fix(core): safely recover malformed tool input (#37698)

packages/ai/test/provider/anthropic-messages.test.ts

@@ -484,6 +484,30 @@ describe("Anthropic Messages route", () => {
     }),
   )
 
+  it.effect("keeps malformed server tool input terminal", () =>
+    Effect.gen(function* () {
+      const body = sseEvents(
+        { type: "message_start", message: { usage: { input_tokens: 5 } } },
+        {
+          type: "content_block_start",
+          index: 0,
+          content_block: { type: "server_tool_use", id: "call_1", name: "web_search" },
+        },
+        {
+          type: "content_block_delta",
+          index: 0,
+          delta: { type: "input_json_delta", partial_json: '{"query":"partial' },
+        },
+        { type: "content_block_stop", index: 0 },
+      )
+
+      const error = yield* LLMClient.generate(request).pipe(Effect.provide(fixedResponse(body)), Effect.flip)
+
+      expect(error).toBeInstanceOf(LLMError)
+      expect(error.message).toContain("Invalid JSON input for anthropic-messages tool call web_search")
+    }),
+  )
+
   it.effect("fails with a typed provider error for stream error frames", () =>
     Effect.gen(function* () {
       const error = yield* LLMClient.generate(request).pipe(

packages/ai/test/provider/bedrock-converse.test.ts

@@ -303,6 +303,32 @@ describe("Bedrock Converse route", () => {
     }),
   )
 
+  it.effect("emits malformed tool input as an unexecuted tool error", () =>
+    Effect.gen(function* () {
+      const body = eventStreamBody(
+        ["messageStart", { role: "assistant" }],
+        [
+          "contentBlockStart",
+          {
+            contentBlockIndex: 0,
+            start: { toolUse: { toolUseId: "tool_1", name: "lookup" } },
+          },
+        ],
+        ["contentBlockDelta", { contentBlockIndex: 0, delta: { toolUse: { input: '{"query":"partial' } } }],
+        ["contentBlockStop", { contentBlockIndex: 0 }],
+        ["messageStop", { stopReason: "end_turn" }],
+      )
+      const response = yield* LLMClient.generate(baseRequest).pipe(Effect.provide(fixedBytes(body)))
+
+      expect(response.events.find((event) => event.type === "tool-input-error")).toMatchObject({
+        id: "tool_1",
+        name: "lookup",
+        raw: '{"query":"partial',
+      })
+      expect(response.finishReason).toBe("tool-calls")
+    }),
+  )
+
   it.effect("decodes reasoning deltas", () =>
     Effect.gen(function* () {
       const body = eventStreamBody(

packages/ai/test/provider/openai-responses.test.ts

@@ -1,7 +1,7 @@
 import { describe, expect } from "bun:test"
 import { ConfigProvider, Effect, Layer, Stream } from "effect"
 import { Headers, HttpClientRequest } from "effect/unstable/http"
-import { LLM, LLMError, Message, Model, ToolCallPart, Usage } from "../../src"
+import { LLM, LLMError, LLMEvent, Message, Model, ToolCallPart, Usage } from "../../src"
 import { Auth, LLMClient, RequestExecutor, WebSocketExecutor } from "../../src/route"
 import * as Azure from "../../src/providers/azure"
 import * as OpenAI from "../../src/providers/openai"
@@ -1259,6 +1259,71 @@ describe("OpenAI Responses route", () => {
     }),
   )
 
+  it.effect("emits malformed final function arguments as an unexecuted tool error", () =>
+    Effect.gen(function* () {
+      const body = sseEvents(
+        {
+          type: "response.output_item.added",
+          item: { type: "function_call", id: "item_1", call_id: "call_1", name: "lookup", arguments: "" },
+        },
+        { type: "response.function_call_arguments.delta", item_id: "item_1", delta: '{"query":"streamed"}' },
+        {
+          type: "response.output_item.done",
+          item: {
+            type: "function_call",
+            id: "item_1",
+            call_id: "call_1",
+            name: "lookup",
+            arguments: '{"query":"partial',
+          },
+        },
+        { type: "response.completed", response: { usage: { input_tokens: 5, output_tokens: 1 } } },
+      )
+      const response = yield* LLMClient.generate(
+        LLM.updateRequest(request, {
+          tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
+        }),
+      ).pipe(Effect.provide(fixedResponse(body)))
+
+      expect(response.events.find(LLMEvent.is.toolInputError)).toEqual({
+        type: "tool-input-error",
+        id: "call_1",
+        name: "lookup",
+        raw: '{"query":"partial',
+        message: "Invalid JSON input for openai-responses tool call lookup",
+        providerMetadata: { openai: { itemId: "item_1" } },
+      })
+      expect(response.finishReason).toBe("tool-calls")
+      expect(response.events.some(LLMEvent.is.toolCall)).toBeFalse()
+    }),
+  )
+
+  it.effect("settles malformed function arguments when output_item.added is absent", () =>
+    Effect.gen(function* () {
+      const body = sseEvents(
+        {
+          type: "response.output_item.done",
+          item: {
+            type: "function_call",
+            id: "item_1",
+            call_id: "call_1",
+            name: "lookup",
+            arguments: '{"query":"partial',
+          },
+        },
+        { type: "response.completed", response: { usage: { input_tokens: 5, output_tokens: 1 } } },
+      )
+      const response = yield* LLMClient.generate(request).pipe(Effect.provide(fixedResponse(body)))
+
+      expect(response.events.find(LLMEvent.is.toolInputError)).toMatchObject({
+        id: "call_1",
+        name: "lookup",
+        raw: '{"query":"partial',
+      })
+      expect(response.finishReason).toBe("tool-calls")
+    }),
+  )
+
   it.effect("decodes web_search_call as provider-executed tool-call + tool-result", () =>
     Effect.gen(function* () {
       const item = {