Ollama

ollama

Ollama is a local inference framework client that allows one-click deployment of LLMs such as Llama 2, Mistral, Llava, etc. Dify supports integrating LLM and Text Embedding capabilities of large language models deployed with Ollama.

Quick Integration

Download and Launch Ollama

1. Download Ollama

   Visit https://ollama.ai/download to download the Ollama client for your system.

2. Run Ollama and Chat with Llava

   ollama run llava

   After successful launch, Ollama starts an API service on local port 11434, which can be accessed at http://localhost:11434.

   For other models, visit Ollama Models for more details.

3. Integrate Ollama in Dify

   In Settings > Model Providers > Ollama, fill in:

   

   • Model Name: llava

   • Base URL: http://<your-ollama-endpoint-domain>:11434

     Enter the base URL where the Ollama service is accessible.

     If Dify is deployed using docker, consider using the local network IP address, e.g., http://192.168.1.100:11434 or the docker host machine IP address, e.g., http://172.17.0.1:11434.

     For local source code deployment, use http://localhost:11434.

   • Model Type: Chat

   • Model Context Length: 4096

     The maximum context length of the model. If unsure, use the default value of 4096.

   • Maximum Token Limit: 4096

     The maximum number of tokens returned by the model. If there are no specific requirements for the model, this can be consistent with the model context length.

   • Support for Vision: Yes

     Check this option if the model supports image understanding (multimodal), like llava.

   Click "Save" to use the model in the application after verifying that there are no errors.

   The integration method for Embedding models is similar to LLM, just change the model type to Text Embedding.

4. Use Ollama Models

   

   Enter Prompt Eng. page of the App that needs to be configured, select the llava model under the Ollama provider, and use it after configuring the model parameters.

FAQ

⚠️ If you are using docker to deploy Dify and Ollama, you may encounter the following error:

httpconnectionpool(host=127.0.0.1, port=11434): max retries exceeded with url:/cpi/chat (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f8562812c20>: fail to establish a new connection:[Errno 111] Connection refused'))

httpconnectionpool(host=localhost, port=11434): max retries exceeded with url:/cpi/chat (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f8562812c20>: fail to establish a new connection:[Errno 111] Connection refused'))

This error occurs because the Ollama service is not accessible from the docker container. localhost usually refers to the container itself, not the host machine or other containers. To resolve this issue, you need to expose the Ollama service to the network.

Setting environment variables on Mac

If Ollama is run as a macOS application, environment variables should be set using launchctl:

1. For each environment variable, call launchctl setenv.

   launchctl setenv OLLAMA_HOST "0.0.0.0"

2. Restart Ollama application.

Setting environment variables on Linux

If Ollama is run as a systemd service, environment variables should be set using systemctl:

1. Edit the systemd service by calling systemctl edit ollama.service. This will open an editor.

2. For each environment variable, add a line Environment under section [Service]:

   [Service]
   Environment="OLLAMA_HOST=0.0.0.0"

3. Save and exit.

4. Reload systemd and restart Ollama:

   systemctl daemon-reload
   systemctl restart ollama

Setting environment variables on Windows

On windows, Ollama inherits your user and system environment variables.

1. First Quit Ollama by clicking on it in the task bar

2. Edit system environment variables from the control panel

3. Edit or create New variable(s) for your user account for OLLAMA_HOST, OLLAMA_MODELS, etc.

4. Click OK/Apply to save

5. Run ollama from a new terminal window

How can I expose Ollama on my network?

Ollama binds 127.0.0.1 port 11434 by default. Change the bind address with the OLLAMA_HOST environment variable.

More Information

For more information on Ollama, please refer to:

• Ollama

• Ollama FAQ