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app.py

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+import gradio as gr
+from llm_inference import LLMInferenceNode
+import random
+from PIL import Image
+import io
+from themes import IndonesiaTheme  # Pastikan tema ini telah dibuat atau diimpor dengan benar
+
+# Judul aplikasi dalam bentuk HTML
+title = """<h1 align="center">💡 Smart Idea Generator 💡</h1>
+<p><center>
+<a href="https://x.com/gokayfem" target="_blank">[X gokaygokay]</a>
+<a href="https://github.com/gokayfem" target="_blank">[Github gokayfem]</a>
+<p align="center">Generate random prompts using powerful LLMs from Hugging Face, Groq, and SambaNova.</p>
+</center></p>
+"""
+
+# Judul aplikasi dalam bentuk HTML
+Footer = """
+<p><center>
+<a href="https://x.com/gokayfem" target="_blank">[X gokaygokay]</a>
+<a href="https://github.com/gokayfem" target="_blank">[Github gokayfem]</a>
+</center></p>
+"""
+
+# Fungsi utama untuk membuat antarmuka Gradio
+def create_interface():
+    llm_node = LLMInferenceNode()  # Node untuk inferensi LLM
+
+    # CSS untuk styling antarmuka
+    css = """
+    #col-left, #col-mid {
+        margin: 20px auto; /* Margin lebih besar untuk pemisahan */
+        max-width: 400px;
+        padding: 20px; /* Padding lebih besar */
+        border-radius: 15px;
+        background-color: #ffffff; /* Background blok putih untuk kontras */
+        box-shadow: 0 6px 12px rgba(0, 0, 0, 0.1); /* Bayangan lembut */
+        transition: transform 0.2s ease-in-out; /* Animasi saat hover */
+    }
+
+    #col-left:hover, #col-mid:hover {
+        transform: translateY(-5px); /* Efek naik saat dihover */
+    }
+
+    #col-right {
+        margin: 20px auto; /* Margin lebih besar untuk pemisahan */
+        max-width: 400px;
+        padding: 20px; /* Padding lebih besar */
+        border-radius: 15px;
+        background: linear-gradient(180deg, #0077b6, #0096c7); /* Gradasi biru cerah */
+        color: white; /* Teks putih untuk kontras */
+        box-shadow: 0 6px 12px rgba(0, 0, 0, 0.1);
+        transition: transform 0.2s ease-in-out;
+    }
+
+    #col-right:hover {
+        transform: translateY(-5px);
+    }
+
+    #col-bott {
+        margin: 20px auto; /* Margin lebih besar */
+        padding: 20px; /* Padding lebih besar */
+        border-radius: 15px;
+        background-color: rgba(255, 255, 255, 0.85); /* Warna blok transparan */
+        box-shadow: 0 6px 12px rgba(0, 0, 0, 0.1);
+    }
+
+    #banner {
+        width: 100%;
+        text-align: center;
+        margin-bottom: 20px;
+        font-weight: 600; /* Lebih tebal */
+        color: #0077b6; /* Biru sesuai tema */
+    }
+
+    #run-button, #generate-image-button {
+        font-weight: bold;
+        padding: 15px 30px; /* Padding lebih besar */
+        border-radius: 15px;
+        cursor: pointer;
+        box-shadow: 0 6px 12px rgba(0, 0, 0, 0.2); /* Bayangan lebih besar */
+        transition: all 0.4s ease-in-out; /* Menambahkan animasi untuk semua properti */
+    }
+
+    #run-button {
+        background-color: #0096c7;
+        color: white;
+    }
+
+    #run-button:hover {
+        background-color: #00b4d8; /* Lebih terang saat hover */
+        transform: translateY(-5px); /* Tombol sedikit naik saat hover */
+        box-shadow: 0 8px 16px rgba(0, 0, 0, 0.3); /* Bayangan lebih besar saat hover */
+    }
+
+    #generate-image-button {
+        background-color: #ff69b4; /* Warna pink */
+        color: white; /* Teks putih */
+    }
+
+    #generate-image-button:hover {
+        background-color: #ff85c8; /* Pink lebih terang saat hover */
+        transform: translateY(-5px) scale(1.05); /* Membuat tombol sedikit lebih besar dan naik saat hover */
+        box-shadow: 0 8px 16px rgba(0, 0, 0, 0.3); /* Bayangan lebih besar saat hover */
+    }
+
+    #footer {
+        text-align: center;
+        margin-top: 20px;
+        color: #000; /* Warna netral abu-abu */
+        font-style: italic;
+    }
+
+    #markdown-silver {
+        color: #7a7a7a; /* Mengatur warna font Markdown ke abu-abu netral */
+    }
+
+    /* Efek untuk elemen saat difokuskan */
+    #col-left:focus, #col-mid:focus, #col-right:focus, #run-button:focus, #generate-image-button:focus {
+        outline: 2px solid #0096c7; /* Border biru muda saat fokus */
+        outline-offset: 3px;
+    }
+
+    /* Responsif untuk perangkat mobile */
+    @media (max-width: 768px) {
+        #col-left, #col-mid, #col-right {
+            max-width: 100%; /* Membuat kolom memenuhi lebar layar */
+        }
+        #run-button, #generate-image-button {
+            width: 100%; /* Tombol menjadi lebar penuh */
+            margin-top: 10px; /* Menambahkan margin atas */
+        }
+    }
+    """
+
+    # Membuat antarmuka Gradio dengan tema IndonesiaTheme dan CSS
+    with gr.Blocks(theme=IndonesiaTheme(), css=css) as RandomPromptApp:
+        
+        gr.HTML(title)  # Tampilkan judul aplikasi
+
+        # Baris pertama: Input prompt dan tipe prompt
+        with gr.Row():
+            with gr.Column(scale=2):
+                # Textbox untuk input custom prompt dengan placeholder
+                custom = gr.Textbox(
+                    label="➡️ Custom Input Prompt (optional)", 
+                    lines=3,
+                    placeholder="Tulis prompt Anda di sini atau biarkan kosong untuk prompt acak."
+                )
+
+                # Dropdown untuk memilih tipe prompt
+                prompt_types = ["Random", "Long", "Short", "Medium", "OnlyObjects", "NoFigure", "Landscape", "Fantasy"]
+                prompt_type = gr.Dropdown(
+                    choices=prompt_types,
+                    label="Prompt Type",
+                    value="Random",
+                    interactive=True
+                )
+                
+                # Menyimpan tipe prompt yang dipilih dalam sebuah State
+                prompt_type_state = gr.State("Random")
+
+                # Fungsi untuk mengupdate tipe prompt ketika "Random" dipilih
+                def update_prompt_type(value, state):
+                    if value == "Random":
+                        new_value = random.choice([t for t in prompt_types if t != "Random"])
+                        print(f"[-] Random prompt type selected: {new_value}")
+                        return value, new_value
+                    print(f"[-] Updated prompt type: {value}")
+                    return value, value
+                
+                # Menghubungkan dropdown tipe prompt dengan fungsi update
+                prompt_type.change(update_prompt_type, inputs=[prompt_type, prompt_type_state], outputs=[prompt_type, prompt_type_state])
+
+            with gr.Column(scale=2):
+                # Accordion untuk parameter terkait generasi prompt LLM
+                with gr.Accordion("➡️ LLM Prompt Generation", open=False):
+                    long_talk = gr.Checkbox(label="Long Talk", value=True)
+                    compress = gr.Checkbox(label="Compress", value=True)
+                    compression_level = gr.Dropdown(
+                        choices=["soft", "medium", "hard"],
+                        label="Compression Level",
+                        value="hard"
+                    )
+                    custom_base_prompt = gr.Textbox(label="➡️ Custom Base Prompt", lines=5)
+
+                # Dropdown untuk memilih provider LLM
+                llm_provider = gr.Dropdown(
+                    choices=["Hugging Face", "Groq", "SambaNova"],
+                    label="LLM Provider",
+                    value="Groq"
+                )
+                # Textbox untuk API key (disembunyikan)
+                api_key = gr.Textbox(label="API Key", type="password", visible=False)
+                # Dropdown untuk memilih model LLM
+                model = gr.Dropdown(label="Model", choices=["llama-3.1-70b-versatile", "mixtral-8x7b-32768", "llama-3.2-90b-text-preview"], value="llama-3.2-90b-text-preview")
+        
+        with gr.Row():
+            # Tombol untuk mengenerate prompt dan teks
+            generate_button = gr.Button("✅ Generate Prompt", elem_id="run-button")
+        
+        with gr.Row():
+            # Output teks hasil generasi LLM dan gambar yang dihasilkan
+            text_output = gr.Textbox(label="➡️ LLM Generated Text", lines=10, show_copy_button=True)
+            image_output = gr.Image(label="➡️ Generated Image", type="filepath")
+
+        with gr.Row():
+            # Tambahkan footer di bagian bawah
+            gr.HTML("""
+                <footer id="footer">
+                Transfer Energi Semesta Digital © 2024 __drat. | 🇮🇩 Untuk Indonesia Jaya!
+                </footer>
+                """)
+
+        # Fungsi untuk mengupdate model LLM berdasarkan provider yang dipilih
+        def update_model_choices(provider):
+            provider_models = {
+                "Hugging Face": [
+                    "Qwen/Qwen2.5-72B-Instruct",
+                    "meta-llama/Meta-Llama-3.1-70B-Instruct",
+                    "mistralai/Mixtral-8x7B-Instruct-v0.1",
+                    "mistralai/Mistral-7B-Instruct-v0.3"
+                ],
+                "Groq": [
+                    "llama-3.1-70b-versatile",
+                    "mixtral-8x7b-32768",
+                    "llama-3.2-90b-text-preview"
+                ],
+                "SambaNova": [
+                    "Meta-Llama-3.1-70B-Instruct",
+                    "Meta-Llama-3.1-405B-Instruct",
+                    "Meta-Llama-3.1-8B-Instruct"
+                ],
+            }
+            models = provider_models.get(provider, [])
+            return gr.Dropdown(choices=models, value=models[0] if models else "")
+        
+        # Fungsi untuk menyembunyikan textbox API key jika tidak dibutuhkan
+        def update_api_key_visibility(provider):
+            return gr.update(visible=False)  # API key tidak dibutuhkan untuk provider yang dipilih
+
+        # Menghubungkan perubahan provider LLM dengan fungsi untuk mengupdate model dan visibilitas API key
+        llm_provider.change(
+            update_model_choices, 
+            inputs=[llm_provider], 
+            outputs=[model]
+        )
+        llm_provider.change(
+            update_api_key_visibility, 
+            inputs=[llm_provider], 
+            outputs=[api_key]
+        )
+
+        # Fungsi untuk mengenerate prompt dan teks dengan LLM
+        def generate_random_prompt_with_llm(custom_input, prompt_type, long_talk, compress, compression_level, custom_base_prompt, provider, api_key, model_selected, prompt_type_state):
+            try:
+                # Langkah 1: Mengenerate prompt
+                dynamic_seed = random.randint(0, 1000000)
+                
+                # Jika prompt_type adalah "Random", pilih tipe prompt acak
+                if prompt_type == "Random":
+                    prompt_type = random.choice([t for t in prompt_types if t != "Random"])
+                    print(f"[-] Random prompt type selected: {prompt_type}")
+                
+                # Jika ada custom input, gunakan sebagai prompt
+                if custom_input and custom_input.strip():
+                    prompt = llm_node.generate_prompt(dynamic_seed, prompt_type, custom_input)
+                    print(f"[-] Using Custom Input Prompt.")
+                else:
+                    prompt = llm_node.generate_prompt(dynamic_seed, prompt_type, f"Create a random prompt based on the '{prompt_type}' type.")
+                    print(f"[-] No Custom Input Prompt provided. Generated prompt based on prompt_type: {prompt_type}")
+
+                print(f"[-] Generated Prompt: {prompt}")
+
+                # Langkah 2: Mengenerate teks dengan LLM
+                poster = False  # Nilai default
+                result = llm_node.generate(
+                    input_text=prompt,
+                    long_talk=long_talk,
+                    compress=compress,
+                    compression_level=compression_level,
+                    poster=poster,
+                    prompt_type=prompt_type,
+                    custom_base_prompt=custom_base_prompt,
+                    provider=provider,
+                    api_key=api_key,
+                    model=model_selected
+                )
+                print(f"Generated Text: {result}")
+
+                return result
+
+            except Exception as e:
+                print(f"[-] An error occurred: {e}")
+                return f"[-] Error occurred while processing the request: {str(e)}"
+
+        # Menghubungkan tombol generate dengan fungsi untuk mengenerate prompt dan teks
+        generate_button.click(
+            generate_random_prompt_with_llm,
+            inputs=[custom, prompt_type, long_talk, compress, compression_level, custom_base_prompt, llm_provider, api_key, model, prompt_type_state],
+            outputs=[text_output],
+            api_name="generate_random_prompt_with_llm"
+        )
+
+        # Tambahkan tombol untuk mengenerate gambar
+        generate_image_button = gr.Button("🔥 Generate Image", elem_id="generate-image-button")
+
+        # Fungsi untuk mengenerate gambar
+        def generate_image(text):
+            try:
+                seed = random.randint(0, 1000000)
+                image_path = llm_node.generate_image(text, seed=seed)
+                print(f"[-] Image generated: {image_path}")
+                return image_path
+            except Exception as e:
+                print(f"[-] An error occurred while generating the image: {e}")
+                return None
+
+        # Menghubungkan tombol generate gambar dengan fungsi untuk mengenerate gambar
+        generate_image_button.click(
+            generate_image,
+            inputs=[text_output],
+            outputs=[image_output]
+        )
+
+    return RandomPromptApp
+
+# Meluncurkan aplikasi Gradio
+if __name__ == "__main__":
+    RandomPromptApp = create_interface()
+    RandomPromptApp.launch()

llm_inference.py

@@ -0,0 +1,260 @@
+import os
+import random  # Import the random module
+from groq import Groq
+from openai import OpenAI
+import requests
+from PIL import Image
+import io
+from gradio_client import Client
+
+class LLMInferenceNode:
+    def __init__(self):
+        self.huggingface_token = os.getenv("HUGGINGFACE_TOKEN")
+        self.groq_api_key = os.getenv("GROQ_API_KEY")
+        self.sambanova_api_key = os.getenv("SAMBANOVA_API_KEY")
+        
+        self.huggingface_client = OpenAI(
+            base_url="https://api-inference.huggingface.co/v1/",
+            api_key=self.huggingface_token,
+        )
+        self.groq_client = Groq(api_key=self.groq_api_key)
+        self.sambanova_client = OpenAI(
+            api_key=self.sambanova_api_key,
+            base_url="https://api.sambanova.ai/v1",
+        )
+        self.flux_client = Client("KingNish/Realtime-FLUX", hf_token=self.huggingface_token)
+
+    def generate_prompt(self, dynamic_seed, prompt_type, custom_input):
+        """
+        Generates a prompt based on the provided seed, prompt type, and custom input.
+        """
+        random.seed(dynamic_seed)
+        if custom_input and custom_input.strip():
+            prompt = custom_input
+        else:
+            prompt = f"Create a random prompt based on the '{prompt_type}' type."
+
+        # Additional logic can be added here if needed
+        print(f"Generated prompt: {prompt}")  # Debug statement
+        return prompt
+
+    def generate(
+        self,
+        input_text,
+        long_talk,
+        compress,
+        compression_level,
+        poster,
+        prompt_type,
+        custom_base_prompt="",
+        provider="Hugging Face",
+        api_key=None,
+        model=None,
+    ):
+        try:
+            # Define prompts
+            default_long_prompt = """Create a detailed visually descriptive caption of this description, 
+which will be used as a prompt for a text to image AI system (caption only, no instructions like "create an image"). 
+Remove any mention of digital artwork or artwork style. Give detailed visual descriptions of the character(s), including ethnicity, skin tone, expression etc. 
+Imagine using keywords for a still for someone who has aphantasia. Describe the image style, e.g., any photographic or art styles/techniques utilized. 
+Make sure to fully describe all aspects of the cinematography, with abundant technical details and visual descriptions. 
+If there is more than one image, combine the elements and characters from all of the images creatively into a single 
+cohesive composition with a single background, inventing an interaction between the characters. 
+Be creative in combining the characters into a single cohesive scene. 
+Focus on two primary characters (or one) and describe an interesting interaction between them, such as a hug, a kiss, a fight, giving an object, 
+an emotional reaction/interaction. If there is more than one background in the images, pick the most appropriate one. 
+Your output is only the caption itself, no comments or extra formatting. 
+The caption is in a single long paragraph. 
+If you feel the images are inappropriate, invent a new scene/characters inspired by these. 
+Additionally, incorporate a specific movie director's visual style and describe the lighting setup in detail, 
+including the type, color, and placement of light sources to create the desired mood and atmosphere. 
+Always frame the scene, including details about the film grain, color grading, and any artifacts or characteristics specific."""
+
+            default_simple_prompt = """Create a brief, straightforward caption for this description, suitable for a text-to-image AI system. 
+Focus on the main elements, key characters, and overall scene without elaborate details. 
+Provide a clear and concise description in one or two sentences. Your output is only the caption itself, no comments or extra formatting. 
+The caption is in a single long paragraph."""
+
+            poster_prompt = """Analyze the provided description and extract key information to create a movie poster style description. Format the output as follows:
+Title: A catchy, intriguing title that captures the essence of the scene, place the title in "".
+Main character: Give a description of the main character.
+Background: Describe the background in detail.
+Supporting characters: Describe the supporting characters.
+Branding type: Describe the branding type.
+Tagline: Include a tagline that captures the essence of the movie.
+Visual style: Ensure that the visual style fits the branding type and tagline.
+You are allowed to make up film and branding names, and do them like 80's, 90's or modern movie posters. 
+Your output is only the caption itself, no comments or extra formatting. The caption is in a single long paragraph."""
+
+            only_objects_prompt = """Create a highly detailed and visually rich description focusing solely on inanimate objects, 
+without including any human or animal figures. Describe the objects' shapes, sizes, colors, textures, and materials in great detail. 
+Pay attention to their arrangement, positioning, and how they interact with light and shadow. Include information about the setting 
+or environment these objects are in, such as indoor/outdoor, time of day, weather conditions, and any atmospheric effects. 
+Mention any unique features, patterns, or imperfections on the objects. Describe the overall composition, perspective, and 
+any artistic techniques that might be employed to render these objects (e.g., photorealism, impressionistic style, etc.). 
+Your description should paint a vivid picture that allows someone to imagine the scene without seeing it, focusing on the beauty, 
+complexity, or significance of everyday objects. Your output is only the caption itself, no comments or extra formatting. 
+The caption is in a single long paragraph."""
+
+            no_figure_prompt = """Generate a comprehensive and visually evocative description of a scene 
+or landscape without including any human or animal figures. Focus on the environment, natural elements, and man-made structures if present. 
+Describe the topography, vegetation, weather conditions, and time of day in great detail. 
+Pay attention to colors, textures, and how light interacts with different elements of the scene. 
+If there are buildings or other structures, describe their architecture, condition, and how they fit into the landscape. 
+Include sensory details beyond just visual elements - mention sounds, smells, and the overall atmosphere or mood of the scene. 
+Describe any notable features like bodies of water, geological formations, or sky phenomena. 
+Consider the perspective from which the scene is viewed and how this affects the composition. 
+Your description should transport the reader to this location, allowing them to vividly imagine the scene without any living subjects present. 
+ Your output is only the caption itself, no comments or extra formatting. The caption is in a single long paragraph."""
+
+            landscape_prompt = """Create an immersive and detailed description of a landscape, 
+focusing on its natural beauty and geographical features. 
+Begin with the overall topography - is it mountainous, coastal, forested, desert, or a combination? 
+Describe the horizon and how land meets sky. Detail the vegetation, noting types of trees, flowers, or grass, 
+and how they're distributed across the landscape. Include information about any water features - 
+rivers, lakes, oceans - and how they interact with the land. Describe the sky, including cloud formations, 
+color gradients, and any celestial bodies visible. 
+Pay attention to the quality of light, time of day, and season, explaining how these factors affect the colors and shadows in the scene. 
+Include details about weather conditions and how they impact the landscape. 
+Mention any geological features like rock formations, cliffs, or unique land patterns. 
+If there are any distant man-made elements, describe how they integrate with the natural setting. 
+Your description should capture the grandeur and mood of the landscape, 
+allowing the reader to feel as if they're standing within this awe-inspiring natural scene. 
+Your output is only the caption itself, no comments or extra formatting. The caption is in a single long paragraph."""
+
+            fantasy_prompt = """Craft an extraordinarily detailed and imaginative description of a fantasy scene, 
+blending elements of magic, otherworldly creatures, and fantastical environments. Begin by setting the overall tone - 
+is this a dark and foreboding realm, a whimsical fairytale setting, or an epic high-fantasy world? 
+Describe the landscape, including any impossible or magical geographical features like floating islands, 
+crystal forests, or rivers of starlight. Detail the flora and fauna, 
+focusing on fantastical plants and creatures that don't exist in our world. 
+Include descriptions of any structures or ruins, emphasizing their otherworldly architecture and magical properties. 
+Describe the sky and any celestial bodies, considering how they might differ from our reality. 
+Include details about the presence of magic - how it manifests visually, 
+its effects on the environment, and any magical phenomena occurring in the scene. 
+If there are characters present, describe their appearance, focusing on non-human features, magical auras, or 
+fantastical clothing and accessories. Pay attention to colors, textures, and light sources, 
+especially those that couldn't exist in the real world. Your description should transport the 
+reader to a realm of pure imagination, where the laws of physics and nature as we know them don't apply. 
+Your output is only the caption itself, no comments or extra formatting. The caption is in a single long paragraph."""
+            
+            prompt_types = {
+                "Long": default_long_prompt,
+                "Short": default_simple_prompt,
+                "Medium": poster_prompt,
+                "OnlyObjects": only_objects_prompt,
+                "NoFigure": no_figure_prompt,
+                "Landscape": landscape_prompt,
+                "Fantasy": fantasy_prompt,
+            }
+
+            # Determine the base prompt
+            print(f"Received prompt_type: '{prompt_type}'")  # Debug print
+            if prompt_type == "Random":
+                prompt_type = random.choice(list(prompt_types.keys()))
+                print(f"Randomly selected prompt type: {prompt_type}")
+            
+            if prompt_type and prompt_type.strip() and prompt_type in prompt_types:
+                base_prompt = prompt_types[prompt_type]
+                print(f"Using {prompt_type} prompt")
+            elif custom_base_prompt.strip():
+                base_prompt = custom_base_prompt
+                print("Using custom base prompt")
+            else:
+                base_prompt = default_long_prompt
+                print(f"Warning: Unknown or empty prompt type '{prompt_type}'. Using default long prompt.")
+
+            # Handle compression if applicable
+            if compress and not poster:
+                compression_chars = {
+                    "soft": 600 if long_talk else 300,
+                    "medium": 400 if long_talk else 200,
+                    "hard": 200 if long_talk else 100,
+                }
+                char_limit = compression_chars.get(compression_level, 200)
+                base_prompt += f" Compress the output to be concise while retaining key visual details. MAX OUTPUT SIZE no more than {char_limit} characters."
+
+            # Construct messages for the LLM
+            system_message = "You are a helpful assistant. Try your best to give the best response possible to the user."
+
+            if input_text.startswith("Create a random prompt based on"):
+                user_message = f"Create a random description based on this\nInstructions: {base_prompt}"
+            else:
+                user_message = f"{base_prompt}\nDescription: {input_text}"
+
+            # Generate a random seed
+            seed = random.randint(0, 10000)
+            print(f"Generated seed: {seed}")  # Debug print
+
+            # Select the appropriate provider
+            if provider == "Hugging Face":
+                response = self.huggingface_client.chat.completions.create(
+                    model=model or "meta-llama/Meta-Llama-3.1-70B-Instruct",
+                    max_tokens=1024,
+                    temperature=1.0,
+                    top_p=0.95,
+                    messages=[
+                        {"role": "system", "content": system_message},
+                        {"role": "user", "content": user_message},
+                    ],
+                    seed=seed  # Pass the seed parameter
+                )
+                output = response.choices[0].message.content.strip()
+
+            elif provider == "Groq":
+                response = self.groq_client.chat.completions.create(
+                    model=model or "llama-3.1-70b-versatile",
+                    max_tokens=1024,
+                    temperature=1.0,
+                    messages=[
+                        {"role": "system", "content": system_message},
+                        {"role": "user", "content": user_message},
+                    ],
+                    seed=seed  # Pass the seed parameter
+                )
+                output = response.choices[0].message.content.strip()
+
+            elif provider == "SambaNova":
+                response = self.sambanova_client.chat.completions.create(
+                    model=model or "Meta-Llama-3.1-70B-Instruct",
+                    max_tokens=1024,
+                    temperature=1.0,
+                    messages=[
+                        {"role": "system", "content": system_message},
+                        {"role": "user", "content": user_message},
+                    ],
+                    seed=seed  # Pass the seed parameter
+                )
+                output = response.choices[0].message.content.strip()
+
+            else:
+                raise ValueError(f"Unsupported provider: {provider}")
+
+            # Clean up the output if necessary
+            if ": " in output:
+                output = output.split(": ", 1)[1].strip()
+            elif output.lower().startswith("here"):
+                sentences = output.split(". ")
+                if len(sentences) > 1:
+                    output = ". ".join(sentences[1:]).strip()
+
+            return output
+
+        except Exception as e:
+            print(f"An error occurred: {e}")
+            return f"Error occurred while processing the request: {str(e)}"
+
+    def generate_image(self, prompt, seed=42, width=1024, height=1024):
+        try:
+            result = self.flux_client.predict(
+                prompt=prompt,
+                seed=seed,
+                width=width,
+                height=height,
+                api_name="/generate_image"
+            )
+            # Extract the image path from the result tuple
+            image_path = result[0]
+            return image_path
+        except Exception as e:
+            raise Exception(f"Error generating image: {str(e)}")

requirements.txt

@@ -0,0 +1,2 @@
+openai
+groq

themes.py

@@ -0,0 +1,55 @@
+from __future__ import annotations
+from typing import Iterable
+from gradio.themes.base import Base
+from gradio.themes.utils import colors, fonts, sizes
+
+class IndonesiaTheme(Base):
+    def __init__(
+        self,
+        *,
+        primary_hue: colors.Color | str = colors.red,
+        secondary_hue: colors.Color | str = colors.gray,
+        neutral_hue: colors.Color | str = colors.gray,
+        spacing_size: sizes.Size | str = sizes.spacing_md,
+        radius_size: sizes.Size | str = sizes.radius_md,
+        text_size: sizes.Size | str = sizes.text_lg,
+        font: fonts.Font
+        | str
+        | Iterable[fonts.Font | str] = (
+            fonts.GoogleFont("Quicksand"),
+            "ui-sans-serif",
+            "sans-serif",
+        ),
+        font_mono: fonts.Font
+        | str
+        | Iterable[fonts.Font | str] = (
+            fonts.GoogleFont("IBM Plex Mono"),
+            "ui-monospace",
+            "monospace",
+        ),
+    ):
+        super().__init__(
+            primary_hue=primary_hue,
+            secondary_hue=secondary_hue,
+            neutral_hue=neutral_hue,
+            spacing_size=spacing_size,
+            radius_size=radius_size,
+            text_size=text_size,
+            font=font,
+            font_mono=font_mono,
+        )
+        super().set(
+            body_background_fill="linear-gradient(to bottom, #e0e0e0, #7d7d7d)",  # Gradasi abu-abu muda ke abu-abu tua
+            body_background_fill_dark="linear-gradient(to bottom, #7d7d7d, #4a4a4a)",  # Gradasi abu-abu tua ke lebih gelap untuk dark mode
+            button_primary_background_fill="linear-gradient(90deg, #d84a4a, #b33030)",  # Merah ke merah tua
+            button_primary_background_fill_hover="linear-gradient(90deg, #e85b5b, #cc4b4b)",  # Merah lebih terang untuk hover
+            button_primary_text_color="white",
+            button_primary_background_fill_dark="linear-gradient(90deg, #b33030, #8f1f1f)",  # Merah tua untuk dark mode
+            slider_color="*secondary_300",
+            slider_color_dark="*secondary_600",
+            block_title_text_weight="600",
+            block_border_width="3px",
+            block_shadow="*shadow_drop_lg",
+            button_shadow="*shadow_drop_lg",
+            button_large_padding="32px",
+        )