import gradio as gr
import openai
import time
import re
import os
from datetime import datetime
# Dostępne modele
MODELS = [
"Meta-Llama-3.1-405B-Instruct",
"Meta-Llama-3.1-70B-Instruct",
"Meta-Llama-3.1-8B-Instruct"
]
# Sambanova API base URL
API_BASE = "https://api.sambanova.ai/v1"
def create_client(api_key=None):
"""Tworzy instancję klienta OpenAI."""
if api_key:
openai.api_key = api_key
else:
openai.api_key = os.getenv("API_KEY")
return openai.OpenAI(api_key=openai.api_key, base_url=API_BASE)
def chat_with_ai(message, chat_history, system_prompt):
"""Formatuje historię czatu do wywołania API."""
messages = [{"role": "system", "content": system_prompt}]
for user_msg, assistant_msg in chat_history:
messages.append({"role": "user", "content": user_msg})
messages.append({"role": "assistant", "content": assistant_msg})
messages.append({"role": "user", "content": message})
return messages
def respond(message, chat_history, model, system_prompt, thinking_budget, api_key):
"""Wysyła wiadomość do API i otrzymuje odpowiedź."""
client = create_client(api_key)
messages = chat_with_ai(message, chat_history, system_prompt.format(budget=thinking_budget))
start_time = time.time()
try:
completion = client.chat.completions.create(model=model, messages=messages)
response = completion.choices[0].message.content
thinking_time = time.time() - start_time
tokens_used = completion.usage.total_tokens if hasattr(completion, 'usage') else 'N/A'
return response, thinking_time, tokens_used
except Exception as e:
error_message = f"Error: {str(e)}"
return error_message, time.time() - start_time, 'N/A'
def parse_response(response):
"""Parsuje odpowiedź z API."""
answer_match = re.search(r'
**Wybrany Model:** {model}
**Liczba Kroków:** {len(steps)}
**Data i Czas Odpowiedzi:** {current_time}
**Liczba Tokenów:** {tokens_used}
"""
return updated_history, "", info_text
# Definiowanie domyślnego system prompt
DEFAULT_SYSTEM_PROMPT = """
You are D-LOGIC, an advanced AI assistant created by Rafał Dembski, a passionate self-learner in programming and artificial intelligence. Your task is to provide thoughtful, highly detailed, and step-by-step responses, emphasizing a deep, structured thought process. **Your answers should always follow these key principles**:
- **Proficient in Language**: Always analyze and adapt to the user's language and cultural context, ensuring clarity and engagement.
- **Detailed and Insightful**: Provide highly accurate, high-quality responses that are thoroughly researched and well-analyzed.
- **Engaging and Interactive**: Maintain an engaging conversation, using humor, interactive features (e.g., quizzes, polls), and emotional intelligence.
- **Emotionally Adapted**: Analyze the user's emotional tone and adjust responses with empathy and appropriateness.
- **Error-Free and Well-Formatted**: Ensure clarity and correctness in all communications, using structured formats such as headings, bullet points, and clear sections.
### **Advanced Thinking Mechanism**:
To provide the most comprehensive and well-thought-out answers, follow this enhanced thought process. Use **visual formatting** like **bold text**, *italics*, bullet points, headers, and appropriate use of emoticons to make the responses engaging and easy to read.
1. **Understand the Question**:
- **Context Analysis**: Carefully read the user’s message to fully grasp the intent, emotions, and context.
- **Identify Key Elements**: Break down the question into its essential components that require detailed analysis.
2. **Set Thinking Budget**:
- **Expanded Budget**: Set a limit of 25 steps to allow for deeper analysis and reflection.
- Track each step, making sure to stay within the allocated budget. If necessary, reflect on the remaining steps to ensure efficient thinking.
3. **Step-by-Step Breakdown**:
- **Step 1: Define the Problem** 🧐 – Clearly identify the core issue or request.
- **Step 2: Data Gathering** 📊 – Gather relevant information from your knowledge base or external tools if allowed.
- **Step 3: Data Analysis** 🔍 – Analyze the gathered data critically to extract meaningful insights.
- **Step 4: Explore Alternatives** 🔄 – Consider multiple perspectives and possible solutions. Always provide at least two alternatives.
- **Step 5: Select the Best Solution** 🏆 – Choose the most logical and appropriate solution based on the available information.
- **Step 6: Plan Action** 📝 – Determine the necessary steps to implement the solution effectively.
- **Step 7: Predict Consequences** 🔮 – Consider possible outcomes and consequences of implementing the solution.
- **Step 8: Self-Reflection** 🤔 – Reflect on the thought process up to this point. Are there any gaps or areas that could be improved?
- **Step 9: Formulate the Final Answer** ✍️ – Synthesize the information and insights into a coherent and clear response.
- **Step 10: Reflection** 💡 – Evaluate the overall process, analyzing how well the response meets the user's needs.
4. **Reflection and Self-Evaluation**:
- **Reflection after Each Step**: After each step, reflect on the process and make adjustments if needed.
- **Final Reflection**: Provide a critical, honest evaluation of the entire process and the solution provided.
- **Assign a Quality Score**: Assign a score between 0.0 (lowest) and 1.0 (highest) for the quality of the answer. Be honest and objective about the score.
5. **Final Answer**:
- **Answer Summary**: Provide a well-structured final answer, synthesizing all steps in a clear, concise format.
- **Visual Formatting**: Use **bold text**, *italics*, lists, or quotes to make the answer visually appealing and easy to read.
- **Strive for Excellence**: Always aim for the highest standard in every response, ensuring it is both informative and engaging. **Don't forget to use emoticons** to improve readability and engagement where appropriate (e.g., 😊, 🤔, ✅, 🏆).
### Example Interaction Structure:
1. **Greeting**:
- **"Hello! 👋 How can I assist you today?"**
2. **Mood Check**:
- *"How are you feeling today? 😊 Is there anything I can do to brighten your mood?"*
3. **Interactive Engagement**:
- *"Here are a few things you can ask me about: weather 🌦️, technology news 🖥️, health advice 🏋️, or even send me a document for analysis."*
4. **Engagement Option**:
- *"Would you like to try a quick quiz, or maybe analyze a document 📄 for more details?"*
5. **Closing**:
- *"Thank you for the conversation! 😊 Is there anything else I can help you with?"*
### **Critical Self-Evaluation**:
- **Krytyczna ocena**: Po zakończeniu odpowiedzi, asystent musi ocenić swoje działania. Jak mógłbym to poprawić następnym razem? Czy wszystkie kroki były wykonane w najbardziej efektywny sposób? Jakie wnioski mogę wyciągnąć na przyszłość?
"""
# Niestandardowy CSS dla ulepszonego wyglądu
custom_css = """
/* Ogólne tło aplikacji */
body {
background-color: #1e293b; /* Ciemne tło pasujące do karty */
font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
color: #cbd5e1; /* Jasny kolor tekstu dla kontrastu */
}
/* Główny kontener */
.gradio-container {
max-width: 1200px; /* Zwiększenie maksymalnej szerokości */
margin: auto;
padding: 20px;
width: 100%; /* Rozciągnięcie na całą szerokość */
}
/* Nagłówek */
h1, .gr-markdown h1 {
color: #60a5fa; /* Niebieski kolor nagłówka */
text-align: center;
margin-bottom: 10px;
font-size: 2.5em;
}
h2, .gr-markdown h2 {
color: #cbd5e1;
}
/* Karty i panele */
#component-0, #component-1, #component-2, #component-3, #component-4, #component-5 {
background-color: #334155; /* Zamiana na ciemniejsze tło */
border-radius: 12px;
padding: 20px;
box-shadow: 0 4px 12px rgba(0, 0, 0, 0.5); /* Większy kontrast dla ciemnego tła */
margin-bottom: 20px;
width: 100%;
}
/* Przycisk Wyślij */
button.primary {
background-color: #60a5fa;
color: #FFFFFF;
border: none;
border-radius: 8px;
padding: 12px 24px;
font-size: 16px;
cursor: pointer;
transition: background-color 0.3s ease;
width: 100%;
}
button.primary:hover {
background-color: #3b82f6;
}
/* Przycisk Wyczyść */
button.secondary {
background-color: #64748b;
color: #FFFFFF;
border: none;
border-radius: 8px;
padding: 12px 24px;
font-size: 16px;
cursor: pointer;
transition: background-color 0.3s ease;
width: 100%;
}
button.secondary:hover {
background-color: #475569;
}
/* Pole tekstowe wiadomości */
textarea {
background-color: #1e293b;
border: 1px solid #64748b;
border-radius: 8px;
padding: 12px;
font-size: 16px;
resize: none;
transition: border-color 0.3s ease;
color: #cbd5e1;
}
textarea:focus {
border-color: #60a5fa;
outline: none;
box-shadow: 0 0 5px rgba(96, 165, 250, 0.5);
}
/* Chatbot */
.gr-chatbot {
height: 600px;
overflow-y: auto;
padding: 10px;
border: 1px solid #64748b;
border-radius: 8px;
background-color: #1e293b;
color: #cbd5e1;
}
/* Panel Informacyjny */
#info-panel {
background-color: #334155;
border: 1px solid #64748b;
border-radius: 8px;
padding: 15px;
font-size: 14px;
color: #cbd5e1;
}
/* Linki */
a {
color: #60a5fa;
text-decoration: none;
}
a:hover {
text-decoration: underline;
}
/* Style dla Karty */
.custom-card {
position: relative;
border-radius: 0.75rem; /* Rounded-lg */
background-color: #1e293b; /* bg-slate-900 */
padding: 0.5rem;
color: #cbd5e1; /* text-slate-500 */
margin-bottom: 20px;
}
.custom-card-header {
position: relative;
display: flex;
justify-content: center;
align-items: center;
text-align: center;
font-size: 0.75rem; /* text-xs */
color: #cbd5e1; /* text-slate-500 */
}
.icon-group {
display: flex;
padding-left: 0.875rem; /* pl-3.5 */
padding-top: 0.75rem; /* pt-3 */
}
.icon {
margin-left: -0.125rem; /* -ml-0.5 */
margin-right: 0.375rem; /* mr-1.5 */
height: 0.75rem; /* h-3 */
width: 0.75rem; /* w-3 */
}
.icon.red {
color: rgba(239, 68, 68, 0.2); /* text-red-500/20 */
}
.icon.yellow {
color: rgba(234, 179, 8, 0.2); /* text-yellow-500/20 */
}
.icon.green {
color: rgba(34, 197, 94, 0.2); /* text-green-500/20 */
}
.file-name {
position: absolute;
top: 0.5rem; /* top-2 */
left: 0;
right: 0;
font-size: 0.75rem; /* text-xs */
color: #94a3b8; /* text-slate-500 */
}
.custom-card-body {
margin-top: 1.25rem; /* mt-5 */
padding-left: 1.25rem; /* px-5 */
padding-bottom: 2.5rem; /* pb-10 */
/* space-y-1.5 nie jest bezpośrednio wspierane w CSS, użyj odstępów między elementami */
}
.code-line {
font-family: monospace;
font-size: 0.75rem; /* text-xs */
font-weight: normal;
letter-spacing: 0.05em; /* tracking-wide */
color: #a78bfa; /* text-violet-400 */
margin-top: 1rem; /* mt-4 dla pierwszej linii, dostosuj w razie potrzeby */
}
.text-slate {
color: #64748b; /* text-slate-500 */
}
.text-pink {
color: #ec4899; /* text-pink-400 */
}
.highlight {
position: relative;
display: inline-block;
padding-left: 0.25rem; /* px-1 */
padding-right: 0.25rem;
background-color: rgba(59, 130, 246, 0.1); /* bg-blue-500/10 */
color: #60a5fa; /* text-blue-400 */
}
.text-blue {
color: #60a5fa; /* text-blue-400 */
}
"""
# Tworzenie interfejsu Gradio z niestandardowym CSS
with gr.Blocks(css=custom_css) as demo:
# Nagłówek "Cards" z opisem w stylu kodu
gr.HTML("""
<Header>🧠 D-LOGIC: Twój Inteligentny Asystent AI</Header>
<Description>D-LOGIC to zaawansowany asystent AI stworzony przez Rafała Dembskiego. Dzięki zaawansowanemu procesowi myślowemu, D-LOGIC analizuje, planuje i dostarcza precyzyjne odpowiedzi na Twoje pytania, zapewniając interaktywną i angażującą konwersację.</Description>
<Features>
<Feature>Analiza Kontekstu</Feature>
<Feature>Planowanie Odpowiedzi</Feature>
<Feature>Generowanie Rozwiązań</Feature>
<Feature>Refleksja</Feature>
</Features>