f706b3b982
- Add Ollama client library (ollama npm package) - Create LlmService for chat completion and embeddings - Support streaming responses via Server-Sent Events - Add configuration via env vars (OLLAMA_HOST, OLLAMA_TIMEOUT) - Create endpoints: GET /llm/health, GET /llm/models, POST /llm/chat, POST /llm/embed - Replace old OllamaModule with new LlmModule - Add comprehensive tests with >85% coverage Closes #21
8 lines
983 B
TypeScript
8 lines
983 B
TypeScript
import { IsArray, IsString, IsOptional, IsBoolean, IsNumber, ValidateNested, IsIn } from "class-validator";
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import { Type } from "class-transformer";
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export type ChatRole = "system" | "user" | "assistant";
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export class ChatMessageDto { @IsString() @IsIn(["system", "user", "assistant"]) role!: ChatRole; @IsString() content!: string; }
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export class ChatRequestDto { @IsString() model!: string; @IsArray() @ValidateNested({ each: true }) @Type(() => ChatMessageDto) messages!: ChatMessageDto[]; @IsOptional() @IsBoolean() stream?: boolean; @IsOptional() @IsNumber() temperature?: number; @IsOptional() @IsNumber() maxTokens?: number; @IsOptional() @IsString() systemPrompt?: string; }
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export interface ChatResponseDto { model: string; message: { role: ChatRole; content: string }; done: boolean; totalDuration?: number; promptEvalCount?: number; evalCount?: number; }
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export interface ChatStreamChunkDto { model: string; message: { role: ChatRole; content: string }; done: boolean; }
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