--- a
+++ b/openai_wrapper.py
@@ -0,0 +1,141 @@
+import io
+import os
+import json
+import pyaudio
+import configparser
+from pydub import AudioSegment
+from openai import OpenAI
+
+from audio import  CHANNELS, RATE
+from prompt import get_prompt, SYSTEM_Commentary, SYSTEM_Debates
+
+from local_llm import local_llm_call
+
+# Function to read API key from a file
+def read_api_key(file_path = r'./api_key.txt'):
+    if os.path.exists(file_path):
+        with open(file_path, 'r') as file:
+            return file.read().strip()
+    else:
+        return None
+
+pyaudio.PyAudio()
+
+# Initialize API Client
+api_key = read_api_key()
+if api_key:
+    client = OpenAI(api_key = read_api_key())  
+else:
+    client = None
+
+HISTORY = []
+HISTORY.append({"role": "system", 
+                 "content":[{
+                     "type": "text", 
+                     "text":SYSTEM_Debates
+                     }],
+                })
+
+def save_to_json_file(transcript, instruction, response, file_name=r'Data/data.json'):
+    # Prepare new data entry
+    
+    new_data = {
+        "transcript":transcript,
+        "prompt": instruction,
+        "response": response
+    }
+    # Read existing data
+    try:
+        with open(file_name, "r") as json_file:
+            all_data = json.load(json_file)
+    except FileNotFoundError:
+        all_data = []
+    
+    # Append new data
+    all_data.append(new_data)
+
+    # Write updated data back to file
+    with open(file_name, "w") as json_file:
+        json.dump(all_data, json_file)
+
+
+def text_fallacy_classification(formatted_base64_image, transcript):
+    # Create a more nuanced prompt for the LLM
+    prompt = get_prompt(transcript)
+    # Call the local LLM if client is None
+    if client is None:
+        print(f'Prompting local LLM...')
+        llm_response = local_llm_call(prompt)
+        return llm_response
+
+
+    # Initialize ConfigParser
+    config = configparser.ConfigParser()
+
+    # Read settings.ini file
+    config.read('settings.ini')
+    # Get values
+    gpt_model = config.get('ChatGPT API Settings', 'gpt_model')
+
+
+    # Call ChatGPT API for fallacy detection or other tasks
+    print(f'Prompting openAI...')
+    try:
+        HISTORY.append({"role": "user", "content": [{"type": "text", "text": prompt}]})
+        response = client.chat.completions.create(
+            model=gpt_model,
+            messages=HISTORY,
+            max_tokens=150
+        )
+        llm_response = response.choices[0].message.content.strip()  # Extract and clean the output text
+        HISTORY.append({"role": "assistant", "content": [{"type": "text", "text": llm_response}]})
+        print(llm_response)
+
+
+    except Exception as e:
+        print(e)
+        llm_response = "No reponse"
+    return llm_response
+
+
+def openAI_TTS(text, filename='audio/tts_audio.wav'):
+    response = client.audio.speech.create(
+                    model="tts-1",
+                    voice="onyx",
+                    input=text,
+                )
+    response.stream_to_file(filename)
+    return filename
+
+def openAI_STT(audio_bytearray):
+
+    # Convert the bytearray to an AudioSegment
+    audio = AudioSegment.from_raw(io.BytesIO(audio_bytearray), format="raw", frame_rate=RATE, channels=CHANNELS, sample_width=2)
+
+    # Convert the audio to a supported format (e.g., mp3)
+    buffer = io.BytesIO()
+    audio.export(buffer, format="mp3")
+    buffer.seek(0)
+
+    # Debug: Save the buffer to a file to check the conversion
+    with open("audio/sst_audio.mp3", "wb") as f:
+        f.write(buffer.getvalue())
+
+    audio_file= open("audio/sst_audio.mp3", "rb")
+    transcription_object = client.audio.transcriptions.create(
+                                model="whisper-1", 
+                                file=audio_file
+                                )
+
+     # Access the transcription text
+    try:
+        text = transcription_object.text
+    except AttributeError:
+        # Handle the case where 'text' attribute does not exist
+        # This might involve logging an error or returning a default value
+        text = ""
+
+    return text
+
+if __name__=="__main__":
+    save_to_json_file("transcript", "prompt", "response",  "few_shot_examples")
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