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This behaviour is the source of the following dependency conflicts.\n", "google-genai 1.12.1 requires httpx<1.0.0,>=0.28.1, but you have httpx 0.27.2 which is incompatible.\u001b[0m\u001b[31m\n", "\u001b[0mRequirement already satisfied: bitsandbytes in /usr/local/lib/python3.11/dist-packages (0.45.5)\n", "Requirement already satisfied: torch<3,>=2.0 in /usr/local/lib/python3.11/dist-packages (from bitsandbytes) (2.6.0+cu124)\n", "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.11/dist-packages (from bitsandbytes) (2.0.2)\n", "Requirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from torch<3,>=2.0->bitsandbytes) (3.18.0)\n", "Requirement already satisfied: typing-extensions>=4.10.0 in /usr/local/lib/python3.11/dist-packages (from torch<3,>=2.0->bitsandbytes) (4.13.2)\n", "Requirement already satisfied: networkx in /usr/local/lib/python3.11/dist-packages (from torch<3,>=2.0->bitsandbytes) (3.4.2)\n", "Requirement already satisfied: jinja2 in /usr/local/lib/python3.11/dist-packages (from torch<3,>=2.0->bitsandbytes) (3.1.6)\n", "Requirement already satisfied: fsspec in /usr/local/lib/python3.11/dist-packages (from torch<3,>=2.0->bitsandbytes) (2025.3.2)\n", "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch<3,>=2.0->bitsandbytes) (12.4.127)\n", "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch<3,>=2.0->bitsandbytes) (12.4.127)\n", "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch<3,>=2.0->bitsandbytes) (12.4.127)\n", "Requirement already satisfied: nvidia-cudnn-cu12==9.1.0.70 in /usr/local/lib/python3.11/dist-packages (from torch<3,>=2.0->bitsandbytes) (9.1.0.70)\n", "Requirement already satisfied: nvidia-cublas-cu12==12.4.5.8 in /usr/local/lib/python3.11/dist-packages (from torch<3,>=2.0->bitsandbytes) (12.4.5.8)\n", "Requirement already satisfied: nvidia-cufft-cu12==11.2.1.3 in /usr/local/lib/python3.11/dist-packages (from torch<3,>=2.0->bitsandbytes) (11.2.1.3)\n", "Requirement already satisfied: nvidia-curand-cu12==10.3.5.147 in /usr/local/lib/python3.11/dist-packages (from torch<3,>=2.0->bitsandbytes) (10.3.5.147)\n", "Requirement already satisfied: nvidia-cusolver-cu12==11.6.1.9 in /usr/local/lib/python3.11/dist-packages (from torch<3,>=2.0->bitsandbytes) (11.6.1.9)\n", "Requirement already satisfied: nvidia-cusparse-cu12==12.3.1.170 in /usr/local/lib/python3.11/dist-packages (from torch<3,>=2.0->bitsandbytes) (12.3.1.170)\n", "Requirement already satisfied: nvidia-cusparselt-cu12==0.6.2 in /usr/local/lib/python3.11/dist-packages (from torch<3,>=2.0->bitsandbytes) (0.6.2)\n", "Requirement already satisfied: nvidia-nccl-cu12==2.21.5 in /usr/local/lib/python3.11/dist-packages (from torch<3,>=2.0->bitsandbytes) (2.21.5)\n", "Requirement already satisfied: nvidia-nvtx-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch<3,>=2.0->bitsandbytes) (12.4.127)\n", "Requirement already satisfied: nvidia-nvjitlink-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch<3,>=2.0->bitsandbytes) (12.4.127)\n", "Requirement already satisfied: triton==3.2.0 in /usr/local/lib/python3.11/dist-packages (from torch<3,>=2.0->bitsandbytes) (3.2.0)\n", "Requirement already satisfied: sympy==1.13.1 in /usr/local/lib/python3.11/dist-packages (from torch<3,>=2.0->bitsandbytes) (1.13.1)\n", "Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.11/dist-packages (from sympy==1.13.1->torch<3,>=2.0->bitsandbytes) (1.3.0)\n", "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.11/dist-packages (from jinja2->torch<3,>=2.0->bitsandbytes) (3.0.2)\n", "Requirement already satisfied: transformers in /usr/local/lib/python3.11/dist-packages (4.51.3)\n", "Requirement already satisfied: accelerate in /usr/local/lib/python3.11/dist-packages (1.6.0)\n", "Requirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from transformers) (3.18.0)\n", "Requirement already satisfied: huggingface-hub<1.0,>=0.30.0 in /usr/local/lib/python3.11/dist-packages (from transformers) (0.30.2)\n", "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.11/dist-packages (from transformers) (2.0.2)\n", "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.11/dist-packages (from transformers) (24.2)\n", "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.11/dist-packages (from transformers) (6.0.2)\n", "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.11/dist-packages (from transformers) (2024.11.6)\n", "Requirement already satisfied: requests in /usr/local/lib/python3.11/dist-packages (from transformers) (2.32.3)\n", "Requirement already satisfied: tokenizers<0.22,>=0.21 in /usr/local/lib/python3.11/dist-packages (from transformers) (0.21.1)\n", "Requirement already satisfied: safetensors>=0.4.3 in /usr/local/lib/python3.11/dist-packages (from transformers) (0.5.3)\n", "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.11/dist-packages (from transformers) (4.67.1)\n", "Requirement already satisfied: psutil in /usr/local/lib/python3.11/dist-packages (from accelerate) (5.9.5)\n", "Requirement already satisfied: torch>=2.0.0 in /usr/local/lib/python3.11/dist-packages (from accelerate) (2.6.0+cu124)\n", "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub<1.0,>=0.30.0->transformers) (2025.3.2)\n", "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub<1.0,>=0.30.0->transformers) (4.13.2)\n", "Requirement already satisfied: networkx in /usr/local/lib/python3.11/dist-packages (from torch>=2.0.0->accelerate) (3.4.2)\n", "Requirement already satisfied: jinja2 in /usr/local/lib/python3.11/dist-packages (from torch>=2.0.0->accelerate) (3.1.6)\n", "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch>=2.0.0->accelerate) (12.4.127)\n", "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch>=2.0.0->accelerate) (12.4.127)\n", "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch>=2.0.0->accelerate) (12.4.127)\n", "Requirement already satisfied: nvidia-cudnn-cu12==9.1.0.70 in /usr/local/lib/python3.11/dist-packages (from torch>=2.0.0->accelerate) (9.1.0.70)\n", "Requirement already satisfied: nvidia-cublas-cu12==12.4.5.8 in /usr/local/lib/python3.11/dist-packages (from torch>=2.0.0->accelerate) (12.4.5.8)\n", "Requirement already satisfied: nvidia-cufft-cu12==11.2.1.3 in /usr/local/lib/python3.11/dist-packages (from torch>=2.0.0->accelerate) (11.2.1.3)\n", "Requirement already satisfied: nvidia-curand-cu12==10.3.5.147 in /usr/local/lib/python3.11/dist-packages (from torch>=2.0.0->accelerate) (10.3.5.147)\n", "Requirement already satisfied: nvidia-cusolver-cu12==11.6.1.9 in /usr/local/lib/python3.11/dist-packages (from torch>=2.0.0->accelerate) (11.6.1.9)\n", "Requirement already satisfied: nvidia-cusparse-cu12==12.3.1.170 in /usr/local/lib/python3.11/dist-packages (from torch>=2.0.0->accelerate) (12.3.1.170)\n", "Requirement already satisfied: nvidia-cusparselt-cu12==0.6.2 in /usr/local/lib/python3.11/dist-packages (from torch>=2.0.0->accelerate) (0.6.2)\n", "Requirement already satisfied: nvidia-nccl-cu12==2.21.5 in /usr/local/lib/python3.11/dist-packages (from torch>=2.0.0->accelerate) (2.21.5)\n", "Requirement already satisfied: nvidia-nvtx-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch>=2.0.0->accelerate) (12.4.127)\n", "Requirement already satisfied: nvidia-nvjitlink-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch>=2.0.0->accelerate) (12.4.127)\n", "Requirement already satisfied: triton==3.2.0 in /usr/local/lib/python3.11/dist-packages (from torch>=2.0.0->accelerate) (3.2.0)\n", "Requirement already satisfied: sympy==1.13.1 in /usr/local/lib/python3.11/dist-packages (from torch>=2.0.0->accelerate) (1.13.1)\n", "Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.11/dist-packages (from sympy==1.13.1->torch>=2.0.0->accelerate) (1.3.0)\n", "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.11/dist-packages (from requests->transformers) (3.4.1)\n", "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.11/dist-packages (from requests->transformers) (3.10)\n", "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.11/dist-packages (from requests->transformers) (2.4.0)\n", "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.11/dist-packages (from requests->transformers) (2025.4.26)\n", "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.11/dist-packages (from jinja2->torch>=2.0.0->accelerate) (3.0.2)\n" ] } ], "source": [ "!pip install -q requests torch bitsandbytes transformers sentencepiece accelerate openai httpx==0.27.2\n", "!pip install -U bitsandbytes\n", "!pip install -U transformers accelerate" ] }, { "cell_type": "code", "source": [ "# imports\n", "\n", "import os\n", "import requests\n", "from IPython.display import Markdown, display, update_display\n", "from openai import OpenAI\n", "from google.colab import drive\n", "from huggingface_hub import login\n", "from google.colab import userdata\n", "from transformers import AutoTokenizer, AutoModelForCausalLM, TextStreamer, BitsAndBytesConfig, pipeline, TextGenerationPipeline\n", "import torch" ], "metadata": { "id": "u0qdj2ynjjRz" }, "execution_count": 9, "outputs": [] }, { "cell_type": "code", "source": [ "# Models\n", "GPT = 'gpt2'\n", "FALCON = \"tiiuae/falcon-rw-1b\"\n", "MISTRAL = \"mistralai/Mistral-7B-Instruct-v0.1\"\n", "Databricks = \"databricks/dolly-v2-3b\"\n" ], "metadata": { "id": "a_sHgTj_jpDE" }, "execution_count": 10, "outputs": [] }, { "cell_type": "code", "source": [ "# Sign in to HuggingFace Hub\n", "\n", "hf_token = userdata.get('HF_TOKEN')\n", "login(hf_token, add_to_git_credential=True)" ], "metadata": { "id": "JYjtu3cPj2Th" }, "execution_count": 11, "outputs": [] }, { "cell_type": "code", "source": [ "# Flatten the messages into a single plain prompt\n", "# prompt = \"\"\"\n", "# Generate {{n}} fake job postings for a {{role}} position.\n", "\n", "# Only output a JSON array like:\n", "# [\n", "# {{\n", "# \"title\": \"Software Engineer\",\n", "# \"description\": \"Develop backend APIs and services.\",\n", "# \"requirements\": [\"Python\", \"FastAPI\", \"MongoDB\"],\n", "# \"location\": \"San Francisco\",\n", "# \"company_name\": \"TechCorp\"\n", "# }},\n", "# ...\n", "# ]\n", "# Return valid JSON only. No markdown. No explanations.\n", "# \"\"\"\n", "\n", "# prompt = \"\"\"\n", "# Generate exactly {{n}} fake job postings for a {{role}}.\n", "\n", "# Each posting must be a JSON object with:\n", "# - title\n", "# - description (5-10 sentences)\n", "# - requirements (array of 3-5 strings)\n", "# - location\n", "# - company_name\n", "\n", "# Return a single JSON array with {n} items. No explanations. No markdown.\n", "# ONLY the JSON array as output.\n", "# \"\"\"\n", "\n", "prompt = \"\"\"\n", "Generate one fake job posting for a {{role}}.\n", "\n", "Return only a single JSON object with:\n", "- title\n", "- description (5-10 sentences)\n", "- requirements (array of 4-6 strings)\n", "- location\n", "- company_name\n", "\n", "No explanations, no extra text.\n", "Only the JSON object.\n", "\"\"\"\n", "\n", "\n", "\n" ], "metadata": { "id": "7IUshG1fkQ7k" }, "execution_count": 12, "outputs": [] }, { "cell_type": "code", "source": [ "!pip install safetensors" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "-9nzEpDd-dkd", "outputId": "484ed145-951f-4950-f9ba-bf7ed6e30a13" }, "execution_count": 13, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Requirement already satisfied: safetensors in /usr/local/lib/python3.11/dist-packages (0.5.3)\n" ] } ] }, { "cell_type": "code", "source": [ "import os\n", "os.makedirs(\"/tmp/dolly_offload\", exist_ok=True)" ], "metadata": { "id": "D13qucmC-qGr" }, "execution_count": 14, "outputs": [] }, { "cell_type": "code", "source": [ "bnb_config = BitsAndBytesConfig(\n", " load_in_4bit=True,\n", " bnb_4bit_use_double_quant=True,\n", " bnb_4bit_compute_dtype=torch.bfloat16,\n", " bnb_4bit_quant_type=\"nf4\"\n", ")" ], "metadata": { "id": "4qf967BtEqqx" }, "execution_count": 15, "outputs": [] }, { "cell_type": "code", "source": [ "def load_model_and_tokenizer():\n", " tokenizer = AutoTokenizer.from_pretrained(MISTRAL, trust_remote_code=True)\n", "\n", " model = AutoModelForCausalLM.from_pretrained(\n", " MISTRAL,\n", " device_map={\"\": \"cuda\"},\n", " trust_remote_code=True,\n", " offload_folder=\"/tmp/dolly_offload\",\n", " quantization_config=bnb_config\n", " )\n", "\n", " return model, tokenizer\n" ], "metadata": { "id": "GjV7joEMjujM" }, "execution_count": 16, "outputs": [] }, { "cell_type": "code", "source": [ "# generator = pipeline(\"text-generation\", model=Databricks, device_map=\"auto\", trust_remote_code=True, offload_folder=\"/tmp/dolly_offload\")\n", "\n", "def generate_job(role=\"Software Engineer\", model=None, tokenizer=None):\n", " # prompt = prompt.format(role=role, n=n)\n", " # outputs = generator(prompt, max_new_tokens=500, do_sample=True, temperature=0.9)\n", " # return outputs[0]['generated_text']\n", "\n", " # Apply chat template formatting\n", " # inputs = tokenizer.apply_chat_template(messages, return_tensors=\"pt\").to(model.device)\n", " inputs = tokenizer(prompt.format(role=role), return_tensors=\"pt\")\n", " inputs = {k: v.to(model.device) for k, v in inputs.items()}\n", "\n", "\n", " # Generate output\n", " outputs = model.generate(\n", " **inputs,\n", " max_new_tokens=600,\n", " do_sample=True,\n", " temperature=0.2,\n", " top_p=0.9,\n", " pad_token_id=tokenizer.eos_token_id\n", " )\n", "\n", " # Decode and return\n", " result = tokenizer.decode(outputs[0], skip_special_tokens=True)\n", " return result\n", "\n" ], "metadata": { "id": "5w89B0MwkJWo" }, "execution_count": 17, "outputs": [] }, { "cell_type": "code", "source": [ "\n", "def generate_jobs(role=\"Software Engineer\", n=5):\n", " model, tokenizer = load_model_and_tokenizer()\n", " role = \"Software Engineer\"\n", " fake_jobs = []\n", " for i in range(n):\n", " fake_jobs.append(generate_job(role=role, model=model, tokenizer=tokenizer))\n", " return fake_jobs" ], "metadata": { "id": "ULhKrRe7XZmW" }, "execution_count": 18, "outputs": [] }, { "cell_type": "code", "source": [ "print(generate_jobs(role=\"Software Engineer\", n=10))" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 406, "referenced_widgets": [ "1d1fe06ac632475086ed5964ed000360", "c138f597c98c4944b54d36510ecc8e0b", "bef2531516164e85bb79b86a791dd00d", "1cb9fc011950479a8d4832bc52c3399c", "974e8f7f05ef472d85d5ea71425e6c39", "696090959af8499e9a38777e664b85c1", "973bcc9740b4426da4c680d11f3c1f7e", "3cb5d8fdb5fb4b6a99f6733c00df8378", "58f4369c68434d569d5eb1bc36e71775", "a05df972876941e3b6faab56cc30a4b8", "9c61d90b63dd4fb5a481282d6d6eb8e8", "2b71f87a02a540488a9e07f072f8807a", "548cd7e9fab54470bc52810f27784760", "9c5eb078ece84a57aa9c402c9cad3b0b", "ee00a9f599db4affabb7bf1c4df6ca1a", "52bd638607bf4e1aaf224ebdcfa3693d", "771619a5acd343c788b8189167af09d4", "09a1b30b5659452f95ebb2e72466c750", "145a1f1032a44079a262db381e60d401", "99888ad83b51485f959f977ba4418119", "ec0854c2ea9a4c9280b6876df365db9d", "dac5892c85214f69a5d75d5dc4858dfe", "41b669da565e4204b848b754dfa28ac8", "e806afdada48418c9e353b94a38cd703", "7898b7322b014e96984c3d09a29a57fb", "d665270b05d64effba568ded85eee1b4", "df087de9ade24058b1cf32e1556f7cb6", "584330ab439b4887b1050a7f14dc5d7c", "880b32d3bd1d4af8b5d0b449aab87e8b", "97d09f016e274cca93927f3bd8329352", "d87ef5878c0f4211809716674d0d8413", "556109848b1c4ebc99a6cc7c0be519e0", "8d6cdfd75e3f4a628c9e785d3c469d98", "fb1ff6f4482143c39be1cca57ec2fc8b", "83e6421843ad487c91bc75510b90f198", "9e74a7b74e1a4b119af5b95d572bac3c", "080c34ad56c84c229b1555b15b354aad", "d968bf43e8574d9090326b31c9a7fd93", "e78b05f33ee54c968fd87b77a2470bce", "79a201f7ab7e49efa9e3e1504012dec2", "6e5d431074de4955a97d4ea36621ae36", "bfc581362fbc4aca85df7b2a943dd5e4", "bc9b585bfd2847bb9f22c4720bd19033", "8addd2418c3049f3be32465cc9a408d4", "c7b5bb9ef22f4ebe9969d4d10d63d24c", "d8c3f3ec329743f6b2f21d21601f092a", "2fee19152ef34eeaba541d559b9a0bc0", "2740de6be1ae4e3bacc642c39828883b", "4104813265f34db0ab09c9d6c148ba29", "6d2dbad5a0984f8382abd18910c14343", "32285185818f40a6b07c6d6f6175b70c", "79da3c26e0fb4405a198c2255df9ec00", "c95bea4e04ff49078821a5dd67f0c28a", "3695b9dde85348efb683e31e5d52e210", "1d982bed2d4645b8a19295b7812cef49", "32c58f50bb1c44e085ae3663004fcfff", "c4df70cf509541828d3a06c380fdfe3d", "abd2737f597f48b0846a74c743307917", "a2a52b5e3c104e1cbec513a9f8744db2", "ba57460b8ee24f4e96f8a603914b7073", "d17cd0e49fa94361894660c0645ec9a8", "6cd364a43f6f4ea793b05bf14ee9d687", "a80f72a5e41047f1898d5b6f00a2c69b", "c6f6fca0f35b44fbb9037337a5bc0431", "3d07e648a5644742b8112146e952c44a", "bff978fcc6f94f55bf605c6d9c23cfd2", "eca24e648bcf4cc684f15da684e2791d", "dc82b611b8c145eb8ebc7b80073e9ae1", "f3e6040a241c4ac7b715bb07a9ec6d6b", "e310ab9f4338443e82d257ddc21f48bb", "9dd0e53a7a2a4d668c5640d938b71c9f", "1fc933b90fa546c884181136373ad005", "94f3ee73e2c04092ac5522c6ef038ea1", "81d8563026e04f5ab00eced0da89a7ef", "95f081aaf9e84c2f91c82a4e2f183009", "965cfc093b5040bbaec177820e45ec95", "d328397d81f343e28dd1a6e52c5f0ae7", "f73f9c7f341c4a99b00585343bf4d4bd", "2a11e010825b42d4a949ad64ae0d1933", "15b769156f6a4d2988f1c09f3820f7ef", "a0484e3846c647b892d2de3797496605", "cb042f80aaf04bf1963d637d1771741e", "852ba7d4221a475488411f5014362496", "38dc7c1e65324e3097d8738532272e32", "613da14abc24460db3bb337886cb407c", "37a495a5836f413ea5f662538d51a939", "9c61322c006f465385df301121462e82", "d93d0bb6ebc943a1be6902bd88cef441", "50a2a1bd13db4045a4ae01138470c42b", "ad7cba643d1742cdb47c433bf50072f9", "57ef5d067e7343239525a6da237b29eb", "7567388a58a340d4a0f384f79ee13ddc", "52c2896ab41a4d2592484084cb501e5a", "22957622a42345b991371153c29583c4", "d34c879607b041739a2cc6273509e330", "d1e7bdd4faac4765862fc809017c4856", "fcb0ad846398455faccf0d797549f589", "b381226552c9462d858051fcb7240727", "94e630795bc247e08e6af434c5924cdd", "2b496c218e2049ff9156ff5b3bbdb90b", "62d3b35a3924417894094d3bbf993932", "41737448e98a48dcbe117351645395de", "e83735cd79674a3482f0b90d4c9a3e3d", "eff6ca539e2947e9b2987977f143de9a", "aa75292545a649eda8cb7bab0ac9bbcd", "22c0e2213505435eaeebdfe330b8fbb8", "7de820edeeaf4210af68c721bab3082d", "66ef664b717343bdaf8e5c4610b2a678", "f09534cbda8c4e91b2e073c0eca0cb96", "7d8b5a2a52aa4957bc5905021898d8f4", "1c68a822580a4960acad93be9fd48ce3", "6df81f91b17f41dc91fc9f367fa0afab", "17742936c9ac46e588d1ce42235745d0", "17f0cd6f05184164b48ef906f192505a", "936a67f2de2e44728b83600f4fa0569c", "d5ad82f6b9654a8cb888613caaaaa097", "b014979e237344129545ff2c384c1c1c", "b99c12d57d4a4eab84aefbef58452c32", "5923bbdcf6334393ad832765f129bdec", "260ac8c28531450bba1deac4e4669dc4", "067959a4ef614c498c28bb83c10e16de" ] }, "id": "kKsErltXXwy1", "outputId": "683c2e5e-16d8-4fe3-efdd-664c385c71e7" }, "execution_count": 19, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "tokenizer_config.json: 0%| | 0.00/2.10k [00:00=2.0 in /usr/local/lib/python3.11/dist-packages (from bitsandbytes) (2.6.0+cu124)\n", "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.11/dist-packages (from bitsandbytes) (2.0.2)\n", "Requirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from torch<3,>=2.0->bitsandbytes) (3.18.0)\n", "Requirement already satisfied: typing-extensions>=4.10.0 in /usr/local/lib/python3.11/dist-packages (from torch<3,>=2.0->bitsandbytes) (4.13.2)\n", "Requirement already satisfied: networkx in /usr/local/lib/python3.11/dist-packages (from torch<3,>=2.0->bitsandbytes) (3.4.2)\n", "Requirement 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extract_json_objects_from_text_block(texts):\n", " \"\"\"\n", " Accepts either a single string or a list of strings.\n", " Extracts all valid JSON objects from messy text blocks.\n", " \"\"\"\n", " if isinstance(texts, str):\n", " texts = [texts] # wrap in list if single string\n", "\n", " pattern = r\"\\{[\\s\\S]*?\\}\"\n", " results = []\n", "\n", " for raw_text in texts:\n", " matches = re.findall(pattern, raw_text)\n", " for match in matches:\n", " try:\n", " obj = json.loads(match)\n", " results.append(obj)\n", " except json.JSONDecodeError:\n", " continue\n", "\n", " return results\n", "\n", "text = generate_jobs(role=\"Software Engineer\", n=10)\n", "print(extract_json_objects_from_text_block(text))" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 86, "referenced_widgets": [ "b5dd409cf6e04764adbb7c2a49b7be86", "65187b4ebb2041b39778268e8b4d6b0d", "33317cac10ca4a98bf4433c1eff43435", "f81f5402902c4c04b10895782287e908", "c471914fe0d34ae8967bac2820637d5b", "7aead6f6cffa40a383f1b8c64943329e", "f24fe57d8e164fd68185b4c117e7c097", "f913ca9ab6d44ab1b788a36bd964ed39", "ed34016801264a05bb3697eca2ac22ef", "fe622254072540fda3b0dd6b2cab6e4a", "5d95bdea47594e21855a6e564d0760da" ] }, "id": "1uzTM2G1oqDs", "outputId": "08e88ab0-ca17-46d3-8f9c-6a595863aeba" }, "execution_count": 22, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Loading checkpoint shards: 0%| | 0/2 [00:00=22.0 (from gradio)\n", " Downloading aiofiles-24.1.0-py3-none-any.whl.metadata (10 kB)\n", "Requirement already satisfied: anyio<5.0,>=3.0 in /usr/local/lib/python3.11/dist-packages (from gradio) (4.9.0)\n", "Collecting fastapi<1.0,>=0.115.2 (from gradio)\n", " Downloading fastapi-0.115.12-py3-none-any.whl.metadata (27 kB)\n", "Collecting ffmpy (from gradio)\n", " Downloading ffmpy-0.5.0-py3-none-any.whl.metadata (3.0 kB)\n", "Collecting gradio-client==1.10.0 (from gradio)\n", " Downloading 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parsed_jobs = extract_json_objects_from_text_block(raw_jobs)\n", "\n", " if not isinstance(parsed_jobs, list) or not all(isinstance(item, dict) for item in parsed_jobs):\n", " print(\"[ERROR] Parsed result is not a list of dicts\")\n", " return gr.update(value=[], visible=True), None\n", "\n", " filename = f\"{role.replace(' ', '_').lower()}_jobs.json\"\n", " with open(filename, \"w\") as f:\n", " json.dump(parsed_jobs, f, indent=2)\n", "\n", " print(f\"[INFO] Returning {len(parsed_jobs)} jobs -> {filename}\")\n", " return parsed_jobs, filename\n", "\n", " except Exception as e:\n", " print(f\"[FATAL ERROR] {e}\")\n", " return gr.update(value=[], visible=True), None\n", "\n", "if __name__ == \"__main__\":\n", " with gr.Blocks() as demo:\n", " gr.Markdown(\"# 🧠 Synthetic Job Dataset Generator\")\n", " gr.Markdown(\"Generate a structured dataset of job postings for a specific role.\")\n", "\n", " with gr.Row():\n", " role_input = gr.Textbox(label=\"Job Role\", placeholder=\"e.g. Software Engineer\", value=\"Software Engineer\")\n", " n_input = gr.Number(label=\"Number of Samples\", value=5, precision=0)\n", "\n", " generate_button = gr.Button(\"🚀 Generate\")\n", " output_table = gr.JSON(label=\"Generated Dataset\")\n", " download_button = gr.File(label=\"Download JSON\")\n", "\n", " generate_button.click(\n", " generate_ui,\n", " inputs=[role_input, n_input],\n", " outputs=[output_table, download_button]\n", " )\n", "\n", " demo.launch(debug=True)\n" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 730, "referenced_widgets": [ "9f9defc39ac5437e9512e5fad810b409", "1c126dfdc51c438b9b48c8a65e549ae2", "741d800130ea4830b9266f467fa6a0bf", "73c0a01f1693471c9c017143e9e9058b", "ab8174c1337b43048e05aeca72ca18ef", "5e5a992d86434e62a25fc9b7f75f4b16", "1507b1310f5045c9b691fdb102cc1686", "8a8e81f9d3a54ce49b367f8e984b4a06", "bab02b1f092b40c8983cd6440f7eaf16", "94f30dc2653a4f178c9c2ef454d24644", "a508625ef12d4a639fa9773484507709" ] }, "id": "FEByigZTo5cv", "outputId": "e452754b-e155-4b57-eced-7af37996f1f0" }, "execution_count": 25, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "It looks like you are running Gradio on a hosted a Jupyter notebook. For the Gradio app to work, sharing must be enabled. Automatically setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n", "\n", "Colab notebook detected. This cell will run indefinitely so that you can see errors and logs. To turn off, set debug=False in launch().\n", "* Running on public URL: https://bf27145eb99f8caadd.gradio.live\n", "\n", "This share link expires in 1 week. For free permanent hosting and GPU upgrades, run `gradio deploy` from the terminal in the working directory to deploy to Hugging Face Spaces (https://huggingface.co/spaces)\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "
" ] }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "Loading checkpoint shards: 0%| | 0/2 [00:00 software_engineer_jobs.json\n", "Keyboard interruption in main thread... closing server.\n", "Killing tunnel 127.0.0.1:7860 <> https://bf27145eb99f8caadd.gradio.live\n" ] } ] }, { "cell_type": "code", "source": [ "import os\n", "\n", "# Get list of all .ipynb files in /content\n", "notebooks = [f for f in os.listdir(\"/content\") if f.endswith(\".ipynb\")]\n", "print(notebooks)\n" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "ZfPQJw0Z5UD9", "outputId": "0e4ba82b-e23b-4faa-8b29-eaf87fdf9500" }, "execution_count": 27, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "[]\n" ] } ] }, { "cell_type": "code", "source": [], "metadata": { "id": "Y88jqI_u5WEL" }, "execution_count": null, "outputs": [] } ] }