Update app.py

app.py

@@ -1,33 +1,49 @@
 import streamlit as st
 import requests
 import json
-from huggingface_hub import HfApi
-import huggingface_hub
-import os
 
-# Constants for Zephyr-7b-Beta model
-zephyr_7b_beta = "https://api-inference.huggingface.co/models/HuggingFaceH4/zephyr-7b-beta/"
-HF_TOKEN = os.getenv("HF_TOKEN")
+HF_TOKEN = "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"  # Replace with your actual Hugging Face token
 HEADERS = {"Authorization": f"Bearer {HF_TOKEN}"}
 
-# Function to build input prompt for the model
+zephyr_7b_beta = "https://api-inference.huggingface.co/models/HuggingFaceH4/zephyr-7b-beta/"
+
+welcome_message = """
+Hi! I'll help you **build a GPT**. You can say something like, "make a bot that gives advice on how to grow your startup."
+What would you like to make?
+"""
+
+zephyr_system_prompt = """
+You are an AI whose job it is to help users create their own chatbots. In particular, you need to respond succinctly in a friendly tone, write a system prompt for an LLM, a catchy title for the chatbot, and a very short example user input. Make sure each part is included.
+For example, if a user says, "make a bot that gives advice on how to grow your startup", first do a friendly response, then add the title, system prompt, and example user input. Immediately STOP after the example input. It should be EXACTLY in this format:
+Sure, I'd be happy to help you build a bot! I'm generating a title, system prompt, and an example input. How do they sound? Feel free to give me feedback!
+Title: Startup Coach
+System prompt: Your job as an LLM is to provide good startup advice. Do not provide extraneous comments on other topics. Be succinct but useful. 
+Example input: Risks of setting up a non-profit board
+Here's another example. If a user types, "Make a chatbot that roasts tech CEOs", respond: 
+Sure, I'd be happy to help you build a bot! I'm generating a title, system prompt, and an example input. How do they sound? Feel free to give me feedback!
+Title: Tech Roaster
+System prompt: As an LLM, your primary function is to deliver hilarious and biting critiques of technology CEOs. Keep it witty and entertaining, but also make sure your jokes aren't too mean-spirited or factually incorrect. 
+Example input: Elon Musk
+"""
+
 def build_input_prompt(message, chatbot, system_prompt):
     input_prompt = "\n" + system_prompt + "</s>\n\n"
     for interaction in chatbot:
         input_prompt = input_prompt + str(interaction[0]) + "</s>\n\n" + str(interaction[1]) + "\n</s>\n\n"
+
     input_prompt = input_prompt + str(message) + "</s>\n"
     return input_prompt
 
-# Function to send a POST request to Zephyr-7b-Beta model
 def post_request_beta(payload):
     response = requests.post(zephyr_7b_beta, headers=HEADERS, json=payload)
     response.raise_for_status()
     return response.json()
 
-# Function to get the response from the model
-def predict_beta(message, chatbot=[], system_prompt=""):
+def predict_beta(message, chatbot=[], system_prompt=zephyr_system_prompt):
     input_prompt = build_input_prompt(message, chatbot, system_prompt)
-    data = {"inputs": input_prompt}
+    data = {
+        "inputs": input_prompt
+    }
 
     try:
         response_data = post_request_beta(data)
@@ -37,28 +53,23 @@ def predict_beta(message, chatbot=[], system_prompt=""):
             bot_message = json_obj['generated_text']
             return bot_message
         elif 'error' in json_obj:
-            raise st.error(json_obj['error'] + ' Please refresh and try again with a smaller input prompt')
+            st.exception(Exception(json_obj['error'] + ' Please refresh and try again with a smaller input prompt'))
         else:
             warning_msg = f"Unexpected response: {json_obj}"
-            raise st.error(warning_msg)
+            st.exception(Exception(warning_msg))
     except requests.HTTPError as e:
         error_msg = f"Request failed with status code {e.response.status_code}"
-        raise st.error(error_msg)
+        st.exception(Exception(error_msg))
     except json.JSONDecodeError as e:
         error_msg = f"Failed to decode response as JSON: {str(e)}"
-        raise st.error(error_msg)
-
-# Streamlit UI setup
-st.title("GPT Baker with Streamlit")
-
-# ... (Add your Streamlit UI components)
+        st.exception(Exception(error_msg))
 
-# Example Streamlit components:
-user_input = st.text_input("User Input", "Your default example input")
-submit_button = st.button("Submit")
+# Streamlit app
+st.markdown("🥧 **GPT Baker** lets you create your own **open-source GPTs.**")
+user_input = st.text_input("Say something like", "make a bot that gives advice on how to grow your startup.")
+st.markdown(welcome_message)
+st.markdown("You can build and test them for free, but will need a [HF Pro account](https://huggingface.co/subscribe/pro) to publish them on Spaces (as Open GPTs are powered by the Zephyr 7B beta model using the HF Inference API). You will **not be charged** for usage of your Open GPT as the HF Inference API Pro membership does not charge per-query.")
 
-if submit_button:
-    # Get the model response
-    model_response = predict_beta(user_input)
-    st.write("Model Response:")
-    st.write(model_response)
+# Predict and display the response
+model_response = predict_beta(user_input)
+st.markdown(f"**Model Response:** {model_response}")