mirror of
https://github.com/hwchase17/langchain
synced 2024-10-31 15:20:26 +00:00
170 lines
3.9 KiB
Plaintext
170 lines
3.9 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Tongyi Qwen\n",
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"Tongyi Qwen is a large-scale language model developed by Alibaba's Damo Academy. It is capable of understanding user intent through natural language understanding and semantic analysis, based on user input in natural language. It provides services and assistance to users in different domains and tasks. By providing clear and detailed instructions, you can obtain results that better align with your expectations."
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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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"metadata": {
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"ExecuteTime": {
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"end_time": "2023-07-10T19:55:36.492467Z",
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"start_time": "2023-07-10T19:55:34.037914Z"
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}
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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 dashscope"
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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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"metadata": {
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"ExecuteTime": {
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"end_time": "2023-07-10T19:55:38.553933Z",
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"start_time": "2023-07-10T19:55:36.492287Z"
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}
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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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"# Get a new token: https://help.aliyun.com/document_detail/611472.html?spm=a2c4g.2399481.0.0\n",
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"from getpass import getpass\n",
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"\n",
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"DASHSCOPE_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": 3,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2023-07-10T19:55:38.554152Z",
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"start_time": "2023-07-10T19:55:38.537376Z"
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}
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},
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"outputs": [],
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"source": [
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"import os\n",
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"\n",
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"os.environ[\"DASHSCOPE_API_KEY\"] = DASHSCOPE_API_KEY"
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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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"metadata": {
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"ExecuteTime": {
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"end_time": "2023-07-10T19:55:39.812664Z",
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"start_time": "2023-07-10T19:55:38.540246Z"
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}
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},
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"outputs": [],
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"source": [
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"from langchain.llms import Tongyi\n",
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"from langchain import PromptTemplate, LLMChain"
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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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"metadata": {
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"ExecuteTime": {
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"end_time": "2023-07-10T19:55:39.817327Z",
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"start_time": "2023-07-10T19:55:39.814825Z"
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}
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},
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"outputs": [],
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"source": [
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"template = \"\"\"Question: {question}\n",
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"\n",
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"Answer: Let's think step by step.\"\"\"\n",
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"\n",
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"prompt = PromptTemplate(template=template, input_variables=[\"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": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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"llm = Tongyi()"
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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": 7,
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"metadata": {},
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"outputs": [],
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"source": [
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"llm_chain = LLMChain(prompt=prompt, llm=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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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"\"The year Justin Bieber was born was 1994. The Denver Broncos won the Super Bowl in 1997, which means they would have been the team that won the Super Bowl during Justin Bieber's birth year. So the answer is the Denver Broncos.\""
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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 NFL team won the Super Bowl in the year Justin Beiber was born?\"\n",
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"\n",
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"llm_chain.run(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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"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": "3.10.12"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 1
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}
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