added aitimeout option and troubleshooting section to third-party llms

2026-08-05 13:42:53 -07:00 · 2024-04-24 10:25:03 -06:00
parent 0abd182901
commit a970f28834
3 changed files with 27 additions and 3 deletions
@@ -41,6 +41,18 @@ Once you have installed and configured LocalAI, you can start using it in Wave.
 - **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 LocalAI model.
 - **/chat:** Alternatively, you can use the [/chat](/features/waveAI#chat-command) command followed by your question to get a quick answer from your LocalAI model directly in the terminal.

+## Troubleshooting
+If you encounter issues while using LocalAI with Wave AI, consider the following troubleshooting steps:
+
+- **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.
+- **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.
+- **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.
+- **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.
+- **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.
+
+If you continue to face issues after trying these troubleshooting steps, please see the [Additional Resources](#additional-resources) section below for further assistance.
+
+
 ## Reset Wave AI
 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.

@@ -37,6 +37,17 @@ Once you have installed and configured Ollama, you can start using it in Wave. T
 - **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 Ollama model.
 - **/chat:** Alternatively, you can use the [/chat](/features/waveAI#chat-command) command followed by your question to get a quick answer from your Ollama model directly in the terminal.

+## Troubleshooting
+If you encounter issues while using Ollama with Wave AI, consider the following troubleshooting steps:
+
+- **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.
+- **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.
+- **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.
+- **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.
+- **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.
+
+If you continue to face issues after trying these troubleshooting steps, please see the [Additional Resources](#additional-resources) section below for further assistance.
+
 ## Reset Wave AI
 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.

@@ -35,10 +35,11 @@ This method is ideal for one-off queries or when you need a straightforward answ
 Wave AI comes with default settings that work out of the box. By default, Wave will proxy your requests through our cloud servers to OpenAI. However, you can customize your experience by modifying the following settings in the UI or by using the [/client:set](/reference/slashcommands#client-set) command:

 - `openaiapitoken:` Set your own OpenAI API key if you prefer not to use Wave's default configuration. Note that your API token will never be sent to Wave's cloud servers. When you provide your own API key, all future requests will be sent directly to OpenAI or any other endpoint you specify using `openaibaseurl`.
- `openaimaxtokens:` This setting allows you to control the maximum number of tokens (words or word pieces) that the AI model will generate in a single response.
- `openaimaxchoices:` This option determines the number of different response variations the AI model will generate for each query. Increasing this value will provide more diverse responses, while decreasing it will make the model's output more focused and consistent.
- `openaimodel:` Wave AI uses the ChatGPT *gpt-3.5-turbo* model by default, but you can choose a different model that suits your needs. You will need to also set `openaiapitoken` if you choose to use another ChatGPT model. Also, when configuring other third-party services you will want to change this setting to the appropriate model.
 - `openaibaseurl:` If you want to use other 3rd party APIs compatible with the OpenAI API, you can change the base URL. You will also want to set your `openaiapitoken` in conjunction with the base url to use a different service.
+- `openaimaxchoices:` This option determines the number of different response variations the AI model will generate for each query. Increasing this value will provide more diverse responses, while decreasing it will make the model's output more focused and consistent.
+- `openaimaxtokens:` This setting allows you to control the maximum number of tokens (words or word pieces) that the AI model will generate in a single response.
+- `openaimodel:` Wave AI uses the ChatGPT *gpt-3.5-turbo* model by default, but you can choose a different model that suits your needs. You will need to also set `openaiapitoken` if you choose to use another ChatGPT model. Also, when configuring other third-party services you will want to change this setting to the appropriate model.
+- `openaitimeout:` Specify the maximum time (in milliseconds) to wait for a response from the AI service before timing out. The default value is 10000 (10 seconds). This setting is particularly useful when configuring and troubleshooting local LLMs, as response times can vary significantly depending on the hardware constraints of the system running the model.

 **Note:** In order to prevent abuse, [telemetry](/reference/telemetry) must be enabled to use the cloud servers. There is currently a rate limit of 200 requests per day.