Local Source Code Start

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Prerequisites

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Setup Docker and Docker Compose

Before installing Dify, make sure your machine meets the following minimum system requirements:

• CPU >= 2 Core
• RAM >= 4 GiB

If you need to use OpenAI TTS, FFmpeg must be installed on the system for it to function properly. For more details, refer to: Link.

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Clone Dify Repository

Run the git command to clone the Dify repository.

git clone https://github.com/langgenius/dify.git

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Start Middlewares with Docker Compose

A series of middlewares for storage (e.g. PostgreSQL / Redis / Weaviate (if not locally available)) and extended capabilities (e.g. Dify’s sandbox and plugin-daemon services) are required by Dify backend services. Start the middlewares with Docker Compose by running these commands:

cd docker
cp middleware.env.example middleware.env
docker compose -f docker-compose.middleware.yaml up -d

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Setup Backend Services

The backend services include

1. API Service: serving API requests for Frontend service and API accessing
2. Worker Service: serving the aync tasks for datasets processing, workspaces, cleaning-ups etc.

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Environment Preparation

Python 3.12 is required. It is recommended to use pyenv for quick installation of the Python environment.

To install additional Python versions, use pyenv install.

pyenv install 3.12

To switch to the “3.12” Python environment, use the following command:

pyenv global 3.12

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Start API service

1. Navigate to the api directory:

   cd api
   

2. Prepare the environment variable config file

   cp .env.example .env
   

3. Generate a random secret key and replace the value of SECRET_KEY in the .env file

   awk -v key="$(openssl rand -base64 42)" '/^SECRET_KEY=/ {sub(/=.*/, "=" key)} 1' .env > temp_env && mv temp_env .env
   

4. Dependencies installation

   uv is used to manage dependencies. Install the required dependencies with uv by running:

   uv sync
   

   For macOS: install libmagic with brew install libmagic.

5. Perform the database migration

   Perform database migrations to the latest version:

   uv run flask db upgrade
   

6. Start the API service

   uv run flask run --host 0.0.0.0 --port=5001 --debug
   

   Expected output:

   * Debug mode: on
   INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead.
    * Running on all addresses (0.0.0.0)
    * Running on http://127.0.0.1:5001
   INFO:werkzeug:Press CTRL+C to quit
   INFO:werkzeug: * Restarting with stat
   WARNING:werkzeug: * Debugger is active!
   INFO:werkzeug: * Debugger PIN: 695-801-919
   

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Start the Worker service

To consume asynchronous tasks from the queue, such as dataset file import and dataset document updates, follow these steps to start the Worker service

• for macOS or Linux

  uv run celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail,ops_trace
  

  If you are using a Windows system to start the Worker service, please use the following command instead:

• for Windows

  uv run celery -A app.celery worker -P solo --without-gossip --without-mingle -Q dataset,generation,mail,ops_trace --loglevel INFO
  

  Expected output:

  -------------- celery@bwdeMacBook-Pro-2.local v5.4.0 (opalescent)
  --- ***** -----
  -- ******* ---- macOS-15.4.1-arm64-arm-64bit 2025-04-28 17:07:14
  - *** --- * ---
  - ** ---------- [config]
  - ** ---------- .> app:         app_factory:0x1439e8590
  - ** ---------- .> transport:   redis://:**@localhost:6379/1
  - ** ---------- .> results:     postgresql://postgres:**@localhost:5432/dify
  - *** --- * --- .> concurrency: 1 (gevent)
    -- ******* ---- .> task events: OFF (enable -E to monitor tasks in this worker)
    --- ***** -----
    -------------- [queues]
    .> dataset          exchange=dataset(direct) key=dataset
    .> generation       exchange=generation(direct) key=generation
    .> mail             exchange=mail(direct) key=mail
    .> ops_trace        exchange=ops_trace(direct) key=ops_trace
  
  [tasks]
  . schedule.clean_embedding_cache_task.clean_embedding_cache_task
  . schedule.clean_messages.clean_messages
  . schedule.clean_unused_datasets_task.clean_unused_datasets_task
  . schedule.create_tidb_serverless_task.create_tidb_serverless_task
  . schedule.mail_clean_document_notify_task.mail_clean_document_notify_task
  . schedule.update_tidb_serverless_status_task.update_tidb_serverless_status_task
  . tasks.add_document_to_index_task.add_document_to_index_task
  . tasks.annotation.add_annotation_to_index_task.add_annotation_to_index_task
  . tasks.annotation.batch_import_annotations_task.batch_import_annotations_task
  . tasks.annotation.delete_annotation_index_task.delete_annotation_index_task
  . tasks.annotation.disable_annotation_reply_task.disable_annotation_reply_task
  . tasks.annotation.enable_annotation_reply_task.enable_annotation_reply_task
  . tasks.annotation.update_annotation_to_index_task.update_annotation_to_index_task
  . tasks.batch_clean_document_task.batch_clean_document_task
  . tasks.batch_create_segment_to_index_task.batch_create_segment_to_index_task
  . tasks.clean_dataset_task.clean_dataset_task
  . tasks.clean_document_task.clean_document_task
  . tasks.clean_notion_document_task.clean_notion_document_task
  . tasks.deal_dataset_vector_index_task.deal_dataset_vector_index_task
  . tasks.delete_account_task.delete_account_task
  . tasks.delete_segment_from_index_task.delete_segment_from_index_task
  . tasks.disable_segment_from_index_task.disable_segment_from_index_task
  . tasks.disable_segments_from_index_task.disable_segments_from_index_task
  . tasks.document_indexing_sync_task.document_indexing_sync_task
  . tasks.document_indexing_task.document_indexing_task
  . tasks.document_indexing_update_task.document_indexing_update_task
  . tasks.duplicate_document_indexing_task.duplicate_document_indexing_task
  . tasks.enable_segments_to_index_task.enable_segments_to_index_task
  . tasks.mail_account_deletion_task.send_account_deletion_verification_code
  . tasks.mail_account_deletion_task.send_deletion_success_task
  . tasks.mail_email_code_login.send_email_code_login_mail_task
  . tasks.mail_invite_member_task.send_invite_member_mail_task
  . tasks.mail_reset_password_task.send_reset_password_mail_task
  . tasks.ops_trace_task.process_trace_tasks
  . tasks.recover_document_indexing_task.recover_document_indexing_task
  . tasks.remove_app_and_related_data_task.remove_app_and_related_data_task
  . tasks.remove_document_from_index_task.remove_document_from_index_task
  . tasks.retry_document_indexing_task.retry_document_indexing_task
  . tasks.sync_website_document_indexing_task.sync_website_document_indexing_task
  
  2025-04-28 17:07:14,681 INFO [connection.py:22]  Connected to redis://:**@localhost:6379/1
  2025-04-28 17:07:14,684 INFO [mingle.py:40]  mingle: searching for neighbors
  2025-04-28 17:07:15,704 INFO [mingle.py:49]  mingle: all alone
  2025-04-28 17:07:15,733 INFO [worker.py:175]  celery@bwdeMacBook-Pro-2.local ready.
  2025-04-28 17:07:15,742 INFO [pidbox.py:111]  pidbox: Connected to redis://:**@localhost:6379/1.
  

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Setup Web Service

Start the web service is built for frontend pages .

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Environment Preparation

To start the web frontend service, Node.js v22 (LTS) and PNPM v10 are requied.

• Install NodeJS

  Please visit https://nodejs.org/en/download and choose the installation package for your respective operating system that is v18.x or higher. LTS version is recommanded for common usages.

• Install PNPM

  Follow the the installation guidance to install PNPM. Or just run this command to install pnpm with npm.

  npm i -g pnpm
  

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Start Web Service

1. Enter the web directory

   cd web
   

2. Dependencies installation

   pnpm install --frozen-lockfile
   

3. Prepare the environment variable config file

   Create a file named .env.local in the current directory and copy the contents from .env.example. Modify the values of these environment variables according to your requirements:

   # For production release, change this to PRODUCTION
   NEXT_PUBLIC_DEPLOY_ENV=DEVELOPMENT
   # The deployment edition, SELF_HOSTED or CLOUD
   NEXT_PUBLIC_EDITION=SELF_HOSTED
   # The base URL of console application, refers to the Console base URL of WEB service if console domain is
   # different from api or web app domain.
   # example: http://cloud.dify.ai/console/api
   NEXT_PUBLIC_API_PREFIX=http://localhost:5001/console/api
   # The URL for Web APP, refers to the Web App base URL of WEB service if web app domain is different from
   # console or api domain.
   # example: http://udify.app/api
   NEXT_PUBLIC_PUBLIC_API_PREFIX=http://localhost:5001/api
   
   # SENTRY
   NEXT_PUBLIC_SENTRY_DSN=
   NEXT_PUBLIC_SENTRY_ORG=
   NEXT_PUBLIC_SENTRY_PROJECT=
   

4. Build the web service

   pnpm build
   

5. Start the web service

   pnpm start
   

   Expected output：

      ▲ Next.js 15
      - Local:        http://localhost:3000
      - Network:      http://0.0.0.0:3000
   
    ✓ Starting...
    ✓ Ready in 73ms
   

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Access Dify

Access http://127.0.0.1:3000 via browsers to enjoy all the exciting features of Dify. Cheers ! 🍻