new blog posts
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<head>
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<title>Nicholas Orlowsky</title>
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<link rel="stylesheet" href="/style.css">
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<link rel="icon" type="image/x-icon" href="/favicon.ico">
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</head>
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<body>
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<nav>
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<a href="/">[ Home ]</a>
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<a href="/blog.html">[ Blog ]</a>
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<a href="/projects.html">[ Projects ]</a>
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<a href="/extra.html">[ Extra ]</a>
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<hr/>
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</nav>
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<h1>Side Project Log 8/15/2023</h1>
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<p>This side project log covers work done from 8/8/2023 - 8/15/2023</p>
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<h2 id="olney">Olney</h2>
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<p>
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I added a frontend to Olney and added a feature where it can automatically keep track of your job applications
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by monitoring your email.
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</p>
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<h3>Frontend</h3>
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<p>
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The frontend was made with Svelte. I chose not to use any UI/CSS libraries as I wanted to keep the number of
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dependencies low. This was another good opportunity to learn about Svelte.
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</p>
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<h3>Automatic Tracking via E-Mail</h3>
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<p>
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This is the killer feature that I initially set out to build Olney for. This works by having the user forward their
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E-Mail to an instance of Olney. To receive E-Mail, Olney uses <a href="https://inbucket.org">Inbucket</a>, a mailserver
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easily hostable within Docker. It listens on a websocket for incoming mail. Whenever a new mail message is received,
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Olney uses the OpenAI API to get a summary of the email in the following format:
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</p>
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<pre><code class="language-json">
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{
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isRecruiting: bool, // is the message about recruiting?
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recruitingInfo: null | {
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location: string, // Location in City, Providence/State, Country format
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company: string, // Casual name of company e.g: Google, Cisco, Apple
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position: string, // Name of job position
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type: "assessment" | "interview" | "offer" | "rejection" | "applied" // What the message is discussing
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dateTime: string, // DateTime communication rec'd OR DateTime that is being discussed (i.e. interview date confirmation)
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name: string // Name of event, giving more detail to type
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} // null if message is not about recruiting, fill with values if it is
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}
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</code></pre>
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<p>
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Olney then takes some details from this data, namely: company, position, and location and then uses the OpenAI API to generate
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an <a href="https://www.pinecone.io/learn/vector-embeddings/">embedding</a>. We then query the closest match out of the job applications
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in the database (with <a href="https://github.com/pgvector/pgvector">pgvector</a>). Once we have the job application, we add
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the event to the database, using the job application's id as a fkey.
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</p>
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<p>
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Embeddings was chosen as the lookup method that way we don't have to worry about data being parsed out of the email being an exact
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match for what the user inputted. This also allows the lookup to work even when certain things such as location are missing from the
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email.
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</p>
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<p>
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Olney should be open-sourced/released within the next week or two.
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</p>
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<hr>
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<p><strong>These projects had minimal/no work done on them:</strong> NWS, RingGold, SQUIRREL</p>
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<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.8.0/styles/dark.min.css">
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<script src="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.8.0/highlight.min.js"></script>
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<script>hljs.highlightAll();</script>
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<footer>
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<hr />
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<p style="margin-bottom: 0px;">Copyright © Nicholas Orlowsky 2023</p>
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<p style="margin-top: 0px;">Hosting provided by <a href="https://nws.nickorlow.com">NWS</a></p>
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</footer>
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</body>
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<head>
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<title>Nicholas Orlowsky</title>
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<link rel="stylesheet" href="/style.css">
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<link rel="icon" type="image/x-icon" href="/favicon.ico">
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</head>
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<body>
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<nav>
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<a href="/">[ Home ]</a>
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<a href="/blog.html">[ Blog ]</a>
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<a href="/projects.html">[ Projects ]</a>
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<a href="/extra.html">[ Extra ]</a>
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<hr/>
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</nav>
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<h1>Side Project Log 8/8/2023</h1>
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<p>This side project log covers work done from 7/12/2023 - 8/8/2023</p>
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<h2 id="squirrel">SQUIRREL</h2>
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<p>
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SQUIRREL has been updated to work with INSERT INTO and SELECT queries. I also refactored much of the codebase to do error handling more elegantly and to make the parser
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more extensible. Here's a screenshot of table creation, data insertion, and data selection:
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</p>
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<p>
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The biggest challenge of this part was working on the parser which has now been written three times. The approaches to the parsing were:
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</p>
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<ol>
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<li>
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<b>Stepping through whitespace:</b> <p>This was my initial and naive approach to the problem. I split the input string by its whitespace
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and then queried values by referencing their indexes in the split string. </p>
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</li>
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<li>
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<b>Regex:</b> <p>This approach was cleaner than the first and led to a small parser, however it required an external dependency (which I'm
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trying to minimize), and would make it hard to add additional features to commands later down the line.</p>
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</li>
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<li>
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<b>Finite state machine:</b> <p>This solution was more verbose than the others, however it allows for easier development. This method works
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by splitting the query string into tokens. Tokens are the smallest piece of data that a parser recognizes. SQUIRREL gets them by splitting
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the input by delimiters and using the split list as tokens (excluding whitespace) SQUIRREL recognizes the following characters as delimiters:
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</p>
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<code>
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' ', ',', ';', '(', ')'
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</code>
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<p>
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This means that the string "INSERT INTO test (id) VALUES (12);" would be parsed into the list: "INSERT", "INTO", "test", "(", "id", etc..
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</p>
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<p>
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Once we have our list of tokens, we iterate through them starting at a default state and perform a certain task for the given state, which
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usually includes switching to another state. We do this until we reach the end state.
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</p>
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<p>
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For example, with the above insert statement, we would start in the IntoKeyword state which would ensure that "INTO" is the current token.
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We would then transition to the TableName state which would read the table name and store it in the ParsedCommand struct we're returning. We
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would then move to the ColumnListBegin state which would look for an opening parenthesis, and switch the state to ColumnName. This process
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continues with the other parts of the query until the Semicolon state is reached which checks that the statement ends with a semicolon, then
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returns the ParsedCommand struct.
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</p>
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</li>
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</ol>
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<p>
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Next steps for this are to add column selection to SELECT statements and add WHERE clauses to SELECT statements.
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</p>
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<h2 id="olney">Olney</h2>
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<p>
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I added a feature to the Olney API which scans the <a href="https://github.com/SimplifyJobs/Summer2024-Internships">pittcsc (now Simplify) summer internships Github repo</a>
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and parses the data into JSON format. I parsed the markdown file they have uisng regex which was relatively simple. There were some issues during development due to the
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changing structure of the markdown file. These issues are being fixed on a rolling basis. I expect the changes to slowdown now that the transition from pittcsc to Simplify
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is complete. You can access the JSON at <a href="https://olney.nickorlow.com/jobs">olney.nickorlow.com/jobs</a>.
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</p>
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<hr>
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<p><strong>These projects had minimal/no work done on them:</strong> NWS, RingGold</p>
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<footer>
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<hr />
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<p style="margin-bottom: 0px;">Copyright © Nicholas Orlowsky 2023</p>
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<p style="margin-top: 0px;">Hosting provided by <a href="https://nws.nickorlow.com">NWS</a></p>
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</footer>
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</body>
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