Create app.py

app.py

@@ -0,0 +1,91 @@
+import streamlit as st
+from huggingface_hub import InferenceClient
+import random
+
+# Replace with your desired model ID from Hugging Face Hub
+client = InferenceClient("unsloth/Llama-3.2-1B-Instruct") 
+
+words = [
+    # ... Add your list of nouns, adjectives, verbs, and adverbs here ...
+]
+
+
+class WordGame:
+    def __init__(self):
+        self.points = 0
+        self.target_word = ""
+        self.attempts = 3
+        self.generate_task()
+
+    def generate_task(self):
+        self.attempts = 3
+        self.target_word = random.choice(words)
+        st.session_state["target_word"] = self.target_word  # Store in session state
+        st.title(f'The Game - Current score: {self.points}, remaining attempts: {self.attempts}')
+
+    def check_input_for_word(self, user_input):
+        if self.target_word in user_input.lower():
+            self.generate_task()
+            self.points -= 1
+            st.write(f"You input the target word yourself, so you lost one point and the game reset.")
+            return True
+        else:
+            return False
+
+    def check_output_for_word(self, response):
+        if self.target_word in response.lower():
+            self.points += self.attempts
+            score_gained = self.attempts
+            self.generate_task()
+            return f"Success! You earned {score_gained} points!"
+        else:
+            self.attempts -= 1
+            if self.attempts <= 0:
+                self.generate_task()
+                return f"You did not win in three attempts. Generating new target word."
+            else:
+                return "That didn't quite hit the mark. Try again!"
+
+    def respond(self, user_message):
+        messages = [{"role": "system", "content": st.session_state["system_message"]}]
+        
+        for val in st.session_state["history"]:
+            if val[0]:
+                messages.append({"role": "user", "content": val[0]})
+            if val[1]:
+                messages.append({"role": "assistant", "content": val[1]})
+
+        messages.append({"role": "user", "content": user_message})
+        response = ""
+        for message in client.chat_completion(
+            messages, max_tokens=st.session_state["max_tokens"], stream=True,
+            temperature=st.session_state["temperature"], top_p=st.session_state["top_p"]
+        ):
+            token = message.choices[0].delta.content
+            response += token
+        
+        output_check_result = self.check_output_for_word(response)
+        st.write(response + f"\n\n---\n\n{output_check_result}")
+        st.write(f'Current score: {self.points}, remaining attempts: {self.attempts}')
+
+        # Update session state with history and system message
+        st.session_state["history"].append((user_message, response))
+        st.session_state["system_message"] = response
+
+
+game = WordGame()
+
+# Session state variables to store dynamic information
+st.session_state["history"] = []  # List of tuples (user message, response)
+st.session_state["system_message"] = "You are a friendly Chatbot."  # Initial system message
+
+# Streamlit interface elements
+system_message_input = st.text_input("System message", value=st.session_state["system_message"])
+max_tokens_slider = st.slider("Max new tokens", minimum=1, maximum=2048, value=512, step=1)
+temperature_slider = st.slider("Temperature", minimum=0.1, maximum=4.0, value=0.7, step=0.1)
+top_p_slider = st.slider("Top-p (nucleus sampling)", minimum=0.1, maximum=1.0, value=0.95, step=0.05)
+
+# Update session state with user input for system message
+st.session_state["system_message"] = system_message_input
+
+user_message = st.text_