Search is not available for this dataset
repo_id stringlengths 12 110 | file_path stringlengths 24 164 | content stringlengths 3 89.3M | __index_level_0__ int64 0 0 |
|---|---|---|---|
public_repos/archive | public_repos/archive/community_meetings/community-2021-06-09.md | # 2021-06-09 NumPy Community Meeting
Note: we now alternate between [triage meetings](https://hackmd.io/68i_JvOYQfy9ERiHgXMPvg) and community meetings.
- Time: 20:00 UTC
- Join via Zoom at https://berkeley.zoom.us/j/762261535 (or [dial-in](https://berkeley.zoom.us/u/aC3ENhycM))
- [Trello workboard](https://trello.com... | 0 |
public_repos/archive | public_repos/archive/community_meetings/community-2022-02-02.md | # 2022–02-02 NumPy Community Meeting
Note: we now alternate between [triage meetings](https://hackmd.io/68i_JvOYQfy9ERiHgXMPvg) and community meetings.
- Time: 6:00 pm UTC
- [Numpy community events calendar](https://calendar.google.com/calendar/r?cid=YmVya2VsZXkuZWR1X2lla2dwaWdtMjMyamJobGRzZmIyYzJqODFjQGdyb3VwLmNhbGV... | 0 |
public_repos/archive | public_repos/archive/community_meetings/community-2022-03-16.md | # 2022–03-16 NumPy community meeting
- Time: 6:00 pm UTC
- [Numpy community events calendar](https://calendar.google.com/calendar/r?cid=YmVya2VsZXkuZWR1X2lla2dwaWdtMjMyamJobGRzZmIyYzJqODFjQGdyb3VwLmNhbGVuZGFyLmdvb2dsZS5jb20)
- Join via Zoom at https://berkeley.zoom.us/j/762261535 (or [dial-in](https://berkeley.zoom.u... | 0 |
public_repos/archive | public_repos/archive/community_meetings/community-2023-03-01.md | # 2023-03-01 NumPy community meeting
- Time: 7:00 pm UTC
- [NumPy community events calendar](https://scientific-python.org/calendars/)
- Join via Zoom at https://us06web.zoom.us/j/83278611437?pwd=ekhoLzlHRjdWc0NOY2FQM0NPemdkZz09 (To dial in, find your local number: https://us06web.zoom.us/u/kbGQI0hHSd)
- [Community m... | 0 |
public_repos/archive | public_repos/archive/community_meetings/community-2022-11-23.md | # 2022-11-23 NumPy community meeting
- Time: 7:00 pm UTC
- [NumPy community events calendar](https://scientific-python.org/calendars/)
- Join via Zoom at https://us06web.zoom.us/j/83278611437?pwd=ekhoLzlHRjdWc0NOY2FQM0NPemdkZz09 (To dial in, find your local number: https://us06web.zoom.us/u/kbGQI0hHSd)
- [Community m... | 0 |
public_repos/archive | public_repos/archive/community_meetings/community-2021-06-23.md | # 2021-06-23 NumPy Community Meeting
Note: we now alternate between [triage meetings](https://hackmd.io/68i_JvOYQfy9ERiHgXMPvg) and community meetings.
- Time: 20:00 UTC
- Join via Zoom at https://berkeley.zoom.us/j/762261535 (or [dial-in](https://berkeley.zoom.us/u/aC3ENhycM))
- [Trello workboard](https://trello.com... | 0 |
public_repos/archive | public_repos/archive/community_meetings/community-2021-03-31.md | # 2021-03-31 NumPy Community Meeting
Note: we now alternate between [triage meetings](https://hackmd.io/68i_JvOYQfy9ERiHgXMPvg) and community meetings.
- Time: 20:00 UTC
- Join via Zoom at https://berkeley.zoom.us/j/762261535 (or [dial-in](https://berkeley.zoom.us/u/aC3ENhycM))
- [Trello workboard](https://trello.com... | 0 |
public_repos/archive | public_repos/archive/community_meetings/community-2021-02-17.md | ---
tags: NumPy
---
# 2021-02-17 NumPy Community Meeting
Note: we now alternate between [triage meetings](https://hackmd.io/68i_JvOYQfy9ERiHgXMPvg) and community meetings.
- Time: 12:00 Pacific Time (20:00 UTC)
- Join via Zoom at https://berkeley.zoom.us/j/762261535 (or [dial-in](https://berkeley.zoom.us/u/aC3ENhyc... | 0 |
public_repos/archive | public_repos/archive/community_meetings/community-2020-05-27.md | ---
tags: NumPy
---
# 2020-05-27 NumPy Community Meeting
Note: we now alternate between [triage meetings](https://hackmd.io/68i_JvOYQfy9ERiHgXMPvg) and community meetings.
- Time: 13:00 Pacific Time
- Join via Zoom at https://berkeley.zoom.us/j/762261535 (or [dial-in](https://berkeley.zoom.us/u/aC3ENhycM))
- [Trello... | 0 |
public_repos/archive | public_repos/archive/community_meetings/community-2023-09-13.md | # 2023-09-13 NumPy community meeting
- Time: 5:00pm UTC
- [NumPy community events calendar](https://scientific-python.org/calendars/)
- Join via Zoom at https://numfocus-org.zoom.us/j/83278611437?pwd=ekhoLzlHRjdWc0NOY2FQM0NPemdkZz09 (To dial in, find your local number: https://numfocus-org.zoom.us/u/kekDGNWmRa.)
- [Co... | 0 |
public_repos/archive | public_repos/archive/community_meetings/community-2023-06-07.md | ---
tags: NumPy
---
# 2023-06-07 NumPy community meeting
- Time: 5:00pm UTC
- [NumPy community events calendar](https://scientific-python.org/calendars/)
- Join via Zoom at https://us06web.zoom.us/j/83278611437?pwd=ekhoLzlHRjdWc0NOY2FQM0NPemdkZz09 (To dial in, find your local number: https://us06web.zoom.us/u/kbGQI0h... | 0 |
public_repos/archive | public_repos/archive/community_meetings/community-2021-03-03.md | ---
tags: NumPy
---
# 2021-03-03 NumPy Community Meeting
Note: we now alternate between [triage meetings](https://hackmd.io/68i_JvOYQfy9ERiHgXMPvg) and community meetings.
- Time: 12:00 Pacific Time (20:00 UTC)
- Join via Zoom at https://berkeley.zoom.us/j/762261535 (or [dial-in](https://berkeley.zoom.us/u/aC3ENhyc... | 0 |
public_repos/archive | public_repos/archive/community_meetings/community-2021-04-28.md | ---
tags: NumPy
---
# 2021-04-28 NumPy Community Meeting
Note: we now alternate between [triage meetings](https://hackmd.io/68i_JvOYQfy9ERiHgXMPvg) and community meetings.
- Time: 20:00 UTC
- Join via Zoom at https://berkeley.zoom.us/j/762261535 (or [dial-in](https://berkeley.zoom.us/u/aC3ENhycM))
- [Trello workboa... | 0 |
public_repos/archive | public_repos/archive/community_meetings/community-2020-01-22.md | ---
tags: NumPy
---
# 2020-01-22 NumPy Community Meeting
Note: we now alternate between [triage meetings](https://hackmd.io/68i_JvOYQfy9ERiHgXMPvg) and community meetings.
- Time: 11am Pacific Time
- Join via Zoom at https://berkeley.zoom.us/j/762261535 (or [dial-in](https://berkeley.zoom.us/u/aC3ENhycM))
- [Trello ... | 0 |
public_repos/archive | public_repos/archive/community_meetings/community-2020-08-19.md | ---
tags: NumPy
---
# 2020-08-19 NumPy Community Meeting
Note: we now alternate between [triage meetings](https://hackmd.io/68i_JvOYQfy9ERiHgXMPvg) and community meetings.
- Time: 13:00 Pacific Time (18:00 UTC)
- Join via Zoom at https://berkeley.zoom.us/j/762261535 (or [dial-in](https://berkeley.zoom.us/u/aC3ENhycM... | 0 |
public_repos/archive | public_repos/archive/community_meetings/community-2020-07-22.md | ---
tags: NumPy
---
# 2020-07-22
NumPy Community Meeting
Note: we now alternate between [triage meetings](https://hackmd.io/68i_JvOYQfy9ERiHgXMPvg) and community meetings.
- Time: 13:00 Pacific Time (18:00 UTC)
- Join via Zoom at https://berkeley.zoom.us/j/762261535 (or [dial-in](https://berkeley.zoom.us/u/aC3ENhycM... | 0 |
public_repos/archive | public_repos/archive/community_meetings/community-2023-08-16.md | # 2023-08-16 NumPy community meeting
- Time: 5:00pm UTC
- [NumPy community events calendar](https://scientific-python.org/calendars/)
- Join via Zoom at https://numfocus-org.zoom.us/j/83278611437?pwd=ekhoLzlHRjdWc0NOY2FQM0NPemdkZz09 (To dial in, find your local number: https://numfocus-org.zoom.us/u/kekDGNWmRa.)
- [Co... | 0 |
public_repos/archive | public_repos/archive/web_team_meetings/webteam-2020-02-18.md | # 2020-02-18 NumPy Web Team Meeting
Time: 1:00 PM PST/ 4:00 PM EST
Join Hangouts Meet: meet.google.com/wex-fwsf-dtc
<br> **note: Hangouts works best with Chrome*
Join by phone: +1 651-504-5687 PIN: 950 133 744#
[Slack workspace](https://numpy-team.slack.com)
[Meetings archive](https://github.com/numpy/archive/t... | 0 |
public_repos/archive | public_repos/archive/web_team_meetings/webteam-2019-10-28.md | # 2019-10-28 NumPy Web Team Meeting
Time: 9:00 AM PST
Join Hangouts Meet: https://meet.google.com/trm-gvto-guz
<br> **note: Hangouts works best with Chrome*
Join by phone: +1 980-533-5653 PIN: 455 016 082#
[Slack workspace](https://numpy-team.slack.com)
[Meetings archive](https://github.com/numpy/archive/tree/mast... | 0 |
public_repos/archive | public_repos/archive/web_team_meetings/webteam-2020-02-20.md | # 2020-02-20 NumPy Web Team Meeting
Time: 5:00 PM PST
Join Hangouts Meet: meet.google.com/usa-owrj-gjt
<br> **note: Hangouts works best with Chrome*
Join by phone: https://meet.google.com/tel/usa-owrj-gjt?pin=5379071568271
[Slack workspace](https://numpy-team.slack.com)
[Meetings archive](https://github.com/numpy/... | 0 |
public_repos/archive | public_repos/archive/web_team_meetings/webteam-2019-08-17.md | # 2019-08-17 NumPy Web Team Meeting
**Present:** Ralf, Inessa, Joe, Shekhar
# Agenda
1. Outline major project milestones.
2. Decide on project management tool.
3. Define project organization.
4. Decide on website generator.
5. Discuss deployment strategies.
6. Explore further translation options.
# Minutes
Int... | 0 |
public_repos/archive | public_repos/archive/web_team_meetings/webteam-2019-09-23.md | # 2019-09-23 NumPy Web Team Meeting
**Present:** Ralf, Inessa, Joe, Matti, Sebastian, Hameer
# Agenda
1. Status of the `newsite` branch.
2. Website structure - site map: https://app.flowmapp.com/share/e1b61759a5f95f43d8907baedf42875d/
3. Status of content creation.
4. Status of translations with Crowdin.
5. GitHub... | 0 |
public_repos/archive | public_repos/archive/web_team_meetings/webteam-2019-12-10.md | # 2019-12-10 NumPy Web Team Meeting
Time: 9:00 PM IST / 7:30 AM PST
Join Hangouts Meet: meet.google.com/axt-ezae-tms
<br> **note: Hangouts works best with Chrome*
Join by phone: +1 929-336-0281 PIN: 416 898 831#
[Slack workspace](https://numpy-team.slack.com)
[Meetings archive](https://github.com/numpy/archive/... | 0 |
public_repos | public_repos/chat-langchain/Procfile | # Modify this Procfile to fit your needs
web: uvicorn main:app --host 0.0.0.0 --port 8080 | 0 |
public_repos | public_repos/chat-langchain/poetry.lock | # This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand.
[[package]]
name = "aiohttp"
version = "3.8.6"
description = "Async http client/server framework (asyncio)"
optional = false
python-versions = ">=3.6"
files = [
{file = "aiohttp-3.8.6-cp310-cp310-macosx_10_9_universal2.whl",... | 0 |
public_repos | public_repos/chat-langchain/yarn.lock | # THIS IS AN AUTOGENERATED FILE. DO NOT EDIT THIS FILE DIRECTLY.
# yarn lockfile v1
"@babel/code-frame@^7.0.0":
version "7.22.13"
resolved "https://registry.yarnpkg.com/@babel/code-frame/-/code-frame-7.22.13.tgz#e3c1c099402598483b7a8c46a721d1038803755e"
integrity sha512-XktuhWlJ5g+3TJXc5upd9Ks1HutSArik6jf2eAjYF... | 0 |
public_repos | public_repos/chat-langchain/.dockerignore | chat-langchain/
assets/ | 0 |
public_repos | public_repos/chat-langchain/main.py | """Main entrypoint for the app."""
import asyncio
import os
from operator import itemgetter
from typing import Dict, List, Optional, Sequence, Union
from uuid import UUID
import langsmith
import weaviate
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from langchain.chat_models import Ch... | 0 |
public_repos | public_repos/chat-langchain/constants.py | WEAVIATE_DOCS_INDEX_NAME = "LangChain_agent_docs"
| 0 |
public_repos | public_repos/chat-langchain/Makefile | .PHONY: start
start:
uvicorn main:app --reload --port 8080
.PHONY: format
format:
black .
isort . | 0 |
public_repos | public_repos/chat-langchain/parser.py | import re
from typing import Generator
from bs4 import BeautifulSoup, Doctype, NavigableString, Tag
def langchain_docs_extractor(soup: BeautifulSoup) -> str:
# Remove all the tags that are not meaningful for the extraction.
SCAPE_TAGS = ["nav", "footer", "aside", "script", "style"]
[tag.decompose() for t... | 0 |
public_repos | public_repos/chat-langchain/Dockerfile | FROM python:3.11-buster
RUN pip install poetry==1.5.1
RUN poetry config virtualenvs.create false
COPY ./pyproject.toml ./poetry.lock* ./
RUN poetry install --no-interaction --no-ansi --no-root --no-directory
COPY ./*.py ./
RUN poetry install --no-interaction --no-ansi
CMD exec uvicorn main:app --host 0.0.0.0 --... | 0 |
public_repos | public_repos/chat-langchain/pyproject.toml | [tool.poetry]
name = "chat-langchain"
version = "0.1.0"
description = ""
authors = ["SN <6432132+samnoyes@users.noreply.github.com>"]
readme = "README.md"
[tool.poetry.dependencies]
python = "^3.10"
openai = "^0.28.0"
fastapi = "^0.103.1"
pydantic = "1.10"
langchain = "^0.0.331"
uvicorn = "^0.23.2"
beautifulsoup4 = "^... | 0 |
public_repos | public_repos/chat-langchain/README.md | # 🦜️🔗 Chat LangChain
This repo is an implementation of a locally hosted chatbot specifically focused on question answering over the [LangChain documentation](https://langchain.readthedocs.io/en/latest/).
Built with [LangChain](https://github.com/hwchase17/langchain/), [FastAPI](https://fastapi.tiangolo.com/), and [N... | 0 |
public_repos | public_repos/chat-langchain/LICENSE | MIT License
Copyright (c) 2023 Harrison Chase
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, di... | 0 |
public_repos | public_repos/chat-langchain/ingest.py | """Load html from files, clean up, split, ingest into Weaviate."""
import logging
import os
import re
from parser import langchain_docs_extractor
import weaviate
from bs4 import BeautifulSoup, SoupStrainer
from langchain.document_loaders import RecursiveUrlLoader, SitemapLoader
from langchain.embeddings import OpenAIE... | 0 |
public_repos/chat-langchain | public_repos/chat-langchain/terraform/backend.tf | terraform {
backend "gcs" {
bucket = "YOUR BUCKET"
prefix = "YOUR PREFIX"
}
}
| 0 |
public_repos/chat-langchain | public_repos/chat-langchain/terraform/main.tf | locals {
secret_json = jsondecode(data.google_secret_manager_secret_version.chat_langchain_backend_secrets.secret_data)
region = "YOUR REGION"
project_id = "YOUR PROJECT ID"
}
provider "google" {
project = local.project_id
region = local.region
}
# Load secrets from Secret Manager. You can specify yo... | 0 |
public_repos/chat-langchain/terraform/modules | public_repos/chat-langchain/terraform/modules/chat_langchain_backend/main.tf | # Common environment variables
locals {
voyager_vars = var.voyage_ai_model != "" && var.voyage_api_key != "" ? {
VOYAGE_AI_MODEL = var.voyage_ai_model
VOYAGE_API_KEY = var.voyage_api_key
} : {}
env_vars = merge(local.voyager_vars, {
OPENAI_API_KEY = var.openai_api_key
WEAVIATE_URL =... | 0 |
public_repos/chat-langchain/terraform/modules | public_repos/chat-langchain/terraform/modules/chat_langchain_backend/variables.tf | variable "chat_langchain_backend_name" {
description = "Name to use for resources that will be created"
type = string
}
variable "project_id" {
description = "The ID of the project"
type = string
}
variable "region" {
description = "The region to deploy to"
type = string
}
variable "... | 0 |
public_repos/chat-langchain | public_repos/chat-langchain/_scripts/clear_index.py | """Clear Weaviate index."""
import logging
import os
import weaviate
from langchain.embeddings import OpenAIEmbeddings
from langchain.indexes import SQLRecordManager, index
from langchain.vectorstores import Weaviate
logger = logging.getLogger(__name__)
WEAVIATE_URL = os.environ["WEAVIATE_URL"]
WEAVIATE_API_KEY = os... | 0 |
public_repos/chat-langchain | public_repos/chat-langchain/_scripts/evaluate_chains_agent.py | import argparse
import json
import os
from typing import Optional
import weaviate
from langchain import load as langchain_load
from langchain.agents import AgentExecutor, Tool
from langchain.agents.openai_functions_agent.agent_token_buffer_memory import (
AgentTokenBufferMemory,
)
from langchain.agents.openai_func... | 0 |
public_repos/chat-langchain | public_repos/chat-langchain/_scripts/evaluate_chat_langchain.py | # TODO: Consolidate all these scripts into a single script
# This is ugly
import argparse
from langchain.chat_models import ChatAnthropic, ChatOpenAI
from langchain.smith import RunEvalConfig
from langsmith import Client
# Ugly. Requires PYTHONATH=$(PWD) to run
from main import create_chain, get_retriever
_PROVIDER_... | 0 |
public_repos/chat-langchain | public_repos/chat-langchain/_scripts/evaluate_chains_improved_chain.py | import argparse
import datetime
import functools
import json
import os
from typing import Literal, Optional, Union
import weaviate
from langchain import load as langchain_load
from langchain.chat_models import ChatAnthropic, ChatOpenAI
from langchain.embeddings import OpenAIEmbeddings
from langchain.output_parsers imp... | 0 |
public_repos/chat-langchain | public_repos/chat-langchain/_scripts/evaluate_chains.py | import argparse
import functools
import json
import os
from operator import itemgetter
from typing import Literal, Optional, Union
import weaviate
from langchain import load as langchain_load
from langchain.chat_models import ChatAnthropic, ChatOpenAI
from langchain.embeddings import OpenAIEmbeddings
from langchain.pr... | 0 |
public_repos/chat-langchain | public_repos/chat-langchain/chat-langchain/vercel.json | {
"git": {
"deploymentEnabled": {
"main": false
}
}
}
| 0 |
public_repos/chat-langchain | public_repos/chat-langchain/chat-langchain/yarn.lock | # THIS IS AN AUTOGENERATED FILE. DO NOT EDIT THIS FILE DIRECTLY.
# yarn lockfile v1
"@aashutoshrathi/word-wrap@^1.2.3":
version "1.2.6"
resolved "https://registry.yarnpkg.com/@aashutoshrathi/word-wrap/-/word-wrap-1.2.6.tgz#bd9154aec9983f77b3a034ecaa015c2e4201f6cf"
integrity sha512-1Yjs2SvM8TflER/OD3cOjhWWOZb58A... | 0 |
public_repos/chat-langchain | public_repos/chat-langchain/chat-langchain/.eslintrc.json | {
"extends": "next/core-web-vitals"
}
| 0 |
public_repos/chat-langchain | public_repos/chat-langchain/chat-langchain/tailwind.config.ts | import type { Config } from "tailwindcss";
const config: Config = {
content: [
"./pages/**/*.{js,ts,jsx,tsx,mdx}",
"./components/**/*.{js,ts,jsx,tsx,mdx}",
"./app/**/*.{js,ts,jsx,tsx,mdx}",
],
theme: {
extend: {
backgroundImage: {
"gradient-radial": "radial-gradient(var(--tw-gradien... | 0 |
public_repos/chat-langchain | public_repos/chat-langchain/chat-langchain/.prettierrc | {
"endOfLine": "lf"
}
| 0 |
public_repos/chat-langchain | public_repos/chat-langchain/chat-langchain/tsconfig.json | {
"compilerOptions": {
"target": "es5",
"lib": ["dom", "dom.iterable", "esnext"],
"allowJs": true,
"skipLibCheck": true,
"strict": true,
"forceConsistentCasingInFileNames": true,
"noEmit": true,
"esModuleInterop": true,
"module": "esnext",
"moduleResolution": "bundler",
"re... | 0 |
public_repos/chat-langchain | public_repos/chat-langchain/chat-langchain/postcss.config.js | module.exports = {
plugins: {
tailwindcss: {},
autoprefixer: {},
},
};
| 0 |
public_repos/chat-langchain | public_repos/chat-langchain/chat-langchain/.env.example | ## For JS backend:
# LANGCHAIN_TRACING_V2=true
# LANGCHAIN_ENDPOINT="https://api.smith.langchain.com"
# LANGCHAIN_API_KEY="YOUR_LANGSMITH_KEY"
# LANGCHAIN_PROJECT="YOUR_PROJECT_NAME"
# NEXT_PUBLIC_API_BASE_URL="http://localhost:3000/api"
# OPENAI_API_KEY="YOUR_OPENAI_API_KEY"
# WEAVIATE_HOST="YOUR_WEAVIATE_HOST"
# WE... | 0 |
public_repos/chat-langchain | public_repos/chat-langchain/chat-langchain/next.config.js | /** @type {import('next').NextConfig} */
const nextConfig = {};
module.exports = nextConfig;
| 0 |
public_repos/chat-langchain | public_repos/chat-langchain/chat-langchain/package.json | {
"name": "chat-langchain",
"version": "0.1.0",
"private": true,
"packageManager": "yarn@1.22.19",
"scripts": {
"dev": "next dev",
"build": "next build",
"start": "next start",
"lint": "next lint",
"format": "prettier --write ."
},
"dependencies": {
"@chakra-ui/icons": "^2.1.0",
... | 0 |
public_repos/chat-langchain/chat-langchain | public_repos/chat-langchain/chat-langchain/app/layout.tsx | import "./globals.css";
import type { Metadata } from "next";
import { Inter } from "next/font/google";
const inter = Inter({ subsets: ["latin"] });
export const metadata: Metadata = {
title: "Chat LangChain",
description: "Chatbot for LangChain",
};
export default function RootLayout({
children,
}: {
childr... | 0 |
public_repos/chat-langchain/chat-langchain | public_repos/chat-langchain/chat-langchain/app/page.tsx | "use client";
import { ChatWindow } from "../app/components/ChatWindow";
import { ToastContainer } from "react-toastify";
import { ChakraProvider } from "@chakra-ui/react";
export default function Home() {
return (
<ChakraProvider>
<ToastContainer />
<ChatWindow
titleText="Chat LangChain 🦜... | 0 |
public_repos/chat-langchain/chat-langchain | public_repos/chat-langchain/chat-langchain/app/globals.css | @tailwind base;
@tailwind components;
@tailwind utilities;
body {
color: #f8f8f8;
background: #131318;
}
body input,
body textarea {
color: black;
}
a {
color: #2d7bd4;
}
a:hover {
border-bottom: 1px solid;
}
p {
margin: 8px 0;
}
code {
color: #ffa500;
}
li {
padding: 4px;
}
| 0 |
public_repos/chat-langchain/chat-langchain/app | public_repos/chat-langchain/chat-langchain/app/utils/sendFeedback.tsx | import { v4 as uuidv4 } from "uuid";
import { apiBaseUrl } from "./constants";
type SendFeedbackProps = {
key: string;
runId: string;
score?: number;
value?: string;
comment?: string;
feedbackId?: string;
isExplicit: boolean;
};
type FeedbackResponse = {
feedbackId: string;
code: number;
result: s... | 0 |
public_repos/chat-langchain/chat-langchain/app | public_repos/chat-langchain/chat-langchain/app/utils/constants.tsx | export const apiBaseUrl =
process.env.NEXT_PUBLIC_API_BASE_URL ?? "http://localhost:8080";
| 0 |
public_repos/chat-langchain/chat-langchain/app | public_repos/chat-langchain/chat-langchain/app/components/InlineCitation.tsx | import { Source } from "./SourceBubble";
export function InlineCitation(props: {
source: Source;
sourceNumber: number;
highlighted: boolean;
onMouseEnter: () => any;
onMouseLeave: () => any;
}) {
const { source, sourceNumber, highlighted, onMouseEnter, onMouseLeave } =
props;
return (
<a
hr... | 0 |
public_repos/chat-langchain/chat-langchain/app | public_repos/chat-langchain/chat-langchain/app/components/EmptyState.tsx | import { MouseEvent } from "react";
import {
Heading,
Link,
Card,
CardHeader,
Flex,
Spacer,
} from "@chakra-ui/react";
export function EmptyState(props: { onChoice: (question: string) => any }) {
const handleClick = (e: MouseEvent) => {
props.onChoice((e.target as HTMLDivElement).innerText);
};
r... | 0 |
public_repos/chat-langchain/chat-langchain/app | public_repos/chat-langchain/chat-langchain/app/components/ChatMessageBubble.tsx | import { toast } from "react-toastify";
import "react-toastify/dist/ReactToastify.css";
import { emojisplosion } from "emojisplosion";
import { useState, useRef } from "react";
import { SourceBubble, Source } from "./SourceBubble";
import {
VStack,
Flex,
Heading,
HStack,
Box,
Button,
Divider,
Spacer,
} ... | 0 |
public_repos/chat-langchain/chat-langchain/app | public_repos/chat-langchain/chat-langchain/app/components/AutoResizeTextarea.tsx | import { Textarea, TextareaProps } from "@chakra-ui/react";
import ResizeTextarea from "react-textarea-autosize";
import React from "react";
interface ResizeTextareaProps {
maxRows?: number;
}
const ResizableTextarea: React.FC<ResizeTextareaProps> = ({
maxRows,
...props
}) => {
return <ResizeTextarea maxRows=... | 0 |
public_repos/chat-langchain/chat-langchain/app | public_repos/chat-langchain/chat-langchain/app/components/ChatWindow.tsx | "use client";
import React, { useRef, useState } from "react";
import { v4 as uuidv4 } from "uuid";
import { EmptyState } from "../components/EmptyState";
import { ChatMessageBubble, Message } from "../components/ChatMessageBubble";
import { AutoResizeTextarea } from "./AutoResizeTextarea";
import { marked } from "mar... | 0 |
public_repos/chat-langchain/chat-langchain/app | public_repos/chat-langchain/chat-langchain/app/components/SourceBubble.tsx | import "react-toastify/dist/ReactToastify.css";
import { Card, CardBody, Heading } from "@chakra-ui/react";
import { sendFeedback } from "../utils/sendFeedback";
export type Source = {
url: string;
title: string;
};
export function SourceBubble({
source,
highlighted,
onMouseEnter,
onMouseLeave,
runId,
}... | 0 |
public_repos/chat-langchain/chat-langchain/app/api | public_repos/chat-langchain/chat-langchain/app/api/get_trace/route.ts | // JS backend not used by default, see README for instructions.
import { NextRequest, NextResponse } from "next/server";
import { Client } from "langsmith";
export const runtime = "edge";
const client = new Client();
const pollForRun = async (runId: string, retryCount = 0): Promise<string> => {
await new Promise... | 0 |
public_repos/chat-langchain/chat-langchain/app/api | public_repos/chat-langchain/chat-langchain/app/api/feedback/route.ts | // JS backend not used by default, see README for instructions.
import { NextRequest, NextResponse } from "next/server";
import { Client } from "langsmith";
export const runtime = "edge";
const client = new Client();
export async function POST(req: NextRequest) {
try {
const body = await req.json();
cons... | 0 |
public_repos/chat-langchain/chat-langchain/app/api/chat | public_repos/chat-langchain/chat-langchain/app/api/chat/stream_log/route.ts | // JS backend not used by default, see README for instructions.
import { NextRequest, NextResponse } from "next/server";
import type { BaseLanguageModel } from "langchain/base_language";
import type { Document } from "langchain/document";
import {
Runnable,
RunnableSequence,
RunnableMap,
RunnableBranch,
Ru... | 0 |
public_repos/chat-langchain/chat-langchain/public | public_repos/chat-langchain/chat-langchain/public/images/github-mark.svg | <svg width="98" height="96" xmlns="http://www.w3.org/2000/svg"><path fill-rule="evenodd" clip-rule="evenodd" d="M48.854 0C21.839 0 0 22 0 49.217c0 21.756 13.993 40.172 33.405 46.69 2.427.49 3.316-1.059 3.316-2.362 0-1.141-.08-5.052-.08-9.127-13.59 2.934-16.42-5.867-16.42-5.867-2.184-5.704-5.42-7.17-5.42-7.17-4.448-3.01... | 0 |
public_repos | public_repos/lit-llama/generate.py | import sys
import time
import warnings
from pathlib import Path
from typing import Optional
import lightning as L
import torch
# support running without installing as a package
wd = Path(__file__).parent.parent.resolve()
sys.path.append(str(wd))
from lit_llama import LLaMA, Tokenizer
from lit_llama.utils import lazy... | 0 |
public_repos | public_repos/lit-llama/setup.py | import os
from setuptools import setup, find_packages
_PATH_ROOT = os.path.dirname(__file__)
with open(os.path.join(_PATH_ROOT, "README.md"), encoding="utf-8") as fo:
readme = fo.read()
setup(
name='lit-llama',
version='0.1.0',
description='Implementation of the LLaMA language model',
author='L... | 0 |
public_repos | public_repos/lit-llama/requirements.txt | torch>=2.0.0
lightning @ git+https://github.com/Lightning-AI/lightning@master
sentencepiece
tqdm # convert_checkpoint.py
numpy # train.py dataset memmap
jsonargparse[signatures] # generate.py, convert_checkpoint.py CLI
bitsandbytes # quantization.py
datasets # evaluate.py
zstandard # prepare_redpajama.py
| 0 |
public_repos | public_repos/lit-llama/README.md | <div align="center">
<img src="https://pl-public-data.s3.amazonaws.com/assets_lightning/Lit_LLaMA_Badge3x.png" alt="Lit-LLaMA" width="128"/>
# ⚡ Lit-LLaMA ️
<!--
<p align="center">
<a href="https://www.lightning.ai/">Lightning.ai</a> •
<a href="https://lightning.ai/docs/pytorch/stable/">PyTorch Lightning</a> •
... | 0 |
public_repos | public_repos/lit-llama/LICENSE | Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
1. Definitions.
"License" shall mean the terms and conditions for use, reproduction,
... | 0 |
public_repos/lit-llama | public_repos/lit-llama/pretrain/shakespeare.py | """
This script is a placeholder for training LLaMA from scratch.
Currently, it just trains on the Shakespeare dataset.
"""
from pathlib import Path
import sys
import os
import time
from functools import partial
from typing import Tuple
import lightning as L
from lightning.fabric.strategies import FSDPStrategy
import... | 0 |
public_repos/lit-llama | public_repos/lit-llama/pretrain/redpajama.py | import os
import sys
import math
import glob
import time
from functools import partial
from pathlib import Path
from typing import Tuple, Optional
import lightning as L
from lightning.fabric.strategies import FSDPStrategy
import torch
from torch.utils.data import DataLoader
from torch.distributed.fsdp.wrap import tra... | 0 |
public_repos/lit-llama | public_repos/lit-llama/evaluate/full.py | # This mimics GPTQ's evaluation metrics: https://github.com/IST-DASLab/gptq/
# Thanks to E. Frantar et al GPTQ: Accurate Post-training Compression for GPT, arXiv:2210.17323
import math
import sys
import time
from pathlib import Path
from typing import Optional
import lightning as L
import torch
import tqdm
# support ... | 0 |
public_repos/lit-llama | public_repos/lit-llama/evaluate/adapter_v2.py | # This mimics GPTQ's evaluation metrics: https://github.com/IST-DASLab/gptq/
# Thanks to E. Frantar et al GPTQ: Accurate Post-training Compression for GPT, arXiv:2210.17323
import math
import sys
import time
from pathlib import Path
from typing import Optional
import lightning as L
import torch
import tqdm
# support ... | 0 |
public_repos/lit-llama | public_repos/lit-llama/evaluate/lora.py | # This mimics GPTQ's evaluation metrics: https://github.com/IST-DASLab/gptq/
# Thanks to E. Frantar et al GPTQ: Accurate Post-training Compression for GPT, arXiv:2210.17323
import math
import sys
import time
from pathlib import Path
from typing import Optional
import lightning as L
import torch
import tqdm
# support ... | 0 |
public_repos/lit-llama | public_repos/lit-llama/evaluate/adapter.py | # This mimics GPTQ's evaluation metrics: https://github.com/IST-DASLab/gptq/
# Thanks to E. Frantar et al GPTQ: Accurate Post-training Compression for GPT, arXiv:2210.17323
import math
import sys
import time
from pathlib import Path
from typing import Optional
import lightning as L
import torch
import tqdm
# support ... | 0 |
public_repos/lit-llama | public_repos/lit-llama/lit_llama/model.py | """Full definition of a LLaMA Language Model, all of it in this single file.
Based on the nanoGPT implementation: https://github.com/karpathy/nanoGPT.
"""
# mypy: ignore-errors
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import torch
import torch.nn as nn
from torch.n... | 0 |
public_repos/lit-llama | public_repos/lit-llama/lit_llama/packed_dataset.py | # Very loosely inspired by indexed_dataset in Fairseq, Megatron
# https://github.com/NVIDIA/Megatron-LM/blob/main/megatron/data/indexed_dataset.py
import os
import struct
import random
import numpy as np
import torch
from torch.utils.data import IterableDataset, get_worker_info
dtypes = {
1: np.uint8,
2: n... | 0 |
public_repos/lit-llama | public_repos/lit-llama/lit_llama/adapter_v2.py | import torch
from torch import Tensor
import torch.nn as nn
from torch.nn import functional as F
from lit_llama.adapter import LLaMA
def get_adapter_substrings():
substrings = ["adapter_wte", "gating_factor"] # regular adapter v1 parameters
substrings.extend(["adapter_scale", "adapter_bias"]) # adapter v2:... | 0 |
public_repos/lit-llama | public_repos/lit-llama/lit_llama/lora.py | # Derived from https://github.com/microsoft/LoRA
# ------------------------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License (MIT). See LICENSE in the repo root for license information.
# ------------------... | 0 |
public_repos/lit-llama | public_repos/lit-llama/lit_llama/quantization.py | import os
from contextlib import contextmanager
import warnings
import math
import torch
# configuration for bitsandbytes before import
os.environ["BITSANDBYTES_NOWELCOME"] = "1"
warnings.filterwarnings(
"ignore",
message="MatMul8bitLt: inputs will be cast from torch.float32 to float16 during quantization",
)... | 0 |
public_repos/lit-llama | public_repos/lit-llama/lit_llama/utils.py | """Utility functions for training and inference."""
import functools
import pickle
import warnings
from io import BytesIO
from pathlib import Path
from contextlib import contextmanager
import torch
import torch.utils._device
from lightning.fabric.strategies import DeepSpeedStrategy, FSDPStrategy
from torch.distribute... | 0 |
public_repos/lit-llama | public_repos/lit-llama/lit_llama/adapter.py | """Implementation of the paper:
LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention
https://arxiv.org/abs/2303.16199
| Prefix cross-attention
... | 0 |
public_repos/lit-llama | public_repos/lit-llama/lit_llama/tokenizer.py | import os
from pathlib import Path
from typing import Optional
import torch
from sentencepiece import SentencePieceProcessor, SentencePieceTrainer
class Tokenizer:
"""Tokenizer for LLaMA."""
def __init__(self, model_path: Path) -> None:
self.processor = SentencePieceProcessor(model_file=str(model_pa... | 0 |
public_repos/lit-llama | public_repos/lit-llama/lit_llama/__init__.py | from lit_llama.model import LLaMAConfig, LLaMA, RMSNorm, build_rope_cache, apply_rope
from lit_llama.tokenizer import Tokenizer
| 0 |
public_repos/lit-llama | public_repos/lit-llama/howto/unstructured_dataset.md | # Finetuning on an unstructured dataset
While most scripts were made to finetune on instruction datasets, it is possible to finetune on any dataset. This is useful for experimentation while not being as expensive as training a full model.
This guide is only to prepare the finetuning, as either LoRA or Adapter-v1 meth... | 0 |
public_repos/lit-llama | public_repos/lit-llama/howto/finetune_full.md | # Full Finetuning
Full finetuning updates all layers in the pretrained LLaMA model. This *regular* finetuning procedure is typically considered as the baseline for parameter-efficient alternatives such as Low-Rank Adaptation (LoRA) or LLaMA-Adapter.
The current [finetune/full.py](../finetune/full.py) we provide uses... | 0 |
public_repos/lit-llama | public_repos/lit-llama/howto/tpus.md | # TPU support
Lit-LLaMA used `lightning.Fabric` under the hood, which itself supports TPUs (via [PyTorch XLA](https://github.com/pytorch/xla)).
The following commands will allow you to set up a `Google Cloud` instance with a [TPU v4](https://cloud.google.com/tpu/docs/system-architecture-tpu-vm) VM:
```shell
gcloud c... | 0 |
public_repos/lit-llama | public_repos/lit-llama/howto/finetune_lora.md | # Finetuning with LoRA
[Low-rank adaption (LoRA)](https://arxiv.org/abs/2106.09685) is a technique to approximate the update to the linear layers in a LLM with a low-rank matrix factorization. This significantly reduces the number of trainable parameters and speeds up training with little impact on the final performan... | 0 |
public_repos/lit-llama | public_repos/lit-llama/howto/inference.md | # Inference
We demonstrate how to run inference (next token prediction) with the LLaMA base model in the [`generate.py`](generate.py) script:
```bash
python generate.py --prompt "Hello, my name is"
```
Output:
```
Hello my name is TJ. I have a passion for the outdoors, love hiking and exploring. I also enjoy travelin... | 0 |
public_repos/lit-llama | public_repos/lit-llama/howto/train_redpajama.md | # Pre-train LLaMA on RedPajama
This howto will walk you through setting up the RedPajama dataset and launching the pre-training script.
## What's RedPajama
[RedPajama](https://github.com/togethercomputer/RedPajama-Data) is an open-source reproduction of the original LLaMA training dataset.
It contains a total of 1.... | 0 |
public_repos/lit-llama | public_repos/lit-llama/howto/finetune_adapter_v2.md | # Finetuning with Adapter v2
[LLaMA-Adapter v2](https://arxiv.org/abs/2304.15010) is a form of prefix-tuning that prepends a learnable adaption-prompt to the inputs of the attention blocks in LLaMA. In total, there are only ~4 M parameters to update during finetuning, which significantly reduces the memory footprint a... | 0 |
public_repos/lit-llama | public_repos/lit-llama/howto/finetune_adapter.md | # Finetuning with Adapter
[LLaMA-Adapter](https://arxiv.org/abs/2303.16199) is a form of prefix-tuning that prepends a learnable adaption-prompt to the inputs of the attention blocks in LLaMA. In total, there are only 1.2M parameters to update during finetuning, which significantly reduces the memory footprint and spe... | 0 |
public_repos/lit-llama | public_repos/lit-llama/howto/download_weights.md | ## Downloading pretrained weights
Except for when you are training from scratch, you will need the pretrained weights from Meta.
### Original Meta weights
Download the model weights following the instructions on the official [LLaMA repository](https://github.com/facebookresearch/llama).
Once downloaded, you should ... | 0 |
public_repos/lit-llama | public_repos/lit-llama/howto/customize_paths.md | ## Customize paths
The project is setup to use specific paths to read the original weights and save checkpoints etc.
For all scripts, you can run
```shell
python script.py -h
```
to get a list of available options. For instance, here's how you would modify the checkpoint dir:
```shell
python scripts/convert_checkp... | 0 |
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