From d97614d480c11229dbeeaffe31eb5bad0d6e223b Mon Sep 17 00:00:00 2001 From: Francis Umo Date: Tue, 31 Mar 2026 19:06:02 +0100 Subject: [PATCH 1/6] docs: add Francis Umo role documentation Defines responsibilities, deliverables, and collaboration guidelines for the Carbon Analytics & Validation role. Co-Authored-By: Francis Umo --- team_docs/Francis_Umo_Role.pdf | Bin 0 -> 10813 bytes 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 team_docs/Francis_Umo_Role.pdf diff --git a/team_docs/Francis_Umo_Role.pdf b/team_docs/Francis_Umo_Role.pdf new file mode 100644 index 0000000000000000000000000000000000000000..a263331af36b82fdb86204eea7bce2f19baf4667 GIT binary patch literal 10813 zcmch7Wmp``)-FzPHX3};K#-Zi39i9i0>NE|K?V;bxO;Gd1h)Xef(Hq~-66P>AVaWV z`5D689t?F7`@2aYoQB_KY9n8Un2?l@w4yLx4LPD58Ne5S` z3xEd`s9<9b13cxreWZ@b^W)6-<1Fyw48AL)Zh#3?vM{$Xk#O(;JO$lacm#MjIQaqm z++YrVf!n8=o{km(psIc zg+Oi{+!a+c@pN!?0RUB?7LpDSS9|C`%rL-@I{XBYG;uM3I9UAxb65ADFp>^X7YnEh z48VO??>h(1x3@n%s9V4sT%FA@7l(Ice>#-0fw)*W-&Pi4;$k6XVdh|N zfeBQ!fLgg&12{oo@Le&Oi?fA^J*LO2s3!)nd0rBq;fi`-lbV%%Fb#p|X>pxK;XYG! z`I^1E)fG})Y-k!C5kgIl@{22KgaoPH35J)wBUcEHjt2r;hRg*$6%%tNk3zN7TY(9jO-K395)QOI)(cG7Oe-UQ-P-d(5NGP;w&6C=^b4T9p zEkvi8=h(e5jyQ{JaAzq!iPa$D#N;A2=~>w~6C9!NLX0|PT~3?=+}(BUw{=8mH`Vdi zD1t6(E=a(%A%C_Uw(x+R0bJaGywJ6m5kZ%kWHMO_?ep>DDtqcRuUO@`mz!p}^(5-H;Ms*4}Y6&czbReu^W!?}3m_X!ha`$ZK6vk7FmGlWkK6t#lvM9sie z7O)|qH_E0IKsURG!Ry1E}|HHh$g z<7Qu}M2)6yBB&H4imI|M$FoozCl-rgMTtJ?bR280FM3nHMuC&3F#Ide^v9UM;3u$| z1ANN7%ynvgN);-854FO;S%Ml%$PBhssqga&)SL%k0RYf^*5?+J1EPOuUa6Fxj2KkvAVbJ zPmj>TD9^{7YNhiKO)x+Td=1^XIMAB@qs)hh2I2wtXAYqoglc_tyYii^yAJ{j=>{zZ z`>obXstg&Yo5{Nq2g|UVhmLBx^FKG3mvrpMYR+OZ1d-&_P9i<|!bxpX%wLUFx|n@o zjDSnsVJbb(5&bQn5XMe27U*;3pHQlXu-M5eQcYN-GHTnQyvBR&GgHZ~ zgGg12XYO9n&2>LOEzU}t{Mit_y_nUw7^7G*me+6O&HTzlp}7rSaF-<8UOjkW6Wq(F zkF?yozrBnM!+JivBS*TZ2esYVgw4T(gkkY4BPS!*!~v!)0!;h@YT?6DFeVKOM>afQ z^mR~u?HX|X(v%`gD{rPua1C2sk4Vhc?74Z08JVIpw|()jampYr85^;+W5c$ds7^pA zH%_{O(MoW%j~pn&s+;dK+&yMU_%#RqR_Zi!mDoPd%D~)n&%cFdzHz4(fiW0Vys9u_hp2jnu(g%vKP*TDTnIjvRs9-c5VhFvQu?`{;(f0 zlc8FlyxIGpbfa9kt+{V2uH-wnXWNjP2=tQw>a4R?N)S={JXodfF_jx0UCmY=41f!) zFqj9EI(IFr$QYhl8_z6fmZD!;MndNARojs7*hp+kH%GkJ6P18H&9j=KX>NY{hGM@A zX)3g}H}h$oAa(nQK0_uGj3p{qtpccTH@t^f5l2e0iS&G5(7=pUG52xKZ~1adt1+(y znwy=J&`vCnsQ}m>0EHSdR_FrR7#rh#^k~XyEZM_`+9PVBQbg=mkX+cn{pMpivQzVq zM@Vm{GZ0z} zb$=zUzN$Qo5k{7iB>84{v?(3?z$%t<@x+|$FgGzcpm=zS%&&`Jin6V;>VqE%6(wxY zck&?2WpRNiA?t=be$AU$T?i|@)jcyv`nj{`2?hSOG+zsMb?!>6fJAuIx{T|1RkO z^MXKsN;(c4=6Uh2GvBZJB8X#YMlz_2rr;sRa}V;iDQ(pcViJMOQ|lUf;uZSjaK6MW zsa3J}#_b4*nX_)KjW@Z+be|t?r9Mu zl!q(X>aHJ{9OFGlzbPU7*7oeHl#^m}QM%O=bENXxq_5sAM+6+pbt&O;IjBO-n-V)g z`aC-ZDF<)IZg`kYqXx+z7x}s`MbuW6uXYEbrS#G#v=jJ)7+&p*SRK|slOMJRa3km| zdru>Pu*ChZlCTh2gS?Azh%5z|Ehh(c<1D&L2ev>jQ%7RgHB#gm$EsA-w@cX>%BZa} z@fITH)Y}^&)60^EiELuLNVw76*zkf091U9S0CZvv-!cU2M8g7CU87spVe*W(mrvbQ zn0Y_6(tjA!esU-%B;?ad;g6iv#rlQbL|1V-)w<^seK;8gonTJro~;f&k}M$)i*wbS z?}jVxJFWZMRkB&)+hal~BEE?9oD0ZI&KMhRpw|i#705ElDO%};H3*MFx(%Mhi`%pr z`v7f&YrY^827Wl(Gkzj_f6rIVREzoLyv&fm)mwc=n}(?12C);ZiQ_h75hr9p>|H|9 zFKr%joC0q+^#mGpy2!f>N?aSPeb6l*>V{8C2%jy(=?Sv%BS{I9-47$XIg>X$Ac+G4 z*bfu^&n>KXN-^dX*5^pwSyt@*ngK;67 zOx2b=XK+D1p>Oeq*!>;eP;_0BQNGy9d-;j$q(=LAYDEtWNkJw}Z_0Vk&I54MJ5&y? zU1-(1Gz*h7{8N8IgrUv52OkY`zw&BuP))}OE|Ss2l`4q{n3ojfSpK*}0bEQnSNbIb|Utr8}y532M3r z&v}=%|JhzaQM~S5wMdl5B*ZRg1+74I4pb0ks2DD#WG_3kvc`cuMwivwAd>Pd1~;FG znDA&^lEoEGI$8#0mElF{?VGno#k`$U4`%HzhI=UF3+UtMGLv`6(z~I&$z`J)JT@e*S6P|RJ>+0 zUZie-KlPZ|d$dU%8}hh%Mi_A$u>IThL*mIWtxd*w2hE%hip-w`rE96HUStsyCiG~( zSCLEQ5c#6_IET|&Xd7CxOmDdI`u*rOQ4MrNyXs@^bRwYAF7fK59Y0}8gSNH(`O+|X zqJK>ah1R6>0@UR?#c>xx^(w}A7fqNYEH-+WZqnQOhQ=hV)JIIBWJ-6odi?mj{xKN_ za_MbG`IzqgQunA|MIjI)$pLfv^6S;mF!BQtb$aT!Shr^kjvcJ$;i;Ob*+RV5274Ot zA`#;6OTpsF*vh@t6yqK!%BuM?S$dPtPHWT))ygE|KX(*nkZDpnE76LGZFD85l4dyT znCPcuJf`> z#WlV_DSZN3#>;G+{UnanmLk5NO|JCe1zcD`y@2^M0YxR9EjO1SY;$0i|M+XrpisyZ zDM_`#G-HJ4YvSduF!m6U8;|pbp~FvA%tsKCuJvva7+qQr7$!O9pF~=*d3^Ln$<26R zQ{lqoIXviaq&AgG&0L!8*g7+Q;d(cc!)U8&IqF<;N<9&1eZ$u(`TiuDG92#$BR6z* zWn%boB35IuU20+wGsQ)cVW}pY2m7|00j5EP`N=?wJ=N(!!+=xdi-=_}-scs3n5mx+ zC|YbSGRM%hc>N7w8LTB1qnpj`Z>@{DYc1$pIxS`)MPntax@WVk2O@~wW^t|@e#N79 z?5dATDC*x(q)wF0jYMjv%k!|R^{0{hZCSWUN0C^_H?M#DC}c#(^HSc2pOh7}C;YO1 zV%tD%Bgd|DuwQ4szGk8s-!5O&{X|w%&B;EK)LK(HW_y%7j6DUHk0n%M(?f+;6a${x zq3fb_Z|G&PNVvQW;h9|%HHz3|L(T!&iNW-|s!y-yJafR#9(n=>LgnL*&W(licfc2E zFFd{%z+ zq6^Tw@*SKC9jq=_%$xblYy1joGDMnJo0-T%xg>BDsk&jIGNDSD%W~>yAr@Y9(ydtKOOq1KT%pMi`CS($} zz#wLKBha%)7WJuHVMMG|e5Qb=+61r073;%Eamq?r@v0L2@iZ(8eIK^Qf&iiLMMTmZ zOWVFCdy6`V*6c7xGqaf;iaedRy>!h&OdSQlPzFG!H6kM14wcd zwNa<_>`}k%If^4` zIjiYgfJD+Xeu}CnB&nqlF%*R> zdz0poB6RN9*O^Fb=giJpd)lzjjroCh%H94)IC~jS$odebd#$*S0m=>Wi%4 zBF5FH2ts$x)4b#!t0b-+$B_2c3eBSqfRNe-Jt#`E0#7Q8jikOXH!x{-*(_m8`djqC zaHj>!l;8w-X3xHgmcz0QOS$_585y2Yf0ShfzO0Yn<;tSQ*bv-&bw4oXb*QRS@7&1}=tDye(op1eq8lg!@4`N~n}GcP>Xi$kPUpH>2O zyr7S!N)|7i7(Q`Xo8fBOj07#lvb~+UKUBc&@`l!oyU55*QcDe{A3*9&3!8=D7NT25 z$aqed`F1DvjlVXyf1a-xr0eQxIzc2j<1~Mi>aHxT7=`^CcH(^i-0|B-gjHp2x)5a= zR%bk-HOd&-ynR4a)v^x~3lI$)*`aD9<>pt zBxcCxB`qXS+75(1sA>rFsK;H=DM|^$Y27#tc$WT7K}~ibOP`f~)p6XrL=1gB4(IXC zQU+N-D?YeA#vsWyUjPWwED!)fkbQvj(8021M4sP_8x!uD+S-N=}*S|Ck2D= z7T*8Ok~Zh>&;NFI`J?bpm;aW8dAWK1K*AYM?C++RH;YD2J-!0%bb5JHvk7!v*>+=6Y4u>Kp?lAqB-No;>*!OR1~ z-M#s5%mlae3t|SCS{oMZYWTF!&iJnJiNi%d#Kcg@ubiIe$P%pS1&uE3Vcd6&i_nC- z;C@vtx1<}`BG@<64V1g;F`*BqoYLQLV!-h3>GBcUIy}ADwfa;c5qh{G6qyhh)I+Nm z)L`p%lfYjpxXi@pr*$!FK9blH`$LG6G+;x?WcP(09D5tZu<#5_BCUHctxv3r)wy_(^$2Hxjsv;- zD2&io+T&6hx@YUmOyBE&Os1Du`f#J$JPx3B(H(!3m zX$xTJpzJcw+FLc&GB0|6`ZDjbr{`6#FlZ-PdYS@5JiRbKo5zKQXyB(l96NjlVTPp4 zuZ@>o;h4t>9Zm{f0B2|WMEuc_?ugkuR?k3ab3o>q5CPU zu^lXIdbTx=E3^O_RMdBV#rz~Z1<_n1ddvQ>myXo#9^x#Cjg6txh>6=51S`207&EQX zkV}vtXWyD)uTvSaSQXBvMYoymV#ul0k{fbI+AKOKa#qpXkG_*f1!wmac^zz*(iOR$ zzv*Ir(2a6|?Ggb-#b?Rc4>IV?Td1RY=~1&(7p0M23rW5mSOv7w%Q9XmQ}#1PFT`}l zE@Y5IGiz!y7g0OwZ~A;P$y`|`??JTq0DsooAu}lzV92Vy{P`g?XlOz$;PuXlqd19IP#bz-ZFiQw>$_r4Yf1MZlx!_gu#iwV)L^gZPsLAQh(^u5=T-% z!1yede?gd6tO8@~OApkF&xqe^<*j@DIuD=LRXk7waz5X>q~gW|8buo#8ALuR)5|~K zsSRHpv16)bNGc-tKb!Pe7(%KVXHBd93_G%^{p2^SD4gd7SBn*>894y9k4Af z^GX6nKQHNwLT39QF5>sT^vid!9{gS+Z*s2agFud(AT5uHFepw5_~V@I7mOCB5R{kzff%eerFXgzjXKE-j5 zSt@m#gj!8Kpwg1g>u7gPgNnl)D1mFJr#$)wCC^jm@*5rmj3%tyh}vR-q8)!^IrI%| zc9w77U%G*q&##bMLe9pjlndpjcV=ZtKh`&Jmlt_A>I*5>uCle`y=@WyZM%-!xH_Z1 zyt2)KhgKR6P3@UrC|YEQCOd!A-HvB`h$r+mI{Ymvwomb>5-0G*?P8>4^B1{uS9Zs( z5Xav3Mb9Ie;38g$zY^h(?dPAg^)Dv8+gSd0O!$WlDkdPQ;2l<#cpmuUBH)N5;L(4qsE(VF+?803v^o>|!= zrSNZJ(vZBF9_IQw@MWNFIfPywC7?UkS9M4LMJmv*BS;!CApNYK2BR;#p4f3 z2djK#zp{hs)a1zZbFUCcu-uaeG%#`cix4j&9ej<}mB9blqKlXcvc#AW!o8|@)ckgF)u6AZ@F`*<2 zADyxD=fI~6lN*^=%o2)sk$2ZS6hW}n_SIho`Y*4|c^En9sf~N)1IR*gG$pA+BAklo3A)4UNqh;S3K|e>U=RW?>e4 zl36?AsM%0&c^b8f&`=?3L+L!kBaX=_tTA%>?8dvLF3uWdm&7o5V$1pEhw?set>~8% z8E3moUD>z}VC!D}uv7{-l$`8heQ~TNk%@&2LyHf$z=)_-JB?S2dd0WiL;YYXgoG$q zE7&b}xxh5)AxvwBC(vhMmw~#13#vc;>Lj1mlk<8GiM6s_&a1wygx0NLgY#r>-%D#? zMW@O6Fv9iBNW%n`cRyQ@NJ2U=2xm!Dv|z&=H$Uis3a{i5cYAbtk_vExSRQ|Yih(wN zc!^!wuaXcsKP-9egL1gI8aP@f$O*;gRU>~V$&3UOGJ#vS`n@kFWnAIp;AlgSC zs=}wdkcq=;XN&BJ`S#_rnc#b%*{yRg-jjEj2Z+(JA59)JM?Wp=G~{Tq6YbU&&RZDm zoboZASYbO(&e<_*om>3)J=sS~X*K&SoM!UXAwmj+norY6gX{r2@P>Oi&--mssp1-H zv=Kl5)>|$)o=t;toU5vu=LOMLXzNq)-x02(bdCRJ;QLk7B4GlvkhvAM0D!U<5H|}K z8#5Dj2?vNdCQurBD@d_{S^8>heRCb2lFV|5VT1x%qW4{8j4m zH!%MNgkLwx{sw_v#S~)WHnkj%2t1;2&D5TiOAtIy;zYShxV50&jI#0HCIY$8AT-+268~#P3(h z->-58zjnp5hsX~7sLhT1@m(W@bK!f{1P7?&K8!KAOI&9Cg`6BfR~4d ziw9r{_?PXrFYgWj^q)2`=WSd6WaH$#jod%kxInid{6`xn7yn=UadPwBEtYf8Iy|o(h3D1*8OSn%!z(T! j%_)9+5&6$={1|s&E+)<{KceckP6GUxjEvGMGMN7ZsWrrg literal 0 HcmV?d00001 From ca8571f63fd2df63bf6225bbe9d0bed74d5a4724 Mon Sep 17 00:00:00 2001 From: Olufemi Taiwo Date: Tue, 31 Mar 2026 19:06:26 +0100 Subject: [PATCH 2/6] docs: add Olufemi Taiwo role documentation Defines responsibilities, deliverables, and collaboration guidelines for the API Development & Integration role. Co-Authored-By: Olufemi Taiwo --- team_docs/Olufemi_Taiwo_Role.pdf | Bin 0 -> 11657 bytes 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 team_docs/Olufemi_Taiwo_Role.pdf diff --git a/team_docs/Olufemi_Taiwo_Role.pdf b/team_docs/Olufemi_Taiwo_Role.pdf new file mode 100644 index 0000000000000000000000000000000000000000..9367f2c2b240b5b35df2a5610f465b23cd90fff2 GIT binary patch literal 11657 zcmch7Wmp{BwksQzkJ%{gY(T2*t@T;s`02`N@E8z%q^1OZ|CW&lA!0J}KM z-U<%n2C&PU8rlIhIqwcB0l0tP^8UW%`+W<(_fgUYuq!|fP4&cJPC!l2orRl^n~ehk zgm8h`AbfX6m7T4jK=zk<#!x$eurL5>Wq6Onad+lVycgC`D^UZuDa`5*Fd(~>DO?6< zWp80|7vSFYnVvJu9u8!GVFeY3S=d`z{ljbr{5^-CAmVy(JqwueFEIDH|AY~TS;3)J za62H^ecty0Z0~k|Mo@yuBu>tC5cpZSaJh!Q*hdS< zz*K0HjR-f@P+YnFfEsFL_639aM-hMajEKo4`OvUh^UG(Q)AmQbw1G!s_7rf|&4TUm z3`;}v&3$+#Gaq4c7W<59f>r)Rz^b^0pkDIhIj@o>TC9u@M~08zk&lnW)u;AJjVR|8 zQN&Iyhh!KdWD4R&MI15Ub}@=jpvmHQ4+)bV2Y{`Jr0EyvsHz(!i__o^4U+u1SH% z;h=Z6`}K;5$VUC>$Eq|~rfX(%->6IP_1d5Th_oT*^hNV_XlcZ8i34S}D3|aXVERyf zRo~u)>-!2G89g8Pj->))X zTbBPQ3s$h<4?BhMbsh(7P%?_&nQ6o`UJdMr zf@y#u@4#3Vo}9N?0n&b=dAYqz^J&sulds;?>~fI6q0ce4ib%@gv~=3Qa2X|#RQ++5 zHExAHfG90zpVinn%Gdz-Yy-w!{k`z$Hx~_WWl{#xf_C##GwlP$El+==cOF-)Q z{QH>SvLz;YL(${`o)?~7S{2G_#%$d;`*M|Y2Af2tvgN_xn3aIYD8v=&H;dTu!~xmN1P|}!J#fG8!nmydvg;&Pgq?A{Zk2$ZQT0<8j zMY5Siz3%o7zRn`WPiTZ;`=%5?0g zHUO7mi1>#S3|<{NNl#poh+9^Io_G7T=X@m?)|j!$cYau0peGxhA&t|BG$Ezt-W$hn z%5yLPM07xr(LQ;dN&P8SIQ8X~Tx^&=(XFp7hkJ;7Qa3LJ-Y$t4##pOhXo25vD3`JP zg~~p%vajK-m%LrQzVTNh?NpxqNj7?qs#zQBC#J;nBXOQ%G-gtMVp97)2zycap!B6Z z%uTP1)%`hoV9|KItFJKHTVi=v(W*BrhN~n|_JMZ z)TH9hs) z0+2k-!Aj6W6DCo49gS2$&_p;D8Dfo=&1zqERN~}#G!g#U>-i_aQ|Zif9+`Oidz7Vc zWmA59fs*lbH|+NE zz;EDXGJ34>Y!G>=>;|-HxCc|D1=C2rtlZt9Ftkv4^LpjPdsIUr!H{roA2GEw{u(o} zU_!@w)qx~c?9y}+s4%t`Qj(&imhS6=8`Q)VcxOuD!kK>+ zB*baz%A-ADEa=hr(;en@YLUoJQ-T#~!s&zK68dsdO4BB3{QXr~ml@%Q!=^Kbo%4d+ zS}t4padR(8qn@rj`&tzJ82y=WNM38*$5ZFsJc;sHCCgb-+r0h@M20RIEy$H;XaCH4 z-fWXJ&~LhicBYte9I_I|f3k|TG~Ho=%eav2#c>sBun|r@9(_o^RMGhr>E~8yBsk20;<=&b4@U*aEqfdrt=l-X2IW z#!X_3kf3i@NXIh__`llTIKp@lRk0SvHh0@msOBt>v(8-;bCyw2m=@2V=GI<=f2(c2 z+8s+#qbqhY;#fwBd>Y*1NWWf$sOUZBd`*_o-f12;de$I!@aVMI5%uX;h&tZ>m0bzd zh7X=O`3r+SDhgELOXPImNcIYxfPbXJ970VzZOjI zJ=P&t7$%@L_Vc=p+5;bBO^`8Pti-9+o>62XNd`d9 zDRG9bx9^G8ALQc?%5~4+eo~izav`4oh6_Rdar|E-?iVg}@B1_0f8s)59?0LhP!j(G z_n{I}Mx|)ERz!=Yqgc9K%Yy0|I>nE2G1N$N+BGaM4WjnG+#EW-b0nEUN?bu~#Z6g` z=Ue8iJ-F?m>i1ixNrXfzm11I9P_kPYHdtQ`9oW^itXJbu*~yT4kvMnYv;wHbkRu+i zNtf&|UKb&Ul??2yAFSPO@GgjNJ)rj;#+7YZ5Jt_th{J+>`rN^!di^m^BC^^0D)k)K z4UARy0H>JHm&(TbmcK@_Yq7kbgIecMs})o0A*07TX55PPq&_po&koLyh&4&VzFnFK zf#kH*Tp?9FFm4evUzcx`&9do`S@#QsW^*>w65!ygz_FMfuXR)PKrIyzJ1xGoXO3`>9GeDPUAZt4_gr^Sf*N1x(r?s@ZIDQ#eA*(4X+>EZ>BOKrxq!8 zM3X{T$i6aB-ZLu7^@a#P{CUPiBqsh`c`R}C*b$h_&k-D`hzI|A}0O2BiD>otY9pL)tqW8cw;n3Kk@zu+)#fitF5f4L9ZC9|1jcOc`ffk9w zo6kQ}YrfCN(zi=eKu6xzP441H069?Hh6eZv+e~q#w9t=x@ad5f&?Q*K^gDis27|CM z37_*qy2J+Z8QZeLk-_cNA{AuCo~V;~N(t|;I!t1U7Jhr`d(Q;G1>Y@pM-a9PEHv_*FP zDL1>A9~sJ+;_l{x;y{nWUC) z80az690WYHHj+Y`%My!g%faK8gHMJ8cc;F_^%1Z~e#b6=QUE(y3vUa`qCY3QptUX1 zOL6e3L$JWcvheGxT`^`DILJmBOB*~;k|E-m;#p9n&mluwm(&*GMkuYpwoAv8QD%7hjKcYWKr;tVE;=q4f#}a;e97zV(#>rKi z8rLUL*li4XQat@W5uNF4j`j^#`S&KphVMmFrBWvnuiE{zI_mNg&|`(Ut?8auCh)YI zMB=PVy z9j}oR|A@86oJE>EZml(#nK8<2>8b@_3=;}Dl@27P04($fpp?K2g_Sp=)1{k0#ZUFP z;LlU~&qwo(Q}nT9Kz2rgJgMl_MVl`d6ZZCBO1Z(xuLO$4ksNEU4CZf@Xn<8+P44-* z@n()_PO6Z$Z3dw5E@x-OHCFAkedulm_jD4Wl8xxBC5 zB$L4+Z-c-|7a)LVoD%QspnbU-V{pM{sWTnB>`XBoD^g=zTN}AM8kagWug17H!{gUv z;D?W@s9Q&+upYTOAZw%1e0dl-ce@h7$!QdBetEY1Q3QimsM}TyusfV^b@Cx%?DiF- z!rW?xF87a;VX;`)#^Iy6^r3HJY?8*4@d4?p{oUJck$kzDMUooCjfI=spWb8YfCo0M zG;Omv6@@hC%7#kzU1PTszFW49j-ouZdUs3r0k-|rAMtbeZ0B20?NfOzf*2ygG|R@n%a&8iSg*Z zXoQ!T#hNg;_Ag;forEJxS_qFHD0aae#8KPg2%kOEw{oe>O3ctTbEHTU;*_XGvbH!e zpgHnYEexxeXMSQ(T&1j9mC2~`tV|Fc?E&rTxX44OoTj3&vJLkQom!T;DsO^W=Muf3 zU~k#6Qke1LtnH0ZSV@w|h#MK(2G4pyPC#<8Ga|A3VvO?lV?Q0*AqzCyH}YdaiX^B; zf6X~lLOMYdjMrtMuYqUA;^jEd_|6y$FWaoQG8bPUEaX^+(Y&uQv_H{%n_1979GO0l zn)!g?K#V!iWJ^MIqbBtHKwT74VKi8)M&RCfb#hL5L=3MP)v}zDt88^v_z`7ea5T5- zIz8c+W3pAt4$szI)9~Ufrui^~b;%&__3nd~p7wj6A$Q#R1pb>25@x2Sx!;TN&pYx; z7+m_84y$QG=ZrC^3LdGD8PZr0J;n~>mW6+^S^Sc*U?Kpeu34WZOxu^5eC@6eXW-~; zHPWt8z|JGKE+!hnsj=Fh#|s}>SsA%T*qjj{F=KsNfm3XA*| z*b~Nqrh3`P#d0s1BUt*z!;#+C5Ih``>}6bLDXFL+y*UuLTn)nKZykSknw4r1nAj5# zR+?r>7x1CgFcCcdm1h|`iTia^&#Fy|*ZJlXVY~ED*qT9(04|e(jS_dsCbIcw2=b7+ zcgf`Z0Gv|$+zgK&yycSFD=Hn6LVvhU6o z8@(e{r`Gx>Ez45By>SdSe<_@h4#oVIbC{FNn{ho60`X;kE7tKWIu$Y(?Ov~`7nK&C zikD1sp$ck1+V9w)SFBblTg%@v7OHKG6Q--+Huf7a!BIksFBNTll4BKlXv&)F_Q7>q z%PN&~R$zD^0gm=%4)C=XR<3x$3E2Lq{6d< zA?lU?M48CM@s0jl=8jX&e%{fyg6)DRy&@6;8QG_M%=0BCAZ`k|apkI3oHUcV zUQZZ)qv#Mw^F8Mqpx|sDz9aJFjxFAsFrR}L{MRh>IR#g_WH@f~yxj%4XFCD0yV|Gk zjHNHXFF1=dx&G+u)l1vYUENMkI$SkI^z2&P;XshVaea&SH1+Ccot^%y!I!GXMue(` zOf~2FI!;_~FrzQ5^{7YKf#ueXcz^J)Kz3lP>|-DDs8@ph8MmRPp67{`sci^T{f`XB z7$e;eUSlM$h8RL9$~teUtjwAodfZfrlasCLm*YnLHm!1&*|O7p$iHVs({5^P;!L}% z;L&<%toezvrfAv==0oTGjALvEJ*CIOMU6+DSqh;th*SI+8M#zkn!=3pfn*(6{KeVT z!EI?v{nY31bf*fh%k>wwmvldv>81tZ*DapRD6A{K+EChCARzyKc?%ocF3AFvbDWg) ze=3VKaJI`GSXV5JeIHJ_fgDZL2FdPzhxKLa6TxV4C{Cp}N4f##UZI0_SBhGU-+nZ} zrN1BN**IIVu4rq@W-zfP*H>>gdR4!Xh7tJL=Gc!|m=#)YMA>JI{6#mzm+ExOyTsI{ ziY5#$bFKn|OB-(M^{0=fYh%~@>#e_SvOF}>ncJ(_3y>$$>|KRUJ?dDQrg?fjiI+}Hn~HU6KZ0ertE@*h?k zIQ}^PZ@;jAcm5gjKhg#sUcNukhM3n^uo<2Qw?ZDBt;iF^fu@leZ_of-3ZvQDHHKB- z!q@(uk*0|sS@H>1X|>Oq_hl}q1cH-VgT80%HC*kaLHt~}VPXM^~nhlQgP z^I;3$_@2=`|80jNSpCYyb>0TJ677rc6e;~0;|54=h2ZDAIWhyro>NR~Qs+r&yExxq zUQmc5AQRj0rCk7}AXKI5qp`mrta_kvTPzooU7~x<+l1Ww#hX;3$krP~%QY2q%qUNr z6rG)rjTLWpj{m$OsPSR8Z(oBl@v7FU=HZL@Pu|&s!d6eU@R0Thy0D9pG2)Fn#b~z@ zhx7P5)HTc^w~k0x+}R9R>8+VZF%3H?qn(?tI4#72S?-`m-b@wCZI zj7|*eT!Sj)5-}&}Lrj`d4^y(*3!7zWT+BA)*&VjFgYW7C3R!4@uO=d3ptVDV{wL z=17}hJ-`U%L30~q8g~4xiAN>B5(5qQ;jmvI_l5=Cp^=x1Z=Vn`-0)8WIS0m&^=bxjYUErEo))jNWc!Yli| za2Ex&ncjglyQGxVE-29ESwpG>8a)Y5lGpt^LegH;TPwCMkS=Kp)s&thwcj4zr4kxQXnEd*T*Dk6pbe=@Udt&q|qeuilT(8A-J% zU@{l2wWL1q?W1gl=voECX{3c(UzcPALEE5)c57UePC{pPV!l%uyTjKU-LYhT-=fNf zc(-B|Z`{1`4N-8xSlrjP&JMSSYg>kHHrU26HTn-3ydtR{O}{0lzU8MB;nl7U$YvHy zVza<_-Hi1qKaoZgC*?i(aYNnwF6&-BU4~;LbY!9mJ@JbK8#HQl!XE1tXde{tRGEL9 z)G%+#gVXxr80S^VUlIrt2>6VqB`BstL3&H7pr z_A0|z=46ROI!Xn(46(7_V0njVH#NvK^n(|jNz)?&4`<&Q;nTB;B#rDn=$h(X1Z01l z3Y%Epwz^HKG)hkvug5ktLYlFU^}7buUq3uz-E#?c>ZitfJci9L>Ncy&bwi|v>X0e2 zuw~2j)_eHj>B2t2$c&P&bCW4$a_ubaotk~H*3_&5O0{U2s(orvx2rO3 zj9g^t6Z)Q+?W8Fzbc(RH9eD0$z9PlJbae1VJh6gRT+KbW-MJbBH?1#{bhGc5EE7L) zu?FZ5&Jh`k%DtL^S&Kzud@;bayTa{keuIS(iaW^1^)=Cs1*2<>3`rFj{r#Im#KFRp zxX-7uZtp2~?flP=LQ{CU7P_e02NJ61_NsuW=*E;=`vbxVKblM;SICn*80Hf_G_nqS z#Br@O90HP5kY1=zU#VDWPLB1;Pq(TEjDAvI_n_SeG_$5NRB4_*H{9tOe6#I_E@Uvh z&1;0t3A#!WH4UhH6j~FcI(B-U9VULg=O1iCb|h^g06uX^F#K)r%9ypxhdj}dB(Q~7 zZ*~=CF@jDi z?O(O>UKQ}4YUQ6+`|ouDzjUL)ze)=JW3A){bN{JU7QNoTua!3`%}WbN3P>H5GLZyO zcuRSqNHv~(g3GsHXOLk~^_S04OiI0@#XqjX$|t7)G>$D%cu0m9bL9Kq8t6ICF9Hb$ z7fyR<#?RajFz`Mhu(KSIYBhIU;pbwXvVR}FadVwNerhXch(b-^D@*E+e<+^!kR|Nx zhn5XgRI;gVIxHt)zDo?Jv0Pudh!k3?09iogO-Y=!ZKUz`R9;Q|;O8YGy8T0e0~f+T z(Uo_EaFS#g$f?`L)L=`|_zA@^edO}8Gab}289FtERe=)`<|m%Z+s853+*u{9o2 z_0qAG2+PRQP%P8afvx(MS4yR&+xi>Pfq{j-)3*+1qrC?pi?pA|Oz8A6m#PtYQ1 zmG+{~QRb+h1(W+ihSH@@G@d|{&3XVJX4G@_*=oI_XvE~gasDo2VIK7&i(Ch#E8a-p zlCShlkj!&27=7f{VBu#Z|AU?B!{a`Z?y$U3nztV4KEpKnH9jHrTH@vD8w&D@QG-;P zYEVnv{C<|?p{Q~OW&MK+&e~~;E^Ivg>ijQ}G7lbnz9Pg&JoM3KqQY=HdtmFrA!HB4 zkjp5g^x|}_lkTasik8Bb#u+0F*^oFAr~dSo)@?MiK_-NCY6?I6f)+ANyG7XRxHR2d zFbLojQh!`C`=fUCwmL_0nrM?$cpWfgZU=L@T%A%6C&6cPIg})t22XeEM1Myc7`+|Y zst%rhqz&l1x!G`ih!k~ghqcHiDuX>fPk^r^05}6OO@5AH=iolN5)T@Vnw}0_wqwTB zWg=oqOHD7Kn)*bfL%;b_NT>2jG zd6V7Zs>Q+R!dVIwkW#;*a6QY#)t&wE#-rWo0Y33wq~SRLjRdM^jf_q27(*tmrQ#f0 z`84yao(0XS(sKr9JcQ1d+*7EMC`?4a8#COuQiN36v4#Jdg6L2Krwatp=}s*LzYbLW zK9D2-zJA2WdhO{kGWDf>YK5n7Mup^p{4ISGgr|a%{6w{B$B9{*XeE6|$k7y1lvedv|F->SQd=H0ZCD6eKbfq3?9$$UnyE6aRWJ z8*r9CnloTzUH#;?zwltKp#PN{+INi|+kBnx?j`Pc{CStHq{hyl26wL7RWj8MiY?5} ziwZ^DLKZ4E(suRB4H{Bf5@-5pnL$rx)k~jv8#A7wo~^VW8!w7BcY24-kCO5z>MA#; zWJ5Eg>m`%887NWAS&og;C*qM=ASPWOHa>u*iQWz?ftwBTcc>~U(k-yFwxm{}s4r5h z&px7QqlRq|Bu|{upyzoEn}R27G+fi#`B<#+d8^1eRe1V?3&8C~+ztRF19VH0O!Ar4 zz$J3H7S|SpEz$8EN6xlk8`~#fkJ_gF zRcUX*aE!i6-?WXanX0)Cs;!?-48?`YE8DL!6p;PDb|YYj2- z#<>ko{C@doBAiadb;*&JplQC@g1Xd8n4vSXi*Qd^y^>pQmtDJTFpuOSQ?TLs(Sk9> z`3!$fr_`$TChlT^s>(Zev-wQ6ns|k!o$3zblBH}Uo76s$F}&Un|E3Q8Di9OXvx7?A ziNt{HGEfT#DBRRQk5vq2VF+NCw7L^_nOYeG+0{&~M6K*he;NSnuk7{VzboACKj6SW zm1y^2eyvTv%EtZ;%>MwwudBQN27&d3zJ;lc{hdJVXX^jY*YfMK@4t}lM1!`bP}~23 z_`mkve;*D(L3SxH5d04vBD)j^5d4RNPl^)={#}=NC$wXKX$v!W1%(4O+3z%sKz3!Q z)7?PITHcWau|NLB|M-{H{&i^n)S15@{r?^gz%IoF1pmHt{{MsgYro+C@FVQ~1v|4sNcy zuFzj>Jb#bJ#mRd&3IBW^7Z>;41N3Jb4;Sy>ZQR^{%NfFXPon?qdw)m%YUAUB{PjA( zAQ0rQ7+??>@>gFlh=cF1_XP~%{5QT_e0NXgpK<|%c Date: Sun, 19 Apr 2026 22:22:47 +0100 Subject: [PATCH 3/6] docs: update Victor's role doc with sprint progress and live CI config - Add DONE/PENDING task list for April 2026 sprint - Include actual .github/workflows/ci.yml code in role doc - Update local CI check commands to match current workflow --- team_docs/Victor_Mbachu_Role.pdf | Bin 0 -> 14819 bytes team_docs/generate_role_docs.py | 2312 ++++++++++++++++++++++++++++++ 2 files changed, 2312 insertions(+) create mode 100644 team_docs/Victor_Mbachu_Role.pdf create mode 100644 team_docs/generate_role_docs.py diff --git a/team_docs/Victor_Mbachu_Role.pdf b/team_docs/Victor_Mbachu_Role.pdf new file mode 100644 index 0000000000000000000000000000000000000000..6e747fb0506adccf1ff0bfd7d0c25b75948e0b09 GIT binary patch literal 14819 zcmch;WmH_*wl<6tEVu_KEI^Q=(82@3U4y$8?(P~acp$jD1osf!9Rk56xVwj!^yxk) z-F@yocYNO+w|?vzd+s%5)vmSXv!+nX3yU&>m{^fP0A_%VfjKfSFEa3rjgz$_fD;)g z1u=2}XtF*%QbcC|?aKMvmFu@F=qHaNGUy-ALB9>qMh40l8$tAiY+M1F%umnRx!9Rl zzyL5ChzZQ~^invll24ILpi*1xL;07W5= z;s9$WOUow#KUt;q-E5p30YEux<2N>zPFB|cAUgp5VbSkO-sn5(TiTfZqUNWif2et5 zW9?{c?dSkt`)w9aa_ygP|B#?)>|o<$Z)ofQVEL2GpW1&B_>=b!fuaygM`QaZV=eU^ zjfIU3ZH$bOfzrm-rjBM$LcrjkYz~h0#`;#suBnk~+79z|SYD$Qvx)O|rc}upv9kpY z&Z)U^=ra?!lRRF2;^O`?m<-S6RJMLxd*A^W`#+?}lH$a`*k0~`t48TPA53BH%Rhe? zMJs`Y9NGLKT<&%_VT{EJ8X$@ z>0ZJ$Nm!6AM;(lkPsb=3wjfZQUp**k6_l{7T;ljZ$$0oF*!zOGJ3eEu87C}}O&Ba8cWweJo+O2PE z;}K>BzS2`_STuDw11=S#v@u4np|6jhwG^1Lyt!OhH9bmr7-RHte}C&b&4&6?tYir< zEg@?6sLe&evF5xMmgXJ3y%aD^sE*Mq7QO0rq*8$ZVe;Dc1mop{owI_q%0q9|W`L% z1&KP5*VLnpz=*v;HF>DWqj9SqB4tu^OX5)+DNa>)Qm1OmmcKFQ#7lIe^1 zI9G`z<;hRKCrwz~&*2OF@KTWFY@z#Gm*C(T;1S&^Qbkk3AKe-R?eGC7)K zP^$t%P6k)aM$|0?1DL5v8URXQ3uX?`Nvsz?@nb-V&xW$j(Ku#E&Q}bg-}|cMniuW? z5%n^;rqN-^^CYlKy2~X~ILVA~_9`Yxqv9Su)#Eh_$F4>&?Ho&1D`7FMx>T}S;mQK5~J$7 z^(CzlpLQo}4~stFpkOD>F5 z!SVG6$O9DtZn)>)s297WoEq2y{^wR$|HK8nJ(^>2W zV!FHWx@P#7R8is93bp{esaL3|JfFCnsW6Dz5yD8VqHTR`mbM{|K6~Ha;WdknpyUwoWCN4D7E)5sIkz$b1)){0tE!2$ zGjtb2-OB{8pwcPNM)m@*q!!ijH`s$QoRx?8uU_9F*X#r~(`B}kxXT=`r7Q{&W0dbE zuvG=Sp~s%VY%DjtTb(>GDf)(yile{WCy=CGiHjQ>>L#Bgu1CUIe;{v2FDpw|3XVi} z2(pQ=iw^wwW*QH9LV1CxL5$WF-?W?J4SUH_UW&{QMWT|ol2vbZ%5#Zflfp_0@Nb9x z+A!3P>dw_|5i>i02ij|a;@I)>hlq>{_{2lLQjwV-(VTcM52Va8EoifZER>4p(gaJ& zorAn2rzBG0;#zF%s&{mz@X73w6D$OBqwh=ndK;-CcOHffQkz(T%DiY?2_p#VG~;tp)jKmMh2tq z>e!X#Ubk5p$=DbdajsW5)vtmV;AqXlv5v1lzg?8HPS|^4eD^9F9OdSCRCN08azf-j zhlY2bPKyl{iBa|RyP|D>X%Ug`6xYTA75V$bdSiz+4=8_-9f4ze>^}~dKyx%C^cEqP~A5b?ch(pmmrq8e_y)J zchS=KAUoyTzt8mHf=6gjJoNGu7Z`n8K#g+>KbnJ*bKj5jZ8Ux{h8Q=-bxl12K7dVK z0P80Gbc(0v5PCltJfEp_cdd2jv#`BX{|#4{o0Cb`#6?JCoB_?Gd~?LpD=Y3azr4LQ zy8W!gs;!r5P1=p{ds5wdfrSK8ieSTfw0k*5Tng3Lt&Kf?PN4M-O@%ThlPRkY7ctpu zsr=H6fJ6ZYl_QV-o6l(cHuU>0BfSdg8M$gI69(euT0$B|2>8!P16Q}3-`a(kfv(7O zI^Fd^FX-LSW`Ar@+Zzz7RAO361TFbvayFlZ<~jI&odM``6iJ=$2_;c~wx$mDHz4?) z8YhUzyO?9#ml)lFsW#G)h8=pwMqz~o2ARX>i(HXx7Ddc;b<__bEElb zFT2(+EQ7(A`_%Cd&0b%HgM$0t-%hcCHm08?MIi=F&uVwS-?0zZ$v0s^%buaC_Ng~* zKc@%+;5EE5_(BWZI$LGht)5!aT;$ZNH0rk0~<`dCjV{<)%cR;`U7#y^o@)Lsn4oiLqV?Tl1 zAE4%+D2d}gproG&PVrZG_X|q;$@_=E{|+TRfh5j9p`4nk6|B&aV8eC|mVPpRv2@#Zt-v*p&f?#n}vcV;;K z@I%f|d#?Ox!}_k)K4z?7nRtu4klh}Yz#rc6=h>~~5z15-;pek`G}d9G?1ucaIa1xMMhqT(iqzb!l5_0Hq8=I`5}z%vr2NS+AJ@w ze#BkPcH#eR&*|`0|BjYLC9P@;+c{@bA@YwtwgNdIwW>Sa?&2vwBL{|GTjwl!R}6kI z-m2q7>qZ1CF!_)eh=b_HA|(sIb&-oPnyS|ST?0jiUDMVb(*$XY;S=A4*6D)sE+g(G zd$%O7eE5CnIvzcWhF^7Vi^jAxQma$n*9yTl0so;C(GM6MAE?{gyBiyYJP#YnOBBP! z$b&GoCIia{8x7_PUvi?Q`_7b)GBHK1jqT-94O-scrPY`QKBk2*(KnAbzRrAEW1fqN zZB-g>u7V5D<2#>yraso9co=z=>Fn(xBQU9@lDB${QDQ-7Z_-7-%X^jO?m!wJvpMD%Hc80+D-(VXQ3O54e?P3f$%I18n+#u!YA|n@|BC7K> zvv*S?*WvSxQZO$i10K%>lYH2s91pc}=Enfq=1d~}7d#!^E!5TJH&nW(_egCHRvHHI z6~?tM8*rKxESg$*Oz?Ws$xuP_gf`J*6**mlrhbt;=o>0r_~D|B(O*K2mp-D=zi>9u z^)rngDofxJ+Xy3$)Sgp0!0PSlDB>iME=@Zj2}ej^g>-MHusxm40l+F!MW8x zHO%9Xfdzhi?rJpZdb6`W-MrrN?IoHQSF3gkwI@sBerQ2qsr%x~VUD;#_vsI-i5c%H zSYlzt#zNvnkS zZu=%RBiqHv)(kA*8gS0$;?At}(#Skd5KQD4)ahfcbg+W5H?<@Ox}m+++1z7HT`SrB zh+jiHri=j%*pOqoQBzpq7t0##XN`m5%Tx5ix&N4m7VKr((t7La_Hfd<)RUq}FoWi} zw>sM4c5ONY^??|lkT`m|E62dx3+_ch673tiC01*{QDWbF@5reU^#jrVHX5_UIG;vag=uyu7l=MB^~1zvV#xD;mbHe@2SYLGr)-qw%B_;u-@cH0 z10)RFPPeP4?~ef(8+Wy&a5+bfWX;v7=v&t0`L%!%!VQ2CAzz$(7-!KY zEKPeWrbdW9FXVKN5?VRT-B!aX%ypz72%RB;jVg9I^jrnAb zg1tyPPi;@kZDpy%V*(qQff^dZXSjt@vWYWQF}gwjQ#PfSv*2y2c$yV-Bj7QJsNAqhgm`#*b@P zr;xDEuOdHLxEvk5Xf(zadFvikg|sfSpur)mv0=(*v055uv~F?pO*F>pD+P}qZ%&(+ zsRid-=OYr3IIuCEkHPcZm|nby@8k&sw_dwBG~TkqF)WUkYM6Bg$vUF?ipU9=UwPHh z-Pb1S=}~7W8m(e&xiIkD(xhE93)|7}97-dF-F{*4qVKZONt{Ai*v`&pxplk~DkR^M z7aoRfof)k6i6q}0+$}c;4aw*@G1q-@fc@G@zvVsFyQ*@sBTT^enX9VfK<{-+rYvjb zM~_VM7nv7gSqhQ|f>*d~qM-K+x2!!>s;yM=-@@>-Q*aN~`A~)C6?+LYSzms`3<#%I z5{)`|gkx~H!r?=)qM7p1BD@?wCjauFK%{P9aULBs=~!R--Tqy_MAYG){+MJY2nJ#n zejfdWkMpfZ6nHJrdnO61$>W&7eKY=%z_IE^s1DIeKy0TPb`e*>omm_fwQ05&uqTVp zzp4I#RO>ze;<%3j*TzCxHGDOhQnWPq`s~tT#8f|oXpy(d^V`ZdO?u=GlEg>oGLA@IL<{2+bRmxsUDpEL#B1)?OqoXYO!2tr4M9ql7=JSKC*71ZnPJ0 zGNJIgda@dqAKft<3-U%D4@(u04hgJmK~~(ye3ZIvTOK^QgQ#rPV}+7}horuQDsA>= z!j&%HR|bY(F*RTYG0q%Y-)xe7LH9~*M53Au?1pA=usz6lwQ^7zuW8+-T4b#KfG~J; zEpWW`LzFZ(;3_mOu+i?3|EvkeHm{bUxU3NM9=VzupS~P^f$y!*PNe1gdY_$H4y!S_ zJ?bHJ^5?L@)XyFQgXqB4ub*uXk*EoN;my#KfyQiKbsD}fQE^CM&3O#UngQAl8pGcx ztzd4A?t2f!>hU&5wT7k}w-viKPAaw~y{Ohj8HW;p>p-U?MZ|C=4_~u`v+j%iPUs({ zn4)o@gW&sY(+WPtYvHx|jPa@?@5PjH<-FA5@xC9vzt@Zt{Nrj-gr2%~nX#YvF>DUH zD$X%4B)(^e?8qg)ivg8e0`V~RdI+ue2=<=Xxgfvh?>igO39)3f{@`BFrqkprF z?$U6(-+Ue0#5jT+T4eDV2P;_Vlesb1>mpi7wd9C5C`z08Bxa34n?@IPMYVd(RyUGn z8G8|l(cxs-rNlfL&saSOUI!U|h`8cL7E10KuR>J9yIFT>x07fZHVk4*adtXUD+zH@ z7uXG-Nwosh<5vQRMk8+ty7}r%PP@&W9Y%Kt`ijdm(W+Ro8ii78FP z$AssXx@`GI>&T~C8B!7}3`p{ZVC2(I9MT42I4xYcV?>OJW{7?2VqPgLst4i#y4t0B z;aMYKlZQd1K?(zFCpy7kN{H(DK2mU_!^9wusQ{@@o0sq|G*GHR$F~rf)>8G|lg$2zROjWI_jeboDfgJgM`wqOIL9!VDJ~aLwnWvLtdm~{ZdFhxeBmXQ$Dyr{J~IgTdmtU{)eTq`RH`ipx{j@I3)a6* zGY2qllBtAufaaP5Q_Ra6IFOwxyU!cQ7qo`TGY(!nP`wai zMkB~d4W^cF8Q_>Aqr7}ju%bJs#=6aTOHoGjUWyja-q}!rJQ3bX`4iTxEmeR#yqDE3 z4UZ@PMkn0)df}ehhndgVD~`Oi-zANSB|ber&-Y|Cw+m7%)0J`*h-hw}Lh0T?9NvE= z0@?C6Mc8z*2uz+$m(~j<(KM3eFuIdmyV6`3K5<|g6jR@*?lyoq!ppGoC^EZ}B%ll; zvL-$3So*ek5pY@Bwh_4~WJiYSsZB9j*8)xdnN0WrVs`~^o-5Pu;tY0}2c>GxZ!*rH zyAwo*ln6UMmlxPJnUC+_rnRAB%za*}nMx5d+o~E+8h_45PHq84eR=z4X{u^wlnKxA zVkMO-6^Cg-RKy%`!1mS& zGIluh{=>%3U|+=_q?p+AnOHoY4(E0xnVAY~8%DG4F!bemk8;?wuA1-kgA{yo`F$Hp%xyCz0UCNIg_@m1PJH!u zsaG)Z-eZ1^s(JF8>8jcH5?H0-Sxx6OVM+ky+8B$EBp4_$=<8XC`R6avy~ko|7j*?+ z#44$iPk6#KpeSa%ZNSXFCMcY#5lUJ=0@0Rt!b|#hR_IZ>-ag?i#y+i*HHfdq!uLWx z3%^q#6q1vq)J?(60m_Ju^p!wCekvL``#8EXJ5ptvPp=&@v;3x9XkKXWjD_||_qYtYY>%hNIZ zzf5NQp6vKn7Umak{TuTiBL7==&Bev>7k8~~GvD(wn?bMwBVw;Vevcy}K<$(q#Zjc) z%PHd5QreeL!`^M|BGK5?An+qyT@edHuV~oCQnWg<|B;o|lyG7c2m^e+a}sm}uYePC z)LkUdEtYgczSt_@z06>@dIn{pM9zT4De?IvT z-u8?$=L?Dn+nK2j(WIB4-yKNG-A%i=*6h2gaYDJy_(O(ku=gGwG96EoEO&~VAh*tz zY+~$^TFHlLjkjnIuVXguO-Rpovx_T-l&jT^8Kq0r~kw!Ev z1P=*w+g-0pRqVgCdoP%bgq@w)_yyj&yvFKN+Ip4@ z>}LDNu^v&f8K)f%DSA4|FQ2|9nAiBB;|H1%4_o%?=CSQ3Do@xn4m9ALv~c(@WlDxvQ#31?VaogEW+E~z)M3QcS=s>cyk?t z;G)6AHj=|@5{j&RbYX^|V#@%A1dsBT#)rPBX$>zRPd~#6%cC@#T*P5+nUnE!@LqTd zK3K7^XFMD83`@&&Exv;xt@}-mMKUoRsVqE;%y|7MJPU_=+?JV=dHL&b#@j{F{$6_b z==nyx{7gy9sVdme^~yqP^>%5T319g=qGhL1(kNO{8o3b>HjdkU4MZz>ecSJ@(1+#1 zwefif3Y=!UOb{6SR%jI>t`=L+b0Rocp7HQ*hc!_|9TI;uFCY^5eWK6y*D;Up>n>KL zczNFYs;=Y1VSyQP5H#ij9lV2bsat=+k56Z;b#zquEifs1oi|9}cw(E`)gaw&y&c=s zFOdX;;uc?<5)m!pI3?wLA#+T10&8wLS(D>aafq4A=QZ_R>dDE^6H`)?eihVuUnXt> ztW&V*3u5q%3sloZm!^EG?1zm*WkXNw4Nj=eI#$lt017X>fcyQPAyXUH{L-&e;dd>o z@OpWBLbrMg_(Y=xJ9A&CQ=hu!r)yEejhg06ai2ONi9D1wf;O7we8(~$rZIuh+LNqf zcPkL)<5Sc~AM8h-h|#nllJE~pIZ+DO>E{H-nu}GiI7n2K+edng-~4F%ebf-pKdZhsARKVn?=Z zZD4MVY~PeU(jd|Ln=q;F@<6|_rbP~VRHOp8PgrtxI0}ZsOM0>lZl5QZsH{I$Ebmo~ zq1Wo|nNX7y68n)?1&aqfv-h}^m5mj2)aPCtf4mMY&H%ObF?M;XhcyP{jhlR$d5^w| zQwHRTNdA#5HoSuxY_|(P$(rM087Qw_M?TDH+#GEoawWuPjuEefh@FOxN6Oi{j%mOt!3{8& z5_y(5VmQO+esODbPd0)`KOPOi{4S}!=^v6aoqZ?zz5)8wpO_v}ewiKh!{Mr5=LI^G zZy^tx4dtVG78Ov2=8(#v(zzgxb{?R^48fCo&RBWt+!U z2dLGL5=0x#k9Qn7Z~(A?qQEyPZ}cSYT(;9{g9`VbY>B4LW>l)daGnkoEH%YoY^78G zwAP=|ws5~Y6xGWSV9v#CEAK7JaB@BGCxW=Ff!Z9;J=zNM8_?aY0r}S z{GelwD1CK*vLf#SD>!p->95|fVh9-M-kh_=F8)I3!jFBpa0^B~mgB2uE~@pLvSR+u z0E5FL>x0RzkKK<3{afZ{mR#}R4ZYXA6+v@;y5A#g22JstiZacI5cAC=+ zk4wHKC*7yq#XAy zJ`4ude+k$2nF`+WspfIxDPwn)m=vt`#mn#&zv--;JW)!*xQ~+$AjCMKlXhOX#3DPe zyFc0AAbY6rNb9Z;0N-IZvERQ%V(&3nrSE$mH42WZ(3oAa&xt~>yeA{Po-F@6&iJj$ z;}2BuFQD;zy#K!h8viI4`S)P~(68kl|1Hp9W%+YlAmR78z|~V+;ETAgdF_?a4pz}>k-8d)Z-S4wa^tZlcpx4>0GQ9&)amFDYzDNtZs68l8X1NIu@z^xVqbl_fLqJg;LIZR?o}|jft>}^8w$+M*oK&^yFdf zJatQ3>owA~JaY$wnt5o9Z3@($z#eW((?GS%RQ__+OZxB`+dJ4tgdelecF$VCJsKTD zbR#k!3y$+4RVtMd;do4|#nKZZQ@O_*pT+k~(o_(y6YE+>Gj7%;C8bx^DERzL0=n}~ zYGvs4$XkGQ>e`2jH_3I{?6b+di$wLpw9Eve;_@9>xL+b9>ZN-36p&Lf^KNmVI-yIe z@YY%w6xHgjrUTEo_|;uduo6>lC>yIun$NJykv_YK@6y4WXpN2I6q0w4=3&qrchK=? zDa!im;iw?`+d2o{z7Scj)Z~BfuaUdewoLc}b4772|^KJtK& z_u2adf#)NQN;~~Gz^m=VM0w>D8jWMIdq#5Di#9d=S7U+UJIL$go>n z^WfyTql%2UQdAoEd$@$nF47FW3B=UyDClNnlWLK~jZj1#b&B3mc?qc+-f#0Mdr{=) zWFz8ZV)nheO_p z?_@F8z|juY&HidpGeMMn?&@indWwF+6Y=&dymQP_XMOV_h6>>~VRcN=ggA|~P2>0# zPL)uVEjZ}J^kY#B(BYXPO2LD|RbfmJ)nd8@ks<-bsM#O|Zv!A1{;+WO?yR7Sw}ekh zYrAWeWzW2$nFn24y5T(wvN&~?iLwL5Gp#{_H<%m%Xuk1OC5?1ktGA^9A)&dDS3$06 zJud0xfKvMhBep;V*_#lIy8uT)-ghSUQ<(0|yZe~h#nt>O=;g_&x`8i-fTTEFToo&h zp4=7tvNiymUnbr^(nh*poaf zZjx?lxcVfbN(Fw$BXU7Ab@x_d#`s{>f4*NLIHjGcdTT9csdxDMeaD5K_eo}En7^H5 zxvMIT!tHmW2 z1uG>{XC*G+HJm}qX*8aZb@)gH8@6CCaWX2;<{rKTE@vZCP9v8$AD0s^()K2Xc}My> zUxt(l*3TYJ1!!7A5ejFNldaq$%wcH>B-8M0Js-8RGZUGyYQKIX}MuV?K?x zUy&buyvR0mY#iyAt}n31P2=nqWJyU3K0SyVNBnqB%6g$3Wjcih<=DgDJ9jKFoy=j~|_xA@I%)44W(aNkS;EW>Ua?pM zTp{uAc!!TW90yhwM_qMM2K3x_-mcD|Urpk~X9`22HL&sl{p_n;jtC#*bhJBm;Ng>R z61ACDFE-+$d^x$OmHi}f`{A{ie4j5bB71`?O7=QFq9>HiZHhJAqb$Svy!Rv6)=Sl* z6FP&Wx>#AQ{2Hr76)$OqWcHMf=iX3H@M&Ir9~&t!kE+1q1PW`rtdf;hGK8eAU}G*`)#^xR z;axBD#}T9`RW2p2m^Io6_VQ&a!w21kKB)M$zyYxG2-5PA?_*Qhf;)n4&vrjrRmmxz z+k4ENvkK@^Y0R=UHAU=V*r*_q48H?>MjYbA(ue@>>M!M;)uxm4Du&t$Gtrh=<(nnR z2&b>HN?h?-$@xanzgHGYt9z4kaqr?z%#$C?Mg73}nBW1Tw zI*wPzD3o{RuDF_cFuQ`}{ZV4pS6%D*!(#Kd{V?BDn(F394$1Z`^gidtlQM^ex4hkP zDNe)boQvq`l1>dH>-R-6ns3MmuHKUBg~6y}W>%)) z3_0Au-7K>5Zp5K>3zA!uCk$7BDnFA(v{VIwK~RpYljmMhB)}q3 zs=X-79m+B2yI5Qh$)=TTNRQtjac&e|rG0hoE6;}V`nl>Lqw@2Dw(ZpJUS<&`8`yVl zvJ(yWr>HbZeC07Ts#SuWDfz6AlxihV20ib>T!N%t7!y{+%TtAyF!w&nv@9!uuO#8U zEi@+=mGdg)S5m&_7cRQ*sk+xPuYBFiN{2RMdiM?mWZE%#2i>&aO!Rfc%A}ycNfYm) zsn)u1Zs!@Pul^1wr4O=;L|Uelj7gNJn_pc7>xpbb)ZCuN_8f0^x0=vQ1z!`Vw-^3Z0YrU~AxEVsv$*VZ)PXn@J{eA)rycj=*wqy}eu= zes_crQ!IIqpnol=tB_(}{OVYqK0ikosf7gHd%Np|VfO}f-2?SHtasr0i#+4AW!$@> z2S&{rBSgzjZLQWe*z=d#kbB*7+XN>SLh+zArmrVi*#kaIwrsd(MfUxsleO1(PA5o5 zx;ExM4j!VD%^sgaC9IMYG&2+!PGT19B~GuAvp!O}yC^><=ob*C+pNzAN%Ai5(rOpJ zuE*0|jNhU%#BO4S!C&UR`%K*!6_M}T%?T@_1aQ7`YHZ*f{-Njm<$QrMlTv(LGa#E% z?}Sk%X7rVgnAQbb8jf$AjkWPPUL8=%5D%Jkd&;K^Bm6z;bQJ#S>-Mk7nd|GBm+=#4 zFYfxH6>|7jB+$?qCkJ!nD&!+a=S@N_s_az!3Upn=*CM2F?#7&tvrcIUuf5)vH}=ka zzSvFY`+kZJ)xSXdZ+y+aEg%B@rwXEfl$QS&Cx-uN2@xm9pCgkA2{z&LV2qySqXGi= zPc^{O?I>d@DK0Z9P1;3{#Ni7tErW(;s8=MTYL$!4D*t^X)`Uz|d15R+jQYoA)?_i( z7yPN9So;Q^oIoUU-&nQ+LMAPx=iyfk6-qs;t|xmZXY*c?f_V|NXo^xDxKxcVDG+V+ zoi5#xs$Edk@S+%1kDc8vNo0WNSrD5gdaAF*SGc-DA0vDAp*J(`Su%Fka}4NCJUn-c z_erIYw&s-32+B=tbanSVx(KmM6n# zeDRlGt+f!hw&owKXDz?nxNFzn$x)8+Qh!VhHlb7aHk#RwR$97)Xk$u$G`Cb|TvcgO zTj@2C1Tw(WU0_pCjNRE8lw_sYcEpLn?3Z;+sS0czQ9tf3wUyb@a8yXrPJVyBx{R5$ zGE1MYpDHFM0L`i$8Hfp$tRkQQ-(>SFL}iw*J=f2)@|kYN5kyy4%W{XzB>}1wE;Etd z)n+lIWHe(8gMQ0uTPBJRX`$?b*x}Jqm=KprHEw`PLsL#w>XpnV4{1?Bi=4Ztv%O%l zibH(umktsWJF)%JqI+_?BLu789C7-y)6nmxN}h^#v@HAaU2p5^T=eF!i1udiHp4Mw z#$W3mXbeB&7)DAvq*44n{unar1fRBirZa*+lkua)^TGLqhbnZ3JBpo@JgfQwJ7|?6 z`4I$390AdKl1UfJiuyu1u~;N^kiPaC+`c_1jZrR%+Zf*te6-!HDbXI~Bo@~@v@&h! zRt-kDsXFW5h@>lq9vwj&7$mE?M|XXXMfq=5=C2ukA$2|`YF>a?n*xBU5Nkne2gn};WT29hf#Yu-96uo;=#P58pJIMZB>bB9|2Jy> z7c~5u{rEQ;808EsA$Cqr4H$oz{{M9@EI%_Ue}q5&rRk|f#vWp9|Gyyr*T$RQUI#BP zP!t3J{k|QFvH(E8mtcsp0zkiY-aIvu0Ojp%43&%>0h++44juqd+1T~zMM_vbwWkRE z{{80nZwc*RUJc8iLN7nx{(n}73>0Mp{PsI2{{PYZ>j~t4IMM$l&3`(m{GZPGS5NqV zJLf++%>UCl|GLNg-_H5hZRgEXqt(wIGU2CYEC8)AHw!Zh2QwRpiv`5O!Uocy`(;hI z+8di7GXq$-keUDa0dTOhv$6wB0RN&rExn%~fb~CVpr;XkrLnL+S@D-~tUs6SpJ^=Y z;HQn{FEkF0r_JEcG&YW({bzrnaWX%x;y=?k*uhV4{4X>Pj=$Lg=KQ;TVDR5`fS6f+ z;9w+aB-WsBiE1+rJsa#tdddrluB=6Gi@iF*e$c literal 0 HcmV?d00001 diff --git a/team_docs/generate_role_docs.py b/team_docs/generate_role_docs.py new file mode 100644 index 0000000..0c4aaf2 --- /dev/null +++ b/team_docs/generate_role_docs.py @@ -0,0 +1,2312 @@ +#!/usr/bin/env python3 +""" +Generate personalized ClimateVision role assignment PDFs for each team member. +""" + +from fpdf import FPDF +import os + +OUTPUT_DIR = "/Users/starrexshotit/Desktop/ClimateVision-main/team_docs" +os.makedirs(OUTPUT_DIR, exist_ok=True) + + +class RoleDoc(FPDF): + def __init__(self, member_name): + super().__init__() + self.member_name = member_name + + def header(self): + # Green header bar + self.set_fill_color(34, 120, 74) + self.rect(0, 0, 210, 28, 'F') + self.set_font("Helvetica", "B", 16) + self.set_text_color(255, 255, 255) + self.set_y(5) + self.cell(0, 10, "ClimateVision", align="L", new_x="LMARGIN", new_y="NEXT") + self.set_font("Helvetica", "", 9) + self.cell(0, 6, "Role Assignment & Codebase Ownership", align="L", new_x="LMARGIN", new_y="NEXT") + self.set_text_color(0, 0, 0) + self.ln(10) + + def footer(self): + self.set_y(-15) + self.set_font("Helvetica", "I", 8) + self.set_text_color(130, 130, 130) + self.cell(0, 10, f"ClimateVision | Confidential - Prepared for {self.member_name} | Page {self.page_no()}", align="C") + + def section_title(self, title): + self.set_font("Helvetica", "B", 13) + self.set_text_color(34, 120, 74) + self.cell(0, 8, title, new_x="LMARGIN", new_y="NEXT") + # Underline + self.set_draw_color(34, 120, 74) + self.set_line_width(0.5) + self.line(10, self.get_y(), 200, self.get_y()) + self.ln(4) + self.set_text_color(0, 0, 0) + + def subsection_title(self, title): + self.set_font("Helvetica", "B", 11) + self.set_text_color(50, 50, 50) + self.cell(0, 7, title, new_x="LMARGIN", new_y="NEXT") + self.ln(1) + self.set_text_color(0, 0, 0) + + def _sanitize(self, text): + """Replace unicode chars that latin-1 can't handle.""" + replacements = { + '\u2013': '-', # en dash + '\u2014': '-', # em dash + '\u2018': "'", # left single quote + '\u2019': "'", # right single quote + '\u201c': '"', # left double quote + '\u201d': '"', # right double quote + '\u2022': '-', # bullet + '\u2026': '...', # ellipsis + } + for old, new in replacements.items(): + text = text.replace(old, new) + return text + + def body_text(self, text): + self.set_font("Helvetica", "", 10) + self.multi_cell(0, 5.5, self._sanitize(text)) + self.ln(2) + + def bullet(self, text): + self.set_font("Helvetica", "", 10) + x = self.get_x() + self.cell(6, 5.5, "-", new_x="END") + self.multi_cell(0, 5.5, self._sanitize(text)) + self.ln(1) + + def code_block(self, text): + self.set_font("Courier", "", 9) + self.set_fill_color(240, 240, 240) + lines = text.strip().split("\n") + for line in lines: + self.cell(0, 5, " " + line, fill=True, new_x="LMARGIN", new_y="NEXT") + self.ln(3) + self.set_font("Helvetica", "", 10) + + def key_value(self, key, value): + self.set_font("Helvetica", "B", 10) + self.cell(45, 6, self._sanitize(key) + ":", new_x="END") + self.set_font("Helvetica", "", 10) + self.multi_cell(0, 6, self._sanitize(value)) + self.ln(1) + + def month_block(self, month_title, weeks): + self.set_font("Helvetica", "B", 10) + self.set_fill_color(34, 120, 74) + self.set_text_color(255, 255, 255) + self.cell(0, 7, " " + month_title, fill=True, new_x="LMARGIN", new_y="NEXT") + self.set_text_color(0, 0, 0) + self.ln(2) + for week_title, tasks in weeks: + self.set_font("Helvetica", "B", 10) + self.cell(0, 6, week_title, new_x="LMARGIN", new_y="NEXT") + self.ln(1) + for task in tasks: + self.bullet(task) + self.ln(2) + + +def create_adeolu_doc(): + pdf = RoleDoc("Adeolu Mary Oshadare") + pdf.add_page() + + # Title + pdf.set_font("Helvetica", "B", 18) + pdf.cell(0, 10, "Adeolu Mary Oshadare", align="C", new_x="LMARGIN", new_y="NEXT") + pdf.set_font("Helvetica", "", 11) + pdf.set_text_color(100, 100, 100) + pdf.cell(0, 7, "Data Science Engineer 2 - Data Pipeline & GIS Lead", align="C", new_x="LMARGIN", new_y="NEXT") + pdf.set_text_color(0, 0, 0) + pdf.ln(5) + + # Quick Info + pdf.key_value("GitHub", "@Oshgig") + pdf.key_value("Access Level", "Maintainer") + pdf.key_value("Reports To", "@Goldokpa (Project Owner)") + pdf.key_value("Project Duration", "3 Months") + pdf.ln(3) + + # How It Fits Me + pdf.section_title("How This Role Fits You") + pdf.body_text( + "Your B.Tech in Remote Sensing & GIS from FUTA gives you something no one else on this team has - " + "a formal education in exactly the kind of spatial data ClimateVision processes. You understand " + "satellite imagery at a fundamental level: spectral bands, atmospheric correction, spatial resolution, " + "and coordinate reference systems." + ) + pdf.body_text( + "As a GIS Analyst at Charis Tech Hub, you already worked with Google Earth Engine and AWS, writing " + "Python scripts to model and extract insights from large geospatial datasets. That is precisely what " + "ClimateVision's data pipeline needs - someone who can build the bridge between raw Sentinel-2 imagery " + "and the clean, preprocessed tensors our ML models consume." + ) + pdf.body_text( + "Your MSc in Data Science from Hertfordshire added the machine learning layer: Scikit-Learn, TensorFlow, " + "XGBoost, Pandas, and data pipelines. Your credit card fraud detection project showed you can handle " + "imbalanced datasets (SMOTE) and build production-quality ML models - the same skills needed when dealing " + "with satellite imagery where cloud-free forest pixels are the minority class." + ) + pdf.body_text( + "Your experience with Power BI, Tableau, ArcGIS Story Maps, and data storytelling means you can also " + "create the visual outputs that make our satellite data understandable to non-technical stakeholders " + "like conservation NGOs." + ) + pdf.ln(2) + + # Role Description + pdf.section_title("Your Role on ClimateVision") + pdf.body_text( + "You own the entire data layer - everything that happens between raw satellite imagery arriving from " + "APIs and clean, model-ready data being passed to the ML pipeline. You are the gatekeeper of data quality." + ) + pdf.subsection_title("Core Responsibilities") + pdf.bullet("Build and maintain the automated satellite data ingestion pipeline (Sentinel Hub, Google Earth Engine)") + pdf.bullet("Develop preprocessing workflows: cloud masking, atmospheric correction, image normalization, tiling") + pdf.bullet("Create PyTorch Dataset & DataLoader classes for training and inference") + pdf.bullet("Implement data augmentation strategies (rotation, flipping, spectral perturbations)") + pdf.bullet("Engineer spectral features: NDVI, EVI, moisture indices from raw multispectral bands") + pdf.bullet("Build data validation and quality checks for incoming satellite imagery") + pdf.bullet("Manage the data/ directory structure (raw, processed, satellite)") + pdf.bullet("Create EDA notebooks for spatial data exploration and visualization") + pdf.ln(2) + + # Codebase Ownership + pdf.section_title("Your Codebase Ownership") + pdf.body_text("You are the primary owner of the following files and directories:") + pdf.code_block( + "src/climatevision/data/ # PRIMARY OWNER - Entire data module\n" + " sentinel2.py # Sentinel-2 downloader & preprocessor\n" + " landsat.py # Landsat data loader\n" + " dataset.py # PyTorch Dataset classes\n" + " preprocess.py # Cloud masking, normalization\n" + " augmentation.py # Data augmentation pipeline\n" + " __init__.py # Module exports\n" + "\n" + "src/climatevision/utils/\n" + " geospatial.py # CO-OWNER - Geospatial utilities\n" + " visualization.py # CO-OWNER - Spatial visualizations\n" + "\n" + "scripts/\n" + " setup_gee.py # Google Earth Engine setup\n" + " download_data.py # Automated satellite data download\n" + "\n" + "data/ # Data directory structure\n" + " raw/ | processed/ | satellite/\n" + "\n" + "notebooks/\n" + " 02_data_exploration.ipynb # EDA notebook" + ) + pdf.ln(2) + + # 3-Month Timeline + pdf.section_title("Your 3-Month Delivery Timeline") + pdf.month_block("MONTH 1: Foundation (Weeks 1-4)", [ + ("Week 1-2: Data Ingestion", [ + "Set up Sentinel Hub API and Google Earth Engine authentication", + "Build sentinel2.py - download, parse, and store Sentinel-2 imagery", + "Create landsat.py - Landsat 8/9 data loader with band mapping", + "Implement basic cloud masking using SCL (Scene Classification Layer)", + ]), + ("Week 3-4: PyTorch Data Pipeline", [ + "Build dataset.py - PyTorch Dataset class for satellite image tiles", + "Implement preprocess.py - normalization, atmospheric correction, tiling (256x256)", + "Create data validation checks (band count, resolution, CRS consistency)", + "Write 02_data_exploration.ipynb - EDA notebook with sample visualizations", + ]), + ]) + pdf.month_block("MONTH 2: Advanced Features (Weeks 5-8)", [ + ("Week 5-6: Feature Engineering & Augmentation", [ + "Implement spectral index calculation: NDVI, EVI, SAVI, moisture indices", + "Build augmentation.py using albumentations (rotation, flip, spectral noise)", + "Add temporal compositing - median/max NDVI composites over time windows", + ]), + ("Week 7-8: Scale & Performance", [ + "Integrate Dask for distributed preprocessing of large image collections", + "Optimize data loading with parallel I/O and memory-mapped files", + "Build data caching layer for preprocessed tiles", + ]), + ]) + pdf.month_block("MONTH 3: Production Readiness (Weeks 9-12)", [ + ("Week 9-10: Quality & Validation", [ + "Implement data validation framework (schema checks, anomaly detection)", + "Set up DVC (Data Version Control) for dataset tracking", + "Create data quality reports and monitoring dashboards", + ]), + ("Week 11-12: Documentation & Integration", [ + "Write comprehensive docstrings and module documentation", + "Integration testing with ML pipeline (ensure DataLoader feeds models correctly)", + "Create data pipeline tutorial notebook for onboarding", + ]), + ]) + + # Git Workflow + pdf.section_title("Your Git Workflow") + pdf.body_text("Follow this branching convention for all your work:") + pdf.code_block( + "# Create feature branches from develop\n" + "git checkout develop\n" + "git pull origin develop\n" + "git checkout -b feature/data-sentinel2-loader\n" + "\n" + "# Your branch naming convention:\n" + "feature/data-* (new data features)\n" + "fix/data-* (bug fixes in data module)\n" + "refactor/data-* (restructuring data code)" + ) + pdf.body_text( + "All PRs go to the develop branch. PRs require at least 1 review from another team member. " + "Tag @edoh-Onuh or @franchaise for data-related reviews since they consume your data outputs." + ) + pdf.ln(3) + + # Key Collaborators + pdf.section_title("Your Key Collaborators") + pdf.bullet("@edoh-Onuh (ML Lead) - Your DataLoaders feed directly into their training pipeline. Coordinate on tensor shapes, normalization, and augmentation strategies.") + pdf.bullet("@franchaise (Analytics Lead) - They need processed data for carbon estimation. Align on feature formats and metadata.") + pdf.bullet("Olufemi Taiwo (API Lead) - Inference pipeline uses your preprocessing code. Ensure consistency between training and inference data paths.") + pdf.bullet("@cutewizzy11 (Full-Stack) - Frontend map visualizations may need GeoJSON exports from your geospatial utils.") + + # Code Pipeline + pdf.section_title("Your Code Pipeline") + pdf.body_text("This is your end-to-end working pipeline from environment setup to pushing code.") + + pdf.subsection_title("Step 1: Environment Setup") + pdf.code_block( + "# Clone and install dependencies\n" + "git clone https://github.com/Climate-Vision/ClimateVision.git\n" + "cd ClimateVision\n" + "pip install -r requirements.txt\n" + "\n" + "# Authenticate Google Earth Engine\n" + "python scripts/setup_gee.py\n" + "# Follow browser prompt to authorise your GEE service account" + ) + + pdf.subsection_title("Step 2: Ingest Satellite Data") + pdf.code_block( + "# Download Sentinel-2 imagery for a bounding box and date range\n" + "python scripts/prepare_data.py \\\n" + " --bbox \"-60,-15,-45,5\" \\\n" + " --start 2023-01-01 \\\n" + " --end 2023-12-31 \\\n" + " --source sentinel2 \\\n" + " --output data/raw/amazon_2023\n" + "\n" + "# Output: GeoTIFF tiles saved to data/raw/amazon_2023/" + ) + + pdf.subsection_title("Step 3: Preprocess & Build Dataset") + pdf.code_block( + "# Run cloud masking, normalization, and 256x256 tiling\n" + "python - <<'EOF'\n" + "from climatevision.data.preprocessing import preprocess_tiles\n" + "preprocess_tiles(\n" + " input_dir='data/raw/amazon_2023/',\n" + " output_dir='data/processed/amazon_2023/',\n" + " tile_size=256,\n" + " cloud_threshold=0.2\n" + ")\n" + "EOF\n" + "\n" + "# Validate the PyTorch dataset loads correctly\n" + "python - <<'EOF'\n" + "from climatevision.data.dataset import SatelliteDataset\n" + "ds = SatelliteDataset('data/processed/amazon_2023/', split='train')\n" + "img, mask = ds[0]\n" + "print(f'Dataset size: {len(ds)} | Image shape: {img.shape} | Mask shape: {mask.shape}')\n" + "EOF" + ) + + pdf.subsection_title("Step 4: Compute Spectral Indices") + pdf.code_block( + "# Calculate NDVI, EVI, and moisture indices from raw bands\n" + "python - <<'EOF'\n" + "from climatevision.utils.geospatial import compute_indices\n" + "compute_indices(\n" + " tile_dir='data/processed/amazon_2023/',\n" + " indices=['ndvi', 'evi', 'moisture'],\n" + " output_dir='data/processed/amazon_2023_features/'\n" + ")\n" + "EOF" + ) + + pdf.subsection_title("Step 5: Commit & Push Your Work") + pdf.code_block( + "# Switch to your git identity\n" + "source team_docs/switch_user.sh adeolu\n" + "\n" + "# Create a feature branch\n" + "git checkout develop\n" + "git pull origin develop\n" + "git checkout -b feature/data-sentinel2-preprocessing\n" + "\n" + "# Stage your files\n" + "git add src/climatevision/data/\n" + "git add scripts/prepare_data.py\n" + "\n" + "# Commit\n" + "git commit -m \"feat(data): add Sentinel-2 cloud masking and tile preprocessing pipeline\"\n" + "\n" + "# Push from your account\n" + "git push adeolu feature/data-sentinel2-preprocessing" + ) + + pdf.output(os.path.join(OUTPUT_DIR, "Adeolu_Mary_Oshadare_Role.pdf")) + print("Created: Adeolu_Mary_Oshadare_Role.pdf") + + +def create_francis_doc(): + pdf = RoleDoc("Francis Umo") + pdf.add_page() + + pdf.set_font("Helvetica", "B", 18) + pdf.cell(0, 10, "Francis Umo", align="C", new_x="LMARGIN", new_y="NEXT") + pdf.set_font("Helvetica", "", 11) + pdf.set_text_color(100, 100, 100) + pdf.cell(0, 7, "Data Science Engineer 3 - Carbon Analytics & Validation Lead", align="C", new_x="LMARGIN", new_y="NEXT") + pdf.set_text_color(0, 0, 0) + pdf.ln(5) + + pdf.key_value("GitHub", "@franchaise") + pdf.key_value("Access Level", "Maintainer") + pdf.key_value("Reports To", "@Goldokpa (Project Owner)") + pdf.key_value("Project Duration", "3 Months") + pdf.ln(3) + + # How It Fits Me + pdf.section_title("How This Role Fits You") + pdf.body_text( + "With 8+ years of progressive experience in data analysis and business intelligence, you bring " + "the deepest analytical maturity on this team. While others focus on building models and pipelines, " + "you are the person who makes sure the numbers tell the right story and that the results are trustworthy." + ) + pdf.body_text( + "Your expertise in Python, PostgreSQL, and SQL means you can build the carbon estimation models that " + "require heavy data querying, aggregation, and statistical analysis. At Dataleum, you conducted data " + "quality checks, developed dashboards to monitor financial data, and created reports that reduced fraud " + "by 80% - that same rigour is exactly what's needed when validating whether our ML models are correctly " + "estimating carbon loss from deforestation." + ) + pdf.body_text( + "Your proficiency in Tableau and Power BI is a direct match for building the impact reporting layer. " + "ClimateVision needs to produce clear, visual reports that conservation organizations and government " + "agencies can act on. Your data storytelling background makes you the ideal person to translate " + "raw model outputs into actionable intelligence." + ) + pdf.body_text( + "Your cross-functional collaboration experience - working with IT teams, stakeholders, and bringing " + "analytical models into production - means you understand how to bridge the gap between a data science " + "experiment and a production metric that decision-makers rely on." + ) + pdf.ln(2) + + # Role Description + pdf.section_title("Your Role on ClimateVision") + pdf.body_text( + "You own the analytics and validation layer - everything that turns raw model predictions into " + "meaningful environmental metrics. If the ML model says 'this pixel is deforested,' you quantify " + "what that means in tons of carbon, hectares of forest, and dollars of environmental impact." + ) + pdf.subsection_title("Core Responsibilities") + pdf.bullet("Develop carbon stock estimation models (Random Forest, XGBoost regression)") + pdf.bullet("Build biomass-to-carbon conversion pipelines using allometric equations") + pdf.bullet("Implement uncertainty quantification (bootstrap, Monte Carlo, confidence intervals)") + pdf.bullet("Create ground truth validation framework - compare model outputs to known data") + pdf.bullet("Build statistical testing suite (hypothesis testing, A/B testing for model versions)") + pdf.bullet("Design and generate impact reports (area deforested, carbon lost, trends over time)") + pdf.bullet("Develop KPI dashboards for monitoring model performance and environmental outcomes") + pdf.bullet("Create validation notebooks demonstrating model accuracy across regions") + pdf.ln(2) + + # Codebase Ownership + pdf.section_title("Your Codebase Ownership") + pdf.body_text("You are the primary owner of the following files and directories:") + pdf.code_block( + "src/climatevision/analytics/ # PRIMARY OWNER - New analytics module\n" + " carbon.py # Carbon stock estimation models\n" + " statistics.py # Statistical testing & analysis\n" + " reporting.py # Impact report generation\n" + " validation.py # Ground truth validation framework\n" + " __init__.py # Module exports\n" + "\n" + "src/climatevision/models/\n" + " regression.py # PRIMARY OWNER - Biomass/carbon regression\n" + "\n" + "src/climatevision/utils/\n" + " metrics.py # CO-OWNER - Extend with carbon metrics\n" + "\n" + "notebooks/\n" + " 03_carbon_analysis.ipynb # Carbon estimation analysis\n" + " 04_model_validation.ipynb # Validation & benchmarking\n" + " 05_impact_reporting.ipynb # Reporting notebook\n" + "\n" + "outputs/\n" + " reports/ # Generated impact reports\n" + " dashboards/ # Dashboard configs" + ) + pdf.ln(2) + + # 3-Month Timeline + pdf.section_title("Your 3-Month Delivery Timeline") + pdf.month_block("MONTH 1: Foundation (Weeks 1-4)", [ + ("Week 1-2: Carbon Estimation Models", [ + "Research allometric equations for biomass estimation by forest type", + "Build carbon.py - Random Forest & XGBoost regression for biomass prediction", + "Create feature pipeline: spectral indices -> biomass -> carbon conversion", + "Implement metrics for regression evaluation (RMSE, MAE, R-squared)", + ]), + ("Week 3-4: Validation Framework", [ + "Build validation.py - compare model predictions to ground truth datasets", + "Source and integrate reference data (Global Forest Watch, forest inventory data)", + "Create confusion matrix, precision/recall analysis for segmentation outputs", + "Write 04_model_validation.ipynb with baseline validation results", + ]), + ]) + pdf.month_block("MONTH 2: Advanced Analytics (Weeks 5-8)", [ + ("Week 5-6: Uncertainty & Statistical Testing", [ + "Implement bootstrap confidence intervals for carbon estimates", + "Build Monte Carlo simulation for uncertainty propagation", + "Create statistics.py - hypothesis testing, trend analysis functions", + "Implement A/B testing framework for comparing model versions", + ]), + ("Week 7-8: Impact Reporting", [ + "Build reporting.py - automated report generation (PDF/HTML)", + "Design KPI framework: hectares lost, carbon tons, trend direction", + "Create 05_impact_reporting.ipynb - template for regional impact reports", + "Integrate with PostgreSQL for historical metric storage", + ]), + ]) + pdf.month_block("MONTH 3: Production Readiness (Weeks 9-12)", [ + ("Week 9-10: Dashboard & Integration", [ + "Build dashboard data endpoints (feed metrics to frontend charts)", + "Create time-series analysis for deforestation trend tracking", + "Implement anomaly detection for unusual forest loss patterns", + ]), + ("Week 11-12: Documentation & Case Studies", [ + "Produce 3 regional case study reports (Amazon, Congo, Southeast Asia)", + "Write comprehensive documentation for analytics module", + "Final validation sweep across all model outputs", + "Performance benchmarking and accuracy documentation", + ]), + ]) + + # Git Workflow + pdf.section_title("Your Git Workflow") + pdf.code_block( + "# Create feature branches from develop\n" + "git checkout develop\n" + "git pull origin develop\n" + "git checkout -b feature/analytics-carbon-estimation\n" + "\n" + "# Your branch naming convention:\n" + "feature/analytics-* (new analytics features)\n" + "fix/analytics-* (bug fixes)\n" + "refactor/analytics-* (code restructuring)" + ) + pdf.body_text( + "All PRs go to the develop branch. PRs require at least 1 review. " + "Tag @edoh-Onuh for reviews on model evaluation metrics, and @Oshgig for data format questions." + ) + pdf.ln(3) + + # Key Collaborators + pdf.section_title("Your Key Collaborators") + pdf.bullet("@edoh-Onuh (ML Lead) - Their model predictions are your primary input. Coordinate on output formats, probability thresholds, and confidence scores.") + pdf.bullet("@Oshgig (Data Pipeline Lead) - She provides the preprocessed data you need for carbon regression features. Align on spectral indices and metadata.") + pdf.bullet("Olufemi Taiwo (API Lead) - Your analytics endpoints need to be exposed through the API. Coordinate on response schemas.") + pdf.bullet("@cutewizzy11 (Full-Stack) - Frontend dashboards visualize your metrics. Provide JSON data contracts for charts.") + + # Code Pipeline + pdf.section_title("Your Code Pipeline") + pdf.body_text("Your pipeline starts where the ML model ends - taking prediction masks and turning them into carbon impact numbers and stakeholder reports.") + + pdf.subsection_title("Step 1: Environment Setup") + pdf.code_block( + "git clone https://github.com/Climate-Vision/ClimateVision.git\n" + "cd ClimateVision\n" + "pip install -r requirements.txt\n" + "\n" + "# Verify analytics dependencies\n" + "python -c \"import xgboost, sklearn, mlflow, optuna; print('Analytics stack ready')\"" + ) + + pdf.subsection_title("Step 2: Run Inference to Get Prediction Masks") + pdf.code_block( + "# Generate deforestation masks from a trained model\n" + "python scripts/infer.py \\\n" + " --bbox \"-60,-15,-45,5\" \\\n" + " --date 2023-06-01 \\\n" + " --analysis_type deforestation \\\n" + " --output outputs/masks/\n" + "\n" + "# Output: outputs/masks/deforestation_mask.tif + confidence_scores.npy" + ) + + pdf.subsection_title("Step 3: Estimate Carbon Loss") + pdf.code_block( + "# Run carbon stock estimation on the prediction mask\n" + "python - <<'EOF'\n" + "from climatevision.analytics.carbon import estimate_carbon\n" + "result = estimate_carbon(\n" + " mask_path='outputs/masks/deforestation_mask.tif',\n" + " region='amazon',\n" + " forest_type='tropical_moist'\n" + ")\n" + "print(f\"Deforested area: {result['hectares']:.1f} ha\")\n" + "print(f\"Carbon lost: {result['carbon_tonnes']:.1f} tCO2e\")\n" + "print(f\"Confidence CI: {result['ci_lower']:.1f} - {result['ci_upper']:.1f} tCO2e\")\n" + "EOF" + ) + + pdf.subsection_title("Step 4: Validate Against Ground Truth") + pdf.code_block( + "# Compare model outputs to Global Forest Watch reference data\n" + "python - <<'EOF'\n" + "from climatevision.analytics.validation import validate_predictions\n" + "metrics = validate_predictions(\n" + " pred_mask='outputs/masks/deforestation_mask.tif',\n" + " ground_truth='data/ground_truth/amazon_gfw_2023.tif'\n" + ")\n" + "print(f\"IoU: {metrics['iou']:.3f} | F1: {metrics['f1']:.3f} | Precision: {metrics['precision']:.3f}\")\n" + "EOF" + ) + + pdf.subsection_title("Step 5: Generate Impact Report") + pdf.code_block( + "# Auto-generate a PDF/HTML impact report for stakeholders\n" + "python - <<'EOF'\n" + "from climatevision.analytics.reporting import generate_report\n" + "generate_report(\n" + " region='amazon',\n" + " period='2023-Q2',\n" + " carbon_result=result,\n" + " validation_metrics=metrics,\n" + " output_dir='outputs/reports/'\n" + ")\n" + "EOF\n" + "\n" + "# Output: outputs/reports/amazon_2023-Q2_impact_report.pdf" + ) + + pdf.subsection_title("Step 7: Commit & Push Your Work") + pdf.code_block( + "# Switch to your git identity\n" + "source team_docs/switch_user.sh francis\n" + "\n" + "git checkout develop && git pull origin develop\n" + "git checkout -b feature/analytics-carbon-estimation\n" + "\n" + "git add src/climatevision/analytics/\n" + "git add notebooks/03_carbon_analysis.ipynb\n" + "git commit -m \"feat(analytics): add carbon stock estimation with confidence intervals\"\n" + "\n" + "git push francis feature/analytics-carbon-estimation" + ) + + pdf.output(os.path.join(OUTPUT_DIR, "Francis_Umo_Role.pdf")) + print("Created: Francis_Umo_Role.pdf") + + +def create_olufemi_doc(): + pdf = RoleDoc("Olufemi Taiwo") + pdf.add_page() + + pdf.set_font("Helvetica", "B", 18) + pdf.cell(0, 10, "Olufemi Taiwo", align="C", new_x="LMARGIN", new_y="NEXT") + pdf.set_font("Helvetica", "", 11) + pdf.set_text_color(100, 100, 100) + pdf.cell(0, 7, "Data Science Engineer 4 - API & Data Quality Lead", align="C", new_x="LMARGIN", new_y="NEXT") + pdf.set_text_color(0, 0, 0) + pdf.ln(5) + + pdf.key_value("GitHub", "(To be assigned)") + pdf.key_value("Access Level", "Maintainer") + pdf.key_value("Reports To", "@Goldokpa (Project Owner)") + pdf.key_value("Project Duration", "3 Months") + pdf.ln(3) + + # How It Fits Me + pdf.section_title("How This Role Fits You") + pdf.body_text( + "Your current role as Reporting and Data Quality Officer at the Royal Marsden NHS Foundation Trust " + "is the clearest signal for this assignment. Every working day you validate data flows, investigate " + "mismatches across Epic EPR, troubleshoot system errors using SQL, and hold the line on reporting " + "accuracy for senior clinical stakeholders. That obsessive attention to data integrity at every step " + "from input to output is exactly what ClimateVision's API and inference pipeline need." + ) + pdf.body_text( + "At Fidelity Bank, you kept payment platforms reliable around the clock as an Application Support " + "Analyst - triaging incidents, analysing root causes, and producing service reports that guided " + "operational decisions. ClimateVision runs a similar system: satellite images arrive as requests, " + "the API must respond correctly and quickly, and any failure needs to be caught, logged, and " + "escalated before it reaches users. That is your wheelhouse." + ) + pdf.body_text( + "Your Business Intelligence work at Dataleum - building Power BI dashboards, conducting data quality " + "checks, achieving 98% GDPR compliance - means you already understand auditability. In a climate " + "monitoring system used by NGOs and government agencies, every prediction must be traceable, every " + "alert explainable, and every data flow compliant. You build that confidence layer." + ) + pdf.body_text( + "Your ITIL 4 certification is a direct fit for incident management, change control, and problem " + "management in production. Combined with your MSc in Data Science, you are the person who makes " + "the API not just functional, but operationally trustworthy - with structured logging, audit trails, " + "validated schemas, and monitoring that surfaces issues before users notice them." + ) + pdf.ln(2) + + # Role Description + pdf.section_title("Your Role on ClimateVision") + pdf.body_text( + "You own the API layer and the inference pipeline - everything between a trained model and a user " + "receiving a validated, structured response. You ensure the system is reliable, observable, and " + "produces outputs that are correct and auditable. You are the data quality gatekeeper for every " + "prediction that leaves the system." + ) + pdf.subsection_title("Core Responsibilities") + pdf.bullet("Extend and maintain the FastAPI backend (endpoints, authentication, request validation)") + pdf.bullet("Build Pydantic schemas for all API request/response objects - the contract for data quality") + pdf.bullet("Implement structured logging, error handling, and audit trails throughout the inference flow") + pdf.bullet("Build the inference validation layer - catch bad inputs, validate outputs, flag anomalies") + pdf.bullet("Create the deforestation alert system with configurable thresholds and notification routing") + pdf.bullet("Build API monitoring endpoints: health checks, data quality metrics, run status dashboards") + pdf.bullet("Write SQL queries and admin endpoints for operational reporting and data audits") + pdf.bullet("Design and document the API contract (request/response schemas, error codes, versioning)") + pdf.ln(2) + + # Codebase Ownership + pdf.section_title("Your Codebase Ownership") + pdf.body_text("You are the primary owner of the following files and directories:") + pdf.code_block( + "src/climatevision/inference/ # PRIMARY OWNER\n" + " pipeline.py # Core inference pipeline\n" + " batch_processor.py # Batch processing with job queuing\n" + " postprocess.py # Output filtering & thresholding\n" + " alert_generator.py # Deforestation alert system\n" + " __init__.py\n" + "\n" + "src/climatevision/api/ # PRIMARY OWNER\n" + " main.py # FastAPI application\n" + " auth.py # API key authentication\n" + " middleware.py # Request logging, CORS\n" + " schemas.py # Pydantic request/response schemas\n" + " __init__.py\n" + "\n" + "src/climatevision/db.py # CO-OWNER - Database & audit queries\n" + "\n" + "run_api.sh # API startup script\n" + "config.yaml # API & inference config sections" + ) + pdf.ln(2) + + # 3-Month Timeline + pdf.section_title("Your 3-Month Delivery Timeline") + pdf.month_block("MONTH 1: Foundation (Weeks 1-4)", [ + ("Week 1-2: Schemas & Validation", [ + "Build schemas.py - Pydantic models for every API request and response object", + "Extend pipeline.py with input validation: image shape, band count, coordinate bounds", + "Add structured JSON logging throughout the inference flow (request ID, timestamps, errors)", + "Implement output validation - flag predictions outside expected confidence ranges", + ]), + ("Week 3-4: API Hardening", [ + "Implement auth.py - API key authentication and organisation-based access control", + "Build middleware.py - request logging, CORS, request size limits", + "Create /api/health, /api/status, and /api/metrics endpoints for operational monitoring", + "Write API integration tests covering validation edge cases and error responses", + ]), + ]) + pdf.month_block("MONTH 2: Quality & Alerts (Weeks 5-8)", [ + ("Week 5-6: Inference Quality Layer", [ + "Build postprocess.py - confidence thresholding and prediction filtering", + "Implement anomaly detection for unusual inference outputs (flag for review)", + "Create audit log entries for every prediction: input hash, model version, output summary", + "Build batch_processor.py - parallel image processing with per-job status tracking", + ]), + ("Week 7-8: Alert System & Reporting", [ + "Build alert_generator.py - configurable deforestation threshold alerting", + "Implement notification routing (email, webhook) for triggered alerts", + "Write SQL reporting queries for run history, error rates, and data quality KPIs", + "Create admin endpoints for operational dashboards: throughput, failure rates, alert volumes", + ]), + ]) + pdf.month_block("MONTH 3: Observability & Documentation (Weeks 9-12)", [ + ("Week 9-10: Monitoring & Data Quality Reports", [ + "Build a /api/reports endpoint returning data quality metrics over configurable time windows", + "Implement request tracing: correlate API requests to inference runs to alerts", + "Create a data quality dashboard feed (JSON) for the frontend to visualise pipeline health", + "SQL-based audit trail queries: who requested what, when, and with what result", + ]), + ("Week 11-12: Documentation & Launch Readiness", [ + "Write the API reference: all endpoints, schemas, error codes, and usage examples", + "Document the incident response runbook: what each error means and how to resolve it", + "Security review: input sanitisation, SQL injection checks, API key rotation procedures", + "Final integration testing with all team modules - validate end-to-end data flow", + ]), + ]) + + # Git Workflow + pdf.section_title("Your Git Workflow") + pdf.code_block( + "# Create feature branches from develop\n" + "git checkout develop\n" + "git pull origin develop\n" + "git checkout -b feature/api-schemas\n" + "\n" + "# Your branch naming convention:\n" + "feature/api-* (API features & endpoints)\n" + "feature/inference-* (inference pipeline & validation)\n" + "feature/schemas-* (Pydantic schema changes)\n" + "fix/api-* (bug fixes)" + ) + pdf.body_text( + "All PRs go to the develop branch. Tag @cutewizzy11 for API contract reviews (he consumes your " + "endpoints from the frontend) and @edoh-Onuh when touching inference logic that involves model outputs." + ) + pdf.ln(3) + + # Key Collaborators + pdf.section_title("Your Key Collaborators") + pdf.bullet("@edoh-Onuh (ML Lead) - Their trained models are loaded by your inference pipeline. Coordinate on model format (.pth vs ONNX), input shapes, output schemas, and confidence score formats.") + pdf.bullet("@Oshgig (Data Pipeline Lead) - Your inference input validation must match her preprocessing exactly. Align on normalization constants, expected band order, and coordinate formats.") + pdf.bullet("@franchaise (Analytics Lead) - Their analytics endpoints are exposed through your API. Coordinate on response schemas, pagination, and data quality flags in outputs.") + pdf.bullet("@cutewizzy11 (Full-Stack & CI/CD) - He consumes your API from the frontend and manages Docker and deployment. You two define the API contract together - endpoints, schemas, error codes.") + + # Code Pipeline + pdf.section_title("Your Code Pipeline") + pdf.body_text("Your pipeline covers running and validating the FastAPI server, testing all endpoints, enforcing data quality, and maintaining the inference layer.") + + pdf.subsection_title("Step 1: Environment Setup") + pdf.code_block( + "git clone https://github.com/Climate-Vision/ClimateVision.git\n" + "cd ClimateVision\n" + "pip install -r requirements.txt\n" + "\n" + "# Set environment variables\n" + "cp .env.example .env\n" + "# Edit .env: set MODEL_PATH, DB_PATH, API_KEY_SECRET" + ) + + pdf.subsection_title("Step 2: Start the API Server") + pdf.code_block( + "# Start FastAPI in development mode with auto-reload\n" + "uvicorn climatevision.api.main:app \\\n" + " --reload \\\n" + " --host 0.0.0.0 \\\n" + " --port 8000\n" + "\n" + "# Interactive API docs available at:\n" + "# http://localhost:8000/docs\n" + "# http://localhost:8000/redoc" + ) + + pdf.subsection_title("Step 3: Test Prediction Endpoints") + pdf.code_block( + "# Test JSON prediction endpoint\n" + "curl -X POST http://localhost:8000/predict/json \\\n" + " -H \"Content-Type: application/json\" \\\n" + " -d '{\n" + " \"bbox\": [-60, -15, -45, 5],\n" + " \"start_date\": \"2023-01-01\",\n" + " \"end_date\": \"2023-12-31\",\n" + " \"analysis_type\": \"deforestation\"\n" + " }'\n" + "\n" + "# Test file-upload endpoint\n" + "curl -X POST http://localhost:8000/predict/upload \\\n" + " -F \"file=@data/test/sample_tile.tif\" \\\n" + " -F \"analysis_type=flooding\"\n" + "\n" + "# Health check\n" + "curl http://localhost:8000/health" + ) + + pdf.subsection_title("Step 4: Run Data Quality Checks") + pdf.code_block( + "# Validate all run records in the database meet schema requirements\n" + "python - <<'EOF'\n" + "from climatevision.db import get_db_connection, validate_run_schema\n" + "conn = get_db_connection()\n" + "issues = validate_run_schema(conn)\n" + "if issues:\n" + " print(f'Data quality issues found: {len(issues)}')\n" + " for issue in issues:\n" + " print(f' - {issue}')\n" + "else:\n" + " print('All records pass quality checks')\n" + "EOF" + ) + + pdf.subsection_title("Step 5: Register an NGO Organisation") + pdf.code_block( + "# Create an NGO organisation via the API\n" + "curl -X POST http://localhost:8000/organizations \\\n" + " -H \"Content-Type: application/json\" \\\n" + " -d '{\n" + " \"name\": \"Amazon Conservation Trust\",\n" + " \"email\": \"alerts@amazonconservation.org\",\n" + " \"region\": \"amazon\"\n" + " }'\n" + "\n" + "# Add a regional monitoring subscription\n" + "curl -X POST http://localhost:8000/organizations/1/subscriptions \\\n" + " -H \"Content-Type: application/json\" \\\n" + " -d '{\"bbox\": [-60,-15,-45,5], \"analysis_type\": \"deforestation\", \"alert_threshold\": 0.15}'" + ) + + pdf.subsection_title("Step 6: Commit & Push Your Work") + pdf.code_block( + "# Switch to your git identity\n" + "source team_docs/switch_user.sh olufemi\n" + "\n" + "git checkout develop && git pull origin develop\n" + "git checkout -b feature/api-input-validation\n" + "\n" + "git add src/climatevision/api/main.py\n" + "git add src/climatevision/db.py\n" + "git commit -m \"feat(api): add Pydantic input validation and audit logging to predict endpoints\"\n" + "\n" + "# Push from YOUR GitHub account (femi23)\n" + "git push olufemi feature/api-input-validation" + ) + + pdf.output(os.path.join(OUTPUT_DIR, "Olufemi_Taiwo_Role.pdf")) + print("Created: Olufemi_Taiwo_Role.pdf") + + +def create_edoh_doc(): + pdf = RoleDoc("Edoh-Onuh") + pdf.add_page() + + pdf.set_font("Helvetica", "B", 18) + pdf.cell(0, 10, "Edoh-Onuh (John Edoh Onuh)", align="C", new_x="LMARGIN", new_y="NEXT") + pdf.set_font("Helvetica", "", 11) + pdf.set_text_color(100, 100, 100) + pdf.cell(0, 7, "Data Science Engineer 1 - ML Model Development Lead", align="C", new_x="LMARGIN", new_y="NEXT") + pdf.set_text_color(0, 0, 0) + pdf.ln(5) + + pdf.key_value("GitHub", "@edoh-Onuh") + pdf.key_value("Access Level", "Maintainer") + pdf.key_value("Reports To", "@Goldokpa (Project Owner)") + pdf.key_value("Project Duration", "3 Months") + pdf.ln(3) + + # How It Fits Me + pdf.section_title("How This Role Fits You") + pdf.body_text( + "Your GitHub portfolio makes the case better than any job description could. You built JED Climate - " + "a full-stack climate intelligence platform - independently. It has a FastAPI analytics engine serving " + "a carbon calculator and climate predictor, PyTorch/TensorFlow ML services, real-time Recharts " + "dashboards for CO2 levels, Arctic ice extent, and sea level rise, and a 14-service Docker Compose " + "local stack. That is almost exactly what ClimateVision is. You already know this problem space." + ) + pdf.body_text( + "Your fintech-fraud-detection repo demonstrates the depth of ML engineering this role needs: " + "XGBoost, Random Forest, and Neural Network ensembles with sub-100ms inference latency, SHAP/LIME " + "explainability, concept drift detection, and a production-grade FastAPI serving layer. The same " + "engineering discipline - fast, explainable, reliable model inference - is exactly what ClimateVision's " + "deforestation detection pipeline requires." + ) + pdf.body_text( + "Your classification track record is consistent and strong: diabetes risk prediction (Scikit-learn), " + "fraud detection (XGBoost + Neural Networks), text classification (NLP), and time series forecasting " + "(Tesla stock). Every one of those is a direct analogue to forest vs. non-forest pixel segmentation - " + "the core problem you will be solving here with U-Net and Siamese architectures." + ) + pdf.body_text( + "Your sustainable energy analysis and JED Climate's environmental dashboards show you genuinely " + "understand the climate data domain - spectral trends, temporal signals, and what makes environmental " + "metrics meaningful. That context matters when you are tuning a model to detect 5% forest loss " + "in Sentinel-2 imagery at 10-metre resolution." + ) + pdf.ln(2) + + # Role Description + pdf.section_title("Your Role on ClimateVision") + pdf.body_text( + "You own all deep learning model architectures, the training pipeline, and model evaluation. " + "Your goal is to train models that achieve high accuracy on forest segmentation and change " + "detection, then package them cleanly for the inference pipeline. Carbon regression modelling " + "sits with the Analytics Lead - your focus is purely classification and change detection." + ) + pdf.subsection_title("Core Responsibilities") + pdf.bullet("Improve and extend the U-Net architecture (Attention U-Net, residual connections, multi-scale features)") + pdf.bullet("Train and evaluate the Siamese network for temporal bi-date change detection") + pdf.bullet("Build a complete training pipeline: data loading, training loop, validation, checkpointing") + pdf.bullet("Implement loss functions tuned for satellite imagery class imbalance (Focal Loss, Dice Loss)") + pdf.bullet("Run hyperparameter optimisation using Optuna (learning rate, batch size, architecture depth)") + pdf.bullet("Implement transfer learning from pretrained encoders (ResNet, EfficientNet backbones)") + pdf.bullet("Build model evaluation framework: F1, IoU, precision-recall curves, confusion matrices") + pdf.bullet("Export optimised models to ONNX for production inference speed") + pdf.bullet("Implement experiment tracking with MLflow - log runs, metrics, and artefacts") + pdf.ln(2) + + # Codebase Ownership + pdf.section_title("Your Codebase Ownership") + pdf.body_text("You are the primary owner of the following files and directories:") + pdf.code_block( + "src/climatevision/models/ # PRIMARY OWNER\n" + " unet.py # U-Net & Attention U-Net\n" + " siamese.py # Siamese change detection network\n" + " __init__.py\n" + " # Note: regression.py is owned by @franchaise (Analytics Lead)\n" + "\n" + "src/climatevision/training/ # PRIMARY OWNER - New module\n" + " trainer.py # Training loop & checkpointing\n" + " evaluator.py # Model evaluation framework\n" + " scheduler.py # Learning rate schedulers\n" + " callbacks.py # Early stopping, logging\n" + " __init__.py\n" + "\n" + "src/climatevision/utils/\n" + " metrics.py # CO-OWNER - Loss functions, metrics\n" + "\n" + "scripts/\n" + " run_training.py # Training pipeline script\n" + " train.py # Existing training script\n" + " hyperparameter_search.py # Optuna hyperparameter search\n" + "\n" + "models/ # Trained model weights\n" + "models_pretrained/ # Pretrained backbone weights" + ) + pdf.ln(2) + + # 3-Month Timeline + pdf.section_title("Your 3-Month Delivery Timeline") + pdf.month_block("MONTH 1: Foundation (Weeks 1-4)", [ + ("Week 1-2: Training Infrastructure", [ + "Build trainer.py - complete training loop with mixed-precision, gradient accumulation", + "Implement checkpointing (save best model, resume from checkpoint)", + "Create evaluator.py - F1, IoU, precision, recall, confusion matrix", + "Set up experiment tracking with MLflow - log all runs, hyperparameters, artefacts", + ]), + ("Week 3-4: Baseline Models", [ + "Train baseline U-Net on curated forest segmentation dataset", + "Implement Focal Loss and Dice Loss for forest/non-forest class imbalance", + "Run initial benchmarks: accuracy on Amazon, Congo, Southeast Asia test sets", + "Document baseline results as the performance floor to beat", + ]), + ]) + pdf.month_block("MONTH 2: Advanced Models (Weeks 5-8)", [ + ("Week 5-6: Architecture Improvements", [ + "Implement Attention U-Net with skip connection attention gates", + "Add ResNet/EfficientNet encoder backbone via transfer learning (ImageNet pretrained)", + "Run hyperparameter search with Optuna (learning rate, batch size, depth, dropout)", + "Train Siamese network for bi-temporal change detection", + ]), + ("Week 7-8: Model Optimisation", [ + "Implement model ensemble (U-Net + Attention U-Net prediction averaging)", + "Build Monte Carlo Dropout for per-pixel uncertainty estimation", + "Spatial cross-validation to prevent data leakage across adjacent image tiles", + "Performance benchmarking across all model variants - pick production candidate", + ]), + ]) + pdf.month_block("MONTH 3: Production Models (Weeks 9-12)", [ + ("Week 9-10: Export & Versioning", [ + "Export best-performing models to ONNX format for fast production inference", + "Implement model quantisation and pruning for latency reduction", + "Set up model registry with versioning, metadata, and performance records", + "Create model cards: accuracy, known limitations, training data, bias notes", + ]), + ("Week 11-12: Final Evaluation", [ + "Comprehensive evaluation on held-out test sets across all regions", + "Ablation studies: measure contribution of each architectural choice", + "Write model documentation and training reproduction guide", + "Integration testing with Olufemi's inference pipeline - validate end-to-end", + ]), + ]) + + # Git Workflow + pdf.section_title("Your Git Workflow") + pdf.code_block( + "# Create feature branches from develop\n" + "git checkout develop\n" + "git pull origin develop\n" + "git checkout -b feature/model-attention-unet\n" + "\n" + "# Your branch naming convention:\n" + "feature/model-* (new model architectures)\n" + "feature/training-* (training pipeline features)\n" + "fix/model-* (bug fixes)\n" + "experiment/model-* (experimental architectures)" + ) + pdf.body_text( + "All PRs go to the develop branch. Tag @Oshgig when your models require different data formats, " + "@franchaise when evaluation metrics or output confidence formats change, and Olufemi Taiwo " + "when touching model export formats or inference input shapes." + ) + pdf.ln(3) + + # Key Collaborators + pdf.section_title("Your Key Collaborators") + pdf.bullet("@Oshgig (Data Pipeline Lead) - She builds the DataLoaders you train on. Coordinate on tensor shapes, normalization values, band order, and augmentation strategies.") + pdf.bullet("@franchaise (Analytics Lead) - He owns carbon regression modelling and validates your classification outputs against ground truth. Share model confidence scores and prediction probability formats.") + pdf.bullet("Olufemi Taiwo (API & Data Quality Lead) - He loads your trained models into the inference pipeline. Coordinate on model file format (.pth vs ONNX), expected input shapes, and output schema.") + pdf.bullet("@cutewizzy11 (Full-Stack & CI/CD) - CI/CD pipeline runs your training scripts. Keep scripts deterministic, well-documented, and reproducible.") + + # Code Pipeline + pdf.section_title("Your Code Pipeline") + pdf.body_text("Your pipeline covers model architecture development, training, evaluation, and exporting production-ready checkpoints.") + + pdf.subsection_title("Step 1: Environment Setup") + pdf.code_block( + "git clone https://github.com/Climate-Vision/ClimateVision.git\n" + "cd ClimateVision\n" + "pip install -r requirements.txt\n" + "\n" + "# Verify PyTorch and GPU availability\n" + "python -c \"import torch; print(f'PyTorch {torch.__version__} | CUDA: {torch.cuda.is_available()}')\"" + ) + + pdf.subsection_title("Step 2: Verify Data Is Ready") + pdf.code_block( + "# Confirm @Oshgig's DataLoader feeds correctly into your model\n" + "python - <<'EOF'\n" + "from climatevision.data.dataset import SatelliteDataset\n" + "from torch.utils.data import DataLoader\n" + "ds = SatelliteDataset('data/processed/', split='train')\n" + "loader = DataLoader(ds, batch_size=4, num_workers=2)\n" + "imgs, masks = next(iter(loader))\n" + "print(f'Batch shape: {imgs.shape} | Mask shape: {masks.shape}')\n" + "# Expected: torch.Size([4, 13, 256, 256]) | torch.Size([4, 256, 256])\n" + "EOF" + ) + + pdf.subsection_title("Step 3: Train Baseline U-Net") + pdf.code_block( + "# Train baseline segmentation model\n" + "python scripts/train.py \\\n" + " --model unet \\\n" + " --analysis-type deforestation \\\n" + " --epochs 50 \\\n" + " --batch-size 16 \\\n" + " --lr 1e-4 \\\n" + " --checkpoint-dir models/ \\\n" + " --mlflow-tracking\n" + "\n" + "# Monitor training: open http://localhost:5000 (MLflow UI)\n" + "mlflow ui --port 5000" + ) + + pdf.subsection_title("Step 4: Hyperparameter Search") + pdf.code_block( + "# Run Optuna search over learning rate, batch size, depth\n" + "python scripts/hyperparameter_search.py \\\n" + " --model unet \\\n" + " --n-trials 50 \\\n" + " --study-name unet_deforestation_v1 \\\n" + " --metric val_iou\n" + "\n" + "# Best trial is automatically saved to models/best_hparam_unet.pth" + ) + + pdf.subsection_title("Step 5: Evaluate & Export Model") + pdf.code_block( + "# Full evaluation on held-out test set\n" + "python scripts/evaluate.py \\\n" + " --checkpoint models/best_unet.pth \\\n" + " --split test \\\n" + " --analysis-type deforestation\n" + "\n" + "# Export to ONNX for fast production inference\n" + "python scripts/export_model.py \\\n" + " --checkpoint models/best_unet.pth \\\n" + " --format onnx \\\n" + " --output models/unet_deforestation_v1.onnx" + ) + + pdf.subsection_title("Step 6: Commit & Push Your Work") + pdf.code_block( + "# Switch to your git identity\n" + "source team_docs/switch_user.sh edoh\n" + "\n" + "git checkout develop && git pull origin develop\n" + "git checkout -b feature/model-attention-unet\n" + "\n" + "git add src/climatevision/models/unet.py\n" + "git add src/climatevision/training/\n" + "git commit -m \"feat(model): add attention gates to U-Net encoder skip connections\"\n" + "\n" + "git push edoh feature/model-attention-unet" + ) + + pdf.output(os.path.join(OUTPUT_DIR, "Edoh_Onuh_Role.pdf")) + print("Created: Edoh_Onuh_Role.pdf") + + +def create_victor_doc(): + pdf = RoleDoc("Victor Mbachu") + pdf.add_page() + + pdf.set_font("Helvetica", "B", 18) + pdf.cell(0, 10, "Victor Mbachu", align="C", new_x="LMARGIN", new_y="NEXT") + pdf.set_font("Helvetica", "", 11) + pdf.set_text_color(100, 100, 100) + pdf.cell(0, 7, "Senior Full-Stack Engineer & Infrastructure Co-Owner", align="C", new_x="LMARGIN", new_y="NEXT") + pdf.set_text_color(0, 0, 0) + pdf.ln(5) + + pdf.key_value("GitHub", "@cutewizzy11") + pdf.key_value("Access Level", "Co-Owner (Admin)") + pdf.key_value("Reports To", "@Goldokpa (Project Owner)") + pdf.key_value("Project Duration", "3 Months") + pdf.ln(3) + + # How It Fits Me + pdf.section_title("How This Role Fits You") + pdf.body_text( + "At Zeta Global you design and run distributed microservice systems handling over 2 million API " + "requests daily with 99.9% uptime across multiple AWS regions - ECS Fargate clusters, RDS Aurora, " + "SNS/SQS messaging, and blue-green CI/CD deployments provisioned via Terraform. You also serve as " + "on-call engineer with a 15-minute average incident resolution time. That is the production " + "engineering standard ClimateVision needs to reach, and you have already built it professionally." + ) + pdf.body_text( + "At RWS Global you containerised applications with Docker, deployed across dev, staging, and " + "production environments, led a team of 3 engineers in Agile sprints, and maintained GitHub Actions " + "CI/CD pipelines with TDD coverage. The Docker and deployment ownership on this project - " + "previously unassigned - is a natural fit: you do this as part of your day job, not as a " + "stretch task." + ) + pdf.body_text( + "Your stack breadth is the reason you can serve as repository co-owner rather than just a " + "frontend contributor. React, Next.js, Vue, TypeScript, Node.js, PHP/Laravel, Python/Django - " + "you can read and reason about the FastAPI backend, the PyTorch inference pipeline, and the " + "React dashboard with equal confidence. Reviewing PRs across four data scientists requires " + "that range. Your AWS Certified Cloud Practitioner and Professional Scrum Master certifications " + "anchor both the infrastructure ownership and the project coordination function." + ) + pdf.body_text( + "Your AI integration experience - GPT-4 and Anthropic API work at RWS Global and PetMe - " + "means you understand the ML serving layer you are wrapping with a frontend. When @edoh-Onuh " + "exports a model and Olufemi builds the inference API, you are not reading foreign code. You " + "have shipped production AI features before. Your two co-authored papers on agentic AI systems " + "show that engagement runs deeper than implementation." + ) + pdf.ln(2) + + # Role Description + pdf.section_title("Your Role on ClimateVision") + pdf.body_text( + "You own the frontend application, the CI/CD infrastructure, and the Docker/deployment layer. " + "As co-owner you are also the quality gate for all code entering the repository - the one " + "person on the team who can review and reason about every layer of the stack." + ) + pdf.subsection_title("Core Responsibilities - Frontend") + pdf.bullet("Build the React/TypeScript dashboard with interactive Leaflet map for satellite analysis results") + pdf.bullet("Create Recharts components for deforestation trends, carbon metrics, and model performance") + pdf.bullet("Implement api.ts - the fully-typed API client for all FastAPI backend communication") + pdf.bullet("Build the alert notification panel for real-time deforestation alerts") + pdf.bullet("Implement responsive TailwindCSS design for desktop and tablet viewports") + pdf.bullet("Create the deep-dive analysis page with region selector, date range picker, and model comparison") + pdf.ln(1) + + pdf.subsection_title("Core Responsibilities - Infrastructure & CI/CD") + pdf.bullet("Own the Dockerfile - multi-stage production build for the FastAPI + frontend application") + pdf.bullet("Own docker-compose.yml - local development stack wiring API, database, and frontend services") + pdf.bullet("Build and maintain GitHub Actions CI/CD pipelines: lint, type-check, test, and deploy on every PR") + pdf.bullet("Manage production environment configuration - dev/staging/prod separation and secrets management") + pdf.bullet("Serve as first responder for production incidents - triage, diagnose, and coordinate resolution") + pdf.ln(1) + + pdf.subsection_title("Sprint Progress - April 2026") + pdf.bullet("DONE: GitHub Actions CI pipeline (Python flake8 + pytest, frontend npm build)") + pdf.bullet("DONE: Test scaffolding (tests/ directory with pytest fixtures)") + pdf.bullet("DONE: Frontend build fixes (case-sensitive import paths)") + pdf.bullet("DONE: Dependency fixes (removed gdal pip package, added email-validator)") + pdf.bullet("PENDING: Frontend unit tests with Vitest + React Testing Library") + pdf.bullet("PENDING: Auth UI - capture X-API-Key in AppContext") + pdf.bullet("PENDING: WebSocket client for real-time run status") + pdf.bullet("PENDING: Alert notification UI with severity filters") + pdf.bullet("PENDING: Mask overlay on map component") + pdf.bullet("PENDING: Docker Compose for full-stack local dev") + pdf.ln(1) + + pdf.subsection_title("Core Responsibilities - Co-Owner") + pdf.bullet("Review and merge pull requests from all team members (target: <24 hour turnaround)") + pdf.bullet("Manage GitHub issues, milestones, project boards, and sprint planning") + pdf.bullet("Enforce branch protection rules, code quality standards, and API contract consistency") + pdf.bullet("Manage the release process: version tagging, changelog, and release notes") + pdf.ln(2) + + # Codebase Ownership + pdf.section_title("Your Codebase Ownership") + pdf.body_text("You are the primary owner of the following files and directories:") + pdf.code_block( + "frontend/ # PRIMARY OWNER - Entire frontend\n" + " src/\n" + " App.tsx # Main application shell\n" + " api.ts # Typed API client\n" + " main.tsx # Entry point\n" + " styles.css # TailwindCSS styles\n" + " components/ # Component library\n" + " Map.tsx # Leaflet map\n" + " ResultsViewer.tsx # Prediction results\n" + " Charts.tsx # Recharts visualizations\n" + " AlertPanel.tsx # Alert notifications\n" + " Settings.tsx # User settings\n" + " pages/\n" + " Dashboard.tsx # Main dashboard\n" + " Analysis.tsx # Deep analysis view\n" + " History.tsx # Run history\n" + " package.json | vite.config.ts | tsconfig.json\n" + "\n" + "Dockerfile # PRIMARY OWNER - Multi-stage production build\n" + "docker-compose.yml # PRIMARY OWNER - Local development stack\n" + "\n" + ".github/workflows/ # PRIMARY OWNER\n" + " ci.yml # Continuous integration\n" + " deploy.yml # Deployment pipeline\n" + " tests.yml # Test automation\n" + "\n" + "tests/ # CO-OWNER (with all DS engineers)" + ) + pdf.ln(2) + + # 3-Month Timeline + pdf.section_title("Your 3-Month Delivery Timeline") + pdf.month_block("MONTH 1: Foundation (Weeks 1-4)", [ + ("Week 1-2: Infrastructure & CI/CD", [ + "Write multi-stage Dockerfile for optimised API + frontend production image", + "Build docker-compose.yml wiring FastAPI, SQLite/PostgreSQL, and frontend services locally", + "Set up GitHub Actions CI: lint, type-check, pytest, and Vite build on every PR", + "Create branch protection rules: require passing CI and 1 review before merging to develop", + ]), + ("Week 3-4: Frontend Architecture & Core Components", [ + "Configure React Router, Vite, TypeScript strict mode, TailwindCSS, ESLint, and Prettier", + "Build Map.tsx - Leaflet map with GeoJSON overlay for deforestation masks", + "Implement api.ts - fully-typed API client for all FastAPI endpoints", + "Create Dashboard.tsx - main landing page with summary metrics and run status", + ]), + ]) + pdf.month_block("MONTH 2: Feature Development (Weeks 5-8)", [ + ("Week 5-6: Data Visualisation", [ + "Build Charts.tsx - Recharts components for deforestation trend lines, bar charts, gauges", + "Create ResultsViewer.tsx - segmentation masks overlaid on satellite imagery", + "Implement Analysis.tsx - region selector, date picker, model comparison view", + "Set up Vitest and React Testing Library - component test coverage from the start", + ]), + ("Week 7-8: Real-Time & Interactivity", [ + "Build WebSocket integration for live prediction job status updates", + "Create AlertPanel.tsx - real-time deforestation alert notification feed", + "Implement History.tsx - paginated, filterable list of past analysis runs", + "Build Settings.tsx - user preferences and API key management", + ]), + ]) + pdf.month_block("MONTH 3: Production Readiness (Weeks 9-12)", [ + ("Week 9-10: Deployment & Environment Config", [ + "Configure dev/staging/prod environment separation with secrets management", + "Set up deployment pipeline to Vercel (frontend) and Docker-based backend hosting", + "Implement health monitoring and automated alerting for production incidents", + "Performance pass: code splitting, lazy loading, image optimisation, bundle analysis", + ]), + ("Week 11-12: Integration, Testing & Release", [ + "Full end-to-end integration testing against all backend API endpoints", + "Responsive design audit for tablet and large desktop breakpoints", + "Accessibility review: keyboard navigation and screen reader compatibility", + "Manage v1.0 release: changelog, version tag, release notes, and deployment sign-off", + ]), + ]) + + # Git Workflow + pdf.section_title("Your Git Workflow") + pdf.code_block( + "# Create feature branches from develop\n" + "git checkout develop\n" + "git pull origin develop\n" + "git checkout -b feature/frontend-leaflet-map\n" + "\n" + "# Your branch naming convention:\n" + "feature/frontend-* (frontend features)\n" + "feature/infra-* (Docker, CI/CD, deployment)\n" + "feature/ci-* (GitHub Actions changes)\n" + "fix/frontend-* (bug fixes)\n" + "release/v* (release branches)" + ) + pdf.body_text( + "As co-owner, you can merge directly to develop after self-review for frontend-only or infra-only " + "changes. For changes touching shared Python code or API contracts, get a review from @Goldokpa " + "or the relevant module owner." + ) + pdf.ln(3) + + # Key Collaborators + pdf.section_title("Your Key Collaborators") + pdf.bullet("Olufemi Taiwo (API & Data Quality Lead) - He owns the FastAPI schemas, inference validation, and audit logging. You own the Docker image and deployment pipeline that runs his API. Define the API contract together: endpoint URLs, request/response shapes, auth headers, and error formats.") + pdf.bullet("@franchaise (Analytics Lead) - His carbon metrics and KPI data feed your dashboard charts. Align on JSON data contracts, refresh intervals, and pagination formats.") + pdf.bullet("@edoh-Onuh (ML Lead) - Model prediction outputs need to be visualised on the map. Coordinate on GeoJSON output format, confidence score rendering, and how prediction jobs report status via the API.") + pdf.bullet("@Oshgig (Data Pipeline Lead) - Satellite imagery tile previews on the map may draw on her geospatial utilities. Align on tile formats, coordinate systems, and GeoJSON structures.") + + # Code Pipeline + pdf.section_title("Your Code Pipeline") + pdf.body_text("Your pipeline covers frontend development, Docker orchestration, CI/CD management, and full-stack integration testing.") + + pdf.subsection_title("Step 1: Environment Setup") + pdf.code_block( + "git clone https://github.com/Climate-Vision/ClimateVision.git\n" + "cd ClimateVision\n" + "\n" + "# Backend dependencies\n" + "pip install -r requirements.txt\n" + "\n" + "# Frontend dependencies\n" + "cd frontend && npm install && cd .." + ) + + pdf.subsection_title("Step 2: Start Full Local Dev Stack") + pdf.code_block( + "# Option A: Docker Compose (full stack - recommended)\n" + "docker-compose up --build\n" + "# API: http://localhost:8000\n" + "# Frontend: http://localhost:5173\n" + "# MLflow: http://localhost:5000\n" + "\n" + "# Option B: Run services individually for faster iteration\n" + "uvicorn climatevision.api.main:app --reload --port 8000 &\n" + "cd frontend && npm run dev" + ) + + pdf.subsection_title("Step 3: Frontend Development Loop") + pdf.code_block( + "cd frontend\n" + "\n" + "# Run linting and type checks\n" + "npm run lint\n" + "npm run type-check\n" + "\n" + "# Run component tests\n" + "npm run test\n" + "\n" + "# Build production bundle and check for errors\n" + "npm run build\n" + "\n" + "# Preview production build locally\n" + "npm run preview" + ) + + pdf.subsection_title("Step 4: Current CI/CD Configuration") + pdf.body_text("The following .github/workflows/ci.yml is live and runs on every PR to main/develop:") + pdf.code_block( + "name: CI\n" + "on:\n" + " push:\n" + " branches: [main, develop]\n" + " pull_request:\n" + " branches: [main, develop]\n" + "\n" + "jobs:\n" + " python:\n" + " runs-on: ubuntu-latest\n" + " steps:\n" + " - uses: actions/checkout@v4\n" + " - uses: actions/setup-python@v5\n" + " with: {python-version: '3.11'}\n" + " - run: sudo apt-get update && sudo apt-get install -y libgl1\n" + " - run: pip install -r requirements.txt && pip install -e .\n" + " - run: flake8 src/ --select=E9,F63,F7,F82\n" + " - run: pytest tests/ -v --tb=short\n" + "\n" + " frontend:\n" + " runs-on: ubuntu-latest\n" + " defaults: {run: {working-directory: frontend}}\n" + " steps:\n" + " - uses: actions/checkout@v4\n" + " - uses: actions/setup-node@v4\n" + " with: {node-version: '20', cache: 'npm'}\n" + " - run: npm ci\n" + " - run: npm run build" + ) + pdf.ln(2) + + pdf.subsection_title("Step 5: Build & Test Docker Image") + pdf.code_block( + "# Build production Docker image\n" + "docker build -t climatevision:latest .\n" + "\n" + "# Run container and verify it starts cleanly\n" + "docker run -p 8000:8000 climatevision:latest\n" + "\n" + "# Check all services are healthy inside the container\n" + "curl http://localhost:8000/health\n" + "\n" + "# Inspect image size and layers\n" + "docker image inspect climatevision:latest | grep Size" + ) + + pdf.subsection_title("Step 6: Run Full CI Checks Locally") + pdf.code_block( + "# Simulate the GitHub Actions CI pipeline before pushing\n" + "\n" + "# 1. Python: lint and tests\n" + "flake8 src/ --count --select=E9,F63,F7,F82 --show-source --statistics\n" + "flake8 src/ --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics\n" + "pytest tests/ -v --tb=short\n" + "\n" + "# 2. Frontend: build\n" + "cd frontend && npm run build\n" + "\n" + "# 3. Docker build succeeds\n" + "docker-compose build" + ) + + pdf.subsection_title("Step 6: Commit & Push Your Work") + pdf.code_block( + "# Switch to your git identity\n" + "source team_docs/switch_user.sh victor\n" + "\n" + "git checkout develop && git pull origin develop\n" + "git checkout -b feature/frontend-leaflet-map\n" + "\n" + "git add frontend/src/components/Map.tsx\n" + "git add frontend/src/api.ts\n" + "git commit -m \"feat(frontend): add Leaflet map with GeoJSON deforestation overlay\"\n" + "\n" + "git push victor feature/frontend-leaflet-map\n" + "\n" + "# As co-owner: review and merge PRs from the team\n" + "# gh pr review --approve\n" + "# gh pr merge --squash" + ) + + pdf.output(os.path.join(OUTPUT_DIR, "Victor_Mbachu_Role.pdf")) + print("Created: Victor_Mbachu_Role.pdf") + + +def create_godswill_doc(): + pdf = RoleDoc("Godswill Okoroafor Chukwu") + pdf.add_page() + + pdf.set_font("Helvetica", "B", 18) + pdf.cell(0, 10, "Godswill Okoroafor Chukwu", align="C", new_x="LMARGIN", new_y="NEXT") + pdf.set_font("Helvetica", "", 11) + pdf.set_text_color(100, 100, 100) + pdf.cell(0, 7, "Data Science Engineer 5 - ML Training, Experiment Tracking & Insights Lead", align="C", new_x="LMARGIN", new_y="NEXT") + pdf.set_text_color(0, 0, 0) + pdf.ln(5) + + pdf.key_value("GitHub", "(To be assigned)") + pdf.key_value("Access Level", "Maintainer") + pdf.key_value("Reports To", "@Goldokpa (Project Owner)") + pdf.key_value("Project Duration", "3 Months") + pdf.ln(3) + + # How It Fits Me + pdf.section_title("How This Role Fits You") + pdf.body_text( + "Your MSc in Big Data and Data Science Technology (Distinction) from Northumbria University is the " + "academic backbone this role demands. You have not just studied machine learning - you have delivered " + "it in production environments. At Amdari Inc., you built predictive and forecasting models that drove " + "strategic revenue decisions, applied clustering to identify at-risk student groups, and automated " + "reporting pipelines that cut manual processing time significantly. Every one of those deliverables " + "maps directly onto what ClimateVision needs from its ML training and insights layer." + ) + pdf.body_text( + "Where @edoh-Onuh architects the deep learning models (U-Net, Siamese networks), you are the engineer " + "who drives those models through rigorous training cycles, tracks every experiment, measures every " + "metric, and extracts insights from the results. Your experience running classification, regression, " + "and clustering pipelines in Python - combined with your Data Scientist role at Amdari - means you " + "understand the full lifecycle: data in, model trained, results validated, insights delivered." + ) + pdf.body_text( + "Your proficiency in Power BI and Looker Studio is a strategic asset here. ClimateVision generates " + "real predictions - deforestation percentages, ice extent loss, flood area - that conservation NGOs " + "and research partners need presented clearly. You build the reporting layer that translates raw model " + "outputs into KPI dashboards, trend reports, and alert summaries that non-technical stakeholders " + "can act on. That is the last mile between a working model and measurable real-world impact." + ) + pdf.body_text( + "Your background in automating recurring reporting processes with Python and designing cross-functional " + "dashboards means you also own the bridge between the ML pipeline and the business intelligence layer. " + "With your DataCamp Associate Data Scientist certification and Full Stack Data Science qualification " + "from 10Alytics, you bring both the theoretical depth and the applied toolkit that this role requires." + ) + pdf.ln(2) + + # Role Description + pdf.section_title("Your Role on ClimateVision") + pdf.body_text( + "You own the training analytics, experiment tracking, and insights reporting pipeline - the layer that " + "connects raw model outputs to actionable environmental intelligence. While the ML Lead builds model " + "architectures and the Data Pipeline Lead ingests satellite imagery, you are the engineer who runs " + "training experiments at scale, tracks what works and why, measures model impact, and delivers " + "structured insights to teams and stakeholders. You are the system's analytical conscience." + ) + pdf.subsection_title("Core Responsibilities") + pdf.bullet("Orchestrate model training runs using scripts/train.py and scripts/run_training.py with full experiment tracking via MLflow") + pdf.bullet("Design and execute hyperparameter tuning experiments using Optuna to maximise IoU, F1, and Dice scores") + pdf.bullet("Build and maintain the model evaluation pipeline - benchmarking across deforestation, ice melting, and flooding tasks") + pdf.bullet("Implement clustering analysis on prediction outputs to identify regional environmental patterns and hotspots") + pdf.bullet("Develop forecasting models to project deforestation trends, ice melt rates, and flood risk over time") + pdf.bullet("Automate KPI reporting pipelines that summarise model performance and environmental metrics for NGO stakeholders") + pdf.bullet("Design and maintain Power BI / Looker Studio dashboards tracking training progress, model accuracy, and climate impact") + pdf.bullet("Create data quality reports that validate training datasets and flag anomalies before they reach the model") + pdf.bullet("Produce regional impact analysis notebooks showing before/after environmental change metrics") + pdf.bullet("Feed structured insight data to the API layer and React dashboard for live reporting") + pdf.ln(2) + + # Codebase Ownership + pdf.section_title("Your Codebase Ownership") + pdf.body_text("You are the primary owner of the following files and directories:") + pdf.code_block( + "scripts/ # PRIMARY OWNER - Training & evaluation scripts\n" + " train.py # Model training entry point\n" + " run_training.py # Training orchestration & scheduling\n" + " evaluate.py # Model evaluation & benchmarking\n" + " infer.py # Single inference runner\n" + "\n" + "src/climatevision/training/\n" + " trainer.py # CO-OWNER - Training loop, EMA, mixed precision\n" + " losses.py # CO-OWNER - Focal Loss, Dice Loss tuning\n" + "\n" + "src/climatevision/utils/\n" + " metrics.py # CO-OWNER - IoU, F1, Dice, recall tracking\n" + " visualization.py # CO-OWNER - Training curve & result plots\n" + "\n" + "notebooks/\n" + " 06_training_analysis.ipynb # Experiment tracking & training insights\n" + " 07_model_benchmarking.ipynb # Cross-task model performance comparison\n" + " 08_regional_insights.ipynb # Clustering & trend analysis by region\n" + "\n" + "outputs/\n" + " reports/training/ # Training run reports\n" + " dashboards/kpi/ # KPI dashboard configs\n" + "\n" + "logs/ # Training logs & MLflow run artifacts\n" + "models/ # Model checkpoints (coordinate with ML Lead)" + ) + pdf.ln(2) + + # Key Impact Areas + pdf.section_title("Your High-Impact Contributions") + pdf.body_text( + "Your work directly determines whether ClimateVision's models are as accurate as possible and whether " + "their outputs are trusted by the organisations that rely on them. Three areas define your impact:" + ) + pdf.subsection_title("1. Experiment-Driven Model Improvement") + pdf.body_text( + "Every training run you log is a data point. By systematically tracking learning rate schedules, " + "augmentation strategies, loss function weights, and batch sizes via MLflow and Optuna, you will " + "build the evidence base that drives model accuracy from baseline to production-grade. Your tuning " + "work is the difference between a model that detects 65% of deforestation events and one that " + "detects 85%." + ) + pdf.subsection_title("2. Regional Clustering & Trend Forecasting") + pdf.body_text( + "Your clustering expertise turns raw pixel predictions into geographic intelligence. By grouping " + "regions with similar deforestation trajectories or flood risk patterns, you reveal insights that " + "no single prediction run can show. Paired with time-series forecasting models, you can project " + "where the next environmental crisis is developing before it becomes catastrophic - giving NGO " + "partners the lead time they need to act." + ) + pdf.subsection_title("3. Stakeholder-Ready Reporting") + pdf.body_text( + "Raw model metrics mean nothing to a conservation officer or a policy researcher. Your Power BI " + "and automated Python reporting pipelines convert IoU scores and segmentation masks into carbon " + "loss estimates, hectare counts, and trend alerts that stakeholders can put in a board report. " + "This is the last mile of impact - and you own it." + ) + pdf.ln(2) + + # 3-Month Timeline + pdf.section_title("Your 3-Month Delivery Timeline") + pdf.month_block("MONTH 1: Foundation (Weeks 1-4)", [ + ("Week 1-2: Training Infrastructure & Experiment Tracking", [ + "Set up MLflow tracking server and connect to scripts/train.py", + "Instrument trainer.py to log all hyperparameters, metrics, and artifacts per run", + "Run baseline training experiments for deforestation, ice melting, and flooding tasks", + "Document baseline IoU, F1, and Dice scores per analysis type", + ]), + ("Week 3-4: Evaluation Pipeline", [ + "Build scripts/evaluate.py - full evaluation suite with per-class metrics", + "Extend metrics.py with precision-recall curves and confusion matrix exports", + "Create 07_model_benchmarking.ipynb - cross-task performance comparison", + "Identify top 3 weaknesses in baseline models and propose tuning strategies", + ]), + ]) + pdf.month_block("MONTH 2: Optimisation & Insights (Weeks 5-8)", [ + ("Week 5-6: Hyperparameter Tuning", [ + "Set up Optuna study for learning rate, batch size, loss weights, and augmentation", + "Run tuning experiments targeting IoU improvement of at least 10% over baseline", + "Log all trials in MLflow with full reproducibility (seed, config, checkpoint)", + "Implement best-config automatic checkpoint promotion pipeline", + ]), + ("Week 7-8: Clustering & Trend Forecasting", [ + "Build regional clustering pipeline using K-Means / DBSCAN on prediction outputs", + "Develop time-series forecasting models for deforestation and ice melt trends", + "Create 08_regional_insights.ipynb - hotspot identification and trend projections", + "Generate first set of regional environmental trend reports", + ]), + ]) + pdf.month_block("MONTH 3: Reporting & Production Readiness (Weeks 9-12)", [ + ("Week 9-10: KPI Dashboard & Automated Reporting", [ + "Build automated Python reporting pipeline - weekly model performance summaries", + "Design Power BI / Looker Studio KPI dashboard (accuracy trends, alert counts, coverage)", + "Expose dashboard data via API endpoints coordinated with Olufemi", + "Automate NGO-facing impact reports: area affected, confidence scores, trend direction", + ]), + ("Week 11-12: Documentation & Final Benchmarks", [ + "Write 06_training_analysis.ipynb - full experiment history and lessons learned", + "Produce final benchmark report comparing all model versions across 3 months", + "Document all MLflow experiments, best checkpoints, and recommended configs", + "Deliver 3 regional case study insight reports to the team for stakeholder use", + ]), + ]) + + # Git Workflow + pdf.section_title("Your Git Workflow") + pdf.body_text("Follow this branching convention for all your work:") + pdf.code_block( + "# Create feature branches from develop\n" + "git checkout develop\n" + "git pull origin develop\n" + "git checkout -b feature/training-mlflow-setup\n" + "\n" + "# Your branch naming convention:\n" + "feature/training-* (training pipeline features)\n" + "feature/insights-* (reporting and analytics features)\n" + "fix/training-* (bug fixes in training scripts)\n" + "experiment/tuning-* (hyperparameter experiment branches)" + ) + pdf.body_text( + "All PRs go to the develop branch. PRs require at least 1 review. " + "Tag @edoh-Onuh for model architecture questions and @franchaise for analytics overlap reviews. " + "Always attach MLflow run IDs in PRs that change training logic so reviewers can verify metrics." + ) + pdf.ln(3) + + # Key Collaborators + pdf.section_title("Your Key Collaborators") + pdf.bullet("@edoh-Onuh (ML Model Development Lead) - You run the training experiments on their model architectures. Coordinate on loss function choices, training hyperparameters, and checkpoint formats. Their architecture decisions constrain your tuning search space.") + pdf.bullet("@Oshgig (Data Pipeline Lead) - Your training runs consume her PyTorch DataLoaders. Align on tensor shapes, normalization ranges, augmentation strategies, and the data split structure (train/val/test).") + pdf.bullet("@franchaise (Carbon Analytics Lead) - Your model evaluation outputs are the input to their carbon estimation and validation work. Provide segmentation mask formats, confidence scores, and per-class metrics in agreed schemas.") + pdf.bullet("Olufemi Taiwo (API & Data Quality Lead) - Your KPI reporting data needs to be surfaced via API endpoints. Coordinate on response formats, refresh cycles, and how training run metadata is exposed to the dashboard.") + pdf.bullet("Victor Mbachu (Full-Stack & Infrastructure) - Your dashboard configs and reporting outputs feed the React frontend visualisations. Align on JSON contracts for time-series charts, gauge metrics, and alert summaries.") + + # Code Pipeline + pdf.section_title("Your Code Pipeline") + pdf.body_text("Your pipeline covers experiment tracking setup, running and tuning training jobs, evaluating model performance, and generating insight reports for stakeholders.") + + pdf.subsection_title("Step 1: Environment Setup") + pdf.code_block( + "git clone https://github.com/Climate-Vision/ClimateVision.git\n" + "cd ClimateVision\n" + "pip install -r requirements.txt\n" + "\n" + "# Verify ML and analytics stack\n" + "python -c \"import torch, mlflow, optuna, sklearn; print('ML stack ready')\"\n" + "\n" + "# Start MLflow tracking server\n" + "mlflow server --host 0.0.0.0 --port 5000 &\n" + "# Dashboard: http://localhost:5000" + ) + + pdf.subsection_title("Step 2: Run a Training Experiment") + pdf.code_block( + "# Run a tracked training job\n" + "python scripts/run_training.py \\\n" + " --config config/deforestation.yaml \\\n" + " --mlflow-tracking \\\n" + " --experiment-name deforestation_v1\n" + "\n" + "# All metrics, params, and checkpoints auto-logged to MLflow\n" + "# View results: http://localhost:5000/#/experiments" + ) + + pdf.subsection_title("Step 3: Hyperparameter Tuning with Optuna") + pdf.code_block( + "# Launch an Optuna study to find the best training config\n" + "python - <<'EOF'\n" + "import optuna, mlflow\n" + "from climatevision.training.trainer import train_with_config\n" + "\n" + "def objective(trial):\n" + " config = {\n" + " 'lr': trial.suggest_float('lr', 1e-5, 1e-3, log=True),\n" + " 'batch_size': trial.suggest_categorical('batch_size', [8, 16, 32]),\n" + " 'dropout': trial.suggest_float('dropout', 0.1, 0.5),\n" + " }\n" + " return train_with_config(config, metric='val_iou')\n" + "\n" + "study = optuna.create_study(direction='maximize', study_name='unet_deforestation')\n" + "study.optimize(objective, n_trials=50)\n" + "print(f'Best IoU: {study.best_value:.4f}')\n" + "print(f'Best params: {study.best_params}')\n" + "EOF" + ) + + pdf.subsection_title("Step 4: Evaluate & Benchmark Models") + pdf.code_block( + "# Evaluate best checkpoint across all analysis types\n" + "python scripts/evaluate.py \\\n" + " --checkpoint models/best_unet.pth \\\n" + " --split test \\\n" + " --analysis-type deforestation \\\n" + " --export-metrics outputs/reports/training/deforestation_eval.json\n" + "\n" + "# Compare all model versions logged in MLflow\n" + "python - <<'EOF'\n" + "import mlflow\n" + "runs = mlflow.search_runs(experiment_names=['deforestation_v1'],\n" + " order_by=['metrics.val_iou DESC'])\n" + "print(runs[['run_id','metrics.val_iou','params.lr','params.batch_size']].head(10))\n" + "EOF" + ) + + pdf.subsection_title("Step 5: Generate Stakeholder KPI Report") + pdf.code_block( + "# Run clustering on prediction outputs to find regional hotspots\n" + "python - <<'EOF'\n" + "from sklearn.cluster import KMeans\n" + "import numpy as np, json\n" + "predictions = np.load('outputs/masks/deforestation_confidence.npy')\n" + "kmeans = KMeans(n_clusters=5, random_state=42).fit(predictions.reshape(-1, 1))\n" + "hotspot_regions = np.where(kmeans.labels_ == kmeans.cluster_centers_.argmax())[0]\n" + "print(f'High-risk tiles identified: {len(hotspot_regions)}')\n" + "EOF\n" + "\n" + "# Auto-generate weekly KPI summary report\n" + "python - <<'EOF'\n" + "from climatevision.analytics.reporting import generate_kpi_report\n" + "generate_kpi_report(\n" + " metrics_dir='outputs/reports/training/',\n" + " period='2024-W12',\n" + " output='outputs/dashboards/kpi/weekly_summary.pdf'\n" + ")\n" + "EOF" + ) + + pdf.subsection_title("Step 6: Commit & Push Your Work") + pdf.code_block( + "# Switch to your git identity\n" + "source team_docs/switch_user.sh godswill\n" + "\n" + "git checkout develop && git pull origin develop\n" + "git checkout -b feature/training-mlflow-setup\n" + "\n" + "git add scripts/run_training.py\n" + "git add scripts/evaluate.py\n" + "git add notebooks/06_training_analysis.ipynb\n" + "git commit -m \"feat(training): add MLflow experiment tracking and Optuna hyperparameter search\"\n" + "\n" + "git push godswill feature/training-mlflow-setup" + ) + + pdf.output(os.path.join(OUTPUT_DIR, "Godswill_Chukwu_Role.pdf")) + print("Created: Godswill_Chukwu_Role.pdf") + + +def create_paul_doc(): + pdf = RoleDoc("Paul (cutewizzy11)") + pdf.add_page() + + pdf.set_font("Helvetica", "B", 18) + pdf.cell(0, 10, "Paul", align="C", new_x="LMARGIN", new_y="NEXT") + pdf.set_font("Helvetica", "", 11) + pdf.set_text_color(100, 100, 100) + pdf.cell(0, 7, "Frontend Developer - React Dashboard & UI Lead", align="C", new_x="LMARGIN", new_y="NEXT") + pdf.set_text_color(0, 0, 0) + pdf.ln(5) + + pdf.key_value("GitHub", "@cutewizzy11") + pdf.key_value("Access Level", "Maintainer") + pdf.key_value("Reports To", "@Goldokpa (Project Owner)") + pdf.key_value("Project Duration", "3 Months") + pdf.ln(3) + + # How It Fits + pdf.section_title("How This Role Fits You") + pdf.body_text( + "Your GitHub portfolio shows a developer who is comfortable across the full stack but has a clear " + "strength in TypeScript and JavaScript-driven interfaces. nova-agent, Data-management-Koinonia, " + "and anyebe-web-craft are all TypeScript projects - the same language ClimateVision's frontend is " + "built in. Your react-projects and ecommerce-app repositories show hands-on React experience, and " + "your Heart-Attack-Risk-Predictor on Streamlit shows you can bridge data science outputs and " + "interactive user interfaces - exactly the challenge you face here." + ) + pdf.body_text( + "ClimateVision's dashboard already has a working foundation: React 18, TypeScript strict mode, " + "Vite, TailwindCSS, React Router, Recharts, and a fully-typed API client. Your job is not to " + "start from scratch - it is to take this functional base and build the components, pages, and " + "interactions that turn it into a polished, production-ready environmental monitoring dashboard " + "that NGOs and researchers can actually use." + ) + pdf.body_text( + "Your experience with data management interfaces (Koinonia church app) and e-commerce UIs means " + "you understand how to build interfaces where users interact with structured data - filtering, " + "searching, viewing records, managing subscriptions. That skill maps directly onto ClimateVision's " + "run history browser, NGO subscription manager, and alert tracking panel. You have shipped this " + "category of UI before." + ) + pdf.ln(2) + + # Role Description + pdf.section_title("Your Role on ClimateVision") + pdf.body_text( + "You own the React dashboard - every pixel the end user sees. The backend API is built, the " + "data models are defined, and the component library has a strong foundation. Your mission is " + "to complete the user-facing layer: build missing pages, wire components to live API data, " + "implement real-time updates, and ensure the interface is responsive, accessible, and fast. " + "You are the engineer who makes ClimateVision feel like a real product." + ) + pdf.subsection_title("Core Responsibilities") + pdf.bullet("Build and complete all dashboard pages: Dashboard home, NGO Management, Alerts, and deep-dive Analysis views") + pdf.bullet("Wire all components to live API data using the existing api.ts client - replace mock/static data throughout") + pdf.bullet("Implement real-time run status updates using polling (useRunPolling hook) and WebSocket for live job tracking") + pdf.bullet("Build the NGO management page - organisation registration, subscription setup, alert acknowledgment") + pdf.bullet("Implement the Alerts page - filterable, paginated alert feed with severity badges and map drill-down") + pdf.bullet("Extend the Map components - overlay segmentation masks on the map after prediction completes") + pdf.bullet("Add component-level tests using Vitest and React Testing Library") + pdf.bullet("Ensure full responsive design for tablet and desktop breakpoints using TailwindCSS") + pdf.bullet("Implement accessibility: keyboard navigation, screen reader labels, focus management") + pdf.bullet("Performance: code splitting, lazy loading pages, skeleton loading states already in the UI library") + pdf.ln(2) + + # Codebase Ownership + pdf.section_title("Your Codebase Ownership") + pdf.body_text("You are the primary owner of the entire frontend directory:") + pdf.code_block( + "frontend/src/ # PRIMARY OWNER - Full frontend\n" + "\n" + " pages/ # PRIMARY OWNER - All page components\n" + " NewAnalysis.tsx # Exists - extend with live map result overlay\n" + " Upload.tsx # Exists - connect to /predict/upload endpoint\n" + " RunHistory.tsx # Exists - add filters, pagination, search\n" + " Analytics.tsx # Exists - connect live data, add date picker\n" + " Settings.tsx # Exists - wire to API key and config endpoints\n" + " Dashboard.tsx # BUILD - Home page KPI summary\n" + " NGOManagement.tsx # BUILD - Org registration + subscriptions\n" + " Alerts.tsx # BUILD - Alert feed with severity filters\n" + "\n" + " components/ # PRIMARY OWNER - All UI components\n" + " charts/ # Extend existing Recharts components\n" + " Map/ # Extend - add mask overlay on results\n" + " ngo/ # Complete - wire AlertsPanel, SubscriptionManager\n" + " results/ # Complete - wire ResultsPanel to live predictions\n" + " runs/ # Extend RunCard with status polling\n" + " ui/ # Extend UI library as needed\n" + "\n" + " api.ts # CO-OWNER - Add any missing endpoint calls\n" + " types.ts # CO-OWNER - Add frontend-specific types\n" + " contexts/ # CO-OWNER - AppContext, ToastContext\n" + " hooks/ # PRIMARY OWNER - useGeocoding, useRunPolling\n" + "\n" + " tests/ # PRIMARY OWNER - Component tests (to be created)\n" + " components/\n" + " pages/" + ) + pdf.ln(2) + + # 3-Month Timeline + pdf.section_title("Your 3-Month Delivery Timeline") + pdf.month_block("MONTH 1: Foundation & Live Data (Weeks 1-4)", [ + ("Week 1-2: Setup & API Wiring", [ + "Clone repo, install deps, run dev server - verify all pages render", + "Run the FastAPI backend locally and confirm api.ts endpoints connect", + "Wire RunHistory page to live /runs API data - replace any static data", + "Wire Analytics page to live run metrics - confirm charts render with real data", + "Add loading skeletons (SkeletonCard already exists) to all data-fetching pages", + ]), + ("Week 3-4: Dashboard Home & Settings", [ + "Build Dashboard.tsx - KPI summary cards: total runs, alerts, analysis breakdown", + "Add Dashboard as the new root route (/) and move NewAnalysis to /new-analysis", + "Wire Settings.tsx to API config endpoints - API base URL, analysis preferences", + "Implement Toast notifications for success/error states across all forms", + ]), + ]) + pdf.month_block("MONTH 2: NGO Features & Real-Time (Weeks 5-8)", [ + ("Week 5-6: NGO Management Page", [ + "Build NGOManagement.tsx - list registered organisations from /organizations endpoint", + "Implement organisation registration form with validation", + "Build SubscriptionManager UI - region bbox picker + analysis type + threshold", + "Wire to POST /organizations and POST /organizations/{id}/subscriptions endpoints", + ]), + ("Week 7-8: Alerts & Real-Time Updates", [ + "Build Alerts.tsx - paginated alert feed filtered by severity and analysis type", + "Implement alert acknowledgment button wired to PATCH /organizations/{id}/alerts/{id}", + "Extend useRunPolling hook to poll job status and update UI when predictions complete", + "Add live segmentation mask overlay on RegionMap after a prediction run finishes", + ]), + ]) + pdf.month_block("MONTH 3: Polish & Production (Weeks 9-12)", [ + ("Week 9-10: Testing & Accessibility", [ + "Set up Vitest and React Testing Library - write tests for all page components", + "Test all API integration points with mocked responses", + "Accessibility audit: add aria-labels, keyboard nav, focus rings across all pages", + "Responsive design audit - tablet (768px) and large desktop (1440px) breakpoints", + ]), + ("Week 11-12: Performance & Final Integration", [ + "Implement React.lazy() and Suspense for all page-level code splitting", + "Bundle analysis with vite-bundle-visualizer - eliminate unused dependencies", + "Full end-to-end test: bbox input -> prediction job -> live status -> result on map", + "Final UI polish pass: spacing, typography, colour consistency across all pages", + ]), + ]) + + # Code Pipeline + pdf.section_title("Your Code Pipeline") + pdf.body_text("Your daily pipeline as frontend developer - from clone to a live feature pushed to GitHub.") + + pdf.subsection_title("Step 1: Setup") + pdf.code_block( + "git clone https://github.com/Climate-Vision/ClimateVision.git\n" + "cd ClimateVision/frontend\n" + "npm install\n" + "\n" + "# Start the backend API (needed for live data)\n" + "cd .. && uvicorn climatevision.api.main:app --reload --port 8000 &\n" + "\n" + "# Start the frontend dev server\n" + "cd frontend && npm run dev\n" + "# App running at: http://localhost:5173" + ) + + pdf.subsection_title("Step 2: Build a New Page or Component") + pdf.code_block( + "# Example: building the Dashboard home page\n" + "touch src/pages/Dashboard.tsx\n" + "\n" + "# Import existing UI primitives - don't rebuild what exists\n" + "# Available: Card, Badge, StatusBadge, SkeletonCard, ProgressBar,\n" + "# Tooltip, EmptyState, ErrorBoundary, AnalysisTypeSelector\n" + "\n" + "# Import charts - already built with Recharts\n" + "# Available: TimeSeriesChart, BarChart, GaugeChart\n" + "\n" + "# Import API functions from api.ts\n" + "# import { listRuns, listOrganizations, listAlerts } from '../api'" + ) + + pdf.subsection_title("Step 3: Connect to Live API Data") + pdf.code_block( + "# Example: fetching live runs in a component\n" + "import { useEffect, useState } from 'react'\n" + "import { listRuns } from '../api'\n" + "import type { Run } from '../api'\n" + "\n" + "const [runs, setRuns] = useState([])\n" + "const [loading, setLoading] = useState(true)\n" + "\n" + "useEffect(() => {\n" + " listRuns().then(data => {\n" + " setRuns(data)\n" + " setLoading(false)\n" + " })\n" + "}, [])\n" + "\n" + "# Use SkeletonCard while loading\n" + "if (loading) return " + ) + + pdf.subsection_title("Step 4: Run Quality Checks") + pdf.code_block( + "# From the frontend/ directory:\n" + "\n" + "# TypeScript type check - zero errors before pushing\n" + "npm run type-check\n" + "\n" + "# Lint check\n" + "npm run lint\n" + "\n" + "# Run component tests\n" + "npm run test\n" + "\n" + "# Production build - must succeed before any PR\n" + "npm run build" + ) + + pdf.subsection_title("Step 5: Commit & Push Your Work") + pdf.code_block( + "# Switch to your git identity\n" + "source team_docs/switch_user.sh paul\n" + "\n" + "git checkout develop && git pull origin develop\n" + "git checkout -b feature/frontend-dashboard-home\n" + "\n" + "# Stage only frontend files\n" + "git add frontend/src/pages/Dashboard.tsx\n" + "git add frontend/src/main.tsx\n" + "\n" + "git commit -m \"feat(frontend): add Dashboard home page with KPI summary cards\"\n" + "\n" + "# Push from your GitHub account\n" + "git push paul feature/frontend-dashboard-home\n" + "\n" + "# Branch naming convention:\n" + "# feature/frontend-* new UI features\n" + "# fix/frontend-* bug fixes\n" + "# refactor/frontend-* component refactoring" + ) + + pdf.section_title("Your Key Collaborators") + pdf.bullet("Olufemi Taiwo (femi23) - He owns the FastAPI backend your api.ts calls. Any new endpoint you need, request it from him. Coordinate on response shapes, pagination, and error formats.") + pdf.bullet("@Goldokpa (Project Owner) - He built the original api.ts and App shell. He is your first point of contact for architecture questions and has context on every frontend design decision.") + pdf.bullet("@franchaise (Analytics Lead) - His carbon metrics and KPI data feed your Analytics and Dashboard pages. Agree on the JSON structure for chart data with him.") + pdf.bullet("Victor Mbachu (@cutewizzy11 in other refs) - If Docker or CI/CD issues block your local dev, coordinate with the infrastructure owner.") + pdf.bullet("@edoh-Onuh (ML Lead) - Model prediction outputs appear as map overlays in your UI. Coordinate on the GeoJSON mask format and confidence score schema so your map component renders them correctly.") + + pdf.output(os.path.join(OUTPUT_DIR, "Paul_cutewizzy11_Role.pdf")) + print("Created: Paul_cutewizzy11_Role.pdf") + + +def create_gold_doc(): + pdf = RoleDoc("Gold Okpa") + pdf.add_page() + + pdf.set_font("Helvetica", "B", 18) + pdf.cell(0, 10, "Gold Okpa", align="C", new_x="LMARGIN", new_y="NEXT") + pdf.set_font("Helvetica", "", 11) + pdf.set_text_color(100, 100, 100) + pdf.cell(0, 7, "Project Owner & Lead Architect - ClimateVision", align="C", new_x="LMARGIN", new_y="NEXT") + pdf.set_text_color(0, 0, 0) + pdf.ln(5) + + pdf.key_value("GitHub", "@Goldokpa") + pdf.key_value("Access Level", "Owner (Admin)") + pdf.key_value("Email", "okpagold@gmail.com") + pdf.key_value("Project Duration", "Ongoing") + pdf.ln(3) + + # Role Overview + pdf.section_title("Your Role on ClimateVision") + pdf.body_text( + "You built ClimateVision from the ground up. Every foundational layer of this system - the React " + "frontend and API client, the Google Earth Engine integration with service account auth and synthetic " + "NDVI fallback, the data pipeline scripts, the training and evaluation infrastructure, the Colab " + "training notebook, and the overall architecture - was shipped by you. You are not just the project " + "owner in title. You are the technical architect, the integration lead, and the person who knows " + "every module of this codebase at a deep level." + ) + pdf.body_text( + "As the team scales, your role shifts from building everything yourself to orchestrating six " + "specialist engineers - setting the architectural direction, reviewing and merging their code, " + "maintaining the integrity of the overall system, and ensuring every module fits together cleanly. " + "You are the final authority on what goes into the main branch and what ships to users." + ) + pdf.ln(2) + + pdf.subsection_title("Core Responsibilities") + pdf.bullet("Own the overall system architecture and make final decisions on design patterns, module boundaries, and API contracts") + pdf.bullet("Review and merge all pull requests into the develop and main branches") + pdf.bullet("Maintain config.yaml - the single source of truth for all model, data, and API configuration") + pdf.bullet("Own the Google Earth Engine integration and satellite data orchestration at the system level") + pdf.bullet("Manage GitHub repository: branch protection rules, secrets, environment variables, and access permissions") + pdf.bullet("Coordinate sprint planning, milestone tracking, and cross-team dependency resolution") + pdf.bullet("Own the release process: version tagging, changelog, and production deployment sign-off") + pdf.bullet("Onboard new team members and ensure every engineer has the access and context they need") + pdf.bullet("Make final calls on model selection, analysis type prioritisation, and stakeholder deliverables") + pdf.ln(2) + + # Codebase Ownership + pdf.section_title("Your Codebase Ownership") + pdf.body_text("As project owner you have authority over the full codebase. Your primary ownership areas are:") + pdf.code_block( + "config.yaml # PRIMARY OWNER - All system configuration\n" + ".env / .env.example # PRIMARY OWNER - Environment secrets template\n" + "setup.py / requirements.txt # PRIMARY OWNER - Package definition\n" + "\n" + "src/climatevision/ # ARCHITECT - Full codebase authority\n" + " api/main.py # Co-owner with Olufemi - original author\n" + " analysis/ # Original author - analysis framework\n" + " config.py # PRIMARY OWNER - Config management\n" + " db.py # PRIMARY OWNER - Database schema\n" + "\n" + "scripts/ # ORIGINAL AUTHOR - All pipeline scripts\n" + " prepare_data.py # GEE data pipeline (you built this)\n" + " setup_gee.py # GEE service account auth\n" + " train.py | evaluate.py | infer.py # Training & inference scripts\n" + " export_model.py # ONNX export\n" + "\n" + "frontend/ # ORIGINAL AUTHOR - App shell & API client\n" + " src/App.tsx # Main application\n" + " src/api.ts # API client (you wrote this)\n" + "\n" + "notebooks/ # ORIGINAL AUTHOR\n" + " train_on_colab.ipynb # Colab training notebook\n" + "\n" + ".github/ # PRIMARY OWNER - CI/CD and repo rules\n" + "README.md / CONTRIBUTING.md # PRIMARY OWNER - Public documentation" + ) + pdf.ln(2) + + # 3-Month Plan + pdf.section_title("Your 3-Month Orchestration Plan") + pdf.month_block("MONTH 1: Team Integration (Weeks 1-4)", [ + ("Week 1-2: Onboarding & Access", [ + "Grant all 6 engineers Maintainer access on GitHub", + "Set up branch protection: require passing CI + 1 review on develop", + "Create GitHub project board with milestones mapped to each engineer's 3-month timeline", + "Distribute and walk through each team member's role document", + "Verify all engineers can clone the repo, install dependencies, and run the API locally", + ]), + ("Week 3-4: Architecture Alignment", [ + "Hold kickoff session: walkthrough of config.yaml, module boundaries, and API contracts", + "Define and document tensor shapes, data formats, and model output schemas", + "Review and merge first PRs from each team member - establish code review rhythm", + "Set up MLflow server on shared infrastructure for experiment tracking", + ]), + ]) + pdf.month_block("MONTH 2: Integration & Quality (Weeks 5-8)", [ + ("Week 5-6: Cross-Module Integration", [ + "Integration test: Adeolu's DataLoader -> Edoh's model -> Olufemi's inference API", + "Integration test: Olufemi's API output -> Francis' carbon estimation -> Victor's dashboard", + "Resolve any data contract mismatches between modules", + "Set up automated integration test suite in GitHub Actions", + ]), + ("Week 7-8: Architecture Reviews", [ + "Review all module implementations against original architecture design", + "Identify and resolve any technical debt or design drift before it compounds", + "Run end-to-end test: satellite bbox input -> dashboard output for all 3 analysis types", + "Performance profiling: measure API latency and model inference time", + ]), + ]) + pdf.month_block("MONTH 3: Production & Release (Weeks 9-12)", [ + ("Week 9-10: Production Hardening", [ + "Review all security configurations: API keys, CORS, input validation, secrets management", + "Final review of Docker and CI/CD pipeline with Victor", + "Load test the API endpoints - verify stability under concurrent requests", + "Complete documentation audit: README, API docs, and module docstrings", + ]), + ("Week 11-12: v1.0 Release", [ + "Final code review sweep across all modules", + "Tag v1.0 release with full changelog", + "Deploy to production environment and verify all services healthy", + "Publish project to open-source community and notify NGO partners", + ]), + ]) + + # Code Pipeline + pdf.section_title("Your Code Pipeline") + pdf.body_text("As project owner your pipeline covers architecture, integration testing, PR reviews, and release management - as well as direct development when extending core systems.") + + pdf.subsection_title("Step 1: Daily Project Management") + pdf.code_block( + "# Check open PRs and review queue\n" + "gh pr list --repo Climate-Vision/ClimateVision\n" + "\n" + "# Check CI status across all branches\n" + "gh run list --repo Climate-Vision/ClimateVision --limit 10\n" + "\n" + "# View open issues\n" + "gh issue list --repo Climate-Vision/ClimateVision --label bug" + ) + + pdf.subsection_title("Step 2: Review & Merge a Team Member's PR") + pdf.code_block( + "# Fetch and checkout their branch for local testing\n" + "git fetch origin\n" + "git checkout feature/data-sentinel2-preprocessing\n" + "\n" + "# Test their code runs correctly\n" + "pip install -r requirements.txt\n" + "python -c \"from climatevision.data.preprocessing import preprocess_tiles; print('OK')\"\n" + "\n" + "# Review on GitHub and approve\n" + "gh pr review --approve --body \"Tested locally - preprocessing pipeline works correctly\"\n" + "\n" + "# Merge into develop\n" + "gh pr merge --squash --delete-branch" + ) + + pdf.subsection_title("Step 3: Run End-to-End Integration Test") + pdf.code_block( + "# Start all services\n" + "docker-compose up --build -d\n" + "\n" + "# Test the full pipeline: bbox -> prediction -> response\n" + "curl -X POST http://localhost:8000/predict/json \\\n" + " -H \"Content-Type: application/json\" \\\n" + " -d '{\"bbox\": [-60,-15,-45,5], \"start_date\": \"2023-01-01\",\n" + " \"end_date\": \"2023-12-31\", \"analysis_type\": \"deforestation\"}'\n" + "\n" + "# Run automated integration tests\n" + "pytest tests/integration/ -v\n" + "\n" + "# Verify frontend builds and loads dashboard data\n" + "cd frontend && npm run build && npm run preview" + ) + + pdf.subsection_title("Step 4: Update System Configuration") + pdf.code_block( + "# Edit the master config (all analysis types, thresholds, model params)\n" + "# File: config.yaml\n" + "\n" + "# Example: update deforestation alert threshold\n" + "# deforestation:\n" + "# alert_threshold: 0.15 -> 0.10 (more sensitive)\n" + "\n" + "# Validate config loads correctly after changes\n" + "python - <<'EOF'\n" + "from climatevision.config import load_config\n" + "cfg = load_config('config.yaml')\n" + "print(f\"Analysis types: {list(cfg.keys())}\")\n" + "EOF" + ) + + pdf.subsection_title("Step 5: Tag a Release") + pdf.code_block( + "# Ensure you are on the owner identity\n" + "source team_docs/switch_user.sh gold\n" + "\n" + "# Merge develop into main for release\n" + "git checkout main\n" + "git merge develop --no-ff -m \"release: v1.0.0\"\n" + "\n" + "# Tag the release\n" + "git tag -a v1.0.0 -m \"ClimateVision v1.0.0 - Deforestation, Ice Melt, Flood Detection\"\n" + "\n" + "# Push main and tag to GitHub\n" + "git push origin main\n" + "git push origin v1.0.0\n" + "\n" + "# Create GitHub release with changelog\n" + "gh release create v1.0.0 \\\n" + " --title \"ClimateVision v1.0.0\" \\\n" + " --notes \"First production release. Supports deforestation, arctic ice, and flood detection.\"" + ) + + pdf.subsection_title("Step 6: Direct Development (Core Systems)") + pdf.code_block( + "# When extending core architecture directly\n" + "source team_docs/switch_user.sh gold\n" + "\n" + "git checkout develop && git pull origin develop\n" + "git checkout -b feature/core-new-analysis-type\n" + "\n" + "# Make changes to core modules (analysis/, config.py, db.py, api/main.py)\n" + "\n" + "git add src/climatevision/analysis/\n" + "git add config.yaml\n" + "git commit -m \"feat(core): add drought detection analysis type to registry\"\n" + "\n" + "# Push as project owner\n" + "git push origin feature/core-new-analysis-type" + ) + + pdf.section_title("Your Key Collaborators") + pdf.bullet("Victor Mbachu (@cutewizzy11) - Co-owner for infrastructure decisions. Coordinate on Dockerfile, CI/CD pipelines, and production deployment architecture.") + pdf.bullet("Edoh-Onuh (@edoh-Onuh) - ML Lead. Final authority on model architecture decisions sits with you, but Edoh drives the implementation. Review all model PRs carefully.") + pdf.bullet("Olufemi Taiwo (femi23) - API Lead. You are the original author of main.py. Any structural changes to the API must go through your review.") + pdf.bullet("Adeolu Mary Oshadare (@Oshgig) - Data Pipeline Lead. You built the GEE scripts she extends. Maintain alignment on data contracts between ingestion and training.") + pdf.bullet("Francis Umo (@franchaise) - Analytics Lead. Carbon estimates and impact reports are the primary stakeholder-facing output. Review these deliverables closely.") + pdf.bullet("Godswill Chukwu - ML Insights Lead. His experiment results and KPI reports inform your architectural and model selection decisions.") + + pdf.output(os.path.join(OUTPUT_DIR, "Gold_Okpa_Role.pdf")) + print("Created: Gold_Okpa_Role.pdf") + + +if __name__ == "__main__": + create_adeolu_doc() + create_francis_doc() + create_olufemi_doc() + create_edoh_doc() + create_victor_doc() + create_godswill_doc() + create_paul_doc() + create_gold_doc() + print(f"\nAll 8 role documents generated in: {OUTPUT_DIR}") From 044c6db130740bed209292db40bfcd2b78c728d4 Mon Sep 17 00:00:00 2001 From: Garvit Sharma Date: Wed, 29 Apr 2026 15:13:30 +0530 Subject: [PATCH 4/6] feat(frontend): add ApiError component and improve API error handling --- frontend/src/components/ui/ApiError.tsx | 25 +++++++++++++++++++++++++ frontend/src/pages/NewAnalysis.tsx | 13 ++++++++++--- frontend/src/pages/Upload.tsx | 11 +++++++---- 3 files changed, 42 insertions(+), 7 deletions(-) create mode 100644 frontend/src/components/ui/ApiError.tsx diff --git a/frontend/src/components/ui/ApiError.tsx b/frontend/src/components/ui/ApiError.tsx new file mode 100644 index 0000000..93021f6 --- /dev/null +++ b/frontend/src/components/ui/ApiError.tsx @@ -0,0 +1,25 @@ +import { AlertCircle, X } from "lucide-react"; +import { useState } from "react"; + +interface ApiErrorProps { + message: string; +} + +export function ApiError({ message }: ApiErrorProps) { + const [visible, setVisible] = useState(true); + + if (!visible) return null; + + return ( +
+
+ +

{message}

+
+ + +
+ ); +} \ No newline at end of file diff --git a/frontend/src/pages/NewAnalysis.tsx b/frontend/src/pages/NewAnalysis.tsx index a670bc8..7fc2fb3 100644 --- a/frontend/src/pages/NewAnalysis.tsx +++ b/frontend/src/pages/NewAnalysis.tsx @@ -10,6 +10,7 @@ import { ErrorBoundary } from '../components/ui/ErrorBoundary' import { useToast } from '../contexts/ToastContext' import { useApp } from '../contexts/AppContext' import type { Run } from '../api' +import { ApiError } from '../components/ui/ApiError' const PRESETS = [ { label: 'Last 30d', days: 30 }, @@ -44,6 +45,7 @@ export default function NewAnalysis() { const [busy, setBusy] = useState(false) const [resultRun, setResultRun] = useState(null) const [resultPayload, setResultPayload] = useState | null>(null) + const [error, setError] = useState(null) const canSubmit = bbox !== null && startDate && endDate && !busy @@ -67,8 +69,11 @@ export default function NewAnalysis() { setResultPayload(null) try { + setBusy(true); + setError(null); const res = await predictJson({ kind: 'bbox', analysis_type: analysisType, bbox: bbox!, start_date: startDate, end_date: endDate }) setResultPayload(res.result) + // Construct a minimal Run object for the results panel setResultRun({ id: res.run_id, @@ -85,8 +90,9 @@ export default function NewAnalysis() { label: 'View in history', onClick: () => navigate('/runs'), }) - } catch (e) { - showToast('error', String(e)) + } catch (e:any) { + const message = e?.response?.data?.detail || e?.message || "Something went wrong"; + setError(message); } finally { setBusy(false) } @@ -94,7 +100,8 @@ export default function NewAnalysis() { return (
- + {error && (
)} + {/* Step 1 — Analysis Type */}
diff --git a/frontend/src/pages/Upload.tsx b/frontend/src/pages/Upload.tsx index 5107689..f4c89af 100644 --- a/frontend/src/pages/Upload.tsx +++ b/frontend/src/pages/Upload.tsx @@ -8,6 +8,7 @@ import { MapBBoxPicker } from '../components/Map/MapBBoxPicker' import { ErrorBoundary } from '../components/ui/ErrorBoundary' import { useToast } from '../contexts/ToastContext' import { useApp } from '../contexts/AppContext' +import { ApiError } from '../components/ui/ApiError' const ACCEPTED = ['.tif', '.tiff', '.geotiff', '.nc', '.hdf5'] const MAX_MB = 500 @@ -31,6 +32,7 @@ export default function Upload() { const [startDate, setStartDate] = useState('') const [endDate, setEndDate] = useState('') const [busy, setBusy] = useState(false) + const [error, setError] = useState(null) const [uploadProgress, setUploadProgress] = useState(null) const fileInputRef = useRef(null) @@ -75,9 +77,10 @@ export default function Upload() { }) setFile(null) setUploadProgress(null) - } catch (e) { - showToast('error', String(e)) - setUploadProgress(null) + } catch (e:any) { + const message = e?.response?.data?.detail || e?.message || "Upload failed"; + setError(message); + setUploadProgress(null); } finally { setBusy(false) } @@ -85,7 +88,7 @@ export default function Upload() { return (
- + {error && ()} {/* Drop Zone */}
{ e.preventDefault(); setDragging(true) }} From bdfc0b36f951c5c17f517178af5ef5d64236ece9 Mon Sep 17 00:00:00 2001 From: Garvit Sharma Date: Wed, 29 Apr 2026 15:26:44 +0530 Subject: [PATCH 5/6] fix(frontend): remove unused import and restore ApiError styles --- frontend/src/components/ui/ApiError.tsx | 24 ++++++++++++++---------- frontend/src/pages/NewAnalysis.tsx | 4 ++-- frontend/src/pages/Upload.tsx | 3 ++- 3 files changed, 18 insertions(+), 13 deletions(-) diff --git a/frontend/src/components/ui/ApiError.tsx b/frontend/src/components/ui/ApiError.tsx index 93021f6..3aca085 100644 --- a/frontend/src/components/ui/ApiError.tsx +++ b/frontend/src/components/ui/ApiError.tsx @@ -1,24 +1,28 @@ import { AlertCircle, X } from "lucide-react"; -import { useState } from "react"; + interface ApiErrorProps { - message: string; + message: string | null; + onDismiss: () => void; } -export function ApiError({ message }: ApiErrorProps) { - const [visible, setVisible] = useState(true); - - if (!visible) return null; +export function ApiError({ message, onDismiss }: ApiErrorProps) { + if (!message) return null; return ( -
+
-

{message}

+ +

{message}

-
); diff --git a/frontend/src/pages/NewAnalysis.tsx b/frontend/src/pages/NewAnalysis.tsx index 7fc2fb3..bb23acf 100644 --- a/frontend/src/pages/NewAnalysis.tsx +++ b/frontend/src/pages/NewAnalysis.tsx @@ -64,7 +64,7 @@ export default function NewAnalysis() { return } - setBusy(true) + setResultRun(null) setResultPayload(null) @@ -100,7 +100,7 @@ export default function NewAnalysis() { return (
- {error && (
)} + setError(null)} /> {/* Step 1 — Analysis Type */}
diff --git a/frontend/src/pages/Upload.tsx b/frontend/src/pages/Upload.tsx index f4c89af..7ba2be5 100644 --- a/frontend/src/pages/Upload.tsx +++ b/frontend/src/pages/Upload.tsx @@ -59,6 +59,7 @@ export default function Upload() { const handleUpload = async () => { if (!file) return setBusy(true) + setError(null); setUploadProgress(0) try { @@ -88,7 +89,7 @@ export default function Upload() { return (
- {error && ()} + setError(null)} /> {/* Drop Zone */}
{ e.preventDefault(); setDragging(true) }} From 441601ef1862474f80b0edac43d1bd2b5b1b5933 Mon Sep 17 00:00:00 2001 From: Garvit Sharma Date: Mon, 18 May 2026 12:12:52 +0530 Subject: [PATCH 6/6] fix(frontend): address PR review feedback --- frontend/src/pages/NewAnalysis.tsx | 9 +++++++-- frontend/src/pages/Upload.tsx | 6 +++++- 2 files changed, 12 insertions(+), 3 deletions(-) diff --git a/frontend/src/pages/NewAnalysis.tsx b/frontend/src/pages/NewAnalysis.tsx index bb23acf..64fa897 100644 --- a/frontend/src/pages/NewAnalysis.tsx +++ b/frontend/src/pages/NewAnalysis.tsx @@ -91,8 +91,13 @@ export default function NewAnalysis() { onClick: () => navigate('/runs'), }) } catch (e:any) { - const message = e?.response?.data?.detail || e?.message || "Something went wrong"; - setError(message); + const message = + e?.response?.data?.detail || + e?.response?.data?.message || + e?.message || + 'Prediction failed' + setError(message) + showToast('error', message) } finally { setBusy(false) } diff --git a/frontend/src/pages/Upload.tsx b/frontend/src/pages/Upload.tsx index 7ba2be5..025ec17 100644 --- a/frontend/src/pages/Upload.tsx +++ b/frontend/src/pages/Upload.tsx @@ -79,7 +79,11 @@ export default function Upload() { setFile(null) setUploadProgress(null) } catch (e:any) { - const message = e?.response?.data?.detail || e?.message || "Upload failed"; + const message = + e?.response?.data?.detail || + e?.response?.data?.message || + e?.message || + 'Upload failed' setError(message); setUploadProgress(null); } finally {