jUdZddlZddlZddlmZmZmZmZdZdZ dZ dZ dZ d d d d d ddddd ddddd ddddd ddddd dddd d dd d!dd d"d#d$dd gZ eeeefed%<d d d&d d d&ddd&ddd&ddd&ddd&ddd&ddd&d d!d&d d!d&d#d$d&d#d$d&d' Zeeeeeffed(<d)eeefd*eeeefd+eeeeffd,Zd-eeeefd+eeeffd.Zd+eeeffd/Zy)0z Evidence builder for AI categorization predictions. Extracts evidence signals from a product record and its attributes, then writes evidence rows to the database. Each evidence record maps to a source_type defined in the schema. N)ListDictAnyOptionalpart_number_patternmanufacturer_categoryenrichment_attributeproduct_description category_rulez ^(CB|CAB)- cat_cableszCables & Connectorsg?)patterncodelabelstrengthz ^(R|RES)\d cat_resistors Resistors?z ^(C|CAP)\dcat_capacitors Capacitorsz ^(IC|U)\dcat_icszIntegrated Circuitsgffffff?z ^(SW|BTN)- cat_switcheszSwitches & Buttonsz ^(PSU|PWR)- cat_powerzPower Suppliesz ^(LED|DIODE)- cat_diodesz Diodes & LEDsz ^(FAN|COOL)- cat_coolingzCooling & Thermal_PART_NUMBER_PATTERNSrr) cable connectorresistor capacitor semiconductoricswitchpowerleddiodethermalcooling_MANUFACTURER_CATEGORY_MAPproduct attributesreturnc g}t|jdxsdj}t|jdxsdj}t|jdxsdj}|xs|}|retD]\}t j |d|tj s,|jtdd|d|d d d |d |d |d dn|r_|j}tjD]8\} } | |vs |jtdd|d| d d dd| d | d dn|D]|} t| jdxsdj} t| jdxsdj} | r| s`|jt| | ddddd~|S)u  Build a list of evidence signal dicts for a product. Each returned dict has: source_type (str), source_label (str), evidence_value (str), weight (float 0.0–1.0), signal_strength (float 0.0–1.0), suggested_category_code (str), suggested_category_label (str) Args: product: Dict of product DB row columns. attributes: List of product_attribute DB rows for this product. Returns: List of evidence signal dicts (may be empty if no signals found). skumpnrr zPart Number PatternzSKU 'z$' matches the pattern for category 'r'g?rr source_type source_labelevidence_valueweightsignal_strengthsuggested_category_codesuggested_category_labelzManufacturer CategoryzManufacturer category 'z ' maps to 'gffffff?rattribute_nameattribute_valueg333333?g?N)strgetstriprrematch IGNORECASEappendSOURCE_PART_NUMBER_PATTERNlowerr)itemsSOURCE_MANUFACTURER_CATEGORYSOURCE_ENRICHMENT_ATTRIBUTE)r*r+signalsr.r0r identifierrulemc_lowerkeywordmappingattr attr_name attr_values 9/var/www/html/ai_cats/python/services/evidence_builder.pybuild_evidencerR8s  %'G gkk% &B ' - - /C gkk% &B ' - - /C ,C D JKQQSJ) DxxYR]]C/I/D |, M?!-03/3J/?/3F|/3G}   "(..0 : @ @ B  GW("/K/F12G1HI$$+G$4#5Q804/3/6v/6w/?   "  "23:;AAC "34:;AAC  'B'0'1'+'*'+(,    NrHc4i}|D]d}|jd}|s|jdd|jddz}||vs ||d|ksL|||jd|d||<f|sdd d St|jd }|d |dd S)u Choose the best suggested category from the evidence signals. Picks the category with the highest combined weight × signal_strength among signals that carry a category suggestion. Returns: {"code": str, "label": str} — falls back to generic defaults. r8r6gr7scorer9)rUrrcat_uncategorized Uncategorizedrc |dS)NrU)xs rQzpick_category..s ajrS)keyrr)r=maxvalues)rHscoredsrwbests rQ pick_categoryrcs)+F  uu./  EE(C 155):C#@ @ v g!6!:94@F4L  +oFF v}}$8 9DL4= 99rSctdddddddS)z@Return the standard fallback evidence signal (confidence floor).FallbackzFNo specific evidence found; prediction based on default category rulesgMbP?g?rVrWr2)SOURCE_CATEGORY_RULErYrSrQfallback_signalrgs#$8#- T#(#$3  rS)__doc__jsonr?typingrrrrrCrFrGSOURCE_PRODUCT_DESCRIPTIONrfrr<__annotations__r)rRrcrgrYrSrQrms ,, 4654.H\mpq;HXmpq <mqr=H[mpq /tDcN+ +8MN*8MN- D. E'8MN'8MN,8LM)8HI*H*H+8KL+8KL 9Dd38n!45  LDcNLT#s(^8LLQUVZ[^`c[cVdQeL^:4S#X/:DcN:< c3h rS