Add core Tracer/RunContext types and LlmTool base class

src/core/llm/LlmTool.ts

@@ -0,0 +1,59 @@
+import type { PromptService } from '../langfuse/PromptService';
+import type { ChatMessage, LlmClient } from './LlmClient';
+import type { RunContext } from './RunContext';
+
+export abstract class LlmTool<TInput, TOutput> {
+  protected abstract readonly promptName: string;
+
+  constructor(
+    protected readonly promptService: PromptService,
+    protected readonly llmClient: LlmClient
+  ) {}
+
+  protected abstract buildVariables(input: TInput, ctx: RunContext): Record<string, unknown>;
+
+  protected async preProcess(input: TInput, _ctx: RunContext): Promise<TInput> {
+    return input;
+  }
+
+  protected async postProcess(output: TOutput, _input: TInput, _ctx: RunContext): Promise<TOutput> {
+    return output;
+  }
+
+  protected abstract parseOutput(raw: string, ctx: RunContext): TOutput;
+
+  async runAsync(input: TInput, ctx: RunContext): Promise<TOutput> {
+    const processedInput = await this.preProcess(input, ctx);
+    const variables = this.buildVariables(processedInput, ctx);
+    const compiled = await this.promptService.getCompiled(this.promptName, variables);
+
+    const model = String(compiled.config.model ?? 'gpt-4o-mini');
+    const temperature =
+      typeof compiled.config.temperature === 'number' ? compiled.config.temperature : undefined;
+    const maxTokens =
+      typeof compiled.config.maxTokens === 'number' ? compiled.config.maxTokens : undefined;
+
+    const messages: ChatMessage[] = compiled.messages;
+    const generation = ctx.trace.startGeneration({
+      name: this.promptName,
+      model,
+      input: messages,
+      metadata: { promptVersion: compiled.version },
+    });
+
+    let raw: string;
+    try {
+      const result = await this.llmClient.chat(messages, { model, temperature, maxTokens });
+      raw = result.content;
+      generation.end({ output: raw, usage: result.usage });
+    } catch (err) {
+      generation.end({ output: null, metadata: { error: String(err) } });
+      throw err;
+    }
+
+    const parsed = this.parseOutput(raw, ctx);
+    const output = await this.postProcess(parsed, processedInput, ctx);
+    ctx.logger.info({ tool: this.promptName }, 'llm tool completed');
+    return output;
+  }
+}