diff --git a/.gitattributes b/.gitattributes index a6344aac8c09253b3b630fb776ae94478aa0275b..cca4a3a504c53d420688210b71e20435b3e5c6ea 100644 --- a/.gitattributes +++ b/.gitattributes @@ -1,35 +1 @@ -*.7z filter=lfs diff=lfs merge=lfs -text -*.arrow filter=lfs diff=lfs merge=lfs -text -*.bin filter=lfs diff=lfs merge=lfs -text -*.bz2 filter=lfs diff=lfs merge=lfs -text -*.ckpt filter=lfs diff=lfs merge=lfs -text -*.ftz filter=lfs diff=lfs merge=lfs -text -*.gz filter=lfs diff=lfs merge=lfs -text -*.h5 filter=lfs diff=lfs merge=lfs -text -*.joblib filter=lfs diff=lfs merge=lfs -text -*.lfs.* filter=lfs diff=lfs merge=lfs -text -*.mlmodel filter=lfs diff=lfs merge=lfs -text -*.model filter=lfs diff=lfs merge=lfs -text -*.msgpack filter=lfs diff=lfs merge=lfs -text -*.npy filter=lfs diff=lfs merge=lfs -text -*.npz filter=lfs diff=lfs merge=lfs -text -*.onnx filter=lfs diff=lfs merge=lfs -text -*.ot filter=lfs diff=lfs merge=lfs -text -*.parquet filter=lfs diff=lfs merge=lfs -text -*.pb filter=lfs diff=lfs merge=lfs -text -*.pickle filter=lfs diff=lfs merge=lfs -text -*.pkl filter=lfs diff=lfs merge=lfs -text -*.pt filter=lfs diff=lfs merge=lfs -text -*.pth filter=lfs diff=lfs merge=lfs -text -*.rar filter=lfs diff=lfs merge=lfs -text -*.safetensors filter=lfs diff=lfs merge=lfs -text -saved_model/**/* filter=lfs diff=lfs merge=lfs -text -*.tar.* filter=lfs diff=lfs merge=lfs -text -*.tar filter=lfs diff=lfs merge=lfs -text -*.tflite filter=lfs diff=lfs merge=lfs -text -*.tgz filter=lfs diff=lfs merge=lfs -text -*.wasm filter=lfs diff=lfs merge=lfs -text -*.xz filter=lfs diff=lfs merge=lfs -text -*.zip filter=lfs diff=lfs merge=lfs -text -*.zst filter=lfs diff=lfs merge=lfs -text -*tfevents* filter=lfs diff=lfs merge=lfs -text +*.json filter= diff= merge= -text diff --git a/Dockerfile b/Dockerfile new file mode 100644 index 0000000000000000000000000000000000000000..2adb14ecfe3fa8c8903f1481a0be3029b732344f --- /dev/null +++ b/Dockerfile @@ -0,0 +1,39 @@ +# PrimaryDraft: one image, backend serves the built frontend. +# +# Deliberately does NOT ship the annual-report PDF cache (859 MB). The extracted +# records are 620 KB and the pipeline runs entirely from them; PDFs are only +# needed to RE-extract, and live ingest downloads what it needs on demand. + +# ---- stage 1: build the UI ------------------------------------------------- +FROM node:22-slim AS ui +WORKDIR /ui +COPY app/frontend/package*.json ./ +RUN npm ci --no-audit --no-fund +COPY app/frontend/ ./ +RUN npm run build + +# ---- stage 2: runtime ------------------------------------------------------ +FROM python:3.12-slim +ENV PYTHONUNBUFFERED=1 PIP_NO_CACHE_DIR=1 PORT=8000 + +WORKDIR /app +COPY app/backend/pyproject.toml ./ +COPY app/backend/primarydraft ./primarydraft +RUN pip install --no-cache-dir \ + "fastapi>=0.115" "uvicorn[standard]>=0.32" "pydantic>=2.9" "httpx>=0.27" \ + "pdfplumber>=0.11" "python-docx>=1.1" "python-multipart>=0.0.12" + +# The BSE scrip master (1.8 MB) so search works on the first request, and +# instantly, even if the exchange is slow or blocks the host. +# Shipped as seed_cache/ because the Hub refuses paths under .cache/, then +# mapped back to the runtime cache location inside the image. +COPY app/backend/seed_cache/bse/scrip_master.json ./.cache/bse/scrip_master.json +COPY app/backend/seed_cache/mca ./.cache/mca + +COPY --from=ui /ui/dist ../frontend/dist + +# Writable for run snapshots, exports and any live ingest. +RUN mkdir -p .runs .exports .cache/bse && chmod -R 777 .runs .exports .cache + +EXPOSE 8000 +CMD ["sh","-c","uvicorn primarydraft.main:app --host 0.0.0.0 --port ${PORT:-8000}"] diff --git a/README.md b/README.md index ed4c73e8a3e7539c07dec8126984880e73917058..020ae5ed768dd56208fd22629d12577b06807ee3 100644 --- a/README.md +++ b/README.md @@ -1,10 +1,18 @@ --- -title: Primarydraft -emoji: ๐Ÿ“‰ -colorFrom: gray -colorTo: red +title: PrimaryDraft +emoji: ๐Ÿ“Š +colorFrom: blue +colorTo: green sdk: docker +app_port: 8000 pinned: false +license: mit +short_description: The IPO offer document that checks itself --- -Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference +# PrimaryDraft + +Pre-filing consistency gate for Indian SME IPO offer documents. +27 deterministic checks, no language model in the correctness loop. + +Rename this file to `README.md` in the Space repository root. diff --git a/app/backend/primarydraft/__init__.py b/app/backend/primarydraft/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/app/backend/primarydraft/cin.py b/app/backend/primarydraft/cin.py new file mode 100644 index 0000000000000000000000000000000000000000..7ad4d24aace8b7707eb4a3c9efdd67be3c92682b --- /dev/null +++ b/app/backend/primarydraft/cin.py @@ -0,0 +1,179 @@ +"""Decompose a Corporate Identity Number. + +A CIN is 21 characters and every one of them means something. Reading it costs +nothing and settles several eligibility questions before a single financial +statement is opened: + + U 62090 KA 2025 PTC 207753 + โ”‚ โ”‚ โ”‚ โ”‚ โ”‚ โ””โ”€โ”€ registration number with the ROC + โ”‚ โ”‚ โ”‚ โ”‚ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€ ownership class: PTC is a private limited company + โ”‚ โ”‚ โ”‚ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€ year of incorporation + โ”‚ โ”‚ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€ state of the registrar + โ”‚ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€ NIC industry code + โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€ L listed, U unlisted + +This is pure parsing of a real identifier. Nothing is inferred that the CIN does +not actually encode, and anything unrecognised is reported as unrecognised. +""" + +from __future__ import annotations + +import datetime as _dt +import re +from dataclasses import dataclass + +CIN_RE = re.compile( + r"^(?P[LU])" + r"(?P\d{5})" + r"(?P[A-Z]{2})" + r"(?P\d{4})" + r"(?P[A-Z]{3})" + r"(?P\d{6})$" +) + +#: Ownership classes as used by the MCA. +OWNERSHIP: dict[str, str] = { + "PLC": "Public Limited Company", + "PTC": "Private Limited Company", + "OPC": "One Person Company", + "FLC": "Financial Lease Company (public)", + "FTC": "Subsidiary of a foreign company (private)", + "GAP": "General association (public)", + "GAT": "General association (private)", + "GOI": "Government of India company", + "SGC": "State government company", + "NPL": "Not-for-profit company under section 8", + "ULL": "Unlimited liability company (public)", + "ULT": "Unlimited liability company (private)", +} + +#: Ownership classes that are already a public company for Companies Act purposes. +PUBLIC_CLASSES = {"PLC", "FLC", "GAP", "GOI", "SGC", "ULL"} + +STATES: dict[str, str] = { + "AP": "Andhra Pradesh", "AR": "Arunachal Pradesh", "AS": "Assam", "BR": "Bihar", + "CH": "Chandigarh", "CT": "Chhattisgarh", "DL": "Delhi", "GA": "Goa", + "GJ": "Gujarat", "HR": "Haryana", "HP": "Himachal Pradesh", "JH": "Jharkhand", + "JK": "Jammu and Kashmir", "KA": "Karnataka", "KL": "Kerala", "LD": "Lakshadweep", + "MH": "Maharashtra", "ML": "Meghalaya", "MN": "Manipur", "MP": "Madhya Pradesh", + "MZ": "Mizoram", "NL": "Nagaland", "OR": "Odisha", "PB": "Punjab", + "PY": "Puducherry", "RJ": "Rajasthan", "SK": "Sikkim", "TN": "Tamil Nadu", + "TG": "Telangana", "TS": "Telangana", "TR": "Tripura", "UP": "Uttar Pradesh", + "UR": "Uttarakhand", "UT": "Uttarakhand", "WB": "West Bengal", + "AN": "Andaman and Nicobar Islands", "DN": "Dadra and Nagar Haveli", +} + +#: NIC 2008 divisions, by the first two digits of the industry code. +NIC_DIVISIONS: dict[str, str] = { + "01": "Crop and animal production", "10": "Manufacture of food products", + "11": "Manufacture of beverages", "13": "Manufacture of textiles", + "14": "Manufacture of wearing apparel", "17": "Manufacture of paper products", + "20": "Manufacture of chemicals", "21": "Manufacture of pharmaceuticals", + "22": "Manufacture of rubber and plastic products", + "23": "Manufacture of other non-metallic mineral products", + "24": "Manufacture of basic metals", + "25": "Manufacture of fabricated metal products", + "26": "Manufacture of computer, electronic and optical products", + "27": "Manufacture of electrical equipment", + "28": "Manufacture of machinery and equipment", + "29": "Manufacture of motor vehicles", "30": "Manufacture of other transport equipment", + "35": "Electricity, gas and air conditioning supply", + "41": "Construction of buildings", "42": "Civil engineering", + "43": "Specialised construction activities", + "45": "Wholesale and retail trade of motor vehicles", + "46": "Wholesale trade", "47": "Retail trade", + "49": "Land transport", "52": "Warehousing and support for transportation", + "55": "Accommodation", "56": "Food and beverage service activities", + "58": "Publishing activities", "59": "Motion picture and television production", + "61": "Telecommunications", + "62": "Computer programming, consultancy and related activities", + "63": "Information service activities", + "64": "Financial service activities", "65": "Insurance and pension funding", + "66": "Activities auxiliary to financial services", "68": "Real estate activities", + "69": "Legal and accounting activities", + "70": "Activities of head offices and management consultancy", + "71": "Architecture and engineering, technical testing and analysis", + "72": "Scientific research and development", "73": "Advertising and market research", + "77": "Rental and leasing activities", "78": "Employment activities", + "80": "Security and investigation activities", "82": "Business support activities", + "85": "Education", "86": "Human health activities", +} + + +@dataclass +class ParsedCIN: + raw: str + valid: bool + listing: str = "" + is_listed: bool | None = None + industry_code: str = "" + nic_division: str = "" + nic_division_name: str = "" + state_code: str = "" + state: str = "" + year: int | None = None + age_years: int | None = None + ownership_code: str = "" + ownership: str = "" + is_public_company: bool | None = None + registration_number: str = "" + error: str = "" + + def to_dict(self) -> dict[str, object]: + return self.__dict__.copy() + + +def parse_cin(cin: str, today: _dt.date | None = None) -> ParsedCIN: + """Parse a real CIN. Reports what it cannot recognise rather than guessing.""" + raw = (cin or "").strip().upper().replace(" ", "").replace("-", "") + m = CIN_RE.match(raw) + if not m: + return ParsedCIN( + raw=raw, valid=False, + error=("A Corporate Identity Number is 21 characters in the form " + "U99999AA9999AAA999999: a listing letter, a five digit NIC code, " + "a two letter state code, the year of incorporation, a three letter " + "ownership class and a six digit registration number."), + ) + + g = m.groupdict() + year = int(g["year"]) + today = today or _dt.date.today() + own = g["ownership"] + div = g["industry"][:2] + + return ParsedCIN( + raw=raw, + valid=True, + listing=g["listing"], + is_listed=(g["listing"] == "L"), + industry_code=g["industry"], + nic_division=div, + nic_division_name=NIC_DIVISIONS.get(div, "NIC division not in the local table"), + state_code=g["state"], + state=STATES.get(g["state"], "state code not recognised"), + year=year, + age_years=max(0, today.year - year), + ownership_code=own, + ownership=OWNERSHIP.get(own, "ownership class not recognised"), + is_public_company=(own in PUBLIC_CLASSES) if own in OWNERSHIP else None, + registration_number=g["registration"], + ) + + +def completed_financial_years(year_of_incorporation: int, + today: _dt.date | None = None) -> int: + """How many full Indian financial years the company can possibly have closed. + + An Indian financial year ends on 31 March. A company incorporated during + FY N-1/N cannot have closed more than one year by the following 31 March. + This bounds the track record available for Regulation 229(6); it does not + assert that audited accounts for those years exist. + """ + today = today or _dt.date.today() + # The FY ending 31 March of `fy_end_year` is the last one fully closed. + fy_end_year = today.year if today.month > 3 else today.year - 1 + # A company incorporated in calendar year Y closes its first FY on 31 March + # of Y+1 at the earliest. + first_close = year_of_incorporation + 1 + return max(0, fy_end_year - first_close + 1) diff --git a/app/backend/primarydraft/data/companies/537669.json b/app/backend/primarydraft/data/companies/537669.json new file mode 100644 index 0000000000000000000000000000000000000000..fa5e7938f1eb7db316a04727786d498eb6a57128 --- /dev/null +++ b/app/backend/primarydraft/data/companies/537669.json @@ -0,0 +1,791 @@ +{ + "scrip_code": "537669", + "bse": { + "scrip_name": "Laxmipati Engineering Works Ltd", + "issuer_name": "LAXMIPATI ENGINEERING WORKS LIMITED", + "group": "MT", + "segment": "Equity", + "isin": "INE920P01019", + "face_value": "10.00", + "industry": "", + "sector": "Industrials", + "industry_new": "Capital Goods", + "market_cap": "259.56", + "eps_reported": "47.00", + "pe_reported": "9.60", + "security_id": "LAXMIPATI" + }, + "annual_report": { + "year": "2026", + "url": "https://www.bseindia.com/xml-data/corpfiling/AttachHis/cfdf14dc-e542-478a-b4cd-e22ce988d43b.pdf", + "authorised_at": "2026-06-23T10:51:34.153", + "local_path": "/Users/juni/hackathons-works/1/sebi-techsprint/app/backend/.cache/bse/ar_537669_2026.pdf", + "available_years": [ + "2026", + "2025", + "2024", + "2023", + "2022", + "2021", + "2020", + "2019" + ] + }, + "extraction": { + "scrip_code": "537669", + "pdf_path": "/Users/juni/hackathons-works/1/sebi-techsprint/app/backend/.cache/bse/ar_537669_2026.pdf", + "pages": 117, + "cin": "L35111GJ2012PLC068922", + "isin": "INE920P01019", + "company_name": "Laxmipati Engineering Works Limited", + "emails": [ + "cs@laxmipatiengineering.com", + "evoting@nsdl.co.in", + "helpdesk.evoting@cdslindia.com", + "info@bigshareonline.com", + "investor@bigshareonline.com", + "rbksurat@gmail.com" + ], + "dins": [ + "00005468", + "00005665", + "01685738", + "02227413" + ], + "audited_pl": { + "revenue_from_operations": { + "current": { + "field": "revenue_from_operations", + "value": 719937000.0, + "page": 98, + "line": "I Revenue from Operations 18 7,199.37 5,009.29", + "scale": 100000.0, + "section": "audited_pl", + "basis": null + }, + "previous": { + "field": "revenue_from_operations", + "value": 500929000.0, + "page": 98, + "line": "I Revenue from Operations 18 7,199.37 5,009.29", + "scale": 100000.0, + "section": "audited_pl", + "basis": null + } + }, + "other_income": { + "current": { + "field": "other_income", + "value": 3886000.0, + "page": 98, + "line": "II Other income 19 38.86 5.12", + "scale": 100000.0, + "section": 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total_expenses", + "pat = pbt - tax" + ], + "isin_corroborated": true, + "warnings": [ + "Balance Sheet: a candidate page was found but its accounting identities did not close, so the figures were not trusted and have been withheld.", + "balance sheet not machine-readable in this filing" + ] + }, + { + "scrip_code": "543542", + "name": "Kesar India Ltd", + "cin": "L51220MH2003PLC142989", + "isin": "INE0L1C01019", + "industry": "", + "sector": "Consumer Discretionary", + "year": "2025", + "pages": 114, + "pl_fields": 14, + "bs_fields": 14, + "dr_fields": 0, + "identities": [ + "total_income = revenue + other_income", + "pbt = total_income - total_expenses", + "pat = pbt - tax", + "total assets = total equity and liabilities" + ], + "isin_corroborated": true, + "warnings": [ + "Directors' Report financial results: a candidate page was found but its accounting identities did not close, so the figures were not trusted and have been withheld." + ] + }, + { + "scrip_code": "543953", + "name": "Khazanchi Jewellers Ltd", + "cin": "L36911TN1996PLC034918", + "isin": "INE0OWC01011", + "industry": "", + "sector": "Consumer Discretionary", + "year": "2026", + "pages": 105, + "pl_fields": 12, + "bs_fields": 0, + "dr_fields": 0, + "identities": [ + "total_income = revenue + other_income", + "pat = pbt - tax" + ], + "isin_corroborated": true, + "warnings": [ + "Balance Sheet: a candidate page was found but its accounting identities did not close, so the figures were not trusted and have been withheld.", + "balance sheet not machine-readable in this filing" + ] + }, + { + "scrip_code": "537669", + "name": "Laxmipati Engineering Works Ltd", + "cin": "L35111GJ2012PLC068922", + "isin": "INE920P01019", + "industry": "", + "sector": "Industrials", + "year": "2026", + "pages": 117, + "pl_fields": 14, + "bs_fields": 12, + "dr_fields": 8, + "identities": [ + "total_income = revenue + other_income", + "pbt = total_income - total_expenses", + "total assets = total equity and liabilities", + "total_income = revenue + other_income" + ], + "isin_corroborated": true, + "warnings": [] + }, + { + "scrip_code": "543746", + "name": "Logica Infoway Ltd", + "cin": "L30007WB1995PLC073218", + "isin": "INE0BSU01018", + "industry": "", + "sector": "Consumer Discretionary", + "year": "2025", + "pages": 131, + "pl_fields": 13, + "bs_fields": 0, + "dr_fields": 0, + "identities": [ + "pat = pbt - tax" + ], + "isin_corroborated": true, + "warnings": [ + "Directors' Report financial results: a candidate page was found but its accounting identities did not close, so the figures were not trusted and have been withheld.", + "balance sheet not machine-readable in this filing" + ] + }, + { + "scrip_code": "544434", + "name": "Neetu Yoshi Ltd", + "cin": "U35999UR2020PLC010670", + "isin": "INE0UZO01024", + "industry": "", + "sector": "Industrials", + "year": "2025", + "pages": 94, + "pl_fields": 13, + "bs_fields": 0, + "dr_fields": 6, + "identities": [ + "total_income = revenue + other_income", + "pbt = total_income - total_expenses", + "total_income = revenue + other_income", + "pbt = total_income - total_expenses" + ], + "isin_corroborated": true, + "warnings": [ + "balance sheet not machine-readable in this filing" + ] + }, + { + "scrip_code": "544296", + "name": "Nisus Finance Services Co Ltd", + "cin": "L65923MH2013PLC247317", + "isin": "INE0DQN01013", + "industry": "", + "sector": "Financial Services", + "year": "2025", + "pages": 105, + "pl_fields": 14, + "bs_fields": 0, + "dr_fields": 6, + "identities": [ + "total_income = revenue + other_income", + "pbt = total_income - total_expenses", + "pat = pbt - tax", + "total_income = revenue + other_income" + ], + "isin_corroborated": true, + "warnings": [ + "balance sheet not machine-readable in this filing" + ] + }, + { + "scrip_code": "544498", + "name": "Oval Projects Engineering Ltd", + "cin": "L74900TR2013PLC008465", + "isin": "INE0RTI01017", + "industry": "", + "sector": "Industrials", + "year": "2025", + "pages": 152, + "pl_fields": 14, + "bs_fields": 11, + "dr_fields": 0, + "identities": [ + "total_income = revenue + other_income", + "pbt = total_income - total_expenses", + "pat = pbt - tax", + "total assets = total equity and liabilities" + ], + "isin_corroborated": false, + "warnings": [ + "Directors' Report financial results: a candidate page was found but its accounting identities did not close, so the figures were not trusted and have been withheld." + ] + }, + { + "scrip_code": "544657", + "name": "Pajson Agro India Ltd", + "cin": "L01100DL2021PLC386740", + "isin": "INE14LM01012", + "industry": "", + "sector": "Fast Moving Consumer Goods", + "year": "2026", + "pages": 66, + "pl_fields": 0, + "bs_fields": 0, + "dr_fields": 7, + "identities": [ + "pbt = total_income - total_expenses", + "pat = pbt - tax" + ], + "isin_corroborated": true, + "warnings": [ + "Statement of Profit and Loss: a candidate page was found but its accounting identities did not close, so the figures were not trusted and have been withheld.", + "Balance Sheet: a candidate page was found but its accounting identities did not close, so the figures were not trusted and have been withheld.", + "audited P&L not machine-readable in this filing", + "balance sheet not machine-readable in this filing" + ] + }, + { + "scrip_code": "543363", + "name": "Prevest Denpro Ltd", + "cin": "L85199JK1999PLC001969", + "isin": "INE0GAO01018", + "industry": "", + "sector": "Healthcare", + "year": "2025", + "pages": 177, + "pl_fields": 11, + "bs_fields": 12, + "dr_fields": 0, + "identities": [ + "total_income = revenue + other_income", + "pbt = total_income - total_expenses", + "total assets = total equity and liabilities" + ], + "isin_corroborated": true, + "warnings": [ + "Directors' Report financial results: a candidate page was found but its accounting identities did not close, so the figures were not trusted and have been withheld." + ] + }, + { + "scrip_code": "544141", + "name": "Pune E - Stock Broking Ltd", + "cin": "L67120PN2007PLC130374", + "isin": "INE510U01018", + "industry": "", + "sector": "Financial Services", + "year": "2025", + "pages": 141, + "pl_fields": 14, + "bs_fields": 0, + "dr_fields": 12, + "identities": [ + "total_income = revenue + other_income", + "pbt = total_income - total_expenses", + "pat = pbt - tax", + "total_income = revenue + other_income", + "pat = pbt - tax" + ], + "isin_corroborated": false, + "warnings": [ + "balance sheet not machine-readable in this filing" + ] + }, + { + "scrip_code": "544291", + "name": "Rajesh Power Services Ltd", + "cin": "L31300GJ2010PLC059536", + "isin": "INE0VN801010", + "industry": "", + "sector": "Utilities", + "year": "2025", + "pages": 76, + "pl_fields": 9, + "bs_fields": 0, + "dr_fields": 0, + "identities": [ + "pbt = total_income - total_expenses" + ], + "isin_corroborated": false, + "warnings": [ + "Directors' Report financial results: a candidate page was found but its accounting identities did not close, so the figures were not trusted and have been withheld.", + "balance sheet not machine-readable in this filing" + ] + }, + { + "scrip_code": "544189", + "name": "Sattrix Information Security Ltd", + "cin": "U72200GJ2013PLC076845", + "isin": "INE0QUV01010", + "industry": "", + "sector": "Information Technology", + "year": "2025", + "pages": 193, + "pl_fields": 10, + "bs_fields": 0, + "dr_fields": 6, + "identities": [ + "total_income = revenue + other_income", + "pbt = total_income - total_expenses", + "pbt = total_income - total_expenses" + ], + "isin_corroborated": false, + "warnings": [ + "balance sheet not machine-readable in this filing" + ] + }, + { + "scrip_code": "543782", + "name": "Sealmatic India Ltd", + "cin": "U26900MH2009PLC197524", + "isin": "INE0O4601016", + "industry": "", + "sector": "Industrials", + "year": "2026", + "pages": 167, + "pl_fields": 11, + "bs_fields": 0, + "dr_fields": 7, + "identities": [ + "pbt = total_income - total_expenses", + "pat = pbt - tax", + "pbt = total_income - total_expenses" + ], + "isin_corroborated": false, + "warnings": [ + "Balance Sheet: a candidate page was found but its accounting identities did not close, so the figures were not trusted and have been withheld.", + "balance sheet not machine-readable in this filing" + ] + }, + { + "scrip_code": "544458", + "name": "Shree Refrigerations Ltd", + "cin": "L29191PN2006PLC128377", + "isin": "INE0FMZ01045", + "industry": "", + "sector": "Industrials", + "year": "2026", + "pages": 84, + "pl_fields": 13, + "bs_fields": 0, + "dr_fields": 0, + "identities": [ + "total_income = revenue + other_income", + "pbt = total_income - total_expenses" + ], + "isin_corroborated": true, + "warnings": [ + "Directors' Report financial results: a candidate page was found but its accounting identities did not close, so the figures were not trusted and have been withheld.", + "Balance Sheet: a candidate page was found but its accounting identities did not close, so the figures were not trusted and have been withheld.", + "balance sheet not machine-readable in this filing" + ] + }, + { + "scrip_code": "544267", + "name": "Subam Papers Ltd", + "cin": "U21012TN2004PLC054403", + "isin": "INE0U6201010", + "industry": "", + "sector": "Industrials", + "year": "2025", + "pages": 162, + "pl_fields": 15, + "bs_fields": 0, + "dr_fields": 8, + "identities": [ + "total_income = revenue + other_income", + "pbt = total_income - total_expenses", + "pat = pbt - tax", + "total_income = revenue + other_income", + "pbt = total_income - total_expenses" + ], + "isin_corroborated": false, + "warnings": [ + "Balance Sheet: a candidate page was found but its accounting identities did not close, so the figures were not trusted and have been withheld.", + "balance sheet not machine-readable in this filing" + ] + }, + { + "scrip_code": "544001", + "name": "Sunita Tools Ltd", + "cin": "U29220MH1988PLC045850", + "isin": "INE0Q1S01010", + "industry": "", + "sector": "Industrials", + "year": "2025", + "pages": 108, + "pl_fields": 11, + "bs_fields": 0, + "dr_fields": 0, + "identities": [ + "total_income = revenue + other_income", + "pbt = total_income - total_expenses" + ], + "isin_corroborated": false, + "warnings": [ + "Directors' Report financial results: a candidate page was found but its accounting identities did not close, so the figures were not trusted and have been withheld.", + "Balance Sheet: a candidate page was found but its accounting identities did not close, so the figures were not trusted and have been withheld.", + "balance sheet not machine-readable in this filing" + ] + }, + { + "scrip_code": "543391", + "name": "Suyog Gurbaxani Funicular Ropeways Ltd", + "cin": "L45203MH2010PLC200005", + "isin": "INE07GA01011", + "industry": "", + "sector": "Industrials", + "year": "2025", + "pages": 83, + "pl_fields": 10, + "bs_fields": 0, + "dr_fields": 0, + "identities": [ + "total_income = revenue + other_income", + "pbt = total_income - total_expenses" + ], + "isin_corroborated": false, + "warnings": [ + "Directors' Report financial results: a candidate page was found but its accounting identities did not close, so the figures were not trusted and have been withheld.", + "balance sheet not machine-readable in this filing" + ] + }, + { + "scrip_code": "544406", + "name": "Unified Data Tech Solutions Ltd", + "cin": "L51900MH2010PLC202878", + "isin": "INE1ABX01018", + "industry": "", + "sector": "Information Technology", + "year": "2025", + "pages": 46, + "pl_fields": 0, + "bs_fields": 15, + "dr_fields": 5, + "identities": [ + "total assets = total equity and liabilities", + "total_income = revenue + other_income" + ], + "isin_corroborated": false, + "warnings": [ + "Statement of Profit and Loss: a candidate page was found but its accounting identities did not close, so the figures were not trusted and have been withheld.", + "audited P&L not machine-readable in this filing" + ] + }, + { + "scrip_code": "543931", + "name": "Veefin Solutions Ltd", + "cin": "L72900MH2020PLC347893", + "isin": "INE0Q0M01015", + "industry": "", + "sector": "Information Technology", + "year": "2025", + "pages": 201, + "pl_fields": 15, + "bs_fields": 13, + "dr_fields": 7, + "identities": [ + "total_income = revenue + other_income", + "pbt = total_income - total_expenses", + "pat = pbt - tax", + "total assets = total equity and liabilities", + "pbt = total_income - total_expenses" + ], + "isin_corroborated": true, + "warnings": [] + }, + { + "scrip_code": "544310", + "name": "Yash Highvoltage Ltd", + "cin": "L40109GJ2002PLC040833", + "isin": "INE00GK01023", + "industry": "", + "sector": "Industrials", + "year": "2025", + "pages": 54, + "pl_fields": 5, + "bs_fields": 0, + "dr_fields": 6, + "identities": [ + "total_income = revenue + other_income", + "pbt = total_income - total_expenses" + ], + "isin_corroborated": false, + "warnings": [ + "balance sheet not machine-readable in this filing" + ] + } + ], + "count": 40 +} \ No newline at end of file diff --git a/app/backend/primarydraft/drafting/__init__.py b/app/backend/primarydraft/drafting/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/app/backend/primarydraft/drafting/llm.py b/app/backend/primarydraft/drafting/llm.py new file mode 100644 index 0000000000000000000000000000000000000000..78192c6c3979343b3686daae024a8eaa1ef736c3 --- /dev/null +++ b/app/backend/primarydraft/drafting/llm.py @@ -0,0 +1,137 @@ +"""Optional Claude narrative layer. + +The model may improve the *prose* around figures. It may not touch the figures. +Every `` element is extracted before the call, replaced with an opaque +placeholder, and restored afterwards; if the model drops or alters a placeholder, +the rewrite is rejected and the deterministic template stands. + +With no API key configured the whole layer is inert and the product is unaffected: +the correctness engine never consults it. +""" + +from __future__ import annotations + +import logging +import os +import re +from typing import Any + +log = logging.getLogger(__name__) + +MODEL = os.environ.get("PRIMARYDRAFT_MODEL", "claude-sonnet-5") +CITE_RE = re.compile(r"]*>.*?", re.S | re.I) +PLACEHOLDER = "โŸฆF{}โŸง" +PLACEHOLDER_RE = re.compile(r"โŸฆF(\d+)โŸง") + +SYSTEM = """You are helping draft sections of an Indian SME IPO offer document \ +(a DRHP under SEBI ICDR Regulations, 2018, Schedule VI Part A). + +You will receive section HTML containing placeholders of the form โŸฆF0โŸง, โŸฆF1โŸง โ€ฆ +Each placeholder stands for a figure that has already been verified against the \ +issuer's filed records. + +Absolute rules: +1. Reproduce every placeholder exactly, once, in the same order. Never invent, \ +alter, merge, drop or reorder one. +2. Never introduce a number, date, name, percentage or amount of your own. If a \ +fact is not present, say it is not disclosed in the source records. +3. Do not add claims about the issuer that the input does not support. No \ +marketing language, no forecasts, no opinions on the merits of the issue. +4. Keep the regulatory register: precise, impersonal, in the style of an Indian \ +offer document. Keep the same

,

    ,
      ,
    • and structure. +5. Return only the rewritten HTML fragment. + +Your job is clarity and flow, nothing else. A single invented figure would be a \ +disclosure failure.""" + + +def llm_status() -> dict[str, Any]: + key = os.environ.get("ANTHROPIC_API_KEY") + try: + import anthropic # noqa: F401 + sdk = True + except ImportError: + sdk = False + return { + "enabled": bool(key) and sdk, + "reason": ("ready" if (key and sdk) + else "ANTHROPIC_API_KEY not set" if not key + else "anthropic SDK not installed (pip install '.[ai]')"), + "model": MODEL, + "affects_correctness": False, + "note": ("The narrative layer is optional. The consistency engine is deterministic " + "and runs identically whether or not this is enabled."), + } + + +def _protect(html: str) -> tuple[str, list[str]]: + cites: list[str] = [] + + def sub(m: re.Match[str]) -> str: + cites.append(m.group(0)) + return PLACEHOLDER.format(len(cites) - 1) + + return CITE_RE.sub(sub, html), cites + + +def _restore(html: str, cites: list[str]) -> str | None: + """Put the figures back: but only if the model preserved them exactly.""" + found = [int(m.group(1)) for m in PLACEHOLDER_RE.finditer(html)] + if sorted(found) != list(range(len(cites))): + return None # a placeholder was dropped, duplicated or invented + return PLACEHOLDER_RE.sub(lambda m: cites[int(m.group(1))], html) + + +def rewrite_section_html(html: str, title: str, client: Any) -> tuple[str, bool]: + protected, cites = _protect(html) + try: + msg = client.messages.create( + model=MODEL, + max_tokens=2000, + system=SYSTEM, + messages=[{ + "role": "user", + "content": (f"Section: {title}\n\nRewrite this fragment for clarity, " + f"obeying every rule.\n\n{protected}"), + }], + ) + out = "".join(b.text for b in msg.content if getattr(b, "type", "") == "text").strip() + except Exception as e: # noqa: BLE001 - never let the model break the draft + log.warning("LLM rewrite failed for %s: %s", title, e) + return html, False + + out = re.sub(r"^```(?:html)?|```$", "", out, flags=re.M).strip() + restored = _restore(out, cites) + if restored is None: + log.warning("LLM rewrite for %s dropped or altered a citation: rejected", title) + return html, False + return restored, True + + +def rewrite_sections(run: Any) -> int: + """Rewrite narrative in place. Returns how many sections the model improved.""" + status = llm_status() + if not status["enabled"]: + log.info("LLM narrative layer disabled: %s", status["reason"]) + return 0 + + import anthropic + + client = anthropic.Anthropic() + n = 0 + for sec in run.sections: + new_html, changed = rewrite_section_html(sec.html, sec.title, client) + if changed: + sec.html = new_html + sec.text = re.sub(r"\s+", " ", re.sub(r"<[^>]+>", " ", new_html)).strip() + sec.word_count = len(sec.text.split()) + sec.narrative_source = "llm" + n += 1 + from ..models import Decision + run.decisions.append(Decision( + actor="system", action="generate", + detail=(f"Claude rewrote narrative in {n} of {len(run.sections)} sections. " + "Every figure was held fixed and verified after generation; " + "rewrites that altered a citation were rejected."), + )) + return n diff --git a/app/backend/primarydraft/drafting/templates.py b/app/backend/primarydraft/drafting/templates.py new file mode 100644 index 0000000000000000000000000000000000000000..a27085a2ef13a32b406fc7928b2d0b3eedf70af6 --- /dev/null +++ b/app/backend/primarydraft/drafting/templates.py @@ -0,0 +1,612 @@ +"""Draft the offer document from the ledger: and only from the ledger. + +Templates never contain a figure. They contain tokens: + + {{fact:fin.current.revenue_from_operations}} + +which the renderer resolves against the Disclosure Ledger into a cited span. A +number that is not a token cannot reach the page, which is what lets rule PRV-001 +mechanically prove that no unsourced figure was published. If a token names a +fact the ledger does not hold, the renderer emits a visible abstention rather +than inventing a value. +""" + +from __future__ import annotations + +import html +import re +from typing import Any + +from ..issue import IssueTerms +from ..models import DraftSection, Fact, FactStatus, Unit + +TOKEN_RE = re.compile(r"\{\{fact:([a-zA-Z0-9_.\-]+)\}\}") +ISSUE_RE = re.compile(r"\{\{issue:([a-zA-Z0-9_.\-]+)\}\}") +#: Any bare digit run in rendered prose is a bug: PRV-001 hunts for these. +BARE_NUMBER_RE = re.compile(r"(?#;])\d[\d,]*(?:\.\d+)?(?![\w<])") + + +def fmt_value(f: Fact) -> str: + v = f.value + if isinstance(v, (int, float)): + if f.unit == Unit.INR: + a = abs(v) + if a >= 1_00_00_000: + return f"โ‚น{v / 1_00_00_000:,.2f} crore" + if a >= 1_00_000: + return f"โ‚น{v / 1_00_000:,.2f} lakh" + return f"โ‚น{v:,.2f}" + if f.unit == Unit.PCT: + return f"{v:,.2f}%" + if f.unit == Unit.SHARES: + return f"{v:,.0f}" + if f.unit == Unit.RATIO: + return f"{v:,.2f}" + return f"{v:,.2f}" + return str(v) + + +def fmt_inr(v: float) -> str: + a = abs(v) + if a >= 1_00_00_000: + return f"โ‚น{v / 1_00_00_000:,.2f} crore" + if a >= 1_00_000: + return f"โ‚น{v / 1_00_000:,.2f} lakh" + return f"โ‚น{v:,.2f}" + + +STATUS_CLASS = { + FactStatus.VERIFIED: "cite-verified", + FactStatus.DERIVED: "cite-derived", + FactStatus.UNVERIFIED: "cite-unverified", + FactStatus.CONFLICTED: "cite-conflicted", + FactStatus.ATTESTED: "cite-attested", + FactStatus.RESOLVED: "cite-resolved", +} + + +class Renderer: + """Resolves tokens against the ledger, recording exactly what it used.""" + + def __init__(self, facts: dict[str, Fact], issue: IssueTerms | None = None) -> None: + self.facts = facts + self.issue = issue + self.used: set[str] = set() + self.missing: set[str] = set() + + def _issue_value(self, key: str) -> str | None: + if not self.issue: + return None + mapping: dict[str, Any] = { + "price": fmt_inr(self.issue.price_per_share), + "face_value": fmt_inr(self.issue.face_value), + "fresh_shares": f"{self.issue.fresh_issue_shares:,.0f}", + "ofs_shares": f"{self.issue.ofs_shares:,.0f}", + "total_shares": f"{self.issue.total_issue_shares:,.0f}", + "fresh_value": fmt_inr(self.issue.fresh_issue_value), + "ofs_value": fmt_inr(self.issue.ofs_value), + "total_value": fmt_inr(self.issue.total_issue_value), + "expenses": fmt_inr(self.issue.issue_expenses), + "net_proceeds": fmt_inr(self.issue.net_proceeds), + "platform": self.issue.listing_platform, + } + v = mapping.get(key) + return str(v) if v is not None else None + + def render(self, template: str) -> str: + def fact_sub(m: re.Match[str]) -> str: + fid = m.group(1) + f = self.facts.get(fid) + if f is None: + self.missing.add(fid) + # Abstain visibly rather than invent. + return ('[not disclosed in the ' + 'source records]') + self.used.add(fid) + p = f.provenance[0] if f.provenance else None + cls = STATUS_CLASS.get(f.status, "cite-unverified") + return ( + f'' + f"{html.escape(fmt_value(f))}" + ) + + def issue_sub(m: re.Match[str]) -> str: + key = m.group(1) + v = self._issue_value(key) + if v is None: + return ('[issue term not supplied]') + return (f'{html.escape(v)}') + + out = TOKEN_RE.sub(fact_sub, template) + return ISSUE_RE.sub(issue_sub, out) + + def unbound_numbers(self, rendered_html: str) -> list[str]: + """Bare digits left in prose after rendering: each one is a PRV-001 breach. + + A cited figure is bound by definition, so `` elements are removed + WITH their contents before scanning. Statutory references ("Regulation + 229(6)", "Companies Act, 2013") and page citations ("p.39") are legal + text, not disclosure figures, and are removed too. Whatever survives is a + number that reached the page without a source: which must never happen. + """ + s = re.sub(r"]*>.*?", " ", rendered_html, flags=re.S | re.I) + s = re.sub(r"]*class=\"(?:cite-absent|prov)\"[^>]*>.*?", " ", s, + flags=re.S | re.I) + s = re.sub(r"<[^>]+>", " ", s) + for pat in ( + # statutory references + # "Regulation 23", "Regulations 236 to 239", "Reg 229(6)" + r"(?:Regulations?|Regs?\.?|Sections?|Schedules?|Clauses?|Parts?|Chapters?)\s+" + r"[\dIVXLC]+(?:\s*\([\da-z ]+\))*" + r"(?:\s*(?:to|and|,|-|โ€“)\s*[\dIVXLC]+(?:\s*\([\da-z ]+\))*)*", + r"Act,?\s*\d{4}", + r"\b(?:19|20)\d{2}\b", # years + r"\bp\.\s*\d+\b", # page citations + r"\bFY\s*\d{2,4}\b", + ): + s = re.sub(pat, " ", s, flags=re.I) + return [m.group() for m in BARE_NUMBER_RE.finditer(s)] + + +# ------------------------------------------------------------------- templates + +def _proposed(text: str, locator: str) -> str: + """Wrap a proposed-issue figure so it is cited as user input, not as a fact.""" + return (f'{html.escape(text)}') + + +def _schedule_cells(o: Any) -> str: + return "; ".join(f"{html.escape(k)}: {_proposed(fmt_inr(v), 'deployment schedule')}" + for k, v in o.schedule.items()) + + +def _objects_table(issue: IssueTerms | None) -> str: + if not issue or not issue.objects: + return "

      No objects of the issue have been supplied.

      " + rows = "".join( + f"      " + f'" + f'' + for o in issue.objects + ) + total = sum(o.amount for o in issue.objects) + return ( + '
      {html.escape(o.label)}' + f"{fmt_inr(o.amount)}{_schedule_cells(o) or "-"}
      ' + '' + f'{rows}' + f'' + f'' + f'
      Object of the issueAmountDeployment schedule
      Total{_proposed(fmt_inr(total), "sum of objects")}
      Net proceeds available{_proposed(fmt_inr(issue.net_proceeds), "gross fresh issue less issue expenses")}
      ' + ) + + +SECTIONS: list[dict[str, str]] = [ + { + "id": "general_information", + "number": "I", + "title": "General Information", + "icdr_clause": "ICDR Sch VI Pt A (I) / (IV)", + "body": """ +

      The Issuer is {{fact:co.name}}, a company incorporated in India and bearing +Corporate Identity Number {{fact:co.cin}}. The equity shares of the Issuer bear ISIN +{{fact:co.isin}} and are admitted to trading on the {{fact:co.bse_group}} group of the +BSE SME platform.

      + +

      The Issuer operates in the {{fact:co.industry}} industry within the +{{fact:co.sector}} sector. The equity shares have a face value of +{{fact:co.face_value}} each.

      + +

      The statutory auditors, the registrar to the issue, the bankers to the issue and the +lead manager are to be named by the merchant banker. PrimaryDraft does not assert these +particulars: they are not present in the source records ingested for this draft.

      +""", + }, + { + "id": "capital_structure", + "number": "II", + "title": "Capital Structure", + "icdr_clause": "ICDR Sch VI Pt A (V)", + "body": """ +

      As at the date of the latest audited balance sheet, the issued, subscribed and paid-up +equity share capital of the Issuer was {{fact:fin.current.share_capital}}, comprising +{{fact:cap.shares_outstanding}} equity shares of face value {{fact:co.face_value}} each. +This figure is derived by dividing the paid-up capital as stated in the audited balance +sheet by the face value per share recorded on the exchange master.

      + +

      The Issuer proposes a fresh issue of {{issue:fresh_shares}} equity shares at +{{issue:price}} per share, aggregating to {{issue:fresh_value}}, together with an offer +for sale of {{issue:ofs_shares}} equity shares aggregating to {{issue:ofs_value}}. The +total issue therefore comprises {{issue:total_shares}} equity shares aggregating to +{{issue:total_value}}, proposed to be listed on {{issue:platform}}.

      + +

      Estimated issue expenses of {{issue:expenses}} are to be met out of the gross proceeds +of the fresh issue, leaving net proceeds of {{issue:net_proceeds}} available to the +Issuer. The offer for sale accrues to the selling shareholders and no part of it is +received by the Issuer.

      + +

      The minimum promoter contribution, the lock-in of promoter shareholding under +Regulations 236 to 239, the history of the equity share capital and the shareholding +pattern before and after the issue must be completed by the merchant banker from the +Issuer's share register, which is not part of the records ingested for this draft.

      +""", + }, + { + "id": "objects_of_issue", + "number": "III", + "title": "Objects of the Issue", + "icdr_clause": "ICDR Sch VI Pt A (VI)", + "body": """ +

      The Issuer proposes to deploy the net proceeds of the fresh issue, being +{{issue:net_proceeds}} after meeting estimated issue expenses of {{issue:expenses}} out of +gross proceeds of {{issue:fresh_value}}, towards the objects set out below.

      + +__OBJECTS_TABLE__ + +

      The objects of the issue and the year-wise deployment schedule are proposed terms +entered by the merchant banker. PrimaryDraft reconciles the stated objects against the +net proceeds available and against the limits applicable to an SME issue, and reports any +difference. It does not itself determine the objects.

      + +

      The utilisation of the net proceeds is to be monitored in accordance with the +applicable provisions, and any deployment prior to the issue is to be certified by the +statutory auditors.

      +""", + }, + { + "id": "basis_for_issue_price", + "number": "IV", + "title": "Basis for the Issue Price", + "icdr_clause": "ICDR Sch VI Pt A (VII)", + "body": """ +

      The issue price of {{issue:price}} per equity share of face value +{{fact:co.face_value}} has been determined by the Issuer in consultation with the lead +manager. The quantitative factors set out below are drawn from the restated financial +information in this draft.

      + +

      Basic earnings per share for the latest financial year, as stated in the audited +Statement of Profit and Loss, is {{fact:fin.current.eps_basic}}. Independently computing +profit after tax of {{fact:fin.current.pat}} over {{fact:cap.shares_outstanding}} equity +shares gives {{fact:fin.current.eps_computed}} per share. The consistency engine +reconciles these two figures and reports any difference, because earnings per share is +the principal driver of the issue price.

      + +

      Net worth as at the latest balance sheet date is {{fact:fin.current.net_worth}}, giving +a net asset value of {{fact:fin.current.nav_per_share}} per equity share on a pre-issue +basis. Return on net worth for the year was {{fact:fin.current.ronw}}.

      + +

      Revenue from operations grew by {{fact:fin.revenue_growth}} over the preceding +financial year. A comparison with listed industry peers, and the qualitative factors +supporting the issue price, must be supplied by the merchant banker: peer data is market +information and is not present in the Issuer's own records.

      +""", + }, + { + "id": "financial_information", + "number": "V", + "title": "Financial Information", + "icdr_clause": "ICDR Sch VI Pt A (IX)", + "body": """ +

      The financial information set out below has been extracted from the audited financial +statements of the Issuer for the latest financial year, together with the comparative +figures for the preceding year. Every figure carries a citation to the page of the filing +from which it was read.

      + +

      Revenue from operations for the latest financial year was +{{fact:fin.current.revenue_from_operations}}, against +{{fact:fin.previous.revenue_from_operations}} in the preceding year. Other income was +{{fact:fin.current.other_income}}, giving total income of +{{fact:fin.current.total_income}}.

      + +

      Total expenses for the year were {{fact:fin.current.total_expenses}}, of which finance +costs were {{fact:fin.current.finance_costs}} and depreciation and amortisation were +{{fact:fin.current.depreciation}}. Profit before tax was {{fact:fin.current.pbt}} and +profit after tax was {{fact:fin.current.pat}}, against +{{fact:fin.previous.pat}} in the preceding year.

      + +

      As at the balance sheet date, equity share capital was +{{fact:fin.current.share_capital}} and reserves and surplus were +{{fact:fin.current.reserves_surplus}}, giving net worth of +{{fact:fin.current.net_worth}}. Total assets were {{fact:fin.current.total_assets}}, +equal to total equity and liabilities of +{{fact:fin.current.total_equity_liabilities}}.

      + +

      Earnings before interest, tax, depreciation and amortisation, derived from the +foregoing, was {{fact:fin.current.ebitda}} for the latest financial year. This figure +determines eligibility to issue on the SME platform under Regulation 229(6).

      + +

      The restated financial statements required by Schedule VI, the capitalisation +statement and the statement of financial indebtedness must be prepared by the Issuer's +auditors. This draft reproduces the audited figures as filed and does not restate +them.

      +""", + }, + { + "id": "mdna", + "number": "VI", + "title": "Management Discussion and Analysis", + "icdr_clause": "ICDR Sch VI Pt A (IX)(5)", + "body": """ +

      Revenue from operations for the latest financial year was +{{fact:fin.current.revenue_from_operations}}, compared with +{{fact:fin.previous.revenue_from_operations}} in the preceding financial year, a movement +of {{fact:fin.revenue_growth}}.

      + +

      Profit after tax was {{fact:fin.current.pat}}, compared with +{{fact:fin.previous.pat}} in the preceding year. Finance costs of +{{fact:fin.current.finance_costs}} and depreciation and amortisation of +{{fact:fin.current.depreciation}} were charged during the year.

      + +

      The figures in this section are the same ledger facts that appear in the Financial +Information section. Where a figure is stated in more than one section of the Issuer's +own filing, the consistency engine compares every occurrence and reports any difference, +since a discrepancy between the financial statements and the management discussion is a +recurring cause of exchange observations.

      + +

      A narrative discussion of the factors affecting the results of operations, of +significant developments after the balance sheet date, and of known trends and +uncertainties, must be supplied by the Issuer's management.

      +""", + }, + { + "id": "related_party", + "number": "VII", + "title": "Related Party Transactions", + "icdr_clause": "ICDR Sch VI Pt A (IX)(3)", + "body": """ +

      The related party transactions set out below were read from the related party +disclosures in the audited financial statements. Each is tagged to the page on which it +appears.

      + +__RPT_TABLE__ + +

      Each of these items remains unverified in the disclosure ledger until the counterparty +relationship and the amount are confirmed against the audited note. PrimaryDraft +deliberately does not classify a counterparty as a promoter, a director or a group +company on the strength of a line item alone.

      +""", + }, + { + "id": "risk_factors", + "number": "VIII", + "title": "Risk Factors", + "icdr_clause": "ICDR Sch VI Pt A (II)", + "body": """ +

      The risk factors below are generated only where a specific, sourced figure in the +disclosure ledger supports them. Schedule VI requires risk factors to be specific, +quantified where possible, and ordered by materiality. A generic risk factor that is not +grounded in the Issuer's own records is not drafted here.

      + +__RISK_LIST__ + +

      The complete set of internal and external risk factors, ordered by materiality, must +be settled by the Issuer and the merchant banker. The consistency engine reports which +mandated risk-factor heads are not yet covered by this draft.

      +""", + }, + { + "id": "litigation", + "number": "IX", + "title": "Outstanding Litigation and Material Developments", + "icdr_clause": "ICDR Sch VI Pt A (X)", + "body": """ +

      Schedule VI requires disclosure of outstanding litigation against the Issuer, its +promoters, its directors and its group companies, together with outstanding dues to +creditors and any material developments since the last balance sheet date.

      + +

      The records ingested for this draft: the Issuer's filed annual report and the +exchange master: do not contain a machine-readable schedule of outstanding litigation. +PrimaryDraft therefore makes no assertion in this section. It records the gap rather than +filling it, and the ICDR coverage map reports this clause as not covered.

      + +

      The merchant banker must obtain the litigation certificate from the Issuer's legal +counsel and reconcile the count and aggregate amount of matters against the contingent +liabilities note in the audited financial statements.

      +""", + }, + { + "id": "our_business", + "number": "X", + "title": "Our Business", + "icdr_clause": "ICDR Sch VI Pt A (VIII)", + "body": """ +

      The Issuer operates in the {{fact:co.industry}} industry within the +{{fact:co.sector}} sector, as classified on the exchange master.

      + +

      Revenue from operations for the latest financial year was +{{fact:fin.current.revenue_from_operations}}. Property, plant and equipment carried in +the audited balance sheet was {{fact:fin.current.ppe}} and inventories were +{{fact:fin.current.inventories}}.

      + +

      A description of the Issuer's operations, its products and services, its properties, +its customers and suppliers, its employees and its competitive strengths must be prepared +by the Issuer. These are narrative disclosures that cannot be derived from financial +records, and PrimaryDraft does not generate them.

      +""", + }, + { + "id": "our_management", + "number": "XI", + "title": "Our Management", + "icdr_clause": "ICDR Sch VI Pt A (VIII)(5)", + "body": """ +

      The Director Identification Numbers appearing in the Issuer's filed annual report are +listed in the disclosure ledger and are reproduced in the management section of this +draft.

      + +__DIN_LIST__ + +

      The names, ages, addresses, qualifications, terms of office and remuneration of the +directors and key managerial personnel, and the details of borrowing powers and corporate +governance, must be completed by the merchant banker from the Issuer's statutory +registers. A Director Identification Number alone does not establish the identity or role +of a director, and PrimaryDraft does not infer one.

      +""", + }, + { + "id": "declaration", + "number": "XII", + "title": "Declaration", + "icdr_clause": "ICDR Sch VI Pt A (XII)(2)", + "body": """ +

      All relevant provisions of the Companies Act, 2013 and the rules made thereunder, and +the guidelines, directions and regulations issued by the Securities and Exchange Board of +India applicable to this issue, are to be complied with, and no statement made in the +offer document is to contravene those provisions.

      + +

      This draft was assembled by PrimaryDraft from the Issuer's own filed records. It is +decision-support and is not an offer document. It has not been certified by a merchant +banker, it has not been filed with any exchange or with the Securities and Exchange Board +of India, and it must not be circulated as an offer document.

      + +

      The due diligence certificate required of the merchant banker under Regulation 23, and +the declaration by the directors of the Issuer, remain the responsibility of the persons +required to give them. PrimaryDraft moves the work; it does not move the signature.

      +""", + }, +] + + +def _rpt_table(facts: dict[str, Fact]) -> str: + rows = [] + for fid, f in sorted(facts.items()): + if not fid.startswith("rpt."): + continue + p = f.provenance[0] if f.provenance else None + label = f.label.replace("Related party transaction: ", "") + rows.append( + f"{html.escape(label)}" + f'' + f"{html.escape(fmt_value(f))}" + f'{html.escape(p.locator if p else "")}' + ) + if not rows: + return ("

      No related party transactions were machine-readable in the source " + "records. This is a coverage gap and is reported as such.

      ") + return ('' + '' + + "".join(rows) + "
      TransactionAmountSource
      ") + + +def _din_list(facts: dict[str, Fact]) -> str: + dins = [f for fid, f in sorted(facts.items()) if fid.startswith("mgmt.din.")] + if not dins: + return ("

      No Director Identification Numbers were machine-readable in the source " + "records.

      ") + items = "".join( + f'
    • ' + f"DIN {html.escape(str(f.value))}
      • " + for f in dins + ) + return f"
        {items}
      " + + +def _risk_list(facts: dict[str, Fact], issue: IssueTerms | None) -> str: + """Risk factors only where a sourced figure actually supports one.""" + risks: list[str] = [] + + def val(fid: str) -> float | None: + f = facts.get(fid) + return float(f.value) if f and isinstance(f.value, (int, float)) else None + + pat = val("fin.current.pat") + if pat is not None and pat < 0: + risks.append( + "The Issuer incurred a loss of {{fact:fin.current.pat}} in the latest financial " + "year. Continued losses would erode net worth and may affect the Issuer's ability " + "to fund the objects of the issue from internal accruals.") + + ebitda = val("fin.current.ebitda") + if ebitda is not None and ebitda < 1_00_00_000: + risks.append( + "Operating profit for the latest financial year, derived as " + "{{fact:fin.current.ebitda}}, is below the threshold prescribed by Regulation " + "229(6) for eligibility to issue on the SME platform. Eligibility depends on the " + "position across three financial years and must be established by the merchant " + "banker.") + + growth = val("fin.revenue_growth") + if growth is not None and growth < 0: + risks.append( + "Revenue from operations declined by {{fact:fin.revenue_growth}} compared with the " + "preceding financial year. A sustained decline in revenue would adversely affect " + "the Issuer's results of operations and financial condition.") + + fc, pbt = val("fin.current.finance_costs"), val("fin.current.pbt") + if fc and pbt and pbt > 0 and fc > pbt * 0.5: + risks.append( + "Finance costs of {{fact:fin.current.finance_costs}} are substantial in relation " + "to profit before tax of {{fact:fin.current.pbt}}. The Issuer's results are " + "sensitive to movements in interest rates and to its level of indebtedness.") + + tr = val("fin.current.trade_receivables") + rev = val("fin.current.revenue_from_operations") + if tr and rev and tr > rev * 0.35: + risks.append( + "Trade receivables of {{fact:fin.current.trade_receivables}} are high in relation " + "to revenue from operations of {{fact:fin.current.revenue_from_operations}}. Delay " + "or default in collection would adversely affect working capital.") + + unverified = sum(1 for f in facts.values() + if f.status == FactStatus.UNVERIFIED and f.is_load_bearing) + if unverified: + risks.append( + "A number of figures in this draft were read from a single location in the " + "Issuer's records with no corroborating source. They are marked unverified in the " + "disclosure ledger and must be confirmed by the merchant banker before filing.") + + if issue and issue.objects: + risks.append( + "The objects of the issue, aggregating to {{issue:net_proceeds}} of net proceeds, " + "have not been appraised by any bank or financial institution and are based on " + "management estimates. Deployment is subject to change.") + + if not risks: + return ("

      No risk factor in this draft is supported by a specific sourced figure. " + "The full set must be settled by the Issuer and the merchant banker.

      ") + return "
        " + "".join(f"
      1. {r}
        2. " for r in risks) + "
      " + + +def build_sections(facts: dict[str, Fact], issue: IssueTerms | None = None + ) -> tuple[list[DraftSection], Renderer]: + """Render every section from the ledger, recording which facts were used.""" + r = Renderer(facts, issue) + out: list[DraftSection] = [] + + for spec in SECTIONS: + body = spec["body"] + body = body.replace("__OBJECTS_TABLE__", _objects_table(issue)) + body = body.replace("__RPT_TABLE__", _rpt_table(facts)) + body = body.replace("__DIN_LIST__", _din_list(facts)) + body = body.replace("__RISK_LIST__", _risk_list(facts, issue)) + + before = set(r.used) + rendered = r.render(body) + used_here = sorted(r.used - before) + + text = re.sub(r"<[^>]+>", "", rendered) + text = re.sub(r"\n{2,}", "\n\n", re.sub(r"[ \t]+", " ", text)).strip() + + out.append(DraftSection( + id=spec["id"], number=spec["number"], title=spec["title"], + icdr_clause=spec["icdr_clause"], html=rendered.strip(), text=text, + fact_ids=used_here, word_count=len(text.split()), + )) + return out, r diff --git a/app/backend/primarydraft/engine/__init__.py b/app/backend/primarydraft/engine/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/app/backend/primarydraft/engine/icdr.py b/app/backend/primarydraft/engine/icdr.py new file mode 100644 index 0000000000000000000000000000000000000000..d125bd9c3aae0042b27738cb66c75001a17509af --- /dev/null +++ b/app/backend/primarydraft/engine/icdr.py @@ -0,0 +1,161 @@ +"""SEBI (ICDR) Regulations, 2018: Schedule VI Part A, as a machine-readable map. + +Schedule VI applies to SME issues through Regulation 246. This module encodes the +disclosure structure so coverage can be *measured* rather than asserted, and so a +gap is reported as a gap instead of being quietly omitted. + +Also encodes the numeric thresholds the engine tests against, including the +8 March 2025 SME amendments (OFS cap, general-corporate-purposes cap). +""" + +from __future__ import annotations + +from dataclasses import dataclass + + +@dataclass(frozen=True) +class Clause: + id: str + clause: str # citation as it appears in the regulation + title: str + part: str + section_id: str | None # draft section that discharges it, if we draft it + mandatory: bool = True + + +# --------------------------------------------------------------------- clause map + +CLAUSES: list[Clause] = [ + # (I) Cover pages + Clause("cover.front", "Sch VI Pt A (I)(A)", "Front cover page", "Introductory", "general_information"), + Clause("cover.issuer", "Sch VI Pt A (I)(A)(1)", "Name, CIN, registered office and contact details", "Introductory", "general_information"), + Clause("cover.promoters", "Sch VI Pt A (I)(A)(3)", "Names of the promoters", "Introductory", "promoters"), + Clause("cover.issue", "Sch VI Pt A (I)(A)(5)", "Nature, size and price of the issue", "Introductory", "capital_structure"), + Clause("cover.lm", "Sch VI Pt A (I)(A)(9)", "Lead manager and registrar details", "Introductory", None), + Clause("cover.listing", "Sch VI Pt A (I)(A)(11)", "Proposed listing platform", "Introductory", "general_information"), + + # (II) Risk factors + Clause("risk.internal", "Sch VI Pt A (II)(1)", "Internal risk factors", "Risk Factors", "risk_factors"), + Clause("risk.external", "Sch VI Pt A (II)(2)", "External risk factors", "Risk Factors", "risk_factors"), + Clause("risk.materiality", "Sch VI Pt A (II)(3)", "Risk factors ordered by materiality with quantification", "Risk Factors", "risk_factors"), + Clause("risk.litigation", "Sch VI Pt A (II)(4)", "Risk factors for outstanding litigation", "Risk Factors", "risk_factors"), + + # (III) Introduction + Clause("intro.summary", "Sch VI Pt A (III)(1)", "Summary of the offer document", "Introduction", "general_information"), + Clause("intro.definitions", "Sch VI Pt A (III)(2)", "Definitions and abbreviations", "Introduction", None), + Clause("intro.presentation", "Sch VI Pt A (III)(3)", "Presentation of financial and market data", "Introduction", "financial_information"), + Clause("intro.forward", "Sch VI Pt A (III)(4)", "Forward-looking statements", "Introduction", None), + + # General information + Clause("gen.registered", "Sch VI Pt A (IV)(1)", "Registered and corporate office", "General Information", "general_information"), + Clause("gen.board", "Sch VI Pt A (IV)(2)", "Board of directors", "General Information", "our_management"), + Clause("gen.cs", "Sch VI Pt A (IV)(3)", "Company secretary and compliance officer", "General Information", "our_management"), + Clause("gen.auditors", "Sch VI Pt A (IV)(5)", "Statutory auditors", "General Information", "general_information"), + Clause("gen.bankers", "Sch VI Pt A (IV)(6)", "Bankers to the issue and to the company", "General Information", None), + + # Capital structure + Clause("cap.share_capital", "Sch VI Pt A (V)(1)", "Share capital: authorised, issued, subscribed and paid-up", "Capital Structure", "capital_structure"), + Clause("cap.history", "Sch VI Pt A (V)(2)", "History of the equity share capital", "Capital Structure", "capital_structure"), + Clause("cap.shareholding", "Sch VI Pt A (V)(3)", "Shareholding pattern: pre-issue and post-issue", "Capital Structure", "capital_structure"), + Clause("cap.promoter_holding", "Sch VI Pt A (V)(4)", "Promoter and promoter group shareholding", "Capital Structure", "promoters"), + Clause("cap.mpc", "Sch VI Pt A (V)(5)", "Minimum promoter contribution and lock-in", "Capital Structure", "capital_structure"), + Clause("cap.waca", "Sch VI Pt A (V)(6)", "Weighted average cost of acquisition of promoter shares", "Capital Structure", None), + Clause("cap.top10", "Sch VI Pt A (V)(8)", "Top ten shareholders", "Capital Structure", None), + + # Objects of the issue + Clause("obj.objects", "Sch VI Pt A (VI)(1)", "Objects of the issue", "Objects", "objects_of_issue"), + Clause("obj.proceeds", "Sch VI Pt A (VI)(2)", "Gross proceeds, issue expenses and net proceeds", "Objects", "objects_of_issue"), + Clause("obj.schedule", "Sch VI Pt A (VI)(3)", "Means of finance and year-wise deployment schedule", "Objects", "objects_of_issue"), + Clause("obj.gcp", "Sch VI Pt A (VI)(4)", "General corporate purposes: limit and disclosure", "Objects", "objects_of_issue"), + Clause("obj.monitoring", "Sch VI Pt A (VI)(5)", "Monitoring of utilisation of proceeds", "Objects", "objects_of_issue"), + Clause("obj.interest", "Sch VI Pt A (VI)(6)", "Interest of promoters and directors in the objects", "Objects", None), + + # Basis for issue price + Clause("price.qualitative", "Sch VI Pt A (VII)(1)", "Qualitative factors for the issue price", "Basis for Issue Price", "basis_for_issue_price"), + Clause("price.quantitative", "Sch VI Pt A (VII)(2)", "Quantitative factors: EPS, P/E, RoNW, NAV", "Basis for Issue Price", "basis_for_issue_price"), + Clause("price.peer", "Sch VI Pt A (VII)(3)", "Comparison with listed industry peers", "Basis for Issue Price", "basis_for_issue_price"), + Clause("price.justification", "Sch VI Pt A (VII)(4)", "Justification of the issue price", "Basis for Issue Price", "basis_for_issue_price"), + + # About the issuer + Clause("biz.industry", "Sch VI Pt A (VIII)(1)", "Industry overview", "About the Issuer", "our_business"), + Clause("biz.business", "Sch VI Pt A (VIII)(2)", "Business of the issuer", "About the Issuer", "our_business"), + Clause("biz.regulations", "Sch VI Pt A (VIII)(3)", "Key industry regulations", "About the Issuer", None), + Clause("biz.history", "Sch VI Pt A (VIII)(4)", "History and corporate structure", "About the Issuer", "our_business"), + Clause("biz.management", "Sch VI Pt A (VIII)(5)", "Our management", "About the Issuer", "our_management"), + Clause("biz.promoters", "Sch VI Pt A (VIII)(6)", "Our promoters and promoter group", "About the Issuer", "promoters"), + Clause("biz.group", "Sch VI Pt A (VIII)(7)", "Group companies", "About the Issuer", None), + Clause("biz.dividend", "Sch VI Pt A (VIII)(8)", "Dividend policy", "About the Issuer", "financial_information"), + + # Financial information + Clause("fin.restated", "Sch VI Pt A (IX)(1)", "Restated financial statements", "Financial Information", "financial_information"), + Clause("fin.accounting", "Sch VI Pt A (IX)(2)", "Significant accounting policies and notes", "Financial Information", "financial_information"), + Clause("fin.rpt", "Sch VI Pt A (IX)(3)", "Related party transactions", "Financial Information", "related_party"), + Clause("fin.capitalisation", "Sch VI Pt A (IX)(4)", "Capitalisation statement", "Financial Information", "financial_information"), + Clause("fin.mdna", "Sch VI Pt A (IX)(5)", "Management discussion and analysis", "Financial Information", "mdna"), + Clause("fin.indebtedness", "Sch VI Pt A (IX)(6)", "Statement of financial indebtedness", "Financial Information", "financial_information"), + + # Legal and other information + Clause("legal.litigation", "Sch VI Pt A (X)(1)", "Outstanding litigation and material developments", "Legal", "litigation"), + Clause("legal.dues", "Sch VI Pt A (X)(2)", "Outstanding dues to creditors", "Legal", "litigation"), + Clause("legal.approvals", "Sch VI Pt A (X)(3)", "Government and other statutory approvals", "Legal", None), + Clause("legal.other", "Sch VI Pt A (X)(4)", "Other regulatory and statutory disclosures", "Legal", None), + + # Offering and other information + Clause("offer.terms", "Sch VI Pt A (XI)(1)", "Terms of the issue", "Offering Information", "capital_structure"), + Clause("offer.structure", "Sch VI Pt A (XI)(2)", "Issue structure", "Offering Information", "capital_structure"), + Clause("offer.procedure", "Sch VI Pt A (XI)(3)", "Issue procedure", "Offering Information", None), + Clause("other.contracts", "Sch VI Pt A (XII)(1)", "Material contracts and documents for inspection", "Other Information", None), + Clause("other.declaration", "Sch VI Pt A (XII)(2)", "Declaration", "Other Information", "declaration"), +] + +CLAUSE_BY_ID = {c.id: c for c in CLAUSES} + + +# ------------------------------------------------------------------- thresholds + +class Thresholds: + """Numeric limits the deterministic engine tests against.""" + + #: Reg 229(6): SME issuer operating-profit (EBITDA) eligibility. + SME_MIN_EBITDA_INR = 1_00_00_000 # โ‚น1 crore + SME_MIN_EBITDA_YEARS = 2 # in 2 of the last 3 financial years + SME_EBITDA_LOOKBACK = 3 + + #: ICDR amendment effective 8 March 2025: offer for sale cap for SME IPOs. + SME_MAX_OFS_PCT_OF_ISSUE = 20.0 + + #: ICDR amendment effective 8 March 2025: general corporate purposes cap. + SME_MAX_GCP_PCT_OF_PROCEEDS = 15.0 + SME_MAX_GCP_ABSOLUTE_INR = 10_00_00_000 # โ‚น10 crore + + #: Reg 236: minimum promoter contribution, and Reg 238/239 lock-in. + MIN_PROMOTER_CONTRIBUTION_PCT = 20.0 + MPC_LOCK_IN_YEARS = 3 + PROMOTER_EXCESS_LOCK_IN_YEARS = 1 + + #: Reg 229(1): SME platform post-issue paid-up capital ceiling. + SME_MAX_POST_ISSUE_CAPITAL_INR = 25_00_00_000 # โ‚น25 crore + + #: Tolerance for comparing two printings of the same figure (rounding). + REL_TOL = 0.005 + #: Tolerance for derived arithmetic (EPS, NAV) against a printed figure. + DERIVED_TOL = 0.02 + + +def coverage_for(drafted_section_ids: set[str]) -> list[dict[str, object]]: + """Measure Schedule VI coverage against the sections we actually drafted.""" + out: list[dict[str, object]] = [] + for c in CLAUSES: + covered = bool(c.section_id and c.section_id in drafted_section_ids) + out.append({ + "clause_id": c.id, + "clause": c.clause, + "title": c.title, + "part": c.part, + "covered": covered, + "section_id": c.section_id, + "reason": ("" if covered else + "Not drafted by this prototype: deliberately out of the 7 deep " + "sections; the merchant banker supplies it."), + }) + return out diff --git a/app/backend/primarydraft/engine/rules.py b/app/backend/primarydraft/engine/rules.py new file mode 100644 index 0000000000000000000000000000000000000000..97253ae1d964f1645aaa7b81f131c3559c14d863 --- /dev/null +++ b/app/backend/primarydraft/engine/rules.py @@ -0,0 +1,1106 @@ +"""The deterministic consistency engine. + +There is no LLM in this module and there never will be: `tests/test_no_llm.py` +asserts it at the import level. Every verdict here is plain, auditable Python that +a regulator can read. + +Rules operate on two inputs: + * the Disclosure Ledger, built from the company's REAL filed annual report + * the proposed issue terms, which the merchant banker enters (real user input) + +Nothing is seeded. If a rule fires, it fires because the real numbers disagree. +""" + +from __future__ import annotations + +from typing import Any, Callable + +from ..models import ( + Evidence, + Fact, + FactStatus, + Finding, + Resolution, + RuleResult, + Severity, + Unit, +) +from .icdr import Thresholds as T + +Ctx = dict[str, Any] +RuleFn = Callable[[dict[str, Fact], Ctx], RuleResult] + +REGISTRY: list[tuple[str, str, str, RuleFn]] = [] + + +def rule(rule_id: str, title: str, icdr_ref: str = "") -> Callable[[RuleFn], RuleFn]: + def deco(fn: RuleFn) -> RuleFn: + REGISTRY.append((rule_id, title, icdr_ref, fn)) + return fn + return deco + + +# ------------------------------------------------------------------- utilities + +def fmt_inr(v: float | None) -> str: + """Format rupees the way an Indian offer document does.""" + if v is None: + return "n/a" + a = abs(v) + if a >= 1_00_00_000: + return f"โ‚น{v / 1_00_00_000:,.2f} crore" + if a >= 1_00_000: + return f"โ‚น{v / 1_00_000:,.2f} lakh" + return f"โ‚น{v:,.2f}" + + +def fmt(f: Fact | None) -> str: + if f is None: + return "-" + if f.unit == Unit.INR: + return fmt_inr(_num(f)) + if f.unit == Unit.PCT: + return f"{_num(f):.2f}%" if _num(f) is not None else "-" + if f.unit in (Unit.RATIO,): + return f"{_num(f):,.2f}" if _num(f) is not None else "-" + if f.unit == Unit.SHARES: + n = _num(f) + return f"{n:,.0f} shares" if n is not None else "-" + return str(f.value) + + +def _num(f: Fact | None) -> float | None: + if f is None or not isinstance(f.value, (int, float)): + return None + return float(f.value) + + +def g(facts: dict[str, Fact], fid: str) -> Fact | None: + return facts.get(fid) + + +def gv(facts: dict[str, Fact], fid: str) -> float | None: + return _num(facts.get(fid)) + + +def close(a: float, b: float, tol: float = T.REL_TOL) -> bool: + return abs(a - b) <= tol * max(abs(a), abs(b), 1.0) + + +def ev(facts: dict[str, Fact], fid: str, label: str | None = None) -> Evidence | None: + f = facts.get(fid) + if f is None: + return None + p = f.provenance[0] if f.provenance else None + return Evidence( + label=label or f.label, + value=f.value, + display=fmt(f), + fact_id=fid, + section=(p.section if p else ""), + locator=(p.locator if p else ""), + raw_line=(p.raw_line if p else ""), + ) + + +TRUSTED = (FactStatus.VERIFIED, FactStatus.DERIVED, FactStatus.ATTESTED, + FactStatus.RESOLVED) + + +def trusted(facts: dict[str, Fact], ids: list[str]) -> bool: + """Whether every input to a check is a figure the ledger actually trusts.""" + return all((f := facts.get(i)) is not None and f.status in TRUSTED for i in ids) + + +def temper(facts: dict[str, Fact], ids: list[str], severity: Severity, + explanation: str) -> tuple[Severity, str]: + """Soften a verdict whose own inputs are not trusted. + + A contradiction is only a contradiction between figures we are confident we + read correctly. Where an input is itself unverified, the honest finding is + "these do not reconcile and at least one of them is unconfirmed", not + "the issuer has contradicted itself". Asserting the latter on a shaky read + would be exactly the overreach this tool exists to avoid. + """ + if trusted(facts, ids): + return severity, explanation + weak = [facts[i].label for i in ids + if i in facts and facts[i].status not in TRUSTED] + softened = Severity.MEDIUM if severity == Severity.BLOCKER else severity + return softened, ( + explanation + " This figure could not be independently corroborated in the " + "filing (" + "; ".join(weak[:3]) + "), so the difference may be a limitation of " + "what was machine-readable rather than an error by the issuer. It is reported " + "for confirmation, not asserted as a contradiction." + ) + + +def ok(rid: str, title: str, ref: str, detail: str) -> RuleResult: + return RuleResult(rule_id=rid, title=title, icdr_ref=ref, status="pass", detail=detail) + + +def na(rid: str, title: str, ref: str, detail: str) -> RuleResult: + return RuleResult(rule_id=rid, title=title, icdr_ref=ref, status="not_applicable", + detail=detail) + + +def fail(rid: str, title: str, ref: str, detail: str, findings: list[Finding]) -> RuleResult: + return RuleResult(rule_id=rid, title=title, icdr_ref=ref, status="fail", detail=detail, + findings=findings) + + +# =============================================================== FIN: financials + +@rule("FIN-001", "Revenue is stated identically in every section that reports it", + "ICDR Sch VI Pt A (IX)(1) / (IX)(5)") +def fin_001(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid, title, ref = "FIN-001", fin_001.__doc__ or "", "" + return _cross_section_agreement( + facts, "fin.current.revenue_from_operations", "FIN-001", + "Revenue is stated identically in every section that reports it", + "ICDR Sch VI Pt A (IX)(1) / (IX)(5)", + "Revenue from operations", + ) + + +@rule("FIN-002", "Profit after tax ties across the audited statement and the Directors' Report", + "ICDR Sch VI Pt A (IX)(1)") +def fin_002(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + return _cross_section_agreement( + facts, "fin.current.pat", "FIN-002", + "Profit after tax ties across the audited statement and the Directors' Report", + "ICDR Sch VI Pt A (IX)(1)", "Profit after tax", + ) + + +def _cross_section_agreement(facts: dict[str, Fact], fid: str, rid: str, title: str, + ref: str, what: str) -> RuleResult: + """A figure printed in two independent sections must agree in both.""" + f = facts.get(fid) + if f is None: + return na(rid, title, ref, f"{what} was not machine-readable in this filing.") + + sections = {p.section: p for p in f.provenance} + if f.status == FactStatus.CONFLICTED: + evs = [ + Evidence(label=f"{what}: {p.section.replace('_', ' ')}", value=f.value, + display=p.raw_line.strip()[:160] or fmt(f), fact_id=fid, + section=p.section, locator=p.locator, raw_line=p.raw_line) + for p in f.provenance + ] + return fail(rid, title, ref, f"{what} is not consistent across sections.", [ + Finding( + rule_id=rid, severity=Severity.BLOCKER, + title=f"{what} differs between two sections of the same filing", + explanation=(f.note or f"{what} is reported differently in two places."), + icdr_ref=ref, evidence=evs, fact_ids=[fid], + resolutions=[ + Resolution(id="adopt_audited", label="Adopt the audited financial statements", + description=("Treat the audited Statement of Profit and Loss as " + "authoritative and restate the other section."), + recommended=True, kind="adopt_value", target_fact_id=fid, + justification="Audited statements carry the auditor's opinion."), + Resolution(id="flag", label="Refer to the merchant banker", + description="Record the discrepancy for the banker to reconcile.", + kind="flag_to_banker"), + ], + ) + ]) + + if len(sections) > 1: + where = " and ".join(sorted(s.replace("_", " ") for s in sections)) + return ok(rid, title, ref, + f"{what} = {fmt(f)}, identical in {where}.") + return ok(rid, title, ref, + f"{what} = {fmt(f)}; found in one section only, no contradiction present.") + + +@rule("FIN-003", "Balance sheet balances: total assets equal total equity and liabilities", + "ICDR Sch VI Pt A (IX)(1)") +def fin_003(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid, title = "FIN-003", "Balance sheet balances: total assets equal total equity and liabilities" + ref = "ICDR Sch VI Pt A (IX)(1)" + ta, tel = gv(facts, "fin.current.total_assets"), gv(facts, "fin.current.total_equity_liabilities") + if ta is None or tel is None: + return na(rid, title, ref, "Balance sheet totals were not machine-readable.") + if close(ta, tel): + return ok(rid, title, ref, f"Both sides total {fmt_inr(ta)}.") + return fail(rid, title, ref, "The balance sheet does not balance.", [ + Finding( + rule_id=rid, + severity=temper(facts, ["fin.current.total_assets", + "fin.current.total_equity_liabilities"], + Severity.BLOCKER, "")[0], + title="Balance sheet does not balance", + explanation=temper( + facts, ["fin.current.total_assets", "fin.current.total_equity_liabilities"], + Severity.BLOCKER, + "Total assets and total equity and liabilities must be equal. " + f"They differ by {fmt_inr(abs(ta - tel))}.")[1], + icdr_ref=ref, delta=fmt_inr(abs(ta - tel)), + evidence=[e for e in (ev(facts, "fin.current.total_assets"), + ev(facts, "fin.current.total_equity_liabilities")) if e], + fact_ids=["fin.current.total_assets", "fin.current.total_equity_liabilities"], + resolutions=[Resolution(id="flag", label="Refer to the merchant banker", + description="A balance-sheet imbalance must be resolved " + "against the audited statements.", + recommended=True, kind="flag_to_banker")], + ) + ]) + + +@rule("FIN-004", "Basic EPS equals profit after tax divided by shares outstanding", + "ICDR Sch VI Pt A (IX)(1) / (VII)(2)") +def fin_004(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid = "FIN-004" + title = "Basic EPS equals profit after tax divided by shares outstanding" + ref = "ICDR Sch VI Pt A (IX)(1) / (VII)(2)" + printed, computed = gv(facts, "fin.current.eps_basic"), gv(facts, "fin.current.eps_computed") + if printed is None or computed is None: + return na(rid, title, ref, "EPS or the share count was not machine-readable.") + if close(printed, computed, T.DERIVED_TOL): + return ok(rid, title, ref, + f"EPS as printed ({printed:,.2f}) reconciles to profit after tax " + f"divided by shares outstanding ({computed:,.2f}).") + # A near-exact power of ten between the two is the signature of a scale error: + # a figure printed under a "โ‚น in thousands" heading that does not apply to it. + hint = "" + if printed and computed and (computed / printed) > 0: + import math + + lg = math.log10(computed / printed) + exp = round(lg) + if exp != 0 and abs(lg - exp) < 0.05: + hint = (f" The two differ by almost exactly a factor of {10 ** abs(exp):,}, " + "which usually means one of them was printed under a scale heading " + "that does not apply to it (a share count under a 'โ‚น in thousands' " + "banner is the common case).") + return fail(rid, title, ref, "EPS does not reconcile to profit after tax and share count.", [ + Finding( + rule_id=rid, + severity=temper(facts, ["fin.current.eps_basic", "fin.current.pat", + "cap.shares_outstanding"], Severity.HIGH, "")[0], + title="Earnings per share does not reconcile to the underlying figures", + explanation=( + f"The filing prints basic EPS of {printed:,.2f}. Profit after tax divided by " + f"closing shares outstanding gives {computed:,.2f}." + hint + + " A modest difference is expected where shares were issued during the year, " + "because basic EPS is struck on the weighted average number of shares while " + "this computation uses the closing count. In an offer document EPS drives the " + "Basis for Issue Price, so the weighted average share count must be disclosed " + "and the two reconciled." + ), + icdr_ref=ref, delta=f"{abs(printed - computed):,.2f} per share", + evidence=[e for e in (ev(facts, "fin.current.eps_basic", "Basic EPS as printed"), + ev(facts, "fin.current.eps_computed", "EPS computed from PAT รท shares"), + ev(facts, "fin.current.pat"), + ev(facts, "cap.shares_outstanding")) if e], + fact_ids=["fin.current.eps_basic", "fin.current.eps_computed"], + resolutions=[ + Resolution(id="adopt_computed", label="Adopt the computed EPS", + description=("Use profit after tax divided by shares outstanding, " + "both of which are themselves sourced facts."), + recommended=True, kind="adopt_value", + target_fact_id="fin.current.eps_basic", new_value=round(computed, 2), + justification="Derived from two independently sourced ledger facts."), + Resolution(id="flag", label="Refer to the merchant banker", + description="Reconcile the share count and EPS against the audited " + "statements before filing.", kind="flag_to_banker"), + ], + ) + ]) + + +@rule("FIN-005", "Net worth equals equity share capital plus reserves and surplus", + "ICDR Sch VI Pt A (IX)(1)") +def fin_005(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid = "FIN-005" + title = "Net worth equals equity share capital plus reserves and surplus" + ref = "ICDR Sch VI Pt A (IX)(1)" + sc, rs = gv(facts, "fin.current.share_capital"), gv(facts, "fin.current.reserves_surplus") + nw = gv(facts, "fin.current.net_worth") + if None in (sc, rs, nw): + return na(rid, title, ref, "Share capital or reserves were not machine-readable.") + if close(sc + rs, nw): # type: ignore[operator] + return ok(rid, title, ref, f"Net worth {fmt_inr(nw)} = share capital {fmt_inr(sc)} " + f"+ reserves {fmt_inr(rs)}.") + return fail(rid, title, ref, "Net worth does not reconcile.", [ + Finding(rule_id=rid, severity=Severity.HIGH, title="Net worth does not reconcile", + explanation="Net worth must equal equity share capital plus reserves and surplus.", + icdr_ref=ref, + evidence=[e for e in (ev(facts, "fin.current.share_capital"), + ev(facts, "fin.current.reserves_surplus"), + ev(facts, "fin.current.net_worth")) if e], + fact_ids=["fin.current.net_worth"]) + ]) + + +@rule("FIN-006", "Total income equals revenue from operations plus other income", + "ICDR Sch VI Pt A (IX)(1)") +def fin_006(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid, title = "FIN-006", "Total income equals revenue from operations plus other income" + ref = "ICDR Sch VI Pt A (IX)(1)" + rev, oi = gv(facts, "fin.current.revenue_from_operations"), gv(facts, "fin.current.other_income") + ti = gv(facts, "fin.current.total_income") + if None in (rev, oi, ti): + return na(rid, title, ref, "Income lines were not machine-readable.") + if close(rev + oi, ti): # type: ignore[operator] + return ok(rid, title, ref, f"{fmt_inr(rev)} + {fmt_inr(oi)} = {fmt_inr(ti)}.") + ids = ["fin.current.revenue_from_operations", "fin.current.other_income", + "fin.current.total_income"] + sev, expl = temper(facts, ids, Severity.BLOCKER, + "Revenue from operations plus other income must equal total income; " + f"they differ by {fmt_inr(abs(rev + oi - ti))}.") # type: ignore[operator] + return fail(rid, title, ref, "Total income does not foot.", [ + Finding(rule_id=rid, severity=sev, title="Total income does not foot", + explanation=expl, + icdr_ref=ref, delta=fmt_inr(abs(rev + oi - ti)), # type: ignore[operator] + evidence=[e for e in (ev(facts, "fin.current.revenue_from_operations"), + ev(facts, "fin.current.other_income"), + ev(facts, "fin.current.total_income")) if e], + fact_ids=["fin.current.total_income"]) + ]) + + +@rule("FIN-007", "Profit before tax equals total income less total expenses", + "ICDR Sch VI Pt A (IX)(1)") +def fin_007(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid, title = "FIN-007", "Profit before tax equals total income less total expenses" + ref = "ICDR Sch VI Pt A (IX)(1)" + ti, te = gv(facts, "fin.current.total_income"), gv(facts, "fin.current.total_expenses") + pbt = gv(facts, "fin.current.pbt") + if None in (ti, te, pbt): + return na(rid, title, ref, "Income or expense totals were not machine-readable.") + if close(ti - abs(te), pbt): # type: ignore[operator] + return ok(rid, title, ref, f"{fmt_inr(ti)} โˆ’ {fmt_inr(abs(te))} = {fmt_inr(pbt)}.") + ids7 = ["fin.current.total_income", "fin.current.total_expenses", "fin.current.pbt"] + sev7, expl7 = temper(facts, ids7, Severity.BLOCKER, + "Total income less total expenses must equal profit before tax.") + return fail(rid, title, ref, "Profit before tax does not foot.", [ + Finding(rule_id=rid, severity=sev7, + title="Profit before tax does not foot", + explanation=expl7, + icdr_ref=ref, delta=fmt_inr(abs(ti - abs(te) - pbt)), # type: ignore[operator] + evidence=[e for e in (ev(facts, "fin.current.total_income"), + ev(facts, "fin.current.total_expenses"), + ev(facts, "fin.current.pbt")) if e], + fact_ids=["fin.current.pbt"]) + ]) + + +@rule("FIN-008", "EPS in the filing agrees with the EPS published on the exchange", + "cross-source corroboration") +def fin_008(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid = "FIN-008" + title = "EPS in the filing agrees with the EPS published on the exchange" + ref = "cross-source corroboration" + filed, bse = gv(facts, "fin.current.eps_basic"), gv(facts, "co.eps_bse") + if filed is None or bse is None or bse == 0: + return na(rid, title, ref, "One of the two EPS figures is unavailable.") + if close(filed, bse, 0.10): + return ok(rid, title, ref, f"Filing EPS {filed:,.2f} agrees with BSE-published " + f"EPS {bse:,.2f}.") + return fail(rid, title, ref, "Filing EPS differs from the exchange-published EPS.", [ + Finding(rule_id=rid, severity=Severity.MEDIUM, + title="EPS in the annual report differs from the EPS published by BSE", + explanation=(f"The annual report prints {filed:,.2f}; BSE publishes {bse:,.2f}. " + "These are two independent sources for the same measure. The " + "difference is often a period or consolidation mismatch, but it " + "must be explained in the Basis for Issue Price."), + icdr_ref="ICDR Sch VI Pt A (VII)(2)", + delta=f"{abs(filed - bse):,.2f} per share", + evidence=[e for e in (ev(facts, "fin.current.eps_basic", "EPS: annual report"), + ev(facts, "co.eps_bse", "EPS: BSE published")) if e], + fact_ids=["fin.current.eps_basic", "co.eps_bse"], + resolutions=[Resolution(id="attest", label="Attest the difference is periodic", + description="Record that the difference arises from " + "differing reporting periods.", + kind="attest", target_fact_id="co.eps_bse")]) + ]) + + +# ======================================================= CAP: capital structure + +@rule("CAP-001", "Paid-up capital equals shares outstanding times face value", + "ICDR Sch VI Pt A (V)(1)") +def cap_001(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid, title = "CAP-001", "Paid-up capital equals shares outstanding times face value" + ref = "ICDR Sch VI Pt A (V)(1)" + sc, fv = gv(facts, "fin.current.share_capital"), gv(facts, "co.face_value") + sh = gv(facts, "cap.shares_outstanding") + if None in (sc, fv, sh) or not fv: + return na(rid, title, ref, "Share capital or face value unavailable.") + if close(sh * fv, sc): # type: ignore[operator] + return ok(rid, title, ref, + f"{sh:,.0f} shares ร— {fmt_inr(fv)} = {fmt_inr(sc)}.") # type: ignore[str-format] + return fail(rid, title, ref, "Paid-up capital does not reconcile.", [ + Finding(rule_id=rid, severity=Severity.HIGH, title="Paid-up capital does not reconcile", + explanation="Shares outstanding multiplied by face value must equal paid-up capital.", + icdr_ref=ref, fact_ids=["cap.shares_outstanding"], + evidence=[e for e in (ev(facts, "fin.current.share_capital"), + ev(facts, "co.face_value"), + ev(facts, "cap.shares_outstanding")) if e]) + ]) + + +@rule("CAP-002", "Post-issue paid-up capital reconciles to the proposed fresh issue", + "ICDR Sch VI Pt A (V)(1)") +def cap_002(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid = "CAP-002" + title = "Post-issue paid-up capital reconciles to the proposed fresh issue" + ref = "ICDR Sch VI Pt A (V)(1)" + issue = ctx.get("issue") + sc, fv = gv(facts, "fin.current.share_capital"), gv(facts, "co.face_value") + if not issue or None in (sc, fv): + return na(rid, title, ref, "No proposed issue terms supplied.") + post = sc + issue.fresh_issue_shares * fv # type: ignore[operator] + return ok(rid, title, ref, + f"Pre-issue {fmt_inr(sc)} + {issue.fresh_issue_shares:,.0f} fresh shares ร— " + f"{fmt_inr(fv)} = post-issue {fmt_inr(post)}.") + + +# ================================================== ELG: SME issuer eligibility + +@rule("ELG-001", "Operating profit meets the SME issuer eligibility threshold", + "ICDR Reg 229(6)") +def elg_001(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid = "ELG-001" + title = "Operating profit meets the SME issuer eligibility threshold" + ref = "ICDR Reg 229(6)" + ebitda = gv(facts, "fin.current.ebitda") + if ebitda is None: + return na(rid, title, ref, + "EBITDA could not be derived from the machine-readable statements.") + if ebitda >= T.SME_MIN_EBITDA_INR: + return ok(rid, title, ref, + f"Operating profit (EBITDA) of {fmt_inr(ebitda)} for the latest year " + f"exceeds the {fmt_inr(T.SME_MIN_EBITDA_INR)} threshold. Regulation 229(6) " + f"requires this in {T.SME_MIN_EBITDA_YEARS} of the last " + f"{T.SME_EBITDA_LOOKBACK} financial years; only the latest year is " + "machine-readable from this filing.") + return fail(rid, title, ref, "Operating profit is below the SME eligibility threshold.", [ + Finding(rule_id=rid, severity=Severity.BLOCKER, + title="Operating profit is below the Regulation 229(6) eligibility threshold", + explanation=( + f"Regulation 229(6) requires operating profit (EBITDA) of at least " + f"{fmt_inr(T.SME_MIN_EBITDA_INR)} in {T.SME_MIN_EBITDA_YEARS} of the last " + f"{T.SME_EBITDA_LOOKBACK} financial years. The latest year derives to " + f"{fmt_inr(ebitda)}. On this evidence the issuer does not appear eligible " + "for the SME platform without relying on earlier years."), + icdr_ref=ref, delta=fmt_inr(T.SME_MIN_EBITDA_INR - ebitda), + evidence=[e for e in (ev(facts, "fin.current.ebitda"), + ev(facts, "fin.current.pbt"), + ev(facts, "fin.current.finance_costs"), + ev(facts, "fin.current.depreciation")) if e], + fact_ids=["fin.current.ebitda"], + resolutions=[Resolution(id="flag", label="Refer to the merchant banker", + description="Eligibility must be established across " + "three years of restated financials.", + recommended=True, kind="flag_to_banker")]) + ]) + + +@rule("ELG-002", "Offer for sale is within the SME cap of 20% of the issue", + "ICDR amendment effective 8 March 2025") +def elg_002(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid, title = "ELG-002", "Offer for sale is within the SME cap of 20% of the issue" + ref = "ICDR amendment effective 8 March 2025" + issue = ctx.get("issue") + if not issue or not issue.total_issue_value: + return na(rid, title, ref, "No proposed issue terms supplied.") + pct = 100.0 * issue.ofs_value / issue.total_issue_value + if pct <= T.SME_MAX_OFS_PCT_OF_ISSUE: + return ok(rid, title, ref, + f"Offer for sale is {fmt_inr(issue.ofs_value)}, {pct:.2f}% of the " + f"{fmt_inr(issue.total_issue_value)} issue: within the " + f"{T.SME_MAX_OFS_PCT_OF_ISSUE:.0f}% cap.") + return fail(rid, title, ref, "Offer for sale exceeds the 20% cap.", [ + Finding(rule_id=rid, severity=Severity.BLOCKER, + title="Offer for sale exceeds 20% of the total issue size", + explanation=( + f"The March 2025 amendment caps the offer-for-sale component of an SME IPO " + f"at {T.SME_MAX_OFS_PCT_OF_ISSUE:.0f}% of the total issue size. The proposed " + f"offer for sale of {fmt_inr(issue.ofs_value)} is {pct:.2f}% of the " + f"{fmt_inr(issue.total_issue_value)} issue."), + icdr_ref=ref, + delta=f"{pct - T.SME_MAX_OFS_PCT_OF_ISSUE:.2f} percentage points over", + evidence=[ + Evidence(label="Proposed offer for sale", value=issue.ofs_value, + display=fmt_inr(issue.ofs_value), section="issue_terms", + locator="proposed issue terms"), + Evidence(label="Total issue size", value=issue.total_issue_value, + display=fmt_inr(issue.total_issue_value), section="issue_terms", + locator="proposed issue terms"), + Evidence(label="Regulatory cap", value=T.SME_MAX_OFS_PCT_OF_ISSUE, + display=f"{T.SME_MAX_OFS_PCT_OF_ISSUE:.0f}% of issue size", + section="ICDR", locator="amendment effective 8 March 2025"), + ], + resolutions=[ + Resolution( + id="cap_ofs", label="Reduce the offer for sale to the 20% cap", + description=( + "Resize the offer-for-sale component to " + f"{fmt_inr(issue.total_issue_value * T.SME_MAX_OFS_PCT_OF_ISSUE / 100)}, " + "the maximum permitted."), + recommended=True, kind="adopt_value", + justification="ICDR amendment effective 8 March 2025."), + Resolution(id="flag", label="Refer to the merchant banker", + description="Restructure the issue.", kind="flag_to_banker"), + ]) + ]) + + +@rule("ELG-003", "Post-issue paid-up capital is within the SME platform ceiling", + "ICDR Reg 229(1)") +def elg_003(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid, title = "ELG-003", "Post-issue paid-up capital is within the SME platform ceiling" + ref = "ICDR Reg 229(1)" + issue = ctx.get("issue") + sc, fv = gv(facts, "fin.current.share_capital"), gv(facts, "co.face_value") + if not issue or None in (sc, fv): + return na(rid, title, ref, "No proposed issue terms supplied.") + post = sc + issue.fresh_issue_shares * fv # type: ignore[operator] + if post <= T.SME_MAX_POST_ISSUE_CAPITAL_INR: + return ok(rid, title, ref, f"Post-issue paid-up capital {fmt_inr(post)} is within the " + f"{fmt_inr(T.SME_MAX_POST_ISSUE_CAPITAL_INR)} ceiling.") + return fail(rid, title, ref, "Post-issue capital exceeds the SME ceiling.", [ + Finding(rule_id=rid, severity=Severity.HIGH, + title="Post-issue paid-up capital exceeds the SME platform ceiling", + explanation=(f"Post-issue paid-up capital of {fmt_inr(post)} exceeds the " + f"{fmt_inr(T.SME_MAX_POST_ISSUE_CAPITAL_INR)} ceiling for the SME " + "platform; the issue would need to migrate to the main board."), + icdr_ref=ref, fact_ids=["fin.current.share_capital"], + delta=fmt_inr(post - T.SME_MAX_POST_ISSUE_CAPITAL_INR)) + ]) + + +# ==================================================== OBJ: objects of the issue + +@rule("OBJ-001", "Objects of the issue sum to the net proceeds available", + "ICDR Sch VI Pt A (VI)(2)") +def obj_001(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid, title = "OBJ-001", "Objects of the issue sum to the net proceeds available" + ref = "ICDR Sch VI Pt A (VI)(2)" + issue = ctx.get("issue") + if not issue or not issue.objects: + return na(rid, title, ref, "No objects of the issue supplied.") + total = sum(o.amount for o in issue.objects) + net = issue.net_proceeds + if close(total, net, 0.001): + return ok(rid, title, ref, + f"The {len(issue.objects)} stated objects total {fmt_inr(total)}, equal to " + f"net proceeds of {fmt_inr(net)}.") + over = total - net + evs = [Evidence(label=o.label, value=o.amount, display=fmt_inr(o.amount), + section="objects_of_issue", locator="proposed issue terms") + for o in issue.objects] + evs += [ + Evidence(label="Total of stated objects", value=total, display=fmt_inr(total), + section="objects_of_issue", locator="sum of the objects above"), + Evidence(label="Net proceeds available", value=net, display=fmt_inr(net), + section="objects_of_issue", + locator=(f"gross fresh issue {fmt_inr(issue.fresh_issue_value)} less issue " + f"expenses {fmt_inr(issue.issue_expenses)}")), + ] + verb = "exceed" if over > 0 else "fall short of" + return fail(rid, title, ref, f"Objects {verb} net proceeds by {fmt_inr(abs(over))}.", [ + Finding( + rule_id=rid, severity=Severity.BLOCKER, + title=f"Objects of the issue {verb} the net proceeds by {fmt_inr(abs(over))}", + explanation=( + f"The objects total {fmt_inr(total)} but only {fmt_inr(net)} is available " + f"(gross fresh issue {fmt_inr(issue.fresh_issue_value)} less issue expenses " + f"{fmt_inr(issue.issue_expenses)}). An offer document must deploy exactly the " + "net proceeds: this is one of the most common reasons an exchange returns a " + "draft with observations."), + icdr_ref=ref, delta=fmt_inr(abs(over)), evidence=evs, + resolutions=[ + Resolution(id="scale_gcp", + label="Adjust general corporate purposes to absorb the difference", + description=("Reduce the general-corporate-purposes allocation so the " + "objects total exactly the net proceeds."), + recommended=True, kind="adopt_value", + justification="GCP is the residual object and is capped separately."), + Resolution(id="resize_issue", label="Resize the fresh issue", + description="Increase the fresh issue so net proceeds meet the objects.", + kind="adopt_value"), + Resolution(id="flag", label="Refer to the merchant banker", + description="Rework the objects table.", kind="flag_to_banker"), + ]) + ]) + + +@rule("OBJ-002", "General corporate purposes is within the SME cap", + "ICDR amendment effective 8 March 2025") +def obj_002(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid, title = "OBJ-002", "General corporate purposes is within the SME cap" + ref = "ICDR amendment effective 8 March 2025" + issue = ctx.get("issue") + if not issue or not issue.objects: + return na(rid, title, ref, "No objects of the issue supplied.") + gcp = sum(o.amount for o in issue.objects if o.is_general_corporate) + if gcp <= 0: + return ok(rid, title, ref, "No general-corporate-purposes allocation is proposed.") + cap = min(issue.fresh_issue_value * T.SME_MAX_GCP_PCT_OF_PROCEEDS / 100.0, + float(T.SME_MAX_GCP_ABSOLUTE_INR)) + pct = 100.0 * gcp / issue.fresh_issue_value if issue.fresh_issue_value else 0.0 + if gcp <= cap: + return ok(rid, title, ref, + f"General corporate purposes of {fmt_inr(gcp)} is {pct:.2f}% of gross " + f"proceeds, within the cap of {fmt_inr(cap)}.") + return fail(rid, title, ref, "General corporate purposes exceeds the cap.", [ + Finding(rule_id=rid, severity=Severity.BLOCKER, + title="General corporate purposes exceeds the permitted cap", + explanation=( + f"For an SME issue, general corporate purposes may not exceed " + f"{T.SME_MAX_GCP_PCT_OF_PROCEEDS:.0f}% of gross proceeds or " + f"{fmt_inr(T.SME_MAX_GCP_ABSOLUTE_INR)}, whichever is lower: here " + f"{fmt_inr(cap)}. The proposed allocation is {fmt_inr(gcp)} ({pct:.2f}%)."), + icdr_ref=ref, delta=fmt_inr(gcp - cap), + evidence=[ + Evidence(label="Proposed general corporate purposes", value=gcp, + display=fmt_inr(gcp), section="objects_of_issue", + locator="proposed issue terms"), + Evidence(label="Permitted cap", value=cap, display=fmt_inr(cap), + section="ICDR", + locator=(f"lower of {T.SME_MAX_GCP_PCT_OF_PROCEEDS:.0f}% of gross " + f"proceeds and {fmt_inr(T.SME_MAX_GCP_ABSOLUTE_INR)}")), + ], + resolutions=[Resolution(id="cap_gcp", label="Reduce to the permitted cap", + description=f"Reduce the allocation to {fmt_inr(cap)}.", + recommended=True, kind="adopt_value", + justification="ICDR amendment effective 8 March 2025.")]) + ]) + + +@rule("OBJ-003", "Every object carries a year-wise deployment schedule that sums to its amount", + "ICDR Sch VI Pt A (VI)(3)") +def obj_003(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid = "OBJ-003" + title = "Every object carries a year-wise deployment schedule that sums to its amount" + ref = "ICDR Sch VI Pt A (VI)(3)" + issue = ctx.get("issue") + if not issue or not issue.objects: + return na(rid, title, ref, "No objects of the issue supplied.") + bad = [] + for o in issue.objects: + if not o.schedule: + bad.append((o, None)) + continue + s = sum(o.schedule.values()) + if not close(s, o.amount, 0.001): + bad.append((o, s)) + if not bad: + return ok(rid, title, ref, + f"All {len(issue.objects)} objects carry a deployment schedule that sums " + "to the stated amount.") + findings = [] + for o, s in bad: + findings.append(Finding( + rule_id=rid, severity=Severity.MEDIUM if s is None else Severity.HIGH, + title=(f"'{o.label}' has no deployment schedule" if s is None + else f"Deployment schedule for '{o.label}' does not sum to the object amount"), + explanation=( + "Schedule VI requires a year-wise deployment schedule for each object. " + + ("None is stated." if s is None + else f"The schedule totals {fmt_inr(s)} against an object of " + f"{fmt_inr(o.amount)}.")), + icdr_ref=ref, delta=None if s is None else fmt_inr(abs(s - o.amount)), + evidence=[Evidence(label=o.label, value=o.amount, display=fmt_inr(o.amount), + section="objects_of_issue", locator="proposed issue terms")], + resolutions=[Resolution(id="flag", label="Refer to the merchant banker", + description="Supply the year-wise deployment schedule.", + recommended=True, kind="flag_to_banker")])) + return fail(rid, title, ref, f"{len(bad)} object(s) have an incomplete schedule.", findings) + + +# ============================================================ DIL: issue pricing + +@rule("DIL-001", "The stated price/earnings ratio equals issue price divided by EPS", + "ICDR Sch VI Pt A (VII)(2)") +def dil_001(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid, title = "DIL-001", "The stated price/earnings ratio equals issue price divided by EPS" + ref = "ICDR Sch VI Pt A (VII)(2)" + issue = ctx.get("issue") + eps = gv(facts, "fin.current.eps_basic") + if not issue or eps is None or eps == 0: + return na(rid, title, ref, "Issue price or EPS unavailable.") + pe = issue.price_per_share / eps + if pe < 0: + return fail(rid, title, ref, "The issuer is loss-making at the latest year.", [ + Finding(rule_id=rid, severity=Severity.HIGH, + title="Price/earnings ratio cannot be stated: the issuer is loss-making", + explanation=("Basic EPS for the latest financial year is negative, so a " + "price/earnings ratio cannot be presented. Schedule VI requires " + "the Basis for Issue Price to explain the pricing on other " + "quantitative factors and to carry a specific risk factor."), + icdr_ref=ref, + evidence=[e for e in (ev(facts, "fin.current.eps_basic"),) if e], + fact_ids=["fin.current.eps_basic"], + resolutions=[Resolution(id="flag", label="Refer to the merchant banker", + description="Justify pricing without a P/E multiple.", + recommended=True, kind="flag_to_banker")]) + ]) + return ok(rid, title, ref, + f"At an issue price of {fmt_inr(issue.price_per_share)} and basic EPS of " + f"{eps:,.2f}, the price/earnings ratio is {pe:,.2f}.") + + +@rule("DIL-002", "Post-issue net asset value per share reconciles to net worth and proceeds", + "ICDR Sch VI Pt A (VII)(2)") +def dil_002(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid = "DIL-002" + title = "Post-issue net asset value per share reconciles to net worth and proceeds" + ref = "ICDR Sch VI Pt A (VII)(2)" + issue = ctx.get("issue") + nw, sh = gv(facts, "fin.current.net_worth"), gv(facts, "cap.shares_outstanding") + if not issue or None in (nw, sh): + return na(rid, title, ref, "Net worth or share count unavailable.") + post_shares = sh + issue.fresh_issue_shares # type: ignore[operator] + post_nav = (nw + issue.net_proceeds) / post_shares # type: ignore[operator] + return ok(rid, title, ref, + f"Post-issue net asset value is {post_nav:,.2f} per share " + f"(net worth {fmt_inr(nw)} plus net proceeds {fmt_inr(issue.net_proceeds)}, " + f"over {post_shares:,.0f} shares).") + + +# ===================================================== RPT: related party checks + +@rule("RPT-001", "Related party transactions are disclosed and quantified", + "ICDR Sch VI Pt A (IX)(3)") +def rpt_001(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid, title = "RPT-001", "Related party transactions are disclosed and quantified" + ref = "ICDR Sch VI Pt A (IX)(3)" + rpts = [f for fid, f in facts.items() if fid.startswith("rpt.")] + if not rpts: + return fail(rid, title, ref, "No related party transactions were found.", [ + Finding(rule_id=rid, severity=Severity.MEDIUM, + title="No related party transactions could be read from the filing", + explanation=("Schedule VI requires related party transactions to be disclosed " + "and quantified. None were machine-readable here. This is a " + "coverage gap, not evidence that none exist: it must be " + "confirmed against the audited notes."), + icdr_ref=ref, + resolutions=[Resolution(id="flag", label="Refer to the merchant banker", + description="Confirm the related party note.", + recommended=True, kind="flag_to_banker")]) + ]) + total = sum(_num(f) or 0.0 for f in rpts) + return ok(rid, title, ref, + f"{len(rpts)} related party transactions read from the audited notes, " + f"totalling {fmt_inr(total)}. Each is tagged to its page and remains " + "unverified until the counterparty relationship is confirmed.") + + +# ================================== PRV: provenance / responsible-AI invariants + +@rule("PRV-001", "Every figure in the draft is bound to a sourced ledger fact", + "responsible-AI invariant") +def prv_001(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid, title = "PRV-001", "Every figure in the draft is bound to a sourced ledger fact" + ref = "responsible-AI invariant" + unbound = ctx.get("unbound_numbers") or [] + sections = ctx.get("drafted_sections") or [] + if not sections: + return na(rid, title, ref, "The draft has not been generated yet.") + if not unbound: + return ok(rid, title, ref, + f"Every numeric assertion across {len(sections)} drafted sections resolves to " + "a ledger fact with a page-level citation. No unsourced figure reached the " + "document.") + return fail(rid, title, ref, f"{len(unbound)} unsourced figures found in the draft.", [ + Finding(rule_id=rid, severity=Severity.BLOCKER, + title="An unsourced figure reached the draft", + explanation=("Every number in the offer document must resolve to a ledger fact " + "carrying provenance. These did not: " + ", ".join(unbound[:8])), + icdr_ref=ref, + resolutions=[Resolution(id="flag", label="Refer to the merchant banker", + description="Remove or source the figure.", + recommended=True, kind="flag_to_banker")]) + ]) + + +@rule("PRV-002", "No unverified fact carries a load-bearing disclosure without attestation", + "responsible-AI invariant") +def prv_002(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid = "PRV-002" + title = "No unverified fact carries a load-bearing disclosure without attestation" + ref = "responsible-AI invariant" + used = set(ctx.get("used_fact_ids") or []) + risky = [f for fid, f in facts.items() + if f.status == FactStatus.UNVERIFIED and f.is_load_bearing and fid in used] + if not risky: + return ok(rid, title, ref, + "No unverified figure is carrying a load-bearing disclosure in the draft.") + evs = [Evidence(label=f.label, value=f.value, display=fmt(f), fact_id=f.id, + section=(f.provenance[0].section if f.provenance else ""), + locator=(f.provenance[0].locator if f.provenance else ""), + raw_line=(f.provenance[0].raw_line if f.provenance else "")) + for f in risky[:12]] + return fail(rid, title, ref, f"{len(risky)} unverified figures are in use.", [ + Finding( + rule_id=rid, severity=Severity.MEDIUM, + title=f"{len(risky)} unverified figure(s) are used in the draft", + explanation=( + "These figures were read from a single location with no corroborating section " + "and no accounting identity supporting them. The system has deliberately " + "abstained from treating them as verified. Each must be confirmed and attested " + "by the merchant banker before filing."), + icdr_ref=ref, evidence=evs, fact_ids=[f.id for f in risky], + resolutions=[ + Resolution(id="attest_all", label="Attest these figures", + description=("Record that the merchant banker has confirmed each " + "figure against the audited statements. The attestation " + "is written to the audit manifest with name and time."), + recommended=True, kind="attest"), + Resolution(id="flag", label="Refer to the merchant banker", + description="Leave open for review.", kind="flag_to_banker"), + ]) + ]) + + +@rule("PRV-003", "Conflicting sources have been reconciled", "responsible-AI invariant") +def prv_003(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid, title = "PRV-003", "Conflicting sources have been reconciled" + ref = "responsible-AI invariant" + conflicted = [f for f in facts.values() if f.status == FactStatus.CONFLICTED] + if not conflicted: + return ok(rid, title, ref, + "No figure in the ledger has two sources that disagree.") + return fail(rid, title, ref, f"{len(conflicted)} figures have conflicting sources.", [ + Finding(rule_id=rid, severity=Severity.HIGH, + title=f"{len(conflicted)} figure(s) are sourced from sections that disagree", + explanation=("Where two sections of the filing state different values for the " + "same figure, the ledger records the conflict rather than picking " + "a winner. Each must be reconciled."), + icdr_ref=ref, + evidence=[Evidence(label=f.label, value=f.value, display=fmt(f), fact_id=f.id, + locator=(f.provenance[0].locator if f.provenance else "")) + for f in conflicted[:10]], + fact_ids=[f.id for f in conflicted]) + ]) + + +# ============================================================ DOC: completeness + +@rule("DOC-001", "The issuer's identity is established from more than one source", + "ICDR Sch VI Pt A (I)(A)(1)") +def doc_001(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid, title = "DOC-001", "The issuer's identity is established from more than one source" + ref = "ICDR Sch VI Pt A (I)(A)(1)" + cin, isin = g(facts, "co.cin"), g(facts, "co.isin") + if cin is None: + return fail(rid, title, ref, "No CIN could be read from the filing.", [ + Finding(rule_id=rid, severity=Severity.BLOCKER, + title="Corporate Identity Number could not be established", + explanation="The offer document cover page must carry the issuer's CIN.", + icdr_ref=ref) + ]) + corroborated = isin is not None and isin.status == FactStatus.VERIFIED + if corroborated: + return ok(rid, title, ref, + f"CIN {cin.value} read from the filing; ISIN {isin.value} matches " + "independently between the annual report and the BSE master.") + return ok(rid, title, ref, + f"CIN {cin.value} read from the filing. ISIN could not be independently " + "corroborated between the annual report and the exchange master.") + + +@rule("DOC-002", "The filing's reporting scale is unambiguous", + "ICDR Sch VI Pt A (III)(3)") +def doc_002(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid, title = "DOC-002", "The filing's reporting scale is unambiguous" + ref = "ICDR Sch VI Pt A (III)(3)" + scales = ctx.get("scales") or {} + distinct = {v for v in scales.values() if v} + if len(distinct) <= 1: + return ok(rid, title, ref, + "All statements are presented on a single reporting scale.") + human = {1.0: "units", 1000.0: "thousands", 100000.0: "lakhs", + 1000000.0: "millions", 10000000.0: "crores"} + detail = ", ".join(f"{k.replace('_', ' ')} in {human.get(v, str(v))}" + for k, v in scales.items() if v) + return fail(rid, title, ref, "Statements use different reporting scales.", [ + Finding(rule_id=rid, severity=Severity.MEDIUM, + title="Different sections of the filing report on different scales", + explanation=( + f"The filing presents figures on more than one scale ({detail}). Every " + "figure has been normalised to rupees before checking, but the offer " + "document must state a single presentation basis, and mixed scales are a " + "frequent source of transcription error."), + icdr_ref=ref, + resolutions=[Resolution(id="attest", label="Confirm the presentation basis", + description="State a single presentation basis in the " + "offer document.", + recommended=True, kind="attest")]) + ]) + + +# ==================================================================== entry point + +def run_all(facts: dict[str, Fact], ctx: Ctx | None = None) -> list[RuleResult]: + """Run every registered rule. Deterministic, ordered, and free of side effects.""" + ctx = ctx or {} + out: list[RuleResult] = [] + for rid, title, ref, fn in REGISTRY: + try: + res = fn(facts, ctx) + except Exception as e: # noqa: BLE001 - a rule must never take down the engine + res = RuleResult(rule_id=rid, title=title, icdr_ref=ref, status="not_applicable", + detail=f"rule error: {type(e).__name__}: {e}") + for f in res.findings: + f.rule_id = res.rule_id + out.append(res) + return out + + +def rule_count() -> int: + return len(REGISTRY) + + +# ============================================ CIN: what the identifier settles + +@rule("ELG-004", "The issuer is a public company, as an issue requires", + "Companies Act 2013 s.23 / ICDR Reg 228") +def elg_004(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid = "ELG-004" + title = "The issuer is a public company, as an issue requires" + ref = "Companies Act 2013 s.23 / ICDR Reg 228" + parsed = ctx.get("cin") + if not parsed or not parsed.get("valid"): + return na(rid, title, ref, "No valid Corporate Identity Number was supplied.") + + own, name = parsed["ownership_code"], parsed["ownership"] + if parsed.get("is_public_company"): + return ok(rid, title, ref, + f"The Corporate Identity Number carries ownership class {own}, a " + f"{name.lower()}. A public company may make a public issue.") + if parsed.get("is_public_company") is None: + return na(rid, title, ref, f"Ownership class {own} is not recognised.") + + return fail(rid, title, ref, f"The issuer is a {name.lower()}.", [ + Finding( + rule_id=rid, severity=Severity.BLOCKER, + title="The issuer is a private company and cannot make a public issue", + explanation=( + f"The Corporate Identity Number carries ownership class {own}, which is a " + f"{name.lower()}. Only a public company may offer securities to the public. " + "Before an offer document can be filed the issuer must convert to a public " + "limited company under the Companies Act, which changes its name, its articles " + "and this very identifier. Every disclosure in the draft that names the issuer " + "will change with it."), + icdr_ref=ref, + evidence=[ + Evidence(label="Corporate Identity Number", value=parsed["raw"], + display=parsed["raw"], section="cin", + locator="ownership class, characters 13 to 15"), + Evidence(label="Ownership class", value=own, display=f"{own} ยท {name}", + section="cin", locator="Ministry of Corporate Affairs classification"), + ], + resolutions=[Resolution( + id="flag", label="Refer to the merchant banker", + description=("Conversion to a public limited company is a prerequisite step, " + "not a drafting fix."), + recommended=True, kind="flag_to_banker", + justification="Companies Act 2013, section 23.")], + ) + ]) + + +@rule("ELG-005", "The issuer has enough closed financial years for the track record test", + "ICDR Reg 229(6)") +def elg_005(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + rid = "ELG-005" + title = "The issuer has enough closed financial years for the track record test" + ref = "ICDR Reg 229(6)" + parsed = ctx.get("cin") + if not parsed or not parsed.get("valid") or not parsed.get("year"): + return na(rid, title, ref, "No valid Corporate Identity Number was supplied.") + + from ..cin import completed_financial_years + + year = int(parsed["year"]) + closed = completed_financial_years(year) + need = T.SME_MIN_EBITDA_YEARS + + if closed >= need: + return ok(rid, title, ref, + f"Incorporated in {year}, so at most {closed} financial years have closed. " + f"Regulation 229(6) tests operating profit in {need} of the last " + f"{T.SME_EBITDA_LOOKBACK}, which is reachable.") + + return fail(rid, title, ref, + f"Only {closed} financial year(s) can have closed since incorporation.", [ + Finding( + rule_id=rid, severity=Severity.BLOCKER, + title="The issuer is too recently incorporated to meet the track record test", + explanation=( + f"The Corporate Identity Number records incorporation in {year}. Counting " + f"Indian financial years ending 31 March, at most {closed} can have closed. " + f"Regulation 229(6) requires operating profit of at least " + f"{fmt_inr(T.SME_MIN_EBITDA_INR)} in {need} of the last " + f"{T.SME_EBITDA_LOOKBACK} financial years, so the issuer cannot satisfy it yet " + "however profitable those years were. This is a question of elapsed time, not " + "of performance."), + icdr_ref=ref, + delta=f"{need - closed} more closed financial year(s) required", + evidence=[ + Evidence(label="Year of incorporation", value=year, display=str(year), + section="cin", locator="characters 9 to 12 of the CIN"), + Evidence(label="Financial years closed at most", value=closed, + display=str(closed), section="derived", + locator="Indian financial years ending 31 March"), + Evidence(label="Required by Regulation 229(6)", value=need, + display=f"{need} of the last {T.SME_EBITDA_LOOKBACK}", + section="ICDR", locator="Reg 229(6)"), + ], + resolutions=[Resolution( + id="flag", label="Refer to the merchant banker", + description="Eligibility depends on elapsed financial years and cannot be " + "drafted around.", + recommended=True, kind="flag_to_banker")], + ) + ]) + + +@rule("CAP-004", "Paid-up capital agrees between the register and the audited balance sheet", + "ICDR Sch VI Pt A (V)(1)") +def cap_004(facts: dict[str, Fact], ctx: Ctx) -> RuleResult: + """Two independent authorities for one figure: the register and the auditor.""" + rid = "CAP-004" + title = "Paid-up capital agrees between the register and the audited balance sheet" + ref = "ICDR Sch VI Pt A (V)(1)" + reg = gv(facts, "cap.paidup_capital_registry") + aud = gv(facts, "fin.current.share_capital") + if reg is None or aud is None: + return na(rid, title, ref, + "Paid-up capital is available from only one of the register and the " + "audited balance sheet, so there is nothing to reconcile.") + if close(reg, aud, 0.01): + return ok(rid, title, ref, + f"Paid-up capital of {fmt_inr(aud)} agrees between the Ministry of " + "Corporate Affairs register and the audited balance sheet.") + return fail(rid, title, ref, "Paid-up capital differs between the two sources.", [ + Finding( + rule_id=rid, severity=Severity.HIGH, + title="Paid-up capital differs between the register and the audited accounts", + explanation=( + f"The Ministry of Corporate Affairs register records paid-up capital of " + f"{fmt_inr(reg)}; the audited balance sheet states {fmt_inr(aud)}. These are " + "two independent authorities for the same figure and an offer document must " + "reconcile them. A difference commonly means an allotment made after the " + "registry snapshot, which itself has to be disclosed in the capital " + "structure."), + icdr_ref=ref, delta=fmt_inr(abs(reg - aud)), + evidence=[e for e in (ev(facts, "cap.paidup_capital_registry"), + ev(facts, "fin.current.share_capital")) if e], + fact_ids=["cap.paidup_capital_registry", "fin.current.share_capital"], + resolutions=[Resolution( + id="adopt_audited", label="Adopt the audited balance sheet", + description=("Treat the audited accounts as authoritative and disclose any " + "allotment made since the registry snapshot."), + recommended=True, kind="adopt_value", + target_fact_id="cap.paidup_capital_registry", new_value=aud, + justification="Audited accounts carry the auditor's opinion.")], + ) + ]) diff --git a/app/backend/primarydraft/export/__init__.py b/app/backend/primarydraft/export/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/app/backend/primarydraft/export/docx_export.py b/app/backend/primarydraft/export/docx_export.py new file mode 100644 index 0000000000000000000000000000000000000000..ddbe289d6aa55685200856ae12f6ec5726fbfd77 --- /dev/null +++ b/app/backend/primarydraft/export/docx_export.py @@ -0,0 +1,248 @@ +"""Export the draft as a Word document the merchant banker can actually edit. + +Citations survive the export: every figure carries a footnote-style source marker +and the document ends with a provenance schedule, so the reviewer can check any +number against the filed page it came from without opening the tool. +""" + +from __future__ import annotations + +import re +from pathlib import Path + +from docx import Document +from docx.enum.text import WD_ALIGN_PARAGRAPH +from docx.shared import Pt, RGBColor + +from ..models import FactStatus, Run, Severity + +NAVY = RGBColor(0x0B, 0x1B, 0x2B) +TEAL = RGBColor(0x0E, 0x9F, 0x9A) +SLATE = RGBColor(0x5B, 0x6B, 0x7E) +RED = RGBColor(0xD7, 0x44, 0x3E) +AMBER = RGBColor(0xB0, 0x76, 0x0B) + +CITE_RE = re.compile(r']*data-fact-id="([^"]*)"[^>]*>(.*?)', re.S) +ANY_CITE_RE = re.compile(r"]*>(.*?)", re.S) +TAG_RE = re.compile(r"<[^>]+>") + + +def _unescape(s: str) -> str: + import html as _h + return _h.unescape(s) + + +def _blocks(html: str) -> list[tuple[str, str]]: + """Split rendered section HTML into ('p'|'li'|'table', inner html) blocks.""" + out: list[tuple[str, str]] = [] + for m in re.finditer(r"<(p|li|table)\b[^>]*>(.*?)", html, re.S | re.I): + out.append((m.group(1).lower(), m.group(2))) + return out + + +def build_docx(run: Run, path: Path) -> Path: + doc = Document() + + style = doc.styles["Normal"] + style.font.name = "Calibri" + style.font.size = Pt(10.5) + + # ------------------------------------------------------------------ cover + t = doc.add_paragraph() + t.alignment = WD_ALIGN_PARAGRAPH.CENTER + r = t.add_run("DRAFT RED HERRING PROSPECTUS: WORKING DRAFT") + r.bold = True + r.font.size = Pt(16) + r.font.color.rgb = NAVY + + s = doc.add_paragraph() + s.alignment = WD_ALIGN_PARAGRAPH.CENTER + sr = s.add_run("Not for circulation ยท Not certified ยท Not filed") + sr.italic = True + sr.font.color.rgb = RED + + doc.add_paragraph() + h = doc.add_paragraph() + h.alignment = WD_ALIGN_PARAGRAPH.CENTER + hr = h.add_run(run.company_name) + hr.bold = True + hr.font.size = Pt(20) + hr.font.color.rgb = NAVY + + meta = doc.add_paragraph() + meta.alignment = WD_ALIGN_PARAGRAPH.CENTER + mr = meta.add_run( + f"CIN {run.cin or '-'} ยท BSE scrip {run.scrip_code} ยท " + f"{run.meta.get('industry') or ''}" + ) + mr.font.color.rgb = SLATE + + doc.add_paragraph() + box = doc.add_paragraph() + br = box.add_run( + "This working draft was assembled by PrimaryDraft from the issuer's own filed " + f"annual report ({run.meta.get('annual_report_year')}) and the BSE scrip master. " + "Every figure below resolves to a source in the accompanying audit manifest. " + "Proposed issue terms were supplied by the user and are not facts about the issuer. " + "The merchant banker reviews, edits, certifies and files; PrimaryDraft does none of " + "those things." + ) + br.italic = True + br.font.size = Pt(9.5) + br.font.color.rgb = SLATE + + # ------------------------------------------------------- verdict summary + doc.add_page_break() + hh = doc.add_heading("Consistency check summary", level=1) + hh.runs[0].font.color.rgb = NAVY + + passed = sum(1 for r_ in run.rule_results if r_.status == "pass") + failed = sum(1 for r_ in run.rule_results if r_.status == "fail") + na = sum(1 for r_ in run.rule_results if r_.status == "not_applicable") + p = doc.add_paragraph() + p.add_run( + f"{len(run.rule_results)} deterministic checks were run: {passed} passed, " + f"{failed} failed, {na} not applicable. ICDR Schedule VI clause coverage is " + f"{run.coverage_pct()}%. No language model participated in any check." + ) + + if run.open_findings: + tb = doc.add_table(rows=1, cols=4) + tb.style = "Light Grid Accent 1" + for i, txt in enumerate(("Severity", "Rule", "Finding", "Difference")): + cell = tb.rows[0].cells[i] + cell.text = txt + for para in cell.paragraphs: + for rr in para.runs: + rr.bold = True + for f in sorted(run.open_findings, + key=lambda x: list(Severity).index(x.severity)): + row = tb.add_row().cells + row[0].text = f.severity.value.upper() + row[1].text = f.rule_id + row[2].text = f.title + row[3].text = f.delta or "-" + else: + doc.add_paragraph("No open findings. Every deterministic check that applied passed.") + + # ------------------------------------------------------------- sections + cited: dict[str, str] = {} + + for sec in run.sections: + doc.add_page_break() + hd = doc.add_heading(f"{sec.number}. {sec.title}", level=1) + hd.runs[0].font.color.rgb = NAVY + cl = doc.add_paragraph() + clr = cl.add_run(sec.icdr_clause) + clr.italic = True + clr.font.size = Pt(9) + clr.font.color.rgb = TEAL + + for kind, inner in _blocks(sec.html): + if kind == "table": + _add_table(doc, inner) + continue + para = doc.add_paragraph(style="List Bullet" if kind == "li" else None) + _add_rich(para, inner, run, cited) + + # -------------------------------------------------- provenance schedule + doc.add_page_break() + ph = doc.add_heading("Schedule of sources", level=1) + ph.runs[0].font.color.rgb = NAVY + doc.add_paragraph( + "Every figure cited in this draft, with the source it was read from. " + "Figures marked unverified were found in a single location with no " + "corroborating source and must be confirmed before filing." + ) + + tb = doc.add_table(rows=1, cols=4) + tb.style = "Light Grid Accent 1" + for i, txt in enumerate(("Figure", "Value", "Status", "Source")): + cell = tb.rows[0].cells[i] + cell.text = txt + for para in cell.paragraphs: + for rr in para.runs: + rr.bold = True + + used = run.meta.get("used_fact_ids") or list(run.facts) + for fid in sorted(set(used)): + f = run.facts.get(fid) + if f is None: + continue + prov = f.provenance[0] if f.provenance else None + row = tb.add_row().cells + row[0].text = f.label + row[1].text = cited.get(fid, str(f.value)) + row[2].text = f.status.value + row[3].text = (f"{prov.source_title}: {prov.locator}" if prov else "-") + + # ------------------------------------------------------------ sign-off + doc.add_page_break() + sh = doc.add_heading("Status of this document", level=1) + sh.runs[0].font.color.rgb = NAVY + for line in ( + "This is a working draft produced by an automated pre-filing consistency tool.", + "It has not been certified by a merchant banker.", + "It has not been filed with any stock exchange or with the Securities and Exchange " + "Board of India.", + "It is not an offer document and must not be circulated as one.", + "The due diligence certificate under Regulation 23 remains the responsibility of the " + "merchant banker.", + ): + b = doc.add_paragraph(style="List Bullet") + b.add_run(line) + + path.parent.mkdir(parents=True, exist_ok=True) + doc.save(str(path)) + return path + + +def _add_rich(para, inner: str, run: Run, cited: dict[str, str]) -> None: + """Write a paragraph, colouring cited figures by the status they earned.""" + pos = 0 + for m in ANY_CITE_RE.finditer(inner): + pre = TAG_RE.sub("", inner[pos:m.start()]) + if pre.strip(): + para.add_run(_unescape(re.sub(r"\s+", " ", pre))) + text = _unescape(TAG_RE.sub("", m.group(1))).strip() + fid_m = re.search(r'data-fact-id="([^"]*)"', m.group(0)) + status_m = re.search(r'data-status="([^"]*)"', m.group(0)) + status = status_m.group(1) if status_m else "" + run_ = para.add_run(text) + run_.bold = True + if status == FactStatus.UNVERIFIED.value: + run_.font.color.rgb = AMBER + elif status == FactStatus.CONFLICTED.value: + run_.font.color.rgb = RED + elif status == "proposed": + run_.font.color.rgb = SLATE + else: + run_.font.color.rgb = NAVY + if fid_m: + cited[fid_m.group(1)] = text + pos = m.end() + tail = TAG_RE.sub("", inner[pos:]) + if tail.strip(): + para.add_run(_unescape(re.sub(r"\s+", " ", tail))) + + +def _add_table(doc, inner: str) -> None: + rows = re.findall(r"]*>(.*?)", inner, re.S | re.I) + if not rows: + return + parsed: list[list[str]] = [] + for r in rows: + cells = re.findall(r"<(?:td|th)\b[^>]*>(.*?)", r, re.S | re.I) + parsed.append([_unescape(re.sub(r"\s+", " ", TAG_RE.sub("", c))).strip() + for c in cells]) + width = max(len(r) for r in parsed) + tb = doc.add_table(rows=0, cols=width) + tb.style = "Light Grid Accent 1" + for i, r in enumerate(parsed): + cells = tb.add_row().cells + for j, text in enumerate(r[:width]): + cells[j].text = text + if i == 0: + for para in cells[j].paragraphs: + for rr in para.runs: + rr.bold = True diff --git a/app/backend/primarydraft/export/manifest.py b/app/backend/primarydraft/export/manifest.py new file mode 100644 index 0000000000000000000000000000000000000000..64764e0cd36da918a4b2b7cab4fe73aab25c8336 --- /dev/null +++ b/app/backend/primarydraft/export/manifest.py @@ -0,0 +1,143 @@ +"""The audit manifest. + +This is the artefact that makes the tool defensible to a regulator: for every +figure in the draft it records where the value came from, what status it earned, +what supported it, and which human decided what. A reviewer can reconstruct the +entire draft from this file plus the source filings. +""" + +from __future__ import annotations + +import datetime as _dt +from typing import Any + +from ..engine import rules as rules_mod +from ..models import FactStatus, Run + + +def build_manifest(run: Run) -> dict[str, Any]: + facts_by_status: dict[str, list[dict[str, Any]]] = {s.value: [] for s in FactStatus} + for f in sorted(run.facts.values(), key=lambda x: x.id): + facts_by_status[f.status.value].append({ + "id": f.id, + "label": f.label, + "value": f.value, + "unit": f.unit.value, + "confidence": f.confidence, + "note": f.note, + "identities_supporting": f.identities, + "derived_from": f.derived_from, + "corroborating_sources": f.corroboration(), + "used_in_sections": f.section_refs, + "provenance": [ + { + "source": p.source_title, + "type": p.source_type, + "locator": p.locator, + "page": p.page, + "section": p.section, + "raw_line": p.raw_line, + "url": p.url, + "extractor": p.extractor, + "retrieved_at": p.retrieved_at, + } + for p in f.provenance + ], + "history": f.history, + }) + + used = set(run.meta.get("used_fact_ids") or []) + + return { + "manifest_version": "1.0", + "generated_at": _dt.datetime.now(_dt.timezone.utc).isoformat(timespec="seconds"), + "tool": { + "name": "PrimaryDraft", + "purpose": ("Pre-filing consistency gate for SME IPO offer documents. " + "Decision-support only."), + "deterministic_rule_count": rules_mod.rule_count(), + "llm_in_correctness_loop": False, + "statement": ( + "The correctness verdict in this manifest was produced entirely by " + "deterministic Python rules. No language model participated in any check. " + "Narrative phrasing may be model-assisted, but every figure in the draft " + "resolves to a ledger fact carrying the provenance recorded here." + ), + }, + "issuer": { + "name": run.company_name, + "cin": run.cin, + "bse_scrip_code": run.scrip_code, + "industry": run.meta.get("industry"), + "sector": run.meta.get("sector"), + "bse_group": run.meta.get("bse_group"), + }, + "sources": run.source_documents, + "source_integrity": { + "isin_corroborated_across_sources": run.meta.get("isin_corroborated"), + "accounting_identities_closed": run.meta.get("identities_closed", []), + "statement_pages": run.meta.get("statement_pages", {}), + "reporting_scales": run.meta.get("scales", {}), + "extraction_warnings": run.meta.get("extraction_warnings", []), + }, + "proposed_issue_terms": { + **(run.meta.get("issue") or {}), + "_note": ("Proposed terms supplied by the user. These are not facts about the " + "issuer and are recorded separately from the disclosure ledger."), + }, + "ledger": { + "total_facts": len(run.facts), + "status_counts": run.status_counts(), + "facts_used_in_draft": len(used), + "facts_by_status": facts_by_status, + }, + "draft": { + "sections": [ + {"id": s.id, "number": s.number, "title": s.title, + "icdr_clause": s.icdr_clause, "word_count": s.word_count, + "facts_cited": s.fact_ids, "narrative_source": s.narrative_source} + for s in run.sections + ], + "tokens_abstained": run.meta.get("missing_fact_ids", []), + "unsourced_figures": run.meta.get("unbound_numbers", []), + }, + "icdr_coverage": { + "percent": run.coverage_pct(), + "covered": sum(1 for c in run.coverage if c.covered), + "total": len(run.coverage), + "uncovered_clauses": [ + {"clause": c.clause, "title": c.title, "reason": c.reason} + for c in run.coverage if not c.covered + ], + }, + "checks": [ + { + "rule_id": r.rule_id, + "title": r.title, + "icdr_ref": r.icdr_ref, + "status": r.status, + "detail": r.detail, + "findings": [ + { + "severity": f.severity.value, + "title": f.title, + "explanation": f.explanation, + "delta": f.delta, + "resolved": f.resolved, + "resolved_by": f.resolved_by, + "resolved_at": f.resolved_at, + "evidence": [e.model_dump() for e in f.evidence], + } + for f in r.findings + ], + } + for r in run.rule_results + ], + "decision_log": [d.model_dump() for d in run.decisions], + "sign_off": { + "certified": False, + "statement": ("PrimaryDraft does not certify and does not file. The merchant " + "banker reviews this draft, exercises independent judgement, and " + "gives the due diligence certificate required under Regulation 23."), + }, + } diff --git a/app/backend/primarydraft/issue.py b/app/backend/primarydraft/issue.py new file mode 100644 index 0000000000000000000000000000000000000000..59b54cd06da5e45023eb9f21dd9dbe10d942b983 --- /dev/null +++ b/app/backend/primarydraft/issue.py @@ -0,0 +1,151 @@ +"""Proposed issue terms: the merchant banker's own input. + +The company's financials are real, read from its filed annual report. The issue +being contemplated is a *proposal*, supplied by the user exactly as a merchant +banker would supply it. Keeping the two apart matters: nothing here is presented +as a fact about the company, and the ledger never absorbs it as one. + +Defaults are computed from the issuer's real net worth so the form opens with a +plausible structure, and every field is editable. +""" + +from __future__ import annotations + +from typing import Any + +from pydantic import BaseModel, Field + + +class IssueObject(BaseModel): + """One stated object of the issue.""" + + id: str + label: str + amount: float + is_general_corporate: bool = False + #: FY label -> amount, e.g. {"FY2027": 1_00_00_000} + schedule: dict[str, float] = Field(default_factory=dict) + + +class IssueTerms(BaseModel): + """A proposed SME IPO structure. User input, clearly separated from filed facts.""" + + face_value: float = 10.0 + price_per_share: float = 100.0 + fresh_issue_shares: float = 0.0 + ofs_shares: float = 0.0 + issue_expenses: float = 0.0 + objects: list[IssueObject] = Field(default_factory=list) + lead_manager: str = "" + listing_platform: str = "BSE SME" + + # --------------------------------------------------------------- derivations + + @property + def fresh_issue_value(self) -> float: + return self.fresh_issue_shares * self.price_per_share + + @property + def ofs_value(self) -> float: + return self.ofs_shares * self.price_per_share + + @property + def total_issue_value(self) -> float: + return self.fresh_issue_value + self.ofs_value + + @property + def total_issue_shares(self) -> float: + return self.fresh_issue_shares + self.ofs_shares + + @property + def net_proceeds(self) -> float: + """Only the fresh issue reaches the company; an OFS goes to selling shareholders.""" + return self.fresh_issue_value - self.issue_expenses + + def to_public(self) -> dict[str, Any]: + return { + **self.model_dump(), + "fresh_issue_value": self.fresh_issue_value, + "ofs_value": self.ofs_value, + "total_issue_value": self.total_issue_value, + "total_issue_shares": self.total_issue_shares, + "net_proceeds": self.net_proceeds, + } + + +def _round_to(v: float, step: float) -> float: + return max(step, round(v / step) * step) + + +def default_terms(facts: dict[str, Any]) -> IssueTerms: + """Open the form with a structure scaled to the issuer's real balance sheet. + + These are suggestions for the banker to edit, not claims about the company. + They are deliberately built to be *plausible but not pre-reconciled*: the + engine's job is to check the proposal, so it must be checked honestly. + """ + + def val(fid: str) -> float | None: + f = facts.get(fid) + v = getattr(f, "value", None) + return float(v) if isinstance(v, (int, float)) else None + + face_value = val("co.face_value") or 10.0 + net_worth = val("fin.current.net_worth") or 0.0 + eps = val("fin.current.eps_basic") or val("fin.current.eps_computed") or 0.0 + shares = val("cap.shares_outstanding") or 0.0 + + # Price on a modest multiple of real earnings, floored at face value. + price = _round_to(max(eps * 15.0, face_value * 1.5, face_value + 1.0), 1.0) + + # Raise roughly 40% of net worth, floored so the structure is meaningful. + target_raise = max(net_worth * 0.40, 5_00_00_000.0) + fresh_shares = _round_to(target_raise / price, 10_000.0) + + # Keep the opening proposal inside the SME platform's post-issue capital + # ceiling (Reg 229(1)); the banker can still push it past, and the engine + # will say so. + sme_capital_ceiling = 25_00_00_000.0 + share_capital = shares * face_value + if face_value: + headroom = max(0.0, (sme_capital_ceiling - share_capital) / face_value) + if headroom: + fresh_shares = min(fresh_shares, _round_to(headroom * 0.9, 10_000.0)) + + # A modest OFS, sized at 15% of the total issue: inside the 20% SME cap. + ofs_shares = _round_to(fresh_shares * 0.1765, 10_000.0) + if shares: + ofs_shares = min(ofs_shares, _round_to(shares * 0.10, 10_000.0)) + + gross = fresh_shares * price + expenses = _round_to(gross * 0.06, 1_00_000.0) + net = gross - expenses + + capex = _round_to(net * 0.45, 1_00_000.0) + wc = _round_to(net * 0.30, 1_00_000.0) + debt = _round_to(net * 0.12, 1_00_000.0) + gcp = net - capex - wc - debt + + objects = [ + IssueObject(id="capex", label="Funding capital expenditure towards plant and machinery", + amount=capex, + schedule={"FY2027": round(capex * 0.6, 2), "FY2028": round(capex * 0.4, 2)}), + IssueObject(id="working_capital", + label="Funding incremental working capital requirements", amount=wc, + schedule={"FY2027": round(wc * 0.5, 2), "FY2028": round(wc * 0.5, 2)}), + IssueObject(id="debt_repayment", + label="Repayment or prepayment of certain borrowings", amount=debt, + schedule={"FY2027": debt}), + IssueObject(id="gcp", label="General corporate purposes", amount=round(gcp, 2), + is_general_corporate=True, schedule={"FY2027": round(gcp, 2)}), + ] + + return IssueTerms( + face_value=face_value, + price_per_share=price, + fresh_issue_shares=fresh_shares, + ofs_shares=ofs_shares, + issue_expenses=expenses, + objects=objects, + listing_platform="BSE SME", + ) diff --git a/app/backend/primarydraft/ledger.py b/app/backend/primarydraft/ledger.py new file mode 100644 index 0000000000000000000000000000000000000000..b4fea86b5519b5d6c689f0bbd15f00bd19acbce5 --- /dev/null +++ b/app/backend/primarydraft/ledger.py @@ -0,0 +1,423 @@ +"""Build the Disclosure Ledger from real extracted filings. + +Status is *earned*, never assumed: + + two independent sections agree -> VERIFIED (corroborated) + one section, but an identity closes -> VERIFIED (identity-supported) + two sections disagree -> CONFLICTED (engine raises a finding) + one section, nothing supports it -> UNVERIFIED (abstain; says what to confirm) + +Nothing is invented. A value we could not read is simply absent from the ledger, +and the ICDR coverage map reports that absence honestly. +""" + +from __future__ import annotations + +from typing import Any + +from .models import Fact, FactStatus, Provenance, Unit + +# Human labels for the canonical fields we extract. +LABELS: dict[str, str] = { + "revenue_from_operations": "Revenue from operations", + "other_income": "Other income", + "total_income": "Total income", + "cost_of_materials": "Cost of materials consumed", + "purchases_stock_in_trade": "Purchases of stock-in-trade", + "employee_benefits": "Employee benefits expense", + "finance_costs": "Finance costs", + "depreciation": "Depreciation and amortisation", + "other_expenses": "Other expenses", + "total_expenses": "Total expenses", + "pbt": "Profit before tax", + "tax_current": "Current tax", + "tax_deferred": "Deferred tax", + "pat": "Profit after tax (restated)", + "eps_basic": "Basic earnings per share", + "eps_diluted": "Diluted earnings per share", + "share_capital": "Equity share capital", + "reserves_surplus": "Reserves and surplus", + "borrowings_non_current": "Long-term borrowings", + "borrowings_current": "Short-term borrowings", + "deferred_tax_liability": "Deferred tax liabilities (net)", + "other_current_liabilities": "Other current liabilities", + "short_term_provisions": "Short-term provisions", + "trade_payables": "Trade payables", + "total_equity_liabilities": "Total equity and liabilities", + "ppe": "Property, plant and equipment", + "non_current_investments": "Non-current investments", + "long_term_loans_advances": "Long-term loans and advances", + "current_investments": "Current investments", + "inventories": "Inventories", + "trade_receivables": "Trade receivables", + "cash_and_equivalents": "Cash and cash equivalents", + "total_assets": "Total assets", +} + +# Which ICDR offer-document sections consume each field. +SECTION_REFS: dict[str, list[str]] = { + "revenue_from_operations": ["financial_information", "mdna", "basis_for_issue_price"], + "other_income": ["financial_information", "mdna"], + "total_income": ["financial_information", "mdna"], + "total_expenses": ["financial_information", "mdna"], + "pbt": ["financial_information", "mdna"], + "pat": ["financial_information", "mdna", "basis_for_issue_price"], + "eps_basic": ["basis_for_issue_price", "financial_information"], + "eps_diluted": ["basis_for_issue_price", "financial_information"], + "share_capital": ["capital_structure", "financial_information"], + "reserves_surplus": ["financial_information", "basis_for_issue_price"], + "total_assets": ["financial_information"], + "total_equity_liabilities": ["financial_information"], +} + +UNITS: dict[str, Unit] = { + "eps_basic": Unit.RATIO, + "eps_diluted": Unit.RATIO, +} + +SECTION_TITLES = { + "audited_pl": "Statement of Profit and Loss (audited)", + "directors_report": "Directors' Report: Financial Results", + "balance_sheet": "Balance Sheet (audited)", +} + +# Fields the two P&L presentations should agree on. Tax lines are excluded: the +# Directors' Report presents them as negatives inside a derivation, so a raw +# comparison would flag a presentational difference as a contradiction. +CROSS_CHECK_FIELDS = ( + "revenue_from_operations", "other_income", "total_income", + "pat", "eps_basic", "eps_diluted", +) + +REL_TOL = 0.005 # 0.5%: absorbs rounding between two printings of one figure + + +def _close(a: float, b: float, tol: float = REL_TOL) -> bool: + scale = max(abs(a), abs(b), 1.0) + return abs(a - b) <= tol * scale + + +def _prov(src: dict[str, Any], ex: dict[str, Any], section: str, cell: dict[str, Any], + extractor: str = "deterministic") -> Provenance: + return Provenance( + source_id=f"ar_{src['scrip_code']}_{src['annual_report']['year']}", + source_title=(f"Annual Report {src['annual_report']['year']}: " + f"{src['bse']['scrip_name']}"), + source_type="annual_report", + page=cell.get("page"), + locator=f"p.{cell.get('page')} ยท {SECTION_TITLES.get(section, section)}", + raw_line=cell.get("line", ""), + section=section, + url=src["annual_report"].get("url"), + extractor=extractor, # type: ignore[arg-type] + ) + + +def _identity_supports(field: str, identities: list[str]) -> list[str]: + """Which closed identities vouch for this particular field.""" + out = [] + for ident in identities: + toks = ident.replace("=", " ").replace("+", " ").replace("-", " ").split() + norm = {t.strip().lower() for t in toks} + if field in norm: + out.append(ident) + elif field == "revenue_from_operations" and "revenue" in norm: + out.append(ident) + elif field == "other_income" and "other_income" in ident: + out.append(ident) + elif field in ("total_assets", "total_equity_liabilities") and "total" in ident: + out.append(ident) + return out + + +def build_ledger(record: dict[str, Any]) -> dict[str, Fact]: + """Turn one real company record into provenance-bound facts.""" + ex = record["extraction"] + facts: dict[str, Fact] = {} + + year = str(record["annual_report"].get("year") or "") + periods = {"current": f"FY{year}", "previous": "FY-prior"} + + statements = { + "audited_pl": (ex.get("audited_pl") or {}, ex.get("audited_pl_identities") or []), + "directors_report": (ex.get("directors_pl") or {}, ex.get("directors_pl_identities") or []), + "balance_sheet": (ex.get("balance_sheet") or {}, ex.get("balance_sheet_identities") or []), + } + + # ---- 1. gather every reading of every (field, period) across all statements + readings: dict[tuple[str, str], list[tuple[str, dict[str, Any], list[str]]]] = {} + for section, (stmt, idents) in statements.items(): + for field, cols in stmt.items(): + for period, cell in cols.items(): + readings.setdefault((field, period), []).append((section, cell, idents)) + + # ---- 2. reconcile each into exactly one fact + for (field, period), obs in readings.items(): + label = LABELS.get(field, field.replace("_", " ").capitalize()) + unit = UNITS.get(field, Unit.INR) + fid = f"fin.{period}.{field}" + + provs = [_prov(record, ex, sec, cell) for sec, cell, _ in obs] + values = [cell["value"] for _, cell, _ in obs] + supporting: list[str] = [] + for sec, _cell, idents in obs: + supporting += _identity_supports(field, idents) + + distinct_sections = {sec for sec, _, _ in obs} + + # Two readings are only comparable when they are on the SAME reporting + # basis. A standalone figure and a consolidated figure are different + # measures, and a Directors' Report that prints both side by side is + # ambiguous. Comparing across bases would manufacture a contradiction + # from two correctly-stated numbers, so we decline to compare at all. + bases = {cell.get("basis") for _, cell, _ in obs} + comparable = len(bases) == 1 and None not in bases + cross_checkable = field in CROSS_CHECK_FIELDS and comparable + + # If the two sections print the SAME digits but we scaled them differently, + # the disagreement is ours, not the issuer's: one of the two scale headings + # was misread. That is a presentation ambiguity (DOC-002), never a + # contradiction to put in front of a regulator. + raw_values = [cell["value"] / (cell.get("scale") or 1.0) for _, cell, _ in obs] + same_digits = len(obs) > 1 and all(_close(raw_values[0], r) for r in raw_values[1:]) + scale_mismatch = same_digits and not all(_close(values[0], v) for v in values[1:]) + + if scale_mismatch: + status = FactStatus.UNVERIFIED + conf = 0.55 + note = ( + "Both sections print the same figure, but they declare different " + "reporting scales, so the amounts do not agree once normalised. This is " + "an ambiguity in how the filing states its units, not a difference in " + "the underlying number. Confirm the presentation basis." + ) + elif len(obs) > 1 and cross_checkable and not all( + _close(values[0], v) for v in values[1:] + ): + # Two independent sections of the company's own filing disagree. + status = FactStatus.CONFLICTED + conf = 0.35 + note = ( + "Two sections of the filing state different values for this figure: " + + "; ".join( + f"{SECTION_TITLES.get(sec, sec)} = {cell['value']:,.2f}" + for sec, cell, _ in obs + ) + ) + elif len(distinct_sections) > 1 and cross_checkable: + status = FactStatus.VERIFIED + conf = 0.99 + note = None + elif supporting: + status = FactStatus.VERIFIED + conf = 0.9 + note = None + elif len(obs) > 1 and not comparable: + status = FactStatus.UNVERIFIED + conf = 0.6 + seen = ", ".join(sorted(str(b or "basis not stated") for b in bases)) + note = ( + "This figure appears in more than one section, but on different " + f"reporting bases ({seen}), so the readings are not comparable and " + "have not been treated as corroborating each other. Confirm which " + "basis the offer document should present." + ) + else: + status = FactStatus.UNVERIFIED + conf = 0.5 + note = ( + "Read from a single location with no corroborating section and no " + "accounting identity supporting it. Confirm against the audited " + "financial statements before filing." + ) + + facts[fid] = Fact( + id=fid, + label=f"{label} ({periods.get(period, period)})", + value=values[0], + unit=unit, + status=status, + confidence=conf, + provenance=provs, + section_refs=SECTION_REFS.get(field, ["financial_information"]), + note=note, + period=period, + identities=sorted(set(supporting)), + ) + + # ---- 3. company identity facts (BSE master + the filing itself) + bse = record["bse"] + api_prov = Provenance( + source_id=f"bse_{record['scrip_code']}", + source_title="BSE India: scrip master & company header (live API)", + source_type="bse_api", + locator="api.bseindia.com ยท ListofScripData / ComHeadernew", + section="bse_master", + url="https://api.bseindia.com/BseIndiaAPI/api/ListofScripData/w", + extractor="deterministic", + ) + filing_prov = Provenance( + source_id=f"ar_{record['scrip_code']}_{record['annual_report']['year']}", + source_title=f"Annual Report {record['annual_report']['year']}", + source_type="annual_report", + locator="cover / corporate information", + section="corporate_information", + url=record["annual_report"].get("url"), + extractor="deterministic", + ) + + def add(fid: str, label: str, value: Any, unit: Unit, provs: list[Provenance], + status: FactStatus, refs: list[str], note: str | None = None) -> None: + if value in (None, "", []): + return + facts[fid] = Fact(id=fid, label=label, value=value, unit=unit, status=status, + confidence=0.99 if status == FactStatus.VERIFIED else 0.6, + provenance=provs, section_refs=refs, note=note) + + add("co.name", "Name of the Issuer", bse["scrip_name"], Unit.TEXT, + [api_prov, filing_prov], FactStatus.VERIFIED, ["general_information"]) + add("co.cin", "Corporate Identity Number", ex.get("cin"), Unit.TEXT, + [filing_prov], FactStatus.VERIFIED, ["general_information"]) + + # ISIN appears in BOTH the BSE master and the company's own annual report. + isin_status = (FactStatus.VERIFIED if record.get("isin_corroborated") + else FactStatus.UNVERIFIED) + add("co.isin", "ISIN", bse.get("isin"), Unit.TEXT, + [api_prov, filing_prov] if record.get("isin_corroborated") else [api_prov], + isin_status, ["general_information"], + None if record.get("isin_corroborated") + else "ISIN in the BSE master could not be matched to the annual report text.") + + add("co.face_value", "Face value per equity share", _f(bse.get("face_value")), Unit.INR, + [api_prov], FactStatus.VERIFIED, ["capital_structure"]) + add("co.industry", "Industry", bse.get("industry"), Unit.TEXT, [api_prov], + FactStatus.VERIFIED, ["our_business"]) + add("co.sector", "Sector", bse.get("sector"), Unit.TEXT, [api_prov], + FactStatus.VERIFIED, ["our_business"]) + add("co.bse_group", "BSE trading group (SME platform)", bse.get("group"), Unit.TEXT, + [api_prov], FactStatus.VERIFIED, ["general_information"]) + add("co.market_cap", "Market capitalisation (BSE)", _f(bse.get("market_cap")), Unit.INR, + [api_prov], FactStatus.VERIFIED, ["basis_for_issue_price"]) + add("co.eps_bse", "Earnings per share as published by BSE", _f(bse.get("eps_reported")), + Unit.RATIO, [api_prov], FactStatus.VERIFIED, ["basis_for_issue_price"]) + add("co.pe_bse", "Price/earnings ratio as published by BSE", _f(bse.get("pe_reported")), + Unit.RATIO, [api_prov], FactStatus.VERIFIED, ["basis_for_issue_price"]) + + for i, aud in enumerate(ex.get("auditors") or []): + if "chartered accountant" not in aud.lower() or len(aud) > 80: + continue + add(f"co.auditor.{i}", "Statutory auditor (as named in the filing)", aud, Unit.TEXT, + [filing_prov], FactStatus.UNVERIFIED, ["general_information"], + "Auditor name read from the filing text; confirm the firm registration number.") + + for i, din in enumerate((ex.get("dins") or [])[:10]): + add(f"mgmt.din.{i}", "Director Identification Number disclosed in the filing", din, + Unit.TEXT, [filing_prov], FactStatus.VERIFIED, ["our_management"]) + + for i, rp in enumerate((ex.get("related_party") or [])[:14]): + p = Provenance( + source_id=f"ar_{record['scrip_code']}_{record['annual_report']['year']}", + source_title="Annual Report: Related Party Disclosures", + source_type="annual_report", page=rp.get("page"), + locator=f"p.{rp.get('page')} ยท Related Party Disclosures", + raw_line=rp.get("line", ""), section="related_party", + url=record["annual_report"].get("url"), + ) + facts[f"rpt.{i}"] = Fact( + id=f"rpt.{i}", label=f"Related party transaction: {rp['label']}", + value=rp["amount"], unit=Unit.INR, status=FactStatus.UNVERIFIED, + confidence=0.55, provenance=[p], section_refs=["related_party", "financial_information"], + note=("Read from the related-party note. Confirm the counterparty relationship " + "and that the amount ties to the RPT summary."), + ) + + # ---- 4. derived facts, with explicit lineage + _add_derived(facts, record) + return facts + + +def _f(v: Any) -> float | None: + try: + return float(str(v).replace(",", "").strip()) + except (TypeError, ValueError): + return None + + +def _add_derived(facts: dict[str, Fact], record: dict[str, Any]) -> None: + """Facts computed from other facts. Lineage is recorded; nothing is guessed.""" + year = str(record["annual_report"].get("year") or "") + + def val(fid: str) -> float | None: + f = facts.get(fid) + return float(f.value) if f and isinstance(f.value, (int, float)) else None + + dp = Provenance( + source_id="derived", source_title="Computed by PrimaryDraft from ledger facts", + source_type="derived", locator="deterministic computation", section="derived", + extractor="derived", + ) + + def derive(fid: str, label: str, value: float | None, parents: list[str], + unit: Unit, refs: list[str], note: str | None = None) -> None: + if value is None or not all(p in facts for p in parents): + return + facts[fid] = Fact( + id=fid, label=label, value=round(value, 4), unit=unit, + status=FactStatus.DERIVED, confidence=0.95, provenance=[dp], + section_refs=refs, derived_from=parents, note=note, + ) + + pbt, pat = val("fin.current.pbt"), val("fin.current.pat") + if pbt is not None and pat is not None: + derive("fin.current.tax_total", f"Total tax expense (FY{year}, derived)", pbt - pat, + ["fin.current.pbt", "fin.current.pat"], Unit.INR, ["financial_information"], + "Derived as profit before tax less profit after tax.") + + pbt_, fc, dep, oi = (val("fin.current.pbt"), val("fin.current.finance_costs"), + val("fin.current.depreciation"), val("fin.current.other_income")) + if None not in (pbt_, fc, dep, oi): + derive("fin.current.ebitda", f"EBITDA (FY{year}, derived)", + pbt_ + fc + dep - oi, # type: ignore[operator] + ["fin.current.pbt", "fin.current.finance_costs", + "fin.current.depreciation", "fin.current.other_income"], + Unit.INR, ["basis_for_issue_price", "financial_information"], + "Profit before tax plus finance costs and depreciation, less other income. " + "Drives the Reg 229(6) SME eligibility test.") + + sc, rs = val("fin.current.share_capital"), val("fin.current.reserves_surplus") + if sc is not None and rs is not None: + derive("fin.current.net_worth", f"Net worth (FY{year}, derived)", sc + rs, + ["fin.current.share_capital", "fin.current.reserves_surplus"], + Unit.INR, ["financial_information", "basis_for_issue_price"]) + + fv = val("co.face_value") + if sc is not None and fv: + derive("cap.shares_outstanding", "Equity shares outstanding (derived)", sc / fv, + ["fin.current.share_capital", "co.face_value"], Unit.SHARES, + ["capital_structure", "basis_for_issue_price"], + "Equity share capital divided by face value per share.") + + shares, pat_ = val("cap.shares_outstanding"), val("fin.current.pat") + if shares and pat_ is not None: + derive("fin.current.eps_computed", f"Basic EPS (FY{year}, computed)", pat_ / shares, + ["fin.current.pat", "cap.shares_outstanding"], Unit.RATIO, + ["basis_for_issue_price"], + "Profit after tax divided by shares outstanding: reconciled against the " + "EPS as printed in the filing.") + + nw = val("fin.current.net_worth") + if nw is not None and shares: + derive("fin.current.nav_per_share", "Net asset value per equity share (derived)", + nw / shares, ["fin.current.net_worth", "cap.shares_outstanding"], + Unit.RATIO, ["basis_for_issue_price"]) + if nw and pat_ is not None: + derive("fin.current.ronw", "Return on net worth (derived, %)", 100.0 * pat_ / nw, + ["fin.current.pat", "fin.current.net_worth"], Unit.PCT, + ["basis_for_issue_price"]) + + rev_c, rev_p = val("fin.current.revenue_from_operations"), val("fin.previous.revenue_from_operations") + if rev_c is not None and rev_p: + derive("fin.revenue_growth", "Revenue growth over the previous year (derived, %)", + 100.0 * (rev_c - rev_p) / abs(rev_p), + ["fin.current.revenue_from_operations", "fin.previous.revenue_from_operations"], + Unit.PCT, ["mdna", "basis_for_issue_price"]) diff --git a/app/backend/primarydraft/live.py b/app/backend/primarydraft/live.py new file mode 100644 index 0000000000000000000000000000000000000000..b967f64e964fe7b3039ac9eeb727192a449e4bba --- /dev/null +++ b/app/backend/primarydraft/live.py @@ -0,0 +1,269 @@ +"""Live search over the BSE universe, and on-demand ingestion of any issuer. + +Search runs against the real BSE scrip master (4,949 active equity scrips, of which +~513 sit on the SME platform). Choosing an issuer we have not seen before downloads +its actual annual report and parses it, which takes real time and can genuinely +fail. Progress is reported honestly, and so is failure: a filing that is a scanned +image with no text layer yields nothing citable, and we say exactly that rather +than inventing a ledger. +""" + +from __future__ import annotations + +import json +import logging +import threading +import time +import uuid +from concurrent.futures import ThreadPoolExecutor +from typing import Any + +from .sources.bse import SME_GROUPS, BSEClient +from .sources.corpus import DATA, INDEX, Unusable, build_one + +log = logging.getLogger(__name__) + +_MASTER_LOCK = threading.Lock() +_master: list[dict[str, Any]] | None = None +_master_at: float = 0.0 +MASTER_TTL = 60 * 60 * 6 # the scrip master changes rarely; re-read every 6 hours + + +def scrip_master(offline: bool = False) -> list[dict[str, Any]]: + """The live BSE scrip master, memoised in process and cached on disk.""" + global _master, _master_at + with _MASTER_LOCK: + if _master is not None and (time.time() - _master_at) < MASTER_TTL: + return _master + with BSEClient(offline=offline) as c: + _master = c.scrip_master() + _master_at = time.time() + return _master + + +def prepared_codes() -> set[str]: + return {p.stem for p in DATA.glob("*.json")} + + +def search(q: str, scope: str = "sme", limit: int = 40) -> list[dict[str, Any]]: + """Search every active BSE company by name, scrip code or ISIN.""" + rows = scrip_master() + have = prepared_codes() + ql = q.strip().lower() + + def is_sme(r: dict[str, Any]) -> bool: + return (r.get("GROUP") or "").strip() in SME_GROUPS + + pool = [r for r in rows if is_sme(r)] if scope == "sme" else rows + + if ql: + def hit(r: dict[str, Any]) -> bool: + return (ql in (r.get("Scrip_Name") or "").lower() + or ql in (r.get("Issuer_Name") or "").lower() + or ql in str(r.get("SCRIP_CD") or "") + or ql in (r.get("ISIN_NUMBER") or "").lower() + or ql in (r.get("INDUSTRY") or "").lower()) + pool = [r for r in pool if hit(r)] + + def rank(r: dict[str, Any]) -> tuple: + name = (r.get("Scrip_Name") or "").lower() + try: + mcap = float(str(r.get("Mktcap") or 0).replace(",", "")) + except ValueError: + mcap = 0.0 + # Prepared issuers first, then exact prefix matches, then by size. + return ( + str(r.get("SCRIP_CD")) not in have, + not name.startswith(ql) if ql else True, + -mcap, + ) + + out = [] + for r in sorted(pool, key=rank)[:limit]: + code = str(r.get("SCRIP_CD")) + out.append({ + "scrip_code": code, + "name": (r.get("Scrip_Name") or "").strip(), + "issuer_name": (r.get("Issuer_Name") or "").strip(), + "isin": (r.get("ISIN_NUMBER") or "").strip() or None, + "industry": (r.get("INDUSTRY") or "").strip(), + "group": (r.get("GROUP") or "").strip(), + "face_value": r.get("FACE_VALUE"), + "market_cap": r.get("Mktcap"), + "is_sme": is_sme(r), + "prepared": code in have, + }) + return out + + +def enrich_filings(results: list[dict[str, Any]], limit: int = 14) -> None: + """Mark which issuers actually have an annual report on BSE, in place. + + Many recently listed SME issuers have not filed one yet, and a scanned filing + has nothing citable in it. Checking up front means the user is not sent down a + dead end. The index call is cheap JSON and is cached, so this is fast after the + first look. + """ + todo = [r for r in results[:limit] if not r["prepared"]] + if not todo: + for r in results: + r.setdefault("has_filing", r["prepared"] or None) + return + + def check(row: dict[str, Any]) -> None: + try: + with BSEClient() as c: + reports = c.annual_reports(row["scrip_code"]) + row["has_filing"] = bool(reports) + row["filing_year"] = reports[0].get("Year") if reports else None + except Exception: # noqa: BLE001 - unknown is a valid answer here + row["has_filing"] = None + + with ThreadPoolExecutor(max_workers=8) as ex: + list(ex.map(check, todo)) + + for r in results: + if r["prepared"]: + r["has_filing"] = True + else: + r.setdefault("has_filing", None) + + +def universe_counts() -> dict[str, int]: + rows = scrip_master() + return { + "total": len(rows), + "sme": sum(1 for r in rows if (r.get("GROUP") or "").strip() in SME_GROUPS), + "prepared": len(prepared_codes()), + } + + +# ------------------------------------------------------------------- ingestion + +class Job: + """One live ingestion, observable while it runs.""" + + def __init__(self, scrip_code: str, name: str) -> None: + self.id = uuid.uuid4().hex[:12] + self.scrip_code = scrip_code + self.name = name + self.status = "running" # running | done | failed + self.stage = "queued" + self.detail = "Waiting for a worker" + self.pct = 0 + self.error: str | None = None + self.result: dict[str, Any] | None = None + self.started = time.time() + self.events: list[dict[str, Any]] = [] + + def push(self, stage: str, detail: str, pct: int) -> None: + self.stage, self.detail, self.pct = stage, detail, pct + self.events.append({"stage": stage, "detail": detail, "pct": pct, + "at": round(time.time() - self.started, 1)}) + + def to_dict(self) -> dict[str, Any]: + return { + "id": self.id, "scrip_code": self.scrip_code, "name": self.name, + "status": self.status, "stage": self.stage, "detail": self.detail, + "pct": self.pct, "error": self.error, + "elapsed": round(time.time() - self.started, 1), + "events": self.events, + "summary": self.result, + } + + +_JOBS: dict[str, Job] = {} +_POOL = ThreadPoolExecutor(max_workers=2, thread_name_prefix="ingest") +_BY_CODE: dict[str, str] = {} + + +def _run(job: Job) -> None: + try: + rows = scrip_master() + row = next((r for r in rows if str(r.get("SCRIP_CD")) == job.scrip_code), None) + if row is None: + raise Unusable("That scrip code is not in the active BSE equity master.") + + with BSEClient() as client: + rec = build_one(client, row, progress=job.push) + + if rec is None: + raise Unusable("The issuer's records could not be read.") + + DATA.mkdir(parents=True, exist_ok=True) + (DATA / f"{rec['scrip_code']}.json").write_text(json.dumps(rec, indent=1)) + _refresh_index() + + ex = rec["extraction"] + job.result = { + "scrip_code": rec["scrip_code"], + "name": rec["bse"]["scrip_name"], + "cin": ex["cin"], + "pages": ex["pages"], + "year": rec["annual_report"]["year"], + "pl_fields": len(ex["audited_pl"]), + "bs_fields": len(ex["balance_sheet"]), + "identities": (ex["audited_pl_identities"] + ex["balance_sheet_identities"] + + ex["directors_pl_identities"]), + "isin_corroborated": rec["isin_corroborated"], + "warnings": ex.get("warnings", []), + } + job.push("done", f"Read {ex['pages']} pages and built a record for {ex['cin']}", 100) + job.status = "done" + + except Unusable as e: + job.error = str(e) + job.status = "failed" + job.push("failed", str(e), 100) + except Exception as e: # noqa: BLE001 + log.exception("ingest failed for %s", job.scrip_code) + job.error = f"{type(e).__name__}: {e}" + job.status = "failed" + job.push("failed", job.error, 100) + + +def start_ingest(scrip_code: str, name: str = "") -> Job: + """Begin (or re-join) a live ingestion for one issuer.""" + existing = _BY_CODE.get(scrip_code) + if existing and existing in _JOBS and _JOBS[existing].status == "running": + return _JOBS[existing] + + job = Job(scrip_code, name) + _JOBS[job.id] = job + _BY_CODE[scrip_code] = job.id + _POOL.submit(_run, job) + return job + + +def get_job(job_id: str) -> Job | None: + return _JOBS.get(job_id) + + +def _refresh_index() -> None: + """Rebuild the corpus index from whatever is on disk.""" + idx: list[dict[str, Any]] = [] + for p in sorted(DATA.glob("*.json")): + try: + r = json.loads(p.read_text()) + e = r["extraction"] + except Exception: # noqa: BLE001 + continue + idx.append({ + "scrip_code": r["scrip_code"], + "name": r["bse"]["scrip_name"], + "cin": e["cin"], + "isin": r["bse"]["isin"], + "industry": r["bse"]["industry"], + "sector": r["bse"]["sector"], + "year": r["annual_report"]["year"], + "pages": e["pages"], + "pl_fields": len(e["audited_pl"]), + "bs_fields": len(e["balance_sheet"]), + "dr_fields": len(e.get("directors_pl") or {}), + "identities": (e["audited_pl_identities"] + e["balance_sheet_identities"] + + e.get("directors_pl_identities", [])), + "isin_corroborated": r.get("isin_corroborated", False), + "warnings": e.get("warnings", []), + }) + idx.sort(key=lambda c: c["name"]) + INDEX.write_text(json.dumps({"companies": idx, "count": len(idx)}, indent=1)) diff --git a/app/backend/primarydraft/main.py b/app/backend/primarydraft/main.py new file mode 100644 index 0000000000000000000000000000000000000000..120ac08d81baa28b150c9335843474b631825c19 --- /dev/null +++ b/app/backend/primarydraft/main.py @@ -0,0 +1,395 @@ +"""PrimaryDraft HTTP service. + +REST plus one SSE endpoint that streams the disclosure ledger as it is built. +The service holds no correctness logic: verdicts come from `engine.rules`, which +has no LLM in it. +""" + +from __future__ import annotations + +import asyncio +import json +import logging +from pathlib import Path +from typing import Any + +from fastapi import Body, FastAPI, HTTPException, Query +from fastapi.middleware.cors import CORSMiddleware +from fastapi.responses import FileResponse, JSONResponse, StreamingResponse +from fastapi.staticfiles import StaticFiles + +from . import live +from . import pipeline as P +from .drafting.llm import llm_status, rewrite_sections +from .engine import rules as rules_mod +from .export.docx_export import build_docx +from .export.manifest import build_manifest +from .issue import IssueTerms +from .models import Run +from .store import STORE + +log = logging.getLogger("primarydraft") + +app = FastAPI(title="PrimaryDraft", version="1.0.0", + description="The IPO offer document that checks itself.") + +app.add_middleware( + CORSMiddleware, allow_origins=["*"], allow_methods=["*"], allow_headers=["*"], +) + +EXPORT_DIR = Path(__file__).resolve().parents[1] / ".exports" +FRONTEND = Path(__file__).resolve().parents[2] / "frontend" / "dist" + + +# ------------------------------------------------------------------ serialisers + +def run_summary(run: Run) -> dict[str, Any]: + return { + "id": run.id, + "scrip_code": run.scrip_code, + "company_name": run.company_name, + "cin": run.cin, + "status": run.status, + "created_at": run.created_at, + "fact_count": len(run.facts), + "fact_status": run.status_counts(), + "severity": run.severity_counts(), + "section_count": len(run.sections), + "coverage_pct": run.coverage_pct(), + "rule_count": rules_mod.rule_count(), + "rules_passed": sum(1 for r in run.rule_results if r.status == "pass"), + "rules_failed": sum(1 for r in run.rule_results if r.status == "fail"), + "rules_na": sum(1 for r in run.rule_results if r.status == "not_applicable"), + "open_findings": len(run.open_findings), + "resolved_findings": sum(1 for f in run.findings if f.resolved), + "meta": run.meta, + "source_documents": run.source_documents, + } + + +def run_full(run: Run) -> dict[str, Any]: + return { + **run_summary(run), + "facts": {k: v.model_dump() for k, v in run.facts.items()}, + "sections": [s.model_dump() for s in run.sections], + "rule_results": [r.model_dump() for r in run.rule_results], + "coverage": [c.model_dump() for c in run.coverage], + "decisions": [d.model_dump() for d in run.decisions], + } + + +def _get(run_id: str) -> Run: + run = STORE.get(run_id) + if run is None: + raise HTTPException(404, f"no run {run_id}") + return run + + +# ------------------------------------------------------------------- endpoints + +@app.get("/api/health") +def health() -> dict[str, Any]: + return { + "ok": True, + "rule_count": rules_mod.rule_count(), + "companies": len(P.load_index()), + "llm": llm_status(), + "engine_is_deterministic": True, + } + + +@app.get("/api/companies") +def companies(q: str = Query("", description="filter by name, CIN or industry")) -> dict[str, Any]: + idx = P.load_index() + if q: + ql = q.lower() + idx = [c for c in idx + if ql in (c.get("name") or "").lower() + or ql in (c.get("cin") or "").lower() + or ql in (c.get("industry") or "").lower() + or ql in str(c.get("scrip_code"))] + return {"companies": idx, "count": len(idx)} + + +@app.get("/api/search") +def search_companies(q: str = Query("", description="name, scrip code, ISIN or industry"), + scope: str = Query("sme", pattern="^(sme|all)$"), + limit: int = Query(40, ge=1, le=100)) -> dict[str, Any]: + """Search every active company on BSE, live.""" + try: + results = live.search(q, scope, limit) + live.enrich_filings(results) + counts = live.universe_counts() + except Exception as e: # noqa: BLE001 - offline is a normal condition, not a crash + raise HTTPException( + 503, + "The BSE scrip master could not be reached and is not cached locally, so " + f"live search is unavailable ({type(e).__name__}). The issuers already " + "prepared are still available.", + ) from e + return {"results": results, "count": len(results), "universe": counts, "scope": scope} + + +@app.post("/api/ingest") +def start_ingest(payload: dict[str, Any] = Body(...)) -> dict[str, Any]: + """Ingest an issuer we have not seen: download its filing and parse it.""" + scrip = str(payload.get("scrip_code") or "").strip() + if not scrip: + raise HTTPException(400, "scrip_code is required") + job = live.start_ingest(scrip, str(payload.get("name") or "")) + return job.to_dict() + + +@app.get("/api/ingest/{job_id}") +def ingest_status(job_id: str) -> dict[str, Any]: + job = live.get_job(job_id) + if job is None: + raise HTTPException(404, f"no ingestion job {job_id}") + return job.to_dict() + + +@app.get("/api/ingest/{job_id}/stream") +async def ingest_stream(job_id: str) -> StreamingResponse: + """Stream ingestion progress, so a slow real download is visible.""" + job = live.get_job(job_id) + if job is None: + raise HTTPException(404, f"no ingestion job {job_id}") + + async def gen(): + sent = 0 + while True: + while sent < len(job.events): + e = job.events[sent] + sent += 1 + yield f"event: progress\ndata: {json.dumps(e)}\n\n" + if job.status != "running": + yield f"event: {job.status}\ndata: {json.dumps(job.to_dict())}\n\n" + return + await asyncio.sleep(0.35) + + return StreamingResponse(gen(), media_type="text/event-stream", + headers={"Cache-Control": "no-cache", + "X-Accel-Buffering": "no"}) + + +@app.post("/api/runs") +def create_run(payload: dict[str, Any] = Body(...)) -> dict[str, Any]: + scrip = str(payload.get("scrip_code") or "").strip() + if not scrip: + raise HTTPException(400, "scrip_code is required") + try: + run = P.create_run(scrip) + except FileNotFoundError as e: + raise HTTPException(404, str(e)) from e + STORE.put(run) + return run_summary(run) + + +@app.post("/api/runs/from-cin") +def create_run_from_cin(payload: dict[str, Any] = Body(...)) -> dict[str, Any]: + """Start a run for an unlisted, pre-IPO issuer from its CIN.""" + cin = str(payload.get("cin") or "").strip() + if not cin: + raise HTTPException(400, "cin is required") + try: + run = P.create_run_from_cin(cin, str(payload.get("name") or "")) + except ValueError as e: + raise HTTPException(400, str(e)) from e + STORE.put(run) + return run_summary(run) + + +@app.get("/api/cin/{cin}") +def inspect_cin(cin: str) -> dict[str, Any]: + """Decompose a Corporate Identity Number without starting a run.""" + from .cin import parse_cin + return parse_cin(cin).to_dict() + + +@app.get("/api/runs/{run_id}") +def get_run(run_id: str) -> dict[str, Any]: + return run_full(_get(run_id)) + + +@app.get("/api/runs/{run_id}/ledger") +def get_ledger(run_id: str, status: str = "", section: str = "") -> dict[str, Any]: + run = _get(run_id) + facts = list(run.facts.values()) + if status: + facts = [f for f in facts if f.status.value == status] + if section: + facts = [f for f in facts if section in f.section_refs] + return { + "facts": [f.model_dump() for f in facts], + "count": len(facts), + "status_counts": run.status_counts(), + } + + +@app.get("/api/runs/{run_id}/ledger/stream") +async def stream_ledger(run_id: str, delay_ms: int = 18) -> StreamingResponse: + """Stream the ledger fact by fact, so the reviewer watches it being built.""" + run = _get(run_id) + + async def gen(): + facts = list(run.facts.values()) + total = len(facts) + yield f"event: start\ndata: {json.dumps({'total': total})}\n\n" + # Group order keeps related facts adjacent as they land on screen. + for i, f in enumerate(sorted(facts, key=lambda x: (x.id.split('.')[0], x.id))): + payload = {"index": i, "total": total, "fact": f.model_dump()} + yield f"event: fact\ndata: {json.dumps(payload, default=str)}\n\n" + if delay_ms: + await asyncio.sleep(delay_ms / 1000.0) + yield (f"event: done\ndata: " + f"{json.dumps({'total': total, 'status_counts': run.status_counts()})}\n\n") + + return StreamingResponse(gen(), media_type="text/event-stream", + headers={"Cache-Control": "no-cache", + "X-Accel-Buffering": "no"}) + + +@app.get("/api/runs/{run_id}/issue") +def get_issue(run_id: str) -> dict[str, Any]: + return _get(run_id).meta.get("issue", {}) + + +@app.put("/api/runs/{run_id}/issue") +def put_issue(run_id: str, payload: dict[str, Any] = Body(...)) -> dict[str, Any]: + run = _get(run_id) + for k in ("fresh_issue_value", "ofs_value", "total_issue_value", + "total_issue_shares", "net_proceeds"): + payload.pop(k, None) + try: + terms = IssueTerms(**payload) + except Exception as e: # noqa: BLE001 + raise HTTPException(400, f"invalid issue terms: {e}") from e + P.update_issue(run, terms) + STORE.put(run) + return run.meta["issue"] + + +@app.post("/api/runs/{run_id}/draft") +def make_draft(run_id: str, use_llm: bool = False) -> dict[str, Any]: + run = _get(run_id) + P.generate_draft(run) + if use_llm: + rewrite_sections(run) + STORE.put(run) + return { + **run_summary(run), + "sections": [s.model_dump() for s in run.sections], + "coverage": [c.model_dump() for c in run.coverage], + } + + +@app.get("/api/runs/{run_id}/draft") +def get_draft(run_id: str) -> dict[str, Any]: + run = _get(run_id) + return {"sections": [s.model_dump() for s in run.sections], + "coverage_pct": run.coverage_pct()} + + +@app.post("/api/runs/{run_id}/check") +def check(run_id: str) -> dict[str, Any]: + run = _get(run_id) + if not run.sections: + P.generate_draft(run) + P.run_checks(run) + STORE.put(run) + return { + **run_summary(run), + "rule_results": [r.model_dump() for r in run.rule_results], + } + + +@app.post("/api/runs/{run_id}/resolve") +def resolve(run_id: str, payload: dict[str, Any] = Body(...)) -> dict[str, Any]: + run = _get(run_id) + rule_id = payload.get("rule_id") + resolution_id = payload.get("resolution_id") + actor = payload.get("actor") or "Merchant banker" + if not rule_id or not resolution_id: + raise HTTPException(400, "rule_id and resolution_id are required") + try: + P.apply_resolution(run, rule_id, resolution_id, actor) + except ValueError as e: + raise HTTPException(400, str(e)) from e + # Re-draft so the document reflects the decision, then re-judge. + P.generate_draft(run) + P.run_checks(run) + STORE.put(run) + return {**run_summary(run), + "rule_results": [r.model_dump() for r in run.rule_results]} + + +@app.post("/api/runs/{run_id}/attest") +def attest(run_id: str, payload: dict[str, Any] = Body(...)) -> dict[str, Any]: + run = _get(run_id) + fact_ids = payload.get("fact_ids") or [] + actor = payload.get("actor") or "Merchant banker" + n = P.attest_facts(run, fact_ids, actor) + P.generate_draft(run) + P.run_checks(run) + STORE.put(run) + return {**run_summary(run), "attested": n, + "rule_results": [r.model_dump() for r in run.rule_results]} + + +@app.get("/api/runs/{run_id}/coverage") +def coverage(run_id: str) -> dict[str, Any]: + run = _get(run_id) + return {"coverage": [c.model_dump() for c in run.coverage], + "coverage_pct": run.coverage_pct(), + "covered": sum(1 for c in run.coverage if c.covered), + "total": len(run.coverage)} + + +@app.get("/api/runs/{run_id}/manifest") +def manifest(run_id: str) -> JSONResponse: + return JSONResponse(build_manifest(_get(run_id))) + + +@app.get("/api/runs/{run_id}/export/manifest") +def export_manifest(run_id: str) -> FileResponse: + run = _get(run_id) + EXPORT_DIR.mkdir(parents=True, exist_ok=True) + p = EXPORT_DIR / f"PrimaryDraft-Audit-Manifest-{run.scrip_code}-{run.id}.json" + p.write_text(json.dumps(build_manifest(run), indent=2)) + run.decisions.append(_export_decision("audit manifest")) + STORE.put(run) + return FileResponse(p, filename=p.name, media_type="application/json") + + +@app.get("/api/runs/{run_id}/export/docx") +def export_docx(run_id: str) -> FileResponse: + run = _get(run_id) + EXPORT_DIR.mkdir(parents=True, exist_ok=True) + p = EXPORT_DIR / f"PrimaryDraft-{run.scrip_code}-{run.id}.docx" + build_docx(run, p) + run.decisions.append(_export_decision("offer document DOCX")) + STORE.put(run) + return FileResponse( + p, filename=p.name, + media_type="application/vnd.openxmlformats-officedocument.wordprocessingml.document", + ) + + +def _export_decision(what: str): + from .models import Decision + return Decision(actor="Merchant banker", action="export", detail=f"Exported {what}.") + + +@app.get("/api/rules") +def list_rules() -> dict[str, Any]: + return { + "count": rules_mod.rule_count(), + "rules": [{"rule_id": rid, "title": title, "icdr_ref": ref} + for rid, title, ref, _ in rules_mod.REGISTRY], + } + + +# ------------------------------------------------------- static frontend (built) + +if FRONTEND.exists(): + app.mount("/", StaticFiles(directory=str(FRONTEND), html=True), name="frontend") diff --git a/app/backend/primarydraft/models.py b/app/backend/primarydraft/models.py new file mode 100644 index 0000000000000000000000000000000000000000..f3f71e949576c33899e871d9c352c4c201fb08ac --- /dev/null +++ b/app/backend/primarydraft/models.py @@ -0,0 +1,238 @@ +"""Core domain model for PrimaryDraft. + +The central object is the Fact: an atomic disclosure value bound to the real page +of the real filing it came from. A Fact with no provenance cannot exist: the +constructor requires at least one source. That constraint is what makes the +"the LLM never asserts an unsourced fact" claim structural rather than aspirational. +""" + +from __future__ import annotations + +import datetime as _dt +from enum import Enum +from typing import Any, Literal + +from pydantic import BaseModel, Field, field_validator + + +def _now() -> str: + return _dt.datetime.now(_dt.timezone.utc).isoformat(timespec="seconds") + + +class FactStatus(str, Enum): + """How much weight a fact can bear. + + VERIFIED corroborated by two independent sections, or supported by an + accounting identity that closes. + UNVERIFIED found once and unsupported: the abstain path. Carries a note + saying exactly what a human must confirm. Never silently promoted. + CONFLICTED two sources disagree. The engine raises a finding. + RESOLVED a human chose between conflicting sources. + ATTESTED a human signed off an unverified fact. Recorded in the manifest. + DERIVED computed from other facts; lineage in `derived_from`. + """ + + VERIFIED = "verified" + UNVERIFIED = "unverified" + CONFLICTED = "conflicted" + RESOLVED = "resolved" + ATTESTED = "attested" + DERIVED = "derived" + + +class Unit(str, Enum): + INR = "INR" + PCT = "PCT" + SHARES = "SHARES" + RATIO = "RATIO" + TEXT = "TEXT" + DATE = "DATE" + COUNT = "COUNT" + + +class Severity(str, Enum): + BLOCKER = "blocker" + HIGH = "high" + MEDIUM = "medium" + INFO = "info" + + +class Provenance(BaseModel): + """Where a value physically came from. Every field here is checkable.""" + + source_id: str + source_title: str + source_type: Literal["annual_report", "bse_api", "mca", "derived", "human"] + locator: str = "" # "p.72 ยท Statement of Profit and Loss" + page: int | None = None + raw_line: str = "" # the literal text line as printed in the filing + section: str = "" # "audited_pl" | "directors_report" | "balance_sheet" + url: str | None = None + extractor: Literal["deterministic", "identity", "llm", "derived", "human"] = "deterministic" + retrieved_at: str = Field(default_factory=_now) + + +class Fact(BaseModel): + """One atomic, sourced disclosure value.""" + + id: str + label: str + value: Any + unit: Unit = Unit.INR + status: FactStatus = FactStatus.UNVERIFIED + confidence: float = 0.5 + provenance: list[Provenance] = Field(default_factory=list) + section_refs: list[str] = Field(default_factory=list) + derived_from: list[str] = Field(default_factory=list) + note: str | None = None + period: str | None = None # "current" | "previous" + identities: list[str] = Field(default_factory=list) # identities supporting it + history: list[dict[str, Any]] = Field(default_factory=list) + + @field_validator("provenance") + @classmethod + def _require_source(cls, v: list[Provenance]) -> list[Provenance]: + if not v: + raise ValueError("a Fact must carry at least one Provenance") + return v + + @property + def is_load_bearing(self) -> bool: + return self.unit in (Unit.INR, Unit.SHARES, Unit.PCT, Unit.RATIO) + + def corroboration(self) -> int: + return len({(p.source_id, p.section) for p in self.provenance}) + + +class Evidence(BaseModel): + """One side of a contradiction, shown to the reviewer verbatim.""" + + label: str + value: Any + display: str = "" + fact_id: str | None = None + section: str = "" + locator: str = "" + raw_line: str = "" + + +class Resolution(BaseModel): + """A concrete, sourced way to fix a finding.""" + + id: str + label: str + description: str + recommended: bool = False + kind: Literal["adopt_value", "attest", "flag_to_banker"] = "adopt_value" + target_fact_id: str | None = None + new_value: Any = None + justification: str = "" + + +class Finding(BaseModel): + """One deterministic check result.""" + + rule_id: str + severity: Severity + title: str + explanation: str + icdr_ref: str = "" + evidence: list[Evidence] = Field(default_factory=list) + delta: str | None = None + resolutions: list[Resolution] = Field(default_factory=list) + caused_by: str | None = None + fact_ids: list[str] = Field(default_factory=list) + resolved: bool = False + resolved_by: str | None = None + resolved_at: str | None = None + + +class RuleResult(BaseModel): + """Outcome of one rule: including the passes, which are the reassurance.""" + + rule_id: str + title: str + icdr_ref: str = "" + status: Literal["pass", "fail", "not_applicable"] = "pass" + detail: str = "" + findings: list[Finding] = Field(default_factory=list) + + +class Decision(BaseModel): + """A human action. The audit manifest is a list of these.""" + + at: str = Field(default_factory=_now) + actor: str + action: Literal["resolve", "attest", "override", "generate", "check", "export"] + rule_id: str | None = None + resolution_id: str | None = None + fact_ids: list[str] = Field(default_factory=list) + detail: str = "" + + +class DraftSection(BaseModel): + """One rendered offer-document section.""" + + id: str + number: str + title: str + icdr_clause: str = "" + html: str = "" + text: str = "" + fact_ids: list[str] = Field(default_factory=list) + word_count: int = 0 + narrative_source: Literal["template", "llm"] = "template" + + +class ClauseCoverage(BaseModel): + clause_id: str + clause: str + title: str + covered: bool + section_id: str | None = None + reason: str = "" + + +class Run(BaseModel): + """One end-to-end pass over one real company.""" + + id: str + scrip_code: str + company_name: str + cin: str | None = None + created_at: str = Field(default_factory=_now) + status: Literal["ingesting", "ledger_ready", "drafted", "checked", "complete"] = "ingesting" + facts: dict[str, Fact] = Field(default_factory=dict) + sections: list[DraftSection] = Field(default_factory=list) + rule_results: list[RuleResult] = Field(default_factory=list) + decisions: list[Decision] = Field(default_factory=list) + coverage: list[ClauseCoverage] = Field(default_factory=list) + source_documents: list[dict[str, Any]] = Field(default_factory=list) + meta: dict[str, Any] = Field(default_factory=dict) + + # ------------------------------------------------------------------ helpers + + @property + def findings(self) -> list[Finding]: + return [f for r in self.rule_results for f in r.findings] + + @property + def open_findings(self) -> list[Finding]: + return [f for f in self.findings if not f.resolved] + + def severity_counts(self) -> dict[str, int]: + out = {s.value: 0 for s in Severity} + for f in self.open_findings: + out[f.severity.value] += 1 + return out + + def status_counts(self) -> dict[str, int]: + out = {s.value: 0 for s in FactStatus} + for f in self.facts.values(): + out[f.status.value] += 1 + return out + + def coverage_pct(self) -> float: + if not self.coverage: + return 0.0 + return round(100.0 * sum(1 for c in self.coverage if c.covered) / len(self.coverage), 1) diff --git a/app/backend/primarydraft/pipeline.py b/app/backend/primarydraft/pipeline.py new file mode 100644 index 0000000000000000000000000000000000000000..289ca3dd72a8a598ec351687486677a8b95a6fa3 --- /dev/null +++ b/app/backend/primarydraft/pipeline.py @@ -0,0 +1,499 @@ +"""Orchestration: real record -> ledger -> draft -> deterministic verdict. + +This module sequences the pipeline and applies human decisions. It holds no +correctness logic of its own: the verdict always comes from `engine.rules`. +""" + +from __future__ import annotations + +import json +import uuid +from pathlib import Path +from typing import Any + +from .cin import parse_cin +from .sources.mca import lookup as mca_lookup, to_float as _mca_float +from .drafting.templates import build_sections +from .engine import rules as rules_mod +from .engine.icdr import coverage_for +from .issue import IssueTerms, default_terms +from .ledger import build_ledger +from .models import ( + ClauseCoverage, + Decision, + Fact, + FactStatus, + Finding, + Provenance, + Run, +) + +DATA = Path(__file__).resolve().parent / "data" +COMPANIES = DATA / "companies" +INDEX = DATA / "index.json" + + +# ------------------------------------------------------------------- corpus IO + +def load_index() -> list[dict[str, Any]]: + if not INDEX.exists(): + return [] + return json.loads(INDEX.read_text()).get("companies", []) + + +def load_record(scrip_code: str) -> dict[str, Any]: + p = COMPANIES / f"{scrip_code}.json" + if not p.exists(): + raise FileNotFoundError(f"no real record for scrip {scrip_code}") + return json.loads(p.read_text()) + + +def source_documents(record: dict[str, Any]) -> list[dict[str, Any]]: + """The real documents this run is grounded in: shown on the intake screen.""" + ex = record["extraction"] + ar = record["annual_report"] + return [ + { + "id": f"ar_{record['scrip_code']}_{ar['year']}", + "title": f"Annual Report {ar['year']}", + "type": "annual_report", + "pages": ex.get("pages", 0), + "url": ar.get("url"), + "detail": (f"Filed with BSE ยท {ex.get('pages', 0)} pages ยท statements located on " + f"pages {ex.get('statement_pages', {})}"), + "real": True, + }, + { + "id": f"bse_{record['scrip_code']}", + "title": "BSE scrip master and company header", + "type": "bse_api", + "pages": 0, + "url": "https://api.bseindia.com/BseIndiaAPI/api/ListofScripData/w", + "detail": (f"Live BSE API ยท scrip {record['scrip_code']} ยท " + f"group {record['bse'].get('group')} (SME platform)"), + "real": True, + }, + ] + + +# --------------------------------------------------------------------- pipeline + +def create_run(scrip_code: str, issue: IssueTerms | None = None) -> Run: + record = load_record(scrip_code) + facts = build_ledger(record) + ex = record["extraction"] + + run = Run( + id=uuid.uuid4().hex[:12], + scrip_code=scrip_code, + company_name=record["bse"]["scrip_name"], + cin=ex.get("cin"), + status="ledger_ready", + facts=facts, + source_documents=source_documents(record), + meta={ + "annual_report_year": record["annual_report"].get("year"), + "annual_report_url": record["annual_report"].get("url"), + "pages": ex.get("pages"), + "isin_corroborated": record.get("isin_corroborated", False), + "identities_closed": (ex.get("audited_pl_identities", []) + + ex.get("balance_sheet_identities", [])), + "extraction_warnings": ex.get("warnings", []), + "statement_pages": ex.get("statement_pages", {}), + "scales": _scales(ex), + "industry": record["bse"].get("industry"), + "sector": record["bse"].get("sector"), + "bse_group": record["bse"].get("group"), + }, + ) + if ex.get("cin"): + # Mutate run.facts, not the local dict: the model copies on construction. + reg = add_registry_facts(run.facts, ex["cin"]) + run.meta["mca"] = {k: v for k, v in reg.items() if k != "record"} + run.meta["issue"] = (issue or default_terms(facts)).to_public() + return run + + +def _scales(ex: dict[str, Any]) -> dict[str, float]: + out: dict[str, float] = {} + for key, stmt in (("audited_pl", ex.get("audited_pl")), + ("directors_report", ex.get("directors_pl")), + ("balance_sheet", ex.get("balance_sheet"))): + if not stmt: + continue + for cols in stmt.values(): + cur = cols.get("current") + if cur and cur.get("scale"): + out[key] = float(cur["scale"]) + break + return out + + +def issue_from_run(run: Run) -> IssueTerms: + raw = dict(run.meta.get("issue") or {}) + for k in ("fresh_issue_value", "ofs_value", "total_issue_value", + "total_issue_shares", "net_proceeds"): + raw.pop(k, None) + return IssueTerms(**raw) + + +def generate_draft(run: Run) -> Run: + issue = issue_from_run(run) + sections, renderer = build_sections(run.facts, issue) + run.sections = sections + + drafted = {s.id for s in sections} + run.coverage = [ClauseCoverage(**c) for c in coverage_for(drafted)] # type: ignore[arg-type] + + run.meta["used_fact_ids"] = sorted(renderer.used) + run.meta["missing_fact_ids"] = sorted(renderer.missing) + run.meta["unbound_numbers"] = sorted( + {n for s in sections for n in renderer.unbound_numbers(s.html)} + ) + run.status = "drafted" + run.decisions.append(Decision( + actor="system", action="generate", + detail=(f"Drafted {len(sections)} sections from {len(renderer.used)} ledger facts; " + f"{len(renderer.missing)} tokens abstained for want of a source."), + )) + return run + + +def run_checks(run: Run) -> Run: + issue = issue_from_run(run) + ctx = { + "issue": issue, + # The CIN settles several eligibility questions on its own, before any + # financial statement is opened. + "cin": parse_cin(run.cin).to_dict() if run.cin else None, + "drafted_sections": [s.id for s in run.sections], + "used_fact_ids": run.meta.get("used_fact_ids", []), + "unbound_numbers": run.meta.get("unbound_numbers", []), + "scales": run.meta.get("scales", {}), + "meta": run.meta, + } + previously_resolved = { + (f.rule_id, f.title) for f in run.findings if f.resolved + } + run.rule_results = rules_mod.run_all(run.facts, ctx) + # Findings already dealt with stay dealt with across re-runs. + for f in run.findings: + if (f.rule_id, f.title) in previously_resolved: + f.resolved = True + run.status = "checked" + run.decisions.append(Decision( + actor="system", action="check", + detail=(f"Ran {rules_mod.rule_count()} deterministic checks: " + f"{sum(1 for r in run.rule_results if r.status == 'pass')} passed, " + f"{sum(1 for r in run.rule_results if r.status == 'fail')} failed, " + f"{sum(1 for r in run.rule_results if r.status == 'not_applicable')} " + "not applicable."), + )) + return run + + +# ------------------------------------------------------------ human decisions + +def _human_prov(actor: str, detail: str) -> Provenance: + return Provenance( + source_id="human", source_title=f"Decision recorded by {actor}", + source_type="human", locator=detail, section="decision", extractor="human", + ) + + +def apply_resolution(run: Run, rule_id: str, resolution_id: str, actor: str) -> Finding: + finding = next((f for f in run.findings + if f.rule_id == rule_id and not f.resolved), None) + if finding is None: + raise ValueError(f"no open finding for rule {rule_id}") + res = next((r for r in finding.resolutions if r.id == resolution_id), None) + if res is None: + raise ValueError(f"no resolution {resolution_id} on {rule_id}") + + detail = f"{res.label}: {res.description}" + + if res.kind == "adopt_value" and res.target_fact_id and res.new_value is not None: + fact = run.facts.get(res.target_fact_id) + if fact: + fact.history.append({"previous_value": fact.value, "by": actor, + "reason": res.label}) + fact.value = res.new_value + fact.status = FactStatus.RESOLVED + fact.confidence = 0.95 + fact.note = f"Adopted by {actor}: {res.justification or res.label}" + fact.provenance.append(_human_prov(actor, detail)) + + elif res.kind == "attest": + targets = ([res.target_fact_id] if res.target_fact_id else finding.fact_ids) + for fid in targets: + fact = run.facts.get(fid) + if fact and fact.status in (FactStatus.UNVERIFIED, FactStatus.CONFLICTED): + fact.history.append({"previous_status": fact.status.value, "by": actor}) + fact.status = FactStatus.ATTESTED + fact.confidence = 0.9 + fact.note = f"Attested by {actor} as confirmed against the audited records." + fact.provenance.append(_human_prov(actor, detail)) + + elif res.kind == "adopt_value" and res.id in ("scale_gcp", "cap_gcp", "cap_ofs", + "resize_issue"): + _apply_issue_patch(run, res.id) + + finding.resolved = True + finding.resolved_by = actor + from .models import Decision as _D + stamp = _D(actor=actor, action="resolve", rule_id=rule_id, resolution_id=resolution_id, + fact_ids=finding.fact_ids, detail=detail) + finding.resolved_at = stamp.at + run.decisions.append(stamp) + return finding + + +def _apply_issue_patch(run: Run, kind: str) -> None: + """Apply a structural fix to the proposed issue, then let the engine re-judge.""" + from .engine.icdr import Thresholds as T + + issue = issue_from_run(run) + if kind in ("scale_gcp",): + target = issue.net_proceeds + total = sum(o.amount for o in issue.objects) + delta = total - target + gcp = next((o for o in issue.objects if o.is_general_corporate), None) + if gcp is not None: + gcp.amount = round(gcp.amount - delta, 2) + gcp.schedule = {k: round(gcp.amount, 2) for k in list(gcp.schedule)[:1]} or {} + elif kind == "cap_gcp": + cap = min(issue.fresh_issue_value * T.SME_MAX_GCP_PCT_OF_PROCEEDS / 100.0, + float(T.SME_MAX_GCP_ABSOLUTE_INR)) + gcp = next((o for o in issue.objects if o.is_general_corporate), None) + if gcp is not None: + gcp.amount = round(cap, 2) + elif kind == "cap_ofs": + max_ofs_value = (issue.fresh_issue_value * T.SME_MAX_OFS_PCT_OF_ISSUE + / (100.0 - T.SME_MAX_OFS_PCT_OF_ISSUE)) + issue.ofs_shares = round(max_ofs_value / issue.price_per_share, 0) + elif kind == "resize_issue": + need = sum(o.amount for o in issue.objects) + issue.issue_expenses + issue.fresh_issue_shares = round(need / issue.price_per_share, 0) + + run.meta["issue"] = issue.to_public() + + +def attest_facts(run: Run, fact_ids: list[str], actor: str) -> int: + n = 0 + for fid in fact_ids: + f = run.facts.get(fid) + if f and f.status in (FactStatus.UNVERIFIED, FactStatus.CONFLICTED): + f.history.append({"previous_status": f.status.value, "by": actor}) + f.status = FactStatus.ATTESTED + f.confidence = 0.9 + f.note = f"Attested by {actor} as confirmed against the audited records." + f.provenance.append(_human_prov(actor, "attestation")) + n += 1 + if n: + run.decisions.append(Decision(actor=actor, action="attest", fact_ids=fact_ids, + detail=f"Attested {n} figure(s) as confirmed.")) + return n + + +def update_issue(run: Run, issue: IssueTerms) -> Run: + run.meta["issue"] = issue.to_public() + return run + + +# ------------------------------------------------- pre-IPO issuer, by CIN alone + +def add_registry_facts(facts: dict[str, Any], cin: str) -> dict[str, Any]: + """Add MCA register facts for a CIN, if the published snapshot reaches it. + + Used by both intake paths. For a listed issuer this is what gives paid-up + capital a second, independent authority to be reconciled against the audited + balance sheet. + """ + from .models import Fact, FactStatus, Provenance, Unit + + reg = mca_lookup(cin) + rec = reg.get("record") + if not reg.get("found") or not rec: + return reg + + rprov = Provenance( + source_id=f"mca_{cin}", + source_title=f"MCA Company Master Data ({reg['dataset']['title']})", + source_type="mca", + locator="data.gov.in ยท Ministry of Corporate Affairs", + section="mca_master", + url="https://api.data.gov.in/resource/" + reg["dataset"]["resource_id"], + extractor="deterministic", + ) + + def rf(fid, label, value, unit, refs, status=FactStatus.VERIFIED, note=None): + if value in (None, "", "NA"): + return + facts[fid] = Fact(id=fid, label=label, value=value, unit=unit, status=status, + confidence=0.95, provenance=[rprov], section_refs=refs, note=note) + + rf("co.name_registry", "Name of the Issuer (registry)", rec.get("company_name"), + Unit.TEXT, ["general_information"]) + rf("co.status", "Company status on the register", rec.get("company_status"), + Unit.TEXT, ["general_information"]) + rf("co.class", "Company class on the register", rec.get("company_class"), + Unit.TEXT, ["general_information"]) + rf("co.registered_office", "Registered office", rec.get("registered_office_address"), + Unit.TEXT, ["general_information"]) + rf("co.roc", "Registrar of Companies", rec.get("registrar_of_companies"), + Unit.TEXT, ["general_information"]) + rf("co.date_of_registration", "Date of registration", + (rec.get("date_of_registration") or "")[:10], Unit.DATE, ["our_business"]) + rf("cap.authorised_capital", "Authorised share capital (registry)", + _mca_float(rec.get("authorized_cap")), Unit.INR, ["capital_structure"]) + rf("cap.paidup_capital_registry", "Paid-up share capital (registry)", + _mca_float(rec.get("paidup_capital")), Unit.INR, ["capital_structure"]) + rf("co.email", "Email address on the register", rec.get("email_addr"), Unit.TEXT, + ["general_information"], FactStatus.UNVERIFIED, + "Read from a periodic registry snapshot; confirm it is current.") + return reg + + +def create_run_from_cin(cin: str, name: str = "") -> Run: + """Start a run for an issuer that is not listed, from its CIN. + + This is the path a genuine pre-IPO issuer takes. A private limited company has + no exchange filing history, so the only records that exist are the ones it + supplies itself. What a CIN encodes is real and citable; everything else is + absent until documents are uploaded, and the ledger says so plainly rather + than filling the gaps. + """ + from .models import Fact, FactStatus, Provenance, Unit + + parsed = parse_cin(cin) + if not parsed.valid: + raise ValueError(parsed.error) + + prov = Provenance( + source_id=f"cin_{parsed.raw}", + source_title="Corporate Identity Number issued by the Ministry of Corporate Affairs", + source_type="mca", + locator=f"CIN {parsed.raw}", + section="cin", + extractor="deterministic", + ) + + def fact(fid: str, label: str, value: Any, unit: Unit, locator: str, + status: FactStatus = FactStatus.VERIFIED, + refs: list[str] | None = None) -> tuple[str, Fact]: + p = prov.model_copy(update={"locator": f"CIN {parsed.raw} ยท {locator}"}) + return fid, Fact( + id=fid, label=label, value=value, unit=unit, status=status, + confidence=0.99 if status == FactStatus.VERIFIED else 0.6, + provenance=[p], section_refs=refs or ["general_information"], + derived_from=["co.cin"] if fid != "co.cin" else [], + ) + + facts = dict([ + fact("co.cin", "Corporate Identity Number", parsed.raw, Unit.TEXT, + "the identifier itself"), + fact("co.company_type", "Class of company", parsed.ownership, Unit.TEXT, + f"ownership class {parsed.ownership_code}, characters 13 to 15"), + fact("co.state", "State of the Registrar of Companies", parsed.state, Unit.TEXT, + f"state code {parsed.state_code}, characters 7 and 8"), + fact("co.incorporation_year", "Year of incorporation", parsed.year, Unit.COUNT, + "characters 9 to 12", refs=["our_business"]), + fact("co.nic_code", "Industry classification (NIC)", parsed.industry_code, Unit.TEXT, + f"{parsed.nic_division_name}, characters 2 to 6", refs=["our_business"]), + fact("co.registration_number", "Registration number with the Registrar", + parsed.registration_number, Unit.TEXT, "characters 16 to 21"), + fact("co.listing_status", "Listing status recorded in the identifier", + "Listed" if parsed.is_listed else "Unlisted", Unit.TEXT, + f"listing letter {parsed.listing}, character 1"), + ]) + + # Independent registry record, where the MCA snapshot reaches this company. + reg = add_registry_facts(facts, parsed.raw) + if False: + rec = reg["record"] + rprov = Provenance( + source_id=f"mca_{parsed.raw}", + source_title=f"MCA Company Master Data ({reg['dataset']['title']})", + source_type="mca", + locator="data.gov.in ยท Ministry of Corporate Affairs", + section="mca_master", + url="https://api.data.gov.in/resource/" + reg["dataset"]["resource_id"], + extractor="deterministic", + ) + + def reg_fact(fid, label, value, unit, refs, status=FactStatus.VERIFIED, note=None): + if value in (None, "", "NA"): + return + facts[fid] = Fact(id=fid, label=label, value=value, unit=unit, status=status, + confidence=0.95, provenance=[rprov], section_refs=refs, + note=note) + + reg_fact("co.name_registry", "Name of the Issuer (registry)", + rec.get("company_name"), Unit.TEXT, ["general_information"]) + reg_fact("co.status", "Company status on the register", + rec.get("company_status"), Unit.TEXT, ["general_information"]) + reg_fact("co.class", "Company class on the register", + rec.get("company_class"), Unit.TEXT, ["general_information"]) + reg_fact("co.registered_office", "Registered office", + rec.get("registered_office_address"), Unit.TEXT, ["general_information"]) + reg_fact("co.roc", "Registrar of Companies", + rec.get("registrar_of_companies"), Unit.TEXT, ["general_information"]) + reg_fact("co.date_of_registration", "Date of registration", + (rec.get("date_of_registration") or "")[:10], Unit.DATE, ["our_business"]) + reg_fact("cap.authorised_capital", "Authorised share capital (registry)", + _mca_float(rec.get("authorized_cap")), Unit.INR, ["capital_structure"]) + reg_fact("cap.paidup_capital_registry", "Paid-up share capital (registry)", + _mca_float(rec.get("paidup_capital")), Unit.INR, ["capital_structure"]) + reg_fact("co.email", "Email address on the register", + rec.get("email_addr"), Unit.TEXT, ["general_information"], + FactStatus.UNVERIFIED, + "Read from a periodic registry snapshot; confirm it is current.") + + if name.strip(): + facts["co.name"] = Fact( + id="co.name", label="Name of the Issuer", value=name.strip(), unit=Unit.TEXT, + status=FactStatus.UNVERIFIED, confidence=0.5, + provenance=[Provenance( + source_id="user", source_title="Name supplied by the user", + source_type="human", locator="entered at intake", section="intake", + extractor="human")], + section_refs=["general_information"], + note=("Supplied by hand and not corroborated against any register. Confirm " + "against the certificate of incorporation before filing."), + ) + + run = Run( + id=uuid.uuid4().hex[:12], + scrip_code="", + company_name=name.strip() or parsed.raw, + cin=parsed.raw, + status="ledger_ready", + facts=facts, + source_documents=[{ + "id": f"cin_{parsed.raw}", + "title": "Corporate Identity Number", + "type": "mca", + "pages": 0, + "url": None, + "detail": (f"{parsed.ownership}, incorporated {parsed.year} in {parsed.state}. " + "A registry identifier, not a financial record."), + "real": True, + }], + meta={ + "intake": "cin", + "mca": {k: v for k, v in mca_lookup(parsed.raw).items() if k != "record"}, + "cin_parsed": parsed.to_dict(), + "identities_closed": [], + "extraction_warnings": [ + "No financial statements have been supplied for this issuer. Every " + "financial disclosure in the draft will abstain until documents are " + "provided." + ], + "scales": {}, + "industry": parsed.nic_division_name, + "sector": "", + "bse_group": "", + }, + ) + run.meta["issue"] = default_terms(facts).to_public() + return run diff --git a/app/backend/primarydraft/sources/__init__.py b/app/backend/primarydraft/sources/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/app/backend/primarydraft/sources/bse.py b/app/backend/primarydraft/sources/bse.py new file mode 100644 index 0000000000000000000000000000000000000000..f1eb03c95383f96397c31845da22c76d89cda2b6 --- /dev/null +++ b/app/backend/primarydraft/sources/bse.py @@ -0,0 +1,155 @@ +"""Real BSE India public API client. + +Every endpoint here is a live, unauthenticated BSE endpoint. Nothing is synthesised. +Responses are cached to disk so a demo never depends on the network being up. + +Verified working (Aug 2026): + ListofScripData -> full active scrip master (4,949 rows; SME = groups M/MT/MS) + ComHeadernew -> per-scrip ISIN, face value, industry, sector, EPS/PE + AnnualReport_New -> per-scrip annual report PDF URLs, by year +""" + +from __future__ import annotations + +import json +import logging +import time +from pathlib import Path +from typing import Any + +import httpx + +log = logging.getLogger(__name__) + +API = "https://api.bseindia.com/BseIndiaAPI/api" +UA = ( + "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 " + "(KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36" +) +# BSE rejects requests without a browser Origin/Referer pair. +HEADERS = { + "User-Agent": UA, + "Origin": "https://www.bseindia.com", + "Referer": "https://www.bseindia.com/", + "Accept": "application/json, text/plain, */*", + "Accept-Language": "en-US,en;q=0.9", +} + +#: BSE trading groups that constitute the SME platform. +SME_GROUPS = {"M", "MT", "MS"} + +CACHE = Path(__file__).resolve().parents[2] / ".cache" / "bse" + + +def _cache_path(key: str, ext: str = "json") -> Path: + p = CACHE / f"{key}.{ext}" + p.parent.mkdir(parents=True, exist_ok=True) + return p + + +class BSEClient: + """Live BSE client with a read-through disk cache. + + ``offline=True`` serves only from cache: used on stage so the demo cannot be + broken by conference wifi. + """ + + def __init__(self, offline: bool = False, timeout: float = 45.0) -> None: + self.offline = offline + self._client = httpx.Client(headers=HEADERS, timeout=timeout, follow_redirects=True) + + def close(self) -> None: + self._client.close() + + def __enter__(self) -> "BSEClient": + return self + + def __exit__(self, *exc: Any) -> None: + self.close() + + # ---------------------------------------------------------------- internals + + def _get_json(self, key: str, path: str, params: dict[str, Any]) -> Any: + cp = _cache_path(key) + if cp.exists(): + try: + return json.loads(cp.read_text()) + except json.JSONDecodeError: + cp.unlink(missing_ok=True) + if self.offline: + raise FileNotFoundError(f"offline and no cache for {key}") + + last: Exception | None = None + for attempt in range(3): + try: + r = self._client.get(f"{API}/{path}", params=params) + r.raise_for_status() + data = r.json() + cp.write_text(json.dumps(data)) + return data + except Exception as e: # noqa: BLE001 - retry any transport/parse failure + last = e + time.sleep(1.5 * (attempt + 1)) + raise RuntimeError(f"BSE request failed for {key}: {last}") + + # ------------------------------------------------------------------- public + + def scrip_master(self) -> list[dict[str, Any]]: + """Full active equity scrip master. Real BSE data, ~4,949 rows.""" + return self._get_json( + "scrip_master", + "ListofScripData/w", + { + "Group": "", + "Scripcode": "", + "industry": "", + "segment": "Equity", + "status": "Active", + }, + ) + + def sme_universe(self) -> list[dict[str, Any]]: + """Active BSE SME-platform companies (groups M / MT / MS).""" + rows = [r for r in self.scrip_master() if (r.get("GROUP") or "").strip() in SME_GROUPS] + return sorted(rows, key=lambda r: (r.get("Scrip_Name") or "")) + + def company_header(self, scrip_code: str) -> dict[str, Any]: + """ISIN, face value, industry, sector, EPS/PE for one scrip.""" + return self._get_json( + f"header_{scrip_code}", + "ComHeadernew/w", + {"quotetype": "EQ", "scripcode": scrip_code, "seriesid": ""}, + ) + + def annual_reports(self, scrip_code: str) -> list[dict[str, Any]]: + """Annual report PDF URLs for one scrip, newest first.""" + data = self._get_json( + f"annrep_{scrip_code}", "AnnualReport_New/w", {"scripcode": scrip_code} + ) + rows = data.get("Table", []) if isinstance(data, dict) else [] + out = [r for r in rows if r.get("PDFDownload")] + out.sort(key=lambda r: str(r.get("Year") or ""), reverse=True) + return out + + def fetch_pdf(self, url: str, key: str) -> Path: + """Download an annual report PDF, cached on disk by key.""" + cp = _cache_path(key, "pdf") + if cp.exists() and cp.stat().st_size > 20_000: + return cp + if self.offline: + raise FileNotFoundError(f"offline and no cached PDF for {key}") + + with self._client.stream( + "GET", url, headers={**HEADERS, "Accept": "application/pdf,*/*"} + ) as r: + r.raise_for_status() + tmp = cp.with_suffix(".part") + with tmp.open("wb") as fh: + for chunk in r.iter_bytes(65536): + fh.write(chunk) + tmp.replace(cp) + + if cp.stat().st_size < 20_000: + cp.unlink(missing_ok=True) + raise RuntimeError(f"PDF too small / not a real report: {url}") + return cp diff --git a/app/backend/primarydraft/sources/corpus.py b/app/backend/primarydraft/sources/corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..a87906ec65ef60b6bf86f00cce1e77af4b84c3e4 --- /dev/null +++ b/app/backend/primarydraft/sources/corpus.py @@ -0,0 +1,223 @@ +"""Build the real company corpus from live BSE data + real annual-report PDFs. + +Run: python -m primarydraft.sources.corpus --target 30 + +For each company we keep only what a real source actually yielded. A company whose +annual report is a scanned image (no text layer) is skipped rather than filled in +an empty record would be a fabrication. +""" + +from __future__ import annotations + +import argparse +import json +import logging +import sys +import traceback +from concurrent.futures import ThreadPoolExecutor, as_completed +from pathlib import Path +from typing import Any + +from .bse import BSEClient +from .pdf_extract import extract_annual_report + +log = logging.getLogger("corpus") + +DATA = Path(__file__).resolve().parents[1] / "data" / "companies" +INDEX = Path(__file__).resolve().parents[1] / "data" / "index.json" + +#: A record is only usable if we recovered a CIN and a P&L that self-validates. +MIN_PL_FIELDS = 6 + + +class Unusable(Exception): + """The issuer's own records could not yield a usable record. + + Raised with a reason the user can act on, because "we could not read it" is a + legitimate outcome that must be reported rather than papered over. + """ + + +def build_one(client: BSEClient, row: dict[str, Any], + progress: Any = None) -> dict[str, Any] | None: + """Fetch + extract one real company. + + Returns None (batch mode) or raises Unusable (live mode) when the sources are + unusable. `progress(stage, detail, pct)` is called as the work proceeds. + """ + scrip = str(row.get("SCRIP_CD") or "").strip() + name = (row.get("Scrip_Name") or "").strip() + + def step(stage: str, detail: str = "", pct: int = 0) -> None: + if progress: + progress(stage, detail, pct) + + def give_up(reason: str) -> None: + log.info("%s (%s) unusable: %s", scrip, name, reason) + if progress: + raise Unusable(reason) + + if not scrip: + return None + + step("header", "Reading the company header from the BSE master", 5) + try: + header = client.company_header(scrip) + except Exception as e: # noqa: BLE001 + log.warning("%s header failed: %s", scrip, e) + header = {} + + step("reports", "Listing the annual reports this issuer has filed", 12) + try: + reports = client.annual_reports(scrip) + except Exception as e: # noqa: BLE001 + log.warning("%s annual reports failed: %s", scrip, e) + give_up("The BSE annual-report index could not be reached for this issuer.") + return None + if not reports: + give_up("This issuer has no annual report filed on BSE, so there are no " + "records to read.") + return None + + latest = reports[0] + step("download", f"Downloading the {latest.get('Year')} annual report from BSE", 22) + try: + pdf = client.fetch_pdf(latest["PDFDownload"], f"ar_{scrip}_{latest.get('Year')}") + except Exception as e: # noqa: BLE001 + log.warning("%s pdf download failed: %s", scrip, e) + give_up("The annual report PDF could not be downloaded from BSE.") + return None + + mb = pdf.stat().st_size / 1_000_000 + step("extract", f"Reading the filing ({mb:.1f} MB). This is the slow part.", 45) + try: + ex = extract_annual_report(pdf, scrip) + except Exception as e: # noqa: BLE001 + log.warning("%s extraction failed: %s", scrip, e) + give_up(f"The annual report could not be parsed ({type(e).__name__}).") + return None + + step("verify", f"Checking what {ex.pages} pages actually yielded", 88) + if not ex.cin: + give_up("No Corporate Identity Number could be read from this filing. It is " + "almost certainly a scanned image with no text layer, so nothing in it " + "can be cited. PrimaryDraft will not guess at the contents.") + return None + if len(ex.audited_pl) < MIN_PL_FIELDS and len(ex.directors_pl) < MIN_PL_FIELDS: + give_up("No machine-readable financial statement was found in this filing. " + "Rather than publish figures it cannot cite, PrimaryDraft declines to " + "build a ledger for this issuer.") + return None + + api_isin = (header.get("ISIN") or "").strip() or None + return { + "scrip_code": scrip, + "bse": { + "scrip_name": name, + "issuer_name": (row.get("Issuer_Name") or "").strip(), + "group": (row.get("GROUP") or "").strip(), + "segment": (row.get("Segment") or "").strip(), + "isin": api_isin or (row.get("ISIN_NUMBER") or "").strip() or None, + "face_value": row.get("FACE_VALUE"), + "industry": (row.get("INDUSTRY") or "").strip(), + "sector": (header.get("Sector") or "").strip(), + "industry_new": (header.get("IndustryNew") or "").strip(), + "market_cap": row.get("Mktcap"), + "eps_reported": header.get("EPS"), + "pe_reported": header.get("PE"), + "security_id": header.get("SecurityId"), + }, + "annual_report": { + "year": latest.get("Year"), + "url": latest["PDFDownload"], + "authorised_at": latest.get("Fld_AuthoriseDate"), + "local_path": str(pdf), + "available_years": [r.get("Year") for r in reports[:8]], + }, + "extraction": ex.to_dict(), + # Independent corroboration: the ISIN printed in the company's own annual + # report versus the ISIN BSE holds on its master. Two sources, one fact. + "isin_corroborated": bool(api_isin and ex.isin and api_isin == ex.isin), + } + + +def build(target: int, candidates: int, workers: int, offline: bool) -> None: + DATA.mkdir(parents=True, exist_ok=True) + client = BSEClient(offline=offline) + universe = client.sme_universe() + log.info("BSE SME universe: %d active companies", len(universe)) + + # Prefer larger SMEs: they file richer, better-structured annual reports. + def mcap(r: dict[str, Any]) -> float: + try: + return float(str(r.get("Mktcap") or 0).replace(",", "")) + except ValueError: + return 0.0 + + pool = sorted(universe, key=mcap, reverse=True)[:candidates] + log.info("attempting %d candidates for %d slots", len(pool), target) + + built: list[dict[str, Any]] = [] + with ThreadPoolExecutor(max_workers=workers) as ex: + futs = {ex.submit(build_one, client, r): r for r in pool} + for fut in as_completed(futs): + row = futs[fut] + if len(built) >= target: + break + try: + rec = fut.result() + except Exception: # noqa: BLE001 + log.warning("worker crashed for %s\n%s", row.get("SCRIP_CD"), traceback.format_exc()) + continue + if not rec: + continue + built.append(rec) + path = DATA / f"{rec['scrip_code']}.json" + path.write_text(json.dumps(rec, indent=1)) + e = rec["extraction"] + log.info( + "[%2d/%d] %-42s CIN=%s pl=%d bs=%d ids=%d", + len(built), target, rec["bse"]["scrip_name"][:42], e["cin"], + len(e["audited_pl"]), len(e["balance_sheet"]), + len(e["audited_pl_identities"]) + len(e["balance_sheet_identities"]), + ) + + index = [ + { + "scrip_code": r["scrip_code"], + "name": r["bse"]["scrip_name"], + "cin": r["extraction"]["cin"], + "isin": r["bse"]["isin"], + "industry": r["bse"]["industry"], + "sector": r["bse"]["sector"], + "year": r["annual_report"]["year"], + "pages": r["extraction"]["pages"], + "pl_fields": len(r["extraction"]["audited_pl"]), + "bs_fields": len(r["extraction"]["balance_sheet"]), + "identities": (r["extraction"]["audited_pl_identities"] + + r["extraction"]["balance_sheet_identities"]), + "isin_corroborated": r["isin_corroborated"], + } + for r in sorted(built, key=lambda r: r["bse"]["scrip_name"]) + ] + INDEX.write_text(json.dumps({"companies": index, "count": len(index)}, indent=1)) + log.info("wrote %d real company records -> %s", len(index), DATA) + client.close() + + +def main() -> int: + ap = argparse.ArgumentParser() + ap.add_argument("--target", type=int, default=30) + ap.add_argument("--candidates", type=int, default=90) + ap.add_argument("--workers", type=int, default=6) + ap.add_argument("--offline", action="store_true") + a = ap.parse_args() + logging.basicConfig( + level=logging.INFO, format="%(asctime)s %(levelname)s %(message)s", stream=sys.stdout + ) + build(a.target, a.candidates, a.workers, a.offline) + return 0 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/app/backend/primarydraft/sources/mca.py b/app/backend/primarydraft/sources/mca.py new file mode 100644 index 0000000000000000000000000000000000000000..aa617f6163721102e9e700b738a43f795798bb15 --- /dev/null +++ b/app/backend/primarydraft/sources/mca.py @@ -0,0 +1,191 @@ +"""MCA Company Master Data, via the open government data platform. + +The Ministry of Corporate Affairs publishes company master data as state-wise +datasets on data.gov.in. They are official, free, and queryable by CIN. One row +carries several disclosures an offer document needs on its cover page and in its +capital structure: + + corporate_identification_number, company_name, company_status, company_class, + company_category, date_of_registration, authorized_cap, paidup_capital, + registered_office_address, registrar_of_companies, email_addr, + latest_year_ar, latest_year_bs + +The paid-up capital here is the second, independent source for a figure the +audited balance sheet also states, which is exactly what lets the ledger mark it +verified instead of merely read. + +KNOWN LIMITS, stated plainly and measured rather than assumed: + * the snapshots run to 31 March 2021, so a company incorporated after that is absent + * they are PARTIAL extracts, not the complete register, so a miss proves nothing +A hit is therefore real evidence and a miss is silence. The module never treats a +miss as a fact about the company. +""" + +from __future__ import annotations + +import json +import logging +import re +from pathlib import Path +from typing import Any + +import httpx + +log = logging.getLogger(__name__) + +BASE = "https://api.data.gov.in" +#: The platform's published sample key, documented for open access. +API_KEY = "579b464db66ec23bdd000001cdd3946e44ce4aad7209ff7b23ac571b" + +CACHE = Path(__file__).resolve().parents[2] / ".cache" / "mca" +CATALOG = CACHE / "catalog.json" + +#: Two-letter code in a CIN -> the state name used in dataset titles. +CIN_STATE_TO_NAME: dict[str, str] = { + "AP": "Andhra Pradesh", "AR": "Arunachal Pradesh", "AS": "Assam", "BR": "Bihar", + "CH": "Chandigarh", "CT": "Chhattisgarh", "DL": "Delhi", "GA": "Goa", + "GJ": "Gujarat", "HR": "Haryana", "HP": "Himachal Pradesh", "JH": "Jharkhand", + "JK": "Jammu", "KA": "Karnataka", "KL": "Kerala", "MH": "Maharashtra", + "ML": "Meghalaya", "MN": "Manipur", "MP": "Madhya Pradesh", "MZ": "Mizoram", + "NL": "Nagaland", "OR": "Odisha", "PB": "Punjab", "PY": "Puducherry", + "RJ": "Rajasthan", "SK": "Sikkim", "TN": "Tamil Nadu", "TZ": "Tamil Nadu", "TG": "Telangana", + "TS": "Telangana", "TR": "Tripura", "UP": "Uttar Pradesh", "UR": "Uttarakhand", + "UT": "Uttarakhand", "WB": "West Bengal", +} + +_YEAR_RE = re.compile(r"(\d{4})\s*$") + + +# data.gov.in stalls on a default client but answers a browser-shaped request +# in well under a second. Same handling the BSE client needs. +HEADERS = { + "User-Agent": ("Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 " + "(KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36"), + "Accept": "application/json, text/plain, */*", + "Accept-Language": "en-US,en;q=0.9", +} + + +def _client() -> httpx.Client: + return httpx.Client(timeout=20.0, follow_redirects=True, headers=HEADERS) + + +def _get(path: str, params: dict[str, Any], attempts: int = 2) -> dict[str, Any] | None: + """GET with retries. The platform is intermittently slow, and an unavailable + registry must degrade to 'we could not check' rather than break a run.""" + import time + + for i in range(attempts): + try: + with _client() as c: + r = c.get(f"{BASE}{path}", params=params) + if r.status_code == 200: + return r.json() + log.info("data.gov.in %s -> %s", path, r.status_code) + except Exception as e: # noqa: BLE001 + log.info("data.gov.in %s attempt %d failed: %s", path, i + 1, type(e).__name__) + time.sleep(1.0 * (i + 1)) + return None + + +def catalog(refresh: bool = False) -> dict[str, dict[str, Any]]: + """Map state name -> the most recent Company Master Data dataset for it.""" + CACHE.mkdir(parents=True, exist_ok=True) + if CATALOG.exists() and not refresh: + try: + return json.loads(CATALOG.read_text()) + except json.JSONDecodeError: + CATALOG.unlink(missing_ok=True) + + found: dict[str, dict[str, Any]] = {} + for offset in (0, 100, 200): + data = _get("/lists", { + "api-key": API_KEY, "format": "json", "limit": 100, + "offset": offset, "filters[title]": "company master data", + }) + if data is None: + break + if True: + for rec in data.get("records", []): + title = rec.get("title") or "" + if "company master data" not in title.lower(): + continue + for code, state in CIN_STATE_TO_NAME.items(): + if state.lower() in title.lower(): + m = _YEAR_RE.search(title.strip()) + year = int(m.group(1)) if m else 0 + prev = found.get(state) + if prev is None or year > prev["year"]: + found[state] = { + "resource_id": rec["index_name"], + "title": title, + "year": year, + } + break + + if found: + CATALOG.write_text(json.dumps(found, indent=1)) + return found + + +def dataset_for_cin(cin: str) -> dict[str, Any] | None: + code = cin[6:8].upper() if len(cin) >= 8 else "" + state = CIN_STATE_TO_NAME.get(code) + if not state: + return None + return catalog().get(state) + + +def lookup(cin: str) -> dict[str, Any]: + """Look one CIN up in the MCA master data. + + Returns `{"found": bool, "record": โ€ฆ, "dataset": โ€ฆ, "note": โ€ฆ}`. A miss is a + result, not an error: for a company incorporated after the snapshot, absence + is the correct and honest answer. + """ + cin = (cin or "").strip().upper() + ds = dataset_for_cin(cin) + if ds is None: + return {"found": False, "record": None, "dataset": None, + "note": ("No MCA master dataset is published for the state in this CIN, " + "so no independent registry record could be consulted.")} + + key = CACHE / f"{cin}.json" + if key.exists(): + try: + return json.loads(key.read_text()) + except json.JSONDecodeError: + key.unlink(missing_ok=True) + + data = _get(f"/resource/{ds['resource_id']}", { + "api-key": API_KEY, "format": "json", "limit": 5, + "filters[corporate_identification_number]": cin, + }) + if data is None: + # Unreachable is not the same as absent, and must not be cached as absent. + return {"found": False, "record": None, "dataset": ds, "unreachable": True, + "note": ("The MCA dataset could not be reached, so the registry could not " + "be consulted. This is not evidence that the company is absent " + "from it.")} + records = data.get("records", []) + + out = { + "found": bool(records), + "record": records[0] if records else None, + "dataset": ds, + "note": ("" if records else + f"This CIN is not in '{ds['title']}'. That snapshot runs to {ds['year']} " + "and is a partial extract rather than the complete register, so absence " + "from it is NOT evidence that the company is not registered. No registry " + "figures were used for this issuer."), + } + CACHE.mkdir(parents=True, exist_ok=True) + key.write_text(json.dumps(out, indent=1)) + return out + + +def to_float(v: Any) -> float | None: + try: + return float(str(v).replace(",", "").strip()) + except (TypeError, ValueError): + return None diff --git a/app/backend/primarydraft/sources/pdf_extract.py b/app/backend/primarydraft/sources/pdf_extract.py new file mode 100644 index 0000000000000000000000000000000000000000..8d7eec6068b7d4108b59ec1757992b5455bd3f2e --- /dev/null +++ b/app/backend/primarydraft/sources/pdf_extract.py @@ -0,0 +1,589 @@ +"""Extract structured disclosure data from real annual-report PDFs. + +Everything returned by this module is traced to a real page and a real source line +in a real filing. Nothing is synthesised: if a value cannot be found, it is absent, +and the ledger records that absence as an abstention rather than a guess. + +Design notes from real BSE SME filings: + * numbers carry Indian digit grouping AND stray internal spaces ("1 ,52,170") + * scale is declared per-statement, not per-document ("(Rs in '000)", "(โ‚น in Lakhs)") + * the SAME figures appear in two independent places: the audited Statement of + Profit and Loss, and the "Financial Results" table in the Directors' Report. + We extract BOTH and let the deterministic engine reconcile them. That pair is + the real cross-section check at the heart of the product. +""" + +from __future__ import annotations + +import re +from dataclasses import dataclass, field +from pathlib import Path +from typing import Any + +import pdfplumber + +# --------------------------------------------------------------------------- regex + +CIN_RE = re.compile(r"\b([LU]\d{5}[A-Z]{2}\d{4}[A-Z]{3}\d{6})\b") +ISIN_RE = re.compile(r"\b(INE[A-Z0-9]{9})\b") +PAN_RE = re.compile(r"\b([A-Z]{5}\d{4}[A-Z])\b") +DIN_RE = re.compile(r"\b(?:DIN|D\.I\.N\.?)[\s:\-]*(\d{8})\b", re.I) +EMAIL_RE = re.compile(r"\b[\w.\-]+@[\w\-]+\.[\w.\-]+\b") + +# A number token. PDF text extraction inserts stray spaces AROUND separators +# ("1 ,52,170") but a space between two bare digit groups is a COLUMN break +# ("19 85,728" = note 19, then value 85,728). So spaces are only tolerated +# adjacent to a comma or decimal point: never between plain digits. +# Indian grouping puts 2 or 3 digits after each comma, never 4, and the lookahead +# stops a date ("March 31, 2025") being swallowed as the number 312025. +NUM_RE = re.compile(r"\(?\s*-?\s*\d+(?:\s*,\s*\d{2,3}(?!\d))*(?:\s*\.\s*\d+)?\s*\)?") + +# Scale is declared in a statement header, in many dialects: "(Rs in '000)", +# "(โ‚น'000)", "(Amount in Lakhs)", "โ‚น in millions". The apostrophe form carries no +# "in" at all, so it needs its own pattern. +# Real headers seen in filed reports: "(Rs in '000)", "(โ‚น'000)", "(Rs in Lakhs)", +# "(All amounts are in Indian Rupees lakhs, except share data)". A bare word match +# is what survives that variety: scanned only over the header region of a page so +# a passing mention in a note cannot rescale a statement. +SCALE_PATTERNS: list[tuple[re.Pattern[str], float]] = [ + (re.compile(r"\bcrores?\b", re.I), 10_000_000.0), + (re.compile(r"\blakh?s?\b|\blacs?\b", re.I), 100_000.0), + (re.compile(r"\bmillions?\b|\bmn\b", re.I), 1_000_000.0), + (re.compile(r"['โ€˜โ€™\"]\s*000\b|\bthousands?\b|\bin\s*000\b", re.I), 1_000.0), +] +#: Lines from the top of a page within which a scale declaration is believed. +SCALE_HEADER_LINES = 16 + +LAKH = 100_000.0 + + +def parse_number(tok: str) -> float | None: + """Parse a PDF-extracted Indian-format number. Returns None if not numeric.""" + t = tok.strip() + neg = t.startswith("(") and t.endswith(")") + t = t.strip("()").replace(",", "").replace(" ", "").replace("\u00a0", "") + if t in {"", "-", "--", ".", "NIL", "nil"}: + return None + try: + v = float(t) + except ValueError: + return None + return -v if neg else v + + +def detect_scale(text: str) -> float: + """Detect the rupee scale declared in a statement header.""" + header = "\n".join(text.splitlines()[:SCALE_HEADER_LINES]) + for pat, mult in SCALE_PATTERNS: + if pat.search(header): + return mult + return 1.0 + + +def trailing_numbers(line: str, limit: int = 4) -> list[float]: + """Pull the trailing numeric columns off a financial-statement line.""" + out: list[float] = [] + for m in NUM_RE.finditer(line): + v = parse_number(m.group()) + if v is not None: + out.append(v) + return out[-limit:] if len(out) > limit else out + + +def value_columns(line: str) -> list[float]: + """The (current, previous) value columns of a statement line. + + Indian statements print `