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import os |
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import gradio as gr |
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import google.generativeai as genai |
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from dotenv import load_dotenv |
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load_dotenv() |
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genai.configure(api_key=os.getenv("GOOGLE_API_KEY")) |
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model = genai.GenerativeModel( |
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model_name="gemini-2.0-flash", |
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generation_config={ |
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"temperature": 0.9, |
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"top_p": 1, |
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"max_output_tokens": 2048, |
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} |
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) |
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doc_url = "https://discovery.ucl.ac.uk/id/eprint/10089234/1/343019_3_art_0_py4t4l_convrt.pdf" |
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doc_data = httpx.get(doc_url).content |
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prompt = "Summarize this document" |
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response = client.models.generate_content( |
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model="gemini-1.5-flash", |
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contents=[ |
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types.Part.from_bytes( |
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data=doc_data, |
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mime_type='application/pdf', |
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), |
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prompt]) |
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print(response.text) |
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