Synthetic Sciences Releases OpenScience: An Open-Source, Model-Agnostic AI Workbench for Machine Learning, Biology, Physics, and Chemistry Research

npm set up -g @synsci/openscience
openscience

# Bring your individual key; requests go straight to the supplier
export ANTHROPIC_API_KEY=sk-ant-...
openscience

# Or open a particular venture listing
openscience ~/code/my-project

Run analysis loop</button>
<button class=”os-btn os-reset” id=”os-reset”>Reset</button>
</div>
</div>

<div class=”os-stages” id=”os-stages”></div>

<div class=”os-main”>
<div class=”os-console”>
<div class=”os-console-bar”>
<div class=”os-dot” type=”background:#e05a5a”></div>
<div class=”os-dot” type=”background:#e0b400″></div>
<div class=”os-dot” type=”background:#76B900″></div>
<span class=”os-mono”>openscience · agent runtime</span>
</div>
<div class=”os-log” id=”os-log”>
<div class=”os-idle”>Choose a mannequin and a objective, then run the loop. The agent streams every step right here.</div>
</div>
</div>

<div class=”os-side”>
<div class=”os-card”>
<h4>Skills fired</h4>
<div id=”os-skills”><span class=”os-idle”>Idle</span></div>
</div>
<div class=”os-card”>
<h4>Databases queried</h4>
<div id=”os-dbs”><span class=”os-idle”>Idle</span></div>
</div>
<div class=”os-card”>
<h4>Inline render</h4>
<div class=”os-render” id=”os-render”><div class=”os-empty”>Output seems after the experiment step.</div></div>
</div>
</div>
</div>

<div class=”os-foot”>
<div class=”os-note”>Illustrative demo. Steps, abilities, and renders are simulated to point out the OpenScience loop. Real runs rely on the mannequin and knowledge you present.</div>
<div class=”os-mtp”>Marktechpost</div>
</div>
</div>

<script>
(operate(){
var MODELS = [
{id:”claude-opus”, label:”Claude”},
{id:”gpt-5″, label:”GPT”},
{id:”gemini”, label:”Gemini”},
{id:”glm”, label:”GLM”},
{id:”kimi”, label:”Kimi”},
{id:”deepseek”, label:”DeepSeek”},
{id:”local-ft”, label:”Local fine-tune”}
];
var STAGES = [“Literature”,”Hypothesis”,”Code”,”Experiment”,”Analysis”,”Write-up”];

var GOALS = {
ml: {
label:”ML”, agent:”ml”,
desc:”Goal: PEFT fine-tune a small mannequin and report the loss.”,
abilities:[“arxiv-search”,”peft-lora”,”trl-sft”,”eval-harness”,”figures-matplotlib”],
dbs:[“arXiv”,”OpenAlex”,”Semantic Scholar”],
lit:”Retrieved 7 arXiv papers on parameter-efficient fine-tuning.”,
hyp:”LoRA rank 16 ought to match full fine-tune inside 2% at decrease value.”,
code:”Wrote prepare.py utilizing PEFT + TRL SFTTrainer on a 1.3B base mannequin.”,
exp:”Ran 3 epochs; logged prepare/val loss per step to disk.”,
ana:”Val loss fell 2.41 -> 0.88; LoRA inside 1.6% of full fine-tune.”,
write:”Drafted a brief report with the loss curve and a strategies notice.”,
render:”loss”
},
bio: {
label:”Biology”, agent:”biology”,
desc:”Goal: examine a protein goal and suggest mutations.”,
abilities:[“uniprot-fetch”,”pdb-structure”,”structure-viewer”,”variant-scan”,”figures”],
dbs:[“UniProt”,”PDB”,”Ensembl”],
lit:”Pulled goal entry from UniProt and 4 associated buildings.”,
hyp:”A binding-pocket residue swap could increase ligand affinity.”,
code:”Loaded PDB construction; mapped conserved residues within the pocket.”,
exp:”Rendered the construction inline and scored 5 candidate mutations.”,
ana:”Two mutations improved the anticipated pocket rating; logged provenance.”,
write:”Summarized candidates with the construction determine and citations.”,
render:”protein”
},
chem: {
label:”Chemistry”, agent:”analysis”,
desc:”Goal: display screen small molecules for a goal exercise.”,
abilities:[“chembl-query”,”pubchem-fetch”,”rdkit-filter”,”admet-flags”,”figures”],
dbs:[“ChEMBL”,”PubChem”,”arXiv”],
lit:”Queried ChEMBL for recognized actives in opposition to the goal.”,
hyp:”Scaffold with a polar substituent ought to hold exercise, decrease logP.”,
code:”Wrote an RDKit filter over 1,200 candidate SMILES.”,
exp:”Applied exercise and ADMET filters; ranked the survivors.”,
ana:”Kept 38 candidates; prime scaffold plotted by exercise vs logP.”,
write:”Produced a ranked desk and an exercise plot with sources.”,
render:”molecule”
}
};

var state = { mannequin:”claude-opus”, objective:”ml”, operating:false };

var $ = operate(id){ return doc.getElementById(id); };
var modelsEl=$(“os-models”), goalsEl=$(“os-goals”), stagesEl=$(“os-stages”),
logEl=$(“os-log”), skillsEl=$(“os-skills”), dbsEl=$(“os-dbs”), renderEl=$(“os-render”),
flagEl=$(“os-flagcode”), goalDescEl=$(“os-goaldesc”), runBtn=$(“os-run”), resetBtn=$(“os-reset”);

// construct mannequin drugs
MODELS.forEach(operate(m){
var p=doc.createElement(“div”);
p.className=”os-pill”+(m.id===state.mannequin?” on”:””);
p.textContent=m.label; p.dataset.id=m.id;
p.onclick=operate(){ if(state.operating) return;
state.mannequin=m.id; syncPills(modelsEl,m.id);
flagEl.textContent=m.id; };
modelsEl.appendChild(p);
});
// construct objective drugs
Object.keys(GOALS).forEach(operate(g){
var p=doc.createElement(“div”);
p.className=”os-pill”+(g===state.objective?” on”:””);
p.textContent=GOALS[g].label; p.dataset.id=g;
p.onclick=operate(){ if(state.operating) return;
state.objective=g; syncPills(goalsEl,g); goalDescEl.textContent=GOALS[g].desc; };
goalsEl.appendChild(p);
});
// construct phases
STAGES.forEach(operate(s,i){
var d=doc.createElement(“div”); d.className=”os-stage”; d.id=”os-stg-“+i;
d.innerHTML=”<span class=’n’>0″+(i+1)+”</span>”+s; stagesEl.appendChild(d);
});
goalDescEl.textContent=GOALS[state.goal].desc;

operate syncPills(container,id){
Array.prototype.forEach.name(container.kids,operate(c){
c.classList.toggle(“on”, c.dataset.id===id); });
}

operate line(html){
if(logEl.querySelector(“.os-idle”)) logEl.innerHTML=””;
var d=doc.createElement(“div”); d.className=”os-line os-mono”; d.innerHTML=html;
logEl.appendChild(d); logEl.scrollTop=logEl.scrollHeight;
}
operate chip(container, objects, i){
if(i===0) container.innerHTML=””;
var c=doc.createElement(“span”); c.className=”os-chip”; c.textContent=objects[i];
container.appendChild(c);
setTimeout(operate(){ c.classList.add(“fireplace”); },40);
}

operate mannequinLabel(){ for(var i=0;i<MODELS.size;i++) if(MODELS[i].id===state.mannequin) return MODELS[i].label; return state.mannequin; }

operate setStage(i){
for(var ok=0;ok<STAGES.size;ok++){
var el=$(“os-stg-“+ok); el.classList.take away(“energetic”);
if(ok<i) el.classList.add(“accomplished”);
if(ok===i) el.classList.add(“energetic”);
}
}

var timers=[];
operate schedule(fn,ms){ timers.push(setTimeout(fn,ms)); }

operate run(){
if(state.operating) return;
reset(true); state.operating=true; runBtn.disabled=true;
var g=GOALS[state.goal], ml=mannequinLabel(), t=0, step=520;

schedule(operate(){ line(“<span class=’p’>openscience</span> <span class=’t’>agent=”+g.agent+” · routed to “+ml+”</span>”); },t+=120);
schedule(operate(){ setStage(0); line(“<span class=’t’>[01] literature</span> “+g.lit); chip(dbsEl,g.dbs,0); },t+=step);
schedule(operate(){ chip(dbsEl,g.dbs,1); chip(skillsEl,g.abilities,0); },t+=step);
schedule(operate(){ if(g.dbs[2]) chip(dbsEl,g.dbs,2); },t+=step);

schedule(operate(){ setStage(1); line(“<span class=’t’>[02] speculation</span> “+g.hyp); },t+=step);
schedule(operate(){ setStage(2); line(“<span class=’t’>[03] code</span> <span class=’ok’>”+g.code+”</span>”); chip(skillsEl,g.abilities,1); chip(skillsEl,g.abilities,2); },t+=step);
schedule(operate(){ setStage(3); line(“<span class=’t’>[04] experiment</span> “+g.exp); chip(skillsEl,g.abilities,3); drawRender(g.render); },t+=step);
schedule(operate(){ setStage(4); line(“<span class=’t’>[05] evaluation</span> <span class=’s’>”+g.ana+”</span>”); chip(skillsEl,g.abilities,4); },t+=step);
schedule(operate(){ setStage(5); line(“<span class=’t’>[06] write-up</span> “+g.write); },t+=step);
schedule(operate(){
setStage(6);
line(“<span class=’okay’>✓ loop full</span> <span class=’t’>· session + provenance saved to disk</span>”);
state.operating=false; runBtn.disabled=false;
},t+=step);
}

operate reset(keepSelection){
timers.forEach(clearTimeout); timers=[];
state.operating=false; runBtn.disabled=false;
logEl.innerHTML=”<div class=’os-idle’>Choose a mannequin and a objective, then run the loop. The agent streams every step right here.</div>”;
skillsEl.innerHTML=”<span class=’os-idle’>Idle</span>”;
dbsEl.innerHTML=”<span class=’os-idle’>Idle</span>”;
renderEl.innerHTML=”<div class=’os-empty’>Output seems after the experiment step.</div>”;
for(var ok=0;ok<STAGES.size;ok++){ var el=$(“os-stg-“+ok); el.classList.take away(“energetic”,”accomplished”); }
}

// —- inline SVG renders —-
operate drawRender(variety){
if(variety===”loss”) renderEl.innerHTML=svgLoss();
else if(variety===”protein”) renderEl.innerHTML=svgProtein();
else renderEl.innerHTML=svgMolecule();
}
operate svgLoss(){
var pts=”0,10 22,34 44,58 66,78 88,96 110,112 132,122 154,130 176,135 198,138 220,140″;
return “<svg viewBox=’0 0 240 160′ width=’240′>”+
“<line x1=’24’ y1=’6′ x2=’24’ y2=’150′ stroke=’#2b2f2b’/><line x1=’24’ y1=’150′ x2=’234′ y2=’150′ stroke=’#2b2f2b’/>”+
“<polyline factors='”+shift(pts)+”‘ fill=’none’ stroke=’#76B900′ stroke-width=’2.5′ stroke-linecap=’spherical’>”+
“<animate attributeName=’stroke-dasharray’ from=’0,400′ to=’400,0′ dur=’1.1s’ fill=’freeze’/></polyline>”+
“<textual content x=’30’ y=’16’ fill=’#8b968a’ font-size=’9′ font-family=’monospace’>val loss</textual content>”+
“<textual content x=’120′ y=’159′ fill=’#8b968a’ font-size=’8′ font-family=’monospace’>steps</textual content></svg>”;
}
operate shift(p){ return p.cut up(” “).map(operate(pair){ var a=pair.cut up(“,”); return (+a[0]+24)+”,”+(+a[1]+8); }).be part of(” “); }
operate svgProtein(){
var s=”<svg viewBox=’0 0 220 160′ width=’210′>”;
for(var i=0;i<22;i++){
var x=20+i*8.6, y=80+Math.sin(i*0.9)*38, r=(ipercent2? 5:4);
s+=”<circle cx='”+x.toFixed(1)+”‘ cy='”+y.toFixed(1)+”‘ r='”+r+”‘ fill='”+(ipercent3===0?’#76B900′:’#3f5a1a’)+”‘>”+
“<animate attributeName=’opacity’ from=’0′ to=’1′ start='”+(i*0.045)+”s’ dur=’0.3s’ fill=’freeze’/></circle>”;
if(i>0){ var px=20+(i-1)*8.6, py=80+Math.sin((i-1)*0.9)*38;
s+=”<line x1='”+px.toFixed(1)+”‘ y1='”+py.toFixed(1)+”‘ x2='”+x.toFixed(1)+”‘ y2='”+y.toFixed(1)+”‘ stroke=’#4f7d00′ stroke-width=’2’/>”; }
}
s+=”<textual content x=’16’ y=’150′ fill=’#8b968a’ font-size=’9′ font-family=’monospace’>PDB construction (illustrative)</textual content></svg>”;
return s;
}
operate svgMolecule(){
var cx=110,cy=78,R=34, s=”<svg viewBox=’0 0 220 160′ width=’200′>”, pts=[];
for(var i=0;i<6;i++){ var a=Math.PI/3*i-Math.PI/2; pts.push([cx+R*Math.cos(a), cy+R*Math.sin(a)]); }
for(var i=0;i<6;i++){ var p=pts[i], q=pts[(i+1)%6];
s+=”<line x1='”+p[0].toFixed(1)+”‘ y1='”+p[1].toFixed(1)+”‘ x2='”+q[0].toFixed(1)+”‘ y2='”+q[1].toFixed(1)+”‘ stroke=’#76B900’ stroke-width=’2.4’/>”; }
for(var i=0;i<6;i++){ var p=pts[i];
s+=”<circle cx='”+p[0].toFixed(1)+”‘ cy='”+p[1].toFixed(1)+”‘ r=’6′ fill=’#111′ stroke=’#76B900′ stroke-width=’2′>”+
“<animate attributeName=’r’ from=’0′ to=’6′ start='”+(i*0.06)+”s’ dur=’0.25s’ fill=’freeze’/></circle>”; }
s+=”<circle cx='”+(cx+R+18)+”‘ cy='”+cy+”‘ r=’7′ fill=’#3f5a1a’ stroke=’#76B900′ stroke-width=’1.5’/>”;
s+=”<line x1='”+(pts[1][0]).toFixed(1)+”‘ y1='”+(pts[1][1]).toFixed(1)+”‘ x2='”+(cx+R+11)+”‘ y2='”+cy+”‘ stroke=’#4f7d00′ stroke-width=’2’/>”;
s+=”<textual content x=’24’ y=’150′ fill=’#8b968a’ font-size=’9′ font-family=’monospace’>candidate scaffold (illustrative)</textual content></svg>”;
return s;
}

runBtn.onclick=run;
resetBtn.onclick=operate(){ reset(); };

// auto-resize for WordPress iframe embed
operate postHeight(){
var el=doc.getElementById(“os-demo”);
var h=(el?el.offsetHeight:doc.physique.offsetHeight)+40;
if(window.dad or mum) window.dad or mum.postMessage({osDemoHeight:h},”*”);
}
window.addEventListener(“load”,postHeight);
var mo=new MutationObserver(postHeight);
mo.observe(doc.getElementById(“os-log”),{childList:true});
mo.observe(doc.getElementById(“os-render”),{childList:true});
setInterval(postHeight,1200);
})();
</script>
</physique>
</html>
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