Update worker.py

worker.py

@@ -4,13 +4,72 @@ import requests
 openai_client = OpenAI()
 
 
+
 def speech_to_text(audio_binary):
-    return None
+
+    # Set up Watson Speech-to-Text HTTP Api url
+    base_url = 'https://sn-watson-stt.labs.skills.network'
+    api_url = base_url+'/speech-to-text/api/v1/recognize'
+
+    # Set up parameters for our HTTP reqeust
+    params = {
+        'model': 'en-US_Multimedia',
+    }
+
+    # Set up the body of our HTTP request
+    body = audio_binary
+
+    # Send a HTTP Post request
+    response = requests.post(api_url, params=params, data=audio_binary).json()
+
+    # Parse the response to get our transcribed text
+    text = 'null'
+    while bool(response.get('results')):
+        print('speech to text response:', response)
+        text = response.get('results').pop().get('alternatives').pop().get('transcript')
+        print('recognised text: ', text)
+        return text
 
 
 def text_to_speech(text, voice=""):
-    return None
+    # Set up Watson Text-to-Speech HTTP Api url
+    base_url = 'https://sn-watson-tts.labs.skills.network'
+    api_url = base_url + '/text-to-speech/api/v1/synthesize?output=output_text.wav'
+
+    # Adding voice parameter in api_url if the user has selected a preferred voice
+    if voice != "" and voice != "default":
+        api_url += "&voice=" + voice
+
+    # Set the headers for our HTTP request
+    headers = {
+        'Accept': 'audio/wav',
+        'Content-Type': 'application/json',
+    }
+
+    # Set the body of our HTTP request
+    json_data = {
+        'text': text,
+    }
+
+    # Send a HTTP Post request to Watson Text-to-Speech Service
+    response = requests.post(api_url, headers=headers, json=json_data)
+    print('text to speech response:', response)
+    return response.content
 
 
 def openai_process_message(user_message):
-    return None
+    # Set the prompt for OpenAI Api
+    prompt = "Act like a personal assistant. You can respond to questions, translate sentences, summarize news, and give recommendations."
+    # Call the OpenAI Api to process our prompt
+    openai_response = openai_client.chat.completions.create(
+        model="gpt-3.5-turbo", 
+        messages=[
+            {"role": "system", "content": prompt},
+            {"role": "user", "content": user_message}
+        ],
+        max_tokens=4000
+    )
+    print("openai response:", openai_response)
+    # Parse the response to get the response message for our prompt
+    response_text = openai_response.choices[0].message.content
+    return response_text