{ "cells": [ { "cell_type": "markdown", "id": "a2996243-a398-4e7f-86e6-b1fbb3d0b38f", "metadata": {}, "source": [ "# Building a Gradio Frontend " ] }, { "cell_type": "markdown", "id": "27359fd5-fc05-40aa-b636-97dc340aa77e", "metadata": {}, "source": [ "## Installing packages" ] }, { "cell_type": "code", "execution_count": 1, "id": "c6d2ba96-e517-4126-b09a-a063155f9596", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Requirement already satisfied: keras_nlp in /opt/conda/lib/python3.10/site-packages (0.17.0)\n", "Requirement already satisfied: kaggle in /opt/conda/lib/python3.10/site-packages (1.6.17)\n", "Requirement already satisfied: gradio in /opt/conda/lib/python3.10/site-packages (5.4.0)\n", "Requirement already satisfied: tensorflow in /opt/conda/lib/python3.10/site-packages (2.18.0)\n", "Requirement already satisfied: keras-hub==0.17.0 in /opt/conda/lib/python3.10/site-packages (from keras_nlp) (0.17.0)\n", "Requirement already satisfied: absl-py in /opt/conda/lib/python3.10/site-packages (from keras-hub==0.17.0->keras_nlp) (1.4.0)\n", "Requirement already satisfied: numpy in /opt/conda/lib/python3.10/site-packages (from keras-hub==0.17.0->keras_nlp) (1.26.4)\n", "Requirement already satisfied: packaging in /opt/conda/lib/python3.10/site-packages (from keras-hub==0.17.0->keras_nlp) (24.1)\n", "Requirement already satisfied: regex in /opt/conda/lib/python3.10/site-packages (from keras-hub==0.17.0->keras_nlp) (2024.9.11)\n", "Requirement already satisfied: rich in /opt/conda/lib/python3.10/site-packages (from keras-hub==0.17.0->keras_nlp) (13.9.2)\n", "Requirement already satisfied: kagglehub in /opt/conda/lib/python3.10/site-packages (from keras-hub==0.17.0->keras_nlp) (0.3.3)\n", "Requirement already satisfied: tensorflow-text in /opt/conda/lib/python3.10/site-packages (from keras-hub==0.17.0->keras_nlp) (2.18.0)\n", "Requirement already satisfied: six>=1.10 in /opt/conda/lib/python3.10/site-packages (from kaggle) (1.16.0)\n", "Requirement already satisfied: certifi>=2023.7.22 in /opt/conda/lib/python3.10/site-packages (from kaggle) (2024.8.30)\n", "Requirement already satisfied: python-dateutil in /opt/conda/lib/python3.10/site-packages (from kaggle) (2.9.0.post0)\n", "Requirement already satisfied: requests in /opt/conda/lib/python3.10/site-packages (from kaggle) (2.32.3)\n", "Requirement already satisfied: tqdm in /opt/conda/lib/python3.10/site-packages (from kaggle) (4.66.5)\n", "Requirement already satisfied: python-slugify in /opt/conda/lib/python3.10/site-packages (from kaggle) (8.0.4)\n", "Requirement already satisfied: urllib3 in /opt/conda/lib/python3.10/site-packages (from kaggle) (1.26.20)\n", "Requirement already satisfied: bleach in /opt/conda/lib/python3.10/site-packages (from kaggle) (6.1.0)\n", "Requirement already satisfied: aiofiles<24.0,>=22.0 in /opt/conda/lib/python3.10/site-packages (from gradio) (23.2.1)\n", "Requirement already satisfied: anyio<5.0,>=3.0 in 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(3.10.10)\n", "Requirement already satisfied: pandas<3.0,>=1.0 in /opt/conda/lib/python3.10/site-packages (from gradio) (2.2.3)\n", "Requirement already satisfied: pillow<12.0,>=8.0 in /opt/conda/lib/python3.10/site-packages (from gradio) (10.4.0)\n", "Requirement already satisfied: pydantic>=2.0 in /opt/conda/lib/python3.10/site-packages (from gradio) (2.9.2)\n", "Requirement already satisfied: pydub in /opt/conda/lib/python3.10/site-packages (from gradio) (0.25.1)\n", "Requirement already satisfied: python-multipart==0.0.12 in /opt/conda/lib/python3.10/site-packages (from gradio) (0.0.12)\n", "Requirement already satisfied: pyyaml<7.0,>=5.0 in /opt/conda/lib/python3.10/site-packages (from gradio) (6.0.2)\n", "Requirement already satisfied: ruff>=0.2.2 in /opt/conda/lib/python3.10/site-packages (from gradio) (0.7.1)\n", "Requirement already satisfied: safehttpx<1.0,>=0.1.1 in /opt/conda/lib/python3.10/site-packages (from gradio) (0.1.1)\n", "Requirement already satisfied: semantic-version~=2.0 in /opt/conda/lib/python3.10/site-packages (from gradio) (2.10.0)\n", "Requirement already satisfied: starlette<1.0,>=0.40.0 in /opt/conda/lib/python3.10/site-packages (from gradio) (0.41.2)\n", "Requirement already satisfied: tomlkit==0.12.0 in /opt/conda/lib/python3.10/site-packages (from gradio) (0.12.0)\n", "Requirement already satisfied: typer<1.0,>=0.12 in /opt/conda/lib/python3.10/site-packages (from gradio) (0.12.5)\n", "Requirement already satisfied: typing-extensions~=4.0 in /opt/conda/lib/python3.10/site-packages (from gradio) (4.12.2)\n", "Requirement already satisfied: uvicorn>=0.14.0 in /opt/conda/lib/python3.10/site-packages (from gradio) (0.31.1)\n", "Requirement already satisfied: fsspec in /opt/conda/lib/python3.10/site-packages (from gradio-client==1.4.2->gradio) (2024.9.0)\n", "Requirement already satisfied: websockets<13.0,>=10.0 in /opt/conda/lib/python3.10/site-packages (from gradio-client==1.4.2->gradio) (12.0)\n", "Requirement already 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requests->kaggle) (3.3.2)\n", "Requirement already satisfied: markdown>=2.6.8 in /opt/conda/lib/python3.10/site-packages (from tensorboard<2.19,>=2.18->tensorflow) (3.7)\n", "Requirement already satisfied: tensorboard-data-server<0.8.0,>=0.7.0 in /opt/conda/lib/python3.10/site-packages (from tensorboard<2.19,>=2.18->tensorflow) (0.7.2)\n", "Requirement already satisfied: werkzeug>=1.0.1 in /opt/conda/lib/python3.10/site-packages (from tensorboard<2.19,>=2.18->tensorflow) (3.0.6)\n", "Requirement already satisfied: click>=8.0.0 in /opt/conda/lib/python3.10/site-packages (from typer<1.0,>=0.12->gradio) (8.1.7)\n", "Requirement already satisfied: shellingham>=1.3.0 in /opt/conda/lib/python3.10/site-packages (from typer<1.0,>=0.12->gradio) (1.5.4)\n", "Requirement already satisfied: webencodings in /opt/conda/lib/python3.10/site-packages (from bleach->kaggle) (0.5.1)\n", "Requirement already satisfied: text-unidecode>=1.3 in /opt/conda/lib/python3.10/site-packages (from python-slugify->kaggle) (1.3)\n", "Requirement already satisfied: markdown-it-py>=2.2.0 in /opt/conda/lib/python3.10/site-packages (from rich->keras-hub==0.17.0->keras_nlp) (3.0.0)\n", "Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /opt/conda/lib/python3.10/site-packages (from rich->keras-hub==0.17.0->keras_nlp) (2.18.0)\n", "Requirement already satisfied: mdurl~=0.1 in /opt/conda/lib/python3.10/site-packages (from markdown-it-py>=2.2.0->rich->keras-hub==0.17.0->keras_nlp) (0.1.2)\n" ] } ], "source": [ "!pip install keras_nlp kaggle gradio tensorflow" ] }, { "cell_type": "code", "execution_count": 2, "id": "e8bd9ce4-a2b9-4778-9081-9a0f2cf666f4", "metadata": { "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "2024-10-31 19:29:35.482316: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", "2024-10-31 19:29:35.844009: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", "2024-10-31 19:29:36.148747: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:477] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n", "E0000 00:00:1730402976.395556 5425 cuda_dnn.cc:8310] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", "E0000 00:00:1730402976.465622 5425 cuda_blas.cc:1418] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", "2024-10-31 19:29:37.078974: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n", "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n" ] } ], "source": [ "import keras_nlp\n", "import os\n", "import tensorflow as tf" ] }, { "cell_type": "markdown", "id": "225e9356-246f-4b41-a054-7802f14b9980", "metadata": {}, "source": [ "## Loading the model from kaggle" ] }, { "cell_type": "code", "execution_count": 4, "id": "d553e22c-b794-4ce1-8c66-1179467515b9", "metadata": { "tags": [] }, "outputs": [], "source": [ "#For safety, add this to kaggle or google secrets\n", "os.environ['KAGGLE_USERNAME'] = 'ayomidezulkazeem' #username\n", "os.environ['KAGGLE_KEY'] = '245a313b018fe8355198d9c48413b991' #kaggle_key" ] }, { "cell_type": "code", "execution_count": 5, "id": "3c9b993f-8fa3-47b2-a100-f3d604a69bf8", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Path to model files: /home/jupyter/.cache/kagglehub/models/ayomidezulkazeem/hydrosense/keras/gemma-hydrosense-instruct-2b/1\n" ] } ], "source": [ "import kagglehub\n", "\n", "# Download latest version\n", "path = kagglehub.model_download(\"ayomidezulkazeem/hydrosense/keras/gemma-hydrosense-instruct-2b\")\n", "\n", "print(\"Path to model files:\", path)" ] }, { "cell_type": "code", "execution_count": 6, "id": "ec3555c5-18f8-4de6-ac9d-bf8525cb1a69", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Model path: /home/jupyter/.cache/kagglehub/models/ayomidezulkazeem/hydrosense/keras/gemma-hydrosense-instruct-2b/1\n" ] } ], "source": [ "print(\"Model path:\", path)" ] }, { "cell_type": "code", "execution_count": 7, "id": "624658c2-e268-43c1-8007-a3d73859dc6e", "metadata": { "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "2024-10-31 19:30:18.754472: E external/local_xla/xla/stream_executor/cuda/cuda_driver.cc:152] failed call to cuInit: INTERNAL: CUDA error: Failed call to cuInit: UNKNOWN ERROR (303)\n", "2024-10-31 19:30:18.795603: W external/local_xla/xla/tsl/framework/cpu_allocator_impl.cc:83] Allocation of 2097152000 exceeds 10% of free system memory.\n", "2024-10-31 19:30:22.851420: W external/local_xla/xla/tsl/framework/cpu_allocator_impl.cc:83] Allocation of 2097152000 exceeds 10% of free system memory.\n", "2024-10-31 19:30:23.277000: W external/local_xla/xla/tsl/framework/cpu_allocator_impl.cc:83] Allocation of 2097152000 exceeds 10% of free system memory.\n", "normalizer.cc(51) LOG(INFO) precompiled_charsmap is empty. use identity normalization.\n", "2024-10-31 19:30:42.746775: W external/local_xla/xla/tsl/framework/cpu_allocator_impl.cc:83] Allocation of 2097152000 exceeds 10% of free system memory.\n" ] } ], "source": [ "model_path = \"/home/jupyter/.cache/kagglehub/models/ayomidezulkazeem/hydrosense/keras/gemma-hydrosense-instruct-2b/1\"\n", "gemma_lm = keras_nlp.models.GemmaCausalLM.from_preset(model_path)" ] }, { "cell_type": "markdown", "id": "8cbbc6ff-00b7-4986-bfda-b6ca83734472", "metadata": {}, "source": [ "## Post-Processing the Output" ] }, { "cell_type": "code", "execution_count": 8, "id": "b684e998-f39b-44cf-ba37-e292730a512e", "metadata": { "tags": [] }, "outputs": [], "source": [ "def post_process_output(prompt, generated_text):\n", " # Remove the prompt if it's repeated at the beginning of the answer\n", " answer = generated_text.strip()\n", " if answer.startswith(prompt):\n", " answer = answer[len(prompt):].strip()\n", "\n", " # Remove any leading colons or whitespace\n", " answer = answer.lstrip(':')\n", "\n", " # Ensure the answer starts with a capital letter\n", " answer = answer.capitalize()\n", "\n", " # Ensure the answer ends with a period if it doesn't already\n", " if not answer.endswith('.'):\n", " answer += '.'\n", "\n", " return f\"{answer}\"" ] }, { "cell_type": "code", "execution_count": 9, "id": "6024cf30-930b-4fbd-ba69-dcb26f8351b8", "metadata": { "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n", "I0000 00:00:1730403102.029145 5684 service.cc:148] XLA service 0x7f34ec079e20 initialized for platform Host (this does not guarantee that XLA will be used). Devices:\n", "I0000 00:00:1730403102.032560 5684 service.cc:156] StreamExecutor device (0): Host, Default Version\n", "I0000 00:00:1730403102.142617 5684 device_compiler.h:188] Compiled cluster using XLA! This line is logged at most once for the lifetime of the process.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Based on the last service date of 2023-02-14 and the bi-annual maintenance interval, the next service due for lift station-485083 is 2023-06-12.\n" ] } ], "source": [ "prompt = \"When is the next maintenance due for Lift Station-485083 based on its last service date?\"\n", "generated_text = gemma_lm.generate(prompt, max_length=100)\n", "\n", "# Apply post-processing\n", "formatted_output = post_process_output(prompt, generated_text)\n", "print(formatted_output)" ] }, { "cell_type": "markdown", "id": "10cbb2e1-0028-4837-ad95-73e46a470561", "metadata": {}, "source": [ "## Gradio Interface" ] }, { "cell_type": "code", "execution_count": 10, "id": "f4d8e9e3-bc6f-405a-90e9-f76a5306a0b8", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "* Running on local URL: http://127.0.0.1:7860\n", "* Running on public URL: https://e357bb4e5bce8bd94b.gradio.live\n", "\n", "This share link expires in 72 hours. 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" ] }, { "data": { "text/html": [ "
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import gradio as gr\n", "import time\n", "from huggingface_hub import InferenceClient\n", "import os\n", "\n", "custom_css = \"\"\"\n", "@import url('https://fonts.googleapis.com/css2?family=Edu+AU+VIC+WA+NT+Dots:wght@400..700&family=Give+You+Glory&family=Sofia&family=Sunshiney&family=Vujahday+Script&display=swap');\n", ".gradio-container, .gradio-container * {\n", " font-family: \"Playfair Display\", serif;\n", " font-optical-sizing: auto;\n", " font-weight: ;\n", " font-style: normal;\n", "}\n", "\"\"\"\n", "js = \"\"\"\n", "function refresh() {\n", " const url = new URL(window.location);\n", " if (url.searchParams.get('__theme') === 'light') {\n", " url.searchParams.set('__theme', 'light');\n", " window.location.href = url.href;\n", " }\n", "}\n", "\"\"\"\n", "\n", "\n", "previous_sessions = []\n", "memory = [{}]\n", "\n", "\n", "\n", "def inference(prompt_text):\n", " prompt_text = prompt_text\n", " generated_text = gemma_lm.generate(prompt_text)\n", "\n", " #Apply post-processing\n", " formatted_output = post_process_output(prompt_text, generated_text)\n", " print(formatted_output)\n", "\n", " #adding a bit of delay\n", " time.sleep(1)\n", " result = formatted_output\n", " sessions = add_session(prompt_text)\n", " return result, sessions\n", "\n", "\n", "def remember(prompt, result):\n", " global memory\n", " # Store the session as a dictionary\n", " session = {'prompt': prompt, 'result': result}\n", " memory.append(session)\n", "\n", " # Update previous_sessions for display\n", " session_display = [f\"Q: {s['prompt']} \\nA: {s['result']}\" for s in memory]\n", " \n", " return \"\\n\\n\".join(session_display) # Return formatted sessions as a string\n", "\n", "\n", "def add_session(prompt_text):\n", " global previous_sessions\n", " session_name = ' '.join(prompt_text.split()[:5])\n", " \n", " if session_name and session_name not in previous_sessions:\n", " previous_sessions.append(session_name)\n", " \n", " return \"\\n\".join(previous_sessions) # Return only the session logs as a string\n", "\n", "\n", "def clear_sessions():\n", " global previous_sessions\n", " previous_sessions.clear()\n", " return \"\\n\".join(previous_sessions)\n", "\n", "def clear_fields():\n", " return \"\", \"\" # Return empty strings to clear the prompt and output fields\n", "\n", "\n", "with gr.Blocks(theme='gradio/soft', css=custom_css) as demo:\n", " gr.Markdown(\"

HydroFlow LLM Demo

\")\n", " gr.Markdown(\"

Ask me anything on Wastewater or Stormwater!

\")\n", "\n", " with gr.Row():\n", " with gr.Column(scale=1):\n", " gr.Markdown(\"## Previous Sessions\")\n", " session_list = gr.Textbox(label=\"Sessions\", value=\"\\n\".join(previous_sessions), interactive=False, lines=4, max_lines=20)\n", " add_button = gr.Button(\"New Session\")\n", " clear_session = gr.Button(\"Clear Session\")\n", "\n", " with gr.Column(scale=2):\n", " output = gr.Textbox(label=\"Result\", lines=5, max_lines=20)\n", " prompt = gr.Textbox(label=\"Enter your Prompt here\", max_lines=20)\n", " \n", " with gr.Row():\n", " generate_btn = gr.Button(\"Generate Answer\", variant=\"primary\", size=\"sm\")\n", " reset_btn = gr.Button(\"Clear Content\", variant=\"secondary\", size=\"sm\", elem_id=\"primary\")\n", "\n", "\n", " generate_btn.click(\n", " fn=inference,\n", " inputs=[prompt],\n", " outputs=[output, session_list],\n", " )\n", "\n", " prompt.submit(\n", " fn=inference,\n", " inputs=[prompt],\n", " outputs=[output, session_list],\n", " )\n", "\n", " reset_btn.click(\n", " lambda: (\"\", \"\"),\n", " inputs=None,\n", " outputs=[prompt, output]\n", " )\n", "\n", "\n", " # Button to clear the prompt and output fields\n", " add_button.click(\n", " fn=clear_fields, # Only call the clear_fields function\n", " inputs=None, # No inputs needed\n", " outputs=[prompt, output] # Clear the prompt and output fields\n", ")\n", "\n", "\n", " clear_session.click(\n", " fn=clear_sessions,\n", " inputs=None,\n", " outputs=[session_list]\n", " )\n", "\n", "demo.launch(share=True)" ] }, { "cell_type": "code", "execution_count": 1, "id": "237c776f-947b-4888-b5f9-54e055ccaff7", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Requirement already satisfied: huggingface_hub in /opt/conda/lib/python3.10/site-packages (0.26.2)\n", "Requirement already satisfied: filelock in /opt/conda/lib/python3.10/site-packages (from huggingface_hub) (3.16.1)\n", "Requirement already satisfied: fsspec>=2023.5.0 in /opt/conda/lib/python3.10/site-packages (from huggingface_hub) (2024.9.0)\n", "Requirement already satisfied: packaging>=20.9 in /opt/conda/lib/python3.10/site-packages (from huggingface_hub) (24.1)\n", "Requirement already satisfied: pyyaml>=5.1 in /opt/conda/lib/python3.10/site-packages (from huggingface_hub) (6.0.2)\n", "Requirement already satisfied: requests in /opt/conda/lib/python3.10/site-packages (from huggingface_hub) (2.32.3)\n", "Requirement already satisfied: tqdm>=4.42.1 in /opt/conda/lib/python3.10/site-packages (from huggingface_hub) (4.66.5)\n", "Requirement already satisfied: typing-extensions>=3.7.4.3 in /opt/conda/lib/python3.10/site-packages (from huggingface_hub) (4.12.2)\n", "Requirement already satisfied: charset-normalizer<4,>=2 in /opt/conda/lib/python3.10/site-packages (from requests->huggingface_hub) (3.3.2)\n", "Requirement already satisfied: idna<4,>=2.5 in /opt/conda/lib/python3.10/site-packages (from requests->huggingface_hub) (3.10)\n", "Requirement already satisfied: urllib3<3,>=1.21.1 in /opt/conda/lib/python3.10/site-packages (from requests->huggingface_hub) (1.26.20)\n", "Requirement already satisfied: certifi>=2017.4.17 in /opt/conda/lib/python3.10/site-packages (from requests->huggingface_hub) (2024.8.30)\n" ] } ], "source": [ "!pip install huggingface_hub" ] }, { "cell_type": "code", "execution_count": 3, "id": "9c2c0eaa-070e-49c7-84f5-fa300c9cd32c", "metadata": { "tags": [] }, "outputs": [], "source": [ "!git config --global credential.helper store" ] }, { "cell_type": "code", "execution_count": 4, "id": "393a76d2-90ba-4967-b80b-a81171b94fe0", "metadata": { "tags": [] }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "aa3a1d4acb7848938cbf0de6dbebc44f", "version_major": 2, "version_minor": 0 }, "text/plain": [ "VBox(children=(HTML(value='