diff --git a/network-poc/frontend/src/pages/index.astro b/network-poc/frontend/src/pages/index.astro
index d59b406..49476ea 100644
--- a/network-poc/frontend/src/pages/index.astro
+++ b/network-poc/frontend/src/pages/index.astro
@@ -486,7 +486,7 @@ OUTPUT FORMAT:
// === kpnRun: lähettää promptin mallille ===
const activeStreams = {};
- async function kpnRun(model, prompt, silent) {
+ async function kpnRun(model, prompt, silent, agentOpts) {
const taskId = crypto.randomUUID();
const statusDiv = document.createElement('div');
statusDiv.className = 'terminal-line';
@@ -511,10 +511,24 @@ OUTPUT FORMAT:
statusDiv.innerHTML = ` → ${model} käsittelee...`;
+ // Rakennetaan pyyntö: agentin asetukset tai globaalit oletukset
+ const opts = agentOpts || {};
+ const payload = {
+ model,
+ prompt,
+ task_id: taskId,
+ system_prompt: opts.systemPrompt || settings.systemPrompt || undefined,
+ temperature: opts.temperature ?? settings.temperature ?? undefined,
+ top_k: opts.topK ?? settings.topK ?? undefined,
+ max_tokens: opts.maxTokens ?? settings.maxTokens ?? undefined,
+ repeat_penalty: opts.repeatPenalty ?? settings.repeatPenalty ?? undefined,
+ stop: settings.stopSequences ? settings.stopSequences.split('\\n').filter(Boolean) : undefined,
+ };
+
const res = await fetch('/api/v1/chat/completions', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
- body: JSON.stringify({ model, prompt, task_id: taskId }),
+ body: JSON.stringify(payload),
});
if (res.status === 503 && !wasmNodeStarted) {
@@ -792,7 +806,7 @@ OUTPUT FORMAT:
prompt += fileDef.instructions + '\n';
prompt += 'Adapt the example to match the project description. Import from already written files. Write ONLY the code, no explanations.';
- const code = await kpnRun(fileAgent.model, prompt);
+ const code = await kpnRun(fileAgent.model, prompt, false, fileAgent);
if (!code) {
termLog(` ✗ Keskeytyi (${fileName})`, '#f85149');
return;
@@ -817,7 +831,7 @@ OUTPUT FORMAT:
else explainStep('Uudelleentarkistus', `${tst.name} tarkistaa korjaukset.`);
const reviewPrompt = (tst.prompt ? tst.prompt+'\n\n' : '') + `Review this project:\n\n${currentCode}`;
- const review = await kpnRun(tst.model, reviewPrompt);
+ const review = await kpnRun(tst.model, reviewPrompt, false, tst);
stepN++;
// LGTM → ei korjauksia tarvita
@@ -832,7 +846,7 @@ OUTPUT FORMAT:
explainStep('Korjaus', `${tst.name} löysi ongelmia. ${cdr.name} saa palautteen ja korjaa.`);
const fixPrompt = `${cdr.prompt ? cdr.prompt+'\n\n' : ''}Fix these issues:\n${review}\n\nCurrent code:\n${currentCode}\n\nWrite ALL corrected files. Start each file with: --- filename.py ---`;
- const fixedCode = await kpnRun(cdr.model, fixPrompt);
+ const fixedCode = await kpnRun(cdr.model, fixPrompt, false, cdr);
// Parsitaan korjatut tiedostot takaisin files-objektiin
if (fixedCode) {
@@ -858,7 +872,7 @@ OUTPUT FORMAT:
highlightAgent('qa');
explainStep('Testit', `${qaAgent.name} kirjoittaa pytest-testit korjatulle koodille.`);
const qaPrompt = (qaAgent.prompt ? qaAgent.prompt+'\n\n' : '') + `Write pytest tests for this project:\n\n${updatedCode}\n\nWrite a complete test_main.py file with TestClient.`;
- const tests = await kpnRun(qaAgent.model, qaPrompt);
+ const tests = await kpnRun(qaAgent.model, qaPrompt, false, qaAgent);
if (tests) files['test_main.py'] = tests;
stepN++;
}
@@ -878,7 +892,7 @@ OUTPUT FORMAT:
`- Expose port 8000\n` +
`- CMD: uv run uvicorn main:app --host 0.0.0.0 --port 8000\n` +
`\nWrite ONLY the Dockerfile, no explanations.`;
- const dockerfile = await kpnRun(tst.model, dockerPrompt);
+ const dockerfile = await kpnRun(tst.model, dockerPrompt, false, tst);
if (dockerfile) files['Dockerfile'] = dockerfile;
stepN++;
@@ -913,7 +927,7 @@ OUTPUT FORMAT:
`## Architecture\nDescribe the project structure and design decisions.\n\n` +
`## Risk Assessment\n| Severity | Issue |\n|----------|-------|\n| ... | ... |\n\n` +
`Project code:\n${finalCode}`;
- const readme = await kpnRun(obs.model, obsPrompt);
+ const readme = await kpnRun(obs.model, obsPrompt, false, obs);
if (readme) {
files['README.md'] = readme;
// Tallennetaan raportti globaalisti jotta tarkkailija-klikkaus avaa sen
diff --git a/network-poc/hub/src/main.rs b/network-poc/hub/src/main.rs
index ac89d25..78c2217 100644
--- a/network-poc/hub/src/main.rs
+++ b/network-poc/hub/src/main.rs
@@ -1141,6 +1141,16 @@ struct ChatCompletionRequest {
task_id: String,
#[serde(default)]
max_tokens: Option,
+ #[serde(default)]
+ system_prompt: Option,
+ #[serde(default)]
+ temperature: Option,
+ #[serde(default)]
+ top_k: Option,
+ #[serde(default)]
+ repeat_penalty: Option,
+ #[serde(default)]
+ stop: Option>,
}
#[derive(serde::Serialize)]
@@ -1308,9 +1318,13 @@ async fn api_chat_completions(
"model": payload.model,
"task_id": payload.task_id,
});
- if let Some(mt) = payload.max_tokens {
- msg.as_object_mut().unwrap().insert("max_tokens".to_string(), serde_json::json!(mt));
- }
+ let obj = msg.as_object_mut().unwrap();
+ if let Some(mt) = payload.max_tokens { obj.insert("max_tokens".to_string(), serde_json::json!(mt)); }
+ if let Some(ref sp) = payload.system_prompt { obj.insert("system_prompt".to_string(), serde_json::json!(sp)); }
+ if let Some(t) = payload.temperature { obj.insert("temperature".to_string(), serde_json::json!(t)); }
+ if let Some(k) = payload.top_k { obj.insert("top_k".to_string(), serde_json::json!(k)); }
+ if let Some(rp) = payload.repeat_penalty { obj.insert("repeat_penalty".to_string(), serde_json::json!(rp)); }
+ if let Some(ref s) = payload.stop { obj.insert("stop".to_string(), serde_json::json!(s)); }
// Oneshot-kanava: solmu palauttaa tuloksen suoraan tälle pyynnölle
let (resp_tx, resp_rx) = tokio::sync::oneshot::channel::();
diff --git a/network-poc/native-node/src/inference.rs b/network-poc/native-node/src/inference.rs
index ab8f17b..8f0657e 100644
--- a/network-poc/native-node/src/inference.rs
+++ b/network-poc/native-node/src/inference.rs
@@ -1,6 +1,15 @@
use std::time::Instant;
use std::cell::RefCell;
+pub struct GenerateOptions {
+ pub max_tokens: usize,
+ pub system_prompt: Option,
+ pub temperature: Option,
+ pub top_k: Option,
+ pub repeat_penalty: Option,
+ pub stop: Option>,
+}
+
pub struct LlmEngine {
ollama_url: String,
model: RefCell,
@@ -96,25 +105,34 @@ impl LlmEngine {
}
}
- pub async fn generate(&self, prompt: &str, max_tokens: usize) -> Result {
- // System prompt tulee agentin konfiguraatiosta (frontend lähettää sen osana promptia).
- // Tässä ei yliajeta sitä — Ollama saa vain prompt-kentän.
+ pub async fn generate(&self, prompt: &str, opts: &GenerateOptions) -> Result {
let model = self.model.borrow().clone();
+ let default_stop: Vec = vec![
+ "<|im_end|>".into(), "\n###".into(), "\nExplanation".into(),
+ "\nNote:".into(), "\nPlease note".into(), "\nThis is".into(),
+ "\n```\n\n".into(), "\n// Example".into(), "\n# Example".into(),
+ ];
+
+ let mut body = serde_json::json!({
+ "model": model,
+ "prompt": prompt,
+ "stream": false,
+ "options": {
+ "num_predict": opts.max_tokens,
+ "temperature": opts.temperature.unwrap_or(0.7),
+ "top_k": opts.top_k.unwrap_or(40),
+ "repeat_penalty": opts.repeat_penalty.unwrap_or(1.15),
+ "stop": opts.stop.as_ref().unwrap_or(&default_stop),
+ }
+ });
+ if let Some(ref sp) = opts.system_prompt {
+ body.as_object_mut().unwrap().insert("system".to_string(), serde_json::json!(sp));
+ }
+
let start = Instant::now();
let resp = self.client.post(format!("{}/api/generate", self.ollama_url))
- .json(&serde_json::json!({
- "model": model,
- "prompt": prompt,
- "stream": false,
- "options": {
- "num_predict": max_tokens,
- "temperature": 0.7,
- "top_k": 40,
- "repeat_penalty": 1.15,
- "stop": ["<|im_end|>", "\n###", "\nExplanation", "\nNote:", "\nPlease note", "\nThis is", "\n```\n\n", "\n// Example", "\n# Example"]
- }
- }))
+ .json(&body)
.send()
.await
.map_err(|e| format!("Ollama generate: {}", e))?;
diff --git a/network-poc/native-node/src/main.rs b/network-poc/native-node/src/main.rs
index 39ac673..4393ad2 100644
--- a/network-poc/native-node/src/main.rs
+++ b/network-poc/native-node/src/main.rs
@@ -472,7 +472,14 @@ async fn main() {
if !prompt.is_empty() && (msg_model.starts_with("qwen-coder") || msg_model.starts_with("qwen2.5-coder") || msg_model.starts_with("phi")) {
if let Some(ref engine) = llm {
- let max_tokens = task.get("max_tokens").and_then(|v| v.as_u64()).unwrap_or(1024) as usize;
+ let gen_opts = inference::GenerateOptions {
+ max_tokens: task.get("max_tokens").and_then(|v| v.as_u64()).unwrap_or(1024) as usize,
+ system_prompt: task.get("system_prompt").and_then(|v| v.as_str()).map(|s| s.to_string()),
+ temperature: task.get("temperature").and_then(|v| v.as_f64()),
+ top_k: task.get("top_k").and_then(|v| v.as_u64()),
+ repeat_penalty: task.get("repeat_penalty").and_then(|v| v.as_f64()),
+ stop: task.get("stop").and_then(|v| v.as_array()).map(|a| a.iter().filter_map(|s| s.as_str().map(|s| s.to_string())).collect()),
+ };
let prompt_lines = prompt.lines().count();
let prompt_last: String = prompt.lines().last().unwrap_or("").chars().take(60).collect();
tracing::info!("→ task_id:{} | {}r prompti | \"{}...\"", task_id, prompt_lines, prompt_last);
@@ -480,11 +487,10 @@ async fn main() {
let mut st = tui_state.write().await;
st.cur_task_id = Some(task_id.to_string());
st.cur_prompt = Some(format!("→ {} riviä | \"{}...\"", prompt_lines, prompt_last));
- // Ei login puskemista vielä tässä! Yhdistetään se valmiin lohkoon yhdelle riville.
}
let model_name = engine.model_name();
- match engine.generate(prompt, max_tokens).await {
+ match engine.generate(prompt, &gen_opts).await {
Ok(result) => {
let tokens_sec = (result.tokens_per_sec * 10.0).round() / 10.0;
tracing::info!(
diff --git a/network-poc/node/src/lib.rs b/network-poc/node/src/lib.rs
index 1873d97..12a6363 100644
--- a/network-poc/node/src/lib.rs
+++ b/network-poc/node/src/lib.rs
@@ -368,11 +368,17 @@ pub async fn start_agent_node(hub_url: String, has_webgpu: bool, device_info_jso
let _ = ws_clone.borrow().send_with_str(&err_msg.to_string());
}
} else {
+ // Välitetään parametrit JSON-promptina coderille
+ let coder_prompt = serde_json::json!({
+ "prompt": prompt,
+ "system": task.get("system_prompt").and_then(|v| v.as_str()).unwrap_or(""),
+ "max_tokens": task.get("max_tokens").and_then(|v| v.as_u64()).unwrap_or(512),
+ }).to_string();
let use_3b = current_task == 5;
LLM_BUSY.store(true, Ordering::SeqCst);
let ws_for_async = ws_clone.clone();
wasm_bindgen_futures::spawn_local(async move {
- qwen_coder::run_coder_inference(prompt, ws_for_async, use_3b, task_id).await;
+ qwen_coder::run_coder_inference(coder_prompt, ws_for_async, use_3b, task_id).await;
LLM_BUSY.store(false, Ordering::SeqCst);
});
}