Update app.py

app.py

@@ -1,59 +1,67 @@
 import openai
 import gradio as gr
-import csv
+from gtts import gTTS
+from io import BytesIO
+from IPython.display import Audio, display
 import os
 
+# Set OpenAI API key
+openai.api_key = os.environ.get("OPENAI_API_KEY")
+
+# Set OpenAI GPT-3 model
 MODEL = "gpt-3.5-turbo"
-chat_history_file = "chat_history.csv"
 
-openai.api_key = os.environ.get("OPENAI_API_KEY")
+# Load chat history from file
+with open("chat_history.txt", "r") as f:
+    chat_history = f.read().strip()
+
+# Define chatbot response function
+def chatbot_response(text_input, voice_input):
+    # Concatenate text and voice input
+    input_text = text_input + " " + voice_input
 
-def generate_chat_response(input_text):
-    prompt = f"Conversation:\nUser: {input_text}\nAI:"
-    completion = openai.ChatCompletion.create(
+    # Concatenate input text with chat history
+    input_text_with_history = input_text + "\n\n" + chat_history
+
+    # Use OpenAI API to generate response
+    response = openai.Completion.create(
         model=MODEL,
+        prompt=input_text_with_history,
         max_tokens=3000,
         n=1,
         stop=None,
-        temperature=0.5,
-        messages=[{"role": "user", "content": "Hello!"}]
+        temperature=0.5
     )
-    response = (completion.choices[0].message)
-    return render_template("talkgpt.html", response=response)
-
-
-def chatbot_response(input_text):
-    # load chat history from file
-    chat_history = []
-    with open(chat_history_file, "r") as f:
-        reader = csv.reader(f)
-        for row in reader:
-            chat_history.append({"input": row[0], "output": row[1]})
 
-    # add current input to chat history
-    chat_history.append({"input": input_text, "output": ""})
+    # Extract response text from OpenAI API output
+    response_text = response.choices[0].text.strip()
 
-    # use OpenAI ChatCompletion model to generate a response
-    # based on the user's input text
-    response_text = generate_chat_response(input_text)
+    # Convert response text to speech
+    tts = gTTS(text=response_text)
+    audio_bytes = BytesIO()
+    tts.write_to_fp(audio_bytes)
+    audio_bytes.seek(0)
+    response_audio = Audio(audio_bytes, autoplay=True)
 
-    # add response to chat history
-    chat_history[-1]["output"] = response_text
+    # Update chat history with input and response text
+    global chat_history
+    chat_history += f"\n\nUser: {text_input}\nChatbot: {response_text}"
 
-    # save chat history to file
-    with open(chat_history_file, "w") as f:
-        writer = csv.writer(f)
-        for row in chat_history:
-            writer.writerow([row["input"], row["output"]])
+    # Save chat history to file
+    with open("chat_history.txt", "w") as f:
+        f.write(chat_history)
 
-    return response_text
+    # Return response text and audio for display in interface
+    return response_text, response_audio
 
+# Define chatbot interface
 chatbot_interface = gr.Interface(
     fn=chatbot_response,
-    inputs=["text", gr.inputs.Voice()],
-    outputs=["text", gr.outputs.Voice()],
+    inputs=["text", gr.inputs.Microphone(type="live", duration=10)],
+    outputs=["text", "audio"],
     title="Chatbot",
     description="Talk to the chatbot using text and speech inputs."
 )
 
+# Launch chatbot interface
 chatbot_interface.launch()