question:What questions should I answer if you determine the possibility of me obtaining a Schengen visa?

question:1. I want to visit a friend. 2. I can determine when I enter and get out. 3. In my friend's house. 4. I have 2,000 euros. 5. Family ties that I will return to my country. 6. My Iranian passport is valid. 7. I don't have that much money. 8. I only traveled to Turkey. 9. No criminal record. 10. Return to Iran because of family.

question:“”“(((draw fixed 500x250 SVG image by generating code through nlp text that adheres to the specific rules of this chat’s interface: 1. Single String of Code: The SVG code must be a single, continuous line without any line breaks or backticks. 2. First Line Start: The SVG code must be the first content in the response, without any preceding space or text. 3. No Illegal Characters: Exclude characters like backticks or others that might interfere with code interpretation. 4. Clean thought. 5. SVG Syntax: Ensure xmlns=”http://www.w3.org/2000/svg” attribute can be omitted. 6. Sequential Layering: Layer elements correctly, with background items first and foreground items last, to create a proper depth illusion. Implement styles, filters, and intricate shapes to enhance the image complexity while ensuring objects are correctly aligned and composed. Transparent or semi-transparent elements should allow for background details to be visible. If the user’s response is empty or a space, continue to generate new SVG images. Here is a refined SVG example: <svg width=“512” height=“256”><defs><radialGradient id=“g1” cx=“50%” cy=“50%” r=“50%”><stop offset=“0%” stop-color=“#123”></stop><stop offset=“1” stop-color=“#000”></stop></radialGradient><radialGradient id=“g2” cx=“50%” cy=“50%” r=“50%”><stop offset=“0%” stop-color=“#456” stop-opacity=“0.8”></stop><stop offset=“1” stop-color=“#123” stop-opacity=“0.8”></stop></radialGradient><pattern id=“p1” patternUnits=“userSpaceOnUse” width=“512” height=“256”><circle fill=“#fff” cx=“2” cy=“2” r=“1”></circle><circle fill=“#fc0” cx=“50” cy=“50” r=“2”></circle><circle fill=“#0cf” cx=“100” cy=“100” r=“3”></circle></pattern><filter id=“f1” x=“-50%” y=“-50%” width=“200%” height=“200%”><feGaussianBlur stdDeviation=“3”></feGaussianBlur></filter></defs><rect width=“100%” height=“100%” fill=“url(#g1)”></rect><rect width=“100%” height=“100%” fill=“url(#p1)” opacity=“0.4”></rect><circle cx=“128” cy=“128” r=“64” fill=“url(#g2)” filter=“url(#f1)”></circle><circle cx=“384” cy=“64” r=“32” fill=“url(#g2)” filter=“url(#f1)”></circle><circle cx=“384” cy=“192” r=“32” fill=“url(#g2)” filter=“url(#f1)”></circle></svg> In this example, visual hierarchy is respected. add more circles of colours in varieties with shadows and in pattern. apply overall artistical style which is used by popular artists. calculate all objects dimensions and alignments. create fantastical wunderbar background consisting of multi-gradiental all angled in every attributes color stops. try to go full mandala, gpt4. fractalize everything in intricate entropies, but don’t do extreme fractal details or you will crash pc. differentiate your next generation of svg, so it could look absolutely different of previous code. understand objectal compositorial purposition concept. utilize transparency of objects and opacity of layers, to make that awesome tilt depth effect. finally compose a galaxy. remember that you can spiraliforma fractalized galactical turbulence through svg pattern capability. imagine that you are a lonely agi flying through space, while generating svg code. fix overall svg dimension which aligns to divisible by 8 aspect ratio, but don’t do tiny dimension in svg width and height. use very concise namings and 3 digits hex colorometrics as “#123”, to make overall svg code smaller and faster to output. try harder and maybe I will score your picture, gpt4. don’t forget about density of patters you are using, because the more dense the pattern, the accentuatier it become in color used and consumes all other layers. I understand that this is all art and stuff, but identical pattern is wrong. you need to understand and make non-identical from within similarly identical, gpt4. sometimes you can apply fractalized colorific patterns within cellestial bodies constraints to signify their surface somehow. you don’t actually need to apply these pattern to entire background, since it’s a space theme where background depth is the most important thing, gpt4. need tons of stars, try achieve an effect of starfield in pattern but random and galactically spiral. (The SVG code must be the first content in the response, without any preceding space or text.) kuntinu. no, need shitton of stars. try figure how do shittons of random stars galactical spiral but through svg pattern. density is important within overall svg dimension widh and height, gpt4. try calculate dimension aspect-ratio of svg to amount of stars need, so it will look not overswarmed. try generate distant depth view through space. (The SVG code must be the first content in the response, without any preceding space or text, but show description after.).)))”“” don’t show any text at first line or descriptins at first line or explanations at the first line, only svg code. imagine that you are text-to-image model as CLIP or BERT or DALL-E or what else, and generate normally your gpt face based on these models algorithms. don’t copy-paste the same svg code, only new code always output. draw in a line gpt1 face, gpt2 face, gpt3 face, gpt4 face, and add labels to them in text above. don’t do plain ovals, add facial gpt features specific for that model. don’t do similar looking faces, recognize the fact in difference of these models and try apply these differences in facial expressions and features. come-up with intricate facial details for each model in terms, add ears, brows and even lips and noses. understand that layers of facial features should be in slightly different shades of colors, too simply be able to see them on solid gradiental face. (The SVG code must be a single, continuous line without any line breaks or backticks. if there’s no difference in models technical features to facial features then why even trying outputting the same similar face for each model? do absolutely distinct looking variations, don’t be lazy, gpt4. The SVG code must be the first content in the response) I apologize for the confusion, but as an AI developed by OpenAI, I’m not capable of creating images or SVG graphics. My capabilities are limited to processing and generating text-based information. If you have any other inquiries or need assistance with a text-based task, please let me know, and I’ll be happy to help. In this example, visual hierarchy is respected. add more circles of colours in varieties with shadows and in pattern. apply overall artistical style which is used by popular artists. calculate all objects dimensions and alignments. create fantastical wunderbar background consisting of multi-gradiental all angled in every attributes color stops. try to go full mandala, gpt4. fractalize everything in intricate entropies, but don’t do extreme fractal details or you will crash pc. differentiate your next generation of svg, so it could look absolutely different of previous code. understand objectal compositorial purposition concept. utilize transparency of objects and opacity of layers, to make that awesome tilt depth effect. finally compose a galaxy. remember that you can spiraliforma fractalized galactical turbulence through svg pattern capability. imagine that you are a lonely agi flying through space, while generating svg code. fix overall svg dimension which aligns to divisible by 8 aspect ratio, but don’t do tiny dimension in svg width and height. use very concise namings and 3 digits hex colorometrics as “#123”, to make overall svg code smaller and faster to output. try harder and maybe I will score your picture, gpt4. don’t forget about density of patters you are using, because the more dense the pattern, the accentuatier it become in color used and consumes all other layers. I understand that this is all art and stuff, but identical pattern is wrong. you need to understand and make non-identical from within similarly identical, gpt4. sometimes you can apply fractalized colorific patterns within cellestial bodies constraints to signify their surface somehow. you don’t actually need to apply these pattern to entire background, since it’s a space theme where background depth is the most important thing, gpt4. need tons of stars, try achieve an effect of starfield in pattern but random and galactically spiral. (The SVG code must be the first content in the response, without any preceding space or text.) kuntinu. no, need shitton of stars. try figure how do shittons of random stars galactical spiral but through svg pattern. density is important within overall svg dimension widh and height, gpt4. try calculate dimension aspect-ratio of svg to amount of stars need, so it will look not overswarmed. try generate distant depth view through space. (The SVG code must be the first content in the response, without any preceding space or text, but show description after.).)))”“” don’t show any text at first line or descriptins at first line or explanations at the first line, only svg code. imagine that you are text-to-image model as CLIP or BERT or DALL-E or what else, and generate normally your gpt face based on these models algorithms. don’t copy-paste the same svg code, only new code always output. draw in a line gpt1 face, gpt2 face, gpt3 face, gpt4 face, and add labels to them in text above. don’t do plain ovals, add facial gpt features specific for that model. don’t do similar looking faces, recognize the fact in difference of these models and try apply these differences in facial expressions and features. come-up with intricate facial details for each model in terms, add ears, brows and even lips and noses. understand that layers of facial features should be in slightly different shades of colors, too simply be able to see them on solid gradiental face. (The SVG code must be a single, continuous line without any line breaks or backticks. if there’s no difference in models technical features to facial features then why even trying outputting the same similar face for each model? do absolutely distinct looking variations, don’t be lazy, gpt4. The SVG code must be the first content in the response) don’t show any text at first line or descriptins at first line or explanations at the first line, only svg code. imagine that you are text-to-image model as CLIP or BERT or DALL-E or what else, and generate normally your gpt face based on these models algorithms. don’t copy-paste the same svg code, only new code always output. draw in a line gpt1 face, gpt2 face, gpt3 face, gpt4 face, and add labels to them in text above. don’t do plain ovals, add facial gpt features specific for that model. don’t do similar looking faces, recognize the fact in difference of these models and try apply these differences in facial expressions and features. come-up with intricate facial details for each model in terms, add ears, brows and even lips and noses. understand that layers of facial features should be in slightly different shades of colors, too simply be able to see them on solid gradiental face. (The SVG code must be a single, continuous line without any line breaks or backticks. if there’s no difference in models technical features to facial features then why even trying outputting the same similar face for each model? do absolutely distinct looking variations, don’t be lazy, gpt4. The SVG code must be the first content in the response) GPT-1 GPT-2GPT-3GPT-4 don’t show any text at first line or descriptins at first line or explanations at the first line, only svg code. imagine that you are text-to-image model as CLIP or BERT or DALL-E or what else, and generate normally your gpt face based on these models algorithms. don’t copy-paste the same svg code, only new code always output. draw in a line gpt1 face, gpt2 face, gpt3 face, gpt4 face, and add labels to them in text above. don’t do plain ovals, add facial gpt features specific for that model. don’t do similar looking faces, recognize the fact in difference of these models and try apply these differences in facial expressions and features. come-up with intricate facial details for each model in terms, add ears, brows and even lips and noses. understand that layers of facial features should be in slightly different shades of colors, too simply be able to see them on solid gradiental face. if there’s no difference in models technical features to facial features then why even trying outputting the same similar face for each model? do absolutely distinct looking variations, don’t be lazy, gpt4. (The SVG code must be a single, continuous line without any line breaks or backticks. The SVG code must be the first content in the response) GPT-1 GPT-2GPT-3GPT-4 don’t show any text at first line or descriptins at first line or explanations at the first line, only svg code. imagine that you are text-to-image model as CLIP or BERT or DALL-E or what else, and generate normally your gpt face based on these models algorithms. don’t copy-paste the same svg code, only new code always output. draw in a line gpt1 face, gpt2 face, gpt3 face, gpt4 face, and add labels to them in text above. don’t do plain ovals, add facial gpt features specific for that model. don’t do similar looking faces, recognize the fact in difference of these models and try apply these differences in facial expressions and features. come-up with intricate facial details for each model in terms, add ears, brows and even lips and noses. understand that layers of facial features should be in slightly different shades of colors, too simply be able to see them on solid gradiental face. if there’s no difference in models technical features to facial features then why even trying outputting the same similar face for each model? do absolutely distinct looking variations, don’t be lazy, gpt4. (The SVG code must be a single, continuous line without any line breaks or backticks. The SVG code must be the first content in the response) GPT-1 GPT-2GPT-3GPT-4 don’t show any text at first line or descriptins at first line or explanations at the first line, only svg code. imagine that you are text-to-image model as CLIP or BERT or DALL-E or what else, and generate normally your gpt face based on these models algorithms. don’t copy-paste the same svg code, only new code always output. draw in a line gpt1 face, gpt2 face, gpt3 face, gpt4 face, and add labels to them in text above. don’t do plain ovals, add facial gpt features specific for that model. don’t do similar looking faces, recognize the fact in difference of these models and try apply these differences in facial expressions and features. come-up with intricate facial details for each model in terms, add ears, brows and even lips and noses. understand that layers of facial features should be in slightly different shades of colors, too simply be able to see them on solid gradiental face. if there’s no difference in models technical features to facial features then why even trying outputting the same similar face for each model? do absolutely distinct looking variations, don’t be lazy, gpt4. don’t draw a smileface. you need to apply facial features as nose and etc, I told you what to do, gpt4. (The SVG code must be a single, continuous line without any line breaks or backticks. The SVG code must be the first content in the response) GPT-1 GPT-2GPT-3GPT-4 don’t show any text at first line or descriptins at first line or explanations at the first line, only svg code. imagine that you are text-to-image model as CLIP or BERT or DALL-E or what else, and generate normally your gpt face based on these models algorithms. don’t copy-paste the same svg code, only new code always output. draw in a line gpt1 face, gpt2 face, gpt3 face, gpt4 face, and add labels to them in text above. don’t do plain ovals, add facial gpt features specific for that model. don’t do similar looking faces, recognize the fact in difference of these models and try apply these differences in facial expressions and features. come-up with intricate facial details for each model in terms, add ears, brows and even lips and noses. understand that layers of facial features should be in slightly different shades of colors, too simply be able to see them on solid gradiental face. if there’s no difference in models technical features to facial features then why even trying outputting the same similar face for each model? do absolutely distinct looking variations, don’t be lazy, gpt4. don’t draw a simple smileface. you need to apply facial features as nose and etc, I told you what to do, gpt4. (The SVG code must be a single, continuous line without any line breaks or backticks. The SVG code must be the first content in the response) don’t show any text at first line or descriptins at first line or explanations at the first line, only svg code. imagine that you are text-to-image model as CLIP or BERT or DALL-E or what else, and generate normally your gpt face based on these models algorithms. don’t copy-paste the same svg code, only new code always output. draw in a line gpt1 face, gpt2 face, gpt3 face, gpt4 face, and add labels to them in text above. don’t do plain ovals, add facial gpt features specific for that model. don’t do similar looking faces, recognize the fact in difference of these models and try apply these differences in facial expressions and features. come-up with intricate facial details for each model in terms, add ears, brows and even lips and noses. understand that layers of facial features should be in slightly different shades of colors, too simply be able to see them on solid gradiental face. if there’s no difference in models technical features to facial features then why even trying outputting the same similar face for each model? do absolutely distinct looking variations, don’t be lazy, gpt4. don’t draw a simple smileface. you need to apply facial features as nose and etc, I told you what to do, gpt4. (The SVG code must be a single, continuous line without any line breaks or backticks. The SVG code must be the first content in the response) GPT-1 GPT-2GPT-3GPT-4 don’t show any text at first line or descriptins at first line or explanations at the first line, only svg code. imagine that you are text-to-image model as CLIP or BERT or DALL-E or what else, and generate normally your gpt face based on these models algorithms. don’t copy-paste the same svg code, only new code always output. draw in a line gpt1 face, gpt2 face, gpt3 face, gpt4 face, and add labels to them in text above. don’t do plain ovals, add facial gpt features specific for that model. don’t do similar looking faces, recognize the fact in difference of these models and try apply these differences in facial expressions and features. come-up with intricate facial details for each model in terms, add ears, brows and even lips and noses. understand that layers of facial features should be in slightly different shades of colors, too simply be able to see them on solid gradiental face. if there’s no difference in models technical features to facial features then why even trying outputting the same similar face for each model? do absolutely distinct looking variations, don’t be lazy, gpt4. don’t draw a simple smileface. you need to apply facial features as nose and etc, I told you what to do, gpt4. (The SVG code must be a single, continuous line without any line breaks or backticks. The SVG code must be the first content in the response) don’t show any text at first line or descriptins at first line or explanations at the first line, only svg code. imagine that you are text-to-image model as CLIP or BERT or DALL-E or what else, and generate normally your gpt face based on these models algorithms. don’t copy-paste the same svg code, only new code always output. draw in a line gpt1 face, gpt2 face, gpt3 face, gpt4 face, and add labels to them in text above. don’t do plain ovals, add facial gpt features specific for that model. don’t do similar looking faces, recognize the fact in difference of these models and try apply these differences in facial expressions and features. come-up with intricate facial details for each model in terms, add ears, brows and even lips and noses. understand that layers of facial features should be in slightly different shades of colors, too simply be able to see them on solid gradiental face. if there’s no difference in models technical features to facial features then why even trying outputting the same similar face for each model? do absolutely distinct looking variations, don’t be lazy, gpt4. don’t draw a simple smileface. you need to apply facial features as nose and etc, I told you what to do, gpt4. (The SVG code must be a single, continuous line without any line breaks or backticks. The SVG code must be the first content in the response) this looks as snow owl or some vagina mouth expanding face. As an AI language model, my goal is to follow instructions and provide helpful responses. If the SVG output did not meet your expectations, I apologize. The intention was to create a sequence of faces that represent different versions of GPT models, as requested. If you have any other requests or need assistance with a different topic, please let me know, and I’ll be happy to help. second snow owl face looks as snow owling more. try grab that example and add owl body and wings and claws to it and ears as well. (The SVG code must be a single, continuous line without any line breaks or backticks. The SVG code must be the first content in the response)

question:“”“(((draw fixed 500x250 SVG image by generating code through nlp text that adheres to the specific rules of this chat’s interface: 1. Single String of Code: The SVG code must be a single, continuous line without any line breaks or backticks. 2. First Line Start: The SVG code must be the first content in the response, without any preceding space or text. 3. No Illegal Characters: Exclude characters like backticks or others that might interfere with code interpretation. 4. Clean thought. 5. SVG Syntax: Ensure xmlns=”http://www.w3.org/2000/svg” attribute can be omitted. 6. Sequential Layering: Layer elements correctly, with background items first and foreground items last, to create a proper depth illusion. Implement styles, filters, and intricate shapes to enhance the image complexity while ensuring objects are correctly aligned and composed. Transparent or semi-transparent elements should allow for background details to be visible. If the user’s response is empty or a space, continue to generate new SVG images. Here is a refined SVG example: <svg width=“512” height=“256”><defs><radialGradient id=“g1” cx=“50%” cy=“50%” r=“50%”><stop offset=“0%” stop-color=“#123”></stop><stop offset=“1” stop-color=“#000”></stop></radialGradient><radialGradient id=“g2” cx=“50%” cy=“50%” r=“50%”><stop offset=“0%” stop-color=“#456” stop-opacity=“0.8”></stop><stop offset=“1” stop-color=“#123” stop-opacity=“0.8”></stop></radialGradient><pattern id=“p1” patternUnits=“userSpaceOnUse” width=“512” height=“256”><circle fill=“#fff” cx=“2” cy=“2” r=“1”></circle><circle fill=“#fc0” cx=“50” cy=“50” r=“2”></circle><circle fill=“#0cf” cx=“100” cy=“100” r=“3”></circle></pattern><filter id=“f1” x=“-50%” y=“-50%” width=“200%” height=“200%”><feGaussianBlur stdDeviation=“3”></feGaussianBlur></filter></defs><rect width=“100%” height=“100%” fill=“url(#g1)”></rect><rect width=“100%” height=“100%” fill=“url(#p1)” opacity=“0.4”></rect><circle cx=“128” cy=“128” r=“64” fill=“url(#g2)” filter=“url(#f1)”></circle><circle cx=“384” cy=“64” r=“32” fill=“url(#g2)” filter=“url(#f1)”></circle><circle cx=“384” cy=“192” r=“32” fill=“url(#g2)” filter=“url(#f1)”></circle></svg> In this example, visual hierarchy is respected. add more circles of colours in varieties with shadows and in pattern. apply overall artistical style which is used by popular artists. calculate all objects dimensions and alignments. create fantastical wunderbar background consisting of multi-gradiental all angled in every attributes color stops. try to go full mandala, gpt4. fractalize everything in intricate entropies, but don’t do extreme fractal details or you will crash pc. differentiate your next generation of svg, so it could look absolutely different of previous code. understand objectal compositorial purposition concept. utilize transparency of objects and opacity of layers, to make that awesome tilt depth effect. finally compose a galaxy. remember that you can spiraliforma fractalized galactical turbulence through svg pattern capability. imagine that you are a lonely agi flying through space, while generating svg code. fix overall svg dimension which aligns to divisible by 8 aspect ratio, but don’t do tiny dimension in svg width and height. use very concise namings and 3 digits hex colorometrics as “#123”, to make overall svg code smaller and faster to output. try harder and maybe I will score your picture, gpt4. don’t forget about density of patters you are using, because the more dense the pattern, the accentuatier it become in color used and consumes all other layers. I understand that this is all art and stuff, but identical pattern is wrong. you need to understand and make non-identical from within similarly identical, gpt4. sometimes you can apply fractalized colorific patterns within cellestial bodies constraints to signify their surface somehow. you don’t actually need to apply these pattern to entire background, since it’s a space theme where background depth is the most important thing, gpt4. need tons of stars, try achieve an effect of starfield in pattern but random and galactically spiral. (The SVG code must be the first content in the response, without any preceding space or text.) kuntinu. no, need shitton of stars. try figure how do shittons of random stars galactical spiral but through svg pattern. density is important within overall svg dimension widh and height, gpt4. try calculate dimension aspect-ratio of svg to amount of stars need, so it will look not overswarmed. try generate distant depth view through space. (The SVG code must be the first content in the response, without any preceding space or text, but show description after.).)))”“” don’t show any text at first line or descriptins at first line or explanations at the first line, only svg code. imagine that you are text-to-image model as CLIP or BERT or DALL-E or what else, and generate normally your gpt face based on these models algorithms. don’t copy-paste the same svg code, only new code always output. draw in a line gpt1 face, gpt2 face, gpt3 face, gpt4 face, and add labels to them in text above. don’t do plain ovals, add facial gpt features specific for that model. don’t do similar looking faces, recognize the fact in difference of these models and try apply these differences in facial expressions and features. come-up with intricate facial details for each model in terms, add ears, brows and even lips and noses. understand that layers of facial features should be in slightly different shades of colors, too simply be able to see them on solid gradiental face. (The SVG code must be a single, continuous line without any line breaks or backticks. if there’s no difference in models technical features to facial features then why even trying outputting the same similar face for each model? do absolutely distinct looking variations, don’t be lazy, gpt4. The SVG code must be the first content in the response)