Update in Search Feature (It can now search based on Title && Content) (arm-education#96)

* search with description

Author: jc2409

docs/_includes/search-providers/default/search-data.js

@@ -5,6 +5,7 @@ window.TEXT_SEARCH_DATA={
       {%- for _article in _collection.docs -%}
       {%- unless forloop.first -%},{%- endunless -%}
       {'title':{{ _article.title | jsonify }},
+      'full_description':{{ _article.full_description | jsonify }},
       {%- include snippets/prepend-baseurl.html path=_article.url -%}
       {%- assign _url = __return -%}
       'url':{{ _url | jsonify }}}

docs/_includes/search-providers/default/search.js

@@ -20,9 +20,10 @@ window.Lazyload.js([SOURCES.jquery, PAHTS.search_js], function() {
     for (i = 0; i < keys.length; i++) {
       key = keys[i];
       for (j = 0; j < searchData[key].length; j++) {
-        cur = searchData[key][j], _title = cur.title;
+        cur = searchData[key][j];
+        var haystack = (cur.title || '').toLowerCase() + ' ' + (cur.full_description || '').toLowerCase();
         if ((result[key] === undefined || result[key] && result[key].length < 4 )
-          && _title.toLowerCase().indexOf(query.toLowerCase()) >= 0) {
+          && haystack.indexOf(query.toLowerCase()) >= 0) {
           if (result[key] === undefined) {
             result[key] = [];
           }

docs/_posts/2025-05-30-AI-Agents.md

@@ -4,6 +4,47 @@ description: This self-service project builds a sandboxed AI agent on Arm hardwa
   DevOps pipelines to e-commerce tasks—demonstrating secure, efficient automation
   on accessible Arm platforms.
 donation: null
+full_description: "### Description\n\n**Why this is important?** \n\nAI Agents enhance
+  large language models (LLMs) by performing user-driven actions, enabling various
+  commercial applications. This is a nascent domain will emerging frameworks such
+  as the model context protocol (MCP) leading to commercial products and services.
+  The Arm architecture, from microcontrollers to servers, will be used to carry out
+  agentic functions and Arm has many initatives to support the AI future. See [our
+  website for more details](https://www.arm.com/markets/artificial-intelligence).
+  \n\n**Project Summary**\n\nParticipants must develop an AI-powered agent that automates
+  repetitive and complex workflow tasks in a specific domain, such as software development,
+  e-commerice, or DevOps. The foundational model can be a suitable model of your choice
+  (e.g., [OpenAI API](https://openai.com/api/)) but you must consider the appropriate
+  model for cost, reliability and accessibility. Additionally, you are free to choose
+  the tools for agent functionality, such as [LLama-cpp-agent](https://github.com/Maximilian-Winter/llama-cpp-agent).
+  One stipulatation, is that the LLM and/or agent must run on an Arm-based system,
+  such as a Google Pixel phone or Arm-based server. \n\nThe AI agent will be deployed
+  in a sandboxed environment to ensure safety and prevent unintended consequences,
+  including prompt guardrails \n\n## Prerequisites\n\n- Intermediate understanding
+  in an OOP language such as Python  (for front-end, if needed). \n- Familiarity using
+  Databases such as PostgreSQL, MongoDB, VectorDB. \n- Access to a LLM (e.g., through
+  an API or on-device LLM)\n- Optional API access to target workflow tools such as
+  Jira, Jenkins etc.\n\n\n## Resources from Arm and our partners\n\n- Learning path:
+  [Deploy and MCP Server on a Raspberry Pi5 for AI Agent Interaction](https://learn.arm.com/learning-paths/cross-platform/mcp-ai-agent/)\n\n-
+  Learning path: [Deploy an AI Agent on Arm with llama.cpp and llama-cpp-agent](https://learn.arm.com/learning-paths/servers-and-cloud-computing/ai-agent-on-cpu/)\n\n##
+  Support Level\n\nThis project is designed to be self-serve but comes with opportunity
+  of some community support from Arm Ambassadors, who are part of the Arm Developer
+  program. If you are not already part of our program, [click here to join](https://www.arm.com/resources/developer-program?#register).\n\n##
+  Benefits \n\nStandout project contributions will result in preferential internal
+  referrals to Arm Talent Acquisition (with digital badges for CV building).  And
+  we are currently discussing with national agencies the potential for funding streams
+  for Arm Developer Labs projects, which would flow to you, not us.\n\nTo receive
+  the benefits, you must show us your project through our [online form](https://forms.office.com/e/VZnJQLeRhD).
+  Please do not include any confidential information in your contribution. Additionally
+  if you are affiliated with an academic institution, please ensure you have the right
+  to share your material.\n\n### Previous Submissions\n1. [AI to Solve Maths Example
+  Sheets at University of Cambridge. (Finley Stirk, Eliyahu Gluschove-Koppel and Ronak
+  De)](https://github.com/egkoppel/example-papers)\n\n2. [AI that interprets user
+  requests, generates circuit descriptions, creates LTSpice ASC code, and iteratively
+  refines circuit designs using a combination of GPT-based language models, a vision
+  analysis module, and LTSpice simulation. (Gijeong Lee, Bill Leoutsakos)](https://github.com/BillLeoutsakosvl346/ElectroNinjaRefined)\n\n3.
+  [AI agent to track real-time student engagement and exam performance (Jasper Wang,
+  Sritej Tummuru, Talha Javed)](https://github.com/JasperWANG-911/AI_Agent)"
 layout: article
 license: null
 platform:

docs/_posts/2025-05-30-AI-Powered-Porting-Tool.md

@@ -4,6 +4,58 @@ description: This self-service project creates an AI-driven porting engine that
   native macOS and Windows-on-Arm support for bioinformatics and R software so researchers
   can run demanding workflows directly on modern Arm devices.
 donation: null
+full_description: "## Description\n\n**Why this is important?** \n\nBioconda is a
+  specialized package repository for bioinformatics and genomics. Since 2020, there
+  has been notable growth in multi-core Arm-based laptops and desktops, including
+  the recent launch of Windows on Arm. In the coming years, Arm anticipates an increase
+  in available OEM (original equipment manufacturer) devices. These machines facilitate
+  the execution of computationally intensive bioinformatics and statistics tasks locally.
+  Potential downstream applications include faster, more affordable diagnoses that
+  can be conducted closer to hospital patients, exemplified by the pilot [ROBIN software](https://www.nottingham.ac.uk/news/genetic-brain-tumour-diagnosis).
+  While many leading Bioconda packages now support Linux/Arm, there remains a gap
+  in native macOS and Windows on Arm support, as numerous packages default to emulated
+  x86 environments. Additionally, the R community faces challenges with Windows-on-Arm
+  support for community-created packages, with many unable to build due to x86-specific
+  code issues.\n\n**Project Summary**\n\nThis project challenges you to build an intelligent
+  automation tool for porting software packages — for use in domains such as [bioinformatic
+  pipelines with Nextflow](https://github.com/arm-university/Arm-Developer-Labs/blob/main/Projects/Projects/Bioinformatic-Pipeline-Analysis.md)
+  or [statistics with R](https://github.com/arm-university/Arm-Developer-Labs/blob/main/Projects/Projects/R-Arm-Community-Support.md).\n\nGiven
+  the large number of community packages, applying manual patches is not only time-consuming
+  but also inefficient, as many involve similar, repetitive adjustments—highlighting
+  the need for a scalable, automated solution.\nThe goal is to build a sophisticated
+  system (beyond simple shell scripts) that uses dependency graph analysis, machine
+  learning, to:\n\n- Identify unported packages\n- Trace recursive dependency issues\n-
+  Recommend or auto-generate build recipes and steps\n- Evaluate build success and
+  reattempt intelligently\n- Generate pull requests when confident of a fix. \n- For
+  complex packages, offer guidance to developers on how to port them—for example,
+  by suggesting tools like SSE2NEON for translating x86 SSE intrinsics.\n- Be extensible
+  to work with various  packaging systems and languages\n\nThis project is a blend
+  of automation, machine learning, and systems programming. The outcome could directly
+  contribute to open source ecosystems and help bring cutting-edge bioinformatics
+  tools to wider hardware audiences.\n\n## Prerequisites\n\n- Access to Apple Silicon
+  or Windows on Arm machine. \n- Familiarity with Python, Bash and Nextflow\n- Familiar
+  with genomics/bioinformatics or statistics with the R language. \n- Experience or
+  willing to learn nf-core pipelines, Conda, BioConda and Docker/Singularity.\n\n\n##
+  Resources from Arm and our partners\n\n- External Resource: [Example Porting Script
+  for Bioconda](https://github.com/dslarm/bioconda-contrib-notes/tree/main), [Arm64
+  nf-core pipelines](https://github.com/ewels/nf-core-arm-discovery/tree/main) and
+  [Bioconda package repository](https://bioconda.github.io/)\n- Documentation: [nf-core
+  documentation](https://nf-co.re/docs/)\n- External Documentation: [Bioconductor
+  Build Reports](https://bioconductor.org/checkResults/), Package installation results
+  for [CRAN](https://www.r-project.org/nosvn/winutf8/ucrt3/CRAN_aarch64/install_out/)
+  and [Bioconductor](https://www.r-project.org/nosvn/winutf8/ucrt3/BIOC_aarch64/install_out/)
+  packages\n- Dataset: Example [NCBI Datasets](https://www.ncbi.nlm.nih.gov/datasets/)\n\n##
+  Support Level\n\nThis project is designed to be self-serve but comes with opportunity
+  of some community support from Arm Ambassadors, who are part of the Arm Developer
+  program. If you are not already part of our program, [click here to join](https://www.arm.com/resources/developer-program?#register).\n\n##
+  Benefits \n\nStandout project contributions will result in preferential internal
+  referrals to Arm Talent Acquisition (with digital badges for CV building).  And
+  we are currently discussing with national agencies the potential for funding streams
+  for Arm Developer Labs projects, which would flow to you, not us.\n\nTo receive
+  the benefits, you must show us your project through our [online form](https://forms.office.com/e/VZnJQLeRhD).
+  Please do not include any confidential information in your contribution. Additionally
+  if you are affiliated with an academic institution, please ensure you have the right
+  to share your material."
 layout: article
 license: null
 platform:

docs/_posts/2025-05-30-AMBA-Simulator-Framework.md

@@ -4,6 +4,35 @@ description: This self-guided hardware project has you implement, simulate, and
   with Arm’s interconnect backbone and yielding a reusable reference design for future
   embedded systems.
 donation: null
+full_description: "<img class="image image--xl" src="/Arm-Developer-Labs/images/AMBA.avif"/>\n\n## Audience\nElectronic Engineering\n\n##
+  Description\nThis project aims to develop a reference design of AMBA (Advanced Microcontroller
+  Bus Architecture) infrastructure. You are free to choose which AMBA protocol and
+  version of the interconnect standard to implement with more simple specifications
+  e.g., APB, being easier to create than coherent protocols such as AMBA CHI. \n\nThe
+  main deliverables include the Verilog design of the AMBA infrastructure, a Verilog
+  test bench for testing the design, an RTL (Register Transfer Level) simulation flow
+  to verify the functionality, and an FPGA prototyping platform to demonstrate the
+  design in a real-world environment. The project will provide a comprehensive understanding
+  of AMBA protocols and their implementation, making it an excellent learning opportunity
+  for students interested in digital design and hardware description languages.\n\n##
+  Prequisites\n\n- Intermediate understanding of Verilog, SystemVerilog or other hardware
+  description languages (HDL).\n- Access and basic understanding of ModelSim, Quartus
+  and Vivado\n- Access to a suitable FPGA development board (e.g., Xilinx or Altera),
+  simulation tools\n\n## Resources from Arm and our partners\n\n\n- Video: [Introductory
+  Video to AMBA](https://www.youtube.com/watch?v=zayyWwSxyW4)\n- Documentation: [AMBA
+  Interconnect Specifications](https://www.arm.com/architecture/system-architectures/amba/amba-specifications)\n\n##
+  Support Level\n\nThis project is designed to be self-serve but comes with opportunity
+  of some community support from Arm Ambassadors, who are part of the Arm Developer
+  program. If you are not already part of our program, [click here to join](https://www.arm.com/resources/developer-program?#register).\n\n##
+  Previous Submissions\n\nSimilar projects:\n    - https://github.com/kumarraj5364/AMBA-APB-PROTOCOL
+  \n\n## Benefits \n\nStandout project contributions will result in preferential internal
+  referrals to Arm Talent Acquisition (with digital badges for CV building).  And
+  we are currently discussing with national agencies the potential for funding streams
+  for Arm Developer Labs projects, which would flow to you, not us.\n\nTo receive
+  the benefits, you must show us your project through our [online form](https://forms.office.com/e/VZnJQLeRhD).
+  Please do not include any confidential information in your contribution. Additionally
+  if you are affiliated with an academic institution, please ensure you have the right
+  to share your material."
 layout: article
 license: null
 platform:

docs/_posts/2025-05-30-Academic-Trends-Dashboard.md

@@ -4,6 +4,39 @@ description: This self-service project creates a web-scraping, database-driven d
   partners and chip architects align future hardware designs with emerging algorithmic
   trends.
 donation: null
+full_description: "<img class="image image--xl" src="/Arm-Developer-Labs/images/dashboard.png"/>\n\n## Description\n\n**Why
+  this is important?** \n\nThe field of computer science research is continually evolving,
+  with new algorithms shaping the design of future hardware. This project aims to
+  guide computer architecture decisions, ensuring that upcoming hardware aligns with
+  the needs of software algorithms and applications. The dashboard you create can
+  be of use to Arm partners manufacturing physical chips and used to guide architecture
+  decisions.  \n\n**Project Summary**\n\nThe main deliverable is a web scraping tool
+  that pulls keywords from academic papers, considering the popularity of the paper
+  and its publication. The data will be stored in an appropriate database and displayed
+  in a web browser format, allowing users to visualize trends and changes in research
+  focus over time. This project will provide practical experience in using APIs, web
+  scraping, and data analysis. Some academic search engines to consider are Google
+  Scholar, [BASE](https://www.base-search.net/), [Core](https://core.ac.uk/) and [Science.gov](https://science.gov/).
+  \n\n\n## Prequisites\n\n- Software: Intermediate understand of a scripting programming
+  language (e.g., Python, JavaScript), web development and statistics.\n- Hardware:
+  Access to a computer with internet connectivity\n- API access to scrape specific
+  journal websites, you may need to obtain explicit permission from the website administrators
+  or owners.\n\n## Resources from Arm and our partners\n\n- Learning path: [Deploy
+  MariaDB on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/mariadb/))\n-
+  Learning path: [Learn how to deploy PostgresSQL](https://learn.arm.com/learning-paths/servers-and-cloud-computing/postgresql/)\n-
+  Software Libraries: Example libraries for web scraping are [BeautifulSoup](https://pypi.org/project/beautifulsoup4/),
+  Selenium.\n\n\n## Support Level\n\nThis project is designed to be self-serve but
+  comes with opportunity of some community support from Arm Ambassadors, who are part
+  of the Arm Developer program. If you are not already part of our program, [click
+  here to join](https://www.arm.com/resources/developer-program?#register).\n\n##
+  Benefits \n\nStandout project contributions will result in preferential internal
+  referrals to Arm Talent Acquisition (with digital badges for CV building).  And
+  we are currently discussing with national agencies the potential for funding streams
+  for Arm Developer Labs projects, which would flow to you, not us.\n\nTo receive
+  the benefits, you must show us your project through our [online form](https://forms.office.com/e/VZnJQLeRhD).
+  Please do not include any confidential information in your contribution. Additionally
+  if you are affiliated with an academic institution, please ensure you have the right
+  to share your material."
 layout: article
 license: null
 platform:

docs/_posts/2025-05-30-Architecture-Insight-Dashboard.md

@@ -4,6 +4,39 @@ description: This self-service project develops a data-rich dashboard that visua
   specific extensions—giving developers an instant, validated view of where their
   workloads will run best.
 donation: null
+full_description: "<img class="image image--xl" src="/Arm-Developer-Labs/images/can-i-use.jpg"/>\n\n\n### Description\n\n**Why
+  this is important?** \n\nDevelopers often face challenges in selecting the appropriate
+  platform for their software. With numerous smartphones and cloud instances available,
+  gauging consumer popularity and availability can be difficult, and identifying software
+  stack dependencies can be time-consuming. As Arm anticipates an increase in Arm-based
+  products in the coming years, this situation is likely to become even more complex,
+  requiring the need for a single, validated solution. \n\n**Project Summary**\n\nThis
+  project aims to develop a comprehensive dashboard that lets a developer know what
+  proportion of devices support a specific Arm CPU extension, similar to [“Can I use”](https://caniuse.com/)
+  for web development and any software compatibility issues. The functional requirements
+  for the Architecture Insights dashboard:\n\n- Popularity of Arm architectures and
+  Operating System combinations over time\n- Searchable index of software, libraries
+  and tools that have been optimised for a specific architecture. For example, \"Does
+  the video processing software, FFMPEG, support acceleration for SVE2 with Windows
+  11?\"\n\n \nStudents will gain hands-on experience with data visualization, statistical
+  analysis, web development, and market analysis, providing valuable insights into
+  the Arm ecosystem. \n\n## Prequisites\n\nYou are free to explore your own implementation.
+  The skills below are examples.\n\n- Intemediate understanding of an OOP language
+  such as Python or JavaScript\n- Access to a computer with internet connectivity\n\n\n##
+  Resources from Arm and our partners\n\n- Website: [Arm Software Ecosystem Dashboard](https://www.arm.com/developer-hub/ecosystem-dashboard)\n-
+  Website: [Windows on Arm Support Wiki page](https://linaro.atlassian.net/wiki/spaces/WOAR/overview)\n-
+  Website: [\"Can I Use?\" dashboard](https://caniuse.com/) \n\n## Support Level\n\nThis
+  project is designed to be self-serve but comes with opportunity of some community
+  support from Arm Ambassadors, who are part of the Arm Developer program. If you
+  are not already part of our program, [click here to join](https://www.arm.com/resources/developer-program?#register).\n\n\n##
+  Benefits \n\nStandout project contributions will result in preferential internal
+  referrals to Arm Talent Acquisition (with digital badges for CV building).  And
+  we are currently discussing with national agencies the potential for funding streams
+  for Arm Developer Labs projects, which would flow to you, not us.\n\nTo receive
+  the benefits, you must show us your project through our [online form](https://forms.office.com/e/VZnJQLeRhD).
+  Please do not include any confidential information in your contribution. Additionally
+  if you are affiliated with an academic institution, please ensure you have the right
+  to share your material."
 layout: article
 license: null
 platform: