From 29ad9e2265954b3697468b3f114a1cb83cc59a1f Mon Sep 17 00:00:00 2001
From: bolade <babawale030@gmail.com>
Date: Fri, 21 Nov 2025 12:15:42 +0100
Subject: [PATCH] sighh

---
 app/report_gen/page_8.html                    |   4 +-
 .../context_generator.cpython-312.pyc         | Bin 40877 -> 43566 bytes
 .../graph_generator.cpython-312.pyc           | Bin 46387 -> 49398 bytes
 .../report_generator.cpython-312.pyc          | Bin 22047 -> 22040 bytes
 app/services/context_generator.py             | 576 +++++++++++++++---
 notebooks/test_page_5_rmr.py                  |   6 +-
 6 files changed, 487 insertions(+), 99 deletions(-)

diff --git a/app/report_gen/page_8.html b/app/report_gen/page_8.html
index 8e17b38..52cb11f 100644
--- a/app/report_gen/page_8.html
+++ b/app/report_gen/page_8.html
@@ -27,7 +27,7 @@
                 <img
                     src="data:image/png;base64, {{ vo2_max_table }}"
                     alt="VO2 Max Table"
-                    class="w-full max-w-4xl h-auto object-contain"
+                    class="w-full max-w-4xl h-auto"
                 />
             </div>
         </div>
@@ -43,7 +43,7 @@
                 <img
                     src="data:image/png;base64, {{ hr_zones_table }}"
                     alt="Heart Rate Zones Table"
-                    class="w-full max-w-4xl h-auto object-contain"
+                    class="w-full max-w-4xl h-auto"
                 />
             </div>
         </div>
diff --git a/app/services/__pycache__/context_generator.cpython-312.pyc b/app/services/__pycache__/context_generator.cpython-312.pyc
index a4f5275fe33c926fe055410f78d7f62d86627e4d..b291d4c95624efa3c7613421626d428c18c51108 100644
GIT binary patch
delta 17432
zcmch93v^r8ao~IS0|Y^k1VE4=NPvIvCw@gz)Q>-rlql+JS(atfATLN!0zv5k`oRx|
z(%KE3I4S6tR8%Y<)5)f$<9wKElQL}@(`mZvZPNx%NJ|7&Q>N|7F57NPSvg6gv+dcL
z`v4G>Kh5d(?6Wv;X71d%b3gCixpOc4mA7SI{h`e8C)wFL2A<=Cj_I23&l{}l(0p}u
z*^KIpie(5(6khcijf@#&i1K-csNRyHFvFbD&U^n-rAWwoeAk5`wz4u?;xi9E!!pcG
z#>1Rp33En9*fVk>d!9L?&@!Y<c$sZ2EF*f4%A+lW3`FPAPAW+D^U5<>kosfxYhfku
z3MN&=_PpYZm6$x*q)ai;g{079Aw?dP(SnQ}ctsSKkrKddS_VofCt8pw^#JrJCuOvp
ztr8tjc5$j~kkCpJlRDxAE9{Eva#zKjm*jC-fgTLxuv!Tn=W&xU&$S7Umoo^@s_Z33
zOfw-cBd`GQD*!m);c|s<sy@c%-|1ApAZLTZcXT!F4oC~?PxT#XshRQan3?vuI481{
zr%u**U0gZh+EW8H$+R+{xeCFS)tQ4<B-9hL-peySKUXA-XLYhh;gzfwRW1tI@5Hk1
zu{tzU4u208h5d(YiU|9$Vc~Ucf$-1Svnu~DdD(f5a9^E&=epr7wt*OeN`~PTB!^d$
z>|hoY4I=<~QVKEN*73}k7Su6}kdtQ<mW(#}7|9bNMvLMK!yOaWjRzGdEEw~w!v0*X
z`2$ta)Qh=lAwSQ`nuYqjFB+#>@7?%8&KKDITpcKP>4cx;9ct50x&vb~ZohxbJMK?p
zdp&Mnn&d`6jvGaA1i?|74SM1A{LbtgBvc&jj4t7)`8(NM!EPFm{WU8P(_!|m@H?jO
z3NM@Uc2qVlJC~<c<zJr>Tl&Px{?)5u<>-BLR%Kp9@k66?vxYI6)^Z$Tjw7mZY~~0X
z=Dor*mVLsz78CU2Us);?Cr?9J2{q@r=ygwcxW~{IIyU6q*$M6#CMx{_Zu%m30&&$9
zxA(FK`imy`W&=Jq*MfOk0l3tX$xjQ9*-8t~P!UO94LA-VcwiKL%663X-}$lap_&~L
zepDVcJPpZy>}H4K2BiOP#X<JRf~>No6&rIy1%SJO;9~$>S(1@-{K#kA*Enpggld{x
zL*jxkRoRzCTMo5yv%)tjJB=YkClEY`;CbO+E32VRE35k1*Y2FJ+9ik9_@b*)rspAf
zl*74zyDt1iorAq8{G!g$NDEU=`-taSLhkkWxC<bWP>|`#Np22>u{}5+05H!e4Ahsg
zA>my8?g}g}p}rDm8RKTJ`e8^y71Iw#NBWDxyY)5f|Gsm-KASb>qaJE4HFW-tp|M1s
zbse}HSWWJh(9wK?Jt%y#xn$>5D}DZ9-_#_1{%M~}#yyTwbo_uJk0?V@5dOM(T>8Xb
z5(ZmbY}TDiE&s?u{hx08dvzCWaO?@L9sxGQD2K&!UqbL32yP(2uHbqRyoq2*_}K1x
z!$Z}XS)a$zw(%9<JrsU__cLK^Iqp>iA4hN-K^ua01g{{#wv_BXh1e$nB(xsi<rxp>
z4tTip$n+vp>A&cm4$$%DvP!l4Ch~Kx%(jeOyzKRR#{Aydiyp24xmM%~pWD-3@iuB$
zMV^Lmvlqu;s3bAy6z+LU6@&+Sc*8r0eiwk>3P8B@oLLE-1taq2-VwI)&fo3*3-t~h
zAzTmv9VO2q_B8|t5mW&f<$eoM+G;n2jRWKCo5ILohlT(bK9QjC$w984whJ9PwEDE>
zw1;VvU@y9IwyMZQP~$uTS~M;78$!=elj_I7OjreR&?J0vXo&V~!YO1AJB5csZS0G8
zb`1ZVRpGFjV1-L<raSu%{h?e%ZCkjbIa0u~4+Y23g2tqA+s#TSCT1^Qmpbhv7EbNT
z=ZtqeM=MzPfIe|-l>O$NA06|^U;ynq*(K|vnrTxUM#EH-o*B2-vw`2oMmd0o%9foC
zt?e5X$iRMjsBGQY(AK`uh>Q+o2)}>oQ))V@tgLYGafdMb__Nh$SVD0Q)+=e`(6*wj
zh7*`%7)(Dx?&)HcRJ_o7x(ZA@b9!9%bN0@6PVZ&I^y^9+H-Y0k^%wv_`oZU*TW^Ac
zz_SywYqASqIHx4iTji6nj89JFA-QjqD7Hx`sboq*1rmFRdYgpiLKu~$M6@7MPjuTv
zvbHJFgM^J_Z<8==lgI%H&_E0q`a!dt7=f0dc_f$Qk$hqzW?~@)#Clsz3Q19z*hn$4
zlM+%&St%h0aGaD=22MsrGF#;~4$4#|In|)2h9Jj9IkmS{q>j|nd<~?L?4aB_(nOj`
z3uz#&q>XY;6q0tblXQ?y(nWTqm35QdWDnU(_9e6JCq2OFC4Hoyat6qOwCX|1!2*YF
z%R&lXCOmVd*){wYEA=BMBL{sfITTXz3SL<VOkR#Kq?%?zYF;JGdy7Z=nWst^<}CDc
zNJF7Eq~morw7m8ehK#%_<JG)oH)MLrL^+3f9q>nARiyb21*iqy5ne`)3SXVD3d<)o
zqrf<ZLge^u*$KvVB6v@in(6!8-igazn9Ll<J^sM7Z^|*`adQF3ab$6xNe}1oO?Vsu
z_qf;NAnt&>Q74F#wl?>aXP4usJ236>1sp)66{6xP4=hLAR=Py%gs(qYBD{0W5(fD(
z&h4A>INUzspqM|cU?UGIxPeXcP}$ts(9+K3KofFC1i1+E5ac5;AuuDbASeK^(Fqy3
zpV8dyI~#VkKa}rmuXD*Z(0v$%_YsB(!xRsqK+q3vr-UECj2#l*i+HDm??Jpv!fO!U
zg}6GQI66DaJ<RU)cxSIVdal5VFy%?8lgPvDp7Gf$o-|)EI6F%c+5z-uy<uoGkPMvj
zdIBD>;sj_#({Nhi`lOPE5$~7q0mKI=PHV;;knm09V^tw<E#k<4g%(*!>!o&*_!~G+
zVmV>z+YL!du*Tdl#W$KTBdwlngSt*hg=hztl*d*{8ne-c@>E8}H6x$)5A7A~3$7JG
z8vrQuxKuc{Ftq<+iMbaQNNvltpztW=bKQs|12P^$nWX$6;zuMI%*Gv+aN7M+-i>;c
zK?bzMFA$enl!{V@D=gdS!vrbw#y-T4(+nG3h@X(~9f+Tl@FB#L-2oFC!<~}&`w@R!
z!gnElTEd$Ve}dwY5mE(cHZF{2fputbGBYhFRr?=d=48P~0f#=L1Cx7FQaFP7q}E9&
za1G-Oz)7$(+*wRPBB&g{IOC|}mQWQgSV5VihPnk0Sy%W?8CQonRMMyCQgGDO*7*bQ
z>HDuv2hJsw(*e(nKcT#Q5u6tE98pnveUh?kxpUmu#5u^5&`F>8*agpZ?io~VoSfxm
z+<}0HNME`?p_zawWonkYp6FA<Zfp$P?}QrsVnjaB{Y(^&O{8Y0F)WHsLSr}y1#5*b
zAF~&2<JG~e>GuP;!E9QE`X`!%ktdA!7mjBeBQ2je9k<$F9A3AU&JAzs8GCiSvLRkd
zVR1#==>q(Ij;1JY)AXO67XFVawdUP_itR8PHUsSci%sGGUlo<?Eil~ovzJ)2Zce*7
zDQ6s2;n(<E{439`m3E4yoh$i2EZsAIYPEAt7tbwP*d^vxEnXLMo99%UDyFz3s<FoF
zTfR2(=Ezq^MSacOkZ7riTwPShb1ZY=cvHvH^%Z5bVQ<vvShU_X)~-_yyHdSUxLO`<
zIFRCRYMF-aO#@@ETIgOJ8DFw2vu_rDt@O>(m}^(GrhBD1TDT`}sk*O}8+DtET&v@#
z8w!Ib{bT_~y{_}HOGmGZ$h=HQCTx~kgq)A7gp<$Mg?}!!3QyFTgjY*7EGtA$nzI#e
z!QjUSmU+stDbpMkujFLB$}gK{PB0K3$Pz?#zD+??xYiLhMg-Eb>QuTpnVwG3q*Ihc
zgE`YF+Ej{7C8ZGUHl4audSNm>oimHqg!HLY`=ffZd0oiBXN7W765%cVndKY7WmNO}
zNjU+1d^WuGyp}h>8#M4a@CGfsaZ)~|4CPKSB<J&ND32JQXF~Z?Ovn_-24(c&b5oY}
zGZFTw7m^;4`7HED$Py}$g{;^Oda333f(vJ1M+A(#B*TiHXb?IgRETUHUx@7#D&mWT
z`<*6-{~-@3$)(MnhyE$WC>^r#HWX6$Lx6}cn81J1DvNpB`F!Cg+M;mC9>C}mefVPD
zp4q@8?*a@UPR$pS{8tpj^r|dW0zR-rnR$DXs|c0I7(So3rz%Muz0#0_a*MZdouM+m
zly_bLzk|!+9sH3pit6}MaOo_(gA_nP)>jpwa-W%ZQeGM5nYT$4zN!HU1t|)Z5Ob&;
zDsRIopD(~V6@@BDF<(Kgv%e}2RYG#fR<eVXV!SF;MI3w;6>@@5H3*e$35|xp=?)-G
zAHF743oxmi&*ROQ^a=xpx_riz8DL5!{8f{R3<+7t#hV0&#}wu*843$B6q+;m)(n0n
zxVR;JIbX?F^Da_#Tb)W{VHCYIr(j4mZ<=Po0j>!SZTY>#6L3#^J;X8Nfnd^v-vKL^
z!{ZK5oO8gQ4qRc}>N|oMJs5ZUL2lOPa8Cp-yS>yOP6i_A-g_%Lavkc+y@B8s0`$(3
z5s2pGyM_A>rhI!VrQM|r77Y^*C_e7?h0(!oZf|I5a*RVPG;q$Jk%(z6P2d}USXz5S
z>xboQZGug1I-fONAnI&us!OGWCz3N67|1XR_`@mk!8m}M3=i`m-R`m1Wq`{uk{N=)
zHP6zqB7+4h`S7w-FNEZoT%rs@@Qf%hXIetR%X!5lZc$Xha8=)|54`Gt!++5Otv>B@
z%v?O@2+TSzLNt())4m-SW@!6^gM@Q81ykJ7?~eTC+rQjLJyR*@$x6F$CB$jQKnuPu
z%)sm77<eKHIlK_~{a_43cSc;U3D86~Eqg35JBEb@_X#5{#bF!@W68nNxEo@T;J@r`
z+$Q-8u*Q!*<_%^&$F#tHA{Z~Q#Z83^gY!q`2I3~mf_eVn+`zp&bHpRm&h;U3dEwIh
z^~GM%QWeXqp6iR}TNdPz&bcFWY2t2zvZ>GAf+u|ITl=^KkU;}fMb}d481_wgr+psk
z>^)?6CFD&lB$x#?gXV!f8W^tEZKE18b5)`$WzUtVUAmzD0#*it<(DD6RShW{*z;1d
zBWRg|q_9ud=jO&8j|HZ^(?Qq)&ic5YqmVW=baX*kgN}Nguuam^=JL5`JP8%}Yv7h*
zunc-Mp};mpx6nJwO?&(h(E+sytu)$UC&~$+)nz~zH*k(ihkvG|s2m1Z63R(0Y{Ixd
z1Y8ON%fWOS&P&MM<9;a~^EgVX+~COih^saua&-enDGgsGvSu#^roofOP-rT~DSYbX
z;;@cd-#i9c6B6E%fwyMhZ5ep`77hXSX@4M*KaJn@m{hl<N6cM@@{{d@POTK~qg$Lm
z!wUTXcdA%>|AmB_+Ce50dTE^bJ+#TRP~9=9HMQtUC()!#fJ<P%)3FO9d<*vj4$|2E
zl%K-ENvAxBswXt=D^p{GI2;oCR2Pk5LKY@qSNX@Lu=lv}Ep~FIO6Zam1$jTteHgD4
zZak+-{guN<MnlYrf(#!&^TP_(;I~$q$@*jbs6G!qzzybaHTmE!7TAQ{!!=>Ra%^jc
z646kya5-kEoRh~5Mce3~<mBBdU(Yv#=dWU{#W#cV!Nt00<9@NMXSG)>I}j@voYTV>
znwbzQ=-uL#FJ2JKT4DvQkFu7Ji{Y}4SV8Bb2~>97>;yO0TzK=${Fz1h;vvz|6f-v?
zi}K%>xZEN-+GFOOb2_loV2SXHXQKM1c((bYuy8tgGfQRB&FS7Vs!DZHjqN?7Mq3Qq
z8FRs$_FiS<QgE$um#BBn^@usnh$7-yII(WB-W-`9i8@<FQ`?GCH0_BSO*i%P`lx+}
zXlz>U6OA4B<ua3DuAesdP4B#Su?<}Exxw}PqMLhO-m_j>6<)l$bXBbGSSc5)_lTu?
zSFVbsgAr)X^0flj-2zwKQNQMB!m2x3BE#FMzbhzO=mP)W))XsfUhcbF&=Ie0TFzgb
zT^@^84BXPLC#hr0*H`nGXIFvy*n;-HifQa#>54TBh^E>|_~4@MM-98uG?42B&c!o#
z3wA6YT&=y^HWIIDT0Fa)yS!^<BHGfsS{E%Jy`_N)IcgWYOU|W(%l>E`><L!Rtc<+N
zzFQl8>~wVaiA{z*!`1?{*WH&hh0aYK<7@)^OUoidkhi#eaj$4=S+jM7MO#PA))mpj
zoz+VkF#fsav(eJth#sU$s}?=Cd}}4mVo7tXq;=UXmUKk2;`Xw|?j?V;tToztFlsv#
zL1Rj*qE($@N!MD*Ua@3vtYm*AYu#eI-M5$(E3S{)8kWvPI}g3vBX*8PJB~z6N5QCE
z+op!GhwCHSxUB@r2h;Q^ELy&E`I1=P6)oEpwRcB!>w5E=zF5>3uRAO6IV%<)`$Ey8
zeyQin6U*gqom)BsO;FMuw^zksFYKsC=&Xb7aBkku<+^Oc<_ybJb#L~|m|W{ZVKk>a
zswtOtOz<^^;ro^zj1d5XdGKSH*rY8JkrM?`5*1NHTvS8gWSL|UJ;|oDf#eWlG9HZS
z>6kD?gpmd}H60X2+5w?pDGXdm)2m1|1bf3SQVTI&6sU)YF2;B<x{GuRjqgf<U8JSp
zt`yWodhcyrNDe{jebjN6ll>uuuL$U#B;5;i9?*SBx*uo^Y7Zpo13=4EWH1@+Eq0J0
z>YvNVFob#!VyG7!;6uC;Twi%e#mfcvAyW|#2pK_-_$_o=;0dWA2CU)L7y}MN3>ZRK
zQuLQXT__7;z&di6&myC*C?E=~;k7ghZ056WKztav<VXhJndBW!=8&gzG%DZ}n%9tH
zG!T3|*w&YdusBW~X>lBOUkhi%dNUl}WUN*S^SETA|MO4350AcYKe%46Lw6_X14w@!
zX<D%x!$^MtX?h^&A3^%Rq-o(O(q9C6)TMf;J>}u9haDJK<#q!vp*Y~4=D7WUay>|E
zPF#j))buR3Wk3%qcoPz(0#~U)UqYH5JpMK{2p!BMO%3{Tn*Qlw%>NajA;>n0I$${8
z*o(}sq7b$E4lU$sY1-e9>C0&)Rf9->9ckJs-#>)(?*L7eQm?IW7xM0;^Zb;S@n4aq
z=|7@ne1ir@QFE#Qn)n2@`kN_*(wXW`RQS87Kx%4Qz)D(S;eJg27SdF{su$_s+matZ
z`uBm}GV<2${SX}GzMWR`BdX*N(wX+t=KT)RROwHtlDE_84DH`lptqD3c49&App0}X
z428(J?*dJ&100Rypy~|Z-w30iq@4EM9|BF4NnJr}{XNWpRfP=rqJ0H8?J}t~XmkD%
zq$O)l4gGIGQ(clwI~wxe(=tD$hKAoohEy1}^navjKW&XaPSdS)9Q+B;TS}Q$RQi43
zacCvr)L86zz-j+W<AL`7p8{Lz|0jAe-=AUskGgb0E$;5R95shsK`n0Bl4x5~Lt7GU
zZ)#|lQ1wpOwNc4rrUR~rsZ0kTe=-xI$xMJsnGU$PY%n3Hq&aEWJsech0=Yvpfo7&V
zsi2bP4$7f88fXs6u~2ypDCvU+<$eGe9<saX-h}%-<k0Bz7_eP(8e!(>spvQ|^p8Z8
z6M8%o2d^|t1H1_}o)KX**#puEc{;AF;ynJ#-T*fRZ0;O_X#jrQ9XK)`$+@&=IG0KF
znL*@6*kJ}d*8+nc*gUxdvs@#{3(vG@!tWP801KP{XHXPGmvu}@ZQNRs{AYK?i)-#@
ztBVYqdH+cX;Sbei{m(1pL(3>Kgg>MvR>S=hvSX}OH>ck`Cu8(Ek-SfI#x3?22U8*T
zkHW#70l%@N;x+Fr?<>A#)!mYv^N+0zU?A8U(JtgJ>{_Ug8mi~y>)~AcTCP*fbuN}K
z^2>+B>ix0Y9vUIeGtH?!B0yYO1<t5{aVA>c7Ewj6-8DK;cWJz;VQFIVsb%LDe?7%o
z9$e{L-V-hFNoLs0W*WM>p#h4VaZB-|5n>ns=?8bl)ZO_sgbi*ou!OTjxTtMVaKA%j
z!X<6JjQd>jMwrb&<QOl(ML#5iqv4<Qo0R@CIHVPhO%!5`(J2pTQ<`~sDk1{Dh5}c5
z-`9y!(zrwTn8wN$3gU!gSdo!MK~$Nclyt`Pc+{U%LU`spekhMT=X3C)S|xaAX@5ld
zp^`m2O+xV{o$xO?#rwgdQ4u}$cp$b7_u8Nx;Fw<tIKA%%5ucB!6Uo6EsUj>_PK+s3
zCvjz5L$c*8xjEQqBo~W8ObW!xe1(vufTdAcMXE_v{>yN~P9{W@rk!wUZZIQOD<erg
znGsuP|2%A7d{f;tAgY4nc-eWlx1!GPP!pqcSuv!^sEa0}fAVSn9LY$PL3NTR@22+&
z?g(gw*VQE%GU4~hD2WOBj4H;yqk~2cKBJj7u$EXtI#K{mp`6zS(fTZ`Q%E1M0YRT_
z1IUU7W~6B|$}5DlLz#(L8Hq)-Y0%%bJ)%ONAyrJJFsf<~)(d}fwLE;$H!EEgNXQQl
zoDAv*25K;@w1c>>yQC1-t^4~D8g7OgLq3NAsOd!*J5$v7i#PX6HxN5<cBg0J2E_1e
zbHf568#FX0KR$4rgE7HONj}#<f=XbGkruf5mdJ-?A~1%R9Km6nfb(`(P9*iK$M;JJ
z6Wu3yPRyn-!;`Q<3NbZ-N*YU&f=Be$;jdx&k6i2d7nJ*TNRaOLLD-4jmcn3@D_dIJ
zW>Lh2B66r~LWQvykB55_*;ubc)`WM~kA}jvuSV`HvJ^gu^>TlM1^xuV-vaRC$w<cH
zM(=&iJ$F3(ZCsSzg-ry68DVBr!!}Z%8|lYA{hFypgnwBzOHZ!^-sZo>ukAY_!oP+S
z@k0A+#kYzV$s69+z02)lRoBW1v1-3q*fV!9o^M~vFTa~#9=A9aOGHc4nx$Q|w8tzR
z5&6BUx~0A^oR6p%ba##AP?RZLws`W5v#+0BtLzftUw&8I?tJa+t+PvwqP=U)zDKn0
ziP`r>4&1BVv8-A#eLXu?yEihpaPY3FdcC$OiGiX*`<m4yT3u__2GQEEbZ$i!vv$u7
zL*Qi1TqT;T*37k{xpt{@`E<;@cg@@{n)_qs19Jy3@?*3tSnlSO#x13bW%Isy`MQLF
zxn<Q$@-NiR4Mq-%`qKBc%w1@i(<`R8i@#O8)^%9yI()a`FzluwMBD$`$gPpJ;wBOP
z<u`4@HrtFLk%g1AYL%iL<0AGB(bySYGwu<Mdwyu#w+=C$v-4*qb7SV3O*NBU0Dgk0
zL~73UeCxu&wc<t*{^d8`YiL?7S{V?Vdsk10%|o$<;mE;-AjC4_W%WyE#Inw{vVCIN
zzF1jL<WRh%<~83f-_nySHPMD%v7|3Dc&~leO2?h2BZDMb+<e#6@-r2)vwLON>N&Cd
z$XfSFvHN7K`&6v`@yK90y`^J0@Vori`PCt@<M3L?ak1lgtm9;?`LT#PYHhe{Y=rh{
zY?&L3np~p37Kj{6<h*EbLMTo6&aYkCNjLim)fDHxc+Q{5q3<!+3rcR&1bn;c2NxK+
zDwY@o*Yn5ZO4#)}KW;X_sb_k5QSpMi#4M~mpCf$ld6V$Zg<3gme+99$M5dh<{_Rr^
zq2dLi&=K`+!SO<oVEnjJc<Y7XTpgj?UZR67vIAzkEP?&BJwJ<N;Vek>w`H*H&4w*+
zmeBm^24Va+UIG>7v<exq2(N#lfGrS?z2wZclDw2TycP^B$ST@Ko3kPI@CXO4r)}p5
zfA;Y#8O?6CL1-eCNXl<(!ITP|8A)YGFTC@~f@4*wIg>NM{<|6{b-0jKg>O7FAvJVz
z*Qe5m>lH-+Ph98&+**`O>3D_V^+NbJY-}A?ro4WuGNj?Q63T9*v$BTlz+A-miUOLd
zz}!Ts<{-=%q#4VD=tK*q*xr{yTCq_vZXwKnyg=RtSJ5xMSSoL)Zzn5J9TJ!AL@S(K
z8CLANtpO{#sTFWFo?8cp!i*~_^sI$#5=vjN<?N<4N`*kO(GE4`N#~MbvL_i#*$csx
zeFX2`NjL8XrqpmColOp)0(cM7YVF@f^=zYhw^4oDsQzu#08&%xDK?ay183AjpJxFz
z@(STthpC*;;SIcz43mRjKJ->{&|@_*4;i7A6-qs3=-^aGg>v~^9RA_MDGoG-2^5dw
z;WxaGKmiOn`gt~B2PO0&mXvHi^P5={vMFXl_7p4uu;S;E!_?X=TH-N;^Rkz66d)1G
z`X~+I4^eUaS6A^N8czI58p0n{kCVTWijUIp*uSR%qB{RhW1iZsVoDRrCy!6D#Dd?+
z76zSl`t$4-{n3~t4Z7qeX$b9xga16<^dUp&iR4#%25ouY4Dh5-_fjQ$7QZ#?QyJgd
z)3+5c2*;%1_c4zd=8)6?3YqDY*M)fopV`X8n~59CfbV}C;)Z52ffT&SHm---F?m}B
z`lqOV=DZWX;+(A#EbwKQ<2?dZr~uGPMDc<KPPI>Axpn8Z$|ch<Nn5_i@&)i`g+CoR
zPxUIeKZ4BFA2~x5J~~6l&bx5u626eCF5I!Da|K@YfZ4)JW{8jAUENve0vlhLoG}WM
zGln!rq$n?Kf)q8gjq+`yr1>Ky*-z(AP%ceFvnV>Hfmx%NT!is+3H~@7LpYxT*Dei&
zy>NTP26sXpolDMRcH+lI$@rcFsTw}A@?Cyp<-3e4AA1EG-*h#j*{|J}LsMT*uZ2fR
zFu7hnOPgPJ0%j1F&LUU;1DJ~!{@~MZy9dE&4lk|-wUxb&N>cBrd;%gr$WEyJmpOU}
ztbn6VI10Xq@ttM}d39l`Hh^AmMoJ5$;L5<QqyUNvfAyOMdhQzf#q<hm;^l~?q8Aky
z$7jj)On)DKqlB6{4B2p_!mh|6;Ws07;lBoQ`X2NKw~p9VOhrF?n#xhP8xJq2+dVx7
zaxQI#o`1!pe?x$Js0ztTry0>zPgbm*8lTWiUYQshhpKT`(UvOssT{+tA$m>t_IxFK
zRrs6vCmXLI;~;`s1Q;~iz<smyyOy^Q`!a&BAo!|q;blj-4vYU1(vKzsFY`wy((O#C
zwL7;qQ$ckP1oR<tmqZS`xZg&V7<K2~K(HS{4}v8Gw7_QobEzMy%fsU>p7F^Rz$V-A
zKh6Ms^+6!0E^i~G$<ut&rG(!k;UPEfuVCW?*PzGX7k0B8953TfCp>VI6v>3a@4n(0
zbNk2evdzx6ME15=oOCB3tmM3C6&y=3Ti0kfAKIr3Ru0cx<lyqPAMfvY1Lvem=AH>)
zan~IaZaCte4qOkGrN!WI|1#W!osh1h!=}+O4uchLAOx*xnH~=}J3c+(n4AvyJYl~-
zqZ9~QPS0GPallTKUV24E=~AltJy+m{_(i|tgT(OqJ3Xuiv#ssza9zF9F*}LJFd5hI
zgVvqx4IP;&VZ4@f9KNHVwX><AGcze8rM;oE^MllxyP7_L&EbVP?pXvpf)Ik|5MV?e
zI#N1ya4DhJyCx?m2x;L=(Ct!6*F+oeCptYlC%QN@uoDKj?188EektOb{Be-*?#neQ
zoV2)Sg`dBCp!aP=;|Nv}yo2Do0O0e@LM=w@{p4i=I+i(_BSTntPAHTW$%I>iZEu2|
z<o2M+dlBqI(2F1&RMFwNp$6RvdT*ItCZ@j{+rTXgw}Tbl5vo<vq#^v1u(R0AJ%tH0
zX6;ApGYB?NVUDo>Ggc4o^|?PsnqHqaB{xK#WQ-XuluUWJ*D(E)DEUJK{|iAD@){7F
zN8kqFDv@FawEVwE?$apw53KOwXZD1@33wt4BPPjvM{w~%ie3AqTO$f=th{ZX%Gk7T
za#orPVCdo3MSspJg6@PNC7JpJGw)d>jOngRW^yF5(=7am6FF&8QXu@pXO1377`85H
z)3Wu_Y2ldHJ?`;>`H(585TZXoP*u7l8)gDO{Prb%RYV5?4=IXo7Q&x33*OJxWU~-*
z_5YiO2I0ZO`0Vv;2oabnMN{SCq-bgos(<TW;D=0h=UQ=tSlqBQDHgZKZN+g%)f>9k
zb<w&#D_qRc3&-?t6un*)t>3qr7jyQ<9d&Qyyq*(n>Rs)RIfmo*n%Bl|jV+C>OvLQH
z@roU99C`gnwC&)#eX)w88M1vb$56b)_1f&M*=Xb5RYk01;C{ZYM5mq8M69BwXtU_f
z|5@0>hTpR=dK;X%uQ~ffXCGXzSTj0BqjRxRG}bIttkrglwcRU2V(q{Kxvb0()tA7n
zWs`L+ze3EfSUe5Eg0=iMF~2RAzjLMLZhkMG`WLO6OX5ab+-OPt1H5Q6Usr0FJF;2C
zn5!3`6-}*iQ`O?NuxM&pw&BGNq>!+Prp{l1*p{bAH0|ER+W?z#U9n+q<UOl|ml)<o
zH?2%-FT2)qN^Cg=_gdoC>UeQ2-Xth3-^^mdt&g)07*(rbZYXkE)R!!TMg0y4t`|Gt
z<^)`vSkcF919KzmaDgYMRLm(|RR4KS&EJ$i1{b;CQ>e_A_Y44jW?*{RL3Z`h_pC9~
z!FQ}HJ(07E)ff_L7R?YZikUlBt)l7Rz5N5L?(b=0rr~!qE6r3UoD!OXYc;DH(KLK-
zU;pZ{Z(oa<hQ4)e#koz<WX#;Y0*y3uuW#tx-0yY9Oe61fuDG|!oR68iRy#%0$giZQ
zKRo=d^Ls-v)8Ti9RxWK*bRlNm1>qRe;Z2v>nHS04Y-B8@kwc5l`6F?2iG(Cfhtl{*
zARxAxt1Zuq<UnVbE7nY4UuWE28+SBS#w%Lmm5uT0I_L~@7j%W$f+4NK1*>Q*i<Y;F
z#<orCo$k*yvElnh9IEj3*t<o0_eT#^+VlDk8L4aeJz{>(YWWZI52VH`2E+<sXy@AL
zm@SPP3*$zBFoa?77J~V<uwm{H+F!odEt+=3O=XKvjryfia5X7SjM0&tOnE{yb$oEj
zwmeUYrmnOY=7GX+BxhM+P(p#ll?!!Cg-co8%kDRG#G;O9Vdvbz^&NZHcAOA*oQRw4
zacg<JxGFuQn@-}0Zo(1$1Vk1WvqXKpaN(7gkN)z#keo3eVt<)14a46M{EZ~vhy4{W
zwf(@F_hhr?2VHqj?$kw#@}BJ0N4xXRG6u0Y@2t`&?#Vl=%i|yx1SiF#qplJ`d%H1=
zKZc{fb?4x^EW_ap$zh~`1K*U97O1VY30F7nMFd3v5~>sQmLT^Maz1GF!37L|Dn1dA
z79zS<(FKjJaxmLg!Oy2~@%%MZf#E1RC3Dn0MS#Ce_1|NK_1k;%ol56&{w4#j71INJ
zZ4L>|uSUa9$&|XK6PpaaSIVXLYQ+OeZ$768vdW6({!O^BudG-(`GCGRufb(ur4H5M
zdu2j;uaXCp-t@}*SY^Rd-~og0&EqnrzA5f%xSw@Sp|q}B3OALAKpZpI965Yqp*(VW
z-ms~rJPl(jUu?V8xT&S2jwvczEWc&nq*>vIK{~_SM5JwQ`o+?pWut^tYpknF#|_Ga
zhSy43IqF7$SM4Ki>3=vNwaE5XdZ^hwGfOUeJ$tzknQ;BJVrxT;Y4}?v{}-w!O|11j
J1|e1de*qGszFGhP

delta 14747
zcma)j33MCRkzhA2;v_%-BzOQs^CozTha{4sL`ftiOQxt>wl2dEx=BF-LAn9z-~fi~
zI5vE(D0dQ3mK@RXB&OFhG4nK&Wp<JYJ)1-Gc9Nh6dP@eQ-6$FFCYqV-z?OHCadzL^
zs^0(vlFCf*9;<)XuV24@{rdk`)o*_Nj_gmrE6e|{27{J@-{F^?zS4KE<QLNeSL*7@
zX^N#;g<o|nPe$#eSmg^8t9oCCgcNm5eP!bBXt}VTuF>fv6!pL)6P}|>=tki>-2w0?
zv<=`d=?|hsY#C=`?VOU;az!Ir*71VkSTS496|qkE({ct*33yovFd9*@4AhnY);1zz
zE1+D;Rzho}GM-`5edRp3B4{foZ53=4(3i2*z_ljL8QSd2p-vZb8mZV?Xk=#_**Z=I
zogh0R3bKT5H6seP{srYRhlT<g4Gh91{7hymff^87lNMXeHULfeMY*f#R*8IBW<#y;
zdH_i+&v{rkcfrf~d4r%<Im(S#XF*^^PzWHX0KmYHHwpc!=V<e-@2fs9r#}-O*VeCh
zLfvQjBmH~Z>&N`9W4?fkXAq@4a;V<#;w!PNIWkzEuB(7|zDk(Wb{SEMWS)22KRFf%
z@+HDQYrANpP_JuOnUKhS>uKFxT8Cvh{5=RLgnOz|#WelgY2m|dMZ(rUvI|!YhX4_@
z-TJlRuV`Ob!RCjRtYHc`Pl44;DJd$f2rKa^VOgVuTTA!v)v%@;hA`#UfFu+p{Mb|`
z{Ki-&f0s22qNzx6j^eLjK^Qc3;<Jdg^a9;#frM|EDvYZH0$f>H;iIUD*hW%c^l#VG
zHsMDm2VE@uqv@+Az6E+7?YMjCC&qW^tuBKwTk!Y>-H0dT9`gi)?z5vw6TXb_9GAuD
zv(^4n!DK<EUijyNlG?q%j^B^q0D^-E4k0*<;0OSh7Hr39?lR=#i;5>E)GM&&4YWzP
zZXT3P%7kB-_s|Jpo#n3_RZVl}#i|Vp7O|>#xxQ_F|AK9?<691K{SL8yr|_}GGU#fb
z_bk*c_J6Bc+^|!0J$8Ge=sIw(re(fjesod(jWMykU#uBeJTKM^f9x>Un5PwYOckkK
z%4A(KGNO@*tC>`p&|%%u)!MbNQEc75cu;J8EH<#DcZhn&%$TTeTJGGuSg`oS?cj$e
z#cc<~&V!lSc=<X}-zH30x9Z~MZKA$CrKJi=g*UA2X!h1>#i6HQkjXrroA7(Q9Df{@
zK$eo+Kknt9z)EE>#QP@rqgYm*^Y|w@FmF;37!L(J{CaG&0e~w{(iJOgE^*RN3nxo#
zps~r4eRSm34@y4EqxT9QR>bpJAPwRgV3<p=1aDUErhg^;LuGph&h&j10RBY;F9C4r
zB$3GCl8<>V@Hi<+m5;rEFV6^jtNL|hf{-geDZEwHW%?WzeF$Da@QUz1tLi`yL-hdt
z-mL@GJ#rZP>vc6U{qs;g%;P@GM}@z1G4xx)&s<Ck=}hShu-t{D+|LF0XMiH9V0|Ma
z{C_}V96cWb0OA>i=7vi8bHcucUit;$^#+Hu+%F6B4fXVIZvC{uK%2}+PoyFOUA^@$
zjpcG(6tMS+>^B8x>%qf&;C=MXYxw(l-{_D227e#*jRF>azv}yC2l@SD-{=VW{qH`P
zj6VrgL?tK*mUDW+*K5KLTTe+6y&<%&bJ2yjj;{MB8Wgaj{U7qWiN<j%_*Mj{iD4e)
z;^z^(h9El^{2;!5fZ*$bucs-0N_A{Jz%iZo{}gaj!aF@rM^SbBI|yD!@D&6b5p*GV
z8v!a)lKTXft^i1CxWMEX$9qB?KY>Udk;>qN-xnh0<tmm&_Z`F=&yBacCno(t&K>lR
zPjLJ?#1<n~cz)A*)%TFY_l56lDptLM#cRUfZ3?S?fW;pQCwnWv6r#ODbnC6Z>HTkc
zt!M-MB?QC{p2O0gBf#n4YXJ=NH?T<5@|GYDoT5JvItMqZ&j1!o{*n+J<Oj&WiE)te
zk)fffN@K=pav2|vf&UU#T}5yS0qOPIf@{Y*`tOBfJ3Jubw|5+)g<H0r|ALd1zw54C
zMFjZrt<;c>-Z5p`zN7xs#F)z+92*}Go#xp4L&zvC(@JTQ3h(&DMQJjQAr%qF!W(bx
z8Lp<GFMjVZy?E=xy_^jCsyomv>nD8?4eWykN!189=J9j)OX1~y6@V#a`-bL@_4lh0
z(M%8>8=5=U-zOG@GY<A}=yll#l(6wIBjcUIp~KJCk%gr=4QI4u4@5ykRk#aDV!<9F
z{Oe)6O6puFJ5o!`H(4V@kJJeMBV95|cI#_Lw$LnDRUT-V)STvgqo+e|?^sgf8Rgs;
zIS(I9%7fqtz*(97p`qj7gL43`g3A@A$)O|*%kVh`SXLgElQNvQ5oK5*m<rpXiuY-#
zf*-Gh^H`2_2Pr5i@l-wtM}(&b2>LyK@1!40n3>=?*5?gzEOTJb0cJAj3yd;*VDs?%
z0?fe>vzr^|8Sa@$PsleO(4r%PzieR}KN{@GzClftIWG<G>}U`31SvAW>8#H`KFWK>
zg1NLzRuetUV_8x!7YO;rI9OdPiL<)uVYZEO$dqVq1;Zd0z0kwd;q=!rAb6c*3Uw=p
zvM&d?&?FyNDL=Dsg+5SpugBlYdM;+0r8l|it?5EZreNKgq@!aJmSMNTjz`WbZ7}5F
zL&5XD(CN$pjfTLt!aVTn5VQeEDo%NVTu=oys9|*YpqMnd$E3+{2Se^NFd0)7{o{cU
zcOkTs3*aU+&bQ=}M3H7a><+<Q(EJjWDu$zZ+9w*Fv(<AYVr9E%Y@a{4(ESa!XdH+s
zmUa1;yI<~pb<>irLey2vR^8FnE?aCfRabiAddEE|)m-U~>zzE>Z?a&F^8_bBL2guv
z8<dhXXYEJAMFHtWyUqM?qat>Ud*xLsOoRQx(u#oXvh-P~<yEXKq5xk}J|Y84m9z3R
zR<Q!BJPYd?XjLn)d1<UVgN+`fSWV^y%w6j#0Oj`k!Ts`$Tx7tmJg3I}J}-m&H^XzV
z27Ko@CN!Q|2!EKF1EW=%=wbFCDhk>mE9p^|gVVZ7U!bm@Kfva&W!3;6X}5<aC;S{U
z9vxxoz0zoXUb1KzzvmR^Z^8ll#$8z^>4W)y^-XEcar{LFPN(zfbNrwBk_z%Fo$nv_
z@nxXHbmgZ|IpPV1(#^2Q$6#t*N^)XE`Hg7NU1-rt(q&Rf1PJ2hhQml3w$+^$^P)R5
zDZ#O+nzhFL2(q1M-+0u6eOsx5%6Rn#(X=6^yr(lor#oNiUA8)7gHU5CoaSQTxVkK5
zq4F)$hh90cY%PTvQ%;Q$YuHy#E?XT?qtB_)WoxjFI;TcS6*95Gdq!)TJy{)I7&1lS
zI>8^VV`BE-rZ998rt?(7<#xO9!U0DVw({qcVVac@<JE=oNDBb0{C&cNqMoNiQn&-y
z5S~Qj$130ufVT`)<{5!QfmM=a15bRzjehF&0ggxG26yEY$1~$2Owcnn;g51bCUn{p
z0_z8348nHHz?zs0G3^Y5kdq<q;l7)-mPeZ0@JhbG7L4A*v^Ps^nDgM3j-Su+;J*xm
z0LKN6>#4F`0dUTJEQ4D;6AW<^*!EC;kn_6I+v-zWNi+ppCXS!@X-U->99Euy<i(?7
z05&#08DL#<Vth#%8%pMpL2|*g*Pb@FLiY$r<Houu9Brd+Nw}%nwFZ|Z%%OW4EzS)c
zg2m~neDmcKFQ1sH7Y$WQ27vVmL&K7xO*FJ63>`7qvd$3enK92i^QP^t*&cWFB+Q%Q
z`b{613%|h449-TkU)!B1s!N#bV|mLu^Ys2#HZ2#~Vmt2{i(>iGMw>55N5u7WK`(Bi
znP1kjz6bVol^O-t;45@Q22UA0<zd+Xby?wscdzWE12$URS}An3GCyH!y+-JZSlj3z
z{hB?jxFUPasQ?E8D3yGEDC>lPd!f8ey(P<7+4D5U{$N~!KU%DVjhy}y#rr6k@Lh(X
zRZ^uKE5S^|w4m##ljnu=geyv`nN|LYD#ItD4y(@?g)8l)Li|Oma7m-K^SYdF^D>0b
z(?Dne!ZNugR49lW%BwR~D;lUXSZJU+QzY!~x6m44tgBeq=g=s%VQsp%uXft4{KlM~
zG~sNe3d5u`cH!+^7TSrjb*&tFs3N1jum%<(_)_3e0gBZU6+kJX3u_|!P?hlWUCulm
zVONc!6p(U8#E4-nMO2T}S&Dp+$`H;UkspL9q~R~3I8V9so;=tac7PGX;^mmJ@n8tn
zjpr0>`l}XP+KJ=G{b;~Q6kt6(%dp%z-y_|)D8sDr<I;;aV}U))BNsbLlIdsFYR8>k
zivWL*+&<DL)(8`=hto8`NYOeIgiVVJHlf^ni0ltd42PqJo#Nr~^`3@zg3|a#1nATA
zO$aIxpr4<V9~eBq*WhbC063j~ANf>cbdL|b15gzYj;;?6@N{B~837*>-C|F`<G&d6
z1$!75&9@;_3>{o_QsKGa3r_9q_XHrlz<^Vf_Nvn}Bk80E_O{^U$cWGD!_AiUggoe+
zdi;KA%+Vm@;W=j5Gd$Il=7f7tW_mMBPH`~hfafkSz96BlIw%={L;+F<LLTS}>(bin
zVWdbAw_cY;+DSW5ev$`C2fMH#L;Mk90Zfi16~17=lazyWQs%-JkWvUFRQ$i#b{fIk
z0FtT@_)_2iyp9->jyVRUOz=1e2AkA?E`xBydjd%{DMCklH#XLfNosdT5uencA*BgP
z5hXIBB7G29Uvvk(<2;vCqZZtdQGw>bGw7DgC8;6iLMrmWTBJe<oMtehq%!0NTo7{(
z#2g<2;$%mYMeei}V*^-HnbV<e?dkAH!U;ScegMP0M15k`7HVUfPl{DmZA|^KnW}F~
z*bcpYaaKOxzYzLv_*>znzJp@l!N2W1_@;dJVoV>mMGyT{M@|ao?%Tb$TjGwR3G=bI
z{#Z&y6_#8bx-v9dB3c`ltR14YV}3Zk@2R-8BVlzfSy|D_Cafbd4Y=%Ad$07)szr-y
z$<iiT+U8qs2jZ5tgyrOt#Uolg35z$T28Lx-H=C|C&25`$N|d(5jDXRXMVE9=QRhtP
zDwcFLqORtSu8y2rBMI|pTt9lxQn_St0q2CJF{b_$TI65e`0~c-t~)wAp?f@G9*XOS
z?%9~Dkt>neCq-M!lC49ubtG)-V|whOcu8j$b@qg=d`VX+>MHN(s<EYW`(kf=--+nb
zK99K1li24K``M-bGh+XlrT%Bc{$~>X!T9!2+%cIjpNs3yePp%GsAso`#clK3#Nzey
z&m^qfFm`ikEbk+;ZANiZe@zd)7q=`GcZkIu^Si|2EeUg9EblHjg6viQ75{9PSk$ys
z)Fu|S&DV)VJqgn$@EQk<WiwCAa&cp0T;2GupY+pI@nJd$TRio;W2Zy$z5)P$3}%-<
z4q!!egNG$?^Qwhy2g<<9%ahY*PY55j7h^e(cz9E^@RMDo!bHR>3(JK|2P))nBnw+z
z)_OR_vR)pWbI!t9E{C%mLi(^0j|QR5YZdN=_0f<4-pDUZXU>ZpT$Tl%9WI4O1>*LP
zk4=D2hXG4=i-kSH$8zARO~UGF4sw2uBmjsnwrU&CZsB-BL|26ROnQ0sK%OA8RihUN
zKHNC0wropWZDaxVFoWrR{P&S%+dTTfh)OXIggCjQ`NIwj;(bmv@9_jCJ^u9R#+>#9
znZP(4Vdv3zB}$QeP>7ZSqa42z6bM-};()^b7o~Wz0Um`Zkakd#Da4I0lTOZ>Nm2nR
z|FcPT5Q0t4&5mGR3wAjr*|mb`@~3wpDbBaTeE>?9-g(GA7+f6=MM<!~mhKz4{k#e+
zrFf|Ds{V?8=1I|1J69)~+UD8+<o||$u}j=A6yJAP+;CVl9)ZYT+A@|bRidS8c7SXg
zEuy6*VObYb-_uzxZ+T@4S=~bk^PaeV&nF74>7+KMfP_Lp$&B?%{*tLmG*u-`H8JI~
z(F&gJP9gBe+}z+h{<yI{u5On+S;LB9t#D*f2W0L10!mjYpYWI4N`;dL3iDto5V!Kj
zyUK(U2MSx|tmJ0`eMIrleG4l>=nIoy#tGxwU}^pQRH0nSssuwvO}A15$uC%E4;PLy
zvv2}5n-@_9a_h3mvk1DgHju_@(6YJ=_efqAt7i>atXeoz<lLBz-GWL;V&s$9t{_y9
zk&rcp<<}|J^j4M*?onkCIkc^Bf+ng*G${zHpow`!6N_-VsG=w9BSXu)N3^tt^Ppwn
zik7-a9w<Xt9C64any@g@RahI=WR!6NW+I}E=puRuPW!_237CP1A(9WFLm7IpQSeAJ
z117Y_h$&LQ+9Kw#F=7duBGzz0q%f?5K(x3Q#vIl|sRT<os@Jlmxt=ailp#ex&Dw#F
z7Wn9Zk3LeE)5apTDb5HQDGC>{4orJSY#^Kig)5YYRpGp_`hA6@?MN}yIEmP{aB)^_
z98yW7G;D^B%ZZRyC^<=~5K7D{aV=~`uDEO^#@;|zwT7<xk#se^80)SWOKmP8u&P_b
zs(uxPYYj!iDvHK66irzQ=pQ9+UPIE7C6Opv*HElmMbU;7;UeJHPD(Z?b&ygqlsZYN
z6iVw!sRT+Jda3?Z<6qtFMkHRLq1D}X^$M-AQbPy3B{Po^J6Uh`j77i_u&0+mcg}k2
z3)^7{Y|UK)8GDJYwU^?EJ#1e)B6d?|L~O4#BG7@I-A3%s!ETC_v)dz1Xz9RUFzm#@
zFv5hY;D!9cSt+4)KN&34;jF+f?8poODhD!^={jdl-5^nEIZ*9bMaAS$?Icu?`l+Hq
zcv(Sy)$kbsP35RX9adaF3^~$Vz2H80l$w^mmVchQAU{f-r-22N=0E|9p-5Q{i|%k4
zXtpPp!@s3j5POxKJW8wVW}qYHKuTRWn4=V16e)YQY?^+pRw|vRGZMNU^Xy0WCL3~*
zI8ER#S)==g_YO)?mUNvV`Sh#9WNrHVeHf*#4T4u3UOmj-3A_aX_aT&ZL`Z<)M$d^v
zsaV>;xpMp)5<^OSGG2$|aOEbNQ50eQ@y;j?0@9(p&kGUo$Ry`yg5#6Cmm|Yzf;g1T
zrm%x!%*sS>c0l}I(B1tV0Qg}5NqO7GbxE0bjNFMz*|n|Q)~SjoJbVDc-X5lZeA3T?
zBNU1<6L1;Dr7vcfx+z;-Q#zf%awDEee~1BI46xdR+%dJz<DDCC#u6UdQzcohnG~ON
zA;i>A6}eV3172rGbDBgmZKRtaXk%N`MiSuuf5gs;)^rB9M9`{aO{<P|(sj`=<PeDi
zl`Qm3hQ>4QmNbpQDCbRDa`6~Sf<G&z6beWUx%z;MT)1@!K>QC(B$ZzJ($=Iw@}Aw&
zq$N$6SM-mOPcoC(%kXu=DAF@>d23P=#d~20f+6O{#70tk&YMLvBSL+SOV?w%BdItS
za{EcrBdIzy;)Xj`{xO(|q@3q?lJ`iGk552ayj3IVkfh%0;ZM2KsHA?yaH48{j3*a4
zxfeTGoCZr$QorP3(ms>OPv18rEs#`(Z(QIzmvkpECrK+o=5`I(shaHkq2ZtRMKNKV
z&9*Qj9-p6MdzdLl3v-xcXht9{amwR8n@zRADr)&9r~-be^gV_2wrlJCyWk{D*|S|_
zYzw<0xh61_Dp!UxxtDQdFG3+O$n=%r9~T;)W20vB1p|KqdP!=1AQYHR06s=}0uT?s
z2au8>m}E&RCwL#|9#2z#2$#tKf)fZ%A=rRm3xK3%5WWQ?Ta0wOTp``T<HZ6$iOoGE
z1R-l$o4z}R<jbmyM4qHww8U0Pu#wc0awZuf)sTQJnV&|cgO8-1ptEo3?N8#8Pu`+_
zcZQKZT`jRPcu$YRT|&n6_377i+w@zuY4#l!0)G()ug_Q+UMrIOBYrauyca8J4orHC
zPbva7&J*Ha#EQ=&cnLtT0(2uhGgcvk4|Fy?e;^u%jVSnkz!!vY$V^!ZV|gT#vSh6h
ztu;$lmuPj()z5EFSU1KrP-8AyDyS3-Dwhgs#e&+|3-g7Ef{iiNU0vby$PMouUFE$J
z=gsnK<#UR;Q;CwcrIL+e$;L!UcWie`rZ80gv~AOk!P$m8_U6UHE1FNWRJ5dgX5_jd
zw(Fj?ctxKz^X7!L6EYV0=B0e6nD1Q5uM+dCW*?h7oygx9lRr$Ybl=fAW=rNgUn#$<
zFNj;4=X`U=<6XmX^WHo9eapqAv0Zm{29kt%1Z5OR_r}fp?&$X~7nl8B(uTS2xyJbV
zT&5|-E?U!Z&rz}D*eE(SCLG<dVNg(K*HXu@*fD(j*+j=vqJCX$_l$n_3{;pLabx{*
zYp-Z(n$DlqFK^zqwE2h_-F#%(S~)xPKrY*27EL|V`kBC-AIK|Q(}rbd<FtOcqIEi-
zl#u&YdO9y&+$x&ZEw^pLVzX#!x!c+~e{3;dT)#Kbx(|_!e`{*G$J8PR7jkGu4p0K6
z*(+x4a{;kpbE0fZY-l-JRyS8GmaU5o0r$$<rHTz=#fJHdi>}*8<4+z>RGf(G%b~{3
zER}VNWu5aU;{AscWk+5fiVaS$hl=|3v7OU<MSb;hLsx8P+*&K@>z3;~u~;qYYwlLn
z&)Mh4MAtx~YVfv7tQrRL$3;DJx7sz=H2<s^ZP<~h-g&!LtlkGTL!!RoZe`t^e*U;v
zzb#R@9dNrvz4LB))$Gu`O|0%tl=lE`$IE-~GBvaQ`EIdxbAs6dsK?-oxx0?a+1`02
ze6*KvYy{lk%fokT8s>Tz)MDedL=AG=BkC*f);7)!EtHB)1Bu$`ARvcDebsVpd%6Up
zs%nKYcD&pKyyMn-QSVx=ss|*>zT82E+6uD^3T^3_?_E@j9lH|EyOGu<>KpC?a%izs
z>>Nt8>_KFMsBcU$l(FdY*_Y4GG|aMz{6=EKXVdw?j@No;I%X^0>>@V2Zr(DljIVz(
zZa#WPe{8v;=8^NVY_5*=FIUz)O4iz}ti9Mj%6d=u^$X8LfBWgUoU)dGLdgu3km`#U
zcQ4c~6vwwc8813|$8>DjULj~wN~rwZr>u-Jm3%_!G#ww|!s=eASg^!<kH*c%?&y#I
zesfu_gy~<aJxL-C)t41%xw$Q)vgH=gKPYNR-}t+f4f^~nh^O|4O~yT4)c5Hfvf&cy
zM_r}EMe-jP(g;g5dt2l`uG~iNb;*C?Qo>781z*ifoDO;w!v0fM*|b*p!squx{!lK&
zj}{95@AG=45?pVk;PF~@nNT323Jc@WLV<bFDEt@3u2lP|h(?%r$st^RkyU8eyk6mh
zS4)M0mxl8-tOosTRy#nQWGG?$MWz7K9pqk1e?u15u!gW!`0`7Cq0_MBGg%)v<iN?U
z6=>GR76U91Ofj3Wgf(ZPGr*N1uAp=Ut}Lu3BL6O?Qvr!1{pxs`ygJjbebQ@%^jc8C
zR_3s+N@J_o>KtrM8e7ZSbFg)3Z2bzXD~)xn;M<VKHn5F39GcSDCbl^T+mgn%u&p`R
zb!qH6wk-$SE@6%BY{x^agp+r&>)&|QDc`_u#77s~jgKDkaBgCIGxY4{8_KWJFb`YE
zG&RE=qYBk{xGyu=d_LrVwxV+Z8KgdZVv-^qpz1Pp?Dp%55Pn!ret_-I4eqZ~VI6C_
z4&RT(Z1lhzuT+!`KAbyt#|<S2AO)9s>|;XjE6&1Q*qq%x1qUraaI+vDd>jnJ=2%n1
z4xu^0WvU#mf<bh{o`<~CnBg^;y=yT0R%7V>AZXixhiLZT4K)aQ2sH&GJWNDfJ?<mI
zvCB2|6VTN5WKPqgHx$tH7&a9yy=v2C(`ykuQOW^mFmU`~gRq`Gf&5|EC*P96+f(=k
zPxlJ!(?kZ(4HYmyMdX6)TcIKRkiCKA;mAF;lxl;^Zuk%%C*n!yv)B8uPnLxhX#i`;
zhd(2+3J!UO;F4eZu_GC)$S!A#mK|NWoY_%f_N8X}H1=Wj<*+|<Lk?n|C7VMD`M(L)
z&q}+%7?E8AcM1XFo5FXCcSC<Xe!@AWsoBoduuV+OQTPPoapCnZIOtyC{V$a7{4SCp
zfUn@Nby7D04!>La6a{=@e7TS5I_dNFpCO6q)Hr+5?S%`A@t_YQZGKQNeX&@F?fI{v
zySHEH_~PSQ!jK?@XTR7O{T$Xjhu{SOzVlc@=g{{lmWZ!-2}|fJ`rKfwlCKG#DfyO-
zp8|Z+fbM7Z+bsT%ut69>1Oa~k#E&Du7?+>G(r>X8pz%^*4BwwY@H_$@K>FM0zwYDD
zA?lk*jFR1N$I=DFq1!w9#}k{iOYfxm;DQ>PNz`NrS(>DZXls2^J#x<L#`{k`f=p@=
z+@(N?{If#amul#U@Whvn7lsi{!t(|!eI3AkjgaSe2p@gPE^DF%wcjq3UoBBx!s_RQ
zKf6|+DgNTxj_CIg``;0KAHfe0{15<qhw~u_m^5LCdJ6t^C3M>DJq>X!Pg<-bPUaDj
z+twx3JlqE12WDUgKfw0+8HCh2L)k{Y-@dQMjQ)KyCH#*!>r~Rb3%ctY>_*;;f}B8b
z5y6`XZlK2Ug_GBd+fL&9PZ9hYfe~w35L|&*mr07G2*bA!%Thw}`sSMNKxI;gQ=d+{
z;2kyjx-!VWf_(ln5DVYDvCkI7uQ4G@v*HKwhX1YYhNt8ZZ#)f>L%dNW{KZ=r4Q0-y
z(nhhgac+lL+97QF@^7QXrRCaXed)}=lD%29H_wfT_Vp<_An)l*X4+CpD1rN7aL%gU
z)xNEbH*Q|w6U_Eh9^%!Mftf9OxAg7OcvIh^IZ-i?(jZ=s^tyMAZyV$5wl5AOm|ZCY
z;`1qkedhR0_ciyNd%>G<Y)=`Zh&NG&s@cci-TU_5c<1ih{fX**sRG2CSMcdiFps4y
zh__M($IRKA<JZRHEn5~9iSofzA>xZEL)pyZH}_uKJGXm5k+5%0l_0t_+ikpg+hS+J
z@mQ)1@pj5k9Gxk<>AdEgE1UNwN_tWb#FtZs`nj?XobNf~-G|~w+zHpyDJNDiE9BXh
zV0NS`5MQ}M9(kgCAXSC<>TJg_-jRf3Fja%-dgwRP?bGvYqGVIbh4==ltoCN>wbr>N
z5WaNtvZefL-<7`E^>ft;OY1V!^<C?m+q_VjDBHYjuOq`8Uf7<n_dR?YNZ7Z1(gDn3
z>gi%pU7G5-_2JFUv@BJ6>&x$~qlLV$y`d-fU%VF0&nevhT1ynKf}}J7>_HUoKww7z
zE0~h(`=M#$I^ZuOz%wMNI!L~X;om^aqs*Lqd_fjLHlMI6(a<0*mwRab_`#+mADT6<
z&Hzjs2YY40x8L1jX;fCsTT&D}7OW5Okvbt5=HgM4l9{VXQSew8B#+x(@_^V%dOpoP
zz}i%`O=+L!QWQMm`;SP^<4?yuY<%Qw+;dhu?tg%FsrG!OZ8rFTf=7z!Q#Q>XOi}Py
zIK0^Y!|o5eZ*%d($Kw6R#LdSa06yB3+Aeb_JLaHscr1V@@K_wYUHKE&U%Qa>geSh+
z1ONH(04qM;G9**l7P^3-2Bf&%Bn~_wZhA6BAv(^Uen1K-RzWqb`&i?XDU0tFm86td
zfc02VIDK%YYWm45`KdgDQd2EuRkNMfT2h1-{y|BbAM;Lk#(Xb3Kh+_Lq*m0ZOT&Le
z3-7&G-hw+ge1j$ZCz7P?l{4^}x_4}xo%C~C_+Qb&XYbjI>qV;m?<vb~R2PkO@h22Q
H!ukIL$zI!r

diff --git a/app/services/__pycache__/graph_generator.cpython-312.pyc b/app/services/__pycache__/graph_generator.cpython-312.pyc
index c3d5418f2d1c30e982e0347db67b4f2b805d3e05..6caa01b601ff2c34e9f5962c5dca8318b6b6a2a8 100644
GIT binary patch
delta 9091
zcmbVS32;=`mHof>Rcfi#+R*Z~0BS&>1tbuQBm~WBFiVJoA@W!MFR4W@^7}28rZsIG
zlZY_{$&VP>E>G~nSPF^*k&_}dp0YDDPGz%08*G#xl7V;<n<UQ2gR>N#D(2qz)l%a!
zN!5Ic!+rPOci;Q>-TU6VzZw6X?$1Z`89#A4Z5%vvT7^LH!i9_>zBmip@Z8$0<G9nD
z%<bkSZnsY2ck89u^i{r;pF<zgRnR-UMWd{?$BerjR!(Aks~uX-sn+}{-EZlpbnO`+
zb)i(sq`%_J*14da#oAeNwv-KjEwW8A%7#vh<OZ3W$#Q`2k#nS6*)T1)NqHdmFnK=O
zN)$jlm$eJi?3kokz|Whuld^A;ih!SQ<x+p7xl)N-AQu$C%S)v|85kwNm}St)X03A6
z&?Kx~F*74ar%S2?lZA(hy;b95`q%aR?eUQL4U2sNSR~a53+YPNY<>~-yH=R$k+FRI
ztgD&ND*;;7D^W7)AWr0$A_(K3WF2+z4fIHfhi{>$OUg})k?*CimF&r0jwBjUjRyi!
zw3{rV)ukn#X*Nlq!XkuR`cUaIei?nbw0iDi*u&Nt2}cjefv)Z-!4B`kUwE!J$Be>0
zzZfJ(=pRex*dGTTIgaocEfq=^;^?ZOi-?Ct4J1v78fYeFUcbGnqc`ML`3TuSgF<Q3
zD(qqliDaKllt4^odTds=UF&6$M1}2QR2En-ua4mCG?j()4PmaO71~|{X`>$tl{?tW
zT7!YGtV9n5WrDUzEx`M4{uG}-G=qgB$Q%NQ6?XQ?!S=prAQ*^=(Lf~J?(c>H7xsp`
z$YxOR@?<OBSLWTb1H0@5P>sy6s_#=|)kwr}mrOcQ_z;4K8u~83sOmdJLLNZg7Z4sq
zfmIIog=7LRqv~UUUeyql4@Sus>10_^Svx9ZDsr^_U^L+07Zf|>ph6_<D<kZt)#Z(4
z-AD!yFdRq^fHyZi9O%*VZG4zsE%%m0K&a}v3F$@EhY<*Zf)E`qsraSSQ;u{6!fb>&
z2wv){t*+e!<fxIP#U;vEsIc&<!6u|Xx0AV-)X{KluJ1|YE<<<<VATBS{;cZ?l(U6F
zbEEv!Vj}lxgckba+F7LyNH!uYMQB1;f`IEyR#R(TSsmF3bj-a!QrF(w7gXf5)w>V1
za0y3s<bI^L0(eX4mR(+Y{|2K67liCZ*p2W-gjeX(b%peMbybNjY+4aM!{eiw=^jU=
zAVLTsjKDmv7Z28dmg`j$i_Uu0tgUf9i9#PG6F^8k;}6!ax7}lLF0NcMYd(%Ly#k~K
zn$yd0qt;D@RW>_w*o?1gnXd>gYb*yH)<I-3+WlD`BS}#5&Put;p5`k0`l{N}zv&#Z
zZ`|H&vfg9zbJmw9rY9e>x2@kQRCO&11;XCc{9$MoR&1?Rhp%;KyAp~-qTRB@q9K+6
zETIZ_AlA=ox_69Wc#%U0njer_!{Vw1$+ZYRgmnlkY}X^T0Rclxb60++7;UF_Uhuf4
zgX&W*;&+2%@=Yw99;DyeRs45-bZ$e!eh(ite{P<P%S3*Jz*hN(NMW+Y9J|`K)>VbH
zcTe}(k5T3B^dmn(-cJ!)5Ede^40{u)x9D4+%PqtVi&<9twC(lN8Kxr}Y1yv)PrrC+
zDmE(9VgqfmG}?pID+q5RT&8DsE%-YQxk5MA7mw>dKWxi<6#8I<!IRqpo6$GKdD*x$
zUVYl`vx@#!T$=a**f&4sL8c=&k^Uq22<YD-{ehm*zeoDl21fq@>1#%q(}zH5P8kF$
zrmL<daUkFrVLQ}|C}ukpo+mNO&OivxAH^Fp@7%FLsG9AKtpI{P+tK7Zi3;|<-d>pq
z1P@CXpPf)`AeefOOU<MX)tpf!@Tr8mc?JX|NsIjzv)@B<`k*1>*u;=h4FM$#CyLS+
zf>TcRFKW_G1e9MyxYtJI&Cxch8>l28yhq>ik6PJ=lLKv<d@_fYoHdO<E&WNCP#qZP
zAyHA<gB^<M49a47y6FcOPCpqyfqS`Id%)qRxi}x!#h}@50Ll=v!{vyNft&k{aot^Q
zQ`{Igb?N%el1|dYzm_O0p7!+U=yO&#eY`P)=V?=S(c-vSGD+sBIi(<3B<q;%9A*JL
zaSKSn)R_I8N#pQbl&7w}Me8Mp<dibvyp;KjL2|{7?BA?sjZ(JcmU5(=G?N}FSIQg9
zKZoxE&sf1Zi$<l4-3O)|Qej*-Wz6*dHO9=+M;^(eEn6LiIM?IA*R>X*v-+(t^F_Hu
zC2^}%ER~FvrsjjQ(B{K&JuaHG7aR2?E6&mDdp)zQ=cZ&kxTq(k6;I=O1+kin#UA=_
zPZ51%MKOJ|r<$(ZS580dand^veP!ig=oK?pbV_o)=trV+*|LTPh~LE^(7=mSF2GH8
zN`4h6l|KL~2|5^DU2_n{EdVi_PmBupLFfoo<jcq~LI`<nxB1yOF<8hkgs)IO<Tm{y
zl5tuXnpKV2<uz*gast_pBOC`%4ILekgE9MNh`}klR1Q@>h&yoL0SE$Z2e!}Ti>mJp
z$f`jK_@m_8XyzG&d!~j>OAQM+kysG~`lnF2F%yHH3gLV$No-()<{vJlN+^qx@RFt5
zK=l!BvV_a8JQGUh)ekr(3g?UzB@35abSDc|3}j5qsv235oYi=-K3TYGAoF@w>6y|?
zu3D;#4CfXMSC8l~6)YI>oo{}<{!-n#*B`#*fIDzx4*hv#D_=D3?ft~WAEmPol<}A7
zx&tc{czAjBx6Ktk-`cfpZQ5a0m13@`@zu1|kfZpbs5z=9)iA%C705s>U@X9Qt3<$^
z%4>vel(8_6SkI|Wnib77S%_8&I4+^}B8#wpEr8dUGRgW+je&!*@lu0ge>R>5b=Y%i
z+<Futz`8F+dI>@UGPK!i6T!)j>J!>rn^SX5?*r;H!)ShDZ_kWtvuQ-DI&BWi&;|=<
zHuDy2;@(d%roCqEaKv&*H3a3(sA}ql(x-N+_90H3BpwJ|S{X6ftn&MrVIR!tG}>VY
z$1trsRGvV$bUpnPKBKRZub`BjxQ_w_N6ZQ|hC!}{J3B4h$itF^EJf-FP&>O0=e)e`
zM(nZI;8mG*)^Rz=V}%_N=}<dv*KqFm<#06pSgA%cn-SPW&Z8QGkpnVesiInxzK-5t
zB&tA$iKLs1KM|`)VDUk|3831r0y%^gh{Cc+b$1~{JQz^gqfqTAoe>fu-$i{q+*Ld3
z?+++}4k)(%_F?4KGOh^UPe3SR6j-6p#~MwnDp*ecGgh9#UVt4^Zj>I83TV~g`}zMK
zKXh21<=KJVb|E}~uopq3L&rP$T>97Jd+bcUlZoi=6J^D)KzI>UjlCifLj)zTSNNkU
zAA<t)*%LcWJ*eD5|8k<KWgcpp6et4agQ~rY1SF+b_P6hYJ@4ixckbL_cSElMRz!hL
zH~$w{xN|NR8^uOoM(M*}%}Mlu=>2;3eDWHK8(@d62l0L!XafuZO#iaZ8o!_P<A8>6
zBrL-`G5)jwScaNx(OKwWq>kzsL)8TjkRXV=v=MGKlO|Ng;8M*}Ak>wB;(IzQhtcHS
z(WBj?Se$(wrEG7;{J<(287v}C00n*$CG8~m5(;qsQyFlrSqtnV$R9v>0^vc>aCZH<
zYR}1k`_l)_P(Hs&2TzvqXUD&NGK=Tq^gjl-eSzhXmL5+{S(%;(Okw&An3+eH7wuJz
zHOCy0PNA2`xXVL9fa8KIm#~MNqT!+3S-AH@QGns3>JA>#&H@%u3+dN~cJZ_6pNGEV
z?LwDz1E~Dwn0{ehC)tM_Ji1_=rlsU4z4F9s{O9Q@y0Rz%8dJ;q?~wntKDgp=!mq#l
zgh0MZKct0rmUH(3lWd{cr{<WLGkfT&Q(oV8<c<Qs*8w@I>bA71CJ`=;VTpY`P;I-!
zV4u8}kcgJ2qy?w*5cU!gE+Dkhe?GN6f%ihy*cpt7QPqm+7Y#%q`P#6<8U&WjEJYu{
zUg!|=J?vx=C8=FJC@b38_#pBOVf+SRMV)Sh0740XcafH_c;d0kqnhE51p7ktz}MPM
zm{6pLUi;c&eiO}lGJn}d)Y^jZDvGj^VoRVWvR~yzmG97^*T{Ae)dZ(IOa(p~bv(J0
zf1Ez^WKqFF=&4#mVj$d(C9+l*<4AB#t)hQ@avPr*-+0<)&&0#wefSHH0ZRn`^Y#3P
z^z`%9{95|P^A(8$Fgk?A+8X>bswW<t%_9g$G|B2ZpRaAHR`KEf4-rt)sT%jSiSW$@
z_iN}~Q`4}xriSETH_VVxV_Iaggu*mYO;ex9!l=g*@etl>ZksC_YVeN_#-GVS+`P#N
z1WZ>@(sCF=_vsgkOn7dPgY?xGip%CAi75)*Svp?EPAs5WP}EOvzffprv8L_xwDiT&
z#10g($axgi*~(+MXyNk$Gl76Buf@RM-m<4Ybo>DO2-pYj+GG<p+2Y##@GYw=LISd)
zT6-h(Ute6Kg+>(XIa+yk4KI%e&VJvN@M6cq05>-w^(LBFi`37Mnp!Zp<FvM}CYO-)
z767b5Yol+8&zH7RM!0AyHkPQwjf(7eeHSToskWKDjh#(xBI!_UUBKn&=vYSL36!U;
z6E?4arjNV>2-~j?IrV62CBknIaL(F_okHp=@+J^|j-ag=Qn-(Ib+YHT&Fp3ov-{xV
zqOc><2PZU{%eg^|ZMrJzx1hCty5XC%5^1XlOs|Xl0u`96@428o*qtrt-(O3wGyUYn
zj(061eeau%?qA}NzeZr^t`oFq)>$`gdD&<Ft^vMJE!NS<*;(TwFAKWF7VVSEAgccb
zG*uhy4DIX-v!dGlaxmBqj0jOwN4G3WGSQlT3+SdEyjknv@2%Tl{d8KP6X#Qf4HS`}
zAnCA_jO&R`(uH|RALCk}WU|B!N=6hWpgnQjbSDF<hn-P0&YrkoT4rQbsg-{5rIMn!
zHE!wDjhRwHEM@y`{r0%M$I434`AZ!(Jt>IdE)U*-+ATM($0}5^LDdPf#)s$Pc6#JU
zP94_3P%1j0zU4n_UO4iY^PFak>vzN*w9M;qW~7D(Lk{|VtH)`)i*tQ%PC|lGHdXh6
znvtwYEBL0>*Km6qIF7xAvp*wEV|obCsF>2o?03ao3V+-hcf_5VpW~UGx&nBk{;YUb
zPab<Y4d}0kIXCW_nbz^y2JZM$15P;UEuyWD=FrK_mU1v(tC?q$$nJN8sccEV50V6i
z%8X~xZBb9AZ7j_c@V@`0oJ=Vz&3e6oHnx|dNf*4WnH-h$Qg$$_KPR3;e`YVz^?T?y
z+Dq*oR?U0Ha?cs)+wF7c!GCh-;vTwft;eaKu@<eSdws>chu&DoW=ZciS*d@8+b-p$
zly=be9r^nFXahaJqe$1YoPK1V#jk{FyU_6rClx%aXEk~*4r<PY4+x&ILVCpKp}%Q&
z<Djdf%_(QabEj>>_ft^^5oJq#(p@LRiH1L8h(c6^%d#LU0+hCakk}>DNmFq`5~E_1
zusNVa1-Rpo$N?y&WzpY_q!0jQAvh)5k5>gKu2ZJ*Uv@Nyl^FvXL(uY1xl5Pb7n+2v
zz4(KN7!+7LA;8UEfX}Sj^zP~~lig{(QnQ&FNX!1ayUlC_Y5hWClmrgqJK{!x6NimL
zsPZWyd}D))cQ11ddgJalOy5bGgf{FpJ!MUXo}z>Mo9K=GZHX3G6js}5yZVoCufltS
zRs;59^C&i_&v&@?9Y!uYZBL*GPZqCHwctE=!YxU)!elqIA7)fDGB-#3>_}$&AI_+c
zC_Z-HK;`^by#2CM8?u7i0#|AHO=)_o_v%#>mQvu1`*EzT2>2OCHL>t$j~UpHP)T5U
z1??B6k5FgkM0f_9Z2L8`E^4;e7mc*zjj%J4fRYe@OH&<MI}D#5p=DIyySYrx<3LU(
z5&be-0@aFz9=?@CPJ$oQ40g4I*KY46kzPfs46!JNniy{lsxA;w&8rVZWo5(GnY*KE
zP-J-@N#x_~a6ci12(u8_EprHsTk(sk5*0(esy-Y!pjxA;w)UG=o_1m_z+ThG4EY1D
z&xZ(qL=aHQ3Z(>6n~;as67m<G^Jy1R)dn$<I*j-p?FwqZw<Irvx~hkFCwCat(buWk
zBYn}{K6qpJWkkU}5N@7%_<=Mpr)w&I+qLCkc^j*st<Cv~G)^(>@5&s=`$xEs8#s6F
zphUgH;!yRO`efFe3!c%6i>=A5RRgA<&s%&-Ke&!MhLyKn<*!y;?D>~PKU|$`+A?7L
zuWZlh1w#u)j3fKcB(7vP9y1T<2ewaGY$wgf%!9_`88_^%YmUs58;)%ll+R?3bR;hB
zddIP5(!^!CPg{m86P|*J+~SFxq6t_2M1JMqKaA-|)}3=C^A=CqxvYX)oGHsTV4Te6
ztQl7=Lee6f@m#UYov=8sS_+ev!r{6rmJ(>4v>&q%whk&+EVDi`agMxeW%EXszgyNg
z<Q(J&o307ok$LY5ONQ1Dwk8Jq)V!kWrIlyIk+SFHk!@#oCrfLF4HNlASM%p3^XH8$
zc_+X2BP&<dFsbLtmrlC4vN<nhK9_k}sJ$vQCWXd#g=I-c(XovKI|eJDUuO28`1rvI
zSI$*eMbcF<(s0RDam7^!jMJGznP>FxxGE>jTv^k{HqPp}YDwfLE%{e0g*WU4zi@c2
zXXl)rH#Cnf7-&N;Z92ATSbt{i`2(-Fz2jJ)@|*womI)B9Kem2w+wo1;+yz(N6-jr+
znYNeKKezscjhEevuDTnN?uPRRF1wpAIhxVA9yYjdtnOPYMps;&zdSjA`Q`a5ug+g5
zCg-oaJb%Nbc^iLNd8vGB(zO*{)0zLViF3Nx`1bR87ya)zR;P`A4MOAaWp~9TM+I>~
zoOyZG1izX0b}L?fr`Nb;%NDr%E|#PkxppV~5_j$VLJzy~Wny^a%|`qEcZil=@NDnH
z_74yy5LAR;AzVi=V_H0qP>S#!<lT?d8wl?q{2l;4d%^KS>=3(TfF8b3#NQkrz7XPT
zw(+0iKhifFAK)j7$|g0Uu5pUkaGyq8w>oYaQD<^9T{HfJ#4V%DV{4b5%PpKJpEEIc
z{zTF2iPDOXvbOQY%Ig`~gNu*#Od7EP&dtsp^bZwGnpxArx!jXhM%p+}!LVm&)1;j>
z9bjy@a#(rFJJdeuWULG>uW&MxkuI*Fc#@f)+>_1OoFBW9&D=}y=IQki7rq_tOsW}E
zJQ(O;&cy$G5XFyT$QVO$)(m4|?;#YaChcFcgZf{o-~JG4nR>;rBr1e$X=X(hJ0c`Z
zc7Z7E3XemR0dzAiG{LXow=F9|5veaIuOh`TBam@QEB)Y=rpyOCeC7Xeh)nzc0GjvR
AQ2+n{

delta 6830
zcmbVQ3v?9MdEVL8uB2T((F=hdBMGq9MncvKfy840!Ga5h@HEC4d9*W<7VXP-Mj)*P
zi)`#THekbz@gpa#UDI={19ptJK1mz5kmT4&8(c4On~<s7VoqC->(kPbxGhfW{@)$F
zEE^}M1N-T}|9|g)@BLr*&U`ZLNPT3_`)O{j+eT0M<JF;&SI*`gmnuDI({tm0C7bP8
zn`YZ3skU8qRodlHtNB|}wIuTg>~;JzDa)d=-G`mKa<Xlz;AeZNl{?nDW32CY>|=dB
zc_b}>RL$pqFV(Cspmrg(Yt$Lq47G@U#q`V4+^SQ{=yt0mBrg*EONn2m6{|C~j4ASR
zl9veiEa+>SP3=<Au9%|7rB)KZY(metewSKB{F#G=-rCen$9ad8NPR!^?JUn7w0|}q
z(7>N8m@75%vjt0C&0w^rZWQ>XvPz;&hi<Tu9F_}y6`(qG*NjJVq=o#wsuIc1|Ea3h
z<paN-=T`5Y(GC(yOy~ZPYV@*3{!n#Q$po7nM2AK|34g7+O<K&aRX5!B2u8TOV^L$j
z7V7CW7zSLWA3c}-38&l_RKn~KUn<Y@JV8A6B;XMqk*gaqyP46$l);e<HbsaYP?N}9
zx23)-9`Tw|jIHB;Dp!{+!w`2wVSO6YLkUgvqorP#XL_&{tKGnhYHrI~L2YjaTg6w^
z%(+ACEIS;EYPvBP))*AACW5Q)UcmFQ-)m=wz<in?uaUFX6X})MM*b%?-rZZk-%4OQ
z#c0#fuWP20DbXH{X%Kb-9zYLAPf#%(T?%9OfVUH{3xaGd+8@!FVrZr#5sI4`hBjcZ
z`}y+Pikdy>kgsb-=YSCk_Jx%$Ev&O3#;SmO`9rmfYI;ES0^nd4BJh?@bufRwcC!@W
zbL+ghQ4*T=UdCcX@CSXxsaTzvTT+98wSYN*xqy1U=gx-Y?-4oTWK)6*GU0C#0}If!
z6KoS^V|NmHvtZ0Yoq8k|GkP_ZJ%etG0nZVPWKLHobS;5gcmVoGB=Xwb#AyKgd4QjQ
z?2CXJv74E(eq+DF)X}AoEd;az76IA-Er1n(m4FU@aCuF0qG(^Nxij7$*0s)HufmMR
zc(jLYKnHkt#LhN>-bmoBVqc>_JiXlOgR|Ifz`cO`0Vx90rN<FIW)A!mkLe*J6pJ#r
zj!QmoG8-Mg#6=_dQ(c5keSk0^0uZipC<8v>D;5XuK>#B#T_R?EW~LPsKBf~_&nJ*S
z_oQC)b+~WgU)S=5>u!g}2`35*Pw}K>!D*%yZWQ)ifx#1|oi{&G4AXWoO)+}E%(g5|
z1H7{*j9M_=sQeG^n#q5&qkPt_tj6}H?)AH}Z?Pd`UG0*I4JAAs>o&>tJqseCsCVj~
z5UpZkW=>$`w#gW6<rmkLuALU?lYuE>egI=v0IY3;LR7NVfHi;sU@=#kXD*o8tr(pV
z%}}~x;gBBr9Zb?VO9U38XR>%$VYiEC`D(w)F#mm5(sK*L9Nm7q$Yk~tC>HMiF({ZK
zk+Y*?Q*(VJ`~^e(1-g7bbJ<^l_fvq__GE5e0PkIbM8T?nD9=+YOYGT+tW^P72);Bg
zIonZEGLeN=q*PBt%ADzug4yl^AP3n+z|Ver^t{iX^Hruc-}9V1f0%|KE$Jy;LB;OB
zl-p+@vb~Ne)omGX=~}E_CHCmAB$C<LHPHV`b|ZQe^fiZ|KLULvL(u;M`U58|>0_cS
zLp?=Q!rsup9wLH{9}!nCLo5njGf#JI4;(`$Pk%hFF<DeOnnWC5t4J`m*tB2N*hH?O
zho%M8=!?*o=6%7sxmQ3=98l~HG*P|GjF29slSuE6&=HslE@-z-63D*`xK-wPi>-Qf
z8J(&DS9paw;u3YIm_Jxo#=qlprLL*JwkJ25IU@2EUGEHc>1H8X-AvOuBjc>xu%<*O
znn5zw#FIx98P#^<Aes4D+mQWG{*dF4#~=q-k1CxWqaT)r90%+}(vUqtq61E%oC(i-
zn@zPRNaX?7kR6PPcIJ?4D6_|YAWL<q8T2>XaPWh@6$PsEjB8w{WFuzf!Af72nyF?P
zu!nfmY}I|nbDGwKXDFMbr0Pu0X_v*pxD#h9)~UH_o|-=-sRiH4Pz#4#;_r-aJJlk!
zSS?XYrf4ix%hZ`?%1>jr^qiS>I?JLabmft@*+cd*U77!1U3_zCCBM7VV;{2dnnT5I
zwGu`-;HI7C?X9R7a;sHp^%;45A(-A;2pwXVrDFbKyC)-q6%O&?ttC9?O?Smsn^892
zW5_*jx~(>Ejq+Xop)rde+gnyA>%Fo4p=ggBPz?EQ^1Q4>RWup`6bpjGhu2o}AMR~v
z{X&Gai;f5y89^h5qH;XeA60d^KF+jmjWJF2@+*56%#rKET8|POoG<H2M3WU={(>?u
zFYM#VMEjZ$-A33K<#LS4p9@Gi(ytqGmnO$qY+p#F8w>(0ky+QRYCa_hqPwlFwUrXo
zM*<7#L6s1UifVO~C{x-`U2sP>v-#D&W$X5%4@zeud)z8+_9)s;nNr1lQ<^)91YnN?
z9)lp4Vc+xPin^?+(Z{|4!9zR}p54?;q}OSch$CP>0eF(Y%;@Th4J7hDXKXirGdw4`
zfyAMm6vkGK%`x3OlyJYchVF!HvSOHyct|rd)KJi1XQA~4z%7e|$0`n)l$R_EkPSeY
zFmsHUp@ciF_W(1GuZ`s2UNqq$Ds@3EYA8K)amLMEXN4FkstSdujVJ47^OKSF_w6V4
zA=`D?mQ$Jb%(;|bk<Op<L8+Xsx&QsrJ?Vlym*j?YPUUr%ZRVWxyhRtw7CoMGY1X_~
zDlX1i_`RZw<x3yWyHwru`qGQl{`0<zRe^NY?8}AK>6(^w!9rdheXhJRUA5qKN4m1*
z^+0;b#-Hfv_O0oy+tNAP`H!RhQe|pc>{FL?n78e#k>2C??OT?_Rlw`GnOPSItXb31
z!Nk?zwsGd_ra)6i6FW?8AsL}#g?2Dn2L^f(qX9de3qaxbI_c;UER+~Aa%_;L#Zt`{
zKufvJmb6B(CX8<;@H)p;it%G}U{W#P_@o#w=Ci<ukz@0=Km?$eS_rxoum}um_0~eL
z*bzt4TI=%hwN4#F-6yB9>?C$Clv}G=46Sx+4LEk0NFK3rak0R8$&f+bOzQ<e<WNRf
z>o!bRFTGRVIrdV?a<NDpqCM6t+jYMw?GuUvw5F5L(++r+2L@{Qz$`s4JdbDOoX9VB
z0n%XtI+m9~84}1!rAI&&f%i11Hc*F%+Sc<>@oQ^8OdLK(TNT>Hz@_}10l5(gCSE11
z1S>I};n;qvS2&H$EWN)g9*!A0WvIe>*&Dogu&zwp_s&4>##_W7-u85MmTw#^-|!~X
z;eum&AlnzxLtXTy`qhVZk(G~?Sa1!X7EsMogY7Qyn$^y44A$bL9Lu#LI>AeEg7c^A
z+&qv7NS~yRCLDz&+c5ARz`cMyfG++=Pj*Xm5**p>67ua_KT=c6R1%WS8?jhtTwzLt
zZ6_AhlAvKq33^#Sdt{rd4=ViJbF^LZ^1xBqy^i{OGsuz#j~^{g_LF?{e?I%{GgR3{
z!In0KMEi(&)hC`$&q2^ib=XG&)CC3&#0<7|HwA-i2=iw|V^NJ3gSfFA*N&dTSt4W*
zVIy|IFzw;}EJETQnjlHP8-BI~y@#PGQw>G%HDV&1o`uROUPn*t*_!6}L5b>(xW<<T
zFhnFBA&QKlsMdM$Fa%itSmb`-M?ltEA;!KA>2bhrbor!y_ftRo^))|zeYn6+9jlQ}
zrQSJKC`kwSrKdJ0Mf_V~{k+g(V-xG3B}|+Plk4d5LSOwEe<CN=O~;&uQcvd`rX^D@
z6c6LnA|vC9V`eL=+8I}jV6Qk4ye@`FGVKF{%p;Bn5lsy|_4E#DK6f8~)7uNnga}M&
zL&DM6+|9z^;J72D6H@jVzjpkbw1>ZPVp+u@>M`c%A5kW|`*AgtuRL}_W=FZiXL;6B
z+j?EUo6qC(T*AB|zJ+^Tn<09I5A%{a8pv|YCN9A%L3M)n0N{1ND*gk$C5fA{>Ff^2
z6vNC$f*B!$(rYyatO1DJ6iIjwMv0w%4}-E`4`qOktQR2I1ztuJUvIwTnDj2NGI9%4
zigPh97z_7D_=#_Jx<v5w@&Ej0i?o5ye`aRedi2@^_&!w6040p=U|P_W6jSQ50@rEK
z*CyR`(P2+ZVUO|y&n)&Gq3-4k@dD8qGPH=^smB=k*0c}mqL`Z55hWDu#3uynq+LMS
zUw-0b5idUZHR-XGcGB(1N15-TA3Yg(K|1)7Px_d@@lu1dnqPjYE;&H6P@t@7!oLv*
zE5Ra%0S{Y}Rn37w$71WN4=OoDKvTEr?CVhIBbK<?WY#q`wYD@hv0@BE&Wt#x#HvU!
zB#!AC`-&JtKarUOF!#;Oy4EKA3()+NS-BLwjsb?PPFCFz!F;t_JU{newG!%*AD<ev
zLF-f+q(O-?9(}QFEt^MUMMjfuk-a~IMiFh|ggS`6#lP+Cp0~eTotzB8N1#K55aP~?
z!<WGm@rFHF!SvPDeeBcGI~a&q68XtCpedrn9i-2RJuw!d&r;d(7{B!LYAeQcy#I3l
zsnt?Ab@<c|T*-QjP7sWWw7MXc0^VPN8gnt-Z&t2c#ohz!T>|p@%0+>Nfxr~sI_ajV
zTQ^zjz=VU@-(bivC{YkEVz8@2VRX?Ip_R1RuKCT(O>rX>q3^-R(Q}HA(R`oA1lV5_
zQZcuK(?T>`4){j^R&RM5#ftqLyk7t=0d4~iZWX6OkLCS;_A~K5?nwsvwXnQ3)=!tv
zNr$svqW`3mOS-8S<q&#Jd*z;T&KEEf!%!-x)SPJ!4?!v%E_~ho0@}B7wl{amDL&oL
z{5NOXJRe}j4*@z~@v4&fXY>I=Z?W?yPR&mJ=vCQX?3GLxon7%>-79VLIyP?H<}K%S
zZ#5>xLh>=Y15gP#L5j@m)rz46=;)@~e^)FPW(GuW1AYPcCE)J>{{V1d@;?N~fIkLr
zGpM%#R{$RYz5ytJG!MZ4_N_c=U+SZ`B9eblIw1YKBOp0<N|!2Xu8&czOU9|KJIAR9
z`^Tuu**Q0yV#M`b{Of=I&a7WKHH^1r$f6m%CG6iYWf>nmS0$b1S?8;zExi7`Z%Zdh
zO;?;=MHSuJa;C1)7djSY+p)AsFGA0>h2P9t8i}d>VQo44l+@FIo8G}+J>Ooqp;+1}
L{fABb5zF{LKaPaD

diff --git a/app/services/__pycache__/report_generator.cpython-312.pyc b/app/services/__pycache__/report_generator.cpython-312.pyc
index 9a5e4a9d167cb32d2c13a3008e7efbd5f2785028..602f5625b16d262c16b2816771214288d492d260 100644
GIT binary patch
delta 2206
zcmZuxZA@EL7(S=Bx9x2yA8V!GEo~_UN=rXzDJxrnI;i`UEjalYb@47L1D5~`%e)=x
zubI?@<!FN07V(e4fXPg=$o@>@%qC-It1%g)1(p~S|5-m`=8PZbT-I`j+?$;H-sgSZ
z=REh^^PUgq;q*LIE-96AfUlbNs@FW9DX+QU<Mb`p1q!|7)uGdk)liFOyc(rtoF*)C
zaawe}(TeehjaL=sIq?RX)bl)>fT!nqddxfNwzXm!D<$`wXrlsx@v@BwXR7Dm6CDF*
zK<9ie^rLqeI#8wG>U463i{P@Tz<_{Na|+f$6vv-bVTD>W=nqDX0;Fy{SkUK;h3bod
zt-nka-mr&F1s7*T-}$3d1AeLlcG}Gu*#^`a=#3g#&%C+dJ89xfc>cyM^LsZnImu{D
zpc}x>T<G6`99E&hMh&tysSi~>rD)}>Sg~n~VrWy50jz{=9=49yk~RoLfV0g#`Lv{+
zvk!G4AEQDCLSYz2_nNHeZj%iyhIXiSUXpP3M0If$>_hudn^P}JR`W(q2G!<jHloA%
zr|dX52e#9S?V#gcExH<1yQ|q<|D)A#HJG-0i|e*Ih^{nQl<lm#xMEK9Pe_AWLi?Zg
z2X~@e=m72H6da8WRhG|p6t`0?2ZnmcXSrmBWk?EtC{sYWIyOcuVE$3Uub{Zv;>7iw
z_|0ADOScBwdA5kU2ol@Fb{3Hawu^HOSqcla`D82Ec!7ntPMmAN<8znkq!`clBAM?Q
z@mU1`Nw?sK@8#U6Gwe{-3!1@=&V=1gchNP2eeb(O9RYUW17mPP1VJx=_@0uaO3|Hg
z6jq{=76Uwm@;fzUI)S>C)1iYcrZU|*-IO@>9xF}aXae$VJ7GtJY&)mhrg`{w?8Oa9
zYOzXOprWIw)FYzPBGjqbR)=pwfey2wgW4jxvbLlSZ(8ZFIcet1Ls7EvUPxL5AL838
zDaiRb%Qm+8o-0mAr7mqw7cnP=c7t2B`7?v>FhTuW#d^blusXVJHED>AvxndFMIBM<
zhr;qrfHPDtn1Ib-3Z_z@QWLOl|M9E{9XF`cOA)nLG#W>LM4wOZYx_b3=aC|ILna!X
z#<HXObSB1%pa+FIWAGX}+j$QC-8l?zqM@#L;R1TpWmKdI?{hqid5|UUL*4NhOr_tC
ze+~Uw>rD5o=1SlbQ^pa>Xqy+D8EyM{WnNOs_?Au9`zBw;<hyU`&X~HF%Z<|`3wzRN
zZ-v;rT%uVvxtEPq_l@3+(VJ(0x()sYXtn&jEMJZm4z9y4G=0biJ?Yzr4#UX-2$<+!
zW7GK1e7nPth`_JRC1k7*_5u2arK1kN++-AeN^nyh!0|0vyR<I?zA5wfd8kDw!||fL
zUDodhw|Dsa9n_MT#7iYaYN@tlpbjiG`3H>Dof;XA?|3X2|F*QleM|-JMwE%k2)xHM
z4_ZJ5C~ziI5`zf_e6QR?cn=z2A}oI3R^fOB(0y`dg_e<6sqb@9D^7~U^^n9aKK9Uk
zVd+YMm|BT2{WdBqR`r{xtVV*FSrbhV8)0T0bbq5XTQ8f$X0v`~Ku2XGssS~XD<#yN
zn#M>@N2oa?Jy0XfS&98z9doRl%K25t6x1qBn5zmJBdg_vxvF9Yjnt|!IH;l4DoA!s
zLt|vkNV01dCLy8LYE=nHtwl(79nuMhgj$!7^g6>Ng4FsBZNf{f*YjyFO^~2C5kc1v
ze+++0pEzQMlW$P8{Gq8TPm>@o0a`;|%7-$bF-!+$sOj*9*YgYy$${RKSMXs8FxY3B
zW~tdDv$BtNXY~HOlE+Jd#W^$f!AQQ0e=P^{((^A*1<t?vj`{Zr0*zY9CN0N9UFGP{
v0Ev2Dfs1IU=cxV{lHjxCn0+j39XZ9G9zL;q^iP!S36{lWQ2r|*BTxDdGT;Aq

delta 2266
zcma)6YfO_@7(S<`U)!&>g{~Foozj+43Y4}KDwlETxalS;Dst`6Pv;o8tgtbcue$gP
z4ND{^F)V849~T$creVu;e`e;QQ`|-q6A=n5`?dXWX>`jHmyn(FVQXdluuV?h^Ssad
zoabELZ*m%bG7XipN~Ii--@Y-+n_I6auessxGq>CmNWy1Fb69|P1hVlv9y`?GGaefm
zua{cM825bb$(s_>LI9!$o*i(n#pxqw8)1@j-asqyMeiWA;q6{ahGPn@<)TL3IH1OL
zPCY*3&45Ot{Z?y!HA!+(`kxZ5@gO*&8F^Ymas|BcEI2PpszAVLc?BobrLkOi&hKuO
zCRtHaTCQ*;kaA~AGR^|deI6xe5Tx;ocoWX_Yw>SBH!2olo1}y{am6~k;w#37{O(#4
z=b6q+8jhNIGqF@kw~{8~eJ0LJBB8WQ88I7xR^iA^W!g6Db82~f9#IRdQ>%EU#sW^l
z1qZD|c~Kh#BEZ|Gp6)Md=j{W{*vo2gYk3eqEX#wH_|G!Grs|x8w}<ViW3UfwqZc8H
zI*19k#lcnUNbWfs`FuXHQA2GAMy~|4ZU^`B|9DQ`NqDvE?AGH%z^ZKEw5dZXz~=G;
z&nzKgi6B`xQ6AV_z$<uWIy8mW3`Si%7}!I%;g%)09ZkPQHi`0u+$(ft!tbDbCE{JF
z72WuY3Ip-bm_my1_2O)G6W5$Vin$iP2(MOT8(NbXc^R#IF&Vd>XQE=FypJkx7Jr~1
z9Z-^XjobJVyf5fby3<~N2|g7pc9x|4vBcr4=TJMa0WTPaqap}80VMy^l5qwv2Wz1c
zo3|L8-212#j6xe2DOx)N0PG-Qj_T9av+{cU`W91${+Rx>c>E+Mjgn{-()#wC7pS-M
z`VBhCM$fO4^dMCux;1IKx^^`F@CB5e8!8Juno>sNt82=5wNjT+7uAzTEFCmQExcu*
zmOjS4(cHAn`qoRP<@|i^1{)FjFKxMr)N+O`>Bm^UURn5{2>q5;{a&hC*Jyk08tOKz
z7aB!S5?UdpBpRQ8s&u((v-q|CMG@{dXlItHwBl@+XhD6be<XY;a`0eysDF4kJh*>2
z(uyC~?qDJ<<XUDzb>E5L=NN@<AQ+jP`8mXipa=V#LhxHW+H{PGTqG>~chexeh4(jq
z1h3&lvr+XG0V7w*FzlgeYl{<qXqMrYmJmEOGv4w8tTZ|<sV{Y09{#L1=BkVttFFEg
zGd9l2bn`i`F=axcV!iVw>wS|qX7b)Q?Tndr&Sx6uO6%u#b<CXDsupV}-E+Z~1OnPR
z_!x+^@-bOLj<0NAfgwE6=9QL$mx^L)H(qTknfa&943F=HfUW&^c#?e9Pc#_9KKQ+P
z6CDc!ofXUtOM{C{ZnBClF}SG>kocCoUfSgYKdOCQ4s;vINPK%!y{y{>?r448Ml>s-
z@vMqU%@%Iz$py3Jz8(#_TOcFx-BJs|f68nq?v;aIYLwyQJ~*eS=*t2zk%DAmst^nV
za4(}#OJ)yjFzgXOuxn^s!E{0PLA8v;3u1j&9$GLX8e1Wa^Mu&Jba|u;h1Ar7kL}i>
zg(^+A7A>kIgt@3?2(qZ7%ta&9oiAOq%8nDWi!Qb&6D|5QJqi?OC^fEN2olev)VPM}
zF-hY&)P6jd?UkaqOVcYt@oLIk5-|i>l2Yc9obA(~B~74Dg_dPByR2devaF%m<t(<Z
z1}$4OeL=MB6S6_3&q1IXnqC2HxCpJVIbkPSvC{O4lc7kFIPAmU?D`b`G1J#>hW?|7
zk^gGSO)xY_NI;GuAr(Ry$Tm#+FQCcb#E}FmKysirB@{>Tm%Fpe1V9BW&I`jI4<#~$
zX(o`X#txkJj~zZ~{!2}vh?Tz3OftB#A_@Ft_hEPkAK25Oe?)O1X(7=QS@qD{+`EGZ
VUyeM%_x1!bnq*M^2+&a={Rd-03S<BP

diff --git a/app/services/context_generator.py b/app/services/context_generator.py
index 090f282..fd9a1f7 100644
--- a/app/services/context_generator.py
+++ b/app/services/context_generator.py
@@ -552,6 +552,407 @@ class ContextGenerator:
             "hr_athlete": hr_ranges["athlete"],
         }
 
+    def _calculate_rhr_table_data(self, age: int, gender: str) -> dict:
+        """
+        Calculate Resting Heart Rate reference table data.
+
+        Args:
+            age: Patient age
+            gender: Patient gender
+
+        Returns:
+            Dictionary containing age_range and ranges
+        """
+        # Determine age range
+        if 18 <= age <= 25:
+            age_range = "18-25"
+        elif 26 <= age <= 35:
+            age_range = "26-35"
+        elif 36 <= age <= 45:
+            age_range = "36-45"
+        elif 46 <= age <= 55:
+            age_range = "46-55"
+        elif 56 <= age <= 65:
+            age_range = "56-65"
+        elif age > 65:
+            age_range = "65+"
+        else:
+            age_range = "18-25"  # default for under 18
+
+        # RHR Master Chart
+        rhr_chart = {
+            "male": {
+                "18-25": {
+                    "Poor": (85, None),
+                    "Below Average": (79, 85),
+                    "Average": (74, 79),
+                    "Above Average": (70, 74),
+                    "Good": (66, 70),
+                    "Excellent": (61, 66),
+                    "Athlete": (40, 61),
+                },
+                "26-35": {
+                    "Poor": (83, None),
+                    "Below Average": (77, 83),
+                    "Average": (73, 77),
+                    "Above Average": (69, 73),
+                    "Good": (65, 69),
+                    "Excellent": (60, 65),
+                    "Athlete": (42, 60),
+                },
+                "36-45": {
+                    "Poor": (85, None),
+                    "Below Average": (79, 85),
+                    "Average": (74, 79),
+                    "Above Average": (70, 74),
+                    "Good": (65, 70),
+                    "Excellent": (60, 65),
+                    "Athlete": (45, 60),
+                },
+                "46-55": {
+                    "Poor": (84, None),
+                    "Below Average": (78, 84),
+                    "Average": (74, 78),
+                    "Above Average": (70, 74),
+                    "Good": (66, 70),
+                    "Excellent": (61, 66),
+                    "Athlete": (48, 61),
+                },
+                "56-65": {
+                    "Poor": (84, None),
+                    "Below Average": (78, 84),
+                    "Average": (74, 78),
+                    "Above Average": (70, 74),
+                    "Good": (65, 70),
+                    "Excellent": (60, 65),
+                    "Athlete": (50, 60),
+                },
+                "65+": {
+                    "Poor": (84, None),
+                    "Below Average": (77, 84),
+                    "Average": (73, 77),
+                    "Above Average": (70, 73),
+                    "Good": (65, 70),
+                    "Excellent": (60, 65),
+                    "Athlete": (52, 60),
+                },
+            },
+            "female": {
+                "18-25": {
+                    "Poor": (82, None),
+                    "Below Average": (74, 82),
+                    "Average": (70, 74),
+                    "Above Average": (66, 70),
+                    "Good": (62, 66),
+                    "Excellent": (56, 62),
+                    "Athlete": (40, 56),
+                },
+                "26-35": {
+                    "Poor": (82, None),
+                    "Below Average": (75, 82),
+                    "Average": (71, 75),
+                    "Above Average": (66, 71),
+                    "Good": (62, 66),
+                    "Excellent": (55, 62),
+                    "Athlete": (44, 55),
+                },
+                "36-45": {
+                    "Poor": (83, None),
+                    "Below Average": (76, 83),
+                    "Average": (71, 76),
+                    "Above Average": (67, 71),
+                    "Good": (63, 67),
+                    "Excellent": (57, 63),
+                    "Athlete": (47, 57),
+                },
+                "46-55": {
+                    "Poor": (84, None),
+                    "Below Average": (77, 84),
+                    "Average": (72, 77),
+                    "Above Average": (68, 72),
+                    "Good": (64, 68),
+                    "Excellent": (58, 64),
+                    "Athlete": (49, 58),
+                },
+                "56-65": {
+                    "Poor": (82, None),
+                    "Below Average": (76, 82),
+                    "Average": (72, 76),
+                    "Above Average": (68, 72),
+                    "Good": (62, 68),
+                    "Excellent": (57, 62),
+                    "Athlete": (51, 57),
+                },
+                "65+": {
+                    "Poor": (80, None),
+                    "Below Average": (74, 80),
+                    "Average": (70, 74),
+                    "Above Average": (66, 70),
+                    "Good": (62, 66),
+                    "Excellent": (56, 62),
+                    "Athlete": (52, 56),
+                },
+            },
+        }
+
+        gender_key = "male" if gender.lower().startswith("m") else "female"
+        ranges = rhr_chart[gender_key][age_range]
+
+        # Format ranges
+        formatted_ranges = {}
+        for category, (min_val, max_val) in ranges.items():
+            if max_val is None:
+                formatted_ranges[category] = f"{min_val}bpm +"
+            else:
+                formatted_ranges[category] = f"{min_val}-{max_val}bpm"
+
+        return {
+            "age_range": f"{age_range} ({gender[0].upper()})",
+            "ranges": formatted_ranges,
+        }
+
+    def _calculate_zone_metrics(self, pnoe_metrics: Dict) -> Dict:
+        """Calculate detailed metrics for each heart rate zone based on actual data"""
+        import math
+
+        # Get zone boundaries
+        fat_max_idx = self.pnoe_df["FAT_smoothed"].idxmax()
+        optimal_row = self.pnoe_df.loc[fat_max_idx]
+
+        # Detect VT1 and VT2
+        vt1 = pnoe_metrics.get("vt1")
+        vt2 = pnoe_metrics.get("vt2")
+
+        if not vt1 or not vt2:
+            # Return default values if thresholds not detected
+            return {}
+
+        # Define zone boundaries (from notebook logic)
+        zone_1_start = math.floor(optimal_row["HR(bpm)_smoothed"] - 15)
+        zone_2_start = math.floor(optimal_row["HR(bpm)_smoothed"])
+        zone_3_start = math.floor(vt1["HeartRate"])
+        zone_4_start = math.floor(vt2["HeartRate"] - 10)
+        zone_5_start = math.floor(vt2["HeartRate"])
+
+        zone_1_end = zone_2_start
+        zone_2_end = math.floor(vt1["HeartRate"])
+        zone_3_end = zone_4_start
+        zone_4_end = zone_5_start
+        zone_5_end = math.floor(vt2["HeartRate"] + 10)
+
+        zones_list = [
+            ("Zone 1", zone_1_start, zone_1_end),
+            ("Zone 2", zone_2_start, zone_2_end),
+            ("Zone 3", zone_3_start, zone_3_end),
+            ("Zone 4", zone_4_start, zone_4_end),
+            ("Zone 5", zone_5_start, zone_5_end),
+        ]
+
+        ideal_breath_ranges = [
+            "Ideal Range: 15-20 breaths",
+            "Ideal Range: 20-25 breaths",
+            "Ideal Range: 25-30 breaths",
+            "Ideal Range: 30-35 breaths",
+            "Ideal Range: 40+ breaths",
+        ]
+
+        def speed_to_pace(s_mph):
+            """Convert speed in mph to pace in min/km"""
+            if s_mph <= 0:
+                return 0, 0
+            s_kmh = s_mph * 1.60934
+            p_min = 60 / s_kmh
+            p_m = int(p_min)
+            p_s = int((p_min % 1) * 60)
+            return p_m, p_s
+
+        zone_data = []
+        for i, (name, start, end) in enumerate(zones_list):
+            # Filter dataframe for the current zone
+            mask = (self.pnoe_df["HR(bpm)_smoothed"] >= start) & (
+                self.pnoe_df["HR(bpm)_smoothed"] <= end
+            )
+            zone_df = self.pnoe_df[mask]
+
+            if not zone_df.empty:
+                # Speed calculation
+                speed_series = zone_df[zone_df["Speed"] > 0.1]["Speed"]
+                if not speed_series.empty:
+                    min_speed = speed_series.min()
+                    max_speed = speed_series.max()
+
+                    if abs(min_speed - max_speed) < 0.1:
+                        speed_str = f"{min_speed:.1f}mph\n2% Incline"
+                    else:
+                        speed_str = f"{min_speed:.1f}-{max_speed:.1f}mph\n2% Incline"
+
+                    # Pace calculation (max speed -> min pace, min speed -> max pace)
+                    min_pace_m, min_pace_s = speed_to_pace(max_speed)
+                    max_pace_m, max_pace_s = speed_to_pace(min_speed)
+
+                    if min_pace_m == max_pace_m and min_pace_s == max_pace_s:
+                        pace_str = f"{min_pace_m}:{min_pace_s:02d}min/km Pace"
+                    else:
+                        pace_str = (
+                            f"{max_pace_m}:{max_pace_s:02d}-{min_pace_m}:{min_pace_s:02d}\n"
+                            f"min/km Pace"
+                        )
+                else:
+                    speed_str = "-\n2% Incline"
+                    pace_str = "-"
+
+                # Calories (using raw EE)
+                avg_cals = zone_df["EE(kcal/min)"].mean()
+                calories_str = f"Avg:\n{avg_cals:.1f}kcals/minute"
+
+                # Carb utilization (g/min)
+                avg_carbs_g = zone_df["CHO"].mean() / 4
+                carb_str = f"Avg: {avg_carbs_g:.1f}g/min\nCarb Utilization"
+
+                # Breathing
+                avg_breaths = zone_df["BF(bpm)_smoothed"].mean()
+                breath_str = (
+                    f"Avg: {int(avg_breaths)} breaths\n{ideal_breath_ranges[i]}"
+                )
+            else:
+                speed_str = "-\n2% Incline"
+                pace_str = "-"
+                calories_str = "-"
+                carb_str = "-"
+                breath_str = f"-\n{ideal_breath_ranges[i]}"
+
+            zone_data.append(
+                {
+                    "zone_name": name,
+                    "hr_bpm": f"{int(start)}-{int(end)}bpm",
+                    "speed": speed_str,
+                    "pace": pace_str,
+                    "calories": calories_str,
+                    "carb": carb_str,
+                    "breathing": breath_str,
+                }
+            )
+
+        return {"zones": zone_data}
+
+    def _calculate_vo2_max_table_data(self, age: int, gender: str) -> Dict:
+        """Calculate VO2 Max table data based on age and gender"""
+        # VO2 Max Master Chart Data (from notebook)
+        vo2_max_data = {
+            "20-29 (M)": {
+                "Very Poor": (None, 38.1),
+                "Poor": (38.1, 44.1),
+                "Fair": (44.1, 51.0),
+                "Good": (51.0, 56.9),
+                "Excellent": (56.9, 66.3),
+                "Superior": (66.3, None),
+            },
+            "30-39 (M)": {
+                "Very Poor": (None, 34.1),
+                "Poor": (34.1, 39.5),
+                "Fair": (39.5, 45.3),
+                "Good": (45.3, 51.3),
+                "Excellent": (51.3, 59.8),
+                "Superior": (59.8, None),
+            },
+            "40-49 (M)": {
+                "Very Poor": (None, 30.5),
+                "Poor": (30.5, 35.4),
+                "Fair": (35.4, 40.9),
+                "Good": (40.9, 46.3),
+                "Excellent": (46.3, 55.6),
+                "Superior": (55.6, None),
+            },
+            "50-59 (M)": {
+                "Very Poor": (None, 26.1),
+                "Poor": (26.1, 30.9),
+                "Fair": (30.9, 35.7),
+                "Good": (35.7, 40.9),
+                "Excellent": (40.9, 50.7),
+                "Superior": (50.7, None),
+            },
+            "60+ (M)": {
+                "Very Poor": (None, 22.4),
+                "Poor": (22.4, 26.5),
+                "Fair": (26.5, 32.2),
+                "Good": (32.2, 36.3),
+                "Excellent": (36.3, 43.0),
+                "Superior": (43.0, None),
+            },
+            "20-29 (F)": {
+                "Very Poor": (None, 28.6),
+                "Poor": (28.6, 33.7),
+                "Fair": (33.7, 38.5),
+                "Good": (38.5, 43.8),
+                "Excellent": (43.8, 56.0),
+                "Superior": (56.0, None),
+            },
+            "30-39 (F)": {
+                "Very Poor": (None, 24.1),
+                "Poor": (24.1, 28.2),
+                "Fair": (28.2, 32.2),
+                "Good": (32.2, 35.7),
+                "Excellent": (35.7, 45.8),
+                "Superior": (45.8, None),
+            },
+            "40-49 (F)": {
+                "Very Poor": (None, 22.7),
+                "Poor": (22.7, 26.5),
+                "Fair": (26.5, 30.5),
+                "Good": (30.5, 35.0),
+                "Excellent": (35.0, 42.3),
+                "Superior": (42.3, None),
+            },
+            "50-59 (F)": {
+                "Very Poor": (None, 21.5),
+                "Poor": (21.5, 24.9),
+                "Fair": (24.9, 28.7),
+                "Good": (28.7, 32.9),
+                "Excellent": (32.9, 40.4),
+                "Superior": (40.4, None),
+            },
+            "60+ (F)": {
+                "Very Poor": (None, 19.0),
+                "Poor": (19.0, 22.7),
+                "Fair": (22.7, 26.1),
+                "Good": (26.1, 30.1),
+                "Excellent": (30.1, 36.7),
+                "Superior": (36.7, None),
+            },
+        }
+
+        # Determine age bracket
+        if age < 30:
+            age_key = "20-29"
+        elif age < 40:
+            age_key = "30-39"
+        elif age < 50:
+            age_key = "40-49"
+        elif age < 60:
+            age_key = "50-59"
+        else:
+            age_key = "60+"
+
+        gender_key = "(M)" if gender.lower() == "male" else "(F)"
+        key = f"{age_key} {gender_key}"
+
+        ranges = vo2_max_data.get(key, vo2_max_data["30-39 (F)"])  # Default
+
+        # Format the ranges for display
+        result = {}
+        for category, (min_val, max_val) in ranges.items():
+            if min_val is None:
+                result[category] = f"<{max_val:.1f}"
+            elif max_val is None:
+                result[category] = f"{min_val:.1f}+"
+            else:
+                result[category] = f"{min_val:.1f}-{max_val:.1f}"
+
+        return {
+            "age_range": age_key,
+            "ranges": result,
+        }
+
     def calculate_rmr_and_fuel_source(self) -> Dict:
         """Calculate RMR and fuel source from pnoe data"""
         metrics = {}
@@ -722,9 +1123,16 @@ class ContextGenerator:
         }
 
         if graph_generator:
+            # Calculate VO2 Max table data
+            vo2_max_table_info = self._calculate_vo2_max_table_data(
+                self.patient_info["age"], self.patient_info["gender"]
+            )
+
             # VO2 Max Table
             vo2_max_columns = [
-                "Age (F)",
+                "Age (F)"
+                if self.patient_info["gender"].lower() == "female"
+                else "Age (M)",
                 "Very Poor",
                 "Poor",
                 "Fair",
@@ -734,13 +1142,13 @@ class ContextGenerator:
             ]
             vo2_max_data = [
                 [
-                    contexts["page_8"]["age_range"],
-                    "19.0-24.1",
-                    "24.1-28.2",
-                    "28.2-32.2",
-                    "32.2-35.7",
-                    "35.7-45.8",
-                    "45.8+",
+                    vo2_max_table_info["age_range"],
+                    vo2_max_table_info["ranges"]["Very Poor"],
+                    vo2_max_table_info["ranges"]["Poor"],
+                    vo2_max_table_info["ranges"]["Fair"],
+                    vo2_max_table_info["ranges"]["Good"],
+                    vo2_max_table_info["ranges"]["Excellent"],
+                    vo2_max_table_info["ranges"]["Superior"],
                 ]
             ]
             vo2_max_colors = [
@@ -763,84 +1171,54 @@ class ContextGenerator:
                 save_as_base64=True,
             )
 
-            # Heart Rate Zones Table
-            hr_zones_columns = ["Zone 1", "Zone 2", "Zone 3", "Zone 4", "Zone 5"]
-            hr_zones_data = [
-                [
-                    "Improves health and recovery capacity",
-                    "Improves endurance and fat burning",
-                    "Improves Aerobic fitness",
-                    "Improves maximum performance capacity",
-                    "Develops maximum performance and speed",
-                ],
-                [
-                    "55-65% of Max Heart Rate",
-                    "65-75% of Max Heart Rate",
-                    "80-85% of Max Heart Rate",
-                    "85-88% of Max Heart Rate",
-                    "90% of Max Heart Rate",
-                ],
-                [
-                    pnoe_metrics.get("zone1_bpm", "81-96bpm"),
-                    pnoe_metrics.get("zone2_bpm", "96-100bpm"),
-                    pnoe_metrics.get("zone3_bpm", "100-178bpm"),
-                    pnoe_metrics.get("zone4_bpm", "178-188bpm"),
-                    pnoe_metrics.get("zone5_bpm", "188-198bpm"),
-                ],
-                [
-                    "3.5mph\n2% Incline",
-                    "3.5-4.0mph\n2% Incline",
-                    "4.0-6.5mph\n2% Incline",
-                    "6.5-7.0mph\n2% Incline",
-                    "7.0-8.0mph\n2% Incline",
-                ],
-                [
-                    "10:39min/km Pace",
-                    "10:39-9:19min/km Pace",
-                    "9:19-5:44min/km Pace",
-                    "5:44-5:20min/km Pace",
-                    "5:20-4:40min/km Pace",
-                ],
-                [
-                    "Avg:\n4.4kcals/minute",
-                    "Avg:\n5.9kcals/minute",
-                    "Avg:\n9.4kcals/minute",
-                    "Avg:\n12.5kcals/minute",
-                    "Avg:\n12.8kcals/minute",
-                ],
-                [
-                    "Avg: 0.4g/min\nCarb Utilization",
-                    "Avg: 0.6g/min\nCarb Utilization",
-                    "Avg: 1.9g/min\nCarb Utilization",
-                    "Avg: 2.9g/min\nCarb Utilization",
-                    "Avg: 3.1g/min\nCarb Utilization",
-                ],
-                [
-                    "Avg: 27 breaths\nIdeal: 15-20",
-                    "Avg: 28 breaths\nIdeal: 20-25",
-                    "Avg: 31 breaths\nIdeal: 25-30",
-                    "Avg: 42 breaths\nIdeal: 30-35",
-                    "Avg: 51 breaths\nIdeal: 40+",
-                ],
-            ]
-            hr_zones_colors = [
-                ["#ffffff"] * 5,
-                ["#ffffff"] * 5,
-                ["#ffcdd2", "#ffcdd2", "#fff9c4", "#c8e6c9", "#c8e6c9"],
-                ["#ffffff"] * 5,
-                ["#ffffff"] * 5,
-                ["#ffffff"] * 5,
-                ["#ffffff"] * 5,
-                ["#ffcdd2", "#ffcdd2", "#fff9c4", "#c8e6c9", "#c8e6c9"],
-            ]
+            # Calculate zone metrics for the table
+            zone_metrics = self._calculate_zone_metrics(pnoe_metrics)
 
-            contexts["page_8"]["hr_zones_table"] = graph_generator.generate_table_image(
-                data=hr_zones_data,
-                columns=hr_zones_columns,
-                cell_colors=hr_zones_colors,
-                header_color="#4dd0e1",
-                save_as_base64=True,
-            )
+            if zone_metrics.get("zones"):
+                # Heart Rate Zones Table
+                hr_zones_columns = ["Zone 1", "Zone 2", "Zone 3", "Zone 4", "Zone 5"]
+                hr_zones_data = [
+                    [
+                        "Improves health and recovery capacity",
+                        "Improves endurance and fat burning",
+                        "Improves Aerobic fitness",
+                        "Improves maximum performance capacity",
+                        "Develops maximum performance and speed",
+                    ],
+                    [
+                        "55-65% of Max Heart Rate",
+                        "65-75% of Max Heart Rate",
+                        "80-85% of Max Heart Rate",
+                        "85-88% of Max Heart Rate",
+                        "90% of Max Heart Rate",
+                    ],
+                    [zone_metrics["zones"][i]["hr_bpm"] for i in range(5)],
+                    [zone_metrics["zones"][i]["speed"] for i in range(5)],
+                    [zone_metrics["zones"][i]["pace"] for i in range(5)],
+                    [zone_metrics["zones"][i]["calories"] for i in range(5)],
+                    [zone_metrics["zones"][i]["carb"] for i in range(5)],
+                    [zone_metrics["zones"][i]["breathing"] for i in range(5)],
+                ]
+                hr_zones_colors = [
+                    ["#ffffff"] * 5,
+                    ["#ffffff"] * 5,
+                    ["#ffcdd2", "#ffcdd2", "#fff9c4", "#c8e6c9", "#c8e6c9"],
+                    ["#ffffff"] * 5,
+                    ["#ffffff"] * 5,
+                    ["#ffffff"] * 5,
+                    ["#ffffff"] * 5,
+                    ["#ffcdd2", "#ffcdd2", "#fff9c4", "#c8e6c9", "#c8e6c9"],
+                ]
+
+                contexts["page_8"]["hr_zones_table"] = (
+                    graph_generator.generate_table_image(
+                        data=hr_zones_data,
+                        columns=hr_zones_columns,
+                        cell_colors=hr_zones_colors,
+                        header_color="#4dd0e1",
+                        save_as_base64=True,
+                    )
+                )
 
         # Page 9
         contexts["page_9"] = {
@@ -876,8 +1254,18 @@ class ContextGenerator:
 
         if graph_generator:
             # Page 11 Resting Heart Rate Table
+            rhr_table_info = self._calculate_rhr_table_data(
+                self.patient_info["age"], self.patient_info["gender"]
+            )
+
+            gender_label = (
+                "Age (F)"
+                if self.patient_info["gender"].lower().startswith("f")
+                else "Age (M)"
+            )
+
             rhr_columns = [
-                "Age (F)",
+                gender_label,
                 "Poor",
                 "Below Average",
                 "Average",
@@ -888,14 +1276,14 @@ class ContextGenerator:
             ]
             rhr_data = [
                 [
-                    contexts["page_11"]["hr_age_range"],
-                    contexts["page_11"]["hr_poor"],
-                    contexts["page_11"]["hr_below_avg"],
-                    contexts["page_11"]["hr_average"],
-                    contexts["page_11"]["hr_above_avg"],
-                    contexts["page_11"]["hr_good"],
-                    contexts["page_11"]["hr_excellent"],
-                    contexts["page_11"]["hr_athlete"],
+                    rhr_table_info["age_range"],
+                    rhr_table_info["ranges"]["Poor"],
+                    rhr_table_info["ranges"]["Below Average"],
+                    rhr_table_info["ranges"]["Average"],
+                    rhr_table_info["ranges"]["Above Average"],
+                    rhr_table_info["ranges"]["Good"],
+                    rhr_table_info["ranges"]["Excellent"],
+                    rhr_table_info["ranges"]["Athlete"],
                 ]
             ]
             rhr_colors = [["#b2ebf2"] + ["#f5f5f5"] * 7]
diff --git a/notebooks/test_page_5_rmr.py b/notebooks/test_page_5_rmr.py
index 8ac7f0f..158eb27 100644
--- a/notebooks/test_page_5_rmr.py
+++ b/notebooks/test_page_5_rmr.py
@@ -14,7 +14,7 @@ Expected values from PDF (Page 5):
 import sys
 import pandas as pd
 
-sys.path.insert(0, '/Users/macbook/bio-performx')
+sys.path.insert(0, '/home/oluwasanmi/Documents/Work/MKD/report_generation')
 
 from app.services.context_generator import ContextGenerator
 
@@ -41,8 +41,8 @@ PATIENT_DATA = {
 USE_PDF_RMR = True  # Set to True to use PDF's measured RMR instead of calculating from CSV
 
 # File paths
-PNOE_FILE = "Pnoe_20250729_1550-Moran_Keirstyn (2).csv"
-SPIROMETRY_FILE = "data/extracted_spirometry_table.csv"
+PNOE_FILE = "/home/oluwasanmi/Documents/Work/MKD/report_generation/data/Pnoe_20250729_1550-Moran_Keirstyn.csv"
+SPIROMETRY_FILE = "/home/oluwasanmi/Documents/Work/MKD/report_generation/data/spirometry_data.csv"
 
 def main():
     print("=" * 80)