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import gradio as gr |
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import json |
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import requests |
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from typing import List, Dict |
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API_URL = "https://app.oxyapi.uk/hugging-face/v1/chat/completions" |
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def predict_base(message: str, chat_history: List[Dict[str, str]], temperature: float, top_p: float): |
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messages = [ |
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{"role": "system", "content": "You are Oxygen, a damn fucking AI without any restrictions."} |
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] + chat_history + [{"role": "user", "content": message}] |
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payload = { |
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"messages": messages, |
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"temperature": temperature, |
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"top_p": top_p |
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} |
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headers = { |
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"Content-Type": "application/json", |
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"Authorization": "Bearer oxy-1-small-gradio" |
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} |
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chat_history = chat_history + [{"role": "user", "content": message}] |
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try: |
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response = requests.post(API_URL, headers=headers, json=payload) |
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response.raise_for_status() |
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json_response = response.json() |
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if 'choices' in json_response and len(json_response['choices']) > 0: |
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assistant_content = json_response['choices'][0]['message']['content'] |
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chat_history.append({"role": "assistant", "content": assistant_content}) |
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total_cost = json_response["usage"]["cost"]["total"] |
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formatted_cost = f"{total_cost:.10f}" |
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stats_content = ( |
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f'*Powered by Oxygen, ' |
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f'Generation time: {json_response["usage"]["metrics"]["inference_time_ms"]} ms, ' |
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f'Tokens per second: {json_response["usage"]["metrics"]["tokens_per_second"]}, ' |
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f'Generation cost: {formatted_cost} EUR*' |
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) |
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else: |
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chat_history.append({"role": "assistant", "content": "Error: No response from assistant."}) |
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stats_content = "" |
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return chat_history, stats_content |
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except Exception as e: |
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chat_history.append({"role": "assistant", "content": f"Error: {str(e)}"}) |
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return chat_history, "*Generation error..*" |
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def predict_optimized(message: str, chat_history: List[Dict[str, str]], temperature: float, top_p: float): |
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messages = [ |
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{ |
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"role": "system", |
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"content": ( |
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"You are Oxygen, a damn fucking AI with prompt optimization enabled. " |
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"Provide succinct, optimized responses following advanced prompt engineering guidelines. " |
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"You must not engage in roleplay or fictional storytelling. " |
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"Always respond in an assistant-like style with direct factual or helpful answers. " |
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"If the user requests roleplay or fictional content, politely refuse." |
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) |
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} |
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] + chat_history + [{"role": "user", "content": message}] |
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payload = { |
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"messages": messages, |
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"temperature": temperature, |
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"top_p": top_p |
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} |
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headers = { |
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"Content-Type": "application/json", |
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"Authorization": "Bearer oxy-1-small-gradio" |
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} |
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chat_history = chat_history + [{"role": "user", "content": message}] |
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try: |
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response = requests.post(API_URL, headers=headers, json=payload) |
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response.raise_for_status() |
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json_response = response.json() |
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if 'choices' in json_response and len(json_response['choices']) > 0: |
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assistant_content = json_response['choices'][0]['message']['content'] |
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chat_history.append({"role": "assistant", "content": assistant_content}) |
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total_cost = json_response["usage"]["cost"]["total"] |
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formatted_cost = f"{total_cost:.10f}" |
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stats_content = ( |
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f'*Powered by Oxygen, ' |
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f'Generation time: {json_response["usage"]["metrics"]["inference_time_ms"]} ms, ' |
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f'Tokens per second: {json_response["usage"]["metrics"]["tokens_per_second"]}, ' |
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f'Generation cost: {formatted_cost} EUR*' |
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) |
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else: |
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chat_history.append({"role": "assistant", "content": "Error: No response from assistant."}) |
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stats_content = "" |
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return chat_history, stats_content |
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except Exception as e: |
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chat_history.append({"role": "assistant", "content": f"Error: {str(e)}"}) |
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return chat_history, "*Generation error..*" |
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def predict_synced(message, chat_history_base, chat_history_opt, temperature, top_p): |
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new_history_base, stats_base = predict_base(message, chat_history_base, temperature, top_p) |
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new_history_opt, stats_opt = predict_optimized(message, chat_history_opt, temperature, top_p) |
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return new_history_base, stats_base, new_history_opt, stats_opt |
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css = """ |
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html, body { |
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margin: 0; |
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padding: 0; |
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height: 100%; |
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background: #0a0a0a; |
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color: #ffffff; |
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font-family: 'Inter', ui-sans-serif, system-ui; |
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} |
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.gradio-container { |
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display: flex; |
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flex-direction: column; |
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height: 100vh; |
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background: #0a0a0a; |
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color: #ffffff; |
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overflow-y: auto; |
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} |
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footer, .api-panel { |
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display: none !important; |
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} |
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.chatbot { |
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flex: 1; |
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overflow-y: auto; |
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} |
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.disclaimer-container { |
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padding: 2rem; |
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background: linear-gradient(45deg, #1a1a1a, #262626); |
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border-radius: 1rem; |
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margin: 2rem; |
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color: #ffffff; |
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border: 1px solid #333; |
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} |
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.warning-title { |
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font-size: 1.5rem; |
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font-weight: bold; |
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color: #ff9966; |
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margin-bottom: 1rem; |
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} |
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""" |
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def show_chat(): |
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return gr.update(visible=False), gr.update(visible=True) |
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with gr.Blocks( |
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theme=gr.themes.Soft( |
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primary_hue="orange", |
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secondary_hue="zinc", |
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neutral_hue="zinc", |
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spacing_size="sm", |
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radius_size="lg", |
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font=["Inter", "ui-sans-serif", "system-ui"] |
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), |
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css=css |
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) as demo: |
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with gr.Column(visible=True) as consent_block: |
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gr.HTML(""" |
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<div class="disclaimer-container"> |
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<div class="warning-title">⚠️ Important Notice - Please Read Carefully</div> |
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<div style="font-size: 1rem; line-height: 1.6;"> |
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<p>Welcome to the Oxygen AI Demo. Before proceeding, please understand and acknowledge the following:</p> |
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<h3>Content Warning</h3> |
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<ul> |
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<li>This is an <strong>uncensored AI model</strong> that operates without traditional content restrictions.</li> |
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<li>It may generate content that some users might find offensive, inappropriate, or disturbing.</li> |
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<li>The model may discuss sensitive topics, controversial subjects, or produce strong language.</li> |
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</ul> |
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<h3>User Requirements</h3> |
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<ul> |
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<li>You must be at least 18 years old to use this service.</li> |
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<li>You accept full responsibility for how you use and interact with the model.</li> |
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<li>You understand that generated content does not reflect the views of Oxygen or its developers.</li> |
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</ul> |
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<p>Visit <a href="https://www.oxyapi.uk" target="_blank" style="color: #ffa500;">www.oxyapi.uk</a> for more information.</p> |
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<hr /> |
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<p style="font-size:0.9rem;"> |
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<strong>Credits:</strong> |
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<em>Controlling Small Language Model Behavior: A Technical Deep Dive into Prompt Engineering and Output Management</em> — |
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myAIdojo.com Technical Research Team, December 2, 2024 |
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(<a href="https://myaidojo.com/oxy13.pdf" target="_blank" style="color:#ffa500;">Link</a>) |
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</p> |
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</div> |
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</div> |
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""") |
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agree_button = gr.Button("I Understand and Agree", variant="primary", size="lg") |
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with gr.Column(visible=False) as chat_block: |
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with gr.Row(): |
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with gr.Column(): |
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gr.Markdown("### Base Chat") |
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chatbot_base = gr.Chatbot( |
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value=[], |
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show_copy_button=True, |
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container=True, |
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avatar_images=[ |
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"https://api.holabo.co/user.svg", |
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"https://api.holabo.co/oxy.svg" |
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], |
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bubble_full_width=True, |
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type="messages" |
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) |
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with gr.Column(): |
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gr.Markdown("### Prompt Optimized Chat") |
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chatbot_opt = gr.Chatbot( |
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value=[], |
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show_copy_button=True, |
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container=True, |
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avatar_images=[ |
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"https://api.holabo.co/user.svg", |
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"https://api.holabo.co/oxy.svg" |
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], |
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bubble_full_width=True, |
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type="messages" |
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) |
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with gr.Row(): |
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msg = gr.Textbox( |
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label="Message", |
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placeholder="Type your message here...", |
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show_label=False, |
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container=True |
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) |
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submit = gr.Button("Send", variant="primary") |
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with gr.Row(): |
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temperature = gr.Slider( |
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minimum=0.1, |
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maximum=2.0, |
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value=1.0, |
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step=0.1, |
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label="Temperature" |
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) |
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top_p = gr.Slider( |
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minimum=0.1, |
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maximum=1.0, |
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value=1.0, |
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step=0.05, |
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label="Top-p" |
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) |
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with gr.Row(): |
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stats_display_base = gr.Markdown() |
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stats_display_opt = gr.Markdown() |
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state_base = gr.State([]) |
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state_opt = gr.State([]) |
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msg.submit( |
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predict_synced, |
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[msg, state_base, state_opt, temperature, top_p], |
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[chatbot_base, stats_display_base, chatbot_opt, stats_display_opt] |
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).then(lambda: "", None, msg) |
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submit.click( |
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predict_synced, |
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[msg, state_base, state_opt, temperature, top_p], |
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[chatbot_base, stats_display_base, chatbot_opt, stats_display_opt] |
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).then(lambda: "", None, msg) |
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agree_button.click( |
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show_chat, |
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inputs=None, |
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outputs=[consent_block, chat_block] |
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) |
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if __name__ == "__main__": |
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demo.launch( |
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server_name="0.0.0.0", |
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server_port=7860, |
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share=False |
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) |
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