Extract shared tool batch adapter helper

PIPELINE_TODO.md

@@ -82,8 +82,8 @@
 - [ ] Stage `model_call` должен делать только один model request.
 - [x] Stage `model_call` должен возвращать normalized model output.
 - [x] Stage `tool_loop` должен решать, есть ли tool calls.
-- [ ] Stage `tool_loop` должен выполнять tools через общий `executeToolBatch`.
-- [ ] Stage `tool_loop` должен добавлять tool results в provider adapter.
+- [x] Stage `tool_loop` должен выполнять tools через общий `executeToolBatch`.
+- [x] Stage `tool_loop` должен добавлять tool results в provider adapter.
 - [ ] Stage `tool_loop` должен управлять max rounds.
 - [ ] Stage `tool_loop` должен сохранять tool result artifacts.
 - [x] Stage `tool_loop` должен уметь завершаться без tools как `skipped`.

src/ai/tool-batch-runner.ts

@@ -0,0 +1,28 @@
+import type {AiProviderAdapter} from "./provider-adapters.js";
+import {executeToolBatch, type ToolCallData, type ToolExecutionMemory} from "./unified-ai-runner.shared.js";
+import type {TelegramStreamMessage} from "./telegram-stream-message.js";
+import type {ToolRuntimeContext} from "./tools/runtime.js";
+
+export async function executeToolBatchWithAdapter(params: {
+    userId: number | undefined | null;
+    toolCalls: ToolCallData[];
+    streamMessage: TelegramStreamMessage;
+    toolContext: ToolRuntimeContext;
+    toolMemory: ToolExecutionMemory;
+    adapter: AiProviderAdapter;
+    appendTargets?: unknown[][];
+}): Promise<string[]> {
+    const results = await executeToolBatch(
+        params.userId,
+        params.toolCalls,
+        params.streamMessage,
+        params.toolContext,
+        params.toolMemory,
+    );
+
+    for (const target of params.appendTargets ?? []) {
+        params.adapter.appendToolResults(target, params.toolCalls, results);
+    }
+
+    return results;
+}

src/ai/unified-ai-runner.mistral.ts

@@ -9,7 +9,6 @@ import {getProviderAdapter} from "./provider-adapters";
 import {runToolRankStage} from "./tool-rank-stage";
 
 import {
-    executeToolBatch,
     MAX_TOOL_ROUNDS,
     MistralDocumentReference,
     roundStatus,
@@ -18,6 +17,7 @@ import {
     ToolCallData,
     ToolExecutionMemory
 } from "./unified-ai-runner.shared";
+import {executeToolBatchWithAdapter} from "./tool-batch-runner";
 import {Message} from "typescript-telegram-bot-api";
 
 export async function runMistral(
@@ -102,9 +102,15 @@ export async function runMistral(
                         function: {name: call.name, arguments: call.argumentsText},
                     })),
                 });
-                const toolResults = await executeToolBatch(msg.from?.id, calls, streamMessage, toolContext, toolMemory);
-                adapter.appendToolResults(messages, calls, toolResults);
-                adapter.appendToolResults(requestMessages, calls, toolResults);
+                await executeToolBatchWithAdapter({
+                    userId: msg.from?.id,
+                    toolCalls: calls,
+                    streamMessage,
+                    toolContext,
+                    toolMemory,
+                    adapter,
+                    appendTargets: [messages, requestMessages],
+                });
                 continue;
             }
 
@@ -153,9 +159,15 @@ export async function runMistral(
                 content: roundText,
                 toolCalls: calls.map(c => ({id: c.id, function: {name: c.name, arguments: c.argumentsText}}))
             });
-            const toolResults = await executeToolBatch(msg.from?.id, calls, streamMessage, toolContext, toolMemory);
-            adapter.appendToolResults(messages, calls, toolResults);
-            adapter.appendToolResults(requestMessages, calls, toolResults);
+            await executeToolBatchWithAdapter({
+                userId: msg.from?.id,
+                toolCalls: calls,
+                streamMessage,
+                toolContext,
+                toolMemory,
+                adapter,
+                appendTargets: [messages, requestMessages],
+            });
         }
     } finally {
         await adapter.finalize().catch(() => undefined);

src/ai/unified-ai-runner.ollama.ts

@@ -20,7 +20,6 @@ import {
     allToolSchemaNames,
     dedupeToolCalls,
     DEFAULT_OLLAMA_CONTEXT_SIZE,
-    executeToolBatch,
     isOllamaModelActive,
     isRecord,
     MAX_OLLAMA_CONTEXT_SIZE,
@@ -33,6 +32,7 @@ import {
     ToolCallData,
     ToolExecutionMemory
 } from "./unified-ai-runner.shared";
+import {executeToolBatchWithAdapter} from "./tool-batch-runner";
 import {getToolPrompts} from "./tools/registry";
 import {GetNoteFileResult, GetNoteFileResultSchema} from "./tools/notes";
 import {getModelCapabilities} from "./provider-model-runtime";
@@ -286,7 +286,15 @@ export async function runOllama(
                     })),
                 });
 
-                adapter.appendToolResults(messages, calls, await executeToolBatch(msg.from?.id, calls, streamMessage, toolContext, toolMemory));
+                await executeToolBatchWithAdapter({
+                    userId: msg.from?.id,
+                    toolCalls: calls,
+                    streamMessage,
+                    toolContext,
+                    toolMemory,
+                    adapter,
+                    appendTargets: [messages],
+                });
 
                 continue;
             }
@@ -396,7 +404,15 @@ export async function runOllama(
                 })),
             });
 
-            const toolResults = await executeToolBatch(msg.from?.id, calls, streamMessage, toolContext, toolMemory);
+            const toolResults = await executeToolBatchWithAdapter({
+                userId: msg.from?.id,
+                toolCalls: calls,
+                streamMessage,
+                toolContext,
+                toolMemory,
+                adapter,
+                appendTargets: [messages],
+            });
 
             let successGetNoteFileResult: GetNoteFileResult | undefined = undefined;
 
@@ -428,7 +444,6 @@ export async function runOllama(
                 }).catch(logError);
             }
 
-            adapter.appendToolResults(messages, calls, toolResults);
         }
     } finally {
         if (interval) clearInterval(interval);

src/ai/unified-ai-runner.openai.ts

@@ -19,7 +19,6 @@ import {
     collectOpenAiResponseCodeInterpreterCalls,
     collectOpenAiResponseImages,
     collectOpenAiResponseText,
-    executeToolBatch,
     MAX_TOOL_ROUNDS,
     OPENAI_IMAGE_PARTIALS,
     openAiResponseItemCallId,
@@ -33,6 +32,7 @@ import {
     errorMessage,
     allToolSchemaNames
 } from "./unified-ai-runner.shared";
+import {executeToolBatchWithAdapter} from "./tool-batch-runner";
 import {bot} from "../index";
 import fs from "node:fs";
 import path from "node:path";
@@ -175,9 +175,16 @@ export async function runOpenAi(
                     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 toolResults = await executeToolBatchWithAdapter({
+                    userId: msg.from?.id,
+                    toolCalls,
+                    streamMessage,
+                    toolContext,
+                    toolMemory,
+                    adapter,
+                    appendTargets: [toolOutputs],
+                });
 
                 const uploadFilesResult = await tryToUploadFiles(msg, toolResults);
                 if (uploadFilesResult.found) {
@@ -364,9 +371,16 @@ export async function runOpenAi(
                 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 toolResults = await executeToolBatchWithAdapter({
+                userId: msg.from?.id,
+                toolCalls,
+                streamMessage,
+                toolContext,
+                toolMemory,
+                adapter,
+                appendTargets: [toolOutputs],
+            });
 
             const uploadFilesResult = await tryToUploadFiles(msg, toolResults);
             if (uploadFilesResult.found) {