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fix(openai): return empty array on listModels API error #3

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197 changes: 99 additions & 98 deletions packages/provider-openai/src/index.ts
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Original file line number Diff line number Diff line change
@@ -1,99 +1,100 @@
import type { ProviderPlugin, LLMCompletionRequest, LLMCompletionResponse, LLMCompletionChunk, PluginManifest } from "@mxclaw/core";

const manifest: PluginManifest = {
name: "openai", version: "0.1.0", type: "provider",
description: "OpenAI API provider (GPT-4o, GPT-4, etc.)", author: "mxclaw",
main: "dist/index.js", capabilities: ["completion", "streaming", "tools", "vision"],
};

let apiKey = "";
let baseUrl = "https://api.openai.com/v1";

const plugin: ProviderPlugin = {
manifest,
initialize: async (config) => {
apiKey = (config.apiKey as string) ?? process.env.OPENAI_API_KEY ?? "";
baseUrl = (config.baseUrl as string) ?? "https://api.openai.com/v1";
},
complete: async (request): Promise<LLMCompletionResponse> => {
const timeout = AbortSignal.timeout(120_000); // 2 minute timeout
const resp = await fetch(`${baseUrl}/chat/completions`, {
method: "POST", headers: { Authorization: `Bearer ${apiKey}`, "Content-Type": "application/json" },
body: JSON.stringify({
model: request.model, messages: request.messages,
tools: request.tools, temperature: request.temperature, max_tokens: request.maxTokens,
}),
signal: request.signal ?? timeout,
});
if (!resp.ok) {
const errBody = await resp.text().catch(() => "unknown");
throw new Error(`OpenAI error ${resp.status}: ${errBody}`);
}
const data = (await resp.json()) as { choices: Array<{ message: { content: string; tool_calls?: Array<{ id: string; function: { name: string; arguments: string } }> }; finish_reason: string }>; usage?: { prompt_tokens: number; completion_tokens: number; total_tokens: number } };
const choice = data.choices[0]!;
return {
content: choice.message.content ?? "",
toolCalls: choice.message.tool_calls?.map(tc => {
let args: Record<string, unknown>;
try { args = JSON.parse(tc.function.arguments); } catch { args = { raw: tc.function.arguments }; }
return { id: tc.id, name: tc.function.name, arguments: args };
}),
finishReason: choice.finish_reason as LLMCompletionResponse["finishReason"],
usage: data.usage ? {
promptTokens: data.usage.prompt_tokens,
completionTokens: data.usage.completion_tokens,
totalTokens: data.usage.total_tokens,
} : undefined,
};
},
completeStream: async function* (request): AsyncGenerator<LLMCompletionChunk> {
const resp = await fetch(`${baseUrl}/chat/completions`, {
method: "POST", headers: { Authorization: `Bearer ${apiKey}`, "Content-Type": "application/json" },
body: JSON.stringify({
model: request.model, messages: request.messages,
tools: request.tools, temperature: request.temperature, max_tokens: request.maxTokens,
stream: true,
}),
signal: request.signal,
});
if (!resp.ok) throw new Error(`OpenAI stream error: ${resp.status}`);
const reader = resp.body!.getReader();
const decoder = new TextDecoder();
let buffer = "";
while (true) {
const { done, value } = await reader.read();
if (done) break;
buffer += decoder.decode(value, { stream: true });
const lines = buffer.split("\n");
buffer = lines.pop() ?? "";
for (const line of lines) {
if (!line.startsWith("data: ")) continue;
const data = line.slice(6);
if (data === "[DONE]") return;
try {
const parsed = JSON.parse(data) as { choices: Array<{ delta: { content?: string; tool_calls?: Array<{ index: number; id?: string; function?: { name?: string; arguments?: string } }> }; finish_reason?: string }> };
const delta = parsed.choices[0]?.delta;
if (!delta) continue;
yield {
content: delta.content ?? "",
toolCalls: delta.tool_calls?.map(tc => ({ id: tc.id ?? "", name: tc.function?.name ?? "", arguments: tc.function?.arguments ?? "" })),
finishReason: parsed.choices[0]?.finish_reason as LLMCompletionChunk["finishReason"],
};
} catch { /* skip malformed chunks */ }
}
}
},
listModels: async () => {
const resp = await fetch(`${baseUrl}/models`, { headers: { Authorization: `Bearer ${apiKey}` } });
const data = (await resp.json()) as { data: Array<{ id: string }> };
return data.data.map(m => ({ id: m.id, name: m.id }));
},
healthCheck: async () => {
try {
await fetch(`${baseUrl}/models`, { headers: { Authorization: `Bearer ${apiKey}` } });
return true;
} catch { return false; }
},
};

import type { ProviderPlugin, LLMCompletionRequest, LLMCompletionResponse, LLMCompletionChunk, PluginManifest } from "@mxclaw/core";

const manifest: PluginManifest = {
name: "openai", version: "0.1.0", type: "provider",
description: "OpenAI API provider (GPT-4o, GPT-4, etc.)", author: "mxclaw",
main: "dist/index.js", capabilities: ["completion", "streaming", "tools", "vision"],
};

let apiKey = "";
let baseUrl = "https://api.openai.com/v1";

const plugin: ProviderPlugin = {
manifest,
initialize: async (config) => {
apiKey = (config.apiKey as string) ?? process.env.OPENAI_API_KEY ?? "";
baseUrl = (config.baseUrl as string) ?? "https://api.openai.com/v1";
},
complete: async (request): Promise<LLMCompletionResponse> => {
const timeout = AbortSignal.timeout(120_000); // 2 minute timeout
const resp = await fetch(`${baseUrl}/chat/completions`, {
method: "POST", headers: { Authorization: `Bearer ${apiKey}`, "Content-Type": "application/json" },
body: JSON.stringify({
model: request.model, messages: request.messages,
tools: request.tools, temperature: request.temperature, max_tokens: request.maxTokens,
}),
signal: request.signal ?? timeout,
});
if (!resp.ok) {
const errBody = await resp.text().catch(() => "unknown");
throw new Error(`OpenAI error ${resp.status}: ${errBody}`);
}
const data = (await resp.json()) as { choices: Array<{ message: { content: string; tool_calls?: Array<{ id: string; function: { name: string; arguments: string } }> }; finish_reason: string }>; usage?: { prompt_tokens: number; completion_tokens: number; total_tokens: number } };
const choice = data.choices[0]!;
return {
content: choice.message.content ?? "",
toolCalls: choice.message.tool_calls?.map(tc => {
let args: Record<string, unknown>;
try { args = JSON.parse(tc.function.arguments); } catch { args = { raw: tc.function.arguments }; }
return { id: tc.id, name: tc.function.name, arguments: args };
}),
finishReason: choice.finish_reason as LLMCompletionResponse["finishReason"],
usage: data.usage ? {
promptTokens: data.usage.prompt_tokens,
completionTokens: data.usage.completion_tokens,
totalTokens: data.usage.total_tokens,
} : undefined,
};
},
completeStream: async function* (request): AsyncGenerator<LLMCompletionChunk> {
const resp = await fetch(`${baseUrl}/chat/completions`, {
method: "POST", headers: { Authorization: `Bearer ${apiKey}`, "Content-Type": "application/json" },
body: JSON.stringify({
model: request.model, messages: request.messages,
tools: request.tools, temperature: request.temperature, max_tokens: request.maxTokens,
stream: true,
}),
signal: request.signal,
});
if (!resp.ok) throw new Error(`OpenAI stream error: ${resp.status}`);
const reader = resp.body!.getReader();
const decoder = new TextDecoder();
let buffer = "";
while (true) {
const { done, value } = await reader.read();
if (done) break;
buffer += decoder.decode(value, { stream: true });
const lines = buffer.split("\n");
buffer = lines.pop() ?? "";
for (const line of lines) {
if (!line.startsWith("data: ")) continue;
const data = line.slice(6);
if (data === "[DONE]") return;
try {
const parsed = JSON.parse(data) as { choices: Array<{ delta: { content?: string; tool_calls?: Array<{ index: number; id?: string; function?: { name?: string; arguments?: string } }> }; finish_reason?: string }> };
const delta = parsed.choices[0]?.delta;
if (!delta) continue;
yield {
content: delta.content ?? "",
toolCalls: delta.tool_calls?.map(tc => ({ id: tc.id ?? "", name: tc.function?.name ?? "", arguments: tc.function?.arguments ?? "" })),
finishReason: parsed.choices[0]?.finish_reason as LLMCompletionChunk["finishReason"],
};
} catch { /* skip malformed chunks */ }
}
}
},
listModels: async () => {
const resp = await fetch(`${baseUrl}/models`, { headers: { Authorization: `Bearer ${apiKey}` } });
if (!resp.ok) return [];
const data = (await resp.json()) as { data: Array<{ id: string }> };
return data.data.map(m => ({ id: m.id, name: m.id }));
},
healthCheck: async () => {
try {
await fetch(`${baseUrl}/models`, { headers: { Authorization: `Bearer ${apiKey}` } });
return true;
} catch { return false; }
},
};

export default plugin;