Merge branch 'main' of https://github.com/jacksparrow124/HM-GPT

.github/workflows/greetings.yml

@@ -0,0 +1,16 @@
+name: Greetings
+
+on: [pull_request_target, issues]
+
+jobs:
+  greeting:
+    runs-on: ubuntu-latest
+    permissions:
+      issues: write
+      pull-requests: write
+    steps:
+    - uses: actions/first-interaction@v1
+      with:
+        repo-token: ${{ secrets.GITHUB_TOKEN }}
+        issue-message: "Welcome to HM-GPT issues! Thank you for contributing to this community. 🙂"
+        pr-message: "Welcome to HM-GPT pull requests. Thanks for your interest in improving the community. 🙂"

.github/workflows/label.yml

@@ -0,0 +1,22 @@
+# This workflow will triage pull requests and apply a label based on the
+# paths that are modified in the pull request.
+#
+# To use this workflow, you will need to set up a .github/labeler.yml
+# file with configuration.  For more information, see:
+# https://github.com/actions/labeler
+
+name: Labeler
+on: [pull_request_target]
+
+jobs:
+  label:
+
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      pull-requests: write
+
+    steps:
+    - uses: actions/labeler@v4
+      with:
+        repo-token: "${{ secrets.Labler }}"

README.md

@@ -1,21 +1,16 @@
 <h1> Home Manager GPT</h1>
 <h3> Welcome! 😄</h3>
-<h2> overview </h2>
+<h2> overview </h2>  
 <ul> 
   <li href = "https://github.com/jacksparrow124/HM-GPT#requirements-for-part-1">Requirements</li>
   <li>how it works 🖥️ </li>
   <li>setup 🎈</li>
 <h2> Setup</h2>
   <p>
-    You need a paid OpenAI account with an API key to run this code. Attach a Raspberry Pi Pico to a microphone that will record the .mp3 file, then use this code and setup diagram to wire and code the Pico. you will also need a speaker to attach to the pico to return the output. for materials, see Requirements section. 🙂
+    You need a paid OpenAI account with an API key to run this code. Attach a Raspberry Pi Pico to a microphone that will record the .mp3 file, then use this code and setup diagram to wire and code the Pico. you will also need a speaker to attach to the pico to return the output. for materials, see Requirements section. 🙂 !STILL IN DEVELOPMENT!
   </p>
-<h2>Requirements for part 1</h2>
-  <ul>
-    <li>a paid openai account with api key</li>
-    <li>a microphone:  https://www.adafruit.com/product/1063</li>
-    <li>speaker: https://www.adafruit.com/product/1314</li>
-    <li>Raspberry Pi Pico: https://www.adafruit.com/product/5525</li>
-
+
+
 <h2>how it works</h2>
   <p>
   We are using basic ChatGPT 3.5 as a home manager that you can ask to turn on the radio, turn off the lights, and complete other easily automated tasks (fork the repository or create a pull request to add your own features). It uses a microphone to record commands in .mp3 file, then transcribes the .mp3 file to text and gives it to ChatGPT. Speech output is returned through OpenAI's Whisper.
@@ -28,8 +23,6 @@ The second, optional part of the project is to create a "magic mirror" to house
 
 
 
-<h2 align=left>Acessabitlity</h2>
-    <p> we are currently working on making spanish, chinese, and french versions of the interactive-ness. we would love for others to chip in and help with the effort. to acsess the other language's programs, go to main/main_(the language) and use that code. this will increase ability to customize dramatically. for the time being, we will have the other languages' in main. Once we get the user 1st time start up working, we will move these to a diffrent repo. thanks for understanding! 🙂</p>
 
 
 

main/TextToSpeech.py

@@ -43,9 +43,4 @@ def processText(self,myText):
             counter = 1
         os.remove(file_name)
 
-
-
-
-
-
-
+

main/main.py

@@ -3,16 +3,13 @@
 import openai
 import time
 
-
 import SpeechToText as st
 import TextToSpeech as ts
 
 
 load_dotenv()
 openai.api_key = os.getenv("OPENAI_API_KEY2")
 
-
-
 def chat(input): 
     completion = openai.ChatCompletion.create(
     model="gpt-3.5-turbo",
@@ -32,4 +29,3 @@ def chat(input):
     #content ="this is a test"
     print(content) #type: ignore
     textToSpeech.processText(content)
-