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Update app.py
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app.py
CHANGED
@@ -96,15 +96,16 @@ sp.Load("dungen_dev_preview.model")
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model = tf.keras.models.load_model("dungen_dev_preview_model.keras")
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max_seq_len = 25
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# Logging setup
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CSV_FILE = "flagged_outputs.csv"
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if not os.path.exists(CSV_FILE):
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with open(CSV_FILE, "w", newline="", encoding="utf-8") as csvfile: #added encoding
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writer = csv.writer(csvfile)
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writer.writerow(["Timestamp", "Flagged Text"])
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logging.basicConfig(filename="app.log", level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
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def generate_text(seed_text, next_words=30, temperature=0.5):
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seed_text = seed_text.strip().lower()
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@@ -151,12 +152,17 @@ def generate_text(seed_text, next_words=30, temperature=0.5):
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return decoded
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def flag_output(
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timestamp = datetime.now().isoformat()
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return "Output Flagged. Thank you for your feedback."
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with gr.Blocks() as demo:
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model = tf.keras.models.load_model("dungen_dev_preview_model.keras")
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max_seq_len = 25
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logging.basicConfig(filename="app.log", level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
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# Dataset setup
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FLAGGED_DATASET_ID = "InfinitodeLTD/DungenDev-FlaggedOutputs" # Replace with your dataset ID
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try:
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flagged_dataset = load_dataset(FLAGGED_DATASET_ID)
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except:
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flagged_dataset = Dataset.from_dict({"Timestamp": [], "Prompt": [], "Flagged Text": []})
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flagged_dataset.push_to_hub(FLAGGED_DATASET_ID)
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def generate_text(seed_text, next_words=30, temperature=0.5):
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seed_text = seed_text.strip().lower()
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return decoded
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def flag_output(prompt_used, text_flagged):
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if not text_flagged.strip(): # Check for empty or whitespace-only strings
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return "Cannot flag an empty output."
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logging.info(f"Output flagged: {text_flagged} with prompt: {prompt_used}")
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timestamp = datetime.now().isoformat()
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new_data = {"Timestamp": [timestamp], "Prompt": [prompt_used], "Flagged Text": [text_flagged]}
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new_dataset = Dataset.from_dict(new_data)
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global flagged_dataset
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flagged_dataset = Dataset.from_pandas(flagged_dataset.to_pandas().append(new_dataset.to_pandas(), ignore_index=True))
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flagged_dataset.push_to_hub(FLAGGED_DATASET_ID)
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return "Output Flagged. Thank you for your feedback."
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with gr.Blocks() as demo:
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