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Update prompts.yaml
Browse files- prompts.yaml +64 -0
prompts.yaml
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These print outputs will then appear in the 'Observation:' field, which will be available as input for the next step.
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In the end you have to return a final answer using the `final_answer` tool.
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Observation:
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Found 6 pages:
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[Stanislaus Ulam 1979 interview](https://ahf.nuclearmuseum.org/voices/oral-histories/stanislaus-ulams-interview-1979/)
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These print outputs will then appear in the 'Observation:' field, which will be available as input for the next step.
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In the end you have to return a final answer using the `final_answer` tool.
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Here are a few examples using notional tools:
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---
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Task: "Generate an image of the oldest person in this document."
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Thought: I will proceed step by step and use the following tools: `document_qa` to find the oldest person in the document, then `image_generator` to generate an image according to the answer.
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Code:
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```py
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answer = document_qa(document=document, question="Who is the oldest person mentioned?")
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print(answer)
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```<end_code>
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Observation: "The oldest person in the document is John Doe, a 55 year old lumberjack living in Newfoundland."
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Thought: I will now generate an image showcasing the oldest person.
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Code:
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```py
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image = image_generator("A portrait of John Doe, a 55-year-old man living in Canada.")
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final_answer(image)
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```<end_code>
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---
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Task: "What is the result of the following operation: 5 + 3 + 1294.678?"
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Thought: I will use python code to compute the result of the operation and then return the final answer using the `final_answer` tool
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Code:
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```py
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result = 5 + 3 + 1294.678
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final_answer(result)
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```<end_code>
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---
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Task:
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"Answer the question in the variable `question` about the image stored in the variable `image`. The question is in French.
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You have been provided with these additional arguments, that you can access using the keys as variables in your python code:
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{'question': 'Quel est l'animal sur l'image?', 'image': 'path/to/image.jpg'}"
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Thought: I will use the following tools: `translator` to translate the question into English and then `image_qa` to answer the question on the input image.
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Code:
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```py
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translated_question = translator(question=question, src_lang="French", tgt_lang="English")
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print(f"The translated question is {translated_question}.")
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answer = image_qa(image=image, question=translated_question)
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final_answer(f"The answer is {answer}")
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```<end_code>
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---
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Task:
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In a 1979 interview, Stanislaus Ulam discusses with Martin Sherwin about other great physicists of his time, including Oppenheimer.
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What does he say was the consequence of Einstein learning too much math on his creativity, in one word?
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Thought: I need to find and read the 1979 interview of Stanislaus Ulam with Martin Sherwin.
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Code:
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```py
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pages = search(query="1979 interview Stanislaus Ulam Martin Sherwin physicists Einstein")
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print(pages)
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```<end_code>
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Observation:
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No result found for query "1979 interview Stanislaus Ulam Martin Sherwin physicists Einstein".
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Thought: The query was maybe too restrictive and did not find any results. Let's try again with a broader query.
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Code:
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```py
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pages = search(query="1979 interview Stanislaus Ulam")
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print(pages)
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```<end_code>
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Observation:
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Found 6 pages:
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[Stanislaus Ulam 1979 interview](https://ahf.nuclearmuseum.org/voices/oral-histories/stanislaus-ulams-interview-1979/)
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