Switch Qwen2-VL notebook to GenAI (#2723)

Ticket: CVS-158716

---------

Co-authored-by: Ekaterina Aidova <[email protected]>

notebooks/qwen2-vl/README.md

@@ -34,7 +34,8 @@ The tutorial consists from following steps:
 
 - Install requirements
 - Convert and Optimize model
-- Run OpenVINO model inference
+- Prepare OpenVINO GenAI Inference Pipeline
+- Run OpenVINO GenAI model inference
 - Launch Interactive demo
 
 In this demonstration, you'll create interactive chatbot that can answer questions about provided image's content.

notebooks/qwen2-vl/gradio_helper.py

@@ -1,205 +1,131 @@
+from pathlib import Path
 import gradio as gr
-import copy
-import re
-from threading import Thread
-from transformers import TextIteratorStreamer
-from qwen_vl_utils import process_vision_info
-
-
-def _parse_text(text):
-    lines = text.split("\n")
-    lines = [line for line in lines if line != ""]
-    count = 0
-    for i, line in enumerate(lines):
-        if "```" in line:
-            count += 1
-            items = line.split("`")
-            if count % 2 == 1:
-                lines[i] = f'<pre><code class="language-{items[-1]}">'
-            else:
-                lines[i] = "<br></code></pre>"
-        else:
-            if i > 0:
-                if count % 2 == 1:
-                    line = line.replace("`", r"\`")
-                    line = line.replace("<", "&lt;")
-                    line = line.replace(">", "&gt;")
-                    line = line.replace(" ", "&nbsp;")
-                    line = line.replace("*", "&ast;")
-                    line = line.replace("_", "&lowbar;")
-                    line = line.replace("-", "&#45;")
-                    line = line.replace(".", "&#46;")
-                    line = line.replace("!", "&#33;")
-                    line = line.replace("(", "&#40;")
-                    line = line.replace(")", "&#41;")
-                    line = line.replace("$", "&#36;")
-                lines[i] = "<br>" + line
-    text = "".join(lines)
-    return text
-
-
-def _remove_image_special(text):
-    text = text.replace("<ref>", "").replace("</ref>", "")
-    return re.sub(r"<box>.*?(</box>|$)", "", text)
-
-
-def is_video_file(filename):
-    video_extensions = [".mp4", ".avi", ".mkv", ".mov", ".wmv", ".flv", ".webm", ".mpeg"]
-    return any(filename.lower().endswith(ext) for ext in video_extensions)
-
-
-def transform_messages(original_messages):
-    transformed_messages = []
-    for message in original_messages:
-        new_content = []
-        for item in message["content"]:
-            if "image" in item:
-                new_item = {"type": "image", "image": item["image"]}
-            elif "text" in item:
-                new_item = {"type": "text", "text": item["text"]}
-            elif "video" in item:
-                new_item = {"type": "video", "video": item["video"]}
-            else:
-                continue
-            new_content.append(new_item)
 
-        new_message = {"role": message["role"], "content": new_content}
-        transformed_messages.append(new_message)
 
-    return transformed_messages
+from PIL import Image
+import numpy as np
+import requests
+from threading import Event, Thread
+import inspect
+from queue import Queue
 
+example_image_urls = [
+    (
+        "https://github.com/openvinotoolkit/openvino_notebooks/assets/29454499/1d6a0188-5613-418d-a1fd-4560aae1d907",
+        "bee.jpg",
+    ),
+    (
+        "https://github.com/openvinotoolkit/openvino_notebooks/assets/29454499/6cc7feeb-0721-4b5d-8791-2576ed9d2863",
+        "baklava.png",
+    ),
+]
+for url, file_name in example_image_urls:
+    if not Path(file_name).exists():
+        Image.open(requests.get(url, stream=True).raw).save(file_name)
 
-def make_demo(model, processor):
-    def call_local_model(model, processor, messages):
-        messages = transform_messages(messages)
 
-        text = processor.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
-        image_inputs, video_inputs = process_vision_info(messages)
-        inputs = processor(text=[text], images=image_inputs, videos=video_inputs, padding=True, return_tensors="pt").to(model.device)
+def make_demo(model):
+    import openvino_genai
+    import openvino as ov
 
-        tokenizer = processor.tokenizer
-        streamer = TextIteratorStreamer(tokenizer, timeout=3600.0, skip_prompt=True, skip_special_tokens=True)
+    has_additonal_buttons = "undo_button" in inspect.signature(gr.ChatInterface.__init__).parameters
 
-        gen_kwargs = {"max_new_tokens": 512, "streamer": streamer, **inputs}
+    def read_image(path: str) -> ov.Tensor:
+        """
 
-        thread = Thread(target=model.generate, kwargs=gen_kwargs)
-        thread.start()
+        Args:
+            path: The path to the image.
 
-        generated_text = ""
-        for new_text in streamer:
-            generated_text += new_text
-            yield generated_text
-
-    def create_predict_fn():
-        def predict(_chatbot, task_history):
-            chat_query = _chatbot[-1][0]
-            query = task_history[-1][0]
-            if len(chat_query) == 0:
-                _chatbot.pop()
-                task_history.pop()
-                return _chatbot
-            print("User: " + _parse_text(query))
-            history_cp = copy.deepcopy(task_history)
-            full_response = ""
-            messages = []
-            content = []
-            for q, a in history_cp:
-                if isinstance(q, (tuple, list)):
-                    if is_video_file(q[0]):
-                        content.append({"video": f"file://{q[0]}"})
-                    else:
-                        content.append({"image": f"file://{q[0]}"})
-                else:
-                    content.append({"text": q})
-                    messages.append({"role": "user", "content": content})
-                    messages.append({"role": "assistant", "content": [{"text": a}]})
-                    content = []
-            messages.pop()
-
-            for response in call_local_model(model, processor, messages):
-                _chatbot[-1] = (_parse_text(chat_query), _remove_image_special(_parse_text(response)))
-
-                yield _chatbot
-                full_response = _parse_text(response)
-
-            task_history[-1] = (query, full_response)
-            print("Qwen-VL-Chat: " + _parse_text(full_response))
-            yield _chatbot
-
-        return predict
-
-    def create_regenerate_fn():
-        def regenerate(_chatbot, task_history):
-            if not task_history:
-                return _chatbot
-            item = task_history[-1]
-            if item[1] is None:
-                return _chatbot
-            task_history[-1] = (item[0], None)
-            chatbot_item = _chatbot.pop(-1)
-            if chatbot_item[0] is None:
-                _chatbot[-1] = (_chatbot[-1][0], None)
-            else:
-                _chatbot.append((chatbot_item[0], None))
-            _chatbot_gen = predict(_chatbot, task_history)
-            for _chatbot in _chatbot_gen:
-                yield _chatbot
-
-        return regenerate
-
-    predict = create_predict_fn()
-    regenerate = create_regenerate_fn()
-
-    def add_text(history, task_history, text):
-        task_text = text
-        history = history if history is not None else []
-        task_history = task_history if task_history is not None else []
-        history = history + [(_parse_text(text), None)]
-        task_history = task_history + [(task_text, None)]
-        return history, task_history, ""
-
-    def add_file(history, task_history, file):
-        history = history if history is not None else []
-        task_history = task_history if task_history is not None else []
-        history = history + [((file.name,), None)]
-        task_history = task_history + [((file.name,), None)]
-        return history, task_history
-
-    def reset_user_input():
-        return gr.update(value="")
-
-    def reset_state(task_history):
-        task_history.clear()
-        return []
-
-    with gr.Blocks() as demo:
-        gr.Markdown("""<center><font size=8>Qwen2-VL OpenVINO demo</center>""")
-
-        chatbot = gr.Chatbot(label="Qwen2-VL", elem_classes="control-height", height=500)
-        query = gr.Textbox(lines=2, label="Input")
-        task_history = gr.State([])
-
-        with gr.Row():
-            addfile_btn = gr.UploadButton("📁 Upload (上传文件)", file_types=["image", "video"])
-            submit_btn = gr.Button("🚀 Submit (发送)")
-            regen_btn = gr.Button("🤔️ Regenerate (重试)")
-            empty_bin = gr.Button("🧹 Clear History (清除历史)")
-
-        submit_btn.click(add_text, [chatbot, task_history, query], [chatbot, task_history]).then(
-            predict, [chatbot, task_history], [chatbot], show_progress=True
-        )
-        submit_btn.click(reset_user_input, [], [query])
-        empty_bin.click(reset_state, [task_history], [chatbot], show_progress=True)
-        regen_btn.click(regenerate, [chatbot, task_history], [chatbot], show_progress=True)
-        addfile_btn.upload(add_file, [chatbot, task_history, addfile_btn], [chatbot, task_history], show_progress=True)
-
-        gr.Markdown(
-            """\
-<font size=2>Note: This demo is governed by the original license of Qwen2-VL. \
-We strongly advise users not to knowingly generate or allow others to knowingly generate harmful content, \
-including hate speech, violence, pornography, deception, etc. \
-(注：本演示受Qwen2-VL的许可协议限制。我们强烈建议，用户不应传播及不应允许他人传播以下内容，\
-包括但不限于仇恨言论、暴力、色情、欺诈相关的有害信息。)"""
-        )
+        Returns: the ov.Tensor containing the image.
+
+        """
+        pic = Image.open(path).convert("RGB")
+        image_data = np.array(pic.getdata()).reshape(1, pic.size[1], pic.size[0], 3).astype(np.byte)
+        return ov.Tensor(image_data)
+
+    class TextQueue:
+        def __init__(self) -> None:
+            self.text_queue = Queue()
+            self.stop_signal = None
+            self.stop_tokens = []
 
+        def __call__(self, text):
+            self.text_queue.put(text)
+
+        def __iter__(self):
+            return self
+
+        def __next__(self):
+            value = self.text_queue.get()
+            if value == self.stop_signal or value in self.stop_tokens:
+                raise StopIteration()
+            else:
+                return value
+
+        def reset(self):
+            self.text_queue = Queue()
+
+        def end(self):
+            self.text_queue.put(self.stop_signal)
+
+    def bot_streaming(message, history):
+        print(f"message is - {message}")
+        print(f"history is - {history}")
+
+        if not history:
+            model.start_chat()
+        generation_config = openvino_genai.GenerationConfig()
+        generation_config.max_new_tokens = 128
+        files = message["files"] if isinstance(message, dict) else message.files
+        message_text = message["text"] if isinstance(message, dict) else message.text
+
+        image = None
+        if files:
+            # message["files"][-1] is a Dict or just a string
+            if isinstance(files[-1], dict):
+                image = files[-1]["path"]
+            else:
+                if isinstance(files[-1], (str, Path)):
+                    image = files[-1]
+                else:
+                    image = files[-1] if isinstance(files[-1], (list, tuple)) else files[-1].path
+        if image is not None:
+            image = read_image(image)
+        streamer = TextQueue()
+        stream_complete = Event()
+
+        def generate_and_signal_complete():
+            """
+            generation function for single thread
+            """
+            streamer.reset()
+            generation_kwargs = {"prompt": message_text, "generation_config": generation_config, "streamer": streamer}
+            if image is not None:
+                generation_kwargs["image"] = image
+            model.generate(**generation_kwargs)
+            stream_complete.set()
+            streamer.end()
+
+        t1 = Thread(target=generate_and_signal_complete)
+        t1.start()
+
+        buffer = ""
+        for new_text in streamer:
+            buffer += new_text
+            yield buffer
+
+    additional_buttons = {}
+    if has_additonal_buttons:
+        additional_buttons = {"undo_button": None, "retry_button": None}
+    demo = gr.ChatInterface(
+        fn=bot_streaming,
+        title="Qwen2-VL OpenVINO Demo",
+        examples=[
+            {"text": "What is on the flower?", "files": ["./bee.jpg"]},
+            {"text": "How to make this pastry?", "files": ["./baklava.png"]},
+        ],
+        stop_btn=None,
+        multimodal=True,
+        **additional_buttons,
+    )
     return demo