{ "cells": [ { "cell_type": "markdown", "id": "be58b994-bc68-4166-91d5-282418b78864", "metadata": { "id": "be58b994-bc68-4166-91d5-282418b78864" }, "source": [ "# Project: Text/Langchain Portfolio (Optional)" ] }, { "cell_type": "markdown", "id": "c5120b06-0abf-49e3-b54d-db8afa9eda01", "metadata": { "id": "c5120b06-0abf-49e3-b54d-db8afa9eda01" }, "source": [ "**Instructions for Students:**\n", "\n", "Please carefully follow these steps to complete and submit your assignment:\n", "\n", "1. **Completing the Assignment**: You are required to work on and complete all tasks in the provided assignment. Be disciplined and ensure that you thoroughly engage with each task.\n", " \n", "2. **Creating a Google Drive Folder**: If you don't previously have a folder for collecting assignments, you must create a new folder in your Google Drive. This will be a repository for all your completed assignment files, helping you keep your work organized and easy to access.\n", " \n", "3. **Uploading Completed Assignment**: Upon completion of your assignment, make sure to upload all necessary files, involving codes, reports, and related documents into the created Google Drive folder. Save this link in the 'Student Identity' section and also provide it as the last parameter in the `submit` function that has been provided.\n", " \n", "4. **Sharing Folder Link**: You're required to share the link to your assignment Google Drive folder. This is crucial for the submission and evaluation of your assignment.\n", " \n", "5. **Setting Permission toPublic**: Please make sure your **Google Drive folder is set to public**. This allows your instructor to access your solutions and assess your work correctly.\n", "\n", "Adhering to these procedures will facilitate a smooth assignment process for you and the reviewers." ] }, { "cell_type": "markdown", "id": "eca56111-19cb-46c0-a77b-11bd18c55673", "metadata": { "id": "eca56111-19cb-46c0-a77b-11bd18c55673" }, "source": [ "**Description:**\n", "\n", "Welcome to your text/langchain portfolio project assignment for AI Bootcamp. In this project you will apply what you've learned so far into real-world applications.\n", "\n", "You are free to create anything as long as it's within the category of text based application or model.\n", "\n", "Some ideas for your applications:\n", "* Langchain based summarization application that's given a PDF file or a text from a text box can then create a summary of the text content.\n", "* Text generator application when given a direction in the form of short sentence can generate a 3 - 5 paragraph of text or more based on the direction.\n", "\n", "\n", "For submission, please upload the model and application to Huggingface or your own Github account.\n", "\n", "Your submission will be graded and scored and will add a maximum of 15 points to your final score.\n", "\n", "Remember, the key to mastering these concepts is practice. Do apply your knowledge, and don't hesitate to ask questions if you encounter any difficulties. Good luck!" ] }, { "cell_type": "code", "execution_count": 6, "id": "213a611a-c434-4894-ba35-689963ee5274", "metadata": { "id": "213a611a-c434-4894-ba35-689963ee5274" }, "outputs": [], "source": [ "# @title #### Student Identity\n", "student_id = \"\" # @param {type:\"string\"}\n", "name = \"Gavin Bagus Kenzie Narain\" # @param {type:\"string\"}\n", "drive_link = \"https://drive.google.com/drive/folders/1smdyFGocnCQq7Iex6ozGwW-BGq5K9Ffw?usp=sharing\" # @param {type:\"string\"}\n", "assignment_id = \"00_text_portfolio_project\"" ] }, { "cell_type": "markdown", "id": "2c97aef3-b747-49f7-99e0-4086c03e4200", "metadata": { "id": "2c97aef3-b747-49f7-99e0-4086c03e4200" }, "source": [ "## Installation and Import `rggrader` Package" ] }, { "cell_type": "code", "execution_count": 5, "id": "36c07e23-0280-467f-b0d2-44d966253bb4", "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "36c07e23-0280-467f-b0d2-44d966253bb4", "outputId": "117ef0a6-fc2f-40be-c661-3807fc5192ca" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Collecting rggrader\n", " Downloading rggrader-0.1.6-py3-none-any.whl (2.5 kB)\n", "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from rggrader) (2.31.0)\n", "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from rggrader) (1.5.3)\n", "Requirement already satisfied: Pillow in /usr/local/lib/python3.10/dist-packages (from rggrader) (9.4.0)\n", "Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.10/dist-packages (from pandas->rggrader) (2.8.2)\n", "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->rggrader) (2023.3.post1)\n", "Requirement already satisfied: numpy>=1.21.0 in /usr/local/lib/python3.10/dist-packages (from pandas->rggrader) (1.23.5)\n", "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->rggrader) (3.3.0)\n", "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->rggrader) (3.4)\n", "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->rggrader) (2.0.6)\n", "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->rggrader) (2023.7.22)\n", "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.1->pandas->rggrader) (1.16.0)\n", "Installing collected packages: rggrader\n", "Successfully installed rggrader-0.1.6\n" ] } ], "source": [ "%pip install rggrader\n", "from rggrader import submit_image\n", "from rggrader import submit" ] }, { "cell_type": "markdown", "id": "a4af3420-ff0e-472b-8b44-7a495ddf76c3", "metadata": { "id": "a4af3420-ff0e-472b-8b44-7a495ddf76c3" }, "source": [ "## Working Space" ] }, { "cell_type": "code", "execution_count": 1, "id": "c1fb239a-1c81-4476-9009-d87abadf9506", "metadata": { "id": "c1fb239a-1c81-4476-9009-d87abadf9506" }, "outputs": [], "source": [ "# Write your code here\n", "# !pip install -U langchain python-dotenv openai chromadb bitsandbytes transformers peft accelerate\n", "!pip install -q -U langchain\n", "!pip install -q -U ctransformers[cuda]" ] }, { "cell_type": "code", "execution_count": 1, "id": "vKiTNfz7z8Yv", "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 81, "referenced_widgets": [ "54c0e2e43d27482f9dcb67ce9d60c85c", "a1595618ab5f48e08a7c9a6a0879ad26", "4912fec232b44537a80c52b04291fe7b", "ca88cec6e0834e27990b8350b752c827", "5ba1c94eddd24e2aae5b25d9d6884dc0", "1708f929db494251b19de5d0322ff26d", "2751b58cfcc84215aabfc45de27b77b3", "38895ca8e4f749838b071b724cc39b46", "55b8641523d84c15bea6b35f04c554fc", "866da5a8e421477c8089dbfa1bdcc812", "66bbfff8db6146b2a7b922b1b590f1f9", "0b7b4570dc944e818348db1ce6954e3a", "580648891bde443786cf1b06070f846f", "24e964fbe9044395a3bce8b1a83a05de", "a5e99e6026f24c408cca741c6fc2509c", "095fd8b26865435589b2e79e12ecef24", "a9cb9e343b93467895741fff5f0db25d", "d9bf82bf03984146aadfa5441f89ea98", "5adcafc9d6f84ca9ae372ee9295cd944", "ccd9de576ca9430d9a8064a3a8e1347b", "9d20bac626ef472f848d727d56afc98c", "75490fa060524ef3bd675bb41a0c5eb3" ] }, "id": "vKiTNfz7z8Yv", "outputId": "8b1c80a7-2aeb-4ce1-aab2-f235c001c78c" }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "54c0e2e43d27482f9dcb67ce9d60c85c", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Fetching 1 files: 0%| | 0/1 [00:00[INST] You are a helpful, respectful and honest assistant. Answer exactly in few words from the context\n", "Answer the question below from context below :\n", "{context}\n", "{question} [/INST] \n", "\"\"\"\n", "\n", "prompt = PromptTemplate(template=template, input_variables=[\"question\",\"context\"])\n", "llm_chain = LLMChain(prompt=prompt, llm=llm)" ] }, { "cell_type": "code", "execution_count": 4, "id": "KzW-JFVVCe4U", "metadata": { "id": "KzW-JFVVCe4U" }, "outputs": [], "source": [ "context_p = \"\"\" On August 10 said that its arm JSW Neo Energy has agreed to buy a portfolio of 1753 mega watt renewable energy generation capacity from Mytrah Energy India Pvt Ltd for Rs 10,530 crore.\"\"\"\n" ] }, { "cell_type": "code", "execution_count": null, "id": "83udgnzuCoIQ", "metadata": { "id": "83udgnzuCoIQ" }, "outputs": [], "source": [ "question_p = \"\"\"What is the date for announcement\"\"\"\n", "response = llm_chain.run({\"question\":question_p,\"context\":context_p})\n", "\n", "response" ] }, { "cell_type": "code", "execution_count": 5, "id": "w6Y9ZHVp89wa", "metadata": { "id": "w6Y9ZHVp89wa" }, "outputs": [], "source": [ "question_p = \"\"\"What company is buyer and seller here\"\"\"\n", "response = llm_chain.run({\"question\":question_p,\"context\":context_p})" ] }, { "cell_type": "code", "execution_count": 6, "id": "s0PHieG69YhZ", "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 35 }, "id": "s0PHieG69YhZ", "outputId": "45a8543d-4eed-430e-c50d-f0015b8ba50a" }, "outputs": [ { "data": { "application/vnd.google.colaboratory.intrinsic+json": { "type": "string" }, "text/plain": [ "'The buyer is JSW Neo Energy and the seller is Mytrah Energy India Pvt Ltd.'" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "response" ] }, { "cell_type": "markdown", "id": "ibzXKDR--BR1", "metadata": { "id": "ibzXKDR--BR1" }, "source": [ "## Gradio" ] }, { "cell_type": "code", "execution_count": null, "id": "NFnnoSyr97s-", "metadata": { "id": "NFnnoSyr97s-" }, "outputs": [], "source": [ "!pip -q install gradio" ] }, { "cell_type": "code", "execution_count": 4, "id": "8JuL87Cj-Mkc", "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 715 }, "id": "8JuL87Cj-Mkc", "outputId": "1e6a264b-c783-4bf5-be8f-98a36ef1dd90" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Setting queue=True in a Colab notebook requires sharing enabled. 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://92baaf0e9ff8456b6a.gradio.live\n", "\n", "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n" ] }, { "data": { "text/html": [ "
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "James Webb Space Telescope detects quartz crystals in the atmosphere of exoplanet WASP-17b. What are found on the WASP-17b?\n", "Quartz crystals in the atmosphere of WASP-17b.\n", "Keyboard interruption in main thread... closing server.\n", "Killing tunnel 127.0.0.1:7860 <> https://92baaf0e9ff8456b6a.gradio.live\n" ] }, { "data": { "text/plain": [] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import gradio as gr\n", "\n", "def question_answer(context: str, question: str):\n", " print(context, question)\n", " response = llm_chain.run({\"question\":question, \"context\":context})\n", " print(response)\n", " return response\n", "\n", "theme = gr.themes.Default(\n", " primary_hue=\"indigo\",\n", " secondary_hue=\"pink\",\n", " neutral_hue=\"slate\",\n", ")\n", "\n", "with gr.Blocks(theme=theme) as interface:\n", " context = gr.Textbox(lines=5, placeholder=\"On August 10 said that its arm JSW Neo Energy has agreed to buy a portfolio of 1753 mega watt renewable energy generation capacity from Mytrah Energy India Pvt Ltd for Rs 10,530 crore.\", label=\"Context\")\n", " question = gr.Textbox(placeholder=\"What company is buyer and seller here\", label=\"Question\")\n", " answer = gr.Textbox(placeholder=\"Answer will be here\", label=\"Answer\")\n", " ask_button = gr.Button(\"Ask (this might take a minute since it's using CPU)\")\n", " ask_button.click(fn=question_answer, inputs=[context, question], outputs=answer)\n", "\n", "interface.launch(debug=True)" ] }, { "cell_type": "markdown", "id": "1kOOTJkRGyxX", "metadata": { "id": "1kOOTJkRGyxX" }, "source": [ "![pin](https://media.discordapp.net/attachments/201349824300318721/1163850900838813746/image.png?ex=6541139e&is=652e9e9e&hm=a2213e8ae5b94786bb0661c94435a46885812c9eb532f56fc0270e789787b333&=&width=903&height=486)" ] }, { "cell_type": "markdown", "id": "xMHp65tnEcm7", "metadata": { "id": "xMHp65tnEcm7" }, "source": [ "## To deploy on spaces" ] }, { "cell_type": "code", "execution_count": null, "id": "DGWZwlgVEegn", "metadata": { "id": "DGWZwlgVEegn" }, "outputs": [], "source": [ "import gradio as gr\n", "from langchain.llms import CTransformers\n", "from langchain import PromptTemplate, LLMChain\n", "\n", "config = {'max_new_tokens': 100, 'temperature': 0}\n", "llm = CTransformers(model='TheBloke/Mistral-7B-Instruct-v0.1-GGUF', model_file=\"mistral-7b-instruct-v0.1.Q4_K_M.gguf\", config=config)\n", "\n", "template = \"\"\"[INST] You are a helpful, respectful and honest assistant. Answer exactly in few words from the context\n", "Answer the question below from context below :\n", "{context}\n", "{question} [/INST] \n", "\"\"\"\n", "prompt = PromptTemplate(template=template, input_variables=[\"question\",\"context\"])\n", "llm_chain = LLMChain(prompt=prompt, llm=llm)\n", "\n", "def question_answer(context: str, question: str):\n", " print(context, question)\n", " response = llm_chain.run({\"question\":question, \"context\":context})\n", " print(response)\n", " return response\n", "\n", "theme = gr.themes.Default(\n", " primary_hue=\"indigo\",\n", " secondary_hue=\"pink\",\n", " neutral_hue=\"slate\",\n", ")\n", "\n", "with gr.Blocks(theme=theme) as interface:\n", " context = gr.Textbox(lines=5, placeholder=\"On August 10 said that its arm JSW Neo Energy has agreed to buy a portfolio of 1753 mega watt renewable energy generation capacity from Mytrah Energy India Pvt Ltd for Rs 10,530 crore.\", label=\"Context\")\n", " question = gr.Textbox(placeholder=\"What company is buyer and seller here\", label=\"Question\")\n", " answer = gr.Textbox(placeholder=\"Answer will be here\", label=\"Answer\")\n", " ask_button = gr.Button(\"Ask (this might take a minute since it's using CPU)\")\n", " ask_button.click(fn=question_answer, inputs=[context, question], outputs=answer)\n", "\n", "interface.launch(debug=True)" ] }, { "cell_type": "markdown", "id": "2b151c52-20a3-432f-ab16-4721c16581c4", "metadata": { "id": "2b151c52-20a3-432f-ab16-4721c16581c4" }, "source": [ "## Submit Notebook" ] }, { "cell_type": "code", "execution_count": 7, "id": "ced6b581-708f-4758-86ff-3cd51bf14f99", "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 35 }, "id": "ced6b581-708f-4758-86ff-3cd51bf14f99", "outputId": "72d04fb3-cffc-4647-d045-ee3d24e117cc" }, "outputs": [ { "data": { "application/vnd.google.colaboratory.intrinsic+json": { "type": "string" }, "text/plain": [ "'Assignment successfully submitted'" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "portfolio_link = \"https://huggingface.co/spaces/faldeus0092/mistral7b-simple-qa\"\n", "question_id = \"01_text_portfolio_link\"\n", "submit(student_id, name, assignment_id, str(portfolio_link), question_id, drive_link)" ] }, { "cell_type": "markdown", "id": "792aa177-c74e-42e5-9881-40376cd746a8", "metadata": { "id": "792aa177-c74e-42e5-9881-40376cd746a8" }, "source": [ "# FIN" ] } ], "metadata": { "colab": { "provenance": [], "toc_visible": true }, "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.3" }, "widgets": { "application/vnd.jupyter.widget-state+json": { "095fd8b26865435589b2e79e12ecef24": { "model_module": "@jupyter-widgets/base", "model_module_version": 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