Extract shared tool batch adapter helper
This commit is contained in:
+244
-230
@@ -19,7 +19,6 @@ import {
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collectOpenAiResponseCodeInterpreterCalls,
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collectOpenAiResponseImages,
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collectOpenAiResponseText,
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executeToolBatch,
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MAX_TOOL_ROUNDS,
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OPENAI_IMAGE_PARTIALS,
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openAiResponseItemCallId,
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@@ -33,6 +32,7 @@ import {
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errorMessage,
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allToolSchemaNames
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} from "./unified-ai-runner.shared";
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import {executeToolBatchWithAdapter} from "./tool-batch-runner";
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import {bot} from "../index";
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import fs from "node:fs";
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import path from "node:path";
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@@ -87,51 +87,247 @@ export async function runOpenAi(
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try {
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for (let round = 0; round < MAX_TOOL_ROUNDS; round++) {
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const roundStartedAt = Date.now();
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aiLog("debug", "openai.round.start", {round, inputItems: responseInput.length, stream});
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const rankResult = await runToolRankStage({
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provider: AiProvider.OPENAI,
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model: config.openAiChatTarget.model,
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round,
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config,
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availableTools,
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messages,
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streamMessage,
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signal,
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});
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const filteredTools = rankResult.filteredTools;
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const requestTools = preparedDocumentRag?.vectorStoreIds.length
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? (() => {
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const tools = [...filteredTools];
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const hasFileSearch = allToolSchemaNames(tools).includes("file_search");
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if (!hasFileSearch) {
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const fileSearchTool = availableTools.find(tool => allToolSchemaNames([tool]).includes("file_search"));
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if (fileSearchTool) {
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tools.unshift(fileSearchTool);
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const roundStartedAt = Date.now();
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aiLog("debug", "openai.round.start", {round, inputItems: responseInput.length, stream});
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const rankResult = await runToolRankStage({
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provider: AiProvider.OPENAI,
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model: config.openAiChatTarget.model,
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round,
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config,
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availableTools,
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messages,
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streamMessage,
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signal,
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});
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const filteredTools = rankResult.filteredTools;
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const requestTools = preparedDocumentRag?.vectorStoreIds.length
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? (() => {
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const tools = [...filteredTools];
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const hasFileSearch = allToolSchemaNames(tools).includes("file_search");
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if (!hasFileSearch) {
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const fileSearchTool = availableTools.find(tool => allToolSchemaNames([tool]).includes("file_search"));
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if (fileSearchTool) {
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tools.unshift(fileSearchTool);
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}
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}
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return tools.length ? tools : undefined;
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})()
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: (filteredTools.length ? filteredTools : undefined);
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if (!stream) {
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const request: ResponseCreateParamsNonStreaming = {
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model: config.openAiChatTarget.model,
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input: responseInput as ResponseInputItem[],
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tools: requestTools as ResponseCreateParamsNonStreaming["tools"],
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instructions: systemPrompt,
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};
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const response = await adapter.callModel(request, () => openAi.responses.create(request, {signal})) as OpenAiResponseLike;
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const responseText = collectOpenAiResponseText(response);
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streamMessage.append(responseText);
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aiLog("debug", "openai.response.received", {
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round,
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duration: aiLogDuration(roundStartedAt),
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textChars: responseText.length,
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outputItems: response?.output?.length ?? 0,
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});
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const images = collectOpenAiResponseImages(response);
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if (images.length) {
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await showOpenAiGeneratedImage(
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streamMessage,
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sourceMessage,
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images[images.length - 1],
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`final_${round}`,
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Environment.getImageGenDoneText(config.openAiImageTarget.model),
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true,
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);
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}
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const codeInterpreterCalls = collectOpenAiResponseCodeInterpreterCalls(response);
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if (codeInterpreterCalls.length) {
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aiLog("info", "openai.code_interpreter_calls", {
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round,
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duration: aiLogDuration(roundStartedAt),
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calls: codeInterpreterCalls.map(call => ({
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id: call.id,
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status: call.status,
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containerId: call.containerId,
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codeChars: call.code?.length ?? 0,
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outputItems: call.outputs.length,
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})),
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});
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}
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const calls = adapter.extractToolCalls(response);
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aiLog(calls.length ? "info" : "success", calls.length ? "openai.tool_calls" : "openai.run.done", {
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round,
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duration: calls.length ? aiLogDuration(roundStartedAt) : aiLogDuration(runnerStartedAt),
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calls: calls.map(call => ({
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id: call.id,
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name: call.name,
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arguments: safeJsonParseObject(call.argumentsText)
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})),
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});
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if (!calls.length) return;
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const toolCalls = calls.map(call => ({
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id: call.id,
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name: call.name,
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argumentsText: call.argumentsText,
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}));
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const toolOutputs: Array<{type: "function_call_output"; call_id: string; output: string}> = [];
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const toolResults = await executeToolBatchWithAdapter({
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userId: msg.from?.id,
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toolCalls,
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streamMessage,
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toolContext,
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toolMemory,
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adapter,
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appendTargets: [toolOutputs],
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});
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const uploadFilesResult = await tryToUploadFiles(msg, toolResults);
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if (uploadFilesResult.found) {
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if (!uploadFilesResult.uploaded) {
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const old = toolOutputs[uploadFilesResult.toolIndex];
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const callId = old?.call_id;
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if (uploadFilesResult.toolIndex >= 0) {
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delete toolOutputs[uploadFilesResult.toolIndex];
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}
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if (callId) {
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toolOutputs.push({
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type: "function_call_output" as const,
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call_id: callId,
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output: "Error: " + uploadFilesResult.error
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});
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}
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}
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}
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return tools.length ? tools : undefined;
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})()
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: (filteredTools.length ? filteredTools : undefined);
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if (!stream) {
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const request: ResponseCreateParamsNonStreaming = {
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responseInput = [...responseInput, ...(response.output ?? []), ...toolOutputs];
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continue;
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}
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let completedResponse: OpenAiResponseLike | null = null;
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const request: ResponseCreateParamsStreaming = {
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model: config.openAiChatTarget.model,
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input: responseInput as ResponseInputItem[],
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tools: requestTools as ResponseCreateParamsNonStreaming["tools"],
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instructions: systemPrompt,
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stream: true,
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tools: requestTools as ResponseCreateParamsStreaming["tools"],
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parallel_tool_calls: true,
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instructions: systemPrompt
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};
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const response = await adapter.callModel(request, () => openAi.responses.create(request, {signal})) as OpenAiResponseLike;
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const response = await adapter.callModel(request, () => openAi.responses.create(request, {signal})) as AsyncIterableStream<ResponseStreamEvent>;
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const responseText = collectOpenAiResponseText(response);
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streamMessage.append(responseText);
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aiLog("debug", "openai.response.received", {
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aiLog("debug", "openai.stream.open", {round});
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let localToolCalls: ToolCallData[] = [];
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for await (const event of response) {
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if (signal.aborted) throw new Error("Aborted");
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switch (event.type) {
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case "response.output_text.delta":
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streamMessage.append(adapter.extractTextDelta(event));
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break;
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case "response.image_generation_call.in_progress":
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streamMessage.setStatus(Environment.startingImageGenText);
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await streamMessage.flush();
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break;
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case "response.image_generation_call.generating":
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streamMessage.setStatus(Environment.imageGenText);
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await streamMessage.flush();
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break;
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case "response.image_generation_call.partial_image": {
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const iteration = (event.partial_image_index ?? 0) + 1;
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await showOpenAiGeneratedImage(
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streamMessage,
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sourceMessage,
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event.partial_image_b64,
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`partial_${round}_${iteration}`,
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Environment.getPartialImageGenText(iteration, OPENAI_IMAGE_PARTIALS),
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false,
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);
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break;
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}
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case "response.image_generation_call.completed":
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streamMessage.setStatus(Environment.finalizingImageGenText);
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await streamMessage.flush();
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break;
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case "response.file_search_call.in_progress":
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case "response.file_search_call.searching":
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streamMessage.setStatus(Environment.getUseToolText(["file_search"]));
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await streamMessage.flush();
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break;
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case "response.file_search_call.completed":
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streamMessage.clearStatus();
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await streamMessage.flush();
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break;
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case "response.code_interpreter_call.in_progress":
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case "response.code_interpreter_call.interpreting":
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streamMessage.setStatus(Environment.getUseToolText(["code_interpreter"]));
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await streamMessage.flush();
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break;
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case "response.code_interpreter_call.completed":
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streamMessage.clearStatus();
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await streamMessage.flush();
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break;
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case "response.code_interpreter_call_code.delta":
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case "response.code_interpreter_call_code.done":
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break;
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case "response.output_item.added":
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{
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const streamedCalls = adapter.extractStreamingToolCalls(event);
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if (streamedCalls.length) {
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localToolCalls.push(...streamedCalls);
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}
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aiLog("info", "openai.stream.tool_call.added", {
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round,
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toolCalls: localToolCalls.map(aiLogToolCall)
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});
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streamMessage.setStatus(Environment.getUseToolText(localToolCalls));
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await streamMessage.flush();
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}
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break;
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case "response.output_item.done":
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if (event.item.type === "function_call" && event.item.name) {
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const item = event.item as OpenAiResponseOutputItem & { id?: string };
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const itemId = openAiResponseItemCallId(item);
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const index = localToolCalls.findIndex(c => c.id === itemId);
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if (index !== -1) {
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localToolCalls.splice(index, 1);
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if (localToolCalls.length === 0) {
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streamMessage.clearStatus();
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} else {
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streamMessage.setStatus(Environment.getUseToolText(localToolCalls));
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}
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await streamMessage.flush();
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}
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}
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break;
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case "response.function_call_arguments.delta":
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break;
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case "response.function_call_arguments.done":
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break;
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case "response.completed":
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completedResponse = event.response as OpenAiResponseLike;
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break;
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case "response.failed":
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throw new Error(event.response?.error?.message ?? "OpenAI response failed");
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case "error":
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throw new Error(event.message ?? event?.message ?? "OpenAI stream error");
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}
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}
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if (!completedResponse) throw new Error("OpenAI did not return the final response.completed event.");
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aiLog("debug", "openai.stream.completed", {
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round,
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duration: aiLogDuration(roundStartedAt),
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textChars: responseText.length,
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outputItems: response?.output?.length ?? 0,
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outputItems: completedResponse?.output?.length ?? 0,
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});
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const images = collectOpenAiResponseImages(response);
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const images = collectOpenAiResponseImages(completedResponse);
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if (images.length) {
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await showOpenAiGeneratedImage(
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streamMessage,
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@@ -143,7 +339,7 @@ export async function runOpenAi(
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);
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}
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const codeInterpreterCalls = collectOpenAiResponseCodeInterpreterCalls(response);
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const codeInterpreterCalls = collectOpenAiResponseCodeInterpreterCalls(completedResponse);
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if (codeInterpreterCalls.length) {
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aiLog("info", "openai.code_interpreter_calls", {
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round,
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@@ -158,7 +354,7 @@ export async function runOpenAi(
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});
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}
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const calls = adapter.extractToolCalls(response);
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const calls = adapter.extractToolCalls(completedResponse);
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aiLog(calls.length ? "info" : "success", calls.length ? "openai.tool_calls" : "openai.run.done", {
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round,
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duration: calls.length ? aiLogDuration(roundStartedAt) : aiLogDuration(runnerStartedAt),
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@@ -175,9 +371,16 @@ export async function runOpenAi(
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name: call.name,
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argumentsText: call.argumentsText,
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}));
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const toolResults = await executeToolBatch(msg.from?.id, toolCalls, streamMessage, toolContext, toolMemory);
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const toolOutputs: Array<{type: "function_call_output"; call_id: string; output: string}> = [];
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adapter.appendToolResults(toolOutputs, calls, toolResults);
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const toolResults = await executeToolBatchWithAdapter({
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userId: msg.from?.id,
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toolCalls,
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streamMessage,
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toolContext,
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toolMemory,
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adapter,
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appendTargets: [toolOutputs],
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});
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const uploadFilesResult = await tryToUploadFiles(msg, toolResults);
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if (uploadFilesResult.found) {
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@@ -197,196 +400,7 @@ export async function runOpenAi(
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}
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}
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responseInput = [...responseInput, ...(response.output ?? []), ...toolOutputs];
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continue;
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}
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let completedResponse: OpenAiResponseLike | null = null;
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const request: ResponseCreateParamsStreaming = {
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model: config.openAiChatTarget.model,
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input: responseInput as ResponseInputItem[],
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stream: true,
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tools: requestTools as ResponseCreateParamsStreaming["tools"],
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parallel_tool_calls: true,
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instructions: systemPrompt
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};
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const response = await adapter.callModel(request, () => openAi.responses.create(request, {signal})) as AsyncIterableStream<ResponseStreamEvent>;
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aiLog("debug", "openai.stream.open", {round});
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|
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let localToolCalls: ToolCallData[] = [];
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for await (const event of response) {
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if (signal.aborted) throw new Error("Aborted");
|
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|
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switch (event.type) {
|
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case "response.output_text.delta":
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streamMessage.append(adapter.extractTextDelta(event));
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break;
|
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case "response.image_generation_call.in_progress":
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streamMessage.setStatus(Environment.startingImageGenText);
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await streamMessage.flush();
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break;
|
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case "response.image_generation_call.generating":
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streamMessage.setStatus(Environment.imageGenText);
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await streamMessage.flush();
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break;
|
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case "response.image_generation_call.partial_image": {
|
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const iteration = (event.partial_image_index ?? 0) + 1;
|
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await showOpenAiGeneratedImage(
|
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streamMessage,
|
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sourceMessage,
|
||||
event.partial_image_b64,
|
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`partial_${round}_${iteration}`,
|
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Environment.getPartialImageGenText(iteration, OPENAI_IMAGE_PARTIALS),
|
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false,
|
||||
);
|
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break;
|
||||
}
|
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case "response.image_generation_call.completed":
|
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streamMessage.setStatus(Environment.finalizingImageGenText);
|
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await streamMessage.flush();
|
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break;
|
||||
case "response.file_search_call.in_progress":
|
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case "response.file_search_call.searching":
|
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streamMessage.setStatus(Environment.getUseToolText(["file_search"]));
|
||||
await streamMessage.flush();
|
||||
break;
|
||||
case "response.file_search_call.completed":
|
||||
streamMessage.clearStatus();
|
||||
await streamMessage.flush();
|
||||
break;
|
||||
case "response.code_interpreter_call.in_progress":
|
||||
case "response.code_interpreter_call.interpreting":
|
||||
streamMessage.setStatus(Environment.getUseToolText(["code_interpreter"]));
|
||||
await streamMessage.flush();
|
||||
break;
|
||||
case "response.code_interpreter_call.completed":
|
||||
streamMessage.clearStatus();
|
||||
await streamMessage.flush();
|
||||
break;
|
||||
case "response.code_interpreter_call_code.delta":
|
||||
case "response.code_interpreter_call_code.done":
|
||||
break;
|
||||
case "response.output_item.added":
|
||||
{
|
||||
const streamedCalls = adapter.extractStreamingToolCalls(event);
|
||||
if (streamedCalls.length) {
|
||||
localToolCalls.push(...streamedCalls);
|
||||
}
|
||||
aiLog("info", "openai.stream.tool_call.added", {
|
||||
round,
|
||||
toolCalls: localToolCalls.map(aiLogToolCall)
|
||||
});
|
||||
streamMessage.setStatus(Environment.getUseToolText(localToolCalls));
|
||||
await streamMessage.flush();
|
||||
}
|
||||
break;
|
||||
case "response.output_item.done":
|
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if (event.item.type === "function_call" && event.item.name) {
|
||||
const item = event.item as OpenAiResponseOutputItem & { id?: string };
|
||||
const itemId = openAiResponseItemCallId(item);
|
||||
const index = localToolCalls.findIndex(c => c.id === itemId);
|
||||
if (index !== -1) {
|
||||
localToolCalls.splice(index, 1);
|
||||
if (localToolCalls.length === 0) {
|
||||
streamMessage.clearStatus();
|
||||
} else {
|
||||
streamMessage.setStatus(Environment.getUseToolText(localToolCalls));
|
||||
}
|
||||
await streamMessage.flush();
|
||||
}
|
||||
}
|
||||
break;
|
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case "response.function_call_arguments.delta":
|
||||
break;
|
||||
case "response.function_call_arguments.done":
|
||||
break;
|
||||
|
||||
case "response.completed":
|
||||
completedResponse = event.response as OpenAiResponseLike;
|
||||
break;
|
||||
case "response.failed":
|
||||
throw new Error(event.response?.error?.message ?? "OpenAI response failed");
|
||||
case "error":
|
||||
throw new Error(event.message ?? event?.message ?? "OpenAI stream error");
|
||||
}
|
||||
}
|
||||
|
||||
if (!completedResponse) throw new Error("OpenAI did not return the final response.completed event.");
|
||||
|
||||
aiLog("debug", "openai.stream.completed", {
|
||||
round,
|
||||
duration: aiLogDuration(roundStartedAt),
|
||||
outputItems: completedResponse?.output?.length ?? 0,
|
||||
});
|
||||
|
||||
const images = collectOpenAiResponseImages(completedResponse);
|
||||
if (images.length) {
|
||||
await showOpenAiGeneratedImage(
|
||||
streamMessage,
|
||||
sourceMessage,
|
||||
images[images.length - 1],
|
||||
`final_${round}`,
|
||||
Environment.getImageGenDoneText(config.openAiImageTarget.model),
|
||||
true,
|
||||
);
|
||||
}
|
||||
|
||||
const codeInterpreterCalls = collectOpenAiResponseCodeInterpreterCalls(completedResponse);
|
||||
if (codeInterpreterCalls.length) {
|
||||
aiLog("info", "openai.code_interpreter_calls", {
|
||||
round,
|
||||
duration: aiLogDuration(roundStartedAt),
|
||||
calls: codeInterpreterCalls.map(call => ({
|
||||
id: call.id,
|
||||
status: call.status,
|
||||
containerId: call.containerId,
|
||||
codeChars: call.code?.length ?? 0,
|
||||
outputItems: call.outputs.length,
|
||||
})),
|
||||
});
|
||||
}
|
||||
|
||||
const calls = adapter.extractToolCalls(completedResponse);
|
||||
aiLog(calls.length ? "info" : "success", calls.length ? "openai.tool_calls" : "openai.run.done", {
|
||||
round,
|
||||
duration: calls.length ? aiLogDuration(roundStartedAt) : aiLogDuration(runnerStartedAt),
|
||||
calls: calls.map(call => ({
|
||||
id: call.id,
|
||||
name: call.name,
|
||||
arguments: safeJsonParseObject(call.argumentsText)
|
||||
})),
|
||||
});
|
||||
if (!calls.length) return;
|
||||
|
||||
const toolCalls = calls.map(call => ({
|
||||
id: call.id,
|
||||
name: call.name,
|
||||
argumentsText: call.argumentsText,
|
||||
}));
|
||||
const toolResults = await executeToolBatch(msg.from?.id, toolCalls, streamMessage, toolContext, toolMemory);
|
||||
const toolOutputs: Array<{type: "function_call_output"; call_id: string; output: string}> = [];
|
||||
adapter.appendToolResults(toolOutputs, calls, toolResults);
|
||||
|
||||
const uploadFilesResult = await tryToUploadFiles(msg, toolResults);
|
||||
if (uploadFilesResult.found) {
|
||||
if (!uploadFilesResult.uploaded) {
|
||||
const old = toolOutputs[uploadFilesResult.toolIndex];
|
||||
const callId = old?.call_id;
|
||||
if (uploadFilesResult.toolIndex >= 0) {
|
||||
delete toolOutputs[uploadFilesResult.toolIndex];
|
||||
}
|
||||
if (callId) {
|
||||
toolOutputs.push({
|
||||
type: "function_call_output" as const,
|
||||
call_id: callId,
|
||||
output: "Error: " + uploadFilesResult.error
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
responseInput = [...responseInput, ...(completedResponse.output ?? []), ...toolOutputs];
|
||||
responseInput = [...responseInput, ...(completedResponse.output ?? []), ...toolOutputs];
|
||||
}
|
||||
} finally {
|
||||
if (ownsDocumentRag) {
|
||||
|
||||
Reference in New Issue
Block a user