openAiKey,
llamaCloudKey: props.llamaCloudKey,
vectorDb: props.vectorDb,
model: props.model,
framework: props.framework,
+5 -9
View File
@@ -8,7 +8,6 @@ import { templatesDir } from "./dir";
import { isPoetryAvailable, tryPoetryInstall } from "./poetry";
import { Tool } from "./tools";
import {
FileSourceConfig,
InstallTemplateArgs,
TemplateDataSource,
TemplateVectorDB,
@@ -245,16 +244,13 @@ export const installPythonTemplate = async ({
const dataSourceType = dataSource?.type;
if (dataSourceType !== undefined && dataSourceType !== "none") {
let loaderFolder: string;
if (dataSourceType === "file" || dataSourceType === "folder") {
const dataSourceConfig = dataSource?.config as FileSourceConfig;
loaderFolder = dataSourceConfig.useLlamaParse ? "llama_parse" : "file";
} else {
loaderFolder = dataSourceType;
}
const loaderPath =
dataSourceType === "folder"
? path.join(compPath, "loaders", "python", "file")
: path.join(compPath, "loaders", "python", dataSourceType);
await copy("**", enginePath, {
parents: true,
cwd: path.join(compPath, "loaders", "python", loaderFolder),
cwd: loaderPath,
});
}
}
-2
View File
@@ -15,7 +15,6 @@ export type TemplateDataSourceType = "none" | "file" | "folder" | "web";
// Config for both file and folder
export type FileSourceConfig = {
path?: string;
useLlamaParse?: boolean;
};
export type WebSourceConfig = {
baseUrl?: string;
@@ -36,7 +35,6 @@ export interface InstallTemplateArgs {
eslint: boolean;
customApiPath?: string;
openAiKey?: string;
llamaCloudKey?: string;
forBackend?: string;
model: string;
communityProjectPath?: string;
-16
View File
@@ -154,18 +154,6 @@ const program = new Commander.Command(packageJson.name)
`
Specify the tools you want to use by providing a comma-separated list. For example, 'wikipedia.WikipediaToolSpec,google.GoogleSearchToolSpec'. Use 'none' to not using any tools.
`,
)
.option(
"--llama-parse",
`
Enable LlamaParse.
`,
)
.option(
"--llama-cloud-key <key>",
`
Provide a LlamaCloud API key.
`,
)
.allowUnknownOption()
@@ -183,9 +171,6 @@ if (process.argv.includes("--tools")) {
program.tools = getTools(program.tools.split(","));
}
}
if (process.argv.includes("--no-llama-parse")) {
program.llamaParse = false;
}
const packageManager = !!program.useNpm
? "npm"
@@ -279,7 +264,6 @@ async function run(): Promise<void> {
eslint: program.eslint,
frontend: program.frontend,
openAiKey: program.openAiKey,
llamaCloudKey: program.llamaCloudKey,
model: program.model,
communityProjectPath: program.communityProjectPath,
llamapack: program.llamapack,
+2 -65
View File
@@ -5,11 +5,7 @@ import path from "path";
import { blue, green, red } from "picocolors";
import prompts from "prompts";
import { InstallAppArgs } from "./create-app";
import {
FileSourceConfig,
TemplateDataSourceType,
TemplateFramework,
} from "./helpers";
import { TemplateDataSourceType, TemplateFramework } from "./helpers";
import { COMMUNITY_OWNER, COMMUNITY_REPO } from "./helpers/constant";
import { templatesDir } from "./helpers/dir";
import { getAvailableLlamapackOptions } from "./helpers/llama-pack";
@@ -19,7 +15,7 @@ import { supportedTools, toolsRequireConfig } from "./helpers/tools";
export type QuestionArgs = Omit<
InstallAppArgs,
"appPath" | "packageManager"
> & { files?: string; llamaParse?: boolean };
> & { files?: string };
const supportedContextFileTypes = [
".pdf",
".doc",
@@ -67,7 +63,6 @@ const defaults: QuestionArgs = {
eslint: true,
frontend: false,
openAiKey: "",
llamaCloudKey: "",
model: "gpt-3.5-turbo",
communityProjectPath: "",
llamapack: "",
@@ -526,64 +521,6 @@ export const askQuestions = async (
}
}
if (
program.dataSource?.type === "file" ||
(program.dataSource?.type === "folder" && program.framework === "fastapi")
) {
if (ciInfo.isCI) {
program.llamaCloudKey = getPrefOrDefault("llamaCloudKey");
} else {
const dataSourceConfig = program.dataSource.config as FileSourceConfig;
dataSourceConfig.useLlamaParse = program.llamaParse;
// Is pdf file selected as data source or is it a folder data source
const askingLlamaParse =
dataSourceConfig.useLlamaParse === undefined &&
(program.dataSource.type === "folder"
? true
: dataSourceConfig.path &&
path.extname(dataSourceConfig.path) === ".pdf");
// Ask if user wants to use LlamaParse
if (askingLlamaParse) {
const { useLlamaParse } = await prompts(
{
type: "toggle",
name: "useLlamaParse",
message:
"Would you like to use LlamaParse (improved parser for RAG - requires API key)?",
initial: true,
active: "yes",
inactive: "no",
},
handlers,
);
dataSourceConfig.useLlamaParse = useLlamaParse;
program.dataSource.config = dataSourceConfig;
}
// Ask for LlamaCloud API key
if (
dataSourceConfig.useLlamaParse &&
program.llamaCloudKey === undefined
) {
const { llamaCloudKey } = await prompts(
{
type: "text",
name: "llamaCloudKey",
message: "Please provide your LlamaIndex Cloud API key:",
validate: (value) =>
value
? true
: "LlamaIndex Cloud API key is required. You can get it from: https://cloud.llamaindex.ai/api-key",
},
handlers,
);
program.llamaCloudKey = llamaCloudKey;
}
}
}
if (program.dataSource?.type === "web" && program.framework === "fastapi") {
let { baseUrl } = await prompts(
{
@@ -1,6 +1,6 @@
from llama_index.core.readers import SimpleDirectoryReader
DATA_DIR = "data" # directory containing the documents
DATA_DIR = "data" # directory to cache the generated index
def get_documents():
@@ -1,14 +0,0 @@
from llama_parse import LlamaParse
from llama_index.core import SimpleDirectoryReader
DATA_DIR = "data" # directory containing the documents
def get_documents():
parser = LlamaParse(
result_type="markdown",
verbose=True,
)
reader = SimpleDirectoryReader(DATA_DIR, file_extractor={".pdf": parser})
return reader.load_data()
-6
View File
@@ -1,11 +1,5 @@
# @llamaindex/env
## 0.0.5
### Patch Changes
- 5116ad8: fix: compatibility issue with Deno
## 0.0.4
### Patch Changes
-8
View File
@@ -1,8 +0,0 @@
{
"name": "@llamaindex/env",
"version": "0.0.5",
"exports": {
".": "./src/index.ts",
"./type": "./src/type.ts"
}
}
+1 -1
View File
@@ -1,7 +1,7 @@
{
"name": "@llamaindex/env",
"description": "environment wrapper",
"version": "0.0.5",
"version": "0.0.4",
"type": "module",
"types": "dist/type/index.d.ts",
"main": "dist/cjs/index.js",
-1
View File
@@ -39,4 +39,3 @@ export function randomUUID(): string {
return crypto.randomUUID();
}
export * from "./type.js";
export { getEnv } from "./utils.js";
+1 -2
View File
@@ -34,6 +34,5 @@ export const defaultFS: CompleteFileSystem = {
stat: fs.stat,
};
export type * from "./type.js";
export { getEnv } from "./utils.js";
export * from "./type.js";
export { EOL, ok, path, randomUUID };
+2 -1
View File
@@ -58,8 +58,9 @@ export class InMemoryFileSystem implements CompleteFileSystem {
}
}
async mkdir(path: string): Promise<undefined> {
async mkdir(path: string) {
this.files[path] = _.get(this.files, path, null);
return undefined;
}
async readdir(path: string): Promise<string[]> {
-12
View File
@@ -1,12 +0,0 @@
export function getEnv(name: string): string | undefined {
if (typeof process === "undefined" || typeof process.env === "undefined") {
// @ts-expect-error
if (typeof Deno === "undefined") {
throw new Error("Current environment is not supported");
} else {
// @ts-expect-error
return Deno.env.get(name);
}
}
return process.env[name];
}
-1
View File
@@ -3,7 +3,6 @@
"compilerOptions": {
"rootDir": "./src",
"outDir": "./dist/type",
"tsBuildInfoFile": "./dist/.tsbuildinfo",
"emitDeclarationOnly": true,
"module": "node16",
"moduleResolution": "node16",
-1
View File
@@ -36,7 +36,6 @@ module.exports = {
"PINECONE_INDEX_NAME",
"PINECONE_CHUNK_SIZE",
"PINECONE_INDEX_NAME",
"PINECONE_NAMESPACE",
"AZURE_OPENAI_API_KEY",
"AZURE_OPENAI_API_INSTANCE_NAME",
+87 -200
View File
@@ -53,7 +53,7 @@ importers:
version: link:../../packages/env
'@mdx-js/react':
specifier: ^3.0.0
version: 3.0.0(@types/react@18.2.61)(react@18.2.0)
version: 3.0.0(@types/react@18.2.55)(react@18.2.0)
clsx:
specifier: ^2.1.0
version: 2.1.0
@@ -65,7 +65,7 @@ importers:
version: 2.3.1(react@18.2.0)
raw-loader:
specifier: ^4.0.2
version: 4.0.2(webpack@5.90.3)
version: 4.0.2(webpack@5.90.1)
react:
specifier: ^18.2.0
version: 18.2.0
@@ -78,10 +78,10 @@ importers:
version: 3.1.0(react-dom@18.2.0)(react@18.2.0)
'@docusaurus/preset-classic':
specifier: ^3.1.1
version: 3.1.1(@algolia/client-search@4.22.1)(@types/react@18.2.61)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0)(typescript@5.3.3)
version: 3.1.1(@algolia/client-search@4.22.1)(@types/react@18.2.55)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0)(typescript@5.3.3)
'@docusaurus/theme-classic':
specifier: ^3.1.1
version: 3.1.1(@types/react@18.2.61)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
version: 3.1.1(@types/react@18.2.55)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
'@docusaurus/types':
specifier: ^3.1.1
version: 3.1.1(react-dom@18.2.0)(react@18.2.0)
@@ -160,8 +160,8 @@ importers:
packages/core:
dependencies:
'@anthropic-ai/sdk':
specifier: ^0.15.0
version: 0.15.0
specifier: ^0.13.0
version: 0.13.0
'@aws-crypto/sha256-js':
specifier: ^5.2.0
version: 5.2.0
@@ -169,8 +169,8 @@ importers:
specifier: ^0.1.4
version: 0.1.4
'@llamaindex/cloud':
specifier: 0.0.4
version: 0.0.4
specifier: ^0.0.1
version: 0.0.1
'@llamaindex/env':
specifier: workspace:*
version: link:../env
@@ -406,16 +406,16 @@ importers:
dependencies:
eslint-config-next:
specifier: ^13.5.6
version: 13.5.6(eslint@8.57.0)(typescript@5.3.3)
version: 13.5.6(eslint@8.56.0)(typescript@5.3.3)
eslint-config-prettier:
specifier: ^8.10.0
version: 8.10.0(eslint@8.57.0)
version: 8.10.0(eslint@8.56.0)
eslint-config-turbo:
specifier: ^1.11.3
version: 1.11.3(eslint@8.57.0)
version: 1.11.3(eslint@8.56.0)
eslint-plugin-react:
specifier: 7.28.0
version: 7.28.0(eslint@8.57.0)
version: 7.28.0(eslint@8.56.0)
devDependencies:
next:
specifier: ^13.5.6
@@ -574,8 +574,8 @@ packages:
'@jridgewell/gen-mapping': 0.3.3
'@jridgewell/trace-mapping': 0.3.22
/@anthropic-ai/sdk@0.15.0:
resolution: {integrity: sha512-QMNEFcwGGB64oEIL+U9b+mxSbat5TCdNxvQVV0qCNGQvg/nlnbOmq2/x/0mKhuKD0n5bioL75oCkTbQaAgyYtw==}
/@anthropic-ai/sdk@0.13.0:
resolution: {integrity: sha512-wn315W4tCfCO+Z6FMa/67HgdgaWbjs4ie0Zbx5A6lq8RPEA3sEDknYzw0gCIrSlnSgRHxvUP/bT9KncFmOrmTg==}
dependencies:
'@types/node': 18.19.14
'@types/node-fetch': 2.6.9
@@ -2055,7 +2055,7 @@ packages:
resolution: {integrity: sha512-SPiDHaWKQZpwR2siD0KQUwlStvIAnEyK6tAE2h2Wuoq8ue9skzhlyVQ1ddzOxX6khULnAALDiR/isSF3bnuciA==}
dev: true
/@docsearch/react@3.5.2(@algolia/client-search@4.22.1)(@types/react@18.2.61)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0):
/@docsearch/react@3.5.2(@algolia/client-search@4.22.1)(@types/react@18.2.55)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0):
resolution: {integrity: sha512-9Ahcrs5z2jq/DcAvYtvlqEBHImbm4YJI8M9y0x6Tqg598P40HTEkX7hsMcIuThI+hTFxRGZ9hll0Wygm2yEjng==}
peerDependencies:
'@types/react': '>= 16.8.0 < 19.0.0'
@@ -2075,7 +2075,7 @@ packages:
'@algolia/autocomplete-core': 1.9.3(@algolia/client-search@4.22.1)(algoliasearch@4.22.1)(search-insights@2.13.0)
'@algolia/autocomplete-preset-algolia': 1.9.3(@algolia/client-search@4.22.1)(algoliasearch@4.22.1)
'@docsearch/css': 3.5.2
'@types/react': 18.2.61
'@types/react': 18.2.55
algoliasearch: 4.22.1
react: 18.2.0
react-dom: 18.2.0(react@18.2.0)
@@ -2581,7 +2581,7 @@ packages:
- webpack-cli
dev: true
/@docusaurus/preset-classic@3.1.1(@algolia/client-search@4.22.1)(@types/react@18.2.61)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0)(typescript@5.3.3):
/@docusaurus/preset-classic@3.1.1(@algolia/client-search@4.22.1)(@types/react@18.2.55)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0)(typescript@5.3.3):
resolution: {integrity: sha512-jG4ys/hWYf69iaN/xOmF+3kjs4Nnz1Ay3CjFLDtYa8KdxbmUhArA9HmP26ru5N0wbVWhY+6kmpYhTJpez5wTyg==}
engines: {node: '>=18.0'}
peerDependencies:
@@ -2597,9 +2597,9 @@ packages:
'@docusaurus/plugin-google-gtag': 3.1.1(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
'@docusaurus/plugin-google-tag-manager': 3.1.1(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
'@docusaurus/plugin-sitemap': 3.1.1(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
'@docusaurus/theme-classic': 3.1.1(@types/react@18.2.61)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
'@docusaurus/theme-classic': 3.1.1(@types/react@18.2.55)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
'@docusaurus/theme-common': 3.1.1(@docusaurus/types@3.1.1)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
'@docusaurus/theme-search-algolia': 3.1.1(@algolia/client-search@4.22.1)(@docusaurus/types@3.1.1)(@types/react@18.2.61)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0)(typescript@5.3.3)
'@docusaurus/theme-search-algolia': 3.1.1(@algolia/client-search@4.22.1)(@docusaurus/types@3.1.1)(@types/react@18.2.55)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0)(typescript@5.3.3)
'@docusaurus/types': 3.1.1(react-dom@18.2.0)(react@18.2.0)
react: 18.2.0
react-dom: 18.2.0(react@18.2.0)
@@ -2630,7 +2630,7 @@ packages:
peerDependencies:
react: '*'
dependencies:
'@types/react': 18.2.48
'@types/react': 18.2.55
prop-types: 15.8.1
react: 18.2.0
@@ -2647,7 +2647,7 @@ packages:
- supports-color
dev: false
/@docusaurus/theme-classic@3.1.1(@types/react@18.2.61)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3):
/@docusaurus/theme-classic@3.1.1(@types/react@18.2.55)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3):
resolution: {integrity: sha512-GiPE/jbWM8Qv1A14lk6s9fhc0LhPEQ00eIczRO4QL2nAQJZXkjPG6zaVx+1cZxPFWbAsqSjKe2lqkwF3fGkQ7Q==}
engines: {node: '>=18.0'}
peerDependencies:
@@ -2666,7 +2666,7 @@ packages:
'@docusaurus/utils': 3.1.1(@docusaurus/types@3.1.1)
'@docusaurus/utils-common': 3.1.1(@docusaurus/types@3.1.1)
'@docusaurus/utils-validation': 3.1.1(@docusaurus/types@3.1.1)
'@mdx-js/react': 3.0.0(@types/react@18.2.61)(react@18.2.0)
'@mdx-js/react': 3.0.0(@types/react@18.2.55)(react@18.2.0)
clsx: 2.1.0
copy-text-to-clipboard: 3.2.0
infima: 0.2.0-alpha.43
@@ -2745,14 +2745,14 @@ packages:
- webpack-cli
dev: true
/@docusaurus/theme-search-algolia@3.1.1(@algolia/client-search@4.22.1)(@docusaurus/types@3.1.1)(@types/react@18.2.61)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0)(typescript@5.3.3):
/@docusaurus/theme-search-algolia@3.1.1(@algolia/client-search@4.22.1)(@docusaurus/types@3.1.1)(@types/react@18.2.55)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0)(typescript@5.3.3):
resolution: {integrity: sha512-tBH9VY5EpRctVdaAhT+b1BY8y5dyHVZGFXyCHgTrvcXQy5CV4q7serEX7U3SveNT9zksmchPyct6i1sFDC4Z5g==}
engines: {node: '>=18.0'}
peerDependencies:
react: ^18.0.0
react-dom: ^18.0.0
dependencies:
'@docsearch/react': 3.5.2(@algolia/client-search@4.22.1)(@types/react@18.2.61)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0)
'@docsearch/react': 3.5.2(@algolia/client-search@4.22.1)(@types/react@18.2.55)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0)
'@docusaurus/core': 3.1.1(@docusaurus/types@3.1.1)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
'@docusaurus/logger': 3.1.1
'@docusaurus/plugin-content-docs': 3.1.1(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
@@ -3129,16 +3129,6 @@ packages:
eslint: 8.56.0
eslint-visitor-keys: 3.4.3
/@eslint-community/eslint-utils@4.4.0(eslint@8.57.0):
resolution: {integrity: sha512-1/sA4dwrzBAyeUoQ6oxahHKmrZvsnLCg4RfxW3ZFGGmQkSNQPFNLV9CUEFQP1x9EYXHTo5p6xdhZM1Ne9p/AfA==}
engines: {node: ^12.22.0 || ^14.17.0 || >=16.0.0}
peerDependencies:
eslint: ^6.0.0 || ^7.0.0 || >=8.0.0
dependencies:
eslint: 8.57.0
eslint-visitor-keys: 3.4.3
dev: false
/@eslint-community/regexpp@4.10.0:
resolution: {integrity: sha512-Cu96Sd2By9mCNTx2iyKOmq10v22jUVQv0lQnlGNy16oE9589yE+QADPbrMGCkA51cKZSg3Pu/aTJVTGfL/qjUA==}
engines: {node: ^12.0.0 || ^14.0.0 || >=16.0.0}
@@ -3163,11 +3153,6 @@ packages:
resolution: {integrity: sha512-gMsVel9D7f2HLkBma9VbtzZRehRogVRfbr++f06nL2vnCGCNlzOD+/MUov/F4p8myyAHspEhVobgjpX64q5m6A==}
engines: {node: ^12.22.0 || ^14.17.0 || >=16.0.0}
/@eslint/js@8.57.0:
resolution: {integrity: sha512-Ys+3g2TaW7gADOJzPt83SJtCDhMjndcDMFVQ/Tj9iA1BfJzFKD9mAUXT3OenpuPHbI6P/myECxRJrofUsDx/5g==}
engines: {node: ^12.22.0 || ^14.17.0 || >=16.0.0}
dev: false
/@fastify/busboy@2.1.0:
resolution: {integrity: sha512-+KpH+QxZU7O4675t3mnkQKcZZg56u+K/Ct2K+N2AZYNVK8kyeo/bI18tI8aPm3tvNNRyTWfj6s5tnGNlcbQRsA==}
engines: {node: '>=14'}
@@ -3228,7 +3213,7 @@ packages:
'@jest/schemas': 29.6.3
'@types/istanbul-lib-coverage': 2.0.6
'@types/istanbul-reports': 3.0.4
'@types/node': 20.11.20
'@types/node': 20.11.17
'@types/yargs': 17.0.32
chalk: 4.1.2
@@ -3273,18 +3258,8 @@ packages:
/@leichtgewicht/ip-codec@2.0.4:
resolution: {integrity: sha512-Hcv+nVC0kZnQ3tD9GVu5xSMR4VVYOteQIr/hwFPVEvPdlXqgGEuRjiheChHgdM+JyqdgNcmzZOX/tnl0JOiI7A==}
/@llamaindex/cloud@0.0.4:
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peerDependencies:
node-fetch: ^3.3.2
peerDependenciesMeta:
node-fetch:
optional: true
dependencies:
'@types/qs': 6.9.12
form-data: 4.0.0
js-base64: 3.7.7
qs: 6.11.2
/@llamaindex/cloud@0.0.1:
resolution: {integrity: sha512-7FrLAbY459B4rcG4NaqANatDT5zKvZxIRyrY+nnTSXqu9ZMzkm1Co8IIRYx2/9feps/OLOhXsv7VKGGUr7scNQ==}
dev: false
/@manypkg/find-root@1.1.0:
@@ -3336,14 +3311,14 @@ packages:
transitivePeerDependencies:
- supports-color
/@mdx-js/react@3.0.0(@types/react@18.2.61)(react@18.2.0):
/@mdx-js/react@3.0.0(@types/react@18.2.55)(react@18.2.0):
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peerDependencies:
'@types/react': '>=16'
react: '>=16'
dependencies:
'@types/mdx': 2.0.10
'@types/react': 18.2.61
'@types/react': 18.2.55
react: 18.2.0
/@mistralai/mistralai@0.0.10:
@@ -4168,7 +4143,7 @@ packages:
/@types/connect@3.4.38:
resolution: {integrity: sha512-K6uROf1LD88uDQqJCktA4yzL1YYAK6NgfsI0v/mTgyPKWsX1CnJ0XPSDhViejru1GcRkLWb8RlzFYJRqGUbaug==}
dependencies:
'@types/node': 20.11.20
'@types/node': 20.11.17
/@types/cross-spawn@6.0.0:
resolution: {integrity: sha512-evp2ZGsFw9YKprDbg8ySgC9NA15g3YgiI8ANkGmKKvvi0P2aDGYLPxQIC5qfeKNUOe3TjABVGuah6omPRpIYhg==}
@@ -4205,7 +4180,7 @@ packages:
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dependencies:
'@types/node': 20.11.17
'@types/qs': 6.9.12
'@types/qs': 6.9.11
'@types/range-parser': 1.2.7
'@types/send': 0.17.4
@@ -4214,7 +4189,7 @@ packages:
dependencies:
'@types/body-parser': 1.19.5
'@types/express-serve-static-core': 4.17.42
'@types/qs': 6.9.12
'@types/qs': 6.9.11
'@types/serve-static': 1.15.5
/@types/gtag.js@0.0.12:
@@ -4353,6 +4328,7 @@ packages:
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dependencies:
undici-types: 5.26.5
dev: false
/@types/node@20.11.7:
resolution: {integrity: sha512-GPmeN1C3XAyV5uybAf4cMLWT9fDWcmQhZVtMFu7OR32WjrqGG+Wnk2V1d0bmtUyE/Zy1QJ9BxyiTih9z8Oks8A==}
@@ -4394,8 +4370,8 @@ packages:
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/@types/qs@6.9.11:
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/@types/range-parser@1.2.7:
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@@ -4404,7 +4380,7 @@ packages:
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dependencies:
'@types/history': 4.7.11
'@types/react': 18.2.61
'@types/react': 18.2.55
'@types/react-router': 5.1.20
dev: true
@@ -4428,7 +4404,7 @@ packages:
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dependencies:
'@types/history': 4.7.11
'@types/react': 18.2.48
'@types/react': 18.2.55
dev: true
/@types/react@18.2.48:
@@ -4438,8 +4414,8 @@ packages:
'@types/scheduler': 0.16.4
csstype: 3.1.2
/@types/react@18.2.61:
resolution: {integrity: sha512-NURTN0qNnJa7O/k4XUkEW2yfygA+NxS0V5h1+kp9jPwhzZy95q3ADoGMP0+JypMhrZBTTgjKAUlTctde1zzeQA==}
/@types/react@18.2.55:
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dependencies:
'@types/prop-types': 15.7.11
'@types/scheduler': 0.16.8
@@ -4478,7 +4454,7 @@ packages:
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dependencies:
'@types/mime': 1.3.5
'@types/node': 20.11.20
'@types/node': 20.11.17
/@types/serve-index@1.9.4:
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@@ -4541,7 +4517,7 @@ packages:
dependencies:
'@types/yargs-parser': 21.0.3
/@typescript-eslint/parser@6.19.1(eslint@8.57.0)(typescript@5.3.3):
/@typescript-eslint/parser@6.19.1(eslint@8.56.0)(typescript@5.3.3):
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engines: {node: ^16.0.0 || >=18.0.0}
peerDependencies:
@@ -4556,7 +4532,7 @@ packages:
'@typescript-eslint/typescript-estree': 6.19.1(typescript@5.3.3)
'@typescript-eslint/visitor-keys': 6.19.1
debug: 4.3.4
eslint: 8.57.0
eslint: 8.56.0
typescript: 5.3.3
transitivePeerDependencies:
- supports-color
@@ -5476,17 +5452,6 @@ packages:
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+1 -7
View File
@@ -11,13 +11,7 @@
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