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https://github.com/trustgraph-ai/trustgraph.git
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Advance TS port Effect workbench
This commit is contained in:
elpresidank
parent
92dae8c374
commit
3515106670
116 changed files with 12286 additions and 9584 deletions
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@ -18,6 +18,7 @@ import type { EmbeddingsRequest, EmbeddingsResponse } from "../schema/messages.j
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import { ConsumerSpec } from "../spec/consumer-spec.js";
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import { ParameterSpec } from "../spec/parameter-spec.js";
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import { ProducerSpec } from "../spec/producer-spec.js";
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import type { Spec } from "../spec/types.js";
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export interface EmbeddingsServiceShape {
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readonly embed: (
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@ -30,53 +31,55 @@ export class Embeddings extends Context.Service<Embeddings, EmbeddingsServiceSha
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"@trustgraph/base/services/embeddings-service/Embeddings",
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) {}
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const onEmbeddingsRequest = Effect.fn("EmbeddingsService.onRequest")(function* (
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msg: EmbeddingsRequest,
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properties: Record<string, string>,
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flowCtx: FlowContext<Embeddings>,
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): Effect.fn.Return<void, FlowResourceNotFoundError | MessagingDeliveryError, Embeddings> {
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const requestId = properties.id;
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if (requestId === undefined || requestId.length === 0) {
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return;
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}
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const responseProducer = yield* flowCtx.flow.producerEffect<EmbeddingsResponse>("embeddings-response");
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const embeddings = yield* Embeddings;
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const response = yield* embeddings.embed(msg.text, msg.model).pipe(
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Effect.map((vectors) => ({ vectors }) satisfies EmbeddingsResponse),
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Effect.catch((error) =>
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Effect.logError("[EmbeddingsService] Error processing request", {
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error: errorMessage(error),
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operation: error.operation,
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provider: error.provider ?? "unknown",
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}).pipe(
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Effect.as({
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vectors: [],
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error: {
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type: "embeddings-error",
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message: errorMessage(error),
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},
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} satisfies EmbeddingsResponse),
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),
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),
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);
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yield* responseProducer.send(requestId, response);
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});
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export const makeEmbeddingsSpecs = (): ReadonlyArray<Spec<Embeddings>> => [
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new ConsumerSpec<EmbeddingsRequest, FlowResourceNotFoundError | MessagingDeliveryError, Embeddings>(
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"embeddings-request",
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onEmbeddingsRequest,
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),
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new ProducerSpec<EmbeddingsResponse>("embeddings-response"),
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new ParameterSpec("model"),
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];
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export class EmbeddingsService extends FlowProcessor<Embeddings> {
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constructor(config: ProcessorConfig) {
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super(config);
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this.registerSpecification(
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new ConsumerSpec<EmbeddingsRequest, FlowResourceNotFoundError | MessagingDeliveryError, Embeddings>(
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"embeddings-request",
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this.onRequestEffect.bind(this),
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),
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);
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this.registerSpecification(new ProducerSpec<EmbeddingsResponse>("embeddings-response"));
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this.registerSpecification(new ParameterSpec("model"));
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}
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private onRequestEffect(
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msg: EmbeddingsRequest,
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properties: Record<string, string>,
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flowCtx: FlowContext<Embeddings>,
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): Effect.Effect<void, FlowResourceNotFoundError | MessagingDeliveryError, Embeddings> {
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const requestId = properties.id;
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if (requestId === undefined || requestId.length === 0) {
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return Effect.void;
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for (const spec of makeEmbeddingsSpecs()) {
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this.registerSpecification(spec);
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}
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return Effect.gen(function* () {
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const responseProducer = yield* flowCtx.flow.producerEffect<EmbeddingsResponse>("embeddings-response");
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const embeddings = yield* Embeddings;
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const response = yield* embeddings.embed(msg.text, msg.model).pipe(
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Effect.map((vectors) => ({ vectors }) satisfies EmbeddingsResponse),
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Effect.catch((error) =>
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Effect.logError("[EmbeddingsService] Error processing request", {
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error: errorMessage(error),
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operation: error.operation,
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provider: error.provider ?? "unknown",
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}).pipe(
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Effect.as({
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vectors: [],
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error: {
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type: "embeddings-error",
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message: errorMessage(error),
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},
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} satisfies EmbeddingsResponse),
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),
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),
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);
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yield* responseProducer.send(requestId, response);
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});
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}
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}
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@ -1,6 +1,15 @@
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export { LlmService } from "./llm-service.js";
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export {
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Llm,
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LlmService,
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LlmServiceError,
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makeLlmServiceShape,
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makeLlmSpecs,
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type LlmProvider,
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type LlmServiceShape,
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} from "./llm-service.js";
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export {
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Embeddings,
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EmbeddingsService,
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makeEmbeddingsSpecs,
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type EmbeddingsServiceShape,
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} from "./embeddings-service.js";
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@ -1,125 +1,247 @@
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/**
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* Base LLM service — handles message plumbing, subclasses implement the LLM call.
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* Base LLM capability contract and message-bus adapter.
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*
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* Python reference: trustgraph-base/trustgraph/base/llm_service.py
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*/
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import {FlowProcessor} from "../processor/index.js";
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import { Context, Effect } from "effect";
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import * as S from "effect/Schema";
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import {
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ConsumerSpec, ProducerSpec,
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ParameterSpec
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} from "../spec/index.js";
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import type {ProcessorConfig} from "../processor/index.js";
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import type {FlowContext} from "../messaging/consumer.js";
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errorMessage,
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type FlowResourceNotFoundError,
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type MessagingDeliveryError,
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} from "../errors.js";
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import type { FlowContext } from "../messaging/consumer.js";
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import { FlowProcessor } from "../processor/flow-processor.js";
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import type { ProcessorConfig } from "../processor/async-processor.js";
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import type {
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TextCompletionRequest,
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TextCompletionResponse,
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TextCompletionRequest,
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TextCompletionResponse,
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} from "../schema/messages.js";
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import type {LlmResult, LlmChunk} from "../schema/index.js";
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import type { LlmChunk, LlmResult } from "../schema/primitives.js";
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import { ConsumerSpec } from "../spec/consumer-spec.js";
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import { ParameterSpec } from "../spec/parameter-spec.js";
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import { ProducerSpec } from "../spec/producer-spec.js";
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import type { Spec } from "../spec/types.js";
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export abstract class LlmService extends FlowProcessor {
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protected constructor(config: ProcessorConfig) {
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super(config);
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export class LlmServiceError extends S.TaggedErrorClass<LlmServiceError>()(
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"LlmServiceError",
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{
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message: S.String,
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operation: S.String,
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},
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) {}
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this.registerSpecification(
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ConsumerSpec.fromPromise<TextCompletionRequest>(
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"text-completion-request",
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this.onRequest.bind(this),
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),
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);
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this.registerSpecification(new ProducerSpec<TextCompletionResponse>("text-completion-response"));
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this.registerSpecification(new ParameterSpec("model"));
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this.registerSpecification(new ParameterSpec("temperature"));
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}
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private async onRequest(
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msg: TextCompletionRequest,
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properties: Record<string, string>,
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flowCtx: FlowContext,
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): Promise<void> {
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const requestId = properties.id;
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if (requestId === undefined || requestId.length === 0) return;
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const responseProducer = flowCtx.flow.producer<TextCompletionResponse>("text-completion-response");
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try {
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if (msg.streaming === true && this.supportsStreaming()) {
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for await (const chunk of this.generateContentStream(
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msg.system,
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msg.prompt,
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msg.model,
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msg.temperature,
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)) {
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const response = {
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response: chunk.text,
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...(chunk.model !== undefined ? { model: chunk.model } : {}),
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...(chunk.inToken !== null ? { inToken: chunk.inToken } : {}),
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...(chunk.outToken !== null ? { outToken: chunk.outToken } : {}),
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endOfStream: chunk.isFinal,
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};
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await responseProducer.send(
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requestId,
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response
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);
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}
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} else {
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const result = await this.generateContent(
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msg.system,
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msg.prompt,
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msg.model,
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msg.temperature,
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);
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const response = {
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response: result.text,
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...(result.model !== undefined ? { model: result.model } : {}),
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...(result.inToken !== undefined ? { inToken: result.inToken } : {}),
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...(result.outToken !== undefined ? { outToken: result.outToken } : {}),
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endOfStream: true,
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};
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await responseProducer.send(
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requestId,
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response
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);
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}
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} catch (err) {
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console.error(
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`[LlmService] Error processing request:`,
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err
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);
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const message = err instanceof Error
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? err.message
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: String(err);
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await responseProducer.send(
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requestId,
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{
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response: "",
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error: {
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type: "llm-error",
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message
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},
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endOfStream: true,
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}
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);
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}
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}
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abstract generateContent(
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system: string,
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prompt: string,
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model?: string,
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temperature?: number,
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): Promise<LlmResult>;
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abstract generateContentStream(
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system: string,
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prompt: string,
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model?: string,
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temperature?: number,
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): AsyncGenerator<LlmChunk>;
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supportsStreaming(): boolean {
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return false;
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}
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export interface LlmProvider {
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readonly generateContent: (
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system: string,
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prompt: string,
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model?: string,
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temperature?: number,
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) => Promise<LlmResult>;
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readonly generateContentStream: (
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system: string,
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prompt: string,
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model?: string,
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temperature?: number,
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) => AsyncGenerator<LlmChunk>;
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readonly supportsStreaming: () => boolean;
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}
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export interface LlmServiceShape {
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readonly generateContent: (
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system: string,
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prompt: string,
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model?: string,
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temperature?: number,
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) => Effect.Effect<LlmResult, LlmServiceError>;
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readonly generateContentStream: (
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system: string,
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prompt: string,
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model?: string,
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temperature?: number,
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) => AsyncGenerator<LlmChunk>;
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readonly supportsStreaming: () => boolean;
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}
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export class Llm extends Context.Service<Llm, LlmServiceShape>()(
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"@trustgraph/base/services/llm-service/Llm",
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) {}
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const llmServiceError = (operation: string, cause: unknown) =>
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new LlmServiceError({
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operation,
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message: errorMessage(cause),
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});
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export const makeLlmServiceShape = (provider: LlmProvider): LlmServiceShape => ({
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generateContent: Effect.fn("Llm.generateContent")((
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system,
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prompt,
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model,
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temperature,
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) =>
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Effect.tryPromise({
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try: () => provider.generateContent(system, prompt, model, temperature),
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catch: (cause) => llmServiceError("generate-content", cause),
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}),
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),
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generateContentStream: (
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system,
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prompt,
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model,
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temperature,
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) => provider.generateContentStream(system, prompt, model, temperature),
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supportsStreaming: () => provider.supportsStreaming(),
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});
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type LlmHandlerError =
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| FlowResourceNotFoundError
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| MessagingDeliveryError;
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const resultToResponse = (result: LlmResult): TextCompletionResponse => ({
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response: result.text,
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model: result.model,
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inToken: result.inToken,
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outToken: result.outToken,
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endOfStream: true,
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});
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const chunkToResponse = (chunk: LlmChunk): TextCompletionResponse => ({
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response: chunk.text,
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model: chunk.model,
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...(chunk.inToken !== null ? { inToken: chunk.inToken } : {}),
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...(chunk.outToken !== null ? { outToken: chunk.outToken } : {}),
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endOfStream: chunk.isFinal,
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});
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const llmErrorResponse = (error: LlmServiceError): TextCompletionResponse => ({
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response: "",
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error: {
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type: "llm-error",
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message: error.message,
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},
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endOfStream: true,
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});
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const sendStreamingResponse = Effect.fn("LlmService.sendStreamingResponse")(function* (
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llm: LlmServiceShape,
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requestId: string,
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msg: TextCompletionRequest,
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responseProducer: {
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readonly send: (
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id: string,
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message: TextCompletionResponse,
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) => Effect.Effect<void, MessagingDeliveryError>;
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},
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) {
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const context = yield* Effect.context<never>();
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yield* Effect.tryPromise({
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try: async () => {
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for await (const chunk of llm.generateContentStream(
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msg.system,
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msg.prompt,
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msg.model,
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msg.temperature,
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)) {
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await Effect.runPromiseWith(context)(
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responseProducer.send(requestId, chunkToResponse(chunk)),
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);
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}
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},
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catch: (cause) => llmServiceError("generate-content-stream", cause),
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});
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});
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const onLlmRequest = Effect.fn("LlmService.onRequest")(function* (
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msg: TextCompletionRequest,
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properties: Record<string, string>,
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flowCtx: FlowContext<Llm>,
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): Effect.fn.Return<void, LlmHandlerError, Llm> {
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const requestId = properties.id;
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if (requestId === undefined || requestId.length === 0) return;
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const responseProducer = yield* flowCtx.flow.producerEffect<TextCompletionResponse>(
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"text-completion-response",
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);
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const llm = yield* Llm;
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if (msg.streaming === true && llm.supportsStreaming()) {
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yield* sendStreamingResponse(llm, requestId, msg, responseProducer).pipe(
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Effect.catch((error) =>
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Effect.logError("[LlmService] Error processing streaming request", {
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error: error.message,
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operation: error.operation,
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}).pipe(
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Effect.flatMap(() =>
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responseProducer.send(requestId, llmErrorResponse(error)),
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),
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),
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),
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);
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return;
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}
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const response = yield* llm.generateContent(
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msg.system,
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msg.prompt,
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msg.model,
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msg.temperature,
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).pipe(
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Effect.map(resultToResponse),
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Effect.catch((error) =>
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Effect.logError("[LlmService] Error processing request", {
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error: error.message,
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operation: error.operation,
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}).pipe(
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Effect.as(llmErrorResponse(error)),
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),
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),
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);
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yield* responseProducer.send(requestId, response);
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});
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export const makeLlmSpecs = (): ReadonlyArray<Spec<Llm>> => [
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new ConsumerSpec<TextCompletionRequest, LlmHandlerError, Llm>(
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"text-completion-request",
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onLlmRequest,
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),
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new ProducerSpec<TextCompletionResponse>("text-completion-response"),
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new ParameterSpec("model"),
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new ParameterSpec("temperature"),
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];
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export abstract class LlmService extends FlowProcessor<Llm> implements LlmProvider {
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protected constructor(config: ProcessorConfig) {
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super(config);
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for (const spec of makeLlmSpecs()) {
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this.registerSpecification(spec);
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}
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}
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override startEffect() {
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return super.startEffect().pipe(
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Effect.provideService(Llm, Llm.of(makeLlmServiceShape(this))),
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);
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}
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abstract generateContent(
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system: string,
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prompt: string,
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model?: string,
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temperature?: number,
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): Promise<LlmResult>;
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abstract generateContentStream(
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system: string,
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prompt: string,
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model?: string,
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temperature?: number,
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): AsyncGenerator<LlmChunk>;
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supportsStreaming(): boolean {
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return false;
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}
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}
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|
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