fix: workflow inference chain — surface llama-server errors, user-turn-last, bundle-relative prompts
- LlamaCppInferenceProvider: check HTTP status and surface the real error body instead of masking it as a ChatCompletionResponse deserialization failure - PromptRenderer: render the live conversation layer (L1) last so the user turn is the final message (fixes Qwen 'No user query found' 500 when L3 recall is present) - TomlWorkflowLoader: resolve stage prompts relative to the workflow file's own dir (bundle), CWD-independent; config-dir fallback for globals - SessionOrchestrator: hard-fail a stage whose declared prompt can't resolve (was a silent user-less request) - move healthcheck prompts next to the example workflow (examples/workflows/prompts/)
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@@ -12,6 +12,14 @@ data class ChatMessage(
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)
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object PromptRenderer {
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// L1 (live conversation, ends with the current user turn) must render last so
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// the model template sees the user query as the final message. Background/memory
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// layers (L2, L3, L4) are injected before it.
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private val nonL0RenderOrder: Comparator<ContextLayer> = Comparator { a, b ->
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val priority = { layer: ContextLayer -> if (layer == ContextLayer.L1) Int.MAX_VALUE else layer.ordinal }
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priority(a) - priority(b)
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}
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fun render(contextPack: ContextPack): List<ChatMessage> {
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val sorted = contextPack.layers.entries.sortedBy { it.key.ordinal }
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val systemContent = sorted
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@@ -19,19 +27,22 @@ object PromptRenderer {
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.flatMap { it.value }
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.joinToString("\n\n") { it.content }
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.takeIf { it.isNotBlank() }
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val conversationMessages = sorted.filter { it.key != ContextLayer.L0 }.flatMap { (_, entries) ->
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entries.map { entry ->
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ChatMessage(
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role = when (entry.role) {
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EntryRole.SYSTEM -> "system"
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EntryRole.ASSISTANT -> "assistant"
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EntryRole.TOOL -> "tool"
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EntryRole.USER -> "user"
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},
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content = entry.content,
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)
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val conversationMessages = contextPack.layers.entries
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.filter { it.key != ContextLayer.L0 }
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.sortedWith(Comparator.comparing({ it.key }, nonL0RenderOrder))
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.flatMap { (_, entries) ->
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entries.map { entry ->
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ChatMessage(
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role = when (entry.role) {
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EntryRole.SYSTEM -> "system"
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EntryRole.ASSISTANT -> "assistant"
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EntryRole.TOOL -> "tool"
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EntryRole.USER -> "user"
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},
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content = entry.content,
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)
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}
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}
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}
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val messages = buildList {
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systemContent?.let { add(ChatMessage("system", it)) }
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addAll(conversationMessages)
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+6
-4
@@ -222,7 +222,7 @@ abstract class SessionOrchestrator(
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} ?: emptyList()
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val promptEntries = stageConfig.metadata["prompt"]
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?.let { path ->
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runCatching { promptResolver.resolve(path) }
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val resolvedText = runCatching { promptResolver.resolve(path) }
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.onFailure {
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log.error(
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"[SessionOrchestrator] stage=${stageId.value}: " +
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@@ -230,9 +230,11 @@ abstract class SessionOrchestrator(
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)
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}
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.getOrNull()
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}
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?.takeIf { it.isNotBlank() }
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?.let { text ->
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val text = resolvedText?.takeIf { it.isNotBlank() }
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?: error(
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"[SessionOrchestrator] stage=${stageId.value}: " +
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"declared prompt '$path' could not be resolved",
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)
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listOf(
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ContextEntry(
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id = ContextEntryId(UUID.randomUUID().toString()),
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+9
-3
@@ -21,6 +21,7 @@ import io.ktor.client.request.accept
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import io.ktor.client.request.get
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import io.ktor.client.request.post
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import io.ktor.client.request.setBody
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import io.ktor.client.statement.bodyAsText
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import io.ktor.http.ContentType
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import io.ktor.http.contentType
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import io.ktor.serialization.kotlinx.json.json
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@@ -106,11 +107,16 @@ class LlamaCppInferenceProvider(
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val encoded = json.encodeToString(body)
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log.debug("sending request to llm: {}", encoded)
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val response = httpClient.post("$baseUrl/v1/chat/completions") {
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val httpResponse = httpClient.post("$baseUrl/v1/chat/completions") {
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contentType(ContentType.Application.Json)
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accept(ContentType.Application.Json)
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setBody(encoded)
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}.body<ChatCompletionResponse>()
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}
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if (httpResponse.status.value !in 200..299) {
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val errorBody = httpResponse.bodyAsText()
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error("llama-server returned ${httpResponse.status.value} ${httpResponse.status.description}: $errorBody")
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}
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val response = httpResponse.body<ChatCompletionResponse>()
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log.debug("got response from llm: {}", response)
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@@ -146,4 +152,4 @@ class LlamaCppInferenceProvider(
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}
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override fun capabilities(): Set<CapabilityScore> = descriptor.capabilities
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}
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}
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+12
-4
@@ -15,6 +15,7 @@ import com.fasterxml.jackson.dataformat.toml.TomlMapper
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import com.fasterxml.jackson.module.kotlin.kotlinModule
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import com.fasterxml.jackson.module.kotlin.readValue
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import java.nio.file.Path
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import kotlin.io.path.exists
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import kotlin.io.path.readText
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private data class WorkflowFile(
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@@ -67,10 +68,17 @@ class TomlWorkflowLoader(
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val raw = path.readText()
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val file = runCatching { mapper.readValue<WorkflowFile>(raw) }
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.getOrElse { throw WorkflowValidationException("Failed to parse workflow TOML: ${it.message}") }
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return file.toWorkflowGraph()
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return file.toWorkflowGraph(path.parent)
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}
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private fun WorkflowFile.toWorkflowGraph(): WorkflowGraph {
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private fun resolvePromptPath(raw: String, workflowDir: Path?): String {
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val p = Path.of(raw)
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if (p.isAbsolute) return raw
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val candidate = workflowDir?.resolve(raw)
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return if (candidate != null && candidate.exists()) candidate.toString() else raw
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}
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private fun WorkflowFile.toWorkflowGraph(workflowDir: Path?): WorkflowGraph {
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val startId = StageId(start)
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val stageMap = stages.associate { s ->
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StageId(s.id) to StageConfig(
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@@ -84,8 +92,8 @@ class TomlWorkflowLoader(
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tokenBudget = s.tokenBudget,
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maxRetries = s.maxRetries,
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metadata = buildMap {
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s.prompt?.let { put("prompt", it) }
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s.systemPrompt?.let { put("systemPrompt", it) }
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s.prompt?.let { put("prompt", resolvePromptPath(it, workflowDir)) }
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s.systemPrompt?.let { put("systemPrompt", resolvePromptPath(it, workflowDir)) }
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},
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)
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}
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