| ---
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| sdk: docker
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| app_port: 7860
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| title: ISA 401 Job Scout Chat
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| emoji: 🔎
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| colorFrom: red
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| colorTo: gray
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| pinned: false
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| license: mit
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| short_description: Ask questions about ChatISA Job Scout postings
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| ---
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|
|
| # ISA 401 Job Scout Chat
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|
|
| **Ask a question in plain English, get the SQL and a table back**
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|
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| A twelve-line [querychat](https://github.com/posit-dev/querychat) app built in ISA 401 (Miami University) on the job postings that [ChatISA](https://chatisa.fsb.miamioh.edu) Job Scout collected. It is the starting point for Assignment 05, where you deploy this app to Hugging Face Spaces and then improve it.
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|
|
| ---
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|
|
| ## What is this app?
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|
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| The app connects to a SQLite database (`data/scout.db`), hands the `scout_postings` table to querychat, and lets an LLM translate your question into SQL. Every answer shows the query it ran, so you can check the logic and reuse the SQL yourself.
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|
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| **Example queries:**
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| - "How many of the postings are remote?"
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| - "Which ten companies have the most postings?"
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| - "Show the internship postings in Ohio."
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|
|
| ---
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|
|
| ## Dataset Information
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|
|
| **Dataset:** `scout_postings` table in `data/scout.db` (1,891 rows, 19 columns)
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| **Source:** ChatISA Job Scout, which harvested the postings from public job boards between July 29 and August 23, 2026 (the `source` column records the board: `activejobs` or `usajobs`)
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| **Data dictionary:** `data/data_desc.md` (started in class; you complete it in Assignment 05)
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| **Query rules for the LLM:** `data/extra_instructions.md` (one starter rule; you add more)
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|
|
| ### Key Fields
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|
| | Field | Description |
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| |-------|-------------|
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| | `title` | Job title as it appeared on the board |
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| | `company` | Employer name |
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| | `location_city` | City of the posting (blank for 61 rows) |
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| | `location_state` | Two-letter state code (blank for 30 rows) |
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| | `remote` | `1` if the posting is remote, `0` otherwise |
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| | `category` | `fulltime`, `federal`, or `internship` |
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|
|
| ---
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|
|
| ## Required Secret
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|
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| The app calls OpenAI (`gpt-5.6-luna (reasoning off)`) through [ellmer](https://ellmer.tidyverse.org/), so it needs one environment variable:
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|
|
| ```bash
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| export OPENAI_API_KEY="your-api-key-here"
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| ```
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| On Hugging Face Spaces, add it under **Settings > Variables and secrets** as a secret named `OPENAI_API_KEY`. Never commit the key; `.Renviron` is listed in `.gitignore` for that reason.
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|
|
| ---
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|
|
| ## Running Locally
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|
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| **With R (4.6.0, querychat 0.3.0):**
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| ```r
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| # from inside apps/job_scout_chat/
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| shiny::runApp(".", port = 7860)
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| ```
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|
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| **With Docker:**
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| ```bash
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| docker build -t job_scout_chat .
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| docker run --rm -p 7860:7860 -e OPENAI_API_KEY=$OPENAI_API_KEY job_scout_chat
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| ```
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|
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| Then open http://localhost:7860.
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|
|
| ---
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|
|
| ## Technology Stack
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|
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| - **[Shiny](https://shiny.posit.co/)** - Web application framework for R
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| - **[querychat](https://github.com/posit-dev/querychat)** - Natural language data querying
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| - **[ellmer](https://ellmer.tidyverse.org/)** - LLM client for R
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| - **[RSQLite](https://rsqlite.r-dbi.org/)** - SQLite driver for R
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|
|
| ---
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|
|
| ## Course Information
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|
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| This application was developed for **ISA 401** at **Miami University**. The polished version of the same idea, built on BLS wage data, is the [OEWS Jobs Explorer](https://huggingface.co/spaces/fmegahed/querychat_demo).
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|
