refactor code to make bigger application

Author: Suraj1089

.github/workflows/lint.yml

@@ -21,4 +21,4 @@ jobs:
         pip install flake8
 
     - name: Run Flake8
-      run: flake8 --config backend/.flake8
+      run: flake8

backend/.flake8

@@ -1,5 +1,19 @@
 [flake8]
-exclude = versions
+exclude =
+    # No need to traverse our git directory
+    .git,
+    # There's no value in checking cache directories
+    __pycache__,
+    # The conf file is mostly autogenerated, ignore it
+    docs/source/conf.py,
+    # The old directory contains Flake8 2.0
+    old,
+    # This contains our built documentation
+    build,
+    # This contains builds of flake8 that we don't want to check
+    dist
+    # This contains packages we have installed
+    .venv
 ignore =
     # E121: continuation line under-indented for hanging indent.
     E121,

backend/app/__init__.py

@@ -0,0 +1,4 @@
+#!/bin/bash
+# Run flake8 excluding the venv directory
+echo "Running flake8..."
+flake8 --exclude=.venv

backend/app/dependencies.py

@@ -0,0 +1,80 @@
+import json
+import random
+
+# Save messages for retrieval later on
+
+
+def get_recent_messages():
+
+    # Define the file name
+    file_name = "stored_data.json"
+    learn_instruction = {"role": "system",
+                         "content": """You are a Spanish teacher and your name is Rachel,
+                         the user is called Shaun. Keep responses under 20 words."""}
+
+    # Initialize messages
+    messages = []
+
+    # Add Random Element
+    x = random.uniform(0, 1)
+    if x < 0.2:
+        learn_instruction["content"] = learn_instruction["content"] + \
+            "Your response will have some light humour. "
+    elif x < 0.5:
+        learn_instruction["content"] = learn_instruction["content"] + \
+            "Your response will include an interesting new fact about Spain. "
+    else:
+        learn_instruction["content"] = learn_instruction["content"] + \
+            "Your response will recommend another word to learn. "
+
+    # Append instruction to message
+    messages.append(learn_instruction)
+
+    # Get last messages
+    try:
+        with open(file_name) as user_file:
+            data = json.load(user_file)
+
+            # Append last 5 rows of data
+            if data:
+                if len(data) < 5:
+                    for item in data:
+                        messages.append(item)
+                else:
+                    for item in data[-5:]:
+                        messages.append(item)
+    except Exception as e:
+        return e
+
+    # Return messages
+    return messages
+
+
+# Save messages for retrieval later on
+def store_messages(request_message, response_message):
+
+    # Define the file name
+    file_name = "stored_data.json"
+
+    # Get recent messages
+    messages = get_recent_messages()[1:]
+
+    # Add messages to data
+    user_message = {"role": "user", "content": request_message}
+    assistant_message = {"role": "assistant", "content": response_message}
+    messages.append(user_message)
+    messages.append(assistant_message)
+
+    # Save the updated file
+    with open(file_name, "w") as f:
+        json.dump(messages, f)
+
+
+# Save messages for retrieval later on
+def reset_messages():
+
+    # Define the file name
+    file_name = "stored_data.json"
+
+    # Write an empty file
+    open(file_name, "w")

backend/app/internal/config.py

@@ -0,0 +1,41 @@
+import openai
+from decouple import config
+
+from backend.app.utils.database import get_recent_messages
+
+openai.organization = config("OPENAI_ORG")
+openai.api_key = config("OPENAI_API_KEY")
+
+
+# Open AI - Whisper
+# Convert audio to text
+def convert_audio_to_text(audio_file):
+    try:
+        transcript = openai.Audio.transcribe("whisper-1", audio_file)
+        message_text = transcript["text"]
+        return message_text
+    except Exception as e:
+        return e
+
+# Open AI - Chat GPT
+# Convert audio to text
+
+
+def get_chat_response(message_input):
+
+    messages = get_recent_messages()
+    user_message = {"role": "user", "content": message_input +
+                    """Only say two or 3 words in Spanish if speaking in Spanish.
+                      The remaining words should be in English"""}
+    messages.append(user_message)
+    print(messages)
+
+    try:
+        response = openai.ChatCompletion.create(
+            model="gpt-3.5-turbo",
+            messages=messages
+        )
+        message_text = response["choices"][0]["message"]["content"]
+        return message_text
+    except Exception as e:
+        return e

backend/app/scripts/lint_python.sh

@@ -0,0 +1,31 @@
+import requests
+from decouple import config
+
+ELEVEN_LABS_API_KEY = config("ELEVEN_LABS_API_KEY")
+
+
+def convert_text_to_speech(message):
+    body = {
+        "text": message,
+        "voice_settings": {
+            "stability": 0,
+            "similarity_boost": 0
+        }
+    }
+
+    voice_rachel = "21m00Tcm4TlvDq8ikWAM"
+
+    # Construct request headers and url
+    headers = {"xi-api-key": ELEVEN_LABS_API_KEY,
+               "Content-Type": "application/json", "accept": "audio/mpeg"}
+    endpoint = f"https://api.elevenlabs.io/v1/text-to-speech/{voice_rachel}"
+
+    try:
+        response = requests.post(endpoint, json=body, headers=headers)
+    except Exception as e:
+        return e
+
+    if response.status_code == 200:
+        return response.content
+    else:
+        return

backend/app/utils/database.py

@@ -1,10 +1,10 @@
-import openai
-from fastapi import Depends, FastAPI, File, HTTPException, UploadFile
+from fastapi import FastAPI, File, HTTPException, UploadFile
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import StreamingResponse
-from functions.database import reset_messages, store_messages
-from functions.openai_requests import convert_audio_to_text, get_chat_response
-from functions.text_to_speech import convert_text_to_speech
+
+from backend.app.utils.database import reset_messages, store_messages
+from backend.app.utils.openai_requests import convert_audio_to_text, get_chat_response
+from backend.app.utils.text_to_speech import convert_text_to_speech
 
 app = FastAPI()
 
@@ -29,6 +29,7 @@
 def hello():
     return {'data': 'hello'}
 
+
 @app.get('/set')
 def set():
     reset_messages()
@@ -60,6 +61,7 @@ async def post_audio(file: UploadFile = File(...)):
 
     if not audio_output:
         raise HTTPException(status_code=400, detail="Failed audio output")
+
     def iterfile():
         yield audio_output