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renamed ai parameters, added BYOLLM page in ai features page, changed wording around LLMs, simplified install instructions, and other small changes
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Knox Lively
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---
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title: 'BYOLLM'
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description: 'Get up and running with your own LLM'
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---
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Wave AI supports the integration of any LLM provider that uses the same [OpenAI Chat Completions API](https://platform.openai.com/docs/api-reference/chat). This feature allows you to bring your own compatible LLM provider and seamlessly integrate it into your workflow.
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<Tip>
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To see a full list of supported LLM providers, please visit the [Third-Party LLM Support](/features/waveAI#third-party-llm-support) section in the Wave AI features page.
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</Tip>
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## Configuration
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After installing and configuring your own LLM provider, you can start using it in Wave by setting two parameters: `aibaseurl` and `aimodel`. These parameters can be set either through the UI or from the command line, but please note that the parameter names are slightly different depending on the method you choose.
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### **Parameters**
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- **AI Base URL:** Set this parameter to the base URL or endpoint that Wave AI should query.
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- **AI Model**: Specify the model name that you want to use.
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**Note:** If the provided URL (e.g., `http://localhost:8080/v1/chat/completions`) doesn't work, try removing the `/chat/completions` directories from the end of the URL or using just the hostname and port (e.g., `http://localhost:8080`). This often resolves compatibility issues and allows Wave AI to communicate with your LLM provider successfully.
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### Configuring via the UI
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To configure your own LLM provider from the Wave AI user interface, navigate to the "Settings" menu and set the `AI Base URL` and `AI Model` parameters as described in the previous section.
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### Configuring via the CLI
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To configure your own LLM provider using the command line, set the `aibaseurl` and `aimodel` parameters using the [/client:set](/reference/slashcommands#client-set) command, as shown in the example below.
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```
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/client:set aibaseurl=<your-base-url>
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/client:set aimodel=<your-model-name>
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```
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## Usage
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Once you have installed and configured your own LLM provider, you can start using it in Wave. There are two primary ways to interact with your newly configured LLM: [Interactive Mode](/features/waveAI#interactive) and by using the [/chat](/features/waveAI#chat-command) command.
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- **Interactive Mode:** To enter Interactive Mode, click the "Wave AI" button in the command box or use the `ctrl + space` shortcut. This will open an interactive chat session where you can have a continuous conversation with the AI assistant powered by your own LLM provider model.
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- **/chat:** Alternatively, you can use the [/chat](/features/waveAI#chat-command) command followed by your question to get a quick answer from your own LLM provider model directly in the terminal.
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## Troubleshooting
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If you encounter issues while using your own LLM provider with Wave AI, consider the following troubleshooting steps:
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- **Connection failures:** If Wave AI fails to connect to your own LLM provider or returns an error message, verify that your own LLM provider is running.
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- **Timeouts:** If you're unable to complete a query or incur frequent timeouts, try adjusting the [aitimeout](/features/waveAI#customization) parameter to a higher value. This will give your own LLM provider more time to process and respond to your requests, especially if you are running it on a system with limited hardware resources.
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- **Incorrect base URL or port:** Ensure that the [aibaseurl](/features/waveAI#customization) parameter points to the correct URL and port number where your own LLM provider is running. If you have changed the default port or are running your own LLM provider on a remote server, update the URL accordingly.
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- **Incorrect model selection:** If you have multiple LLMs installed, make sure to set the [aimodel](/features/waveAI#customization) parameter to the specific model you want to use.
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- **Unexpected behavior or inconsistent results:** If you encounter unexpected behavior or inconsistent results when using your own LLM provider with Wave AI, try [resetting](#reset-wave-ai) the `aibaseurl` and `aimodel` parameters to their default values and reconfiguring your LLM provider from scratch. This can help rule out any configuration issues that might be causing problems.
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## Reset Wave AI
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At any time if you find that you wish to return to the default Wave AI experience, you can reset the `aibaseurl` and `aimodel` parameters to their default state by using the following commands.
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```
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/client:set aibaseurl=
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/client:set aimodel=
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```
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**Note:** This can also be done in the UI just as described in previous steps.
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@@ -8,18 +8,18 @@ description: 'Get LocalAI up and running in Wave AI'
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**Note:** At the moment, Wave's integration with LocalAI only supports their LLM features. Image generation, audio processing, speech to text, and other capabilities are not yet available but may be added in future updates.
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<Tip>
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To see a full list of supported LLMs, please visit the [Third-Party LLM Support](/features/waveAI#third-party-llm-support) section in the Wave AI features page.
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To see a full list of supported LLM providers, please visit the [Third-Party LLM Support](/features/waveAI#third-party-llm-support) section in the Wave AI features page.
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</Tip>
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## Installation
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Please visit LocalAI's [quickstart](https://localai.io/basics/getting_started/) guide for instructions on downloading and installing LocalAI.
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## Configuration
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After installing and configuring LocalAI, you can start using it in Wave by setting two parameters: `openaibaseurl` and `openaimodel`. These parameters can be set either through the UI or from the command line, but please note that the parameter names are slightly different depending on the method you choose.
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After installing and configuring LocalAI, you can start using it in Wave by setting two parameters: `aibaseurl` and `aimodel`. These parameters can be set either through the UI or from the command line, but please note that the parameter names are slightly different depending on the method you choose.
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### **Parameters**
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- **Base URL:** Set this parameter to the base URL or endpoint that Wave AI should query. For LocalAI running locally, use http://localhost:8080. Please note that the port number `8080` may be different depending on your specific installation. For remote LocalAI instances, replace `localhost` with the appropriate hostname or IP address of the server where LocalAI is running. If the port number is different from the default `8080`, update it accordingly in the URL.
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- **AI Base URL:** Set this parameter to the base URL or endpoint that Wave AI should query. For LocalAI running locally, use http://localhost:8080. Please note that the port number `8080` may be different depending on your specific installation. For remote LocalAI instances, replace `localhost` with the appropriate hostname or IP address of the server where LocalAI is running. If the port number is different from the default `8080`, update it accordingly in the URL.
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- **AI Model**: Specify the LocalAI model you want to use. To discover available models, you can query the LocalAI endpoint, `/v1/models`.
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Example: http://localhost:8080/v1/models.
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@@ -28,11 +28,11 @@ After installing and configuring LocalAI, you can start using it in Wave by sett
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To configure LocalAI from the Wave AI user interface, navigate to the "Settings" menu and set the `AI Base URL` and `AI Model` parameters as described in the previous section.
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### Configuring via the CLI
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To configure LocalAI using the command line, set the `openaibaseurl` and `openaimodel` parameters using the [/client:set](/reference/slashcommands#client-set) command, as shown in the example below. Replace the values with the appropriate `Base URL` and `AI Model` for your LocalAI installation.
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To configure LocalAI using the command line, set the `aibaseurl` and `aimodel` parameters using the [/client:set](/reference/slashcommands#client-set) command, as shown in the example below.
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```
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/client:set openaibaseurl=<your-LocalAI-base-url>
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/client:set openaimodel=<your-LocalAI-model-name>
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/client:set aibaseurl=<your-LocalAI-base-url>
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/client:set aimodel=<your-LocalAI-model-name>
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```
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## Usage
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@@ -45,20 +45,20 @@ Once you have installed and configured LocalAI, you can start using it in Wave.
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If you encounter issues while using LocalAI with Wave AI, consider the following troubleshooting steps:
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- **Connection failures:** If Wave AI fails to connect to LocalAI or returns an error message, [verify that LocalAI is running](https://localai.io/basics/getting_started/#text-generation) and accessible from the system where Wave is installed. Check the LocalAI logs for any error messages or indications of why the connection might be failing.
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- **Timeouts:** If you're unable to complete a query or incur frequent timeouts, try adjusting the [openaitimeout](/features/waveAI#customization) parameter to a higher value. This will give LocalAI more time to process and respond to your requests, especially if you are running it on a system with limited hardware resources.
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- **Incorrect base URL or port:** Ensure that the [openaibaseurl](/features/waveAI#customization) parameter points to the correct URL and port number where LocalAI is running. If you have changed the default port or are running LocalAI on a remote server, update the URL accordingly.
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- **Incorrect model selection:** If you have multiple LocalAI models installed, make sure to set the [openaimodel](/features/waveAI#customization) parameter to the specific model you want to use. You can list available models using the LocalAI list command in your terminal.
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- **Unexpected behavior or inconsistent results:** If you encounter unexpected behavior or inconsistent results when using LocalAI with Wave AI, try [resetting](#reset-wave-ai) the openaibaseurl and openaimodel parameters to their default values and reconfiguring LocalAI from scratch. This can help rule out any configuration issues that might be causing problems.
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- **Timeouts:** If you're unable to complete a query or incur frequent timeouts, try adjusting the [aitimeout](/features/waveAI#customization) parameter to a higher value. This will give LocalAI more time to process and respond to your requests, especially if you are running it on a system with limited hardware resources.
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- **Incorrect base URL or port:** Ensure that the [aibaseurl](/features/waveAI#customization) parameter points to the correct URL and port number where LocalAI is running. If you have changed the default port or are running LocalAI on a remote server, update the URL accordingly.
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- **Incorrect model selection:** If you have multiple LocalAI models installed, make sure to set the [aimodel](/features/waveAI#customization) parameter to the specific model you want to use.
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- **Unexpected behavior or inconsistent results:** If you encounter unexpected behavior or inconsistent results when using LocalAI with Wave AI, try [resetting](#reset-wave-ai) the aibaseurl and aimodel parameters to their default values and reconfiguring LocalAI from scratch. This can help rule out any configuration issues that might be causing problems.
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If you continue to face issues after trying these troubleshooting steps, please see the [Additional Resources](#additional-resources) section below for further assistance.
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## Reset Wave AI
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At any time if you find that you wish to return to the default Wave AI experience, you can reset the `openaibaseurl` and `openaimodel` parameters to their default state by using the following commands.
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At any time if you find that you wish to return to the default Wave AI experience, you can reset the `aibaseurl` and `aimodel` parameters to their default state by using the following commands.
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```
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/client:set openaibaseurl=
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/client:set openaimodel=
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/client:set aibaseurl=
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/client:set aimodel=
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```
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**Note:** This can also be done in the UI just as described in previous steps.
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@@ -6,29 +6,29 @@ description: 'Get Ollama up and running in Wave AI'
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[Ollama](https://ollama.com/) is an open-source language model that offers a powerful and flexible alternative to proprietary LLMs, allowing you to run the model locally or on your own server infrastructure. Ollama provides high-quality language generation and understanding capabilities while giving you full control over your data and privacy.
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<Tip>
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To see a full list of supported LLMs, please visit the [Third-Party LLM Support](/features/waveAI#third-party-llm-support) section in the Wave AI features page.
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To see a full list of supported LLM providers, please visit the [Third-Party LLM Support](/features/waveAI#third-party-llm-support) section in the Wave AI features page.
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</Tip>
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## Installation
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Please visit Ollama's [GitHub](https://github.com/ollama/ollama?tab=readme-ov-file) page for instructions on downloading and installing Ollama, as well as a quickstart guide and a full list of supported models.
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## Configuration
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After installing and configuring Ollama, you can start using it in Wave by setting two parameters: `openaibaseurl` and `openaimodel`. These parameters can be set either through the UI or from the command line, but please note that the parameter names are slightly different depending on the method you choose.
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After installing and configuring Ollama, you can start using it in Wave by setting two parameters: `aibaseurl` and `aimodel`. These parameters can be set either through the UI or from the command line, but please note that the parameter names are slightly different depending on the method you choose.
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### **Parameters**
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- **Base URL:** Set this parameter to the base URL or endpoint that Wave AI should query. For Ollama running locally, use http://localhost:11434/v1. Please note that the port number `11434` may be different depending on your specific installation. For remote Ollama instances, replace `localhost` with the appropriate hostname or IP address of the server where Ollama is running. If the port number is different from the default `11434`, update it accordingly in the URL.
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- **AI Base URL:** Set this parameter to the base URL or endpoint that Wave AI should query. For Ollama running locally, use http://localhost:11434/v1. Please note that the port number `11434` may be different depending on your specific installation. For remote Ollama instances, replace `localhost` with the appropriate hostname or IP address of the server where Ollama is running. If the port number is different from the default `11434`, update it accordingly in the URL.
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- **AI Model**: Specify the Ollama model you want to use. This can be any "pulled" model in Ollama and doesn't need to be actively running. To discover available models, use the `ollama list` command in your terminal.
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### Configuring via the UI
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To configure Ollama from the Wave AI user interface, navigate to the "Settings" menu and set the `AI Base URL` and `AI Model` parameters as described in the previous section.
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### Configuring via the CLI
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To configure Ollama using the command line, set the `openaibaseurl` and `openaimodel` parameters using the [/client:set](/reference/slashcommands#client-set) command, as shown in the example below. Replace the values with the appropriate `Base URL` and `AI Model` for your Ollama installation.
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To configure Ollama using the command line, set the `aibaseurl` and `aimodel` parameters using the [/client:set](/reference/slashcommands#client-set) command, as shown in the example below.
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```
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/client:set openaibaseurl=<your-ollama-base-url>
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/client:set openaimodel=<your-ollama-model-name>
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/client:set aibaseurl=<your-ollama-base-url>
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/client:set aimodel=<your-ollama-model-name>
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```
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## Usage
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@@ -41,19 +41,19 @@ Once you have installed and configured Ollama, you can start using it in Wave. T
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If you encounter issues while using Ollama with Wave AI, consider the following troubleshooting steps:
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- **Connection failures:** If Wave AI fails to connect to Ollama or returns an error message, [verify that Ollama is running](https://github.com/ollama/ollama?tab=readme-ov-file#rest-api) and accessible from the system where Wave is installed. Check the Ollama logs for any error messages or indications of why the connection might be failing.
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- **Timeouts:** If you're unable to complete a query or incur frequent timeouts, try adjusting the [openaitimeout](/features/waveAI#customization) parameter to a higher value. This will give Ollama more time to process and respond to your requests, especially if you are running it on a system with limited hardware resources.
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- **Incorrect base URL or port:** Ensure that the [openaibaseurl](/features/waveAI#customization) parameter points to the correct URL and port number where Ollama is running. If you have changed the default port or are running Ollama on a remote server, update the URL accordingly.
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- **Incorrect model selection:** If you have multiple Ollama models installed, make sure to set the [openaimodel](/features/waveAI#customization) parameter to the specific model you want to use. You can list available models using the ollama list command in your terminal.
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- **Unexpected behavior or inconsistent results:** If you encounter unexpected behavior or inconsistent results when using Ollama with Wave AI, try [resetting](#reset-wave-ai) the openaibaseurl and openaimodel parameters to their default values and reconfiguring Ollama from scratch. This can help rule out any configuration issues that might be causing problems.
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- **Timeouts:** If you're unable to complete a query or incur frequent timeouts, try adjusting the [aitimeout](/features/waveAI#customization) parameter to a higher value. This will give Ollama more time to process and respond to your requests, especially if you are running it on a system with limited hardware resources.
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- **Incorrect base URL or port:** Ensure that the [aibaseurl](/features/waveAI#customization) parameter points to the correct URL and port number where Ollama is running. If you have changed the default port or are running Ollama on a remote server, update the URL accordingly.
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- **Incorrect model selection:** If you have multiple Ollama models installed, make sure to set the [aimodel](/features/waveAI#customization) parameter to the specific model you want to use. You can list available models using the ollama list command in your terminal.
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- **Unexpected behavior or inconsistent results:** If you encounter unexpected behavior or inconsistent results when using Ollama with Wave AI, try [resetting](#reset-wave-ai) the aibaseurl and aimodel parameters to their default values and reconfiguring Ollama from scratch. This can help rule out any configuration issues that might be causing problems.
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If you continue to face issues after trying these troubleshooting steps, please see the [Additional Resources](#additional-resources) section below for further assistance.
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## Reset Wave AI
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At any time if you find that you wish to return to the default Wave AI experience, you can reset the `openaibaseurl` and `openaimodel` parameters to their default state by using the following commands.
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At any time if you find that you wish to return to the default Wave AI experience, you can reset the `aibaseurl` and `aimodel` parameters to their default state by using the following commands.
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```
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/client:set openaibaseurl=
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/client:set openaimodel=
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/client:set aibaseurl=
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/client:set aimodel=
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```
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**Note:** This can also be done in the UI just as described in previous steps.
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