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Release/v2.2 (#1226)
* feat(pandasai_server): pandasai server code commit * fix(docker-compose): add pandasbi backend in docker * fix(pandasai-lint): sort linting errors * refactor: rename modle file name * feat(chat): adding chat endpoint * fix: remove some keywords from spellcheck * fix: poetry lock file * me api integrated * chat api integrated * renamed, fix and add documentation * workspace replaced * fix: add conversation id to response * feat(conversation): return all user conversations * fix: should be equal equal * feat(pandasai_server): pandasai server code commit (#1189) * feat(pandasai_server): pandasai server code commit * fix(docker-compose): add pandasbi backend in docker * fix(pandasai-lint): sort linting errors * refactor: rename modle file name * feat(chat): adding chat endpoint * fix: remove some keywords from spellcheck * fix: poetry lock file * me api integrated * chat api integrated * renamed, fix and add documentation * workspace replaced * fix: add conversation id to response * feat(conversation): return all user conversations * fix: should be equal equal --------- Co-authored-by: Shahrukh Khan <srkbannu@gmail.com> * get all datasets endpoint completed * feat(conversation_messages): return conversation messages (#1196) * get all datasets endpoint completed (#1197) * chore: update poetry.lock * chore: add pgdata to gitignore * chore: fix postgres url in the server .env example * chore: add .env.example for the client * fix: add rollbar * fix: wrong redirects * fix: docker compose to wait for postgres before starting (#1198) * fix: response message should be value for strings and numbers (#1199) * docs: mention the platform in the docs * style: hide rightbar for now * style: move the "new chat" button next to chat * [PAN-816]: Past conversations integrated and workspace removed (#1200) * feat(conversation_messages): return conversation messages * past conversations integrated * workspace page removed * workspace page removed * workspace page removed * workspace page removed * bugfix --------- Co-authored-by: ArslanSaleem <khan.arslan38@gmail.com> * style: remove tooltip from the sidebar * style: clean up the UI * chore: fix typo in volume name * conversation actions removed * conversation actions removed (#1201) * fix: filter out empty conversations * docs: add platform in the docs * get users by workspace id api added * docs: add docs about the platform * pydantic response for workspace user added * workspace datasets endpoint added * archive conversation api added (#1209) * [PAN-820]: archive api integrated on frontend (#1210) * archive conversation api added * archive conversation integrated on frontend * chore: add link about the roadmap * past conversation issues fixed * [PAN-824]: Ui stuck fixed (#1215) * ui stuck fixed * docker fixed * style: ctas in the sidebar fade out on collapse * scroll to bottom bug fix (#1217) * tests(pandasai): write python test cases (#1216) * new conversation not adding to sidebar fixed * fix: frontend docker build (#1219) * merge main to release --------- Co-authored-by: ArslanSaleem <khan.arslan38@gmail.com> Co-authored-by: Shahrukh Khan <srkbannu@gmail.com> Co-authored-by: Shahrukh khan <59122336+shahrukh802@users.noreply.github.com>
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‎.gitignore‎

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# coverage
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.coverage
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coverage.xml
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# pgdata
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pgdata/

‎Makefile‎

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poetry run ruff --select I pandasai examples tests
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spell_check: ## run codespell on the project
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poetry run codespell --toml pyproject.toml --skip=$(IGNORE_FORMATS) -L NotIn
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poetry run codespell --toml pyproject.toml --ignore-words=ignore-words.txt --skip=$(IGNORE_FORMATS)
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spell_fix: ## run codespell on the project and fix the errors
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poetry run codespell --toml pyproject.toml --skip=$(IGNORE_FORMATS) -L NotIn -w
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poetry run codespell --toml pyproject.toml --ignore-words=ignore-words.txt --skip=$(IGNORE_FORMATS) -w
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######################
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# DOCS

‎README.md‎

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# ![PandasAI](images/logo.png)
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# ![PandasAI](assets/logo.png)
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[![Release](https://img.shields.io/pypi/v/pandasai?label=Release&style=flat-square)](https://pypi.org/project/pandasai/)
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[![CI](https://github.com/gventuri/pandas-ai/actions/workflows/ci.yml/badge.svg)](https://github.com/gventuri/pandas-ai/actions/workflows/ci.yml/badge.svg)
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[![Downloads](https://static.pepy.tech/badge/pandasai)](https://pepy.tech/project/pandasai) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
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[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1ZnO-njhL7TBOYPZaqvMvGtsjckZKrv2E?usp=sharing)
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PandasAI is a Python library that makes it easy to ask questions to your data in natural language. It helps you to explore, clean, and analyze your data using generative AI.
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PandasAI is a Python platform that makes it easy to ask questions to your data in natural language. It helps non-technical users to interact with their data in a more natural way, and it helps technical users to save time and effort when working with data.
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# 🚀 Deploying PandasAI
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PandasAI can be used in a variety of ways. You can easily use it in your Jupyter notebooks or streamlit apps, or you can deploy it as a REST API such as with FastAPI or Flask.
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If you are interested in the managed PandasAI Cloud or our self-hosted Enterprise Offering, take a look at [our website](https://pandas-ai.com) or [book a meeting with us](https://zcal.co/gventuri/pandas-ai-demo).
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# 🔧 Getting started
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The documentation for PandasAI to use it with specific LLMs, vector stores and connectors, can be found [here](https://pandas-ai.readthedocs.io/en/latest/).
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You can find the full documentation for PandasAI [here](https://pandas-ai.readthedocs.io/en/latest/).
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You can either decide to use PandasAI in your Jupyter notebooks, streamlit apps, or use the client and server architecture from the repo.
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## ☁️ Using the platform
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[![PandasAI platform](assets/demo.gif?raw=true)](https://www.youtube.com/watch?v=kh61wEy9GYM)
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### 📦 Installation
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PandasAI platform is uses a dockerized client-server architecture. You will need to have Docker installed in your machine.
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```bash
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git clone https://github.com/sinaptik-ai/pandas-ai/
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cd pandas-ai
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docker-compose build
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```
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### 🚀 Running the platform
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## 📦 Installation
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Once you have built the platform, you can run it with:
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```bash
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docker-compose up
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```
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This will start the client and server, and you can access the client at `http://localhost:3000`.
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## 📚 Using the library
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### 📦 Installation
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You can install the PandasAI library using pip or poetry.
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```
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## 🔍 Demo
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### 🔍 Demo
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Try out PandasAI yourself in your browser:
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Try out the PandasAI library yourself in your browser:
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[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1ZnO-njhL7TBOYPZaqvMvGtsjckZKrv2E?usp=sharing)
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# 🚀 Deploying PandasAI
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PandasAI can be deployed in a variety of ways. You can easily use it in your Jupyter notebooks or streamlit apps, or you can deploy it as a REST API such as with FastAPI or Flask.
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If you are interested in managed PandasAI Cloud or self-hosted Enterprise Offering, take a look at [our website](https://pandas-ai.com) or [book a meeting with us](https://zcal.co/gventuri/pandas-ai-demo).
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## 💻 Usage
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### 💻 Usage
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### Ask questions
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#### Ask questions
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```python
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# Sample DataFrame
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sales_by_country = pd.DataFrame({
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"country": ["United States", "United Kingdom", "France", "Germany", "Italy", "Spain", "Canada", "Australia", "Japan", "China"],
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"sales": [5000, 3200, 2900, 4100, 2300, 2100, 2500, 2600, 4500, 7000]
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"revenue": [5000, 3200, 2900, 4100, 2300, 2100, 2500, 2600, 4500, 7000]
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})
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# By default, unless you choose a different LLM, it will use BambooLLM.
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The total sales for the top 3 countries by sales is 16500.
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### Visualize charts
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#### Visualize charts
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You can also ask PandasAI to generate charts for you:
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```python
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agent.chat(
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"Plot the histogram of countries showing for each the gdp, using different colors for each bar",
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"Plot the histogram of countries showing for each one the gd. Use different colors for each bar",
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)
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```
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![Chart](images/histogram-chart.png?raw=true)
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![Chart](assets/histogram-chart.png?raw=true)
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### Multiple DataFrames
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#### Multiple DataFrames
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You can also pass in multiple dataframes to PandasAI and ask questions relating them.
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‎assets/demo.gif‎

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‎client/.env.example‎

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# THE URL OF YOUR CLIENT
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NEXT_PUBLIC_API_URL='http://localhost:8000/'
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# ENVIRONMENT
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NEXT_PUBLIC_ROLLBAR_CLIENT_TOKEN="development"
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# ANALYTICS
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NEXT_PUBLIC_MIXPANEL_TOKEN="04a81d58ade99299e19e5a89fe84c670"
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NEXT_PUBLIC_GOOGLE_ANALYTICS_ID="G-SD7MBGS6J9"
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# SUPPORT CHAT
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NEXT_PUBLIC_INTERCOM_APP_ID="jzfk3qc5"
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# ENV
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NODE_ENV="development"

‎client/.eslintrc.json‎

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{
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"env": {
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"browser": true,
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"es2021": true
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},
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"extends": [
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"next/core-web-vitals",
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"eslint:recommended",
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"plugin:@typescript-eslint/recommended",
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"plugin:react/recommended"
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],
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"parser": "@typescript-eslint/parser",
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"parserOptions": {
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"ecmaVersion": 2023,
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"sourceType": "module"
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},
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"plugins": [
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"@typescript-eslint",
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"react"
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],
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"rules": {
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"react/no-unescaped-entities": ["error", { "forbid": [">", "}"] }],
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"@typescript-eslint/no-explicit-any": "off",
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"no-useless-catch": "off",
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"react-hooks/exhaustive-deps": 0
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}
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}

‎client/.gitignore‎

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# See https://help.github.com/articles/ignoring-files/ for more about ignoring files.
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# dependencies
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/node_modules
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/.pnp
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.pnp.js
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.yarn/install-state.gz
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# testing
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/coverage
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# next.js
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/.next/
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/out/
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# production
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/build
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# misc
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.DS_Store
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*.pem
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# debug
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npm-debug.log*
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yarn-debug.log*
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yarn-error.log*
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# local env files
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.env*.local
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.env
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# vercel
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.vercel
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# typescript
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*.tsbuildinfo
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next-env.d.ts
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# lock files
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package-lock.json
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yarn-lock.json

‎client/Dockerfile‎

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FROM node:19.4.0-alpine3.17
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WORKDIR /app
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COPY package*.json ./
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RUN npm install
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COPY . .
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RUN npm run build
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EXPOSE 3000
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CMD ["npm", "start"]

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