mirror of
https://github.com/hwchase17/langchain.git
synced 2026-04-24 04:36:46 +00:00
00a09e1b71
Ran
```python
import glob
import re
def update_prompt(x):
return re.sub(
r"(?P<start>\b)PromptTemplate\(template=(?P<template>.*), input_variables=(?:.*)\)",
"\g<start>PromptTemplate.from_template(\g<template>)",
x
)
for fn in glob.glob("docs/**/*", recursive=True):
try:
content = open(fn).readlines()
except:
continue
content = [update_prompt(l) for l in content]
with open(fn, "w") as f:
f.write("".join(content))
```
171 lines
3.3 KiB
Plaintext
171 lines
3.3 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "9597802c",
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"metadata": {},
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"source": [
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"# Aleph Alpha\n",
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"\n",
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"[The Luminous series](https://docs.aleph-alpha.com/docs/introduction/luminous/) is a family of large language models.\n",
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"\n",
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"This example goes over how to use LangChain to interact with Aleph Alpha models"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "fe1bf9fb-e9fa-49f3-a768-8f603225ccce",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"# Install the package\n",
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"%pip install --upgrade --quiet aleph-alpha-client"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "0cb0f937-b610-42a2-b765-336eed037031",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"········\n"
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]
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}
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],
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"source": [
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"# create a new token: https://docs.aleph-alpha.com/docs/account/#create-a-new-token\n",
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"\n",
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"from getpass import getpass\n",
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"\n",
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"ALEPH_ALPHA_API_KEY = getpass()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "6fb585dd",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"from langchain.prompts import PromptTemplate\n",
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"from langchain_community.llms import AlephAlpha"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "f81a230d",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"template = \"\"\"Q: {question}\n",
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"\n",
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"A:\"\"\"\n",
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"\n",
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"prompt = PromptTemplate.from_template(template)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "f0d26e48",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"llm = AlephAlpha(\n",
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" model=\"luminous-extended\",\n",
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" maximum_tokens=20,\n",
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" stop_sequences=[\"Q:\"],\n",
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" aleph_alpha_api_key=ALEPH_ALPHA_API_KEY,\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "6811d621",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"llm_chain = prompt | llm"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"id": "3058e63f",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"' Artificial Intelligence is the simulation of human intelligence processes by machines.\\n\\n'"
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]
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"question = \"What is AI?\"\n",
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"\n",
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"llm_chain.invoke({\"question\": question})"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "a3544eff",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.12"
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},
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"vscode": {
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"interpreter": {
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"hash": "2d002ec47225e662695b764370d7966aa11eeb4302edc2f497bbf96d49c8f899"
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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