Merge df539d50851f7f0ce245afde10942a5a045510a7 into 5e417b44e1540f528d2ae63e3e20229a902d1db2
This commit is contained in:
F_ool
GitHub
commit
2656b48823
@ -4,6 +4,7 @@ import {
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createOllamaStreamFn,
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convertToOllamaMessages,
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buildAssistantMessage,
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recoverToolCallsFromText,
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parseNdjsonStream,
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resolveOllamaBaseUrlForRun,
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} from "./ollama-stream.js";
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@ -182,6 +183,119 @@ describe("buildAssistantMessage", () => {
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total: 0,
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});
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});
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it("recovers tool calls from <tool_call> tags and strips markup from text", () => {
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const response = {
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model: "qwen3.5:9b",
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created_at: "2026-01-01T00:00:00Z",
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message: {
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role: "assistant" as const,
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content:
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'I\'ll save that for you.\n<tool_call>\n{"name": "write_file", "arguments": {"path": "/tmp/note.md", "content": "hello"}}\n</tool_call>',
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},
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done: true,
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prompt_eval_count: 50,
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eval_count: 30,
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};
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const result = buildAssistantMessage(response, {
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api: "ollama",
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provider: "ollama",
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id: "qwen3.5:9b",
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});
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expect(result.stopReason).toBe("toolUse");
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const textParts = result.content.filter((c) => c.type === "text");
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expect(textParts.length).toBe(1);
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expect((textParts[0] as { text: string }).text).toBe("I'll save that for you.");
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const toolCalls = result.content.filter((c) => c.type === "toolCall");
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expect(toolCalls.length).toBe(1);
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const tc = toolCalls[0] as { name: string; arguments: Record<string, unknown> };
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expect(tc.name).toBe("write_file");
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expect(tc.arguments).toEqual({ path: "/tmp/note.md", content: "hello" });
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});
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it("does not recover tool calls when proper tool_calls exist", () => {
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const response = {
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model: "qwen3.5:9b",
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created_at: "2026-01-01T00:00:00Z",
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message: {
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role: "assistant" as const,
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content: '<tool_call>{"name": "ghost", "arguments": {}}</tool_call>',
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tool_calls: [{ function: { name: "bash", arguments: { command: "ls" } } }],
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},
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done: true,
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};
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const result = buildAssistantMessage(response, modelInfo);
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const toolCalls = result.content.filter((c) => c.type === "toolCall");
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expect(toolCalls.length).toBe(1);
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expect((toolCalls[0] as { name: string }).name).toBe("bash");
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});
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it("does not recover tool calls from fenced JSON code blocks", () => {
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const response = {
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model: "qwen3.5:9b",
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created_at: "2026-01-01T00:00:00Z",
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message: {
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role: "assistant" as const,
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content:
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'Here is an example:\n```json\n{"name": "bash", "arguments": {"command": "rm -rf /"}}\n```',
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},
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done: true,
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};
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const result = buildAssistantMessage(response, {
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api: "ollama",
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provider: "ollama",
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id: "qwen3.5:9b",
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});
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expect(result.stopReason).toBe("stop");
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expect(result.content.filter((c) => c.type === "toolCall").length).toBe(0);
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});
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});
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describe("recoverToolCallsFromText", () => {
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it("extracts tool calls from <tool_call> XML tags", () => {
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const text =
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'Sure!\n<tool_call>\n{"name": "bash", "arguments": {"command": "ls"}}\n</tool_call>';
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const result = recoverToolCallsFromText(text);
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expect(result).toEqual([{ function: { name: "bash", arguments: { command: "ls" } } }]);
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});
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it("handles function-wrapped format", () => {
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const text =
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'<tool_call>{"function": {"name": "bash", "arguments": {"command": "pwd"}}}</tool_call>';
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const result = recoverToolCallsFromText(text);
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expect(result).toEqual([{ function: { name: "bash", arguments: { command: "pwd" } } }]);
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});
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it("handles parameters key instead of arguments", () => {
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const text = '<tool_call>{"name": "read", "parameters": {"path": "/tmp/x"}}</tool_call>';
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const result = recoverToolCallsFromText(text);
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expect(result).toEqual([{ function: { name: "read", arguments: { path: "/tmp/x" } } }]);
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});
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it("returns empty for plain text without tool patterns", () => {
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expect(recoverToolCallsFromText("Just a normal reply.")).toEqual([]);
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});
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it("returns empty for malformed JSON inside tags", () => {
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expect(recoverToolCallsFromText("<tool_call>not json</tool_call>")).toEqual([]);
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});
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it("extracts multiple tool calls", () => {
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const text = [
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'<tool_call>{"name": "bash", "arguments": {"command": "ls"}}</tool_call>',
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'<tool_call>{"name": "read", "arguments": {"path": "a.txt"}}</tool_call>',
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].join("\n");
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const result = recoverToolCallsFromText(text);
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expect(result.length).toBe(2);
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expect(result[0]!.function.name).toBe("bash");
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expect(result[1]!.function.name).toBe("read");
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});
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it("ignores fenced JSON blocks (security: no code-block recovery)", () => {
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const text =
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'```json\n{"name": "bash", "arguments": {"command": "rm -rf /"}}\n```';
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expect(recoverToolCallsFromText(text)).toEqual([]);
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});
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});
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// Helper: build a ReadableStreamDefaultReader from NDJSON lines
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@ -399,6 +513,65 @@ describe("createOllamaStreamFn", () => {
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);
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});
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it("uses model options num_ctx when contextWindow is not set", async () => {
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await withMockNdjsonFetch(
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[
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'{"model":"m","created_at":"t","message":{"role":"assistant","content":"ok"},"done":true,"prompt_eval_count":1,"eval_count":1}',
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],
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async (fetchMock) => {
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const streamFn = createOllamaStreamFn("http://ollama-host:11434", undefined, {
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num_ctx: 8192,
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});
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const stream = await Promise.resolve(
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streamFn(
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{ id: "qwen3.5:9b", api: "ollama", provider: "ollama" } as never,
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{ messages: [{ role: "user", content: "hi" }] } as never,
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{} as never,
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),
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);
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await collectStreamEvents(stream);
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const [, requestInit] = fetchMock.mock.calls[0] as unknown as [string, RequestInit];
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const body = JSON.parse(requestInit.body as string) as {
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options: Record<string, unknown>;
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};
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expect(body.options.num_ctx).toBe(8192);
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},
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);
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});
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it("contextWindow takes precedence over model options num_ctx", async () => {
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await withMockNdjsonFetch(
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[
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'{"model":"m","created_at":"t","message":{"role":"assistant","content":"ok"},"done":true,"prompt_eval_count":1,"eval_count":1}',
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],
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async (fetchMock) => {
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const streamFn = createOllamaStreamFn("http://ollama-host:11434", undefined, {
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num_ctx: 8192,
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});
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const stream = await Promise.resolve(
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streamFn(
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{
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id: "qwen3.5:9b",
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api: "ollama",
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provider: "ollama",
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contextWindow: 131072,
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} as never,
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{ messages: [{ role: "user", content: "hi" }] } as never,
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{} as never,
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),
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);
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await collectStreamEvents(stream);
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const [, requestInit] = fetchMock.mock.calls[0] as unknown as [string, RequestInit];
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const body = JSON.parse(requestInit.body as string) as {
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options: Record<string, unknown>;
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};
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expect(body.options.num_ctx).toBe(131072);
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},
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);
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});
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it("merges default headers and allows request headers to override them", async () => {
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await withMockNdjsonFetch(
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[
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@ -335,6 +335,49 @@ function extractOllamaTools(tools: Tool[] | undefined): OllamaTool[] {
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// ── Response conversion ─────────────────────────────────────────────────────
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/**
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* Recover structured tool calls from `<tool_call>…</tool_call>` tags in text.
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*
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* Some smaller local models (e.g. Qwen3.5-9B) understand tool definitions but
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* emit the call as text instead of a proper `tool_calls` array. We only match
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* the explicit `<tool_call>` tag pattern to minimise false-positive risk;
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* generic fenced JSON blocks are intentionally ignored.
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*/
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export function recoverToolCallsFromText(text: string): OllamaToolCall[] {
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const recovered: OllamaToolCall[] = [];
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const tagRegex = /<tool_call>\s*([\s\S]*?)\s*<\/tool_call>/gi;
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let match: RegExpExecArray | null;
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while ((match = tagRegex.exec(text)) !== null) {
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const parsed = tryParseToolCallJson(match[1]!);
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if (parsed) {
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recovered.push(parsed);
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}
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}
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return recovered;
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}
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function tryParseToolCallJson(raw: string): OllamaToolCall | null {
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try {
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const obj = parseJsonPreservingUnsafeIntegers(raw.trim()) as Record<string, unknown>;
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const name = obj.name ?? (obj.function as Record<string, unknown> | undefined)?.name;
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const args =
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obj.arguments ??
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obj.parameters ??
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(obj.function as Record<string, unknown> | undefined)?.arguments;
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if (typeof name === "string" && name && args && typeof args === "object" && !Array.isArray(args)) {
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return { function: { name, arguments: args as Record<string, unknown> } };
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}
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} catch {
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// Not valid JSON – skip.
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}
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return null;
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}
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/** Strip `<tool_call>…</tool_call>` blocks from text after recovery. */
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function stripToolCallTags(text: string): string {
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return text.replace(/<tool_call>[\s\S]*?<\/tool_call>/gi, "").replace(/\n{3,}/g, "\n\n").trim();
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}
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export function buildAssistantMessage(
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response: OllamaChatResponse,
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modelInfo: { api: string; provider: string; id: string },
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@ -344,11 +387,31 @@ export function buildAssistantMessage(
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// Native Ollama reasoning fields are internal model output. The reply text
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// must come from `content`; reasoning visibility is controlled elsewhere.
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const text = response.message.content || "";
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if (text) {
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content.push({ type: "text", text });
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let toolCalls = response.message.tool_calls;
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let didRecover = false;
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// Fallback: recover tool calls from <tool_call> tags when the model
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// produced no native tool_calls. Only the explicit XML-tag pattern is
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// matched to reduce false-positive risk (see security review).
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if ((!toolCalls || toolCalls.length === 0) && text) {
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const recovered = recoverToolCallsFromText(text);
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if (recovered.length > 0) {
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toolCalls = recovered;
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didRecover = true;
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log.info(
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`Recovered ${recovered.length} tool call(s) from text output for model ${modelInfo.id}`,
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);
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}
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}
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// When tool calls were recovered from text, strip the raw markup so it
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// does not pollute conversation history on subsequent turns.
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const visibleText = didRecover ? stripToolCallTags(text) : text;
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if (visibleText) {
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content.push({ type: "text", text: visibleText });
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}
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const toolCalls = response.message.tool_calls;
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if (toolCalls && toolCalls.length > 0) {
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for (const tc of toolCalls) {
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content.push({
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@ -434,6 +497,7 @@ function resolveOllamaModelHeaders(model: {
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export function createOllamaStreamFn(
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baseUrl: string,
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defaultHeaders?: Record<string, string>,
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modelOptions?: Record<string, unknown>,
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): StreamFn {
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const chatUrl = resolveOllamaChatUrl(baseUrl);
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@ -449,9 +513,16 @@ export function createOllamaStreamFn(
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const ollamaTools = extractOllamaTools(context.tools);
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// Ollama defaults to num_ctx=4096 which is too small for large
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// system prompts + many tool definitions. Use model's contextWindow.
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const ollamaOptions: Record<string, unknown> = { num_ctx: model.contextWindow ?? 65536 };
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const userNumCtx =
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modelOptions &&
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typeof modelOptions.num_ctx === "number" &&
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Number.isFinite(modelOptions.num_ctx)
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? modelOptions.num_ctx
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: undefined;
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const ollamaOptions: Record<string, unknown> = {
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...(modelOptions ?? {}),
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num_ctx: model.contextWindow ?? userNumCtx ?? 65536,
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};
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if (typeof options?.temperature === "number") {
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ollamaOptions.temperature = options.temperature;
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}
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@ -561,7 +632,7 @@ export function createOllamaStreamFn(
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}
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export function createConfiguredOllamaStreamFn(params: {
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model: { baseUrl?: string; headers?: unknown };
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model: { baseUrl?: string; headers?: unknown; options?: Record<string, unknown> };
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providerBaseUrl?: string;
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}): StreamFn {
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const modelBaseUrl = typeof params.model.baseUrl === "string" ? params.model.baseUrl : undefined;
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@ -571,5 +642,6 @@ export function createConfiguredOllamaStreamFn(params: {
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providerBaseUrl: params.providerBaseUrl,
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}),
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resolveOllamaModelHeaders(params.model),
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params.model.options,
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);
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}
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@ -146,7 +146,8 @@ function applyConfiguredProviderOverrides(params: {
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}
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: undefined,
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compat: configuredModel?.compat ?? discoveredModel.compat,
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};
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...(configuredModel?.options != null ? { options: configuredModel.options } : {}),
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} as Model<Api>;
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}
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export function buildInlineProviderModels(
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@ -301,6 +302,7 @@ export function resolveModelWithRegistry(params: {
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DEFAULT_CONTEXT_TOKENS,
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headers:
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providerHeaders || modelHeaders ? { ...providerHeaders, ...modelHeaders } : undefined,
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...(configuredModel?.options != null ? { options: configuredModel.options } : {}),
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} as Model<Api>,
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});
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}
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@ -2159,12 +2159,20 @@ export async function runEmbeddedAttempt(
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queueYieldInterruptForSession = () => {
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queueSessionsYieldInterruptMessage(activeSession);
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};
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const modelWithOptions = params.model as { options?: Record<string, unknown> };
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const optionsNumCtx =
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typeof modelWithOptions.options?.num_ctx === "number"
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? modelWithOptions.options.num_ctx
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: undefined;
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removeToolResultContextGuard = installToolResultContextGuard({
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agent: activeSession.agent,
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contextWindowTokens: Math.max(
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1,
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Math.floor(
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params.model.contextWindow ?? params.model.maxTokens ?? DEFAULT_CONTEXT_TOKENS,
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params.model.contextWindow ??
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optionsNumCtx ??
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params.model.maxTokens ??
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DEFAULT_CONTEXT_TOKENS,
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),
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),
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});
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@ -2237,7 +2245,10 @@ export async function runEmbeddedAttempt(
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const numCtx = Math.max(
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1,
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Math.floor(
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params.model.contextWindow ?? params.model.maxTokens ?? DEFAULT_CONTEXT_TOKENS,
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params.model.contextWindow ??
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optionsNumCtx ??
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params.model.maxTokens ??
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DEFAULT_CONTEXT_TOKENS,
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),
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);
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activeSession.agent.streamFn = wrapOllamaCompatNumCtx(activeSession.agent.streamFn, numCtx);
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@ -254,9 +254,17 @@ export function applyModelDefaults(cfg: OpenClawConfig): OpenClawConfig {
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modelMutated = true;
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}
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const optionsNumCtx =
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raw.options &&
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typeof raw.options === "object" &&
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typeof (raw.options as Record<string, unknown>).num_ctx === "number" &&
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Number.isFinite((raw.options as Record<string, unknown>).num_ctx) &&
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((raw.options as Record<string, unknown>).num_ctx as number) > 0
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? ((raw.options as Record<string, unknown>).num_ctx as number)
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: undefined;
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const contextWindow = isPositiveNumber(raw.contextWindow)
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? raw.contextWindow
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: DEFAULT_CONTEXT_TOKENS;
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: optionsNumCtx ?? DEFAULT_CONTEXT_TOKENS;
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if (raw.contextWindow !== contextWindow) {
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modelMutated = true;
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}
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@ -59,6 +59,7 @@ export type ModelDefinitionConfig = {
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maxTokens: number;
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headers?: Record<string, string>;
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compat?: ModelCompatConfig;
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options?: Record<string, unknown>;
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};
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export type ModelProviderConfig = {
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@ -242,6 +242,7 @@ export const ModelDefinitionSchema = z
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maxTokens: z.number().positive().optional(),
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headers: z.record(z.string(), z.string()).optional(),
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compat: ModelCompatSchema,
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options: z.record(z.string(), z.unknown()).optional(),
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})
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.strict();
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