Update app.py
Browse files
app.py
CHANGED
@@ -16,18 +16,18 @@ def extract_text_from_excel(file):
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text = ' '.join(df['Unnamed: 1'].astype(str))
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return text
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def save_to_csv(sentence, output, filename="synthetic_data.csv"):
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with open(filename, mode='a', newline='', encoding='utf-8') as file:
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writer = csv.writer(file)
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writer.writerow([sentence, output])
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def generate(file, temperature, max_new_tokens, top_p, repetition_penalty, num_similar_sentences):
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text = extract_text_from_excel(file)
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sentences = text.split('.')
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random.shuffle(sentences) # Shuffle sentences
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with tempfile.NamedTemporaryFile(mode='w', newline='', delete=False, suffix='.csv') as tmp:
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fieldnames = ['Original Sentence', 'Generated Sentence']
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writer = csv.DictWriter(tmp, fieldnames=fieldnames)
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writer.writeheader()
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@@ -46,7 +46,7 @@ def generate(file, temperature, max_new_tokens, top_p, repetition_penalty, num_s
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}
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try:
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stream = client.text_generation(sentence, **generate_kwargs, stream=True, details=True, return_full_text=False)
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output = ""
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for response in stream:
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output += response.token.text
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@@ -58,26 +58,30 @@ def generate(file, temperature, max_new_tokens, top_p, repetition_penalty, num_s
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if not generated_sentences:
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break
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generated_sentence = generated_sentences.pop(random.randrange(len(generated_sentences)))
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writer.writerow({'Original Sentence': sentence, 'Generated Sentence': generated_sentence})
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except Exception as e:
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print(f"Error generating data for sentence '{sentence}': {e}")
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tmp_path = tmp.name
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return tmp_path
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gr.Interface(
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fn=generate,
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inputs=[
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gr.File(label="Upload Excel File", file_count="single", file_types=[".xlsx"]),
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gr.Slider(label="Temperature", value=0.9, minimum=0.0, maximum=1.0, step=0.05, interactive=True, info="Higher values produce more diverse outputs"),
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gr.Slider(label="Max new tokens", value=256, minimum=0, maximum=5120, step=64, interactive=True, info="The maximum numbers of new tokens"),
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gr.Slider(label="Top-p (nucleus sampling)", value=0.95, minimum=0.0, maximum=1, step=0.05, interactive=True, info="Higher values sample more low-probability tokens"),
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gr.Slider(label="Repetition penalty", value=1.0, minimum=1.0, maximum=2.0, step=0.1, interactive=True, info="Penalize repeated tokens"),
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gr.Slider(label="Number of similar sentences", value=10, minimum=1, maximum=20, step=1, interactive=True, info="Number of similar sentences to generate for each original sentence"),
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],
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outputs=
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title="SDG",
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description="AYE QABIL.",
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allow_flagging="never",
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text = ' '.join(df['Unnamed: 1'].astype(str))
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return text
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def save_to_csv(prompt, sentence, output, filename="synthetic_data.csv"):
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with open(filename, mode='a', newline='', encoding='utf-8') as file:
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writer = csv.writer(file)
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writer.writerow([prompt, sentence, output])
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def generate(file, prompt, temperature, max_new_tokens, top_p, repetition_penalty, num_similar_sentences):
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text = extract_text_from_excel(file)
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sentences = text.split('.')
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random.shuffle(sentences) # Shuffle sentences
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with tempfile.NamedTemporaryFile(mode='w', newline='', delete=False, suffix='.csv') as tmp:
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fieldnames = ['Prompt', 'Original Sentence', 'Generated Sentence']
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writer = csv.DictWriter(tmp, fieldnames=fieldnames)
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writer.writeheader()
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}
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try:
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stream = client.text_generation(prompt + sentence, **generate_kwargs, stream=True, details=True, return_full_text=False)
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output = ""
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for response in stream:
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output += response.token.text
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if not generated_sentences:
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break
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generated_sentence = generated_sentences.pop(random.randrange(len(generated_sentences)))
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writer.writerow({'Prompt': prompt, 'Original Sentence': sentence, 'Generated Sentence': generated_sentence})
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except Exception as e:
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print(f"Error generating data for sentence '{sentence}': {e}")
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tmp_path = tmp.name
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return tmp_path, output
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gr.Interface(
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fn=generate,
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inputs=[
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gr.File(label="Upload Excel File", file_count="single", file_types=[".xlsx"]),
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gr.Textbox(label="Prompt", placeholder="Enter your prompt here..."),
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gr.Slider(label="Temperature", value=0.9, minimum=0.0, maximum=1.0, step=0.05, interactive=True, info="Higher values produce more diverse outputs"),
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gr.Slider(label="Max new tokens", value=256, minimum=0, maximum=5120, step=64, interactive=True, info="The maximum numbers of new tokens"),
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gr.Slider(label="Top-p (nucleus sampling)", value=0.95, minimum=0.0, maximum=1, step=0.05, interactive=True, info="Higher values sample more low-probability tokens"),
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gr.Slider(label="Repetition penalty", value=1.0, minimum=1.0, maximum=2.0, step=0.1, interactive=True, info="Penalize repeated tokens"),
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gr.Slider(label="Number of similar sentences", value=10, minimum=1, maximum=20, step=1, interactive=True, info="Number of similar sentences to generate for each original sentence"),
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],
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outputs=[
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gr.File(label="Synthetic Data"),
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gr.Textbox(label="Generated Output")
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],
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title="SDG",
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description="AYE QABIL.",
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allow_flagging="never",
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