chatbot running

utils/chatbot.py

@@ -1,53 +1,55 @@
-from openai import OpenAI
+from  openai import OpenAI
 import gradio as gr
 import os
 
-client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])  # Set your API key securely
-
-
-class SpecializedDoctor:
-    def __init__(self, specialty):
-        self.specialty = specialty
-        self.load_prompts()
-
-    def load_prompts(self):
-        try:
-            with open(f"utils/prompts.txt", "r") as f:
-                self.prompts = f.read().splitlines()
-        except FileNotFoundError:
-            print(f"Error: Prompts file for '{self.specialty}' not found.")
-            self.prompts = []
-
-    def provide_medical_advice(self, patient_query):
-        prompt = f"{self.specialty}: {patient_query}\n{self.prompts[0]}"
-        response = client.chat.completions.create(
-            model="gpt-3.5-turbo",
-            messages=[{"role": "user", "content": prompt}],
-            temperature=0.7,
-            max_tokens=150,
-            top_p=1,
-            frequency_penalty=0,
-            presence_penalty=0.4,
-        )
-        return response.choices[0].message.content.strip()
-
-
-def chat_response(message, history):
-    # Assuming you have only one doctor instance:
-    doctor = SpecializedDoctor("Cardiology")  # Change here if you have more
-    doctor_response = doctor.provide_medical_advice(message)
-
-    # Update history and return
-    history = [{"role": "user", "content": ""}]  # Start with an empty user message
-    if isinstance(history, dict):
-        history = [history]
-    history.append({"role": "user", "content": message})
-    history.append({"role": "assistant", "content": doctor_response})
-    return [{"role": "assistant", "content": doctor_response}], history
-
+client = OpenAI(
+    # This is the default and can be omitted
+    api_key=os.environ.get("OPENAI_API_KEY"),
+)
+
+def chat_response(prompt, history=[]):
+    """
+    Provides a chatbot response based on the given prompt and history.
+
+    Args:
+        prompt (str): The user's input prompt.
+        history (list, optional): List of previous interactions (user and assistant messages). Defaults to [].
+
+    Returns:
+        str: The assistant's response.
+    """
+
+    # Update history with the user's prompt
+    history.append({"role": "user", "content": prompt})
+
+    # Generate response using OpenAI's chat completion API
+    response = client.chat.completions.create(
+        model="gpt-3.5-turbo",
+        messages=[{"role": "user", "content": prompt}],
+        max_tokens=150,
+        temperature=0.7,
+        top_p=1,
+        frequency_penalty=0,
+        presence_penalty=0.6,
+        stop=None,
+        n=1
+    )
+    assistant_response = response.choices[0].message.content
+
+    # Update history with the assistant's response
+    history.append({"role": "assistant", "content": assistant_response})
+
+    return assistant_response, history
 
 # Create the Gradio interface
-iface = gr.ChatInterface(chat_response, title="Cardiologist Assistant")
+interface = gr.Interface(
+    fn=chat_response,
+    inputs=gr.Textbox(lines=3, label="Enter your prompt:"),
+    outputs="text",
+    title="OpenAI Chatbot: Ask Me Anything!",
+    #theme="dark",
+    #use_legacy_return=True,  # Ensure all outputs are returned to Gradio
+)
 
 # Launch the interface
-iface.launch()
+interface.launch()