README and License

LICENSE

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+The MIT License
+
+Copyright (c) Laurie Voss
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in
+all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+THE SOFTWARE.

README.md

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+# LlamaIndex Invoice Reconciler
+
+This is a full-stack web app showing how to use LlamaCloud with the LlamaIndex.TS framework to produce a real-world application, in this case matching the terms of contracts against incoming invoices from the contracted companies, aka "invoice reconciliation".
+
+## User flow
+
+1. The user uploads one or more contracts to the app
+2. These are indexed and made searchable by the app
+3. The user uploads one or more invoices to the app
+4. The app determines which contract each invoice applies to
+5. It examines the terms of the contract and the invoice details and flags any discrepancies
+6. It shows the user the results
+
+## Under the hood
+
+1. The user "logs in" by providing a LlamaCloud API key. This is used to create a LlamaCloud index. (The API key is stored in localStorage, as are other settings. This is not a good practice, but it kept the code simple for a demonstration)
+
+2. Uploaded invoices are uploaded to the LlamaCloud index, which parses them and then stores the parsed chunks in a vector database. The LlamaCloud index also stores the parsed documents and original file names in the metadata, which we use to display them on the frontend.
+
+3. When a user uploads an invoice, we parse it with LlamaParse. Then an LLM call extracts the name of the company that issued the invoice, and runs a retrieval query again the LlamaCloud index with that name.
+
+4. The chunk with the highest match to the name is taken as the contract that the invoice applies to. We retrieve the entire parsed contract from the index.
+
+5. A further LLM call compares the entire parsed contract against the full parsed invoice, and asks it to flag discrepancies. Because this is a complex task, we use OpenAI's o3-mini model for this.
+
+6. The parsed invoices and any discrepancies are returned to the frontend.
+
+## Running the app
+
+The frontend is a vanilla Next.js application. It requires a `.env.local` file with a single variable, your `OPENAI_API_KEY`. Everything else is handled by LlamaCloud and credentials are stored on the client (insecurely!). You can run the app as normal:
+
+```bash
+npm install
+npm run dev
+```