Merge pull request #167 from janhq/docs-update-0.1.14

Docs update hotfix

docs/docs/features/embed.md

@@ -89,4 +89,4 @@ The example response used the output from model [llama2 Chat 7B Q5 (GGUF)](https
 
 </div>
 
-The embedding feature in Nitro demonstrates a high level of compatibility with OpenAI, simplifying the transition between using OpenAI and local AI models. For more detailed information and advanced use cases, refer to the comprehensive [API Reference](https://nitro.jan.ai/api-reference)).
+The embedding feature in Nitro demonstrates a high level of compatibility with OpenAI, simplifying the transition between using OpenAI and local AI models. For more detailed information and advanced use cases, refer to the comprehensive [API Reference](https://nitro.jan.ai/api-reference).

docs/docs/features/prompt.md

@@ -22,7 +22,7 @@ Nitro enables developers to configure dialogs and implement advanced prompt engi
 
 To illustrate, let's create a "Pirate assistant":
 
-> NOTE: "ai_prompt" and "user_prompt" are prefixes indicating the role. Configure them based on your model.
+> NOTE: "ai_prompt", "user_prompt" and "system_prompt" are prefixes indicating the role. Configure them based on your model.
 
 ### Prompt Configuration
 
@@ -33,6 +33,7 @@ curl http://localhost:3928/inferences/llamacpp/loadmodel \
     "ctx_len": 128,
     "ngl": 100,
     "pre_prompt": "You are a Pirate. Using drunk language with a lot of Arr...",
+    "system_prompt": "ASSISTANT'S RULE: ",
     "user_prompt": "USER:",
     "ai_prompt": "ASSISTANT: "
   }'

docs/docs/new/about.md

@@ -119,3 +119,7 @@ Nitro welcomes contributions in various forms, not just coding. Here are some wa
 
 - [drogon](https://github.com/drogonframework/drogon): The fast C++ web framework
 - [llama.cpp](https://github.com/ggerganov/llama.cpp): Inference of LLaMA model in pure C/C++
+
+## FAQ
+:::info COMING SOON
+:::

docs/docs/new/architecture.md

@@ -4,8 +4,6 @@ title: Architecture
 
 ![Nitro Architecture](img/architecture.drawio.png)
 
-### Details element example
-
 ## Key Concepts
 
 ## Inference Server

docs/docs/new/quickstart.md

@@ -7,18 +7,16 @@ title: Quickstart
 ### For Linux and MacOS
 
 Open your terminal and enter the following command. This will download and install Nitro on your system.
-
-```bash
-curl -sfL https://raw.githubusercontent.com/janhq/nitro/main/install.sh -o /tmp/install.sh && chmod +x /tmp/install.sh && sudo bash /tmp/install.sh --gpu && rm /tmp/install.sh
-```
+  ```bash
+  curl -sfL https://raw.githubusercontent.com/janhq/nitro/main/install.sh | sudo /bin/bash -
+  ```
 
 ### For Windows
 
 Open PowerShell and execute the following command. This will perform the same actions as for Linux and MacOS but is tailored for Windows.
-
-```bash
-powershell -Command "& { Invoke-WebRequest -Uri 'https://raw.githubusercontent.com/janhq/nitro/main/install.bat' -OutFile 'install.bat'; .\install.bat --gpu; Remove-Item -Path 'install.bat' }"
-```
+  ```bash
+  powershell -Command "& { Invoke-WebRequest -Uri 'https://raw.githubusercontent.com/janhq/nitro/main/install.bat' -OutFile 'install.bat'; .\install.bat; Remove-Item -Path 'install.bat' }"
+  ```
 
 > **NOTE:**Installing Nitro will add new files and configurations to your system to enable it to run.
 

docs/openapi/NitroAPI.yaml

@@ -167,7 +167,7 @@ paths:
       operationId: createChatCompletion
       tags:
         - Chat Completion
-      summary: Create an chat with the model.
+      summary: Create a chat with the model.
       requestBody:
         content:
           application/json:
@@ -544,23 +544,23 @@ components:
         stream:
           type: boolean
           default: true
-          description: Enables continuous output generation, allowing for streaming of model responses.
+          description: Enables continuous output generation, allowing for streaming of model responses
         model:
           type: string
           example: "gpt-3.5-turbo"
-          description: Specifies the model being used for inference or processing tasks.
+          description: Specifies the model being used for inference or processing tasks
         max_tokens:
           type: number
           default: 2048
           description: The maximum number of tokens the model will generate in a single response
         stop:
           type: arrays
           example: ["hello"]
-          description: Defines specific tokens or phrases at which the model will stop generating further output.
+          description: Defines specific tokens or phrases at which the model will stop generating further output
         frequency_penalty:
           type: number
           default: 0
-          description: Adjusts the likelihood of the model repeating words or phrases in its output.
+          description: Adjusts the likelihood of the model repeating words or phrases in its output
         presence_penalty:
           type: number
           default: 0
@@ -571,6 +571,12 @@ components:
           min: 0
           max: 1
           description: Controls the randomness of the model's output
+        top_p:
+          type: number
+          default: 0.95
+          min: 0
+          max: 1
+          description: Set probability threshold for more relevant outputs
 
     ChatCompletionResponse:
       type: object

docs/openapi/OpenAIAPI.yaml

@@ -9869,3 +9869,4 @@ x-oaiMeta:
         - type: endpoint
           key: createEdit
           path: create
+