Added Hermes
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+58
-5
@@ -38,6 +38,7 @@ class BingImageGrabber:
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"num_of_images": ("INT", {"default": 1}),
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"cache_search": ("BOOLEAN", {"default": True},),
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"cache_images": ("BOOLEAN", {"default": True},),
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"use_number_of_links": ("INT", {"default": -1}),
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},
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}
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@@ -54,7 +55,7 @@ class BingImageGrabber:
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def IS_CHANGED(cls, **kwargs):
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return float("NaN")
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def test(self, search_term, num_of_images, cache_search, cache_images):
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def test(self, search_term, num_of_images, cache_search, cache_images, use_number_of_links):
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iterations = 1
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@@ -118,6 +119,9 @@ class BingImageGrabber:
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if not os.path.exists("./ComfyUI/custom_nodes/ConCarneNode/searchcache/"+texthash) and cache_images:
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os.makedirs("./ComfyUI/custom_nodes/ConCarneNode/searchcache/"+texthash)
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if (use_number_of_links > 0):
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totallinks = totallinks[0:use_number_of_links]
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random.shuffle(totallinks)
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for index in range(len(totallinks)):
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@@ -147,7 +151,7 @@ class BingImageGrabber:
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try:
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request=urllib.request.Request(url,None,urlopenheader)
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image_data=urllib.request.urlopen(request).read()
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image_data=urllib.request.urlopen(request, timeout=3).read()
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except:
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continue
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@@ -172,7 +176,7 @@ class BingImageGrabber:
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foundimage = center_crop(foundimage, minsize, minsize)
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image = foundimage.resize((512,512))
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image = foundimage.resize((1024,1024))
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else:
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@@ -184,6 +188,8 @@ class BingImageGrabber:
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images.append(image)
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print("Image number " + str(len(images)) + " downloaded")
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break
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@@ -251,15 +257,62 @@ class Zephyr:
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return (compiledtext,)
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class Hermes:
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"prompt": ("STRING", {"default": "A list of interesting subjects for photographs are as follows:"}),
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},
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}
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RETURN_TYPES = ("STRING",)
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FUNCTION = "test"
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CATEGORY = "ConCarne"
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#@classmethod
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#def IS_CHANGED(cls, **kwargs):
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# return float("NaN")
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def test(self, prompt):
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tokenizer = AutoTokenizer.from_pretrained('TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ')
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model = AutoModelForCausalLM.from_pretrained(
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'TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ',
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device_map="auto",
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trust_remote_code=False,
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revision="main")
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prompt = prompt
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prompt_template=f'''<|im_start|>system
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{system_message}<|im_end|>
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<|im_start|>user
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{prompt}<|im_end|>
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<|im_start|>assistant
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'''
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input_ids = tokenizer(prompt_template, return_tensors='pt').input_ids.cuda()
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output = model.generate(inputs=input_ids, temperature=0.7, do_sample=True, top_p=0.95, top_k=40, max_new_tokens=512)
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return (tokenizer.decode(output[0]),)
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# A dictionary that contains all nodes you want to export with their names
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# NOTE: names should be globally unique
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NODE_CLASS_MAPPINGS = {
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"BingImageGrabber": BingImageGrabber,
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"Zephyr": Zephyr
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"Zephyr": Zephyr,
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"Hermes": Hermes
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}
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# A dictionary that contains the friendly/humanly readable titles for the nodes
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NODE_DISPLAY_NAME_MAPPINGS = {
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"BingImageGrabber": "Bing Image Grabber",
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"Zephyr": "Zephyr Chat"
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"Zephyr": "Zephyr Chat",
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"Hermes": "Hermes Chat"
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}
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@@ -0,0 +1,2 @@
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--i https://huggingface.github.io/autogptq-index/whl/cu118/
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auto-gptq
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