Create app.py

app.py

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+import os
+import gc
+import torch
+import gradio as ui
+from transformers import pipeline, TextIteratorStreamer
+from threading import Thread
+
+# 1. Initialize Pipeline
+MODEL_ID = "Xerv-AI/tarn"
+
+print("Loading tarn architecture into memory...")
+
+# FIX: Replaced 'torch_dtype' with 'dtype' to clear the transformers deprecation warning.
+pipe = pipeline(
+    "image-text-to-text", 
+    model=MODEL_ID, 
+    model_kwargs={
+        "dtype": torch.float16, 
+        "device_map": "auto"
+    }
+)
+print("tarn is fully initialized.")
+
+# 2. Define the Inference Logic
+def process_chat(message, history):
+    """
+    Handles incoming messages (both images and text), formats them into 
+    the proper Qwen 3.5 VL structure, and yields streamed tokens.
+    """
+    # Force clean any leftover GPU allocation trash before processing
+    gc.collect()
+    torch.cuda.empty_cache()
+
+    # Reconstruct history into Hugging Face chat template format
+    formatted_messages = []
+    
+    # Process previous conversation turns
+    for user_turn, assistant_turn in history:
+        if user_turn:
+            # Check if user input in history was a file/image dict or text
+            if isinstance(user_turn, dict) or (isinstance(user_turn, tuple) and len(user_turn) == 1):
+                img_path = user_turn[0] if isinstance(user_turn, tuple) else user_turn.get("path")
+                formatted_messages.append({"role": "user", "content": [{"type": "image", "url": img_path}]})
+            else:
+                formatted_messages.append({"role": "user", "content": [{"type": "text", "text": str(user_turn)}]})
+        if assistant_turn:
+            formatted_messages.append({"role": "assistant", "content": [{"type": "text", "text": str(assistant_turn)}]})
+
+    # Append current incoming turn
+    current_content = []
+    
+    # Check if the user uploaded an image along with text
+    if message["files"]:
+        for file_info in message["files"]:
+            # Gradio 4+ passes files as dicts or named objects
+            file_path = file_info if isinstance(file_info, str) else file_info.get("path")
+            current_content.append({"type": "image", "url": file_path})
+            
+    if message["text"]:
+        current_content.append({"type": "text", "text": message["text"]})
+        
+    # Guard clause if user sent nothing
+    if not current_content:
+        yield ""
+        return
+
+    formatted_messages.append({"role": "user", "content": current_content})
+
+    # Initialize a non-blocking compilation streamer 
+    streamer = TextIteratorStreamer(pipe.tokenizer, skip_prompt=True, skip_special_tokens=True)
+
+    # Inject VRAM patch configurations directly into generator parameters
+    generate_kwargs = {
+        "text": formatted_messages,
+        "max_new_tokens": 1024,
+        "min_pixels": 256 * 28 * 28,
+        "max_pixels": 512 * 28 * 28,
+        "generate_kwargs": {"streamer": streamer}
+    }
+
+    # Execute text generation on a separate background thread to keep UI interactive
+    thread = Thread(target=pipe, kwargs=generate_kwargs)
+    thread.start()
+
+    # Yield generated tokens back to UI as they arrive
+    partial_text = ""
+    for new_token in streamer:
+        partial_text += new_token
+        yield partial_text
+
+# 3. Build Web Layout using Custom Calm Styling Themes
+custom_theme = ui.themes.Soft(
+    primary_hue="orange",    # Brings in that subtle "tangy" vibe softly
+    neutral_hue="slate",     # Keeps the interface looking professional and clean
+    font=[ui.themes.GoogleFont("Source Sans Pro"), "Arial", "sans-serif"]
+)
+
+# FIX: Removed `theme=custom_theme` from Blocks (moved to launch).
+with ui.Blocks(title="tarn Demo Space") as demo:
+    ui.Markdown(
+        """
+        # 🌌 tarn Multimodal Reasoner
+        ### Fine-tuned for deep visual context analysis and structured step-by-step logic.
+        *Built and maintained by **Xerv-AI**.*
+        """
+    )
+    
+    # Core multi-turn Gradio Chatbot interface
+    chatbot_interface = ui.ChatInterface(
+        fn=process_chat,
+        chatbot=ui.Chatbot(
+            height=550, 
+            placeholder="📸 Upload an image or ask a structural reasoning question...",
+            # FIX: Removed `show_copy_button=True` as it is removed in newer Gradio versions.
+            avatar_images=(None, "https://huggingface.co/front/assets/huggingface/logos/huggingface-logo-dark.svg")
+        ),
+        multimodal=True, # Explicitly turns on the combined image upload + text input array
+        textbox=ui.MultimodalTextbox(
+            placeholder="Type your question here... (Click the paperclip icon to pin an image)",
+            file_types=["image"],
+            scale=7
+        )
+    )
+
+if __name__ == "__main__":
+    # FIX: Passed the theme to the launch method to satisfy Gradio 6.0 requirements.
+    demo.queue().launch(theme=custom_theme)