Update app.py

app.py

@@ -1,34 +1,17 @@
-import gradio as gr
-
-import threading
-
-# Load model directly
-
-
-from transformers import AutoModel
-
-import numpy as np  # Import NumPy for memory-efficient data structures
-
-import gc  # Import garbage collector for explicit memory management
-
-# Increase thread stack size
-
-threading.stack_size(2**33)
-
-# Load the model
-model = gr.load("huggingface/Liquid1/llama-3-8b-liquid-coding-agent")
-
-# Preload large datasets or pre-trained weights (if applicable)
-# ...
-
-# Launch the model in a thread
-thread = threading.Thread(target=model.launch)
-
-# Start the thread
-thread.start()
-
-# Explicitly trigger garbage collection to free up memory
-gc.collect()
-
-# Continue with other tasks or image generation code
-# ...                                                                           
+        import gradio as gr
+import concurrent.futures
+
+# Load the model into RAM
+model = gr.load("models/TheBloke/SOLAR-10.7B-Instruct-v1.0-uncensored-GGUF")
+
+def interact(input):
+    # Define the function for user interaction
+    response = model(input)
+    return response
+
+# Use ThreadPoolExecutor to manage the threads
+with concurrent.futures.ThreadPoolExecutor(max_workers=2) as executor:
+    # Create a Gradio interface with the loaded model
+    interface = gr.Interface(fn=interact, inputs="text", outputs="image")
+    # Handle the interactions with Gradio
+    interface.launch()