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Runtime error
Runtime error
Update app.py
Browse files
app.py
CHANGED
@@ -20,7 +20,7 @@ def text_prompt(request, page_url, contraseña, temp):
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page.parse()
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except Exception as e:
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return "", f"---
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tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
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sentences = page.text.split('.')
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@@ -31,12 +31,12 @@ def text_prompt(request, page_url, contraseña, temp):
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for sentence in sentences:
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tokens.extend(tokenizer.tokenize(sentence))
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#
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if len(tokens) > 1800:
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break
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page_text += sentence + ". "
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#
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page_text = page_text.strip()
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num_tokens = len(tokens)
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@@ -61,8 +61,8 @@ def text_prompt(request, page_url, contraseña, temp):
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response_text = response_text.strip()
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return page.text, response_text, total_tokens
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except Exception as e:
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return page.text, f"---
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return page.text, "--- Min number of tokens
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# define the gradio interface
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iface = gr.Interface(
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@@ -77,11 +77,11 @@ iface = gr.Interface(
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["Generate a summary of the following text. Give me an overview of main business impact from the text following this template:\n- Summary:\n- Business Impact:\n- Companies:", "https://ai.googleblog.com/2019/10/quantum-supremacy-using-programmable.html","",0.7],
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["Generate the next insights based on the following text. Indicates N/A if the information is not available in the text.\n- Summary:\n- Acquisition Price:\n- Why is this important for the acquirer:\n- Business Line for the acquirer:\n- Tech Focus for the acquired (list):","https://techcrunch.com/2022/09/28/eqt-acquires-billtrust-a-company-automating-the-invoice-to-cash-process-for-1-7b/","",0.3]
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],
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title="ChatGPT info extraction
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description="This tool allows querying the text retrieved from the URL using OpenAI's [text-davinci-003] engine.\nThe URL text can be referenced in the prompt as \"following text\".\nA GPT2 tokenizer is included to ensure that the
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)
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#
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error_message = ""
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page.parse()
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except Exception as e:
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return "", f"--- An error occurred while processing the URL: {e} ---", ""
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tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
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sentences = page.text.split('.')
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for sentence in sentences:
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tokens.extend(tokenizer.tokenize(sentence))
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# Trim text to a maximum of 1800 tokens
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if len(tokens) > 1800:
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break
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page_text += sentence + ". "
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# Delete the last space
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page_text = page_text.strip()
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num_tokens = len(tokens)
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response_text = response_text.strip()
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return page.text, response_text, total_tokens
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except Exception as e:
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return page.text, f"--- An error occurred while processing the request: {e} ---", num_tokens
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return page.text, "--- Min number of tokens:", num_tokens
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# define the gradio interface
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iface = gr.Interface(
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["Generate a summary of the following text. Give me an overview of main business impact from the text following this template:\n- Summary:\n- Business Impact:\n- Companies:", "https://ai.googleblog.com/2019/10/quantum-supremacy-using-programmable.html","",0.7],
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["Generate the next insights based on the following text. Indicates N/A if the information is not available in the text.\n- Summary:\n- Acquisition Price:\n- Why is this important for the acquirer:\n- Business Line for the acquirer:\n- Tech Focus for the acquired (list):","https://techcrunch.com/2022/09/28/eqt-acquires-billtrust-a-company-automating-the-invoice-to-cash-process-for-1-7b/","",0.3]
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],
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title="ChatGPT / GPT-3 info extraction from URL",
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description="This tool allows querying the text retrieved from the URL with newspaper3k lib and using OpenAI's [text-davinci-003] engine.\nThe URL text can be referenced in the prompt as \"following text\".\nA GPT2 tokenizer is included to ensure that the 1.800 token limit for OpenAI queries is not exceeded. Provide a prompt with your request, the url for text retrieval, your api-key and temperature to process the text."
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)
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# error capturing in integration as a component
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error_message = ""
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