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51 lines
1.2 KiB
51 lines
1.2 KiB
# !pip install --upgrade swarms==2.0.6
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from swarms.models import BioGPT
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from swarms.models.nougat import Nougat
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from swarms.structs import Flow
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# # URL of the image of the financial document
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IMAGE_OF_FINANCIAL_DOC_URL = "bank_statement_2.jpg"
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# Example usage
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api_key = "" # Your actual API key here
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# Initialize the OCR model
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# Initialize the language flow
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llm = BioGPT()
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# Create a prompt for the language model
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def summary_agent_prompt(analyzed_doc: str):
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model = Nougat(
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max_new_tokens=5000,
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)
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out = model(analyzed_doc)
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return f"""
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Generate an actionable summary of this financial document, provide bulletpoints:
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Here is the Analyzed Document:
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---
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{out}
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"""
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# Initialize the Flow with the language flow
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flow1 = Flow(llm=llm, max_loops=1, dashboard=False)
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# Create another Flow for a different task
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flow2 = Flow(llm=llm, max_loops=1, dashboard=False)
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# Add tasks to the workflow
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summary_agent = flow1.run(summary_agent_prompt(IMAGE_OF_FINANCIAL_DOC_URL))
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# Suppose the next task takes the output of the first task as input
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out = flow2.run(
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f"Provide an actionable step by step plan on how to cut costs from the analyzed financial document. {summary_agent}"
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)
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