Respan Dataset Explorer

User: hi, how are you?
User: hi, how are you?
Assistant:

Hello! I'm doing well, thank you. How can I assist you today?

I want to ask you how to make your own ai

Making your own AI can range from simple projects to very complex systems depending on what you want to achieve. Here’s a general guide to get you started:

### 1. Define Your Goal
- **What kind of AI?** (e.g., chatbot, image recognition, recommendation system)
- **What problem will it solve?**

### 2. Learn the Basics
- **Programming languages:** Python is the most popular for AI.
- **Mathematics:** Linear algebra, calculus, probability, and statistics.
- **Machine Learning concepts:** Supervised/unsupervised learning, neural networks, etc.

### 3. Choose Your Tools and Frameworks
- **Libraries:** TensorFlow, PyTorch, scikit-learn, Keras
- **Data processing:** Pandas, NumPy

### 4. Gather and Prepare Data
- AI models need data to learn.
- Find datasets online (Kaggle, UCI Machine Learning Repository) or collect your own data.
- Clean and preprocess data (handle missing values, normalization, encoding).

### 5. Build a Model
- Start simple: linear regression, decision trees, or simple neural networks.
- Use frameworks to define the architecture of your model.
- Train the model on your dataset.

### 6. Evaluate and Improve
- Use metrics like accuracy, precision, recall to evaluate.
- Tune hyperparameters, try different models, or get more data to improve.

### 7. Deploy Your AI
- Create APIs using Flask or FastAPI.
- Integrate AI into applications or services.

---

### Example: Build a Simple AI Classifier in Python
```python
from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import accuracy_score

# Load dataset
iris = load_iris()
X, y = iris.data, iris.target

# Split into train and test sets
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)

# Create and train model
model = RandomForestClassifier()
model.fit(X_train, y_train)

# Predict and evaluate
y_pred = model.predict(X_test)
print("Accuracy:", accuracy_score(y_test, y_pred))
```

---

If you want to make a more advanced AI (like a neural network, chatbot, or language model), I can guide you through that too. Just let me know!

I want to make a exact replica of chat got 4 but with offline

Creating an *exact replica* of ChatGPT-4 that works offline is an extremely challenging task because:

- **GPT-4 is a proprietary, large-scale model** developed by OpenAI, involving billions of parameters and trained on massive datasets with immense computational resources (hundreds of GPUs over weeks or months).
- **GPT-4 weights and training code are not publicly available**, so you cannot simply download the model and run it offline.
- Running a model of similar size requires very powerful hardware (often multiple high-end GPUs or TPUs), which is expensive and not easily accessible to most individuals.

---

### What you *can* do to create a capable offline chatbot AI:

#### 1. Use Open-Source Large Language Models (LLMs)
There are several open-source models inspired by GPT-3 and GPT-4 that you can run offline on reasonably powerful hardware. Examples include:

- **GPT-J (6B parameters)** by EleutherAI
- **GPT-NeoX (20B parameters)** by EleutherAI
- **LLaMA (7B, 13B models)** by Meta AI (if you obtain the license)
- **Alpaca**, **Vicuna**, **StableLM**, or **BLOOM**

These models are smaller (though some still require strong GPUs), open source, and can be fine-tuned or used as-is to create chatbot-like agents offline.

#### 2. Hardware Requirements
- For models like GPT-J or GPT-NeoX: a GPU with 24GB+ VRAM is recommended (e.g., NVIDIA RTX 3090, 4090).
- Smaller LLaMA or Alpaca models can run on fewer resources but may sacrifice performance and accuracy.
- For CPU-only inference, even smaller models are needed, and performance will be slow.

#### 3. Software and Tools
You can use these frameworks and tools:

- **Transformers library by Hugging Face:** to load and run models easily.
- **Text generation frameworks:** e.g., `text-generation-webui` enables easy hosting with a web interface.
- **LLaMA.cpp**: a C++ optimized runtime to run LLaMA models on CPU efficiently.

#### 4. Steps to set up an offline chatbot similar to ChatGPT

1. **Pick a model**: e.g., GPT-J, LLaMA 7B, or Vicuna (an instruction-tuned LLaMA variant).
2. **Download the pre-trained weights**: from official or community repositories.
3. **Install dependencies**: Python, PyTorch/TensorFlow, Transformers library.
4. **Run inference scripts**: load the model and use a prompt to generate replies.
5. **Optionally, fine-tune or instruction-tune**: to improve chatbot-like behavior.
6. **Create an interface**: CLI, web app, or integrate with desktop apps.

---

### Example: Running GPT-J Offline Using Hugging Face Transformers (very basic)

```bash
pip install transformers torch
```

```python
from transformers import GPTJForCausalLM, AutoTokenizer
import torch

tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-j-6B")
model = GPTJForCausalLM.from_pretrained("EleutherAI/gpt-j-6B")

prompt = "Hello, how are you today?"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_length=100)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```

*Note: You need a GPU with enough VRAM to load this 6B parameter model.*

---

### Summary

| Aspect             | GPT-4 (OpenAI)         | Open Source Offline Models            |
|--------------------|------------------------|--------------------------------------|
| Access             | API only (paid)        | Download weights and run locally     |
| Size               | 175+ billion params    | 6 billion (GPT-J) to 20+ billion (GPT-NeoX), LLaMA variants |
| Hardware needed    | Very powerful clusters | High-end desktop GPUs for best speed |
| Licensing          | Proprietary            | Mostly permissive licenses            |
| Performance        | State-of-the-art       | Good but below GPT-4                  |
| Ease of Use        | Easy via API           | Requires setup and technical skills  |

---

### Resources to start

- [EleutherAI GPT-J](https://github.com/kingoflolz/mesh-transformer-jax/)
- [Hugging Face Models Hub](https://huggingface.co/models)
- [text-generation-webui](https://github.com/oobabooga/text-generation-webui)
- [LLaMA.cpp project](https://github.com/ggerganov/llama.cpp)

---

If you want, I can guide you through setting up one of these open-source models step-by-step for offline use. Just tell me your hardware specs and preferences!

is there any other ai that I can download and give it my name and make it offline uder 700 gb

Yes! If your goal is to have an offline AI chatbot personalized with your name and running within a storage limit of **under 700 GB**, there are definitely options—especially using some of the newer, smaller open-source large language models (LLMs).

---

### What You Can Do:

#### 1. Choose Smaller Open-Source Models

Many open-source LLMs are now available that balance model size, performance, and hardware requirements. Some fit well within your 700 GB storage limit while still providing strong chatbot capabilities.

Examples that fit your size requirement:

- **LLaMA models (7B, 13B)** – Meta AI's LLaMA models are very popular for local usage.
- **Vicuna (7B, 13B)** – Instruction-tuned LLaMA variants optimized for chat.
- **Alpaca (7B)** – Smaller, tuned model based on LLaMA.
- **GPT-J (6B)** – Good-quality open model, about 20GB size.
- **StableLM (7B)** – OpenAI-style open-source LLM.
- **MPT-7B** (MosaicML) – An open, efficient 7 billion parameter model.

Typically, a **7B parameter model** requires roughly 13-14 GB in 16-bit precision on disk. So you can easily fit multiple models or supporting files within 700 GB.

---

#### 2. How to “Give it Your Name” / Personalize

- These models can be prompted to respond with your preferred name or personalities by adding context or instructions in the prompt.

Example prompt to the AI:

```
You are a helpful assistant named [YourName]. Always respond as [YourName] would.
User: Hi, who are you?
```

- For deeper personalization, you can **fine-tune** or **instruction-tune** the model on custom data containing your name and style — but this requires more technical know-how and some computing resources.

---

#### 3. Deploy Offline Chatbot on Your PC

- Use user-friendly projects like **text-generation-webui** that allow you to run and chat with these models on your local machine via a simple webpage interface.
- The web UI supports Vicuna, LLaMA, GPT-J, MPT, and many others.

---

### Example Setup Overview:

- You download a 7B model (~14 GB).
- Download the tokenizer and supporting files (a few GB).
- Clone and set up **text-generation-webui** (small install).
- Run the model on your GPU or even CPU (slower).
- Edit the startup prompt or system prompt so the bot uses your name.

---

### Hardware & Software Recommendations:

| Component         | Notes                                |
|-------------------|------------------------------------|
| GPU               | At least 10-16 GB VRAM recommended |
| RAM               | 16+ GB RAM recommended             |
| Storage           | Under 700 GB fits comfortably      |
| OS                | Windows/Linux/macOS                 |
| Software          | Python 3.8+, PyTorch, text-generation-webui |

---

### Example: Download Vicuna 7B & run locally

- Vicuna 7B weights are about 5-7 GB in 4-bit quantized form.
- You can download the model from Hugging Face (after agreeing to terms).
- Run with the text-generation-webui https://github.com/oobabooga/text-generation-webui

Command to launch:
```bash
python server.py --model vicuna-7b
```

Then access the interface at `http://localhost:5000` in your browser.

You can customize the initial prompt or add a system message:
```
You are a chatbot named [YourName]. Always say your name when greeting.
```

---

### Summary:

- You **can** run a good offline chatbot personalized with your name under 700 GB.
- Use open source models like LLaMA, Vicuna, Alpaca, or GPT-J.
- Use tools like text-generation-webui to easily interact locally.
- Personalize with prompt instructions or custom fine-tuning.

---

If you want detailed step-by-step instructions tailored for your system (like GPU model, OS, etc.) or help with prompt personalization, just share your setup!

     Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers de (ISO 639), en respectant le contexte culinaire.

    Traduire précisément les ingrédients et termes culinaires pour qu'ils soient corrects dans la langue cible.
    Maintenir la structure JSON intacte, en ne modifiant que les valeurs.
    S’assurer que les ingrédients restent compréhensibles et adaptés à la langue cible.

    Return Format
    Tu dois renvoyer une liste d’objets sous la forme reçu.
    - Chaque valeur doit être correctement traduite en de.
    - Les ingrédients doivent être adaptés à la langue cible.
    - Aucune clé ne doit être modifiée.

    Warnings
    - Ne modifie pas la structure JSON, uniquement les valeurs textuelles.
    - Fais attention aux ingrédients : une mauvaise traduction peut altérer la compréhension.
    - Ne laisse aucune valeur non traduite.
    - Ne renvoie que le JSON, sans explication.

    Context Dump
    Langue source : en (ISO 639)
    Langue cible : de (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "c8bf2797bec545f1acb13b0b4ed0e285",
    "updated": "2025-05-17T08:28:58.326Z",
    "title": "Sautéed Pickled Green Beans",
    "subtitle": "Fasulye Turşusu Kavurması",
    "description": "This quick sauté features soft-cooked onions and tomatoes that provide a sweet contrast to crispy, tangy pickled green beans. At Okyanus Balık Evi, a fish restaurant in Sinop on the Black Sea, this dish is typically served as an appetizer alongside hot slices of griddled corn bread. It also pairs well with roasted meats.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "olive oil",
          "onion, coarsely chopped (mounded (59.147 ml)).",
          "1- to (50.8 mm) lengths everyday green bean pickles or store-bought pickled beans, drained",
          "ripe, juicy tomato, coarsely chopped, or canned tomatoes, coarsely chopped",
          "turkish or other crushed red pepper flakes, or taste",
          "water or pickle brine, if needed",
          "fine sea salt (optional)."
        ]
      }
    ],
    "instructions": [
      "Heat the olive oil in an 8-inch skillet over medium heat. Add the onions and sauté, stirring, until they start to curl at the edges and turn golden.",
      "Add the pickled beans, tomato, and red pepper flakes, then cook, stirring, until the red pepper becomes fragrant and the tomatoes begin to soften without breaking down completely, about 2 to 3 minutes. If the mixture starts sticking to the pan, add 1 to 2 tablespoons of water or pickle brine, up to 4 tablespoons as needed. Season with salt to taste and serve hot."
    ],
    "notes_ingredients": "You will need 2 cups of pickled green beans (homemade or store-bought). Pickled green tomatoes can also be a tasty addition. If fresh tomatoes are out of season, canned tomatoes work well as a substitute.",
    "notes_instructions": "For an extra tangy flavor, add a few spoonfuls of pickle brine to the vegetables while cooking."
  }
]

    

```json
[
  {
    "recipeCode": "c8bf2797bec545f1acb13b0b4ed0e285",
    "updated": "2025-05-17T08:28:58.326Z",
    "title": "Gebratene eingelegte grüne Bohnen",
    "subtitle": "Fasulye Turşusu Kavurması",
    "description": "Dieses schnelle Gericht enthält weich gegarte Zwiebeln und Tomaten, die einen süßen Kontrast zu knusprigen, würzigen eingelegten grünen Bohnen bieten. Im Okyanus Balık Evi, einem Fischrestaurant in Sinop am Schwarzen Meer, wird dieses Gericht typischerweise als Vorspeise zusammen mit heißen Scheiben gegrilltem Maisbrot serviert. Es passt auch gut zu Braten.",
    "ingredients": [
      {
        "section": "Für das Rezept",
        "ingredients": [
          "Olivenöl",
          "Zwiebel, grob gehackt (gehäuft (59,147 ml))",
          "1- bis (50,8 mm) lange eingelegte grüne Bohnen oder gekaufte eingelegte Bohnen, abgetropft",
          "reife, saftige Tomate, grob gehackt, oder Dosentomaten, grob gehackt",
          "türkische oder andere zerstoßene Paprikaflocken, nach Geschmack",
          "Wasser oder Essiggurkenlake, falls nötig",
          "feines Meersalz (optional)"
        ]
      }
    ],
    "instructions": [
      "Erhitzen Sie das Olivenöl in einer 20-cm-Pfanne bei mittlerer Hitze. Fügen Sie die Zwiebeln hinzu und sautieren Sie sie unter Rühren, bis die Ränder sich kräuseln und goldgelb werden.",
      "Fügen Sie die eingelegten Bohnen, die Tomate und die Paprikaflocken hinzu und kochen Sie unter Rühren, bis die Paprika aromatisch wird und die Tomaten zu erweichen beginnen, ohne vollständig zu zerfallen, etwa 2 bis 3 Minuten. Wenn die Mischung zu kleben beginnt, fügen Sie 1 bis 2 Esslöffel Wasser oder Essiggurkenlake hinzu, bis zu 4 Esslöffel nach Bedarf. Nach Geschmack mit Salz abschmecken und heiß servieren."
    ],
    "notes_ingredients": "Sie benötigen 2 Tassen eingelegte grüne Bohnen (hausgemacht oder gekauft). Eingelegte grüne Tomaten können ebenfalls eine schmackhafte Ergänzung sein. Wenn frische Tomaten außerhalb der Saison sind, sind Dosentomaten ein guter Ersatz.",
    "notes_instructions": "Für einen besonders säuerlichen Geschmack fügen Sie während des Kochens ein paar Löffel Essiggurkenlake zu den Gemüsen hinzu."
  }
]
```

اريد تقليل المسافة بين الرصيد العددي وكلمة الرصيد:
Row(
                          mainAxisSize: MainAxisSize.min,
                          textDirection: TextDirection.rtl,
                          children: [
                            Text(
                              textDirection: TextDirection.rtl,
                              'الرصيد: ',
                              style: TextStyle(
                                fontSize: 16,
                                fontWeight: FontWeight.w600,
                                fontFamily: tajawalFont,
                                color: lightColorScheme.onSurface,
                              ),
                            ),
                            Container(
                              width: 60, // ضبط العرض هنا مثال (يمكنك تغييره)
                              child: Text(
                                _formatWithThousandsSeparator(_currentBalance),
                                style: TextStyle(
                                  fontSize: 16,
                                  fontWeight: FontWeight.bold,
                                  fontFamily: tajawalFont,
                                  color: lightColorScheme.onSurface,
                                ),
                                maxLines: 1,
                                overflow: TextOverflow.ellipsis,
                                textDirection: TextDirection.ltr,
                              ),
                            ),
                          ],
                        ),

لتقليل المسافة بين كلمة "الرصيد:" والرصيد العددي في ترتيب **Row** في Flutter، يمكنك التحكم في **التباعد بين العناصر** بعدة طرق:

### 1. إزالة أي padding أو margin زائدة
تأكد أن النصوص والـ Container داخلهم لا تحتوي على حواف padding أو margin غير ضرورية تزيد المسافة.

### 2. تقليل عرض الـ Container (أو استبداله بـ SizedBox)
في حالتك، لديك `Container` بعرض 60 وهذا قد يسبب وجود مساحة فارغة بين النصين.

يمكنك استبدال الـ `Container` بـ `SizedBox` لتحديد العرض بدقة أو إزالة العرض تمامًا إذا لم يكن لديك حاجة لتحديد العرض.

### 3. استخدم `SizedBox` مع عرض أصغر (أو حتى استبدله بنص عادي)
أمثلة:

```dart
Row(
  mainAxisSize: MainAxisSize.min,
  textDirection: TextDirection.rtl,
  children: [
    Text(
      'الرصيد: ',
      style: TextStyle(
        fontSize: 16,
        fontWeight: FontWeight.w600,
        fontFamily: tajawalFont,
        color: lightColorScheme.onSurface,
      ),
      textDirection: TextDirection.rtl,
    ),
    // إما نص فقط بدون Container أو SizedBox
    Text(
      _formatWithThousandsSeparator(_currentBalance),
      style: TextStyle(
        fontSize: 16,
        fontWeight: FontWeight.bold,
        fontFamily: tajawalFont,
        color: lightColorScheme.onSurface,
      ),
      maxLines: 1,
      overflow: TextOverflow.ellipsis,
      textDirection: TextDirection.ltr,
    ),
  ],
)
```

أو في حال كنت تريد تحديد عرض لجعل الاحتمالية أقل للالتفاف يمكنك مثلا:

```dart
SizedBox(
  width: 50, // تقليل العرض لتقليل المسافة
  child: Text(
    _formatWithThousandsSeparator(_currentBalance),
    style: TextStyle(
      fontSize: 16,
      fontWeight: FontWeight.bold,
      fontFamily: tajawalFont,
      color: lightColorScheme.onSurface,
    ),
    maxLines: 1,
    overflow: TextOverflow.ellipsis,
    textDirection: TextDirection.ltr,
  ),
),
```

### 4. استخدام `Text.rich` لجمع النص في Widget واحد
بدلاً من `Row` يمكنك استخدام Text.rich لجعل النص "الرصيد: 123456" كفئة واحدة تتحكم بها بشكل أدق، وهذا سيقلل المسافة بشكل طبيعي:

```dart
Text.rich(
  TextSpan(
    text: 'الرصيد: ',
    style: TextStyle(
      fontSize: 16,
      fontWeight: FontWeight.w600,
      fontFamily: tajawalFont,
      color: lightColorScheme.onSurface,
    ),
    children: [
      TextSpan(
        text: _formatWithThousandsSeparator(_currentBalance),
        style: TextStyle(
          fontSize: 16,
          fontWeight: FontWeight.bold,
          fontFamily: tajawalFont,
          color: lightColorScheme.onSurface,
        ),
      ),
    ],
  ),
  textDirection: TextDirection.rtl,
)
```

### خلاصة:
- جرب إزالة الـ `Container` أو تقليل عرضه.
- استخدم `SizedBox` بعرض أقل.
- أفضل حل هو استخدام `Text.rich` لتجميع النصوص بكفاءة مع تحكم كامل في الأساليب والمسافات.

إذا تريد مساعدة إضافية لتجربة أي من تلك الطرق، بس أخبرني!

اريد اضافة مسافة من الاعلى
Row(
                          mainAxisSize: MainAxisSize.min,
                          textDirection: TextDirection.rtl,
                          children: [
                            Text(
                              textDirection: TextDirection.rtl,
                              'الرصيد: ',
                              style: TextStyle(
                                fontSize: 16,
                                fontWeight: FontWeight.w600,
                                fontFamily: tajawalFont,
                                color: lightColorScheme.onSurface,
                              ),
                            ),
                            SizedBox(
                              width: 49, // تقليل العرض لتقليل المسافة
                              child: Text(
                                _formatWithThousandsSeparator(_currentBalance),
                                style: TextStyle(
                                  fontSize: 15,
                                  fontWeight: FontWeight.bold,
                                  fontFamily: tajawalFont,
                                  color: lightColorScheme.onSurface,
                                ),
                                maxLines: 1,
                                overflow: TextOverflow.ellipsis,
                                textDirection: TextDirection.ltr,
                              ),
                            ),
                          ],
                        ),

لإضافة مسافة من الأعلى للـ `Row` في Flutter، يمكنك استخدام إحدى الطرق التالية:

### 1. استخدام `Padding` مع `EdgeInsets.only(top: ...)`

غلف الـ `Row` بـ `Padding` وحدد المسافة التي تريدها من الأعلى، مثلاً:

```dart
Padding(
  padding: const EdgeInsets.only(top: 10.0), // تعديل القيمة حسب المسافة المطلوبة
  child: Row(
    mainAxisSize: MainAxisSize.min,
    textDirection: TextDirection.rtl,
    children: [
      Text(
        'الرصيد: ',
        style: TextStyle(
          fontSize: 16,
          fontWeight: FontWeight.w600,
          fontFamily: tajawalFont,
          color: lightColorScheme.onSurface,
        ),
        textDirection: TextDirection.rtl,
      ),
      SizedBox(
        width: 49,
        child: Text(
          _formatWithThousandsSeparator(_currentBalance),
          style: TextStyle(
            fontSize: 15,
            fontWeight: FontWeight.bold,
            fontFamily: tajawalFont,
            color: lightColorScheme.onSurface,
          ),
          maxLines: 1,
          overflow: TextOverflow.ellipsis,
          textDirection: TextDirection.ltr,
        ),
      ),
    ],
  ),
);
```

### 2. استخدام `Container` مع خاصية `margin`

يمكن استخدام `margin` بنفس الطريقة:

```dart
Container(
  margin: const EdgeInsets.only(top: 10.0), // المسافة من الأعلى
  child: Row(
    mainAxisSize: MainAxisSize.min,
    textDirection: TextDirection.rtl,
    children: [
      // نفس المحتوى
    ],
  ),
);
```

---

**النصيحة:** غالباً الأفضل استخدام `Padding` إذا تريد إضافة الفراغ داخل العنصر، و`margin` إذا تريد التحكم بالفراغ خارجه.

إذا أردت مساعدة إضافية أو شرح أو اختلاف في المسافات، فقط أخبرني!

اريد دالة للتعامل مع الارقام الكبيرة واختصارها الى رقم مع حرف
Container(
                          padding: const EdgeInsets.only(top: 5.5),
                          child: Row(
                            mainAxisSize: MainAxisSize.min,
                            textDirection: TextDirection.rtl,
                            children: [
                              Text(
                                textDirection: TextDirection.rtl,
                                'الرصيد: ',
                                style: TextStyle(
                                  fontSize: 16,
                                  fontWeight: FontWeight.w600,
                                  fontFamily: tajawalFont,
                                  color: lightColorScheme.onSurface,
                                ),
                              ),
                              SizedBox(
                                width: 49, // تقليل العرض لتقليل المسافة
                                child: Text(
                                  _formatWithThousandsSeparator(
                                    _currentBalance,
                                  ),
                                  style: TextStyle(
                                    fontSize: 15,
                                    fontWeight: FontWeight.bold,
                                    fontFamily: tajawalFont,
                                    color: lightColorScheme.onSurface,
                                  ),
                                  maxLines: 1,
                                  overflow: TextOverflow.ellipsis,
                                  textDirection: TextDirection.ltr,
                                ),
                              ),
                            ],
                          ),
                        ),

يمكنك كتابة دالة في Dart تقوم بتحويل الأرقام الكبيرة إلى صيغة مختصرة مع حرف يشير للوحدة (مثل K للألف، M للمليون، B للمليار) بالشكل التالي:

```dart
String formatNumberWithSuffix(num number) {
  if (number >= 1000000000) {
    return (number / 1000000000).toStringAsFixed(1).replaceAll(RegExp(r"\.0$"), "") + "B";
  } else if (number >= 1000000) {
    return (number / 1000000).toStringAsFixed(1).replaceAll(RegExp(r"\.0$"), "") + "M";
  } else if (number >= 1000) {
    return (number / 1000).toStringAsFixed(1).replaceAll(RegExp(r"\.0$"), "") + "K";
  } else {
    return number.toString();
  }
}
```

### طريقة الاستخدام مع كودك:

بدل استخدام `_formatWithThousandsSeparator(_currentBalance)` استعمل الدالة الجديدة مثل:

```dart
Text(
  formatNumberWithSuffix(_currentBalance),
  style: TextStyle(
    fontSize: 15,
    fontWeight: FontWeight.bold,
    fontFamily: tajawalFont,
    color: lightColorScheme.onSurface,
  ),
  maxLines: 1,
  overflow: TextOverflow.ellipsis,
  textDirection: TextDirection.ltr,
)
```

---

### شرح الدالة:
- إذا كان الرقم مليار فأكثر، تقسمه على مليار وتعطيه الحرف `B`
- إذا كان مليون أو أكثر، تعطيه `M`
- إذا كان ألف أو أكثر، تعطيه `K`
- إذا أقل من 1000، تعرض الرقم مباشرة
- تستعمل `toStringAsFixed(1)` لإظهار رقم عشري واحد فقط، ويتم حذف `.0` الزائد إذا كان الرقم صحيح.

هذه الطريقة شائعة وتفيد في الواجهات مع مساحة محدودة لعرض الأرقام.

إذا تريد دالة تدعم صياغة أكبر للأرقام، أو مع علامات فاصلة آلاف مع الاختصار، يمكنني مساعدتك كذلك!

     Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers es (ISO 639), en respectant le contexte culinaire.

    Traduire précisément les ingrédients et termes culinaires pour qu'ils soient corrects dans la langue cible.
    Maintenir la structure JSON intacte, en ne modifiant que les valeurs.
    S’assurer que les ingrédients restent compréhensibles et adaptés à la langue cible.

    Return Format
    Tu dois renvoyer une liste d’objets sous la forme reçu.
    - Chaque valeur doit être correctement traduite en es.
    - Les ingrédients doivent être adaptés à la langue cible.
    - Aucune clé ne doit être modifiée.

    Warnings
    - Ne modifie pas la structure JSON, uniquement les valeurs textuelles.
    - Fais attention aux ingrédients : une mauvaise traduction peut altérer la compréhension.
    - Ne laisse aucune valeur non traduite.
    - Ne renvoie que le JSON, sans explication.

    Context Dump
    Langue source : en (ISO 639)
    Langue cible : es (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "c8bf2797bec545f1acb13b0b4ed0e285",
    "updated": "2025-05-17T08:28:58.326Z",
    "title": "Sautéed Pickled Green Beans",
    "subtitle": "Fasulye Turşusu Kavurması",
    "description": "This quick sauté features soft-cooked onions and tomatoes that provide a sweet contrast to crispy, tangy pickled green beans. At Okyanus Balık Evi, a fish restaurant in Sinop on the Black Sea, this dish is typically served as an appetizer alongside hot slices of griddled corn bread. It also pairs well with roasted meats.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "olive oil",
          "onion, coarsely chopped (mounded (59.147 ml)).",
          "1- to (50.8 mm) lengths everyday green bean pickles or store-bought pickled beans, drained",
          "ripe, juicy tomato, coarsely chopped, or canned tomatoes, coarsely chopped",
          "turkish or other crushed red pepper flakes, or taste",
          "water or pickle brine, if needed",
          "fine sea salt (optional)."
        ]
      }
    ],
    "instructions": [
      "Heat the olive oil in an 8-inch skillet over medium heat. Add the onions and sauté, stirring, until they start to curl at the edges and turn golden.",
      "Add the pickled beans, tomato, and red pepper flakes, then cook, stirring, until the red pepper becomes fragrant and the tomatoes begin to soften without breaking down completely, about 2 to 3 minutes. If the mixture starts sticking to the pan, add 1 to 2 tablespoons of water or pickle brine, up to 4 tablespoons as needed. Season with salt to taste and serve hot."
    ],
    "notes_ingredients": "You will need 2 cups of pickled green beans (homemade or store-bought). Pickled green tomatoes can also be a tasty addition. If fresh tomatoes are out of season, canned tomatoes work well as a substitute.",
    "notes_instructions": "For an extra tangy flavor, add a few spoonfuls of pickle brine to the vegetables while cooking."
  }
]

    

```json
[
  {
    "recipeCode": "c8bf2797bec545f1acb13b0b4ed0e285",
    "updated": "2025-05-17T08:28:58.326Z",
    "title": "Judías Verdes Encurtidas Salteadas",
    "subtitle": "Fasulye Turşusu Kavurması",
    "description": "Este salteado rápido presenta cebollas y tomates cocidos suavemente que proporcionan un contraste dulce a las crujientes y ácidas judías verdes encurtidas. En Okyanus Balık Evi, un restaurante de pescado en Sinop en el Mar Negro, este plato se sirve normalmente como aperitivo junto con rebanadas calientes de pan de maíz a la plancha. También combina bien con carnes asadas.",
    "ingredients": [
      {
        "section": "Para la receta",
        "ingredients": [
          "aceite de oliva",
          "cebolla, picada gruesa (montón (59.147 ml)).",
          "judías verdes encurtidas de uso cotidiano de 1 a (50.8 mm) de largo o judías encurtidas compradas, escurridas",
          "tomate maduro y jugoso, picado grueso, o tomates enlatados, picados gruesos",
          "copos de pimiento rojo turco u otros triturados, al gusto",
          "agua o salmuera del encurtido, si es necesario",
          "sal marina fina (opcional)."
        ]
      }
    ],
    "instructions": [
      "Calienta el aceite de oliva en una sartén de 20 cm a fuego medio. Añade las cebollas y saltea, removiendo, hasta que empiecen a rizarse en los bordes y se vuelvan doradas.",
      "Agrega las judías encurtidas, el tomate y los copos de pimiento rojo, luego cocina, removiendo, hasta que el pimiento rojo suelte aroma y los tomates comiencen a ablandarse sin deshacerse completamente, alrededor de 2 a 3 minutos. Si la mezcla comienza a pegarse a la sartén, añade 1 a 2 cucharadas de agua o salmuera de encurtido, hasta un máximo de 4 cucharadas según sea necesario. Sazona con sal al gusto y sirve caliente."
    ],
    "notes_ingredients": "Necesitarás 2 tazas de judías verdes encurtidas (caseras o compradas). Los tomates verdes encurtidos también pueden ser una adición sabrosa. Si los tomates frescos están fuera de temporada, los tomates enlatados funcionan bien como sustituto.",
    "notes_instructions": "Para un sabor extra ácido, agrega unas cucharadas de salmuera de encurtido a las verduras mientras se cocinan."
  }
]
```

     Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers zh (ISO 639), en respectant le contexte culinaire.

    Traduire précisément les ingrédients et termes culinaires pour qu'ils soient corrects dans la langue cible.
    Maintenir la structure JSON intacte, en ne modifiant que les valeurs.
    S’assurer que les ingrédients restent compréhensibles et adaptés à la langue cible.

    Return Format
    Tu dois renvoyer une liste d’objets sous la forme reçu.
    - Chaque valeur doit être correctement traduite en zh.
    - Les ingrédients doivent être adaptés à la langue cible.
    - Aucune clé ne doit être modifiée.

    Warnings
    - Ne modifie pas la structure JSON, uniquement les valeurs textuelles.
    - Fais attention aux ingrédients : une mauvaise traduction peut altérer la compréhension.
    - Ne laisse aucune valeur non traduite.
    - Ne renvoie que le JSON, sans explication.

    Context Dump
    Langue source : en (ISO 639)
    Langue cible : zh (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "c8bf2797bec545f1acb13b0b4ed0e285",
    "updated": "2025-05-17T08:28:58.326Z",
    "title": "Sautéed Pickled Green Beans",
    "subtitle": "Fasulye Turşusu Kavurması",
    "description": "This quick sauté features soft-cooked onions and tomatoes that provide a sweet contrast to crispy, tangy pickled green beans. At Okyanus Balık Evi, a fish restaurant in Sinop on the Black Sea, this dish is typically served as an appetizer alongside hot slices of griddled corn bread. It also pairs well with roasted meats.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "olive oil",
          "onion, coarsely chopped (mounded (59.147 ml)).",
          "1- to (50.8 mm) lengths everyday green bean pickles or store-bought pickled beans, drained",
          "ripe, juicy tomato, coarsely chopped, or canned tomatoes, coarsely chopped",
          "turkish or other crushed red pepper flakes, or taste",
          "water or pickle brine, if needed",
          "fine sea salt (optional)."
        ]
      }
    ],
    "instructions": [
      "Heat the olive oil in an 8-inch skillet over medium heat. Add the onions and sauté, stirring, until they start to curl at the edges and turn golden.",
      "Add the pickled beans, tomato, and red pepper flakes, then cook, stirring, until the red pepper becomes fragrant and the tomatoes begin to soften without breaking down completely, about 2 to 3 minutes. If the mixture starts sticking to the pan, add 1 to 2 tablespoons of water or pickle brine, up to 4 tablespoons as needed. Season with salt to taste and serve hot."
    ],
    "notes_ingredients": "You will need 2 cups of pickled green beans (homemade or store-bought). Pickled green tomatoes can also be a tasty addition. If fresh tomatoes are out of season, canned tomatoes work well as a substitute.",
    "notes_instructions": "For an extra tangy flavor, add a few spoonfuls of pickle brine to the vegetables while cooking."
  }
]

    

```json
[
  {
    "recipeCode": "c8bf2797bec545f1acb13b0b4ed0e285",
    "updated": "2025-05-17T08:28:58.326Z",
    "title": "炒腌制青豆",
    "subtitle": "腌制青豆炒菜",
    "description": "这道快速炒菜以软煮洋葱和西红柿为特色，甘甜的味道与脆爽酸辣的腌制青豆形成鲜明对比。在黑海地区锡诺普的鱼餐厅Okyanus Balık Evi，这道菜通常作为开胃菜，搭配热乎的玉米烤饼片一起食用。它也很适合搭配烤肉食用。",
    "ingredients": [
      {
        "section": "配方材料",
        "ingredients": [
          "橄榄油",
          "洋葱，粗切（堆积约59.147毫升）",
          "1段长约50.8毫米的日常腌青豆或购买的腌制青豆，沥干",
          "成熟多汁的西红柿，粗切，或罐装西红柿，粗切",
          "土耳其红辣椒碎片或其他红辣椒碎，根据口味添加",
          "水或腌制液（如需要）",
          "细海盐（可选）"
        ]
      }
    ],
    "instructions": [
      "用中火在8英寸煎锅中加热橄榄油。加入洋葱，炒至边缘开始卷曲并呈金黄色，同时不停搅拌。",
      "加入腌制青豆、西红柿和红辣椒碎，炒至红辣椒香气四溢，西红柿开始变软但未完全化开，大约2到3分钟。若混合物开始粘锅，加入1至2汤匙水或腌制液，最多可加至4汤匙。根据口味加入盐调味，趁热食用。"
    ],
    "notes_ingredients": "你需要2杯腌制青豆（自制或购买）。腌制青西红柿也是美味的搭配。如果新鲜西红柿不在季节，罐装西红柿是很好的替代品。",
    "notes_instructions": "为了更浓郁的酸味，烹饪时可在蔬菜中加入几勺腌制液。"
  }
]
```