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# 🖥️ Command Line Interface (CLI)
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## Overview
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Langflow's Command Line Interface (CLI) is a powerful tool that allows you to interact with the Langflow server from the command line. The CLI provides a wide range of commands to help you shape Langflow to your needs.
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Running the CLI without any arguments will display a list of available commands and options.
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```bash
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python -m langflow --help
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# or
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python -m langflow
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```
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Each option is detailed below:
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- `--help`: Displays all available options.
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- `--host`: Defines the host to bind the server to. Can be set using the `LANGFLOW_HOST` environment variable. The default is `127.0.0.1`.
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- `--workers`: Sets the number of worker processes. Can be set using the `LANGFLOW_WORKERS` environment variable. The default is `1`.
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- `--timeout`: Sets the worker timeout in seconds. The default is `60`.
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- `--port`: Sets the port to listen on. Can be set using the `LANGFLOW_PORT` environment variable. The default is `7860`.
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- `--config`: Defines the path to the configuration file. The default is `config.yaml`.
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- `--env-file`: Specifies the path to the .env file containing environment variables. The default is `.env`.
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- `--log-level`: Defines the logging level. Can be set using the `LANGFLOW_LOG_LEVEL` environment variable. The default is `critical`.
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- `--components-path`: Specifies the path to the directory containing custom components. Can be set using the `LANGFLOW_COMPONENTS_PATH` environment variable. The default is `langflow/components`.
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- `--log-file`: Specifies the path to the log file. Can be set using the `LANGFLOW_LOG_FILE` environment variable. The default is `logs/langflow.log`.
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- `--cache`: Select the type of cache to use. Options are `InMemoryCache` and `SQLiteCache`. Can be set using the `LANGFLOW_LANGCHAIN_CACHE` environment variable. The default is `SQLiteCache`.
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- `--dev/--no-dev`: Toggles the development mode. The default is `no-dev`.
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- `--path`: Specifies the path to the frontend directory containing build files. This option is for development purposes only. Can be set using the `LANGFLOW_FRONTEND_PATH` environment variable.
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- `--open-browser/--no-open-browser`: Toggles the option to open the browser after starting the server. Can be set using the `LANGFLOW_OPEN_BROWSER` environment variable. The default is `open-browser`.
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- `--remove-api-keys/--no-remove-api-keys`: Toggles the option to remove API keys from the projects saved in the database. Can be set using the `LANGFLOW_REMOVE_API_KEYS` environment variable. The default is `no-remove-api-keys`.
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- `--install-completion [bash|zsh|fish|powershell|pwsh]`: Installs completion for the specified shell.
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- `--show-completion [bash|zsh|fish|powershell|pwsh]`: Shows completion for the specified shell, allowing you to copy it or customize the installation.
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- `--backend-only`: This parameter, with a default value of `False`, allows running only the backend server without the frontend. It can also be set using the `LANGFLOW_BACKEND_ONLY` environment variable.
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- `--store`: This parameter, with a default value of `True`, enables the store features, use `--no-store` to deactivate it. It can be configured using the `LANGFLOW_STORE` environment variable.
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These parameters are important for users who need to customize the behavior of Langflow, especially in development or specialized deployment scenarios.
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### Environment Variables
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You can configure many of the CLI options using environment variables. These can be exported in your operating system or added to a `.env` file and loaded using the `--env-file` option.
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A sample `.env` file named `.env.example` is included with the project. Copy this file to a new file named `.env` and replace the example values with your actual settings. If you're setting values in both your OS and the `.env` file, the `.env` settings will take precedence.
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27
docs/docs/getting-started/huggingface-spaces.mdx
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docs/docs/getting-started/huggingface-spaces.mdx
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import ThemedImage from "@theme/ThemedImage";
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import useBaseUrl from "@docusaurus/useBaseUrl";
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import ZoomableImage from "/src/theme/ZoomableImage.js";
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import Admonition from "@theme/Admonition";
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# 🤗 HuggingFace Spaces
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Hugging Face provides a great alternative for running Langflow in their Spaces environment. This means you can run Langflow without any local installation required.
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The first step is to go to the [Langflow Space](https://huggingface.co/spaces/Langflow/Langflow?duplicate=true) or [Langflow 1.0 Preview Space](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
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Remember to use a Chromium-based browser for the best experience. You'll be presented with the following screen:
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<ZoomableImage
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alt="Docusaurus themed image"
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sources={{
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light: "img/duplicate-space.png",
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dark: "img/duplicate-space.png",
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}}
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style={{ width: "100%", margin: "20px auto" }}
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/>
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From here, just name your Space, define the visibility (Public or Private), and click on `Duplicate Space` to start the installation process. When that is done, you'll be redirected to the Space's main page to start using Langflow right away!
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Once you get Langflow running, click on New Project in the top right corner of the screen. Langflow provides a range of example flows to help you get started.
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To quickly try one of them, open a starter example, set up your API keys and click ⚡ Run, on the bottom right corner of the canvas. This will open up Langflow's Interaction Panel with the chat console, text inputs, and outputs.
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docs/docs/getting-started/install-langflow.mdx
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77
docs/docs/getting-started/install-langflow.mdx
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import ThemedImage from "@theme/ThemedImage";
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import useBaseUrl from "@docusaurus/useBaseUrl";
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import ZoomableImage from "/src/theme/ZoomableImage.js";
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import Admonition from "@theme/Admonition";
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# 📦 Install Langflow
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<Admonition type="info">
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Langflow v1.0 is also available in a [HuggingFace Preview Space](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) if you'd rather try it out before installing locally.
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</Admonition>
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## Prerequisites
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Langflow requires the following programs installed on your system.
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* [Python 3.10](https://www.python.org/downloads/release/python-3100/)
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* [pip](https://pypi.org/project/pip/) or [pipx](https://pipx.pypa.io/stable/installation/)
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## Install Langflow
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To install Langflow:
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pip:
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```bash
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python -m pip install langflow -U
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```
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pipx:
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```bash
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pipx install langflow --python python3.10 --fetch-missing-python
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```
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Pipx can fetch the missing Python version for you with `--fetch-missing-python`, but you can also install the Python version manually.
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## Install Langflow pre-release
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Use `--force-reinstall` to ensure you have the latest version of Langflow and its dependencies.
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To install a pre-release version of Langflow:
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pip:
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```bash
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python -m pip install langflow --pre --force-reinstall
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```
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pipx:
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```bash
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pipx install langflow --python python3.10 --fetch-missing-python --pip-args="--pre --force-reinstall"
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```
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## Having a problem?
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If you encounter a problem, see [Possible Installation Issues](/migration/possible-installation-issues).
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To get help in the Langflow CLI:
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```bash
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python -m langflow --help
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```
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## ⛓️ Run Langflow
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1. To run Langflow, enter the following command.
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```bash
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python -m langflow run
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```
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2. Confirm that a local Langflow instance starts by visiting `http://127.0.0.1:7860` in your browser.
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```bash
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│ Welcome to ⛓ Langflow │
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│ │
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│ Access http://127.0.0.1:7860 │
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│ Collaborate, and contribute at our GitHub Repo 🚀 │
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```
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3. Continue on to the [Quickstart](./quickstart.mdx).
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docs/docs/getting-started/new-to-llms.mdx
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# 📚 New to LLMs?
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Large Language Models, or LLMs, are part of an exciting new world in computing.
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We made Langflow for anyone to create with LLMs, and hope you'll feel comfortable installing Langflow and [getting started](./quickstart.mdx).
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If you want to learn more about LLMs, prompt engineering, and AI models, Langflow recommends [promptingguide.ai](https://promptingguide.ai), an open-source repository of prompt engineering content maintained by AI experts.
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PromptingGuide offers content for [beginners](https://www.promptingguide.ai/introduction/basics) and [experts](https://www.promptingguide.ai/techniques/cot), as well as the latest [research papers](https://www.promptingguide.ai/papers) and [test results](https://www.promptingguide.ai/research) fueling AI's progress.
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Wherever you are on your AI journey, it's helpful to keep Prompting Guide open in a tab.
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docs/docs/getting-started/quickstart.mdx
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119
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import ThemedImage from "@theme/ThemedImage";
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import useBaseUrl from "@docusaurus/useBaseUrl";
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import ZoomableImage from "/src/theme/ZoomableImage.js";
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import ReactPlayer from "react-player";
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import Admonition from "@theme/Admonition";
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# ⚡️ Quickstart
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This quickstart demonstrates how to install Langflow, run it locally, build a basic prompt flow, and modify that prompt for different outcomes.
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## Prerequisites
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* [Python 3.10](https://www.python.org/downloads/release/python-3100/)
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* [pip](https://pypi.org/project/pip/) or [pipx](https://pipx.pypa.io/stable/installation/)
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* [OpenAI API key](https://platform.openai.com)
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## Install Langflow
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<Admonition type="info">
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Langflow v1.0 is also available in a [HuggingFace Preview Space](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) if you'd rather try it out before installing locally. This quickstart will run there, too.
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</Admonition>
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1. To install Langflow, enter the following command in pip or pipx:
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pip:
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```bash
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python -m pip install langflow -U
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```
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pipx:
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```bash
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pipx install langflow --python python3.10 --fetch-missing-python
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```
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Pipx can fetch the missing Python version for you with `--fetch-missing-python`, but you can also install the Python version manually.
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2. Start a local Langflow instance with the Langflow CLI:
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```bash
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langflow run
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```
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Or start Langflow with Python:
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```bash
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python -m langflow run
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```
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Result:
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```
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│ Welcome to ⛓ Langflow │
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│ │
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│ Access http://127.0.0.1:7860 │
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│ Collaborate, and contribute at our GitHub Repo 🚀 │
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```
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3. Go to `http://127.0.0.1:7860` and confirm the Langflow UI is available.
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<Admonition type="info">
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If you encounter a problem, see [Possible Installation Issues](/migration/possible-installation-issues).
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</Admonition>
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## Create the basic prompting project
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Now that you have Langflow installed and running, let us formally welcome you to Langflow!👋
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You will use Langflow's prompt tools to issue prompts to the OpenAI LLM.
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Prompts serve as the inputs to a large language model (LLM), acting as the interface between human instructions and computational tasks.
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By submitting natural language requests in a prompt to an LLM, you can obtain answers, generate text, and solve problems.
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1. From the Langflow dashboard, click **New Project**.
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2. Select **Basic Prompting**.
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3. The **Basic Prompting** flow is created.
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<ZoomableImage
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alt="Docusaurus themed image"
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sources={{
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light: "img/quickstart.png",
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dark: "img/quickstart.png",
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}}
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style={{ width: "80%", margin: "20px auto" }}
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/>
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This flow allows you to chat with the **OpenAI** component via a **Prompt** component.
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Examine the **Prompt** component. The **Template** field instructs the LLM to `Answer the user as if you were a pirate.`
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This should be interesting...
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4. To create an environment variable for the **OpenAI** component, in the **OpenAI API Key** field, click the **Globe** button, and then click **Add New Variable**.
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1. In the **Variable Name** field, enter `openai_api_key`.
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2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
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3. Click **Save Variable**.
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## Run the basic prompting flow
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1. Click the **Run** button.
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The **Interaction Panel** opens, where you can converse with your bot.
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2. Type a message and press Enter.
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The bot responds in a markedly piratical manner!
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## Modify the prompt for a different result
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1. To modify your prompt results, in the **Prompt** template, click the **Template** field.
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The **Edit Prompt** window opens.
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2. Change `Answer the user as if you were a pirate` to a different character, perhaps `Answer the user as if you were Harold Abelson.`
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3. Run the basic prompting flow again.
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The response will be markedly different.
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## Next steps
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Well done! You've built your first prompt in Langflow. 🎉
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By adding Langflow components to this prompt, you can build all sorts of interesting flows.
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* [Memory chatbot](/starter-projects/memory-chatbot.mdx)
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* [Blog writer](/starter-projects/blog-writer.mdx)
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* [Document QA](/starter-projects/document-qa.mdx)
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