
#!/usr/bin/env python3
import json
import os
import pprint
import urllib.request

import openai

openai.api_key = "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"


def slurp_file(filename):
    with open(filename, 'r') as file:
        data = file.read()
    return data


BASE_PROMPT="""You extract invoice details from pdfs. Some pdfs are invoices, some are credits, and some are statements that may contain statements or credits. Numbers in parenthesis typically indicate credits. Always follow this json schema. Do not respond with anything except the raw json response. Do not respond in code blocks(```). If you don't find any invoices, make sure to fill out the explanation field at least.
```
{}
```
""".format(slurp_file(os.path.join(os.path.dirname(__file__), 'schema.json')))


client = openai.OpenAI(api_key="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")
client.api_key = "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"


def analyze_pdf(pdf_path):
    assistant = client.beta.assistants.create(
        name="pdf-reader",
        instructions=BASE_PROMPT,
        model="gpt-4o",
        tools=[{"type": "file_search"}],
    )

    with open(pdf_path, 'rb') as f:
        message_file = client.files.create(file=f, purpose="assistants")

    thread = client.beta.threads.create(
        messages=[
            {
                "role": "user",
                "content": "extract the invoice(s) and/or credit(s) details from this invoice or statement",
                "attachments": [
                    {"file_id": message_file.id, "tools": [{"type": "file_search"}]}
                ],
            }
        ]
    )
    print(thread.id)

    run = client.beta.threads.runs.create_and_poll(
        thread_id=thread.id, assistant_id=assistant.id
    )

    messages = list(client.beta.threads.messages.list(thread_id=thread.id, run_id=run.id))
    print("MESSAGES")
    pprint.pprint(messages)
    print("\n\n")
    print("status", run.status)
    print("\n\n")
    print("full run")
    pprint.pprint(run)
    return json.loads(messages[0].content[0].text.value)


def analyze_url(url):
    with urllib.request.urlopen(url) as response:
        data = response.read()
    with open("/tmp/test.pdf", "wb") as f:
        f.write(data)
    return analyze_pdf("/tmp/test.pdf")


def handler(event, context):
    print(event)
    url = event['url']
    print("URL IS", url)
    return analyze_url(url)