fill screen height

app.py

@@ -1,92 +1,93 @@
-import gradio as gr
-from transformers import TextIteratorStreamer, AutoModelForCausalLM, AutoProcessor
-from threading import Thread
-import re
-import time
-from PIL import Image
-import torch
-import argparse
-import spaces
-
-parser = argparse.ArgumentParser()
-parser.add_argument('--model', type=str, default='aya')
-args = parser.parse_args()
-
-model_name = args.model
-
-processor = AutoProcessor.from_pretrained(f"WueNLP/centurio_{model_name}", trust_remote_code=True)
-model = AutoModelForCausalLM.from_pretrained(f"WueNLP/centurio_{model_name}",
-                                             trust_remote_code=True,
-                                             torch_dtype=torch.bfloat16,
-                                             low_cpu_mem_usage=True
-                                             ).to("cuda:0")
-
-@spaces.GPU
-def bot_streaming(message, history):
-    if message["files"]:
-        image = message["files"][-1]
-    else:
-        # if there's no image uploaded for this turn, look for images in the past turns
-        # kept inside tuples, take the last one
-        for hist in history:
-            if type(hist[0]) == tuple:
-                image = hist[0][0]
-
-    if "qwen" in model_name:
-        if image is None:
-            prompt = f"<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n<|im_start|>user\n{message['text']}<|im_end|>\n<|im_start|>assistant\n"
-        else:
-            image = Image.open(image).convert("RGB")
-            prompt = f"<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n<|im_start|>user\n<image_placeholder>\n{message['text']}<|im_end|>\n<|im_start|>assistant\n"
-    else:
-        if image is None:
-            prompt = f"<BOS_TOKEN><|START_OF_TURN_TOKEN|><|USER_TOKEN|>{message['text']}<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>"
-        else:
-            image = Image.open(image).convert("RGB")
-            prompt = f"<BOS_TOKEN><|START_OF_TURN_TOKEN|><|USER_TOKEN|><image_placeholder>\n{message['text']}<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>"
-
-    inputs = processor(text=prompt, images=image, return_tensors="pt").to("cuda:0", torch.bfloat16)
-
-    streamer = TextIteratorStreamer(processor, **{"skip_special_tokens": False})
-    generation_kwargs = dict(inputs, streamer=streamer,
-                             do_sample=True,
-                             num_beams=1,
-                             repetition_penalty=1.15,
-                             temperature=0.7,
-                             top_p=0.8,
-                             top_k=20,
-                             max_new_tokens=512, min_new_tokens=1)
-
-    thread = Thread(target=model.generate, kwargs=generation_kwargs)
-    thread.start()
-
-    buffer = ""
-    for new_text in streamer:
-        buffer += new_text
-        if "qwen" in model_name:
-            generated_text_without_prompt = buffer.split("<|im_start|>assistant\n")[-1].split("<|im_end|>")[0]
-        else:
-            generated_text_without_prompt = buffer.split("<|CHATBOT_TOKEN|>")[-1].split("<|END_OF_TURN_TOKEN|>")[0]
-
-        time.sleep(0.04)
-        yield generated_text_without_prompt
-
-
-description = ("""# [Centurio: On Drivers of Multilingual Ability of Large Vision-Language Model](gregor-ge.github.io/Centurio/)
-Try [Centurio](https://huggingface.co/collections/WueNLP/centurio-677cf0ab6ddea874927a154e), a massively multilingual large vision-language model, in this demo (specifically, [Centurio Aya](https://huggingface.co/WueNLP/centurio_aya)). 
-Upload an image and start chatting about it, or try one of the examples below. 
-
-Centurio is trained with 100 languages but quality of answers can differ greatly depending on your language. 
-Centurio is trained to read text in images but struggles with small text and with non-Latin scripts.
-
-> If you don't upload an image, you will receive an error.
-> This demo does not support multi-image prompts or multi-turn dialog. Every new prompt will refer to the last image (if no new image is included) without prior dialog as context.""")
-
-demo = gr.ChatInterface(fn=bot_streaming, title="Centurio Demo",
-                        examples=[{"text": "What is on the flower?", "files": ["./bee.jpg"]},
-                                  {"text": "How to make this pastry?", "files": ["./baklava.png"]}],
-                        description=description,
-                        stop_btn="Stop Generation",
-                        multimodal=True
-                        )
+import gradio as gr
+from transformers import TextIteratorStreamer, AutoModelForCausalLM, AutoProcessor
+from threading import Thread
+import re
+import time
+from PIL import Image
+import torch
+import argparse
+import spaces
+
+parser = argparse.ArgumentParser()
+parser.add_argument('--model', type=str, default='aya')
+args = parser.parse_args()
+
+model_name = args.model
+
+processor = AutoProcessor.from_pretrained(f"WueNLP/centurio_{model_name}", trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(f"WueNLP/centurio_{model_name}",
+                                             trust_remote_code=True,
+                                             torch_dtype=torch.bfloat16,
+                                             low_cpu_mem_usage=True
+                                             ).to("cuda:0")
+
+@spaces.GPU
+def bot_streaming(message, history):
+    if message["files"]:
+        image = message["files"][-1]
+    else:
+        # if there's no image uploaded for this turn, look for images in the past turns
+        # kept inside tuples, take the last one
+        for hist in history:
+            if type(hist[0]) == tuple:
+                image = hist[0][0]
+
+    if "qwen" in model_name:
+        if image is None:
+            prompt = f"<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n<|im_start|>user\n{message['text']}<|im_end|>\n<|im_start|>assistant\n"
+        else:
+            image = Image.open(image).convert("RGB")
+            prompt = f"<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n<|im_start|>user\n<image_placeholder>\n{message['text']}<|im_end|>\n<|im_start|>assistant\n"
+    else:
+        if image is None:
+            prompt = f"<BOS_TOKEN><|START_OF_TURN_TOKEN|><|USER_TOKEN|>{message['text']}<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>"
+        else:
+            image = Image.open(image).convert("RGB")
+            prompt = f"<BOS_TOKEN><|START_OF_TURN_TOKEN|><|USER_TOKEN|><image_placeholder>\n{message['text']}<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>"
+
+    inputs = processor(text=prompt, images=image, return_tensors="pt").to("cuda:0", torch.bfloat16)
+
+    streamer = TextIteratorStreamer(processor, **{"skip_special_tokens": False})
+    generation_kwargs = dict(inputs, streamer=streamer,
+                             do_sample=True,
+                             num_beams=1,
+                             repetition_penalty=1.15,
+                             temperature=0.7,
+                             top_p=0.8,
+                             top_k=20,
+                             max_new_tokens=512, min_new_tokens=1)
+
+    thread = Thread(target=model.generate, kwargs=generation_kwargs)
+    thread.start()
+
+    buffer = ""
+    for new_text in streamer:
+        buffer += new_text
+        if "qwen" in model_name:
+            generated_text_without_prompt = buffer.split("<|im_start|>assistant\n")[-1].split("<|im_end|>")[0]
+        else:
+            generated_text_without_prompt = buffer.split("<|CHATBOT_TOKEN|>")[-1].split("<|END_OF_TURN_TOKEN|>")[0]
+
+        time.sleep(0.04)
+        yield generated_text_without_prompt
+
+
+description = ("""# [Centurio: On Drivers of Multilingual Ability of Large Vision-Language Model](gregor-ge.github.io/Centurio/)
+Try [Centurio](https://huggingface.co/collections/WueNLP/centurio-677cf0ab6ddea874927a154e), a massively multilingual large vision-language model, in this demo (specifically, [Centurio Aya](https://huggingface.co/WueNLP/centurio_aya)). 
+Upload an image and start chatting about it, or try one of the examples below. 
+
+Centurio is trained with 100 languages but quality of answers can differ greatly depending on your language. 
+Centurio is trained to read text in images but struggles with small text and with non-Latin scripts.
+
+> If you don't upload an image, you will receive an error.
+> This demo does not support multi-image prompts or multi-turn dialog. Every new prompt will refer to the last image (if no new image is included) without prior dialog as context.""")
+
+demo = gr.ChatInterface(fn=bot_streaming, title="Centurio Demo",
+                        examples=[{"text": "What is on the flower?", "files": ["./bee.jpg"]},
+                                  {"text": "How to make this pastry?", "files": ["./baklava.png"]}],
+                        description=description,
+                        stop_btn="Stop Generation",
+                        multimodal=True,
+                        fill_height=True,
+                        )
 demo.launch(debug=True, share=True)