Create app.py

app.py

@@ -0,0 +1,59 @@
+import openai
+import gradio as gr
+import csv
+import os
+
+MODEL = "gpt-3.5-turbo"
+chat_history_file = "chat_history.csv"
+
+openai.api_key = os.environ.get("OPENAI_API_KEY")
+
+def generate_chat_response(input_text):
+    prompt = f"Conversation:\nUser: {input_text}\nAI:"
+    completion = openai.ChatCompletion.create(
+        model=MODEL,
+        max_tokens=3000,
+        n=1,
+        stop=None,
+        temperature=0.5,
+        messages=[{"role": "user", "content": "Hello!"}]
+    )
+    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": ""})
+
+    # use OpenAI ChatCompletion model to generate a response
+    # based on the user's input text
+    response_text = generate_chat_response(input_text)
+
+    # add response to chat history
+    chat_history[-1]["output"] = 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"]])
+
+    return response_text
+
+chatbot_interface = gr.Interface(
+    fn=chatbot_response,
+    inputs=["text", gr.inputs.Voice()],
+    outputs=["text", gr.outputs.Voice()],
+    title="Chatbot",
+    description="Talk to the chatbot using text and speech inputs."
+)
+
+chatbot_interface.launch()