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https://github.com/kossakovsky/n8n-install.git
synced 2026-03-07 22:33:11 +00:00
Small doc fixes
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@@ -1,8 +1,11 @@
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# Change the name of this file to .env after updating it!
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############
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# [required]
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# n8n credentials - you set this to whatever you want, just make it a long and secure string for both!
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# [required]
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# n8n credentials - use the command `openssl rand -hex 32` to generate both
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# openssl is available by default on Linux/Mac
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# For Windows, you can use the 'Git Bash' terminal installed with git
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# Or run the command: python -c "import secrets; print(secrets.token_hex(32))"
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############
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N8N_ENCRYPTION_KEY=super-secret-key
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@@ -235,7 +235,7 @@ to the IP address of your cloud instance.
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**NOTE**: If you are using a cloud machine without the "docker compose" command available by default, such as a Ubuntu GPU instance on DigitalOcean, run these commands before running start_services.py:
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- DOCKER_COMPOSE_VERSION=$(curl -s https://api.github.com/repos/docker/compose/releases/latest | grep 'tag_name' | cut -d\" -f4)
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- DOCKER_COMPOSE_VERSION=$(curl -s https://api.github.com/repos/docker/compose/releases/latest | grep 'tag_name' | cut -d\\" -f4)
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- sudo curl -L "https://github.com/docker/compose/releases/download/${DOCKER_COMPOSE_VERSION}/docker-compose-linux-x86_64" -o /usr/local/bin/docker-compose
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- sudo chmod +x /usr/local/bin/docker-compose
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- sudo mkdir -p /usr/local/lib/docker/cli-plugins
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@@ -37,6 +37,9 @@ x-ollama: &service-ollama
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- 11434/tcp
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environment:
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- OLLAMA_CONTEXT_LENGTH=8192
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- OLLAMA_FLASH_ATTENTION=1
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- OLLAMA_KV_CACHE_TYPE=q8_0
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- OLLAMA_MAX_LOADED_MODELS=2
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volumes:
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- ollama_storage:/root/.ollama
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@@ -49,10 +52,6 @@ x-init-ollama: &init-ollama
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command:
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- "-c"
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- "sleep 3; OLLAMA_HOST=ollama:11434 ollama pull qwen2.5:7b-instruct-q4_K_M; OLLAMA_HOST=ollama:11434 ollama pull nomic-embed-text"
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# For a larger context length verison of the model, run these commands:
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# echo "FROM qwen2.5:7b-instruct-q4_K_M\n\nPARAMETER num_ctx 8096" > Modelfile
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# ollama create qwen2.5:7b-8k -f ./Modelfile
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# Change the name of the LLM and num_ctx as you see fit.
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services:
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flowise:
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