Update app.py

app.py

@@ -10,25 +10,24 @@ st.title("🤖 ShotCaller: Prompt Lab")
 st.markdown("Explore how different prompting techniques change AI reasoning.")
 
 # --- 2. Model Setup ---
-# Retrieve your token from Hugging Face Settings > Secrets
 api_token = os.getenv("HUGGINGFACEHUB_API_TOKEN")
 
 if not api_token:
     st.error("Missing HUGGINGFACEHUB_API_TOKEN. Add it to your Space Secrets!")
     st.stop()
 
-# Initialize the endpoint
-# Note: task="text-generation" is required for the underlying class, 
-# but ChatHuggingFace will handle the conversational routing.
-repo_id = "mistralai/Mistral-7B-Instruct-v0.3"
+# Switching to Llama-3.1-8B-Instruct (Highly compatible)
+repo_id = "meta-llama/Llama-3.1-8B-Instruct"
+
 llm = HuggingFaceEndpoint(
     repo_id=repo_id,
-    task="text-generation",
+    task="text-generation", # Base task
     temperature=0.7,
-    huggingfacehub_api_token=api_token
+    huggingfacehub_api_token=api_token,
+    timeout=300
 )
 
-# Wrap the LLM in ChatHuggingFace to satisfy the 'conversational' requirement
+# This wrapper will now correctly identify Llama as a chat-capable model
 chat_model = ChatHuggingFace(llm=llm)
 
 # --- 3. Sidebar Selection ---