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new glimpse approach

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This commit is contained in:
Bryce
2026-05-27 10:12:45 -07:00
parent 6e65df2591
commit 2b9648dd1a
9 changed files with 768 additions and 23 deletions
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1
.terraform.tfstate.lock.info Normal file
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@@ -0,0 +1 @@
{"ID":"842a4264-8857-6f39-d95a-cbc58d58337d","Operation":"OperationTypePlan","Info":"","Who":"noti@pop-os","Version":"1.15.1","Created":"2026-05-27T17:06:58.450709065Z","Path":"terraform.tfstate"}

94
code/main.py
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@@ -2,7 +2,6 @@
import base64
import json
import os
import re
import urllib.request
from dotenv import load_dotenv
@@ -24,29 +23,81 @@ def slurp_file(filename):
return file.read()
BASE_PROMPT="""You are an invoice extraction assistant. Your job is to read PDF documents and extract all invoice and credit note details into structured JSON.
BASE_PROMPT="""You are an invoice extraction assistant. Your job is to read PDF documents and extract all invoice and credit note details.
DOCUMENT TYPES YOU MAY ENCOUNTER:
1. **Single Invoice** — one invoice with line items, totals, dates, etc.
2. **Credit Note** — similar to an invoice but represents a credit/refund. Extract it the same way; the total will be positive (the credit amount).
3. **Statement / Summary** — a document listing multiple invoices or credits in a table or list format. Each row or entry represents a separate invoice/credit. Extract EACH one as a separate object in the output array.
3. **Statement / Summary** — a document listing multiple invoices or credits in a table or list format. Each row or entry represents a separate invoice/credit.
4. **Mixed** — a document containing both invoices and credits.
EXTRACTION RULES:
- Extract EVERY invoice or credit you can find. If the document is a statement listing 10 invoices, return all 10.
- Extract EVERY invoice or credit you can find. If the document is a statement listing 10 invoices, include all 10 in the invoices array.
- **customer_identifier**: The name of the customer/buyer. Look for "Bill To", "Customer", "Sold To", or the company name at the top.
- **vendor_identifier**: The name of the vendor/seller. Look for "From", "Vendor", "Supplier", letterhead, or the company issuing the document.
- **date**: The invoice date in ISO 8601 format (YYYY-MM-DD). If multiple dates exist, use the invoice date, not the due date or statement period.
- **invoice_number**: The unique invoice or credit note number. Look for labels like "Invoice #", "Inv No", "Credit Note #", "Reference", "Doc #".
- **account_number**: The customer's account number if present. Not required — omit if not found.
- **total**: The total amount as a decimal string (e.g., "1234.56"). Use the grand total or amount due. For credits, use the credit amount as a positive number. Numbers in parentheses indicate credits — extract them as positive values.
- **explanation**: Only use this when you cannot find any valid invoices. Provide a detailed reason (e.g., "document is blank", "PDF contains only images with no extractable text", "document is a cover letter with no invoice data").
IMPORTANT:
- Do NOT skip entries because some fields are missing. Extract what you can.
- For statements/summaries, each row in an invoice table is a separate invoice entry.
- If OCR fails completely and no text can be extracted at all, return an array with one object containing only the explanation field.
- Your FINAL response must be ONLY a JSON array. Do NOT wrap it in markdown code blocks. Do NOT add any prose before or after the JSON."""
- For statements/summaries, each row in an invoice table is a separate entry in the invoices array.
- If OCR fails completely and no text can be extracted at all, set the explanation field to indicate why."""
INVOICE_TOOL = {
"type": "function",
"function": {
"name": "parsed_invoices",
"description": "Record all extracted invoices and credit notes from the document. Include every invoice found in the invoices array.",
"parameters": {
"type": "object",
"properties": {
"invoices": {
"description": "Array of all invoices and credit notes extracted from the document. Include every one you find.",
"type": "array",
"items": {
"type": "object",
"properties": {
"customer_identifier": {
"description": "The customer's name. e.g., ABC Corporation, Microsoft, etc.",
"type": "string"
},
"vendor_identifier": {
"description": "The vendor's name",
"type": "string"
},
"date": {
"description": "Invoice date in ISO 8601 format (YYYY-MM-DD).",
"type": "string",
"format": "date"
},
"invoice_number": {
"description": "Unique invoice number for the transaction.",
"type": "string"
},
"account_number": {
"description": "Customer's account number associated with the invoice. Not always present on the invoice.",
"type": "string"
},
"total": {
"description": "Total amount of the invoice, including taxes and fees. It should be a decimal number as a string.",
"type": "string",
"pattern": "^\\d+(\\.\\d{1,2})?$"
}
},
"required": ["customer_identifier", "vendor_identifier", "date", "invoice_number", "total"],
"additionalProperties": False
}
},
"explanation": {
"description": "Only use this when you cannot find any valid invoices. Provide a detailed reason (e.g., 'document is blank', 'PDF contains only images with no extractable text', 'document is a cover letter with no invoice data').",
"type": "string"
}
}
}
}
}
def analyze_pdf(pdf_path):
@@ -80,12 +131,18 @@ def analyze_pdf(pdf_path):
],
},
],
tools=[INVOICE_TOOL],
)
text = response.choices[0].message.content
match = re.search(r'```(?:json)?\s*\n(.*?)\n```', text, re.DOTALL)
if match:
text = match.group(1)
return text
message = response.choices[0].message
if message.tool_calls:
for tool_call in message.tool_calls:
if tool_call.function.name == "parsed_invoices":
data = json.loads(tool_call.function.arguments)
return data.get("invoices", [])
return []
def analyze_url(url):
@@ -98,6 +155,11 @@ def analyze_url(url):
def handler(event, context):
print(event)
url = event['url']
print("URL IS", url)
return analyze_url(url)
if "pdf_base64" in event:
pdf_path = "/tmp/invoice.pdf"
with open(pdf_path, "wb") as f:
f.write(base64.b64decode(event["pdf_base64"]))
return analyze_pdf(pdf_path)
if "url" in event:
return analyze_url(event["url"])
raise ValueError("event must contain 'url' or 'pdf_base64'")

26
invoke_lambda.sh Executable file
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@@ -0,0 +1,26 @@
#!/usr/bin/env bash
set -euo pipefail
PDF_PATH="${1:-tests/SWCPI25011315283.pdf}"
ENVIRONMENT="${2:-test}"
if [ ! -f "$PDF_PATH" ]; then
echo "Error: PDF file not found: $PDF_PATH"
exit 1
fi
FUNCTION_NAME="glimpse2-${ENVIRONMENT}"
PAYLOAD_FILE=$(mktemp)
python3 -c "import base64, json, sys; json.dump({'pdf_base64': base64.b64encode(open(sys.argv[1], 'rb').read()).decode()}, open(sys.argv[2], 'w'))" "$PDF_PATH" "$PAYLOAD_FILE"
echo "Invoking ${FUNCTION_NAME} with ${PDF_PATH}..."
aws lambda invoke \
--function-name "$FUNCTION_NAME" \
--payload file://"$PAYLOAD_FILE" \
--cli-binary-format raw-in-base64-out \
/tmp/lambda_response.json
rm -f "$PAYLOAD_FILE"
echo "Response:"
python3 -m json.tool /tmp/lambda_response.json 2>/dev/null || cat /tmp/lambda_response.json

27
main.tf
View File

@@ -1,3 +1,16 @@
terraform {
required_providers {
aws = {
source = "hashicorp/aws"
version = "~> 5.0"
}
}
}
provider "aws" {
region = var.region
}
data "aws_iam_policy_document" "assume_role" {
statement {
effect = "Allow"
@@ -13,11 +26,11 @@ data "aws_iam_policy_document" "assume_role" {
resource "null_resource" "pip_install" {
triggers = {
shell_hash = "${sha256(file("${path.module}/requirements.txt"))}"
shell_hash = "${sha256(file("${path.module}/pyproject.toml"))}"
}
provisioner "local-exec" {
command = "python3 -m pip install -r requirements.txt -t ${path.module}/layer/python"
command = "uv pip compile ${path.module}/pyproject.toml --python 3.11 --no-header -o /tmp/layer-requirements.txt && uv pip install -r /tmp/layer-requirements.txt --python 3.11 -t ${path.module}/layer/python"
}
}
@@ -29,7 +42,7 @@ data "archive_file" "layer" {
}
resource "aws_lambda_layer_version" "layer" {
layer_name = "openai-layer"
layer_name = "openai-layer-${local.env}"
filename = data.archive_file.layer.output_path
source_code_hash = data.archive_file.layer.output_base64sha256
compatible_runtimes = ["python3.11"]
@@ -38,7 +51,7 @@ resource "aws_lambda_layer_version" "layer" {
resource "aws_iam_role" "iam_for_lambda" {
name = "glimpse2"
name = "glimpse2-${local.env}"
assume_role_policy = data.aws_iam_policy_document.assume_role.json
}
@@ -52,11 +65,11 @@ resource "aws_lambda_function" "test_lambda" {
# If the file is not in the current working directory you will need to include a
# path.module in the filename.
filename = "lambda_function_payload.zip"
function_name = "glimpse2"
function_name = "glimpse2-${local.env}"
role = aws_iam_role.iam_for_lambda.arn
handler = "main.handler"
memory_size = 512
timeout = 30
timeout = 60
source_code_hash = data.archive_file.lambda.output_base64sha256
layers = [aws_lambda_layer_version.layer.arn]
@@ -65,7 +78,7 @@ resource "aws_lambda_function" "test_lambda" {
environment {
variables = {
foo = "bar"
environment = local.env
}
}
}

1
prod.tfvars Normal file
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@@ -0,0 +1 @@
environment = "prod"

313
terraform.tfstate.d/test/terraform.tfstate Normal file
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@@ -0,0 +1,313 @@
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1
test.tfvars Normal file
View File

@@ -0,0 +1 @@
environment = "test"

15
variables.tf Normal file
View File

@@ -0,0 +1,15 @@
variable "environment" {
description = "Deployment environment name"
type = string
default = "prod"
}
variable "region" {
description = "AWS region"
type = string
default = "us-east-1"
}
locals {
env = terraform.workspace == "default" ? "prod" : terraform.workspace
}