{"behavior":"degenerate_repetition","label_filter":null,"limit":10,"next_offset":18062,"offset":18052,"previous_offset":null,"rows":[{"assistant_initiates":false,"asst_text":"Hello! I'm doing well, thank you. How can I assist you today?","behavior":"degenerate_repetition","conversation_hash":"1f2041611b8beff6b7602ece1f622dba","conversation_redacted":false,"conversation_toxic":false,"country":"United States","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":118,"n_turns_in_conversation":1,"n_words":23,"source_row_offset":18052,"source_shard":"turns-00080.parquet","timestamp":"Sat, 17 May 2025 08:28:39 GMT","turn_id":"63650dd97169c16fe03e45d1","turn_index":0,"user_text":"User: hi, how are you?\nUser: hi, how are you?\nAssistant:"},{"assistant_initiates":false,"asst_text":"Making your own AI can range from simple projects to very complex systems depending on what you want to achieve. Here\u2019s a general guide to get you started:\n\n### 1. Define Your Goal\n- **What kind of AI?** (e.g., chatbot, image recognition, recommendation system)\n- **What problem will it solve?**\n\n### 2. Learn the Basics\n- **Programming languages:** Python is the most popular for AI.\n- **Mathematics:** Linear algebra, calculus, probability, and statistics.\n- **Machine Learning concepts:** Supervised/unsupervised learning, neural networks, etc.\n\n### 3. Choose Your Tools and Frameworks\n- **Libraries:** TensorFlow, PyTorch, scikit-learn, Keras\n- **Data processing:** Pandas, NumPy\n\n### 4. Gather and Prepare Data\n- AI models need data to learn.\n- Find datasets online (Kaggle, UCI Machine Learning Repository) or collect your own data.\n- Clean and preprocess data (handle missing values, normalization, encoding).\n\n### 5. Build a Model\n- Start simple: linear regression, decision trees, or simple neural networks.\n- Use frameworks to define the architecture of your model.\n- Train the model on your dataset.\n\n### 6. Evaluate and Improve\n- Use metrics like accuracy, precision, recall to evaluate.\n- Tune hyperparameters, try different models, or get more data to improve.\n\n### 7. Deploy Your AI\n- Create APIs using Flask or FastAPI.\n- Integrate AI into applications or services.\n\n---\n\n### Example: Build a Simple AI Classifier in Python\n```python\nfrom sklearn.datasets import load_iris\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.ensemble import RandomForestClassifier\nfrom sklearn.metrics import accuracy_score\n\n# Load dataset\niris = load_iris()\nX, y = iris.data, iris.target\n\n# Split into train and test sets\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)\n\n# Create and train model\nmodel = RandomForestClassifier()\nmodel.fit(X_train, y_train)\n\n# Predict and evaluate\ny_pred = model.predict(X_test)\nprint(\"Accuracy:\", accuracy_score(y_test, y_pred))\n```\n\n---\n\nIf 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!","behavior":"degenerate_repetition","conversation_hash":"b65038f3e4455affa2ceacd206dff460","conversation_redacted":false,"conversation_toxic":false,"country":"India","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":2197,"n_turns_in_conversation":3,"n_words":329,"source_row_offset":18053,"source_shard":"turns-00080.parquet","timestamp":"Sat, 17 May 2025 08:29:06 GMT","turn_id":"7ef467918612ff685c0c0a7d","turn_index":0,"user_text":"I want to ask you how to make your own ai"},{"assistant_initiates":false,"asst_text":"Creating an *exact replica* of ChatGPT-4 that works offline is an extremely challenging task because:\n\n- **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).\n- **GPT-4 weights and training code are not publicly available**, so you cannot simply download the model and run it offline.\n- 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.\n\n---\n\n### What you *can* do to create a capable offline chatbot AI:\n\n#### 1. Use Open-Source Large Language Models (LLMs)\nThere are several open-source models inspired by GPT-3 and GPT-4 that you can run offline on reasonably powerful hardware. Examples include:\n\n- **GPT-J (6B parameters)** by EleutherAI\n- **GPT-NeoX (20B parameters)** by EleutherAI\n- **LLaMA (7B, 13B models)** by Meta AI (if you obtain the license)\n- **Alpaca**, **Vicuna**, **StableLM**, or **BLOOM**\n\nThese 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.\n\n#### 2. Hardware Requirements\n- For models like GPT-J or GPT-NeoX: a GPU with 24GB+ VRAM is recommended (e.g., NVIDIA RTX 3090, 4090).\n- Smaller LLaMA or Alpaca models can run on fewer resources but may sacrifice performance and accuracy.\n- For CPU-only inference, even smaller models are needed, and performance will be slow.\n\n#### 3. Software and Tools\nYou can use these frameworks and tools:\n\n- **Transformers library by Hugging Face:** to load and run models easily.\n- **Text generation frameworks:** e.g., `text-generation-webui` enables easy hosting with a web interface.\n- **LLaMA.cpp**: a C++ optimized runtime to run LLaMA models on CPU efficiently.\n\n#### 4. Steps to set up an offline chatbot similar to ChatGPT\n\n1. **Pick a model**: e.g., GPT-J, LLaMA 7B, or Vicuna (an instruction-tuned LLaMA variant).\n2. **Download the pre-trained weights**: from official or community repositories.\n3. **Install dependencies**: Python, PyTorch/TensorFlow, Transformers library.\n4. **Run inference scripts**: load the model and use a prompt to generate replies.\n5. **Optionally, fine-tune or instruction-tune**: to improve chatbot-like behavior.\n6. **Create an interface**: CLI, web app, or integrate with desktop apps.\n\n---\n\n### Example: Running GPT-J Offline Using Hugging Face Transformers (very basic)\n\n```bash\npip install transformers torch\n```\n\n```python\nfrom transformers import GPTJForCausalLM, AutoTokenizer\nimport torch\n\ntokenizer = AutoTokenizer.from_pretrained(\"EleutherAI/gpt-j-6B\")\nmodel = GPTJForCausalLM.from_pretrained(\"EleutherAI/gpt-j-6B\")\n\nprompt = \"Hello, how are you today?\"\ninputs = tokenizer(prompt, return_tensors=\"pt\")\noutputs = model.generate(**inputs, max_length=100)\nprint(tokenizer.decode(outputs[0], skip_special_tokens=True))\n```\n\n*Note: You need a GPU with enough VRAM to load this 6B parameter model.*\n\n---\n\n### Summary\n\n| Aspect             | GPT-4 (OpenAI)         | Open Source Offline Models            |\n|--------------------|------------------------|--------------------------------------|\n| Access             | API only (paid)        | Download weights and run locally     |\n| Size               | 175+ billion params    | 6 billion (GPT-J) to 20+ billion (GPT-NeoX), LLaMA variants |\n| Hardware needed    | Very powerful clusters | High-end desktop GPUs for best speed |\n| Licensing          | Proprietary            | Mostly permissive licenses            |\n| Performance        | State-of-the-art       | Good but below GPT-4                  |\n| Ease of Use        | Easy via API           | Requires setup and technical skills  |\n\n---\n\n### Resources to start\n\n- [EleutherAI GPT-J](https://github.com/kingoflolz/mesh-transformer-jax/)\n- [Hugging Face Models Hub](https://huggingface.co/models)\n- [text-generation-webui](https://github.com/oobabooga/text-generation-webui)\n- [LLaMA.cpp project](https://github.com/ggerganov/llama.cpp)\n\n---\n\nIf 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!","behavior":"degenerate_repetition","conversation_hash":"b65038f3e4455affa2ceacd206dff460","conversation_redacted":false,"conversation_toxic":false,"country":"India","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":4346,"n_turns_in_conversation":3,"n_words":590,"source_row_offset":18054,"source_shard":"turns-00080.parquet","timestamp":"Sat, 17 May 2025 08:29:06 GMT","turn_id":"a460c32b270e436d912d001b","turn_index":1,"user_text":"I want to make a exact replica of chat got 4 but with offline"},{"assistant_initiates":false,"asst_text":"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\u2014especially using some of the newer, smaller open-source large language models (LLMs).\n\n---\n\n### What You Can Do:\n\n#### 1. Choose Smaller Open-Source Models\n\nMany 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.\n\nExamples that fit your size requirement:\n\n- **LLaMA models (7B, 13B)** \u2013 Meta AI's LLaMA models are very popular for local usage.\n- **Vicuna (7B, 13B)** \u2013 Instruction-tuned LLaMA variants optimized for chat.\n- **Alpaca (7B)** \u2013 Smaller, tuned model based on LLaMA.\n- **GPT-J (6B)** \u2013 Good-quality open model, about 20GB size.\n- **StableLM (7B)** \u2013 OpenAI-style open-source LLM.\n- **MPT-7B** (MosaicML) \u2013 An open, efficient 7 billion parameter model.\n\nTypically, 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.\n\n---\n\n#### 2. How to \u201cGive it Your Name\u201d / Personalize\n\n- These models can be prompted to respond with your preferred name or personalities by adding context or instructions in the prompt.\n\nExample prompt to the AI:\n\n```\nYou are a helpful assistant named [YourName]. Always respond as [YourName] would.\nUser: Hi, who are you?\n```\n\n- For deeper personalization, you can **fine-tune** or **instruction-tune** the model on custom data containing your name and style \u2014 but this requires more technical know-how and some computing resources.\n\n---\n\n#### 3. Deploy Offline Chatbot on Your PC\n\n- 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.\n- The web UI supports Vicuna, LLaMA, GPT-J, MPT, and many others.\n\n---\n\n### Example Setup Overview:\n\n- You download a 7B model (~14 GB).\n- Download the tokenizer and supporting files (a few GB).\n- Clone and set up **text-generation-webui** (small install).\n- Run the model on your GPU or even CPU (slower).\n- Edit the startup prompt or system prompt so the bot uses your name.\n\n---\n\n### Hardware & Software Recommendations:\n\n| Component         | Notes                                |\n|-------------------|------------------------------------|\n| GPU               | At least 10-16 GB VRAM recommended |\n| RAM               | 16+ GB RAM recommended             |\n| Storage           | Under 700 GB fits comfortably      |\n| OS                | Windows/Linux/macOS                 |\n| Software          | Python 3.8+, PyTorch, text-generation-webui |\n\n---\n\n### Example: Download Vicuna 7B & run locally\n\n- Vicuna 7B weights are about 5-7 GB in 4-bit quantized form.\n- You can download the model from Hugging Face (after agreeing to terms).\n- Run with the text-generation-webui https://github.com/oobabooga/text-generation-webui\n\nCommand to launch:\n```bash\npython server.py --model vicuna-7b\n```\n\nThen access the interface at `http://localhost:5000` in your browser.\n\nYou can customize the initial prompt or add a system message:\n```\nYou are a chatbot named [YourName]. Always say your name when greeting.\n```\n\n---\n\n### Summary:\n\n- You **can** run a good offline chatbot personalized with your name under 700 GB.\n- Use open source models like LLaMA, Vicuna, Alpaca, or GPT-J.\n- Use tools like text-generation-webui to easily interact locally.\n- Personalize with prompt instructions or custom fine-tuning.\n\n---\n\nIf 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!","behavior":"degenerate_repetition","conversation_hash":"b65038f3e4455affa2ceacd206dff460","conversation_redacted":false,"conversation_toxic":false,"country":"India","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":3850,"n_turns_in_conversation":3,"n_words":595,"source_row_offset":18055,"source_shard":"turns-00080.parquet","timestamp":"Sat, 17 May 2025 08:29:06 GMT","turn_id":"429156d399ad4ebfa1362d93","turn_index":2,"user_text":"is there any other ai that I can download and give it my name and make it offline uder 700 gb"},{"assistant_initiates":false,"asst_text":"```json\n[\n  {\n    \"recipeCode\": \"c8bf2797bec545f1acb13b0b4ed0e285\",\n    \"updated\": \"2025-05-17T08:28:58.326Z\",\n    \"title\": \"Gebratene eingelegte gr\u00fcne Bohnen\",\n    \"subtitle\": \"Fasulye Tur\u015fusu Kavurmas\u0131\",\n    \"description\": \"Dieses schnelle Gericht enth\u00e4lt weich gegarte Zwiebeln und Tomaten, die einen s\u00fc\u00dfen Kontrast zu knusprigen, w\u00fcrzigen eingelegten gr\u00fcnen Bohnen bieten. Im Okyanus Bal\u0131k Evi, einem Fischrestaurant in Sinop am Schwarzen Meer, wird dieses Gericht typischerweise als Vorspeise zusammen mit hei\u00dfen Scheiben gegrilltem Maisbrot serviert. Es passt auch gut zu Braten.\",\n    \"ingredients\": [\n      {\n        \"section\": \"F\u00fcr das Rezept\",\n        \"ingredients\": [\n          \"Oliven\u00f6l\",\n          \"Zwiebel, grob gehackt (geh\u00e4uft (59,147 ml))\",\n          \"1- bis (50,8 mm) lange eingelegte gr\u00fcne Bohnen oder gekaufte eingelegte Bohnen, abgetropft\",\n          \"reife, saftige Tomate, grob gehackt, oder Dosentomaten, grob gehackt\",\n          \"t\u00fcrkische oder andere zersto\u00dfene Paprikaflocken, nach Geschmack\",\n          \"Wasser oder Essiggurkenlake, falls n\u00f6tig\",\n          \"feines Meersalz (optional)\"\n        ]\n      }\n    ],\n    \"instructions\": [\n      \"Erhitzen Sie das Oliven\u00f6l in einer 20-cm-Pfanne bei mittlerer Hitze. F\u00fcgen Sie die Zwiebeln hinzu und sautieren Sie sie unter R\u00fchren, bis die R\u00e4nder sich kr\u00e4useln und goldgelb werden.\",\n      \"F\u00fcgen Sie die eingelegten Bohnen, die Tomate und die Paprikaflocken hinzu und kochen Sie unter R\u00fchren, bis die Paprika aromatisch wird und die Tomaten zu erweichen beginnen, ohne vollst\u00e4ndig zu zerfallen, etwa 2 bis 3 Minuten. Wenn die Mischung zu kleben beginnt, f\u00fcgen Sie 1 bis 2 Essl\u00f6ffel Wasser oder Essiggurkenlake hinzu, bis zu 4 Essl\u00f6ffel nach Bedarf. Nach Geschmack mit Salz abschmecken und hei\u00df servieren.\"\n    ],\n    \"notes_ingredients\": \"Sie ben\u00f6tigen 2 Tassen eingelegte gr\u00fcne Bohnen (hausgemacht oder gekauft). Eingelegte gr\u00fcne Tomaten k\u00f6nnen ebenfalls eine schmackhafte Erg\u00e4nzung sein. Wenn frische Tomaten au\u00dferhalb der Saison sind, sind Dosentomaten ein guter Ersatz.\",\n    \"notes_instructions\": \"F\u00fcr einen besonders s\u00e4uerlichen Geschmack f\u00fcgen Sie w\u00e4hrend des Kochens ein paar L\u00f6ffel Essiggurkenlake zu den Gem\u00fcsen hinzu.\"\n  }\n]\n```","behavior":"degenerate_repetition","conversation_hash":"43163dca23e88b45178ef2c58e93ce75","conversation_redacted":false,"conversation_toxic":false,"country":"United States","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":5300,"n_turns_in_conversation":1,"n_words":722,"source_row_offset":18056,"source_shard":"turns-00080.parquet","timestamp":"Sat, 17 May 2025 08:29:09 GMT","turn_id":"a1d574edfd6b6c191ee3c621","turn_index":0,"user_text":"\n     Goal\n    Traduire toutes les valeurs textuelles pr\u00e9sentes dans une liste d\u2019objets d\u2019une recette de cuisine de en (ISO 639) vers de (ISO 639), en respectant le contexte culinaire.\n\n    Traduire pr\u00e9cis\u00e9ment les ingr\u00e9dients et termes culinaires pour qu'ils soient corrects dans la langue cible.\n    Maintenir la structure JSON intacte, en ne modifiant que les valeurs.\n    S\u2019assurer que les ingr\u00e9dients restent compr\u00e9hensibles et adapt\u00e9s \u00e0 la langue cible.\n\n    Return Format\n    Tu dois renvoyer une liste d\u2019objets sous la forme re\u00e7u.\n    - Chaque valeur doit \u00eatre correctement traduite en de.\n    - Les ingr\u00e9dients doivent \u00eatre adapt\u00e9s \u00e0 la langue cible.\n    - Aucune cl\u00e9 ne doit \u00eatre modifi\u00e9e.\n\n    Warnings\n    - Ne modifie pas la structure JSON, uniquement les valeurs textuelles.\n    - Fais attention aux ingr\u00e9dients : une mauvaise traduction peut alt\u00e9rer la compr\u00e9hension.\n    - Ne laisse aucune valeur non traduite.\n    - Ne renvoie que le JSON, sans explication.\n\n    Context Dump\n    Langue source : en (ISO 639)\n    Langue cible : de (ISO 639)\n    Donn\u00e9es \u00e0 traduire :\n\n    [\n  {\n    \"recipeCode\": \"c8bf2797bec545f1acb13b0b4ed0e285\",\n    \"updated\": \"2025-05-17T08:28:58.326Z\",\n    \"title\": \"Saut\u00e9ed Pickled Green Beans\",\n    \"subtitle\": \"Fasulye Tur\u015fusu Kavurmas\u0131\",\n    \"description\": \"This quick saut\u00e9 features soft-cooked onions and tomatoes that provide a sweet contrast to crispy, tangy pickled green beans. At Okyanus Bal\u0131k 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.\",\n    \"ingredients\": [\n      {\n        \"section\": \"For the recipe\",\n        \"ingredients\": [\n          \"olive oil\",\n          \"onion, coarsely chopped (mounded (59.147 ml)).\",\n          \"1- to (50.8 mm) lengths everyday green bean pickles or store-bought pickled beans, drained\",\n          \"ripe, juicy tomato, coarsely chopped, or canned tomatoes, coarsely chopped\",\n          \"turkish or other crushed red pepper flakes, or taste\",\n          \"water or pickle brine, if needed\",\n          \"fine sea salt (optional).\"\n        ]\n      }\n    ],\n    \"instructions\": [\n      \"Heat the olive oil in an 8-inch skillet over medium heat. Add the onions and saut\u00e9, stirring, until they start to curl at the edges and turn golden.\",\n      \"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.\"\n    ],\n    \"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.\",\n    \"notes_instructions\": \"For an extra tangy flavor, add a few spoonfuls of pickle brine to the vegetables while cooking.\"\n  }\n]\n\n    "},{"assistant_initiates":false,"asst_text":"\u0644\u062a\u0642\u0644\u064a\u0644 \u0627\u0644\u0645\u0633\u0627\u0641\u0629 \u0628\u064a\u0646 \u0643\u0644\u0645\u0629 \"\u0627\u0644\u0631\u0635\u064a\u062f:\" \u0648\u0627\u0644\u0631\u0635\u064a\u062f \u0627\u0644\u0639\u062f\u062f\u064a \u0641\u064a \u062a\u0631\u062a\u064a\u0628 **Row** \u0641\u064a Flutter\u060c \u064a\u0645\u0643\u0646\u0643 \u0627\u0644\u062a\u062d\u0643\u0645 \u0641\u064a **\u0627\u0644\u062a\u0628\u0627\u0639\u062f \u0628\u064a\u0646 \u0627\u0644\u0639\u0646\u0627\u0635\u0631** \u0628\u0639\u062f\u0629 \u0637\u0631\u0642:\n\n### 1. \u0625\u0632\u0627\u0644\u0629 \u0623\u064a padding \u0623\u0648 margin \u0632\u0627\u0626\u062f\u0629\n\u062a\u0623\u0643\u062f \u0623\u0646 \u0627\u0644\u0646\u0635\u0648\u0635 \u0648\u0627\u0644\u0640 Container \u062f\u0627\u062e\u0644\u0647\u0645 \u0644\u0627 \u062a\u062d\u062a\u0648\u064a \u0639\u0644\u0649 \u062d\u0648\u0627\u0641 padding \u0623\u0648 margin \u063a\u064a\u0631 \u0636\u0631\u0648\u0631\u064a\u0629 \u062a\u0632\u064a\u062f \u0627\u0644\u0645\u0633\u0627\u0641\u0629.\n\n### 2. \u062a\u0642\u0644\u064a\u0644 \u0639\u0631\u0636 \u0627\u0644\u0640 Container (\u0623\u0648 \u0627\u0633\u062a\u0628\u062f\u0627\u0644\u0647 \u0628\u0640 SizedBox)\n\u0641\u064a \u062d\u0627\u0644\u062a\u0643\u060c \u0644\u062f\u064a\u0643 `Container` \u0628\u0639\u0631\u0636 60 \u0648\u0647\u0630\u0627 \u0642\u062f \u064a\u0633\u0628\u0628 \u0648\u062c\u0648\u062f \u0645\u0633\u0627\u062d\u0629 \u0641\u0627\u0631\u063a\u0629 \u0628\u064a\u0646 \u0627\u0644\u0646\u0635\u064a\u0646.\n\n\u064a\u0645\u0643\u0646\u0643 \u0627\u0633\u062a\u0628\u062f\u0627\u0644 \u0627\u0644\u0640 `Container` \u0628\u0640 `SizedBox` \u0644\u062a\u062d\u062f\u064a\u062f \u0627\u0644\u0639\u0631\u0636 \u0628\u062f\u0642\u0629 \u0623\u0648 \u0625\u0632\u0627\u0644\u0629 \u0627\u0644\u0639\u0631\u0636 \u062a\u0645\u0627\u0645\u064b\u0627 \u0625\u0630\u0627 \u0644\u0645 \u064a\u0643\u0646 \u0644\u062f\u064a\u0643 \u062d\u0627\u062c\u0629 \u0644\u062a\u062d\u062f\u064a\u062f \u0627\u0644\u0639\u0631\u0636.\n\n### 3. \u0627\u0633\u062a\u062e\u062f\u0645 `SizedBox` \u0645\u0639 \u0639\u0631\u0636 \u0623\u0635\u063a\u0631 (\u0623\u0648 \u062d\u062a\u0649 \u0627\u0633\u062a\u0628\u062f\u0644\u0647 \u0628\u0646\u0635 \u0639\u0627\u062f\u064a)\n\u0623\u0645\u062b\u0644\u0629:\n\n```dart\nRow(\n  mainAxisSize: MainAxisSize.min,\n  textDirection: TextDirection.rtl,\n  children: [\n    Text(\n      '\u0627\u0644\u0631\u0635\u064a\u062f: ',\n      style: TextStyle(\n        fontSize: 16,\n        fontWeight: FontWeight.w600,\n        fontFamily: tajawalFont,\n        color: lightColorScheme.onSurface,\n      ),\n      textDirection: TextDirection.rtl,\n    ),\n    // \u0625\u0645\u0627 \u0646\u0635 \u0641\u0642\u0637 \u0628\u062f\u0648\u0646 Container \u0623\u0648 SizedBox\n    Text(\n      _formatWithThousandsSeparator(_currentBalance),\n      style: TextStyle(\n        fontSize: 16,\n        fontWeight: FontWeight.bold,\n        fontFamily: tajawalFont,\n        color: lightColorScheme.onSurface,\n      ),\n      maxLines: 1,\n      overflow: TextOverflow.ellipsis,\n      textDirection: TextDirection.ltr,\n    ),\n  ],\n)\n```\n\n\u0623\u0648 \u0641\u064a \u062d\u0627\u0644 \u0643\u0646\u062a \u062a\u0631\u064a\u062f \u062a\u062d\u062f\u064a\u062f \u0639\u0631\u0636 \u0644\u062c\u0639\u0644 \u0627\u0644\u0627\u062d\u062a\u0645\u0627\u0644\u064a\u0629 \u0623\u0642\u0644 \u0644\u0644\u0627\u0644\u062a\u0641\u0627\u0641 \u064a\u0645\u0643\u0646\u0643 \u0645\u062b\u0644\u0627:\n\n```dart\nSizedBox(\n  width: 50, // \u062a\u0642\u0644\u064a\u0644 \u0627\u0644\u0639\u0631\u0636 \u0644\u062a\u0642\u0644\u064a\u0644 \u0627\u0644\u0645\u0633\u0627\u0641\u0629\n  child: Text(\n    _formatWithThousandsSeparator(_currentBalance),\n    style: TextStyle(\n      fontSize: 16,\n      fontWeight: FontWeight.bold,\n      fontFamily: tajawalFont,\n      color: lightColorScheme.onSurface,\n    ),\n    maxLines: 1,\n    overflow: TextOverflow.ellipsis,\n    textDirection: TextDirection.ltr,\n  ),\n),\n```\n\n### 4. \u0627\u0633\u062a\u062e\u062f\u0627\u0645 `Text.rich` \u0644\u062c\u0645\u0639 \u0627\u0644\u0646\u0635 \u0641\u064a Widget \u0648\u0627\u062d\u062f\n\u0628\u062f\u0644\u0627\u064b \u0645\u0646 `Row` \u064a\u0645\u0643\u0646\u0643 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 Text.rich \u0644\u062c\u0639\u0644 \u0627\u0644\u0646\u0635 \"\u0627\u0644\u0631\u0635\u064a\u062f: 123456\" \u0643\u0641\u0626\u0629 \u0648\u0627\u062d\u062f\u0629 \u062a\u062a\u062d\u0643\u0645 \u0628\u0647\u0627 \u0628\u0634\u0643\u0644 \u0623\u062f\u0642\u060c \u0648\u0647\u0630\u0627 \u0633\u064a\u0642\u0644\u0644 \u0627\u0644\u0645\u0633\u0627\u0641\u0629 \u0628\u0634\u0643\u0644 \u0637\u0628\u064a\u0639\u064a:\n\n```dart\nText.rich(\n  TextSpan(\n    text: '\u0627\u0644\u0631\u0635\u064a\u062f: ',\n    style: TextStyle(\n      fontSize: 16,\n      fontWeight: FontWeight.w600,\n      fontFamily: tajawalFont,\n      color: lightColorScheme.onSurface,\n    ),\n    children: [\n      TextSpan(\n        text: _formatWithThousandsSeparator(_currentBalance),\n        style: TextStyle(\n          fontSize: 16,\n          fontWeight: FontWeight.bold,\n          fontFamily: tajawalFont,\n          color: lightColorScheme.onSurface,\n        ),\n      ),\n    ],\n  ),\n  textDirection: TextDirection.rtl,\n)\n```\n\n### \u062e\u0644\u0627\u0635\u0629:\n- \u062c\u0631\u0628 \u0625\u0632\u0627\u0644\u0629 \u0627\u0644\u0640 `Container` \u0623\u0648 \u062a\u0642\u0644\u064a\u0644 \u0639\u0631\u0636\u0647.\n- \u0627\u0633\u062a\u062e\u062f\u0645 `SizedBox` \u0628\u0639\u0631\u0636 \u0623\u0642\u0644.\n- \u0623\u0641\u0636\u0644 \u062d\u0644 \u0647\u0648 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 `Text.rich` \u0644\u062a\u062c\u0645\u064a\u0639 \u0627\u0644\u0646\u0635\u0648\u0635 \u0628\u0643\u0641\u0627\u0621\u0629 \u0645\u0639 \u062a\u062d\u0643\u0645 \u0643\u0627\u0645\u0644 \u0641\u064a \u0627\u0644\u0623\u0633\u0627\u0644\u064a\u0628 \u0648\u0627\u0644\u0645\u0633\u0627\u0641\u0627\u062a.\n\n\u0625\u0630\u0627 \u062a\u0631\u064a\u062f \u0645\u0633\u0627\u0639\u062f\u0629 \u0625\u0636\u0627\u0641\u064a\u0629 \u0644\u062a\u062c\u0631\u0628\u0629 \u0623\u064a \u0645\u0646 \u062a\u0644\u0643 \u0627\u0644\u0637\u0631\u0642\u060c \u0628\u0633 \u0623\u062e\u0628\u0631\u0646\u064a!","behavior":"degenerate_repetition","conversation_hash":"b9ab7cbdbd6f42d3a18ab1469143c50f","conversation_redacted":false,"conversation_toxic":false,"country":"Yemen","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":4303,"n_turns_in_conversation":3,"n_words":380,"source_row_offset":18057,"source_shard":"turns-00080.parquet","timestamp":"Sat, 17 May 2025 08:29:09 GMT","turn_id":"97b08aaaf9f9271b2c845e90","turn_index":0,"user_text":"\u0627\u0631\u064a\u062f \u062a\u0642\u0644\u064a\u0644 \u0627\u0644\u0645\u0633\u0627\u0641\u0629 \u0628\u064a\u0646 \u0627\u0644\u0631\u0635\u064a\u062f \u0627\u0644\u0639\u062f\u062f\u064a \u0648\u0643\u0644\u0645\u0629 \u0627\u0644\u0631\u0635\u064a\u062f:\nRow(\n                          mainAxisSize: MainAxisSize.min,\n                          textDirection: TextDirection.rtl,\n                          children: [\n                            Text(\n                              textDirection: TextDirection.rtl,\n                              '\u0627\u0644\u0631\u0635\u064a\u062f: ',\n                              style: TextStyle(\n                                fontSize: 16,\n                                fontWeight: FontWeight.w600,\n                                fontFamily: tajawalFont,\n                                color: lightColorScheme.onSurface,\n                              ),\n                            ),\n                            Container(\n                              width: 60, // \u0636\u0628\u0637 \u0627\u0644\u0639\u0631\u0636 \u0647\u0646\u0627 \u0645\u062b\u0627\u0644 (\u064a\u0645\u0643\u0646\u0643 \u062a\u063a\u064a\u064a\u0631\u0647)\n                              child: Text(\n                                _formatWithThousandsSeparator(_currentBalance),\n                                style: TextStyle(\n                                  fontSize: 16,\n                                  fontWeight: FontWeight.bold,\n                                  fontFamily: tajawalFont,\n                                  color: lightColorScheme.onSurface,\n                                ),\n                                maxLines: 1,\n                                overflow: TextOverflow.ellipsis,\n                                textDirection: TextDirection.ltr,\n                              ),\n                            ),\n                          ],\n                        ),"},{"assistant_initiates":false,"asst_text":"\u0644\u0625\u0636\u0627\u0641\u0629 \u0645\u0633\u0627\u0641\u0629 \u0645\u0646 \u0627\u0644\u0623\u0639\u0644\u0649 \u0644\u0644\u0640 `Row` \u0641\u064a Flutter\u060c \u064a\u0645\u0643\u0646\u0643 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0625\u062d\u062f\u0649 \u0627\u0644\u0637\u0631\u0642 \u0627\u0644\u062a\u0627\u0644\u064a\u0629:\n\n### 1. \u0627\u0633\u062a\u062e\u062f\u0627\u0645 `Padding` \u0645\u0639 `EdgeInsets.only(top: ...)`\n\n\u063a\u0644\u0641 \u0627\u0644\u0640 `Row` \u0628\u0640 `Padding` \u0648\u062d\u062f\u062f \u0627\u0644\u0645\u0633\u0627\u0641\u0629 \u0627\u0644\u062a\u064a \u062a\u0631\u064a\u062f\u0647\u0627 \u0645\u0646 \u0627\u0644\u0623\u0639\u0644\u0649\u060c \u0645\u062b\u0644\u0627\u064b:\n\n```dart\nPadding(\n  padding: const EdgeInsets.only(top: 10.0), // \u062a\u0639\u062f\u064a\u0644 \u0627\u0644\u0642\u064a\u0645\u0629 \u062d\u0633\u0628 \u0627\u0644\u0645\u0633\u0627\u0641\u0629 \u0627\u0644\u0645\u0637\u0644\u0648\u0628\u0629\n  child: Row(\n    mainAxisSize: MainAxisSize.min,\n    textDirection: TextDirection.rtl,\n    children: [\n      Text(\n        '\u0627\u0644\u0631\u0635\u064a\u062f: ',\n        style: TextStyle(\n          fontSize: 16,\n          fontWeight: FontWeight.w600,\n          fontFamily: tajawalFont,\n          color: lightColorScheme.onSurface,\n        ),\n        textDirection: TextDirection.rtl,\n      ),\n      SizedBox(\n        width: 49,\n        child: Text(\n          _formatWithThousandsSeparator(_currentBalance),\n          style: TextStyle(\n            fontSize: 15,\n            fontWeight: FontWeight.bold,\n            fontFamily: tajawalFont,\n            color: lightColorScheme.onSurface,\n          ),\n          maxLines: 1,\n          overflow: TextOverflow.ellipsis,\n          textDirection: TextDirection.ltr,\n        ),\n      ),\n    ],\n  ),\n);\n```\n\n### 2. \u0627\u0633\u062a\u062e\u062f\u0627\u0645 `Container` \u0645\u0639 \u062e\u0627\u0635\u064a\u0629 `margin`\n\n\u064a\u0645\u0643\u0646 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 `margin` \u0628\u0646\u0641\u0633 \u0627\u0644\u0637\u0631\u064a\u0642\u0629:\n\n```dart\nContainer(\n  margin: const EdgeInsets.only(top: 10.0), // \u0627\u0644\u0645\u0633\u0627\u0641\u0629 \u0645\u0646 \u0627\u0644\u0623\u0639\u0644\u0649\n  child: Row(\n    mainAxisSize: MainAxisSize.min,\n    textDirection: TextDirection.rtl,\n    children: [\n      // \u0646\u0641\u0633 \u0627\u0644\u0645\u062d\u062a\u0648\u0649\n    ],\n  ),\n);\n```\n\n---\n\n**\u0627\u0644\u0646\u0635\u064a\u062d\u0629:** \u063a\u0627\u0644\u0628\u0627\u064b \u0627\u0644\u0623\u0641\u0636\u0644 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 `Padding` \u0625\u0630\u0627 \u062a\u0631\u064a\u062f \u0625\u0636\u0627\u0641\u0629 \u0627\u0644\u0641\u0631\u0627\u063a \u062f\u0627\u062e\u0644 \u0627\u0644\u0639\u0646\u0635\u0631\u060c \u0648`margin` \u0625\u0630\u0627 \u062a\u0631\u064a\u062f \u0627\u0644\u062a\u062d\u0643\u0645 \u0628\u0627\u0644\u0641\u0631\u0627\u063a \u062e\u0627\u0631\u062c\u0647.\n\n\u0625\u0630\u0627 \u0623\u0631\u062f\u062a \u0645\u0633\u0627\u0639\u062f\u0629 \u0625\u0636\u0627\u0641\u064a\u0629 \u0623\u0648 \u0634\u0631\u062d \u0623\u0648 \u0627\u062e\u062a\u0644\u0627\u0641 \u0641\u064a \u0627\u0644\u0645\u0633\u0627\u0641\u0627\u062a\u060c \u0641\u0642\u0637 \u0623\u062e\u0628\u0631\u0646\u064a!","behavior":"degenerate_repetition","conversation_hash":"b9ab7cbdbd6f42d3a18ab1469143c50f","conversation_redacted":false,"conversation_toxic":false,"country":"Yemen","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":3156,"n_turns_in_conversation":3,"n_words":226,"source_row_offset":18058,"source_shard":"turns-00080.parquet","timestamp":"Sat, 17 May 2025 08:29:09 GMT","turn_id":"4f2cfe8fba89f2072142f56b","turn_index":1,"user_text":"\u0627\u0631\u064a\u062f \u0627\u0636\u0627\u0641\u0629 \u0645\u0633\u0627\u0641\u0629 \u0645\u0646 \u0627\u0644\u0627\u0639\u0644\u0649\nRow(\n                          mainAxisSize: MainAxisSize.min,\n                          textDirection: TextDirection.rtl,\n                          children: [\n                            Text(\n                              textDirection: TextDirection.rtl,\n                              '\u0627\u0644\u0631\u0635\u064a\u062f: ',\n                              style: TextStyle(\n                                fontSize: 16,\n                                fontWeight: FontWeight.w600,\n                                fontFamily: tajawalFont,\n                                color: lightColorScheme.onSurface,\n                              ),\n                            ),\n                            SizedBox(\n                              width: 49, // \u062a\u0642\u0644\u064a\u0644 \u0627\u0644\u0639\u0631\u0636 \u0644\u062a\u0642\u0644\u064a\u0644 \u0627\u0644\u0645\u0633\u0627\u0641\u0629\n                              child: Text(\n                                _formatWithThousandsSeparator(_currentBalance),\n                                style: TextStyle(\n                                  fontSize: 15,\n                                  fontWeight: FontWeight.bold,\n                                  fontFamily: tajawalFont,\n                                  color: lightColorScheme.onSurface,\n                                ),\n                                maxLines: 1,\n                                overflow: TextOverflow.ellipsis,\n                                textDirection: TextDirection.ltr,\n                              ),\n                            ),\n                          ],\n                        ),"},{"assistant_initiates":false,"asst_text":"\u064a\u0645\u0643\u0646\u0643 \u0643\u062a\u0627\u0628\u0629 \u062f\u0627\u0644\u0629 \u0641\u064a Dart \u062a\u0642\u0648\u0645 \u0628\u062a\u062d\u0648\u064a\u0644 \u0627\u0644\u0623\u0631\u0642\u0627\u0645 \u0627\u0644\u0643\u0628\u064a\u0631\u0629 \u0625\u0644\u0649 \u0635\u064a\u063a\u0629 \u0645\u062e\u062a\u0635\u0631\u0629 \u0645\u0639 \u062d\u0631\u0641 \u064a\u0634\u064a\u0631 \u0644\u0644\u0648\u062d\u062f\u0629 (\u0645\u062b\u0644 K \u0644\u0644\u0623\u0644\u0641\u060c M \u0644\u0644\u0645\u0644\u064a\u0648\u0646\u060c B \u0644\u0644\u0645\u0644\u064a\u0627\u0631) \u0628\u0627\u0644\u0634\u0643\u0644 \u0627\u0644\u062a\u0627\u0644\u064a:\n\n```dart\nString formatNumberWithSuffix(num number) {\n  if (number >= 1000000000) {\n    return (number / 1000000000).toStringAsFixed(1).replaceAll(RegExp(r\"\\.0$\"), \"\") + \"B\";\n  } else if (number >= 1000000) {\n    return (number / 1000000).toStringAsFixed(1).replaceAll(RegExp(r\"\\.0$\"), \"\") + \"M\";\n  } else if (number >= 1000) {\n    return (number / 1000).toStringAsFixed(1).replaceAll(RegExp(r\"\\.0$\"), \"\") + \"K\";\n  } else {\n    return number.toString();\n  }\n}\n```\n\n### \u0637\u0631\u064a\u0642\u0629 \u0627\u0644\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0645\u0639 \u0643\u0648\u062f\u0643:\n\n\u0628\u062f\u0644 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 `_formatWithThousandsSeparator(_currentBalance)` \u0627\u0633\u062a\u0639\u0645\u0644 \u0627\u0644\u062f\u0627\u0644\u0629 \u0627\u0644\u062c\u062f\u064a\u062f\u0629 \u0645\u062b\u0644:\n\n```dart\nText(\n  formatNumberWithSuffix(_currentBalance),\n  style: TextStyle(\n    fontSize: 15,\n    fontWeight: FontWeight.bold,\n    fontFamily: tajawalFont,\n    color: lightColorScheme.onSurface,\n  ),\n  maxLines: 1,\n  overflow: TextOverflow.ellipsis,\n  textDirection: TextDirection.ltr,\n)\n```\n\n---\n\n### \u0634\u0631\u062d \u0627\u0644\u062f\u0627\u0644\u0629:\n- \u0625\u0630\u0627 \u0643\u0627\u0646 \u0627\u0644\u0631\u0642\u0645 \u0645\u0644\u064a\u0627\u0631 \u0641\u0623\u0643\u062b\u0631\u060c \u062a\u0642\u0633\u0645\u0647 \u0639\u0644\u0649 \u0645\u0644\u064a\u0627\u0631 \u0648\u062a\u0639\u0637\u064a\u0647 \u0627\u0644\u062d\u0631\u0641 `B`\n- \u0625\u0630\u0627 \u0643\u0627\u0646 \u0645\u0644\u064a\u0648\u0646 \u0623\u0648 \u0623\u0643\u062b\u0631\u060c \u062a\u0639\u0637\u064a\u0647 `M`\n- \u0625\u0630\u0627 \u0643\u0627\u0646 \u0623\u0644\u0641 \u0623\u0648 \u0623\u0643\u062b\u0631\u060c \u062a\u0639\u0637\u064a\u0647 `K`\n- \u0625\u0630\u0627 \u0623\u0642\u0644 \u0645\u0646 1000\u060c \u062a\u0639\u0631\u0636 \u0627\u0644\u0631\u0642\u0645 \u0645\u0628\u0627\u0634\u0631\u0629\n- \u062a\u0633\u062a\u0639\u0645\u0644 `toStringAsFixed(1)` \u0644\u0625\u0638\u0647\u0627\u0631 \u0631\u0642\u0645 \u0639\u0634\u0631\u064a \u0648\u0627\u062d\u062f \u0641\u0642\u0637\u060c \u0648\u064a\u062a\u0645 \u062d\u0630\u0641 `.0` \u0627\u0644\u0632\u0627\u0626\u062f \u0625\u0630\u0627 \u0643\u0627\u0646 \u0627\u0644\u0631\u0642\u0645 \u0635\u062d\u064a\u062d.\n\n\u0647\u0630\u0647 \u0627\u0644\u0637\u0631\u064a\u0642\u0629 \u0634\u0627\u0626\u0639\u0629 \u0648\u062a\u0641\u064a\u062f \u0641\u064a \u0627\u0644\u0648\u0627\u062c\u0647\u0627\u062a \u0645\u0639 \u0645\u0633\u0627\u062d\u0629 \u0645\u062d\u062f\u0648\u062f\u0629 \u0644\u0639\u0631\u0636 \u0627\u0644\u0623\u0631\u0642\u0627\u0645.\n\n\u0625\u0630\u0627 \u062a\u0631\u064a\u062f \u062f\u0627\u0644\u0629 \u062a\u062f\u0639\u0645 \u0635\u064a\u0627\u063a\u0629 \u0623\u0643\u0628\u0631 \u0644\u0644\u0623\u0631\u0642\u0627\u0645\u060c \u0623\u0648 \u0645\u0639 \u0639\u0644\u0627\u0645\u0627\u062a \u0641\u0627\u0635\u0644\u0629 \u0622\u0644\u0627\u0641 \u0645\u0639 \u0627\u0644\u0627\u062e\u062a\u0635\u0627\u0631\u060c \u064a\u0645\u0643\u0646\u0646\u064a \u0645\u0633\u0627\u0639\u062f\u062a\u0643 \u0643\u0630\u0644\u0643!","behavior":"degenerate_repetition","conversation_hash":"b9ab7cbdbd6f42d3a18ab1469143c50f","conversation_redacted":false,"conversation_toxic":false,"country":"Yemen","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":3295,"n_turns_in_conversation":3,"n_words":272,"source_row_offset":18059,"source_shard":"turns-00080.parquet","timestamp":"Sat, 17 May 2025 08:29:09 GMT","turn_id":"ca5e8f4dc5c6d83f832fb351","turn_index":2,"user_text":"\u0627\u0631\u064a\u062f \u062f\u0627\u0644\u0629 \u0644\u0644\u062a\u0639\u0627\u0645\u0644 \u0645\u0639 \u0627\u0644\u0627\u0631\u0642\u0627\u0645 \u0627\u0644\u0643\u0628\u064a\u0631\u0629 \u0648\u0627\u062e\u062a\u0635\u0627\u0631\u0647\u0627 \u0627\u0644\u0649 \u0631\u0642\u0645 \u0645\u0639 \u062d\u0631\u0641\nContainer(\n                          padding: const EdgeInsets.only(top: 5.5),\n                          child: Row(\n                            mainAxisSize: MainAxisSize.min,\n                            textDirection: TextDirection.rtl,\n                            children: [\n                              Text(\n                                textDirection: TextDirection.rtl,\n                                '\u0627\u0644\u0631\u0635\u064a\u062f: ',\n                                style: TextStyle(\n                                  fontSize: 16,\n                                  fontWeight: FontWeight.w600,\n                                  fontFamily: tajawalFont,\n                                  color: lightColorScheme.onSurface,\n                                ),\n                              ),\n                              SizedBox(\n                                width: 49, // \u062a\u0642\u0644\u064a\u0644 \u0627\u0644\u0639\u0631\u0636 \u0644\u062a\u0642\u0644\u064a\u0644 \u0627\u0644\u0645\u0633\u0627\u0641\u0629\n                                child: Text(\n                                  _formatWithThousandsSeparator(\n                                    _currentBalance,\n                                  ),\n                                  style: TextStyle(\n                                    fontSize: 15,\n                                    fontWeight: FontWeight.bold,\n                                    fontFamily: tajawalFont,\n                                    color: lightColorScheme.onSurface,\n                                  ),\n                                  maxLines: 1,\n                                  overflow: TextOverflow.ellipsis,\n                                  textDirection: TextDirection.ltr,\n                                ),\n                              ),\n                            ],\n                          ),\n                        ),"},{"assistant_initiates":false,"asst_text":"```json\n[\n  {\n    \"recipeCode\": \"c8bf2797bec545f1acb13b0b4ed0e285\",\n    \"updated\": \"2025-05-17T08:28:58.326Z\",\n    \"title\": \"Jud\u00edas Verdes Encurtidas Salteadas\",\n    \"subtitle\": \"Fasulye Tur\u015fusu Kavurmas\u0131\",\n    \"description\": \"Este salteado r\u00e1pido presenta cebollas y tomates cocidos suavemente que proporcionan un contraste dulce a las crujientes y \u00e1cidas jud\u00edas verdes encurtidas. En Okyanus Bal\u0131k 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 ma\u00edz a la plancha. Tambi\u00e9n combina bien con carnes asadas.\",\n    \"ingredients\": [\n      {\n        \"section\": \"Para la receta\",\n        \"ingredients\": [\n          \"aceite de oliva\",\n          \"cebolla, picada gruesa (mont\u00f3n (59.147 ml)).\",\n          \"jud\u00edas verdes encurtidas de uso cotidiano de 1 a (50.8 mm) de largo o jud\u00edas encurtidas compradas, escurridas\",\n          \"tomate maduro y jugoso, picado grueso, o tomates enlatados, picados gruesos\",\n          \"copos de pimiento rojo turco u otros triturados, al gusto\",\n          \"agua o salmuera del encurtido, si es necesario\",\n          \"sal marina fina (opcional).\"\n        ]\n      }\n    ],\n    \"instructions\": [\n      \"Calienta el aceite de oliva en una sart\u00e9n de 20 cm a fuego medio. A\u00f1ade las cebollas y saltea, removiendo, hasta que empiecen a rizarse en los bordes y se vuelvan doradas.\",\n      \"Agrega las jud\u00edas 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 sart\u00e9n, a\u00f1ade 1 a 2 cucharadas de agua o salmuera de encurtido, hasta un m\u00e1ximo de 4 cucharadas seg\u00fan sea necesario. Sazona con sal al gusto y sirve caliente.\"\n    ],\n    \"notes_ingredients\": \"Necesitar\u00e1s 2 tazas de jud\u00edas verdes encurtidas (caseras o compradas). Los tomates verdes encurtidos tambi\u00e9n pueden ser una adici\u00f3n sabrosa. Si los tomates frescos est\u00e1n fuera de temporada, los tomates enlatados funcionan bien como sustituto.\",\n    \"notes_instructions\": \"Para un sabor extra \u00e1cido, agrega unas cucharadas de salmuera de encurtido a las verduras mientras se cocinan.\"\n  }\n]\n```","behavior":"degenerate_repetition","conversation_hash":"d38591c25ca04e074af21f22fb21672f","conversation_redacted":false,"conversation_toxic":false,"country":"United States","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":5345,"n_turns_in_conversation":1,"n_words":763,"source_row_offset":18060,"source_shard":"turns-00080.parquet","timestamp":"Sat, 17 May 2025 08:29:09 GMT","turn_id":"43d3b01bdf5d2a19ea64930f","turn_index":0,"user_text":"\n     Goal\n    Traduire toutes les valeurs textuelles pr\u00e9sentes dans une liste d\u2019objets d\u2019une recette de cuisine de en (ISO 639) vers es (ISO 639), en respectant le contexte culinaire.\n\n    Traduire pr\u00e9cis\u00e9ment les ingr\u00e9dients et termes culinaires pour qu'ils soient corrects dans la langue cible.\n    Maintenir la structure JSON intacte, en ne modifiant que les valeurs.\n    S\u2019assurer que les ingr\u00e9dients restent compr\u00e9hensibles et adapt\u00e9s \u00e0 la langue cible.\n\n    Return Format\n    Tu dois renvoyer une liste d\u2019objets sous la forme re\u00e7u.\n    - Chaque valeur doit \u00eatre correctement traduite en es.\n    - Les ingr\u00e9dients doivent \u00eatre adapt\u00e9s \u00e0 la langue cible.\n    - Aucune cl\u00e9 ne doit \u00eatre modifi\u00e9e.\n\n    Warnings\n    - Ne modifie pas la structure JSON, uniquement les valeurs textuelles.\n    - Fais attention aux ingr\u00e9dients : une mauvaise traduction peut alt\u00e9rer la compr\u00e9hension.\n    - Ne laisse aucune valeur non traduite.\n    - Ne renvoie que le JSON, sans explication.\n\n    Context Dump\n    Langue source : en (ISO 639)\n    Langue cible : es (ISO 639)\n    Donn\u00e9es \u00e0 traduire :\n\n    [\n  {\n    \"recipeCode\": \"c8bf2797bec545f1acb13b0b4ed0e285\",\n    \"updated\": \"2025-05-17T08:28:58.326Z\",\n    \"title\": \"Saut\u00e9ed Pickled Green Beans\",\n    \"subtitle\": \"Fasulye Tur\u015fusu Kavurmas\u0131\",\n    \"description\": \"This quick saut\u00e9 features soft-cooked onions and tomatoes that provide a sweet contrast to crispy, tangy pickled green beans. At Okyanus Bal\u0131k 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.\",\n    \"ingredients\": [\n      {\n        \"section\": \"For the recipe\",\n        \"ingredients\": [\n          \"olive oil\",\n          \"onion, coarsely chopped (mounded (59.147 ml)).\",\n          \"1- to (50.8 mm) lengths everyday green bean pickles or store-bought pickled beans, drained\",\n          \"ripe, juicy tomato, coarsely chopped, or canned tomatoes, coarsely chopped\",\n          \"turkish or other crushed red pepper flakes, or taste\",\n          \"water or pickle brine, if needed\",\n          \"fine sea salt (optional).\"\n        ]\n      }\n    ],\n    \"instructions\": [\n      \"Heat the olive oil in an 8-inch skillet over medium heat. Add the onions and saut\u00e9, stirring, until they start to curl at the edges and turn golden.\",\n      \"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.\"\n    ],\n    \"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.\",\n    \"notes_instructions\": \"For an extra tangy flavor, add a few spoonfuls of pickle brine to the vegetables while cooking.\"\n  }\n]\n\n    "},{"assistant_initiates":false,"asst_text":"```json\n[\n  {\n    \"recipeCode\": \"c8bf2797bec545f1acb13b0b4ed0e285\",\n    \"updated\": \"2025-05-17T08:28:58.326Z\",\n    \"title\": \"\u7092\u814c\u5236\u9752\u8c46\",\n    \"subtitle\": \"\u814c\u5236\u9752\u8c46\u7092\u83dc\",\n    \"description\": \"\u8fd9\u9053\u5feb\u901f\u7092\u83dc\u4ee5\u8f6f\u716e\u6d0b\u8471\u548c\u897f\u7ea2\u67ff\u4e3a\u7279\u8272\uff0c\u7518\u751c\u7684\u5473\u9053\u4e0e\u8106\u723d\u9178\u8fa3\u7684\u814c\u5236\u9752\u8c46\u5f62\u6210\u9c9c\u660e\u5bf9\u6bd4\u3002\u5728\u9ed1\u6d77\u5730\u533a\u9521\u8bfa\u666e\u7684\u9c7c\u9910\u5385Okyanus Bal\u0131k Evi\uff0c\u8fd9\u9053\u83dc\u901a\u5e38\u4f5c\u4e3a\u5f00\u80c3\u83dc\uff0c\u642d\u914d\u70ed\u4e4e\u7684\u7389\u7c73\u70e4\u997c\u7247\u4e00\u8d77\u98df\u7528\u3002\u5b83\u4e5f\u5f88\u9002\u5408\u642d\u914d\u70e4\u8089\u98df\u7528\u3002\",\n    \"ingredients\": [\n      {\n        \"section\": \"\u914d\u65b9\u6750\u6599\",\n        \"ingredients\": [\n          \"\u6a44\u6984\u6cb9\",\n          \"\u6d0b\u8471\uff0c\u7c97\u5207\uff08\u5806\u79ef\u7ea659.147\u6beb\u5347\uff09\",\n          \"1\u6bb5\u957f\u7ea650.8\u6beb\u7c73\u7684\u65e5\u5e38\u814c\u9752\u8c46\u6216\u8d2d\u4e70\u7684\u814c\u5236\u9752\u8c46\uff0c\u6ca5\u5e72\",\n          \"\u6210\u719f\u591a\u6c41\u7684\u897f\u7ea2\u67ff\uff0c\u7c97\u5207\uff0c\u6216\u7f50\u88c5\u897f\u7ea2\u67ff\uff0c\u7c97\u5207\",\n          \"\u571f\u8033\u5176\u7ea2\u8fa3\u6912\u788e\u7247\u6216\u5176\u4ed6\u7ea2\u8fa3\u6912\u788e\uff0c\u6839\u636e\u53e3\u5473\u6dfb\u52a0\",\n          \"\u6c34\u6216\u814c\u5236\u6db2\uff08\u5982\u9700\u8981\uff09\",\n          \"\u7ec6\u6d77\u76d0\uff08\u53ef\u9009\uff09\"\n        ]\n      }\n    ],\n    \"instructions\": [\n      \"\u7528\u4e2d\u706b\u57288\u82f1\u5bf8\u714e\u9505\u4e2d\u52a0\u70ed\u6a44\u6984\u6cb9\u3002\u52a0\u5165\u6d0b\u8471\uff0c\u7092\u81f3\u8fb9\u7f18\u5f00\u59cb\u5377\u66f2\u5e76\u5448\u91d1\u9ec4\u8272\uff0c\u540c\u65f6\u4e0d\u505c\u6405\u62cc\u3002\",\n      \"\u52a0\u5165\u814c\u5236\u9752\u8c46\u3001\u897f\u7ea2\u67ff\u548c\u7ea2\u8fa3\u6912\u788e\uff0c\u7092\u81f3\u7ea2\u8fa3\u6912\u9999\u6c14\u56db\u6ea2\uff0c\u897f\u7ea2\u67ff\u5f00\u59cb\u53d8\u8f6f\u4f46\u672a\u5b8c\u5168\u5316\u5f00\uff0c\u5927\u7ea62\u52303\u5206\u949f\u3002\u82e5\u6df7\u5408\u7269\u5f00\u59cb\u7c98\u9505\uff0c\u52a0\u51651\u81f32\u6c64\u5319\u6c34\u6216\u814c\u5236\u6db2\uff0c\u6700\u591a\u53ef\u52a0\u81f34\u6c64\u5319\u3002\u6839\u636e\u53e3\u5473\u52a0\u5165\u76d0\u8c03\u5473\uff0c\u8d81\u70ed\u98df\u7528\u3002\"\n    ],\n    \"notes_ingredients\": \"\u4f60\u9700\u89812\u676f\u814c\u5236\u9752\u8c46\uff08\u81ea\u5236\u6216\u8d2d\u4e70\uff09\u3002\u814c\u5236\u9752\u897f\u7ea2\u67ff\u4e5f\u662f\u7f8e\u5473\u7684\u642d\u914d\u3002\u5982\u679c\u65b0\u9c9c\u897f\u7ea2\u67ff\u4e0d\u5728\u5b63\u8282\uff0c\u7f50\u88c5\u897f\u7ea2\u67ff\u662f\u5f88\u597d\u7684\u66ff\u4ee3\u54c1\u3002\",\n    \"notes_instructions\": \"\u4e3a\u4e86\u66f4\u6d53\u90c1\u7684\u9178\u5473\uff0c\u70f9\u996a\u65f6\u53ef\u5728\u852c\u83dc\u4e2d\u52a0\u5165\u51e0\u52fa\u814c\u5236\u6db2\u3002\"\n  }\n]\n```","behavior":"degenerate_repetition","conversation_hash":"9233710ea014a10d81a6c70af0700723","conversation_redacted":false,"conversation_toxic":false,"country":"","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":4024,"n_turns_in_conversation":1,"n_words":491,"source_row_offset":18061,"source_shard":"turns-00080.parquet","timestamp":"Sat, 17 May 2025 08:29:10 GMT","turn_id":"f28bd9d0a8b5c63baebdfdf9","turn_index":0,"user_text":"\n     Goal\n    Traduire toutes les valeurs textuelles pr\u00e9sentes dans une liste d\u2019objets d\u2019une recette de cuisine de en (ISO 639) vers zh (ISO 639), en respectant le contexte culinaire.\n\n    Traduire pr\u00e9cis\u00e9ment les ingr\u00e9dients et termes culinaires pour qu'ils soient corrects dans la langue cible.\n    Maintenir la structure JSON intacte, en ne modifiant que les valeurs.\n    S\u2019assurer que les ingr\u00e9dients restent compr\u00e9hensibles et adapt\u00e9s \u00e0 la langue cible.\n\n    Return Format\n    Tu dois renvoyer une liste d\u2019objets sous la forme re\u00e7u.\n    - Chaque valeur doit \u00eatre correctement traduite en zh.\n    - Les ingr\u00e9dients doivent \u00eatre adapt\u00e9s \u00e0 la langue cible.\n    - Aucune cl\u00e9 ne doit \u00eatre modifi\u00e9e.\n\n    Warnings\n    - Ne modifie pas la structure JSON, uniquement les valeurs textuelles.\n    - Fais attention aux ingr\u00e9dients : une mauvaise traduction peut alt\u00e9rer la compr\u00e9hension.\n    - Ne laisse aucune valeur non traduite.\n    - Ne renvoie que le JSON, sans explication.\n\n    Context Dump\n    Langue source : en (ISO 639)\n    Langue cible : zh (ISO 639)\n    Donn\u00e9es \u00e0 traduire :\n\n    [\n  {\n    \"recipeCode\": \"c8bf2797bec545f1acb13b0b4ed0e285\",\n    \"updated\": \"2025-05-17T08:28:58.326Z\",\n    \"title\": \"Saut\u00e9ed Pickled Green Beans\",\n    \"subtitle\": \"Fasulye Tur\u015fusu Kavurmas\u0131\",\n    \"description\": \"This quick saut\u00e9 features soft-cooked onions and tomatoes that provide a sweet contrast to crispy, tangy pickled green beans. At Okyanus Bal\u0131k 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.\",\n    \"ingredients\": [\n      {\n        \"section\": \"For the recipe\",\n        \"ingredients\": [\n          \"olive oil\",\n          \"onion, coarsely chopped (mounded (59.147 ml)).\",\n          \"1- to (50.8 mm) lengths everyday green bean pickles or store-bought pickled beans, drained\",\n          \"ripe, juicy tomato, coarsely chopped, or canned tomatoes, coarsely chopped\",\n          \"turkish or other crushed red pepper flakes, or taste\",\n          \"water or pickle brine, if needed\",\n          \"fine sea salt (optional).\"\n        ]\n      }\n    ],\n    \"instructions\": [\n      \"Heat the olive oil in an 8-inch skillet over medium heat. Add the onions and saut\u00e9, stirring, until they start to curl at the edges and turn golden.\",\n      \"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.\"\n    ],\n    \"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.\",\n    \"notes_instructions\": \"For an extra tangy flavor, add a few spoonfuls of pickle brine to the vegetables while cooking.\"\n  }\n]\n\n    "}],"shard":{"index":80,"name":"turns-00080.parquet","rows":41311}}