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The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 1 missing columns ({'human_rewrite_request'})
This happened while the json dataset builder was generating data using
hf://datasets/zixianma/mnms/test_human_verified.json (at revision e9cb0112a0a88788fc7559e27cdf40646f30ad3f)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2013, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
id: int64
user_request: string
plan_str: string
code_str: string
alt_plans_str: string
to
{'id': Value(dtype='int64', id=None), 'user_request': Value(dtype='string', id=None), 'plan_str': Value(dtype='string', id=None), 'code_str': Value(dtype='string', id=None), 'alt_plans_str': Value(dtype='string', id=None), 'human_rewrite_request': Value(dtype='string', id=None)}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1396, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1045, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1029, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1124, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1884, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2015, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 1 missing columns ({'human_rewrite_request'})
This happened while the json dataset builder was generating data using
hf://datasets/zixianma/mnms/test_human_verified.json (at revision e9cb0112a0a88788fc7559e27cdf40646f30ad3f)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
id
int64 | user_request
string | plan_str
string | code_str
string | alt_plans_str
string | human_rewrite_request
string |
|---|---|---|---|---|---|
10 | "I have a review here which says, 'forced, familiar and thoroughly condescending.' I need to understand if this sentiment is positive or negative to shape my response accordingly." | [{'id': 0, 'name': 'text classification', 'args': {'text': 'forced , familiar and thoroughly condescending . '}}] | def solve():
output0 = text_classification(text="forced , familiar and thoroughly condescending . ")
result = {0: output0}
return result | [[{'id': 0, 'name': 'question answering', 'args': {'text': 'forced , familiar and thoroughly condescending . ', 'question': 'Is the text negative, neutral or positive?'}}], [{'id': 0, 'name': 'text generation', 'args': {'text': 'forced , familiar and thoroughly condescending . '}}]] | Can you tell me the general sentiment of this phrase: "forced , familiar and thoroughly condescending . " |
14 | "I've got this review for a movie: 'it is amusing , and that 's all it needs to be . '. Could you analyze this review and let me know if the movie sentiment is positive or negative?" | [{'id': 0, 'name': 'text classification', 'args': {'text': "it is amusing , and that 's all it needs to be . "}}] | def solve():
output0 = text_classification(text="it is amusing , and that 's all it needs to be . ")
result = {0: output0}
return result | [[{'id': 0, 'name': 'question answering', 'args': {'text': "it is amusing , and that 's all it needs to be . ", 'question': 'Is the text negative, neutral or positive?'}}], [{'id': 0, 'name': 'text generation', 'args': {'text': "it is amusing , and that 's all it needs to be . "}}]] | What is the overall sentiment of this sentence: "it is amusing , and that 's all it needs to be . " |
18 | "I have a piece of text saying 'just embarrassment and a vague sense of shame.' Could you analyze the sentiment of this statement and classify it into categories like 'positive', 'negative' or 'neutral'?" | [{'id': 0, 'name': 'text classification', 'args': {'text': 'just embarrassment and a vague sense of shame . '}}] | def solve():
output0 = text_classification(text="just embarrassment and a vague sense of shame . ")
result = {0: output0}
return result | [[{'id': 0, 'name': 'question answering', 'args': {'text': 'just embarrassment and a vague sense of shame . ', 'question': 'Is the text negative, neutral or positive?'}}], [{'id': 0, 'name': 'text generation', 'args': {'text': 'just embarrassment and a vague sense of shame . '}}]] | Tell me the sentiment of this sentence: "just embarrassment and a vague sense of shame . " |
21 | "I'm writing a report on pioneers in the field of geology and I've come across some information. Based on the text 'James Hutton is often viewed as the first modern geologist. In 1785 he presented a paper entitled Theory of the Earth to the Royal Society of Edinburgh. In his paper, he explained his theory that the Earth must be much older than had previously been supposed in order to allow enough time for mountains to be eroded and for sediments to form new rocks at the bottom of the sea, which in turn were raised up to become dry land. Hutton published a two-volume version of his ideas in 1795 (Vol. 1, Vol. 2)', could you help me find out who the first modern geologist is?" | [{'id': 0, 'name': 'question answering', 'args': {'text': 'James Hutton is often viewed as the first modern geologist. In 1785 he presented a paper entitled Theory of the Earth to the Royal Society of Edinburgh. In his paper, he explained his theory that the Earth must be much older than had previously been supposed in order to allow enough time for mountains to be eroded and for sediments to form new rocks at the bottom of the sea, which in turn were raised up to become dry land. Hutton published a two-volume version of his ideas in 1795 (Vol. 1, Vol. 2).', 'question': 'Who is viewed as the first modern geologist?'}}] | def solve():
output0 = question_answering(text="James Hutton is often viewed as the first modern geologist. In 1785 he presented a paper entitled Theory of the Earth to the Royal Society of Edinburgh. In his paper, he explained his theory that the Earth must be much older than had previously been supposed in order to allow enough time for mountains to be eroded and for sediments to form new rocks at the bottom of the sea, which in turn were raised up to become dry land. Hutton published a two-volume version of his ideas in 1795 (Vol. 1, Vol. 2).", question="Who is viewed as the first modern geologist?")
result = {0: output0}
return result | [] | Based on this paragraph: "James Hutton is often viewed as the first modern geologist. In 1785 he presented a paper entitled Theory of the Earth to the Royal Society of Edinburgh. In his paper, he explained his theory that the Earth must be much older than had previously been supposed in order to allow enough time for mountains to be eroded and for sediments to form new rocks at the bottom of the sea, which in turn were raised up to become dry land. Hutton published a two-volume version of his ideas in 1795 (Vol. 1, Vol. 2)." Tell me who is viewed as the first modern geologist?
|
24 | "I was reading up on the history of the Canary Islands and learned that Bethencourt claimed the title of King of the Canary Islands, subject to Henry III of Castile. In 1418, his relative Maciot de Bethencourt sold the rights to the islands to an individual named Enrique Pérez de Guzmán, who was the 2nd Count de Niebla. Could you verify who exactly became the King of the Canary Islands?" | [{'id': 0, 'name': 'question answering', 'args': {'text': "Bethencourt took the title of King of the Canary Islands, as vassal to Henry III of Castile. In 1418, Jean's nephew Maciot de Bethencourt sold the rights to the islands to Enrique Pérez de Guzmán, 2nd Count de Niebla.", 'question': 'Who became the King of the Canary Islands?'}}] | def solve():
output0 = question_answering(text="Bethencourt took the title of King of the Canary Islands, as vassal to Henry III of Castile. In 1418, Jean's nephew Maciot de Bethencourt sold the rights to the islands to Enrique Pérez de Guzmán, 2nd Count de Niebla.", question="Who became the King of the Canary Islands?")
result = {0: output0}
return result | [] | Based on this paragraph: "Bethencourt took the title of King of the Canary Islands, as vassal to Henry III of Castile. In 1418, Jean's nephew Maciot de Bethencourt sold the rights to the islands to Enrique Pérez de Guzmán, 2nd Count de Niebla.", tell me who became the King of the Canary Islands? |
26 | "I recently read that on 7 January 1900, Tesla left Colorado Springs. His lab was torn down in 1904, and its contents were sold two years later to satisfy a debt. Can you confirm when exactly Tesla left Colorado Springs based on these details?" | [{'id': 0, 'name': 'question answering', 'args': {'text': 'On 7 January 1900, Tesla left Colorado Springs.[citation needed] His lab was torn down in 1904, and its contents were sold two years later to satisfy a debt.', 'question': 'When did Tesla depart from Colorado Springs?'}}] | def solve():
output0 = question_answering(text="On 7 January 1900, Tesla left Colorado Springs.[citation needed] His lab was torn down in 1904, and its contents were sold two years later to satisfy a debt.", question="When did Tesla depart from Colorado Springs?")
result = {0: output0}
return result | [] | Based on: "On 7 January 1900, Tesla left Colorado Springs.[citation needed] His lab was torn down in 1904, and its contents were sold two years later to satisfy a debt.", tell me when did Tesla depart from Colorado Springs? |
28 | "I am currently studying plant biology and came across a passage that mentions different types of chloroplasts and something called a 'plastid.' The passage reads: 'These chloroplasts, which can be traced back directly to a cyanobacterial ancestor, are known as primary plastids ("plastid" in this context means almost the same thing as chloroplast). All primary chloroplasts belong to one of three chloroplast lineages—the glaucophyte chloroplast lineage, the rhodophyte, or red algal chloroplast lineage, or the chloroplastidan, or green chloroplast lineage. The second two are the largest, and the green chloroplast lineage is the one that contains the land plants.' Can you help out and tell me 'What does 'plastid' mean?' based on this passage?" | [{'id': 0, 'name': 'question answering', 'args': {'text': 'These chloroplasts, which can be traced back directly to a cyanobacterial ancestor, are known as primary plastids ("plastid" in this context means almost the same thing as chloroplast). All primary chloroplasts belong to one of three chloroplast lineages—the glaucophyte chloroplast lineage, the rhodophyte, or red algal chloroplast lineage, or the chloroplastidan, or green chloroplast lineage. The second two are the largest, and the green chloroplast lineage is the one that contains the land plants.', 'question': "What does 'plastid' mean?"}}] | def solve():
output0 = question_answering(text="These chloroplasts, which can be traced back directly to a cyanobacterial ancestor, are known as primary plastids ('plastid' in this context means almost the same thing as chloroplast). All primary chloroplasts belong to one of three chloroplast lineages—the glaucophyte chloroplast lineage, the rhodophyte, or red algal chloroplast lineage, or the chloroplastidan, or green chloroplast lineage. The second two are the largest, and the green chloroplast lineage is the one that contains the land plants.", question="What does 'plastid' mean?")
result = {0: output0}
return result | [] | Read this paragraph: "These chloroplasts, which can be traced back directly to a cyanobacterial ancestor, are known as primary plastids ("plastid" in this context means almost the same thing as chloroplast). All primary chloroplasts belong to one of three chloroplast lineages—the glaucophyte chloroplast lineage, the rhodophyte, or red algal chloroplast lineage, or the chloroplastidan, or green chloroplast lineage. The second two are the largest, and the green chloroplast lineage is the one that contains the land plants.", tell me what does 'plastid' mean? |
31 | "I'm writing a novel and am trying to paint a detailed picture of the scene for my audience. Can you provide an image of a room with a table, chair, a TV monitor and a stand? This will help me deliver a better immersive experience for my readers." | [{'id': 0, 'name': 'image generation', 'args': {'text': 'an immersive image of a room with a table, chair, a TV monitor and a stand to help create a detailed scene'}}] | def solve():
output0 = image_generation(text="an immersive image of a room with a table, chair, a TV monitor and a stand to help create a detailed scene")
result = {0: output0}
return result | [] | I want a image of "an immersive image of a room with a table, chair, a TV monitor and a stand to help create a detailed scene". |
32 | "I'm working on a project about aviation and I need a unique depiction. Could you generate an illustration based on the description 'A silver jet is flying high in the sky above the clouds' and send it to me?" | [{'id': 0, 'name': 'image generation', 'args': {'text': 'a unique illustration of a silver jet flying high in the sky above the clouds'}}] | def solve():
output0 = image_generation(text="a unique illustration of a silver jet flying high in the sky above the clouds")
result = {0: output0}
return result | [] | Could you provide me an image of "a unique illustration of a silver jet flying high in the sky above the clouds" |
34 | I'm trying to visualize a scene for my upcoming book. Could you show me what 'A girl in a brown jacket staring at a whole pizza' would look like? | [{'id': 0, 'name': 'image generation', 'args': {'text': 'an image visualizing a scene of a girl in a brown jacket staring at a whole pizza.'}}] | def solve():
output0 = image_generation(text="an image visualizing a scene of a girl in a brown jacket staring at a whole pizza.")
result = {0: output0}
return result | [] | Could you give me an image visualizing a scene of a girl in a brown jacket staring at a whole pizza. |
47 | "For the photo titled 2349496.jpg, generate a descriptive text summary." | [{'id': 0, 'name': 'image captioning', 'args': {'image': '2349496.jpg'}}] | def solve():
output0 = image_captioning(image="2349496.jpg")
result = {0: output0}
return result | [[{'id': 0, 'name': 'visual question answering', 'args': {'image': '2349496.jpg', 'question': 'What is in the image?'}}]] | Could you tell me the content of "2349496.jpg"? |
48 | "Can you help me describe the scenario presented in image 2377004.jpg? I want to use this explanation for my blog post covering the annual zombie march." | [{'id': 0, 'name': 'image captioning', 'args': {'image': '2377004.jpg'}}] | def solve():
output0 = image_captioning(image="2377004.jpg")
result = {0: output0}
return result | [[{'id': 0, 'name': 'visual question answering', 'args': {'image': '2377004.jpg', 'question': 'What is in the image?'}}]] | Could you tell me the content of "2377004.jpg"? |
50 | "Could you identify and extract the graffiti text from the image 'COCO_train2014_000000028742.jpg'? I would appreciate it if you could directly translate the words written there." | [{'id': 0, 'name': 'optical character recognition', 'args': {'image': 'COCO_train2014_000000028742.jpg'}}] | def solve():
output0 = optical_character_recognition(image="COCO_train2014_000000028742.jpg")
result = {0: output0}
return result | [[{'id': 0, 'name': 'visual question answering', 'args': {'image': 'COCO_train2014_000000028742.jpg', 'question': 'What are the characters in this image if any?'}}]] | What are the texts in "COCO_train2014_000000028742.jpg"? |
56 | "I have an image COCO_train2014_000000256855.jpg. The image seems to have some text on it. Could you help me find out what the text says?" | [{'id': 0, 'name': 'optical character recognition', 'args': {'image': 'COCO_train2014_000000256855.jpg'}}] | def solve():
output0 = optical_character_recognition(image="COCO_train2014_000000256855.jpg")
result = {0: output0}
return result | [[{'id': 0, 'name': 'visual question answering', 'args': {'image': 'COCO_train2014_000000256855.jpg', 'question': 'What are the characters in this image if any?'}}]] | What are the texts in "COCO_train2014_000000256855.jpg"? |
59 | "I'd like to know the description of the text in the COCO_train2014_000000134502.jpg?" | [{'id': 0, 'name': 'optical character recognition', 'args': {'image': 'COCO_train2014_000000134502.jpg'}}] | def solve():
output0 = optical_character_recognition(image="COCO_train2014_000000134502.jpg")
result = {0: output0}
return result | [[{'id': 0, 'name': 'visual question answering', 'args': {'image': 'COCO_train2014_000000134502.jpg', 'question': 'What are the characters in this image if any?'}}]] | What are the texts in "COCO_train2014_000000134502.jpg"? |
66 | "Could you analyze '16148.jpg' and provide me with a description of the object or animal that is present in the photograph? I'm sorting my photo collection and it would be of great help to know what's in this particular image." | [{'id': 0, 'name': 'image classification', 'args': {'image': '16148.jpg'}}] | def solve():
output0 = image_classification(image="16148.jpg")
result = {0: output0}
return result | [[{'id': 0, 'name': 'object detection', 'args': {'image': '16148.jpg'}}], [{'id': 0, 'name': 'visual question answering', 'args': {'image': '16148.jpg', 'question': 'What is the main subject in the image?'}}], [{'id': 0, 'name': 'image captioning', 'args': {'image': '16148.jpg'}}]] | What is the category of the object in "16148.jpg"? |
71 | "Currently, I'm working on an image named '15653-input.png' which requires a tweak. Specifically, I need to place a bottle behind the vegetables in the picture. Could you help me generate this visual alteration?" | [{'id': 0, 'name': 'image editing', 'args': {'image': '15653-input.png', 'prompt': 'Have there be a bottle behind the vegetables'}}] | def solve():
output0 = image_editing(image="15653-input.png", prompt="Have there be a bottle behind the vegetables")
result = {0: output0}
return result | [] | For 15653-input.png, could you have there be a bottle behind the vegetables? |
72 | "I have an image that I need revised for an upcoming healthy living campaign. The image file is 510027-input.png and it contains different types of vegetables. Could you transform all these vegetables in the image into broccoli? It's for the theme of our campaign 'Benefits of Broccoli'." | [{'id': 0, 'name': 'image editing', 'args': {'image': '510027-input.png', 'prompt': 'change the vegetables into broccoli'}}] | def solve():
output0 = image_editing(image="510027-input.png", prompt="change the vegetables into broccoli")
result = {0: output0}
return result | [] | For 510027-input.png, could you change the vegetables into broccoli? |
74 | "I have this room scene photo, 319096-input.png, and I wanted to test out what it would look like with a mirror on the wall instead of the piece of paper. Can you show me what my room would look like if the paper is replaced by a mirror?" | [{'id': 0, 'name': 'image editing', 'args': {'image': '319096-input.png', 'prompt': 'Make the piece of paper hanging on the wall a mirror'}}] | def solve():
output0 = image_editing(image="319096-input.png", prompt="Make the piece of paper hanging on the wall a mirror")
result = {0: output0}
return result | [] | For 319096-input.png, could you make the piece of paper hanging on the wall a mirror? |
77 | "I'm using the picture called '357903-input.png' for my restaurant's website. The image has too many pizzas in it, and I want you to create a version where one of the pizzas has been removed." | [{'id': 0, 'name': 'image editing', 'args': {'image': '357903-input.png', 'prompt': 'Remove one of the pizzas.'}}] | def solve():
output0 = image_editing(image="357903-input.png", prompt="Remove one of the pizzas.")
result = {0: output0}
return result | [] | For 357903-input.png, could you remove one of the pizzas? |
80 | "I need to identify and categorize different elements in the image 2366358.jpg. Can we systematically outline all distinct objects present in the scene?" | [{'id': 0, 'name': 'object detection', 'args': {'image': '2366358.jpg'}}] | def solve():
output0 = object_detection(image="2366358.jpg")
result = {0: output0}
return result | [[{'id': 0, 'name': 'image segmentation', 'args': {'image': '2366358.jpg'}}]] | I wanna know the objects in the image 2366358.jpg and have the bounding boxes of them. |
82 | "Could you analyze the image 1592452.jpg and let me know which different objects are contained within it? I am trying to identify key elements in this night time cityscape." | [{'id': 0, 'name': 'object detection', 'args': {'image': '1592452.jpg'}}] | def solve():
output0 = object_detection(image="1592452.jpg")
result = {0: output0}
return result | [[{'id': 0, 'name': 'image segmentation', 'args': {'image': '1592452.jpg'}}]] | I wanna know the objects in the image 1592452.jpg and have the bounding boxes of them. |
90 | "I have an image 2374973.jpg, and I'd like to identify and separate the diverse components in the image like the different cars, the road, the exit signs and so on. Can I have individual masks for each section of the image?" | [{'id': 0, 'name': 'image segmentation', 'args': {'image': '2374973.jpg'}}] | def solve():
output0 = image_segmentation(image="2374973.jpg")
result = {0: output0}
return result | [] | I wanna get the segmentation masks of each components in the image 2374973.jpg. |
92 | "Can you help distinguish all the key elements in the picture 2401635.jpg? I specifically need to understand the different components and their shapes in the image, such as the bed, the sheets, the pillows, and the lamp." | [{'id': 0, 'name': 'image segmentation', 'args': {'image': '2401635.jpg'}}] | def solve():
output0 = image_segmentation(image="2401635.jpg")
result = {0: output0}
return result | [] | I wanna get the segmentation masks of each components in the image 2401635.jpg. |
94 | "I have an image 2385634.jpg. Could you help me analyze the different components of this scene for my blog on waste management? It would be great if I could visually separate the oven from the rest of the image to demonstrate how much space it occupies." | [{'id': 0, 'name': 'image segmentation', 'args': {'image': '2385634.jpg'}}] | def solve():
output0 = image_segmentation(image="2385634.jpg")
result = {0: output0}
return result | [] | I wanna get the segmentation masks of each components in the image 2385634.jpg. |
102 | "I have an audio file named '1284-1180-0003.flac'. Can you help me convert this content into written words so that I can analyze it better?" | [{'id': 0, 'name': 'automatic speech recognition', 'args': {'audio': '1284-1180-0003.flac'}}] | def solve():
output0 = automatic_speech_recognition(audio="1284-1180-0003.flac")
result = {0: output0}
return result | [] | I wanna know the content in the audio: 1284-1180-0003.flac. |
106 | "I have this audio file named '237-134500-0000.flac'. Can you provide a transcription for this audio?" | [{'id': 0, 'name': 'automatic speech recognition', 'args': {'audio': '237-134500-0000.flac'}}] | def solve():
output0 = automatic_speech_recognition(audio="237-134500-0000.flac")
result = {0: output0}
return result | [] | I wanna know the content in the audio: 237-134500-0000.flac. |
113 | "I'm writing a detailed descriptive narrative for a storytelling project. I'm using various images for inspiration and I've come upon picture 2346651.jpg featuring a person standing in a forest with his cell phone. Could you identify what this individual is wearing for me?" | [{'id': 0, 'name': 'visual question answering', 'args': {'image': '2346651.jpg', 'question': 'He is wearing what?'}}] | def solve():
output0 = visual_question_answering(image="2346651.jpg", question="He is wearing what?")
result = {0: output0}
return result | [] | There is a man in the image 2346651.jpg, he is wearing what? |
114 | "I have an image 2345745.jpg, where a family is having lunch in their backyard in the rain. Could you help me identify who is holding the umbrella in the top part of the photo?" | [{'id': 0, 'name': 'visual question answering', 'args': {'image': '2345745.jpg', 'question': 'Who holds the umbrella in the top part of the photo?'}}] | def solve():
output0 = visual_question_answering(image="2345745.jpg", question="Who holds the umbrella in the top part of the photo?")
result = {0: output0}
return result | [] | In the image 2345745.jpg, who holds the umbrella in the top part of the photo? |
120 | "I have always been curious about the significance of July 11 in history. Could you tell me some interesting historical facts or events that happened on this date?" | [{'id': 0, 'name': 'get date fact', 'args': {'date': '11-Jul'}}] | def solve():
output0 = get_date_fact(date="11-Jul")
result = {0: output0}
return result | [] | Tell me a fact about 11-July. |
122 | "I'm planning a trivia night for 24th of November. Could you find me some interesting historical facts or events that happened on this day that I could use for my questions?" | [{'id': 0, 'name': 'get date fact', 'args': {'date': '24-Nov'}}] | def solve():
output0 = get_date_fact(date="24-Nov")
result = {0: output0}
return result | [] | Tell me a fact about 24-Nov. |
124 | "I need to prepare a presentation for my class about the historical significance of October 19. Could you find out some interesting and unique events that happened on this date?" | [{'id': 0, 'name': 'get date fact', 'args': {'date': '19-Oct'}}] | def solve():
output0 = get_date_fact(date="19-Oct")
result = {0: output0}
return result | [] | Tell me a fact about 19-Oct. |
126 | "I'm planning a trivia night for a friend's birthday on 7th May. Can you find some unique historical event or fact that happened on this day that I can use in the trivia?" | [{'id': 0, 'name': 'get date fact', 'args': {'date': '7-May'}}] | def solve():
output0 = get_date_fact(date="7-May")
result = {0: output0}
return result | [] | Tell me a fact about 7-May. |
129 | "Can you tell me any unique trivia or fact associated with the date 24th-August? I am a content creator and I am thinking of creating a post themed around 'Fact of the Day' for my followers." | [{'id': 0, 'name': 'get date fact', 'args': {'date': '24-Aug'}}] | def solve():
output0 = get_date_fact(date="24-Aug")
result = {0: output0}
return result | [] | Tell me a fact about 24-Aug. |
130 | "I need a fun tidbit about 2019 for a trivia game I'm hosting tonight. Can you find an interesting fact related to that year for me?" | [{'id': 0, 'name': 'get year fact', 'args': {'year': '2019'}}] | def solve():
output0 = get_year_fact(year="2019")
result = {0: output0}
return result | [] | Tell me a fact happend in 2019. |
132 | "I heard various stories about 2017, but could you find an interesting and specific fact about the year 2017?" | [{'id': 0, 'name': 'get year fact', 'args': {'year': '2017'}}] | def solve():
output0 = get_year_fact(year="2017")
result = {0: output0}
return result | [] | Tell me a fact happend in 2017. |
134 | "Can you tell me an interesting fact about the year 2014?" | [{'id': 0, 'name': 'get year fact', 'args': {'year': '2014'}}] | def solve():
output0 = get_year_fact(year="2014")
result = {0: output0}
return result | [] | Tell me a fact happend in 2014. |
136 | "I'm preparing for a 2023-themed trivia night. Can you find any interesting or notable facts about the year 2023 to feature in the game?" | [{'id': 0, 'name': 'get year fact', 'args': {'year': '2023'}}] | def solve():
output0 = get_year_fact(year="2023")
result = {0: output0}
return result | [] | Tell me a fact happend in 2023. |
138 | "Could you please find me any intriguing event or factoid that occurred in the year 2022?" | [{'id': 0, 'name': 'get year fact', 'args': {'year': '2022'}}] | def solve():
output0 = get_year_fact(year="2022")
result = {0: output0}
return result | [] | Tell me a fact happend in 2022. |
140 | "Can you tell me an interesting fact about the number 9? I want to surprise my children with it as they are learning about it." | [{'id': 0, 'name': 'get math fact', 'args': {'number': '9'}}] | def solve():
output0 = get_math_fact(number="9")
result = {0: output0}
return result | [] | Tell me a fact about number 9. |
142 | "I'm preparing a math lesson for my second graders who are learning number facts. Can you provide me with an interesting fact about the number 6 to make the lesson more engaging?" | [{'id': 0, 'name': 'get math fact', 'args': {'number': '6'}}] | def solve():
output0 = get_math_fact(number="6")
result = {0: output0}
return result | [] | Tell me a fact about number 6. |
144 | "I'm preparing a lesson for my elementary students about the number 0. Can you help me come up with interesting mathematical facts about the number 0 to make the lesson more engaging for them?" | [{'id': 0, 'name': 'get math fact', 'args': {'number': '0'}}] | def solve():
output0 = get_math_fact(number="0")
result = {0: output0}
return result | [] | Tell me a fact about number 0. |
146 | "Can you tell me an interesting fact about the number 2? I've been teaching my kid basic mathematics and want to make learning more fun." | [{'id': 0, 'name': 'get math fact', 'args': {'number': '2'}}] | def solve():
output0 = get_math_fact(number="2")
result = {0: output0}
return result | [] | Tell me a fact about number 2. |
148 | "Can you tell me an interesting fact about the number 4 that I can share with my students in our math class tomorrow?" | [{'id': 0, 'name': 'get math fact', 'args': {'number': '4'}}] | def solve():
output0 = get_math_fact(number="4")
result = {0: output0}
return result | [] | Tell me a fact about number 4. |
150 | "I'm preparing for a trivia night and need to impress my friends. Could you provide me with an interesting fact about the number 8?" | [{'id': 0, 'name': 'get trivia fact', 'args': {'number': '8'}}] | def solve():
output0 = get_trivia_fact(number="8")
result = {0: output0}
return result | [] | Tell me a fun fact about 8. |
152 | "Can you tell me an interesting or fun fact about the number 4? I want to include it in my Math Club presentation to add some fun." | [{'id': 0, 'name': 'get trivia fact', 'args': {'number': '4'}}] | def solve():
output0 = get_trivia_fact(number="4")
result = {0: output0}
return result | [] | Tell me a fun fact about 4. |
154 | "I want to impress my friends with my knowledge about numbers. Can you provide me with an interesting fact about the number 6?" | [{'id': 0, 'name': 'get trivia fact', 'args': {'number': '6'}}] | def solve():
output0 = get_trivia_fact(number="6")
result = {0: output0}
return result | [] | Tell me a fun fact about 6. |
156 | "I'm preparing for a quiz night and I'm expected to bring some interesting trivia. Could you find a fascinating fact about the number 2 that I could use?" | [{'id': 0, 'name': 'get trivia fact', 'args': {'number': '2'}}] | def solve():
output0 = get_trivia_fact(number="2")
result = {0: output0}
return result | [] | Tell me a fun fact about 2. |
158 | "Can you provide an interesting fact about the number 7? I'm curious about its significance and any special properties it might have." | [{'id': 0, 'name': 'get trivia fact', 'args': {'number': '7'}}] | def solve():
output0 = get_trivia_fact(number="7")
result = {0: output0}
return result | [] | Tell me a fun fact about 7. |
160 | "Hey, I'm curious to find out the compatibility between William Thacker and Anna Scott. Can you tell me the chances of a successful love relationship between them?" | [{'id': 0, 'name': 'love calculator', 'args': {'first_name': 'William Thacker', 'second_name': 'Anna Scott'}}] | def solve():
output0 = love_calculator(first_name="William Thacker", second_name="Anna Scott")
result = {0: output0}
return result | [] | Could you tell me the love score (from 0-1) of William Thacker and Anna Scott. |
162 | "I am curious about the potential success of a romantic relationship between Will Traynor and Lou Clark, can you check their compatibility for me?" | [{'id': 0, 'name': 'love calculator', 'args': {'first_name': 'Will Traynor', 'second_name': 'Lou Clark'}}] | def solve():
output0 = love_calculator(first_name="Will Traynor", second_name="Lou Clark")
result = {0: output0}
return result | [] | Could you tell me the love score (from 0-1) of Will Traynor and Lou Clark. |
164 | "I'm curious about the compatibility between Fitzwilliam Darcy and Elizabeth Bennet. Can you calculate the probability of a successful romantic relationship between them?" | [{'id': 0, 'name': 'love calculator', 'args': {'first_name': 'Fitzwilliam Darcy', 'second_name': 'Elizabeth Bennet'}}] | def solve():
output0 = love_calculator(first_name="Fitzwilliam Darcy", second_name="Elizabeth Bennet")
result = {0: output0}
return result | [] | Could you tell me the love score (from 0-1) of Fitzwilliam Darcy and Elizabeth Bennet. |
166 | "Rhett Butler is curious about his compatibility with Scarlett O’Hara and wants to know their potential chances for a successful love relationship. Can we see what the outcome might look like?" | [{'id': 0, 'name': 'love calculator', 'args': {'first_name': 'Rhett Butler', 'second_name': 'Scarlett O’Hara'}}] | def solve():
output0 = love_calculator(first_name="Rhett Butler", second_name="Scarlett O’Hara")
result = {0: output0}
return result | [] | Could you tell me the love score (from 0-1) of Rhett Butler and Scarlett O’Hara. |
168 | "I'm wondering how likely a successful relationship would be between Christian Grey and Anastasia Steele. Can you determine their love compatibility for me?" | [{'id': 0, 'name': 'love calculator', 'args': {'first_name': 'Christian Grey', 'second_name': 'Anastasia Steele'}}] | def solve():
output0 = love_calculator(first_name="Christian Grey", second_name="Anastasia Steele")
result = {0: output0}
return result | [] | Could you tell me the love score (from 0-1) of Christian Grey and Anastasia Steele. |
172 | "Can you provide me the geographical coordinates for the city Los Angeles? I'm plotting out a cross-country road trip, and this will be my final destination." | [{'id': 0, 'name': 'get location', 'args': {'city': 'Los Angeles'}}] | def solve():
output0 = get_location(city="Los Angeles")
result = {0: output0}
return result | [] | Could you tell me the geographical coordinates of the city: Los Angeles. |
174 | "I'm planning to set up a delivery service within San Francisco. Can you provide me with the geographical coordinates of the city to calculate the best delivery routes?" | [{'id': 0, 'name': 'get location', 'args': {'city': 'San Francisco'}}] | def solve():
output0 = get_location(city="San Francisco")
result = {0: output0}
return result | [] | Could you tell me the geographical coordinates of the city: San Francisco. |
178 | "I am planning a road trip to Phoenix and I need the geographical coordinates for routing purposes. Can you provide me with the geographical coordinates for Phoenix?" | [{'id': 0, 'name': 'get location', 'args': {'city': 'Phoenix'}}] | def solve():
output0 = get_location(city="Phoenix")
result = {0: output0}
return result | [] | Could you tell me the geographical coordinates of the city: Phoenix. |
180 | "Can you provide me with information about the movie titled 'Green Book' that came out in 2018? I'm interested in finding out its genre and who directed it." | [{'id': 0, 'name': 'search movie', 'args': {'movie_title': 'Green Book', 'movie_year': '2018'}}] | def solve():
output0 = search_movie(movie_title="Green Book", movie_year="2018")
result = {0: output0}
return result | [[{'id': 0, 'name': 'wikipedia simple search', 'args': {'text': 'Green Book'}}]] | Could you find some information for movie: "Green Book" in 2018? |
182 | "I recently watched this amazing movie called 'Moonlight' that was released in 2016. I want to know more about its genre and who directed it. Can you help me find that information?" | [{'id': 0, 'name': 'search movie', 'args': {'movie_title': 'Moonlight', 'movie_year': '2016'}}] | def solve():
output0 = search_movie(movie_title="Moonlight", movie_year="2016")
result = {0: output0}
return result | [[{'id': 0, 'name': 'wikipedia simple search', 'args': {'text': 'Moonlight'}}]] | Could you find some information for movie: "Moonlight" in 2016? |
184 | "I'm trying to find out more about the movie 'Everything Everywhere All at Once' from 2022. Can you please provide me with basic information like its genre, the director and some specific details about it?" | [{'id': 0, 'name': 'search movie', 'args': {'movie_title': 'Everything Everywhere All at Once', 'movie_year': '2022'}}] | def solve():
output0 = search_movie(movie_title="Everything Everywhere All at Once", movie_year="2022")
result = {0: output0}
return result | [[{'id': 0, 'name': 'wikipedia simple search', 'args': {'text': 'Everything Everywhere All at Once'}}]] | Could you find some information for movie: "Everything Everywhere All at Once" in 2022? |
186 | I need to find out more about the movie 'Argo' from 2012; can you help me gather the basic data such as its director and genre? | [{'id': 0, 'name': 'search movie', 'args': {'movie_title': 'Argo', 'movie_year': '2012'}}] | def solve():
output0 = search_movie(movie_title="Argo", movie_year="2012")
result = {0: output0}
return result | [[{'id': 0, 'name': 'wikipedia simple search', 'args': {'text': 'Argo'}}]] | Could you find some information for movie: "Argo" in 2012? |
188 | "Can you find details for the movie 'Nomadland' that was released in 2020? I am interested in knowing the director and the genre of the movie." | [{'id': 0, 'name': 'search movie', 'args': {'movie_title': 'Nomadland', 'movie_year': '2020'}}] | def solve():
output0 = search_movie(movie_title="Nomadland", movie_year="2020")
result = {0: output0}
return result | [[{'id': 0, 'name': 'wikipedia simple search', 'args': {'text': 'Nomadland'}}]] | Could you find some information for movie: "Nomadland" in 2020? |
190 | "Can you tell me the weather forecast for the coordinates 23.03 longitude and 37.73 latitude? I'm planning a hiking trip and need to know if I should prepare for rain." | [{'id': 0, 'name': 'get weather', 'args': {'lon': '23.03', 'lat': '37.73'}}] | def solve():
output0 = get_weather(lon="23.03", lat="37.73")
result = {0: output0}
return result | [] | What is the current weather for the location with coordinates 23.03 longitude and 37.73 latitude? |
192 | "I'll be visiting Cape Town at coordinates 18.41 longitude and 34.02 latitude. Can you help me with the weather forecast so I can pack accordingly?" | [{'id': 0, 'name': 'get weather', 'args': {'lon': '18.41', 'lat': '34.02'}}] | def solve():
output0 = get_weather(lon="18.41", lat="34.02")
result = {0: output0}
return result | [] | What is the current weather for the location with coordinates 18.41 longitude and 34.02 latitude? |
194 | "I'm planning a trip to latitude 29.79 and longitude 95.39. Could you inform me about the expected weather conditions in that region?" | [{'id': 0, 'name': 'get weather', 'args': {'lon': '95.39', 'lat': '29.79'}}] | def solve():
output0 = get_weather(lon="95.39", lat="29.79")
result = {0: output0}
return result | [] | What is the current weather for the location with coordinates 95.39 longitude and 29.79 latitude? |
196 | "Can you tell me what the weather forecast is for the coordinates 17.14 longitude and 32.81 latitude? I am planning my week and need to know if it's best to carry an umbrella or don a sunhat." | [{'id': 0, 'name': 'get weather', 'args': {'lon': '17.14', 'lat': '32.81'}}] | def solve():
output0 = get_weather(lon="17.14", lat="32.81")
result = {0: output0}
return result | [] | What is the current weather for the location with coordinates 17.14 longitude and 32.81 latitude? |
198 | "Could you tell me the expected weather conditions in the specific geographical coordinates of 87.68 longitude and 41.84 latitude? I'll be traveling to that area tomorrow and need to prepare accordingly." | [{'id': 0, 'name': 'get weather', 'args': {'lon': '87.68', 'lat': '41.84'}}] | def solve():
output0 = get_weather(lon="87.68", lat="41.84")
result = {0: output0}
return result | [] | What is the current weather for the location with coordinates 87.68 longitude and 41.84 latitude? |
201 | "Can you find out specific information for me about the global population? Please refer to the text 'How many people are in the world' and present me the most relevant facts surrounding this." | [{'id': 0, 'name': 'wikipedia simple search', 'args': {'text': 'How many people are in the world'}}] | def solve():
output0 = wikipedia_simple_search(text="How many people are in the world")
result = {0: output0}
return result | [[{'id': 0, 'name': 'text generation', 'args': {'text': 'Tell me about How many people are in the world'}}]] | Could you help me search: "How many people are in the world" in Wikipedia? |
204 | "I'm preparing a presentation about economic downturns. Could you first help me by looking into 'What is a recession?' We can then overview the main points to include in the opening slide." | [{'id': 0, 'name': 'wikipedia simple search', 'args': {'text': 'What is a recession'}}] | def solve():
output0 = wikipedia_simple_search(text="What is a recession")
result = {0: output0}
return result | [[{'id': 0, 'name': 'text generation', 'args': {'text': 'Tell me about What is a recession'}}]] | Could you help me search: "What is a recession" in Wikipedia? |
208 | Query: "Can you help me understand 'woke'? I keep hearing this term but I'm not exactly sure what it means." | [{'id': 0, 'name': 'wikipedia simple search', 'args': {'text': 'What does woke mean'}}] | def solve():
output0 = wikipedia_simple_search(text="What does woke mean")
result = {0: output0}
return result | [[{'id': 0, 'name': 'text generation', 'args': {'text': 'Tell me about What does woke mean'}}]] | Could you help me search: "What does woke mean" in Wikipedia? |
212 | "I've been curious about this for a while - "What Really Happens When You Flush on an Airplane?" Could you research that and give me a thorough explanation but summarize it down so it's easily digestible?" | [{'id': 0, 'name': 'text generation', 'args': {'text': 'a thorough explanation on What Really Happens When You Flush on an Airplane?'}}, {'id': 1, 'name': 'text summarization', 'args': {'text': '<node-0>.text'}}] | def solve():
output0 = text_generation(text="a thorough explanation on What Really Happens When You Flush on an Airplane?")
output1 = text_summarization(text=f"{output0['text']}")
result = {0: output0, 1: output1}
return result | [[{'id': 0, 'name': 'text generation', 'args': {'text': 'a thorough explanation on What Really Happens When You Flush on an Airplane?'}}, {'id': 1, 'name': 'text generation', 'args': {'text': 'Summarize the text: <node-0>.text'}}]] | Can you give me a detailed explanation of what happens when you flush the toilet on an airplane, but then also summarize the main points for me in a few sentences? |
219 | Based on the phrase "You've got to ask yourself one question: Do I feel lucky?" could you generate a possible dialogue or continuation that could come naturally after this? And then, could you give me a short summary of what the generated text primarily conveys? | [{'id': 0, 'name': 'text generation', 'args': {'text': 'a possible dialogue or continuation that could come naturally after "You\'ve got to ask yourself one question: Do I feel lucky?"'}}, {'id': 1, 'name': 'text summarization', 'args': {'text': '<node-0>.text'}}] | def solve():
output0 = text_generation(text="a possible dialogue or continuation that could come naturally after 'You've got to ask yourself one question: Do I feel lucky?'")
output1 = text_summarization(text=f"{output0['text']}")
result = {0: output0, 1: output1}
return result | [[{'id': 0, 'name': 'text generation', 'args': {'text': 'a possible dialogue or continuation that could come naturally after "You\'ve got to ask yourself one question: Do I feel lucky?"'}}, {'id': 1, 'name': 'text generation', 'args': {'text': 'Summarize the text: <node-0>.text'}}]] | "Imagine someone says 'You've got to ask yourself one question: Do I feel lucky?' What could be a natural response or continuation of that dialogue? And then, could you give me a short summary of that potential dialogue? |
226 | "I'm writing a storyline for a new Italian cookbook. Right now, I only have this line: 'The Italian way with the knife is done.' Could you help me generate a few paragraphs that could logically follow this line and then evaluate the tone of the generated text to ensure it instills positivity and excitement in the readers?" | [{'id': 0, 'name': 'text generation', 'args': {'text': 'Generate a few paragraphs that could logically follow this line: "The Italian way with the knife is done."'}}, {'id': 1, 'name': 'text classification', 'args': {'text': '<node-0>.text'}}] | def solve():
output0 = text_generation(text="Generate a few paragraphs that could logically follow this line: 'The Italian way with the knife is done.'")
output1 = text_classification(text=f"{output0['text']}")
result = {0: output0, 1: output1}
return result | [[{'id': 0, 'name': 'text generation', 'args': {'text': 'Generate a few paragraphs that could logically follow this line: "The Italian way with the knife is done."'}}, {'id': 1, 'name': 'question answering', 'args': {'text': '<node-0>.text', 'question': 'Is the text negative, neutral or positive?'}}], [{'id': 0, 'name': 'text generation', 'args': {'text': 'Generate a few paragraphs that could logically follow this line: "The Italian way with the knife is done."'}}, {'id': 1, 'name': 'text generation', 'args': {'text': '<node-0>.text'}}]] | Can you write a few paragraphs that would make sense after the line 'The Italian way with the knife is done'? And then, can you tell me if the overall sentiment of those paragraphs is positive or negative? |
273 | "I'm curious to know about the inaugural Doctor Who audio release. Here's a text that might help: 'The earliest Doctor Who-related audio release was a 21-minute narrated abridgement of the First Doctor television story The Chase released in 1966. Ten years later, the first original Doctor Who audio was released on LP record; Doctor Who and the Pescatons featuring the Fourth Doctor. The first commercially available audiobook was an abridged reading of the Fourth Doctor story State of Decay in 1981. In 1988, during a hiatus in the television show, Slipback, the first radio drama, was transmitted.' Can you deduce what story the first audio release was based on from this text? And after you've done that, could you help me visualize the story with a generated image?" | [{'id': 0, 'name': 'question answering', 'args': {'text': 'The earliest Doctor Who-related audio release was a 21-minute narrated abridgement of the First Doctor television story The Chase released in 1966. Ten years later, the first original Doctor Who audio was released on LP record; Doctor Who and the Pescatons featuring the Fourth Doctor. The first commercially available audiobook was an abridged reading of the Fourth Doctor story State of Decay in 1981. In 1988, during a hiatus in the television show, Slipback, the first radio drama, was transmitted.', 'question': 'What story was the first Doctor Who audio release based on?'}}, {'id': 1, 'name': 'image generation', 'args': {'text': 'a visualization of the story based on <node-0>.text'}}] | def solve():
output0 = question_answering(text="The earliest Doctor Who-related audio release was a 21-minute narrated abridgement of the First Doctor television story The Chase released in 1966. Ten years later, the first original Doctor Who audio was released on LP record; Doctor Who and the Pescatons featuring the Fourth Doctor. The first commercially available audiobook was an abridged reading of the Fourth Doctor story State of Decay in 1981. In 1988, during a hiatus in the television show, Slipback, the first radio drama, was transmitted.", question="What story was the first Doctor Who audio release based on?")
output1 = image_generation(text=f"a visualization of the story based on {output0['text']}")
result = {0: output0, 1: output1}
return result | [] | Based on question: "The earliest Doctor Who-related audio release was a 21-minute narrated abridgement of the First Doctor television story The Chase released in 1966. Ten years later, the first original Doctor Who audio was released on LP record; Doctor Who and the Pescatons featuring the Fourth Doctor. The first commercially available audiobook was an abridged reading of the Fourth Doctor story State of Decay in 1981. In 1988, during a hiatus in the television show, Slipback, the first radio drama, was transmitted.", answer what story was the first Doctor Who audio release based on? Then provide me a visualization of the story. |
276 | "Hello, I've been learning about Super Bowl 50 and I came across some text about the venues that were considered for it. The text says 'The league eventually narrowed the bids to three sites: New Orleans' Mercedes-Benz Superdome, Miami's Sun Life Stadium, and the San Francisco Bay Area's Levi's Stadium.' - now, could you tell me which Louisiana venue was indicated among these options and also sketch an image of the same venue for me?" | [{'id': 0, 'name': 'question answering', 'args': {'text': "The league eventually narrowed the bids to three sites: New Orleans' Mercedes-Benz Superdome, Miami's Sun Life Stadium, and the San Francisco Bay Area's Levi's Stadium.", 'question': 'Which Louisiana venue was one of three considered for Super Bowl 50?'}}, {'id': 1, 'name': 'image generation', 'args': {'text': 'a sketch of the Louisiana venue, <node-0>.text'}}] | def solve():
output0 = question_answering(text="The league eventually narrowed the bids to three sites: New Orleans' Mercedes-Benz Superdome, Miami's Sun Life Stadium, and the San Francisco Bay Area's Levi's Stadium.", question="Which Louisiana venue was one of three considered for Super Bowl 50?")
output1 = image_generation(text=f"a sketch of the Louisiana venue, {output0['text']}")
result = {0: output0, 1: output1}
return result | [] | Based on question: "The league eventually narrowed the bids to three sites: New Orleans' Mercedes-Benz Superdome, Miami's Sun Life Stadium, and the San Francisco Bay Area's Levi's Stadium.", answer which Louisiana venue was one of three considered for Super Bowl 50? Then draw a sketch of the Louisiana venue. |
277 | "I've been digging into the history of the Super Bowl and found this piece of information which says, 'The league eventually narrowed the bids to three sites: New Orleans' Mercedes-Benz Superdome, Miami's Sun Life Stadium, and the San Francisco Bay Area's Levi's Stadium.' From this text, can you clarify which venue in Louisiana was in the running for Super Bowl 50 and afterwards, it would be helpful if you generate a representative image of this venue." | [{'id': 0, 'name': 'question answering', 'args': {'text': "The league eventually narrowed the bids to three sites: New Orleans' Mercedes-Benz Superdome, Miami's Sun Life Stadium, and the San Francisco Bay Area's Levi's Stadium.", 'question': 'Which Louisiana venue was one of three considered for Super Bowl 50?'}}, {'id': 1, 'name': 'image generation', 'args': {'text': 'a representative image of <node-0>.text'}}] | def solve():
output0 = question_answering(text="The league eventually narrowed the bids to three sites: New Orleans' Mercedes-Benz Superdome, Miami's Sun Life Stadium, and the San Francisco Bay Area's Levi's Stadium.", question="Which Louisiana venue was one of three considered for Super Bowl 50?")
output1 = image_generation(text=f"a representative image of {output0['text']}")
result = {0: output0, 1: output1}
return result | [] | Based on question: "The league eventually narrowed the bids to three sites: New Orleans' Mercedes-Benz Superdome, Miami's Sun Life Stadium, and the San Francisco Bay Area's Levi's Stadium.", answer which Louisiana venue was one of three considered for Super Bowl 50? Then a representative image of the Louisiana venue. |
286 | "I've found a text that says, 'The earliest Doctor Who-related audio release was a 21-minute narrated abridgement of the First Doctor television story The Chase released in 1966. Ten years later, the first original Doctor Who audio was released on LP record; Doctor Who and the Pescatons featuring the Fourth Doctor. The first commercially available audiobook was an abridged reading of the Fourth Doctor story State of Decay in 1981. In 1988, during a hiatus in the television show, Slipback, the first radio drama, was transmitted.' I want to know what story was the first Doctor Who audio release based on and then could you find more information for me about this story on Wikipedia?" | [{'id': 0, 'name': 'question answering', 'args': {'text': 'The earliest Doctor Who-related audio release was a 21-minute narrated abridgement of the First Doctor television story The Chase released in 1966. Ten years later, the first original Doctor Who audio was released on LP record; Doctor Who and the Pescatons featuring the Fourth Doctor. The first commercially available audiobook was an abridged reading of the Fourth Doctor story State of Decay in 1981. In 1988, during a hiatus in the television show, Slipback, the first radio drama, was transmitted.', 'question': 'What story was the first Doctor Who audio release based on?'}}, {'id': 1, 'name': 'wikipedia simple search', 'args': {'text': '<node-0>.text'}}] | def solve():
output0 = question_answering(text="The earliest Doctor Who-related audio release was a 21-minute narrated abridgement of the First Doctor television story The Chase released in 1966. Ten years later, the first original Doctor Who audio was released on LP record; Doctor Who and the Pescatons featuring the Fourth Doctor. The first commercially available audiobook was an abridged reading of the Fourth Doctor story State of Decay in 1981. In 1988, during a hiatus in the television show, Slipback, the first radio drama, was transmitted.", question="What story was the first Doctor Who audio release based on?")
output1 = wikipedia_simple_search(text=f"{output0['text']}")
result = {0: output0, 1: output1}
return result | [[{'id': 0, 'name': 'question answering', 'args': {'text': 'The earliest Doctor Who-related audio release was a 21-minute narrated abridgement of the First Doctor television story The Chase released in 1966. Ten years later, the first original Doctor Who audio was released on LP record; Doctor Who and the Pescatons featuring the Fourth Doctor. The first commercially available audiobook was an abridged reading of the Fourth Doctor story State of Decay in 1981. In 1988, during a hiatus in the television show, Slipback, the first radio drama, was transmitted.', 'question': 'What story was the first Doctor Who audio release based on?'}}, {'id': 1, 'name': 'text generation', 'args': {'text': 'Tell me about <node-0>.text'}}]] | Based on question: "The earliest Doctor Who-related audio release was a 21-minute narrated abridgement of the First Doctor television story The Chase released in 1966. Ten years later, the first original Doctor Who audio was released on LP record; Doctor Who and the Pescatons featuring the Fourth Doctor. The first commercially available audiobook was an abridged reading of the Fourth Doctor story State of Decay in 1981. In 1988, during a hiatus in the television show, Slipback, the first radio drama, was transmitted.", answer what story was the first Doctor Who audio release based on? Then search the story in Wikipedia. |
292 | I recently started a tech blog and need a featured image for my upcoming review on ergonomic workspace setups. I'll need an image of a laptop that is sitting near a mouse. Once you've created that, can you please update it to make the tech environment look more dynamic by adding some code snippets displayed on the laptop's screen and turning the background into a nice, wood-textured desk?. | [{'id': 0, 'name': 'image generation', 'args': {'text': 'An image of a laptop that is sitting near a mouse for a featured post on ergonomic workspace setups in a tech blog.'}}, {'id': 1, 'name': 'image editing', 'args': {'image': '<node-0>.image', 'prompt': "adding some code snippets displayed on the laptop's screen and turning the background into a nice, wood-textured desk?"}}] | def solve():
output0 = image_generation(text="An image of a laptop that is sitting near a mouse for a featured post on ergonomic workspace setups in a tech blog.")
output1 = image_editing(image=output0['image'], prompt="adding some code snippets displayed on the laptop's screen and turning the background into a nice, wood-textured desk?")
result = {0: output0, 1: output1}
return result | [] | Could you draw an image of An image of a laptop that is sitting near a mouse for a featured post on ergonomic workspace setups in a tech blog? Then, could you edit the image to add some code snippets on the laptop screen and change the background to look like a nice wooden desk? |
293 | I am creating a promotional banner for a sale on office electronics. Could you generate an image based on a description of 'A laptop that is sitting near a mouse'? Once that is generated, could you please enhance the image by changing the laptop color to blue and placing a red discount tag that says "30% OFF" on the top right corner of the laptop? | [{'id': 0, 'name': 'image generation', 'args': {'text': 'a promotional image featuring A laptop that is sitting near a mouse'}}, {'id': 1, 'name': 'image editing', 'args': {'image': '<node-0>.image', 'prompt': 'changing the laptop color to blue and placing a red discount tag that says "30% OFF" on the top right corner of the laptop'}}] | def solve():
output0 = image_generation(text="a promotional image featuring A laptop that is sitting near a mouse")
output1 = image_editing(image=output0['image'], prompt="changing the laptop color to blue and placing a red discount tag that says '30% OFF' on the top right corner of the laptop")
result = {0: output0, 1: output1}
return result | [] | Could you draw an image of a promotional image featuring A laptop that is sitting near a mouse? Then, could you change the laptop color to blue and place a red discount tag that says "30% OFF" on the top right corner of the laptop? |
295 | I'm designing a poster for a wildlife conservation event. The main theme is passing on the legacy to the next generation. So, can we start with creating an image of an elephant leading a baby elephant towards a door? Once the image is ready, could you then add a setting sun with vivid orange and purple hues in the background, to signify the passing of time? | [{'id': 0, 'name': 'image generation', 'args': {'text': 'an image of an elephant leading a baby elephant towards a door symbolizing the passing on of legacy to the next generation'}}, {'id': 1, 'name': 'image editing', 'args': {'image': '<node-0>.image', 'prompt': 'a setting sun with vivid orange and purple hues in the background'}}] | def solve():
output0 = image_generation(text="an image of an elephant leading a baby elephant towards a door symbolizing the passing on of legacy to the next generation")
output1 = image_editing(image=output0['image'], prompt="a setting sun with vivid orange and purple hues in the background")
result = {0: output0, 1: output1}
return result | [] | Could you draw an image of an elephant leading a baby elephant towards a door symbolizing the passing on of legacy to the next generation? Then, could you add a setting sun with vivid orange and purple hues in the background? |
307 | I'm creating a presentation slide on gender equality at workplaces. I require an image depicting a "Women worker looking at rear view mirror smiling". Once the image is ready, I need an accurate and succinct description of the image that would make the presentation more informative and easily understandable to the audience. | [{'id': 0, 'name': 'image generation', 'args': {'text': 'an image depicting a woman worker looking at rear view mirror smiling'}}, {'id': 1, 'name': 'image captioning', 'args': {'image': '<node-0>.image'}}] | def solve():
output0 = image_generation(text="an image depicting a woman worker looking at rear view mirror smiling")
output1 = image_captioning(image=output0['image'])
result = {0: output0, 1: output1}
return result | [[{'id': 0, 'name': 'image generation', 'args': {'text': 'an image depicting a woman worker looking at rear view mirror smiling'}}, {'id': 1, 'name': 'visual question answering', 'args': {'image': '<node-0>.image', 'question': 'What is in the image?'}}]] | Could you draw an image depicting a woman worker looking at rear view mirror smiling? Then, could you provide me a caption of this image. |
314 | "I'm trying to visualize a tray full of breakfast foods and drinks placed on a bed, and I'd love to identify what specific items are in this imagined breakfast scene. Can we create this visualization and highlight each item, so I can better understand what's in it?" | [{'id': 0, 'name': 'image generation', 'args': {'text': 'A visualization of a tray full of breakfast foods and drinks placed on a bed.'}}, {'id': 1, 'name': 'object detection', 'args': {'image': '<node-0>.image'}}] | def solve():
output0 = image_generation(text="A visualization of a tray full of breakfast foods and drinks placed on a bed.")
output1 = object_detection(image=output0['image'])
result = {0: output0, 1: output1}
return result | [[{'id': 0, 'name': 'image generation', 'args': {'text': 'A visualization of a tray full of breakfast foods and drinks placed on a bed.'}}, {'id': 1, 'name': 'image segmentation', 'args': {'image': '<node-0>.image'}}]] | Can you create an image of a tray full of breakfast foods and drinks sitting on a bed? And then, could you tell me what specific objects are in that image by drawing boxes around them? |
315 | "I have an idea of serving breakfast in bed with a tray full of varied food items and drinks. However, I'm unsure about what items typically make a complete set. Could you create a visual representation from my description and then identify and list out all the items shown?" | [{'id': 0, 'name': 'image generation', 'args': {'text': 'A visual representation of a tray full of varied breakfast foods and drinks on a bed'}}, {'id': 1, 'name': 'object detection', 'args': {'image': '<node-0>.image'}}] | def solve():
output0 = image_generation(text="A visual representation of a tray full of varied breakfast foods and drinks on a bed")
output1 = object_detection(image=output0['image'])
result = {0: output0, 1: output1}
return result | [[{'id': 0, 'name': 'image generation', 'args': {'text': 'A visual representation of a tray full of varied breakfast foods and drinks on a bed'}}, {'id': 1, 'name': 'image segmentation', 'args': {'image': '<node-0>.image'}}]] | Can you create an image of a tray full of varied breakfast foods and drinks on a bed? And then, could you tell me what specific objects are in that image by drawing boxes around them? |
322 | "I want to create a visual representation for the action 'A man is doing tricks with a frisbee' and identify what the predominant element or subject of the generated image is." | [{'id': 0, 'name': 'image generation', 'args': {'text': 'a visual representation of a man doing tricks with a frisbee'}}, {'id': 1, 'name': 'image classification', 'args': {'image': '<node-0>.image'}}] | def solve():
output0 = image_generation(text="a visual representation of a man doing tricks with a frisbee")
output1 = image_classification(image=output0['image'])
result = {0: output0, 1: output1}
return result | [[{'id': 0, 'name': 'image generation', 'args': {'text': 'a visual representation of a man doing tricks with a frisbee'}}, {'id': 1, 'name': 'object detection', 'args': {'image': '<node-0>.image'}}], [{'id': 0, 'name': 'image generation', 'args': {'text': 'a visual representation of a man doing tricks with a frisbee'}}, {'id': 1, 'name': 'visual question answering', 'args': {'image': '<node-0>.image', 'question': 'What is the main subject in the image?'}}], [{'id': 0, 'name': 'image generation', 'args': {'text': 'a visual representation of a man doing tricks with a frisbee'}}, {'id': 1, 'name': 'image captioning', 'args': {'image': '<node-0>.image'}}]] | Can you create an image of a man doing tricks with a frisbee? And then, could you classifies the subject in the image into a category? |
323 | "Can I use the description 'A man is doing tricks with a frisbee' to generate a corresponding visual and tell me what the central object or subject in the created picture is?" | [{'id': 0, 'name': 'image generation', 'args': {'text': 'A visual representation of a man doing tricks with a frisbee'}}, {'id': 1, 'name': 'image classification', 'args': {'image': '<node-0>.image'}}] | def solve():
output0 = image_generation(text="A visual representation of a man doing tricks with a frisbee")
output1 = image_classification(image=output0['image'])
result = {0: output0, 1: output1}
return result | [[{'id': 0, 'name': 'image generation', 'args': {'text': 'A visual representation of a man doing tricks with a frisbee'}}, {'id': 1, 'name': 'object detection', 'args': {'image': '<node-0>.image'}}], [{'id': 0, 'name': 'image generation', 'args': {'text': 'A visual representation of a man doing tricks with a frisbee'}}, {'id': 1, 'name': 'visual question answering', 'args': {'image': '<node-0>.image', 'question': 'What is the main subject in the image?'}}], [{'id': 0, 'name': 'image generation', 'args': {'text': 'A visual representation of a man doing tricks with a frisbee'}}, {'id': 1, 'name': 'image captioning', 'args': {'image': '<node-0>.image'}}]] | Can you create an image of a man doing tricks with a frisbee? And then, could you classifies the subject in the image into a category? |
328 | I'm working on a culinary art project and I need to visualize a specific scene. Can you create a visual representation of 'A desert on a plate with a spoon on the side of the plate' and then tell me what category this scene best fits into in culinary terms? | [{'id': 0, 'name': 'image generation', 'args': {'text': 'a visual representation of A desert on a plate with a spoon on the side of the plate'}}, {'id': 1, 'name': 'image classification', 'args': {'image': '<node-0>.image'}}] | def solve():
output0 = image_generation(text="a visual representation of A desert on a plate with a spoon on the side of the plate")
output1 = image_classification(image=output0['image'])
result = {0: output0, 1: output1}
return result | [[{'id': 0, 'name': 'image generation', 'args': {'text': 'a visual representation of A desert on a plate with a spoon on the side of the plate'}}, {'id': 1, 'name': 'object detection', 'args': {'image': '<node-0>.image'}}], [{'id': 0, 'name': 'image generation', 'args': {'text': 'a visual representation of A desert on a plate with a spoon on the side of the plate'}}, {'id': 1, 'name': 'visual question answering', 'args': {'image': '<node-0>.image', 'question': 'What is the main subject in the image?'}}], [{'id': 0, 'name': 'image generation', 'args': {'text': 'a visual representation of A desert on a plate with a spoon on the side of the plate'}}, {'id': 1, 'name': 'image captioning', 'args': {'image': '<node-0>.image'}}]] | Can you create an image of a desert on a plate with a spoon on the side of the plate? And then, could you classifies the subject in the image into a category? |
333 | For my digital art project, I need an image based on the description 'A man is doing tricks with a frisbee'. After generating the image, could you segregate the unique components such as the man, frisbee, and any other distinguishable aspects? | [{'id': 0, 'name': 'image generation', 'args': {'text': 'an image where a man is doing tricks with a frisbee'}}, {'id': 1, 'name': 'image segmentation', 'args': {'image': '<node-0>.image'}}] | def solve():
output0 = image_generation(text="an image where a man is doing tricks with a frisbee")
output1 = image_segmentation(image=output0['image'])
result = {0: output0, 1: output1}
return result | [] | Can you create an image of an image where a man is doing tricks with a frisbee? And then, could you give me segmentation masks of any components in the image. |
339 | "I'm designing a puzzle game where the player has to identify and interact with various objects within a scene. Can you create a scene showing a baby tabby cat walking behind a bicycle leaning against a wall? Also, can you provide me with the image components separately so that I can arrange them for the gameplay?" | [{'id': 0, 'name': 'image generation', 'args': {'text': 'A scene showing a baby tabby cat walking behind a bicycle leaning against a wall'}}, {'id': 1, 'name': 'image segmentation', 'args': {'image': '<node-0>.image'}}] | def solve():
output0 = image_generation(text="A scene showing a baby tabby cat walking behind a bicycle leaning against a wall")
output1 = image_segmentation(image=output0['image'])
result = {0: output0, 1: output1}
return result | [] | Can you create a scene showing a baby tabby cat walking behind a bicycle leaning against a wall? And then, could you give me segmentation masks of any components in the image. |
345 | "Looking for a unique way to promote our new skiing gear. I'd love to see an image of a man with skis and poles on snow. Once we have the image, let's focus on the left side of it for a more dynamic promotional piece." | [{'id': 0, 'name': 'image generation', 'args': {'text': 'an image of a man with skis and poles on snow for promoting our new skiing gear.'}}, {'id': 1, 'name': 'image crop left', 'args': {'image': '<node-0>.image'}}] | def solve():
output0 = image_generation(text="an image of a man with skis and poles on snow for promoting our new skiing gear.")
output1 = image_crop_left(image=output0['image'])
result = {0: output0, 1: output1}
return result | [[{'id': 0, 'name': 'image generation', 'args': {'text': 'an image of a man with skis and poles on snow for promoting our new skiing gear.'}}, {'id': 1, 'name': 'image crop', 'args': {'image': '<node-0>.image', 'bbox': '[0, 0, 0.5, 1]'}}]] | Can you create an image of a man with skis and poles on snow for promoting our new skiing gear? And then, could you give me the left part of the image. |
354 | "I need an illustration for my new project description. Could you create an image that displays some big red metal boxes located near a road? I only need the right portion of the illustration though, to use as a banner for the project's webpage. | [{'id': 0, 'name': 'image generation', 'args': {'text': 'An illustration displaying some big red metal boxes located near a road'}}, {'id': 1, 'name': 'image crop right', 'args': {'image': '<node-0>.image'}}] | def solve():
output0 = image_generation(text="An illustration displaying some big red metal boxes located near a road")
output1 = image_crop_right(image=output0['image'])
result = {0: output0, 1: output1}
return result | [[{'id': 0, 'name': 'image generation', 'args': {'text': 'An illustration displaying some big red metal boxes located near a road'}}, {'id': 1, 'name': 'image crop', 'args': {'image': '<node-0>.image', 'bbox': '[0.5, 0, 1, 1]'}}]] | Can you create an image of some big red metal boxes located near a road? And then, could you give me the right part of the image. |
355 | "I'm writing a short children's story that involves some big red metal boxes by a road - can you create an image based on those elements for me? Only the right aspect of the image will be utilized for the book cover, to leave space for the title and other information." | [{'id': 0, 'name': 'image generation', 'args': {'text': 'an image of big red metal boxes by a road dedicated for a kids story'}}, {'id': 1, 'name': 'image crop right', 'args': {'image': '<node-0>.image'}}] | def solve():
output0 = image_generation(text="an image of big red metal boxes by a road dedicated for a kids story")
output1 = image_crop_right(image=output0['image'])
result = {0: output0, 1: output1}
return result | [[{'id': 0, 'name': 'image generation', 'args': {'text': 'an image of big red metal boxes by a road dedicated for a kids story'}}, {'id': 1, 'name': 'image crop', 'args': {'image': '<node-0>.image', 'bbox': '[0.5, 0, 1, 1]'}}]] | Can you create an image of big red metal boxes by a road dedicated for a kids story? And then, could you give me the right part of the image. |
370 | I'm redesigning my bathroom and would love to gain some inspiration for my bathtub placement. Could you generate a visual representation of a white bath tub sitting under a window? I'm particularly interested in the bottom half of the scene as I want to understand how the tub interacts with the floor tiling and bathroom fixtures beneath it. | [{'id': 0, 'name': 'image generation', 'args': {'text': 'A visual representation of a white bath tub sitting under a window with a focus on its interaction with the floor tiling and bathroom fixtures.'}}, {'id': 1, 'name': 'image crop bottom', 'args': {'image': '<node-0>.image'}}] | def solve():
output0 = image_generation(text="A visual representation of a white bath tub sitting under a window with a focus on its interaction with the floor tiling and bathroom fixtures.")
output1 = image_crop_bottom(image=output0['image'])
result = {0: output0, 1: output1}
return result | [[{'id': 0, 'name': 'image generation', 'args': {'text': 'A visual representation of a white bath tub sitting under a window with a focus on its interaction with the floor tiling and bathroom fixtures.'}}, {'id': 1, 'name': 'image crop', 'args': {'image': '<node-0>.image', 'bbox': '[0, 0.5, 1, 1]'}}]] | Can you create an image of a white bath tub sitting under a window with a focus on its interaction with the floor tiling and bathroom fixtures? And then, could you give me the bottom part of the image. |
371 | I'm playing around with the idea of placing a white bathtub under a window in my home renovation project. Can you provide a visual of how this might look? And if you can, please give me a focus on the lower part of this image. I want to see how the lower section of the bathtub and the area around it might look in this setup. | [{'id': 0, 'name': 'image generation', 'args': {'text': 'A visualization of a white bath tub sitting under a window in a home renovation setting.'}}, {'id': 1, 'name': 'image crop bottom', 'args': {'image': '<node-0>.image'}}] | def solve():
output0 = image_generation(text="A visualization of a white bath tub sitting under a window in a home renovation setting.")
output1 = image_crop_bottom(image=output0['image'])
result = {0: output0, 1: output1}
return result | [[{'id': 0, 'name': 'image generation', 'args': {'text': 'A visualization of a white bath tub sitting under a window in a home renovation setting.'}}, {'id': 1, 'name': 'image crop', 'args': {'image': '<node-0>.image', 'bbox': '[0, 0.5, 1, 1]'}}]] | Can you create an image of a white bath tub sitting under a window in a home renovation setting? And then, could you give me the bottom part of the image. |
375 | "I'm creating a unique presentation and I need to visualize an extraordinary scene that involves a group of airplanes floating over the ocean. I'm particularly interested in focusing more on the ocean and less on the sky. Can you assist with this preference?" | [{'id': 0, 'name': 'image generation', 'args': {'text': 'An extraordinary scene of a group of airplanes floating over the ocean, with a particular focus more on the ocean and less on the sky.'}}, {'id': 1, 'name': 'image crop bottom', 'args': {'image': '<node-0>.image'}}] | def solve():
output0 = image_generation(text="An extraordinary scene of a group of airplanes floating over the ocean, with a particular focus more on the ocean and less on the sky.")
output1 = image_crop_bottom(image=output0['image'])
result = {0: output0, 1: output1}
return result | [[{'id': 0, 'name': 'image generation', 'args': {'text': 'An extraordinary scene of a group of airplanes floating over the ocean, with a particular focus more on the ocean and less on the sky.'}}, {'id': 1, 'name': 'image crop', 'args': {'image': '<node-0>.image', 'bbox': '[0, 0.5, 1, 1]'}}]] | Can you create an image of an extraordinary scene of a group of airplanes floating over the ocean, with a particular focus more on the ocean and less on the sky? And then, could you give me the bottom part of the image. |
380 | "Hey, I need to create an invitation card for my friend. It should feature an image of a woman playing with a video game controller. Once you've got that, could you please transcribe the text from the generated image to help me build the message for the invitation?" | [{'id': 0, 'name': 'image generation', 'args': {'text': 'An image of a woman playing with a video game controller for an invitation card.'}}, {'id': 1, 'name': 'optical character recognition', 'args': {'image': '<node-0>.image'}}] | def solve():
output0 = image_generation(text="An image of a woman playing with a video game controller for an invitation card.")
output1 = optical_character_recognition(image=output0['image'])
result = {0: output0, 1: output1}
return result | [[{'id': 0, 'name': 'image generation', 'args': {'text': 'An image of a woman playing with a video game controller for an invitation card.'}}, {'id': 1, 'name': 'visual question answering', 'args': {'image': '<node-0>.image', 'question': 'What are the characters in this image if any?'}}]] | Can you create an image of a woman playing with a video game controller for an invitation card? And then, could you give me recognized texts in the image. |
388 | "I need to know what the sign on a bus would say if there was a group of people standing outside of it. Could you generate such a scenario for me and tell me what the resulting text on the bus reads?" | [{'id': 0, 'name': 'image generation', 'args': {'text': 'A scenario where a group of people are standing outside of a bus with a sign.'}}, {'id': 1, 'name': 'optical character recognition', 'args': {'image': '<node-0>.image'}}] | def solve():
output0 = image_generation(text="A scenario where a group of people are standing outside of a bus with a sign.")
output1 = optical_character_recognition(image=output0['image'])
result = {0: output0, 1: output1}
return result | [[{'id': 0, 'name': 'image generation', 'args': {'text': 'A scenario where a group of people are standing outside of a bus with a sign.'}}, {'id': 1, 'name': 'visual question answering', 'args': {'image': '<node-0>.image', 'question': 'What are the characters in this image if any?'}}]] | Can you create an image of a scenario where a group of people are standing outside of a bus with a sign? And then, could you give me recognized texts in the image. |
404 | "I have an image 150517.jpg. Can you convert this into a straightforward text description and then provide a condensed version of that description?" | [{'id': 0, 'name': 'image captioning', 'args': {'image': '150517.jpg'}}, {'id': 1, 'name': 'text summarization', 'args': {'text': '<node-0>.text'}}] | def solve():
output0 = image_captioning(image="150517.jpg")
output1 = text_summarization(text=f"{output0['text']}")
result = {0: output0, 1: output1}
return result | [[{'id': 0, 'name': 'image captioning', 'args': {'image': '150517.jpg'}}, {'id': 1, 'name': 'text generation', 'args': {'text': 'Summarize the text: <node-0>.text'}}], [{'id': 0, 'name': 'visual question answering', 'args': {'image': '150517.jpg', 'question': 'What is in the image?'}}, {'id': 1, 'name': 'text summarization', 'args': {'text': '<node-0>.text'}}], [{'id': 0, 'name': 'visual question answering', 'args': {'image': '150517.jpg', 'question': 'What is in the image?'}}, {'id': 1, 'name': 'text generation', 'args': {'text': 'Summarize the text: <node-0>.text'}}]] | Could you describe the image 150517.jpg and summarize your description? |
413 | As a part of a social media moderation team, we often encounter posts that include images and need to assess the sentiment conveyed by these photos quickly. We have one such image (2318145.jpg). We require help in classifying the sentiment of this image, whether it conveys a positive/joyful or negative/sad image, to determine if it aligns with the platform's content guidelines. | [{'id': 0, 'name': 'image captioning', 'args': {'image': '2318145.jpg'}}, {'id': 1, 'name': 'text classification', 'args': {'text': '<node-0>.text'}}] | def solve():
output0 = image_captioning(image="2318145.jpg")
output1 = text_classification(text=f"{output0['text']}")
result = {0: output0, 1: output1}
return result | [[{'id': 0, 'name': 'image captioning', 'args': {'image': '2318145.jpg'}}, {'id': 1, 'name': 'question answering', 'args': {'text': '<node-0>.text', 'question': 'Is the text negative, neutral or positive?'}}], [{'id': 0, 'name': 'image captioning', 'args': {'image': '2318145.jpg'}}, {'id': 1, 'name': 'text generation', 'args': {'text': '<node-0>.text'}}], [{'id': 0, 'name': 'visual question answering', 'args': {'image': '2318145.jpg', 'question': 'What is in the image?'}}, {'id': 1, 'name': 'text classification', 'args': {'text': '<node-0>.text'}}], [{'id': 0, 'name': 'visual question answering', 'args': {'image': '2318145.jpg', 'question': 'What is in the image?'}}, {'id': 1, 'name': 'question answering', 'args': {'text': '<node-0>.text', 'question': 'Is the text negative, neutral or positive?'}}], [{'id': 0, 'name': 'visual question answering', 'args': {'image': '2318145.jpg', 'question': 'What is in the image?'}}, {'id': 1, 'name': 'text generation', 'args': {'text': '<node-0>.text'}}]] | Could you describe the image 2318145.jpg and tell me the sentiment of your description? |
470 | "I have an image 'COCO_train2014_000000134502.jpg'. Can you help me understand what's written on it and provide some information about it from Wikipedia?" | [{'id': 0, 'name': 'optical character recognition', 'args': {'image': 'COCO_train2014_000000134502.jpg'}}, {'id': 1, 'name': 'wikipedia simple search', 'args': {'text': '<node-0>.text'}}] | def solve():
output0 = optical_character_recognition(image="COCO_train2014_000000134502.jpg")
output1 = wikipedia_simple_search(text=f"{output0['text']}")
result = {0: output0, 1: output1}
return result | [[{'id': 0, 'name': 'optical character recognition', 'args': {'image': 'COCO_train2014_000000134502.jpg'}}, {'id': 1, 'name': 'text generation', 'args': {'text': 'Tell me about <node-0>.text'}}], [{'id': 0, 'name': 'visual question answering', 'args': {'image': 'COCO_train2014_000000134502.jpg', 'question': 'What are the characters in this image if any?'}}, {'id': 1, 'name': 'wikipedia simple search', 'args': {'text': '<node-0>.text'}}], [{'id': 0, 'name': 'visual question answering', 'args': {'image': 'COCO_train2014_000000134502.jpg', 'question': 'What are the characters in this image if any?'}}, {'id': 1, 'name': 'text generation', 'args': {'text': 'Tell me about <node-0>.text'}}]] | Could you get the recognized texts of image COCO_train2014_000000134502.jpg and search the texts in Wikipedia? |
476 | "I've been going through some old photographs and found an image, 'COCO_train2014_000000113236.jpg'. It has some kind of text written on it. I can't read it clearly, can you help me identify this and find more information about it online?" | [{'id': 0, 'name': 'optical character recognition', 'args': {'image': 'COCO_train2014_000000113236.jpg'}}, {'id': 1, 'name': 'wikipedia simple search', 'args': {'text': '<node-0>.text'}}] | def solve():
output0 = optical_character_recognition(image="COCO_train2014_000000113236.jpg")
output1 = wikipedia_simple_search(text=f"{output0['text']}")
result = {0: output0, 1: output1}
return result | [[{'id': 0, 'name': 'optical character recognition', 'args': {'image': 'COCO_train2014_000000113236.jpg'}}, {'id': 1, 'name': 'text generation', 'args': {'text': 'Tell me about <node-0>.text'}}], [{'id': 0, 'name': 'visual question answering', 'args': {'image': 'COCO_train2014_000000113236.jpg', 'question': 'What are the characters in this image if any?'}}, {'id': 1, 'name': 'wikipedia simple search', 'args': {'text': '<node-0>.text'}}], [{'id': 0, 'name': 'visual question answering', 'args': {'image': 'COCO_train2014_000000113236.jpg', 'question': 'What are the characters in this image if any?'}}, {'id': 1, 'name': 'text generation', 'args': {'text': 'Tell me about <node-0>.text'}}]] | Could you get the recognized texts of image COCO_train2014_000000113236.jpg and search the texts in Wikipedia? |
End of preview.
Dataset Card for m&ms
m&ms is a dataset of multi-step multi-modal tasks and corresponding task plans.
Dataset Details
This dataset contains 4K+ multi-step multi-modal tasks involving 33 tools that include 13 multi-modal models, 9 (free) public APIs, and 11 image processing modules. For each of these task queries, we provide automatically generated plans using this realistic toolset. We further provide a high-quality subset of 1,565 human-verified task plans and 882 human-verified, filtered, and correctly executable plans.
Dataset Sources
- Repository: https://github.com/RAIVNLab/mnms
- Paper: https://arxiv.org/abs/2403.11085
Uses
The intended use of this dataset is to evaluate large language model (LLM) agents on their tool-use abilities for multi-step multi-modal tasks.
Direct Use
To use this dataset, you can first obtain plan predictions from LLM agents on the user requests in either JSON or Python code format, and then evaluate the predicted plans against the label plans or code in this dataset.
Out-of-Scope Use
This dataset should not be used for training models.
Source Data
The data inputs to the plans can be accessed here. They are sampled from various existing datasets, including ImageNet, sst2, SQUAD, C4, CNN daily news, COCO, COCO-Text v2.0, GQA, Visual Genome, MagicBrush, and librispeech.
Data Collection and Processing
Bias, Risks, and Limitations
Our dataset has the following limitations:
- The user requests might be biased as they are generated by GPT-4 and do not necessarily represent real-world user requests;
- The task plans are all sequential and require 1-3 tools to solve.
Citation
BibTeX:
@misc{ma2024mms,
title={m&m's: A Benchmark to Evaluate Tool-Use for multi-step multi-modal Tasks},
author={Zixian Ma and Weikai Huang and Jieyu Zhang and Tanmay Gupta and Ranjay Krishna},
year={2024},
eprint={2403.11085},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
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