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Update app.py
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app.py
CHANGED
@@ -46,6 +46,7 @@ AVAILABLE_MODELS = {
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"nous-hermes": {"description": "Nous Hermes (fine-tune of Mistral)", "speed": "Fast"},
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"openchat": {"description": "OpenChat 3.5 (fine-tune of Mistral)", "speed": "Fast"},
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}
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# Diverse Names Dataset
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DIVERSE_NAMES = [
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@@ -116,7 +117,7 @@ def chat(system, prompt, selected_model_name, seed=None, num_exchanges=5):
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follow_up_prompt_messages = [
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{"role": "system", "content": "You are a helpful and engaging assistant. Based on the last assistant response, generate a polite, open-ended, and cute follow-up question or statement from a user to keep a friendly conversation going. Make it relevant to the last message and consistent with a 'cute' and positive tone."},
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{"role": "assistant", "content": ai_response_content}, # Use the last AI response as context
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{"role": "user", "content": "Generate
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]
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human_follow_up_obj = client.chat.completions.create(
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@@ -306,7 +307,7 @@ def generate_and_display_conversations(num_conversations_input, custom_prompts_i
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# --- Auto-push main conversations to Hugging Face Dataset ---
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# Use the custom commit message
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commit_message = f"{commit_subject.strip()}\n\n{commit_body.strip()}" if commit_body.strip() else commit_subject.strip()
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push_status = push_file_to_huggingface_dataset(DATA_FILE, "
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generation_log.append(push_status)
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generation_log.append(f"Process complete at {datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')} (An Nhơn, Binh Dinh, Vietnam)")
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@@ -664,8 +665,7 @@ with gr.Blocks() as demo:
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f"`{HF_DATASET_REPO_ID}` using a Hugging Face token securely stored as a Space Secret (`HF_TOKEN`). "
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"User tokens are not required."
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)
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gr.Markdown(f"Current server time: {current_datetime_vietnam} (An Nhơn, Binh Dinh, Vietnam)")
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# Launch the Gradio app
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"nous-hermes": {"description": "Nous Hermes (fine-tune of Mistral)", "speed": "Fast"},
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"openchat": {"description": "OpenChat 3.5 (fine-tune of Mistral)", "speed": "Fast"},
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}
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current_datetime_vietnam = datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=7))).strftime('%Y-%m-%d %H:%M:%S %Z%z')
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# Diverse Names Dataset
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DIVERSE_NAMES = [
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follow_up_prompt_messages = [
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{"role": "system", "content": "You are a helpful and engaging assistant. Based on the last assistant response, generate a polite, open-ended, and cute follow-up question or statement from a user to keep a friendly conversation going. Make it relevant to the last message and consistent with a 'cute' and positive tone."},
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{"role": "assistant", "content": ai_response_content}, # Use the last AI response as context
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{"role": "user", "content": "Generate friendly follow-up question/statement (max 700 words)."}
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]
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human_follow_up_obj = client.chat.completions.create(
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# --- Auto-push main conversations to Hugging Face Dataset ---
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# Use the custom commit message
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commit_message = f"{commit_subject.strip()}\n\n{commit_body.strip()}" if commit_body.strip() else commit_subject.strip()
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push_status = push_file_to_huggingface_dataset(DATA_FILE, f"data/conversations_{current_datetime_vietnam}.jsonl", commit_message)
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generation_log.append(push_status)
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generation_log.append(f"Process complete at {datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')} (An Nhơn, Binh Dinh, Vietnam)")
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f"`{HF_DATASET_REPO_ID}` using a Hugging Face token securely stored as a Space Secret (`HF_TOKEN`). "
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"User tokens are not required."
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)
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gr.Markdown(f"Current server time: {current_datetime_vietnam} (An Nhơn, Binh Dinh, Vietnam)")
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# Launch the Gradio app
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