Update app.py
Browse files
app.py
CHANGED
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@@ -1,15 +1,13 @@
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import gradio as gr
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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import re
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# ==================== CHARGEMENT DU MODÈLE ====================
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print("🔄 Chargement du modèle...")
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model = AutoModelForCausalLM.from_pretrained(
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"padufour/mistral-accor-emails",
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torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
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device_map="auto",
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low_cpu_mem_usage=True
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)
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@@ -21,7 +19,6 @@ print("✅ Modèle chargé et prêt !")
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def generate_email(email_type, client_name, company, objective,
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segment, priority, history, style, language):
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# Construire le prompt
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prompt = f"""### Instruction : Rédige un email du type "{email_type}" pour un client professionnel. L'email doit être complet, sans placeholder ni crochet [], et ne doit PAS mentionner le segment de clientèle dans le contenu.
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### Input :
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### Réponse :"""
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inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
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)
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email = tokenizer.decode(outputs[0], skip_special_tokens=True)
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# Extraire la réponse
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if "### Réponse :" in email:
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email = email.split("### Réponse :")[1].strip()
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@@ -66,11 +60,9 @@ Important: Ne pas inclure de placeholders [], ne pas mentionner le segment, ne p
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email = re.sub(r'at\s+[\w\.-]+@[\w\.-]+\.\w+', '', email)
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email = re.sub(r'or\s+\+?\d[\d\s\(\)\-\.]+', '', email)
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# Ajouter signature
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if "ACCOR Team" not in email and "Accor Team" not in email:
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email += "\n\nBest regards,\nThe ACCOR Team"
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# Nettoyer espaces
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email = re.sub(r'\n\s*\n\s*\n', '\n\n', email)
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email = re.sub(r' +', ' ', email)
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@@ -95,34 +87,29 @@ with gr.Blocks(theme=gr.themes.Soft(), title="ACCOR Email Generator") as demo:
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email_type = gr.Dropdown(
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choices=["Newsletter", "New offers", "theme", "solution", "Hotel opening"],
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value="Newsletter",
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label="Email Type *"
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info="Type of marketing campaign"
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)
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segment = gr.Dropdown(
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choices=["MICE", "AHBO", "leisure group"],
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value="MICE",
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label="Segment"
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info="Customer segment (used internally, not displayed)"
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)
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gr.Markdown("### 👤 Client Information")
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client_name = gr.Textbox(
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label="Client Name *",
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placeholder="Marie Dupont",
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value="Marie Dupont"
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)
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company = gr.Textbox(
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label="Company *",
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placeholder="Event Solutions SA",
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value="Event Solutions SA"
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)
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objective = gr.Textbox(
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label="Objective *",
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placeholder="Promote winter events",
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value="Promote winter events",
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lines=2
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)
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history = gr.Textbox(
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label="Client History",
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placeholder="New customer",
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value="New customer"
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)
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style = gr.Textbox(
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label="Style",
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placeholder="Professional and engaging",
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value="Professional and engaging"
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)
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lines=25,
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show_copy_button=True
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)
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gr.Markdown(
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"""
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---
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**Model:** [padufour/mistral-accor-emails](https://huggingface.co/padufour/mistral-accor-emails)
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**Tips for best results:**
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- Provide detailed objectives
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- Specify client history for personalization
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- Use descriptive style preferences
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"""
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)
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# Exemples
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gr.Markdown("### 💡 Quick Examples")
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gr.Examples(
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examples=[
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["Newsletter", "Marie Dupont", "Event Solutions SA", "Promote winter events", "MICE", "High", "Long-term client", "Professional and warm", "ENGLISH"],
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["New offers", "Pierre Martin", "Travel Agency Plus", "Showcase summer destinations", "leisure group", "Medium", "Regular customer", "Friendly
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["theme", "Sophie Laurent", "Corporate Events Ltd", "Present emerging trends in 2025", "MICE", "High", "Industry leader", "Modern and innovative", "ENGLISH"],
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["solution", "Thomas Bernard", "Business Travel Corp", "Promote loyalty program benefits", "AHBO", "High", "Frequent traveler", "Professional and convincing", "ENGLISH"],
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],
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inputs=[email_type, client_name, company, objective, segment, priority, history, style, language],
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outputs=output,
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cache_examples=False,
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)
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# Event
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generate_btn.click(
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fn=generate_email,
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inputs=[email_type, client_name, company, objective, segment, priority, history, style, language],
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outputs=output
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)
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# Lancer
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demo.launch()
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import gradio as gr
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import re
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# ==================== CHARGEMENT DU MODÈLE ====================
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print("🔄 Chargement du modèle...")
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# VERSION SIMPLE SANS QUANTIZATION
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model = AutoModelForCausalLM.from_pretrained(
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"padufour/mistral-accor-emails",
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low_cpu_mem_usage=True
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)
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def generate_email(email_type, client_name, company, objective,
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segment, priority, history, style, language):
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prompt = f"""### Instruction : Rédige un email du type "{email_type}" pour un client professionnel. L'email doit être complet, sans placeholder ni crochet [], et ne doit PAS mentionner le segment de clientèle dans le contenu.
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### Input :
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### Réponse :"""
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inputs = tokenizer(prompt, return_tensors="pt")
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outputs = model.generate(
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**inputs,
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max_new_tokens=800,
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temperature=0.7,
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top_p=0.9,
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top_k=50,
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repetition_penalty=1.1,
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do_sample=True,
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pad_token_id=tokenizer.pad_token_id,
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eos_token_id=tokenizer.eos_token_id
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)
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email = tokenizer.decode(outputs[0], skip_special_tokens=True)
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if "### Réponse :" in email:
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email = email.split("### Réponse :")[1].strip()
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email = re.sub(r'at\s+[\w\.-]+@[\w\.-]+\.\w+', '', email)
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email = re.sub(r'or\s+\+?\d[\d\s\(\)\-\.]+', '', email)
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if "ACCOR Team" not in email and "Accor Team" not in email:
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email += "\n\nBest regards,\nThe ACCOR Team"
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email = re.sub(r'\n\s*\n\s*\n', '\n\n', email)
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email = re.sub(r' +', ' ', email)
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email_type = gr.Dropdown(
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choices=["Newsletter", "New offers", "theme", "solution", "Hotel opening"],
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value="Newsletter",
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label="Email Type *"
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)
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segment = gr.Dropdown(
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choices=["MICE", "AHBO", "leisure group"],
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value="MICE",
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label="Segment"
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)
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gr.Markdown("### 👤 Client Information")
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client_name = gr.Textbox(
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label="Client Name *",
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value="Marie Dupont"
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)
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company = gr.Textbox(
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label="Company *",
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value="Event Solutions SA"
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)
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objective = gr.Textbox(
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label="Objective *",
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value="Promote winter events",
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lines=2
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)
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history = gr.Textbox(
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label="Client History",
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value="New customer"
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)
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style = gr.Textbox(
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label="Style",
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value="Professional and engaging"
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)
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lines=25,
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show_copy_button=True
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)
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gr.Examples(
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examples=[
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["Newsletter", "Marie Dupont", "Event Solutions SA", "Promote winter events", "MICE", "High", "Long-term client", "Professional and warm", "ENGLISH"],
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["New offers", "Pierre Martin", "Travel Agency Plus", "Showcase summer destinations", "leisure group", "Medium", "Regular customer", "Friendly", "ENGLISH"],
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],
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inputs=[email_type, client_name, company, objective, segment, priority, history, style, language],
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outputs=output,
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cache_examples=False,
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)
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generate_btn.click(
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fn=generate_email,
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inputs=[email_type, client_name, company, objective, segment, priority, history, style, language],
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outputs=output
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)
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demo.launch()
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