Merge pull request #512 from drk1rd/main

Grammar and punctuations improved

docs/pages/Deploying/Hosting-the-app.md

@@ -18,7 +18,7 @@ After that, it is time to pick your Instance Image. We recommend using "Linux/Un
 
 As for instance plan, it'll vary depending on your unique demands, but a "1 GB, 1vCPU, 40GB SSD and 2TB transfer" setup should cover most scenarios.
 
-Lastly, Identify your instance by giving it a unique name and then hit "Create instance".
+Lastly, identify your instance by giving it a unique name and then hit "Create instance".
 
 PS: Once you create your instance, it'll likely take a few minutes for the setup to be completed.
 
@@ -42,7 +42,7 @@ A terminal window will pop up, and the first step will be to clone the DocsGPT g
 
 #### Download the package information
 
-Once it has finished cloning the repository, it is time to download the package information from all sources. To do so simply enter the following command:
+Once it has finished cloning the repository, it is time to download the package information from all sources. To do so, simply enter the following command:
 
 `sudo apt update`
 
@@ -64,7 +64,7 @@ Enter the following command to access the folder in which DocsGPT docker-compose
 
 #### Prepare the environment
 
-Inside the DocsGPT folder create a `.env` file and copy the contents of `.env_sample` into it.
+Inside the DocsGPT folder, create a `.env` file and copy the contents of `.env_sample` into it.
 
 `nano .env`
 
@@ -95,7 +95,7 @@ You're almost there! Now that all the necessary bits and pieces have been instal
 
 Launching it for the first time will take a few minutes to download all the necessary dependencies and build.
 
-Once this is done you can go ahead and close the terminal window.
+Once this is done, you can go ahead and close the terminal window.
 
 #### Enabling ports 
 

docs/pages/Deploying/Quickstart.md

@@ -1,7 +1,7 @@
 ## Launching Web App
 Note: Make sure you have Docker installed
 
-On Mac OS or Linux just write:
+On macOS or Linux, just write:
 
 `./setup.sh`
 
@@ -10,11 +10,11 @@ It will install all the dependencies and give you an option to download the loca
 Otherwise, refer to this Guide:
 
 1. Open and download this repository with `git clone https://github.com/arc53/DocsGPT.git`.
-2. Create a `.env` file in your root directory and set your `API_KEY` with your [OpenAI api key](https://platform.openai.com/account/api-keys).
+2. Create a `.env` file in your root directory and set your `API_KEY` with your [OpenAI API key](https://platform.openai.com/account/api-keys).
 3. Run `docker-compose build && docker-compose up`.
 4. Navigate to `http://localhost:5173/`.
 
-To stop just run `Ctrl + C`.
+To stop, just run `Ctrl + C`.
 
 ### Chrome Extension
 

docs/pages/Developing/API-docs.md

@@ -18,7 +18,7 @@ fetch("http://127.0.0.1:5000/api/answer", {
 .then(console.log.bind(console))
 ```
 
-In response you will get a json document like this one:
+In response, you will get a JSON document like this one:
 
 ```json
 {
@@ -30,7 +30,7 @@ In response you will get a json document like this one:
 
 ### /api/docs_check
 It will make sure documentation is loaded on a server (just run it every time user is switching between libraries (documentations)).
-It's a POST request that sends a JSON in body with 1 value. Here is a JavaScript fetch example:
+It's a POST request that sends a JSON in a body with 1 value. Here is a JavaScript fetch example:
 
 ```js
 // answer (POST http://127.0.0.1:5000/api/docs_check)
@@ -45,7 +45,7 @@ fetch("http://127.0.0.1:5000/api/docs_check", {
 .then(console.log.bind(console))
 ```
 
-In response you will get a json document like this one:
+In response, you will get a JSON document like this one:
 ```json
 {
   "status": "exists"
@@ -54,17 +54,17 @@ In response you will get a json document like this one:
 
 
 ### /api/combine
-Provides json that tells UI which vectors are available and where they are located with a simple get request.
+Provides JSON that tells UI which vectors are available and where they are located with a simple get request.
 
 Response will include:
 `date`, `description`, `docLink`, `fullName`, `language`, `location` (local or docshub), `model`, `name`, `version`.
 
-Example of json in Docshub and local:
+Example of JSON in Docshub and local:
 <img width="295" alt="image" src="https://user-images.githubusercontent.com/15183589/224714085-f09f51a4-7a9a-4efb-bd39-798029bb4273.png">
 
 
 ### /api/upload
-Uploads file that needs to be trained, response is json with task id, which can be used to check on tasks progress
+Uploads file that needs to be trained, response is JSON with task ID, which can be used to check on task's progress
 HTML example:
 
 ```html
@@ -104,7 +104,7 @@ fetch("http://localhost:5001/api/task_status?task_id=b2d2a0f4-387c-44fd-a443-e4f
 
 Responses:
 There are two types of responses:
-1. while task it still running, where "current" will show progress from 0 to 100
+1. While task is still running, where "current" will show progress from 0 to 100
 ```json
 {
   "result": {

docs/pages/Extensions/Chatwoot-extension.md

@@ -13,7 +13,7 @@ chatwoot_token=<from part 2>
 
 5. Start with `flask run` command.
 
-If you want for bot to stop responding to questions for a specific user or session just add label `human-requested` in your conversation.
+If you want for bot to stop responding to questions for a specific user or session, just add a label `human-requested` in your conversation.
 
 
 ### Optional (extra validation)
@@ -26,4 +26,4 @@ account_id=(optional) 1
 assignee_id=(optional) 1
 ```
 
-Those are chatwoot values and will allow you to check if you are responding to correct widget and responding to questions assigned to specific user.
+Those are chatwoot values and will allow you to check if you are responding to correct widget and responding to questions assigned to specific user.

docs/pages/Extensions/react-widget.md

@@ -4,7 +4,7 @@
 Got to your project and install a new dependency: `npm install docsgpt`.
 
 ### Usage
-Go to your project and in the file where you want to use the widget import it: 
+Go to your project and in the file where you want to use the widget, import it: 
 ```js
 import { DocsGPTWidget } from "docsgpt";
 import "docsgpt/dist/style.css";
@@ -14,12 +14,12 @@ import "docsgpt/dist/style.css";
 Then you can use it like this: `<DocsGPTWidget />`
 
 DocsGPTWidget takes 3 props:
-- `apiHost` — url of your DocsGPT API.
-- `selectDocs` — documentation that you want to use for your widget (eg. `default` or `local/docs1.zip`).
-- `apiKey` — usually its empty.
+- `apiHost` — URL of your DocsGPT API.
+- `selectDocs` — documentation that you want to use for your widget (e.g. `default` or `local/docs1.zip`).
+- `apiKey` — usually it's empty.
 
 ### How to use DocsGPTWidget with [Nextra](https://nextra.site/) (Next.js + MDX)
-Install you widget as described above and then go to your `pages/` folder and create a new file `_app.js` with the following content:
+Install your widget as described above and then go to your `pages/` folder and create a new file `_app.js` with the following content:
 ```js
 import { DocsGPTWidget } from "docsgpt";
 import "docsgpt/dist/style.css";

docs/pages/Guides/Customising-prompts.md

@@ -1,4 +1,4 @@
-## To customize a main prompt navigate to `/application/prompt/combine_prompt.txt`
+## To customize a main prompt, navigate to `/application/prompt/combine_prompt.txt`
 
 You can try editing it to see how the model responses.
 

docs/pages/Guides/How-to-train-on-other-documentation.md

@@ -5,18 +5,18 @@ This AI can use any documentation, but first it needs to be prepared for similar
 
 Start by going to `/scripts/` folder.
 
-If you open this file you will see that it uses RST files from the folder to create a `index.faiss` and `index.pkl`. 
+If you open this file, you will see that it uses RST files from the folder to create a `index.faiss` and `index.pkl`. 
 
-It currently uses OPEN_AI to create vector store, so make sure your documentation is not too big. Pandas cost me around 3-4$.
+It currently uses OPEN_AI to create the vector store, so make sure your documentation is not too big. Pandas cost me around $3-$4.
 
-You can usually find documentation on github in `docs/` folder for most open-source projects.
+You can usually find documentation on Github in `docs/` folder for most open-source projects.
 
 ### 1. Find documentation in .rst/.md and create a folder with it in your scripts directory
 - Name it `inputs/`  
 - Put all your .rst/.md files in there  
 - The search is recursive, so you don't need to flatten them
 
-If there are no .rst/.md files just convert whatever you find to txt and feed it. (don't forget to change the extension in script)
+If there are no .rst/.md files just convert whatever you find to .txt and feed it. (don't forget to change the extension in script)
 
 ### 2. Create .env file in `scripts/` folder
 And write your OpenAI API key inside
@@ -32,7 +32,7 @@ It will tell you how much it will cost
 
 
 ### 5. Run web app
-Once you run it will use new context that is relevant to your documentation
+Once you run it will use new context that is relevant to your documentation  
 Make sure you select default in the dropdown in the UI
 
 ## Customization 
@@ -41,7 +41,7 @@ You can learn more about options while running ingest.py by running:
 `python ingest.py --help`
 |              Options             |                                                                                                                                |
 |:--------------------------------:|:------------------------------------------------------------------------------------------------------------------------------:|
-|            **ingest**            | Runs 'ingest' function converting documentation to Faiss plus Index format                                                  |
+|            **ingest**            | Runs 'ingest' function, converting documentation to Faiss plus Index format                                                  |
 | --dir TEXT                       | List of paths to directory for index creation. E.g. --dir inputs --dir inputs2 [default: inputs]                               |
 | --file TEXT                      | File paths to use (Optional; overrides directory) E.g. --files inputs/1.md --files inputs/2.md                                 |
 | --recursive / --no-recursive     | Whether to recursively search in subdirectories [default: recursive]                                                           |

docs/pages/Guides/How-to-use-different-LLM.md

@@ -1,4 +1,4 @@
-Fortunately there are many providers for LLM's and some of them can even be ran locally
+Fortunately, there are many providers for LLM's and some of them can even be run locally
 
 There are two models used in the app:
 1. Embeddings.
@@ -29,4 +29,4 @@ That's it!
 ### Hosting everything locally and privately (for using our optimised open-source models)
 If you are working with important data and don't want anything to leave your premises.
 
-Make sure you set `SELF_HOSTED_MODEL` as true in you `.env` variable and for your `LLM_NAME` you can use anything that's on Hugging Face.
+Make sure you set `SELF_HOSTED_MODEL` as true in your `.env` variable and for your `LLM_NAME` you can use anything that's on Hugging Face.

docs/pages/Guides/My-AI-answers-questions-using-external-knowledge.md

@@ -1,4 +1,4 @@
-If your AI uses external knowledge and is not explicit enough it is ok, because we try to make docsgpt friendly.
+If your AI uses external knowledge and is not explicit enough, it is ok, because we try to make docsgpt friendly.
 
 But if you want to adjust it, here is a simple way.