to-do.md

1. ~~fix llama3.3 - litellm.exceptions.RateLimitError~~ 
2. local PatBase?
3. patent acceptance prediction
4. predict the primary IPC or CPC code of a patent application given (some subset of) the text of the application.
5. abstractive summarization: given the claims or claims section of a patent application, generate the abstract.
6. chatwPatent


dataset--

{
    "application_number": "...",
    "publication_number": "...",
    "title": "...",
    "decision": "...",
    "date_produced": "...",
    "date_published": "...",
    "main_cpc_label": "...",
    "cpc_labels": ["...", "...", "..."],
    "main_ipcr_label": "...",
    "ipcr_labels": ["...", "...", "..."],
    "patent_number": "...",
    "filing_date": "...",
    "patent_issue_date": "...",
    "abandon_date": "...",
    "uspc_class": "...",
    "uspc_subclass": "...",
    "examiner_id": "...",
    "examiner_name_last": "...",
    "examiner_name_first": "...",
    "examiner_name_middle": "...",
    "inventor_list": [
        {
            "inventor_name_last": "...",
            "inventor_name_first": "...",
            "inventor_city": "...",
            "inventor_state": "...",
            "inventor_country": "..."
        }
    ],
    "abstract": "...",
    "claims": "...",
    "background": "...",
    "summary": "...",
    "full_description": "..."
}


utilize the above fields (specifically - application and publication numbers, title, decision status, filing and publication dates, primary and secondary classification codes, inventor(s), examiner, attorney, abstract, claims, background, summary, and full description of the proposed invention)