-
Notifications
You must be signed in to change notification settings - Fork 346
/
openai.ts
471 lines (431 loc) · 13.6 KB
/
openai.ts
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
import { getEnv } from "@llamaindex/env";
import _ from "lodash";
import type OpenAILLM from "openai";
import type {
ClientOptions,
ClientOptions as OpenAIClientOptions,
} from "openai";
import { AzureOpenAI, OpenAI as OrigOpenAI } from "openai";
import { Tokenizers } from "@llamaindex/env";
import type {
ChatCompletionAssistantMessageParam,
ChatCompletionMessageToolCall,
ChatCompletionRole,
ChatCompletionSystemMessageParam,
ChatCompletionTool,
ChatCompletionToolMessageParam,
ChatCompletionUserMessageParam,
} from "openai/resources/chat/completions";
import type { ChatCompletionMessageParam } from "openai/resources/index.js";
import { wrapEventCaller } from "../internal/context/EventCaller.js";
import { getCallbackManager } from "../internal/settings/CallbackManager.js";
import type { BaseTool } from "../types.js";
import type { AzureOpenAIConfig } from "./azure.js";
import {
getAzureConfigFromEnv,
getAzureModel,
shouldUseAzure,
} from "./azure.js";
import { ToolCallLLM } from "./base.js";
import type {
ChatMessage,
ChatResponse,
ChatResponseChunk,
LLM,
LLMChatParamsNonStreaming,
LLMChatParamsStreaming,
LLMMetadata,
MessageType,
PartialToolCall,
ToolCallLLMMessageOptions,
} from "./types.js";
import { extractText, wrapLLMEvent } from "./utils.js";
export class OpenAISession {
openai: Pick<OrigOpenAI, "chat" | "embeddings">;
constructor(options: ClientOptions & { azure?: boolean } = {}) {
if (options.azure) {
this.openai = new AzureOpenAI(options as AzureOpenAIConfig);
} else {
if (!options.apiKey) {
options.apiKey = getEnv("OPENAI_API_KEY");
}
if (!options.apiKey) {
throw new Error("Set OpenAI Key in OPENAI_API_KEY env variable"); // Overriding OpenAI package's error message
}
this.openai = new OrigOpenAI({
...options,
});
}
}
}
// I'm not 100% sure this is necessary vs. just starting a new session
// every time we make a call. They say they try to reuse connections
// so in theory this is more efficient, but we should test it in the future.
const defaultOpenAISession: {
session: OpenAISession;
options: ClientOptions;
}[] = [];
/**
* Get a session for the OpenAI API. If one already exists with the same options,
* it will be returned. Otherwise, a new session will be created.
* @param options
* @returns
*/
export function getOpenAISession(
options: ClientOptions & { azure?: boolean } = {},
) {
let session = defaultOpenAISession.find((session) => {
return _.isEqual(session.options, options);
})?.session;
if (!session) {
session = new OpenAISession(options);
defaultOpenAISession.push({ session, options });
}
return session;
}
export const GPT4_MODELS = {
"gpt-4": { contextWindow: 8192 },
"gpt-4-32k": { contextWindow: 32768 },
"gpt-4-32k-0613": { contextWindow: 32768 },
"gpt-4-turbo": { contextWindow: 128000 },
"gpt-4-turbo-preview": { contextWindow: 128000 },
"gpt-4-1106-preview": { contextWindow: 128000 },
"gpt-4-0125-preview": { contextWindow: 128000 },
"gpt-4-vision-preview": { contextWindow: 128000 },
"gpt-4o": { contextWindow: 128000 },
"gpt-4o-2024-05-13": { contextWindow: 128000 },
};
// NOTE we don't currently support gpt-3.5-turbo-instruct and don't plan to in the near future
export const GPT35_MODELS = {
"gpt-3.5-turbo": { contextWindow: 4096 },
"gpt-3.5-turbo-0613": { contextWindow: 4096 },
"gpt-3.5-turbo-16k": { contextWindow: 16384 },
"gpt-3.5-turbo-16k-0613": { contextWindow: 16384 },
"gpt-3.5-turbo-1106": { contextWindow: 16384 },
"gpt-3.5-turbo-0125": { contextWindow: 16384 },
};
/**
* We currently support GPT-3.5 and GPT-4 models
*/
export const ALL_AVAILABLE_OPENAI_MODELS = {
...GPT4_MODELS,
...GPT35_MODELS,
};
export function isFunctionCallingModel(llm: LLM): llm is OpenAI {
let model: string;
if (llm instanceof OpenAI) {
model = llm.model;
} else if ("model" in llm && typeof llm.model === "string") {
model = llm.model;
} else {
return false;
}
const isChatModel = Object.keys(ALL_AVAILABLE_OPENAI_MODELS).includes(model);
const isOld = model.includes("0314") || model.includes("0301");
return isChatModel && !isOld;
}
export type OpenAIAdditionalMetadata = {};
export type OpenAIAdditionalChatOptions = Omit<
Partial<OpenAILLM.Chat.ChatCompletionCreateParams>,
| "max_tokens"
| "messages"
| "model"
| "temperature"
| "top_p"
| "stream"
| "tools"
| "toolChoice"
>;
export class OpenAI extends ToolCallLLM<OpenAIAdditionalChatOptions> {
// Per completion OpenAI params
model: keyof typeof ALL_AVAILABLE_OPENAI_MODELS | string;
temperature: number;
topP: number;
maxTokens?: number;
additionalChatOptions?: OpenAIAdditionalChatOptions;
// OpenAI session params
apiKey?: string = undefined;
maxRetries: number;
timeout?: number;
session: OpenAISession;
additionalSessionOptions?: Omit<
Partial<OpenAIClientOptions>,
"apiKey" | "maxRetries" | "timeout"
>;
constructor(
init?: Partial<OpenAI> & {
azure?: AzureOpenAIConfig;
},
) {
super();
this.model = init?.model ?? "gpt-4o";
this.temperature = init?.temperature ?? 0.1;
this.topP = init?.topP ?? 1;
this.maxTokens = init?.maxTokens ?? undefined;
this.maxRetries = init?.maxRetries ?? 10;
this.timeout = init?.timeout ?? 60 * 1000; // Default is 60 seconds
this.additionalChatOptions = init?.additionalChatOptions;
this.additionalSessionOptions = init?.additionalSessionOptions;
if (init?.azure || shouldUseAzure()) {
const azureConfig = {
...getAzureConfigFromEnv({
model: getAzureModel(this.model),
}),
...init?.azure,
};
this.apiKey = azureConfig.apiKey;
this.session =
init?.session ??
getOpenAISession({
azure: true,
maxRetries: this.maxRetries,
timeout: this.timeout,
...this.additionalSessionOptions,
...azureConfig,
});
} else {
this.apiKey = init?.apiKey ?? undefined;
this.session =
init?.session ??
getOpenAISession({
apiKey: this.apiKey,
maxRetries: this.maxRetries,
timeout: this.timeout,
...this.additionalSessionOptions,
});
}
}
get supportToolCall() {
return isFunctionCallingModel(this);
}
get metadata(): LLMMetadata & OpenAIAdditionalMetadata {
const contextWindow =
ALL_AVAILABLE_OPENAI_MODELS[
this.model as keyof typeof ALL_AVAILABLE_OPENAI_MODELS
]?.contextWindow ?? 1024;
return {
model: this.model,
temperature: this.temperature,
topP: this.topP,
maxTokens: this.maxTokens,
contextWindow,
tokenizer: Tokenizers.CL100K_BASE,
};
}
static toOpenAIRole(messageType: MessageType): ChatCompletionRole {
switch (messageType) {
case "user":
return "user";
case "assistant":
return "assistant";
case "system":
return "system";
default:
return "user";
}
}
static toOpenAIMessage(
messages: ChatMessage<ToolCallLLMMessageOptions>[],
): ChatCompletionMessageParam[] {
return messages.map((message) => {
const options = message.options ?? {};
if ("toolResult" in options) {
return {
tool_call_id: options.toolResult.id,
role: "tool",
content: extractText(message.content),
} satisfies ChatCompletionToolMessageParam;
} else if ("toolCall" in options) {
return {
role: "assistant",
content: extractText(message.content),
tool_calls: options.toolCall.map((toolCall) => {
return {
id: toolCall.id,
type: "function",
function: {
name: toolCall.name,
arguments:
typeof toolCall.input === "string"
? toolCall.input
: JSON.stringify(toolCall.input),
},
};
}),
} satisfies ChatCompletionAssistantMessageParam;
} else if (message.role === "user") {
return {
role: "user",
content: message.content,
} satisfies ChatCompletionUserMessageParam;
}
const response:
| ChatCompletionSystemMessageParam
| ChatCompletionUserMessageParam
| ChatCompletionMessageToolCall = {
// fixme(alex): type assertion
role: OpenAI.toOpenAIRole(message.role) as never,
// fixme: should not extract text, but assert content is string
content: extractText(message.content),
};
return response;
});
}
chat(
params: LLMChatParamsStreaming<
OpenAIAdditionalChatOptions,
ToolCallLLMMessageOptions
>,
): Promise<AsyncIterable<ChatResponseChunk<ToolCallLLMMessageOptions>>>;
chat(
params: LLMChatParamsNonStreaming<
OpenAIAdditionalChatOptions,
ToolCallLLMMessageOptions
>,
): Promise<ChatResponse<ToolCallLLMMessageOptions>>;
@wrapEventCaller
@wrapLLMEvent
async chat(
params:
| LLMChatParamsNonStreaming<
OpenAIAdditionalChatOptions,
ToolCallLLMMessageOptions
>
| LLMChatParamsStreaming<
OpenAIAdditionalChatOptions,
ToolCallLLMMessageOptions
>,
): Promise<
| ChatResponse<ToolCallLLMMessageOptions>
| AsyncIterable<ChatResponseChunk<ToolCallLLMMessageOptions>>
> {
const { messages, stream, tools, additionalChatOptions } = params;
const baseRequestParams: OpenAILLM.Chat.ChatCompletionCreateParams = {
model: this.model,
temperature: this.temperature,
max_tokens: this.maxTokens,
tools: tools?.map(OpenAI.toTool),
messages: OpenAI.toOpenAIMessage(messages),
top_p: this.topP,
...Object.assign({}, this.additionalChatOptions, additionalChatOptions),
};
if (
Array.isArray(baseRequestParams.tools) &&
baseRequestParams.tools.length === 0
) {
// remove empty tools array to avoid OpenAI error
delete baseRequestParams.tools;
}
// Streaming
if (stream) {
return this.streamChat(baseRequestParams);
}
// Non-streaming
const response = await this.session.openai.chat.completions.create({
...baseRequestParams,
stream: false,
});
const content = response.choices[0].message?.content ?? "";
return {
raw: response,
message: {
content,
role: response.choices[0].message.role,
options: response.choices[0].message?.tool_calls
? {
toolCall: response.choices[0].message.tool_calls.map(
(toolCall) => ({
id: toolCall.id,
name: toolCall.function.name,
input: toolCall.function.arguments,
}),
),
}
: {},
},
};
}
// todo: this wrapper is ugly, refactor it
@wrapEventCaller
protected async *streamChat(
baseRequestParams: OpenAILLM.Chat.ChatCompletionCreateParams,
): AsyncIterable<ChatResponseChunk<ToolCallLLMMessageOptions>> {
const stream: AsyncIterable<OpenAILLM.Chat.ChatCompletionChunk> =
await this.session.openai.chat.completions.create({
...baseRequestParams,
stream: true,
});
// TODO: add callback to streamConverter and use streamConverter here
//Indices
let idxCounter: number = 0;
// this will be used to keep track of the current tool call, make sure input are valid json object.
let currentToolCall: PartialToolCall | null = null;
const toolCallMap = new Map<string, PartialToolCall>();
for await (const part of stream) {
if (part.choices.length === 0) continue;
const choice = part.choices[0];
// skip parts that don't have any content
if (!(choice.delta.content || choice.delta.tool_calls)) continue;
let shouldEmitToolCall: PartialToolCall | null = null;
if (
choice.delta.tool_calls?.[0].id &&
currentToolCall &&
choice.delta.tool_calls?.[0].id !== currentToolCall.id
) {
shouldEmitToolCall = {
...currentToolCall,
input: JSON.parse(currentToolCall.input),
};
}
if (choice.delta.tool_calls?.[0].id) {
currentToolCall = {
name: choice.delta.tool_calls[0].function!.name!,
id: choice.delta.tool_calls[0].id,
input: choice.delta.tool_calls[0].function!.arguments!,
};
toolCallMap.set(choice.delta.tool_calls[0].id, currentToolCall);
} else {
if (choice.delta.tool_calls?.[0].function?.arguments) {
currentToolCall!.input +=
choice.delta.tool_calls[0].function.arguments;
}
}
const isDone: boolean = choice.finish_reason !== null;
getCallbackManager().dispatchEvent("stream", {
index: idxCounter++,
isDone: isDone,
token: part,
});
if (isDone && currentToolCall) {
// for the last one, we need to emit the tool call
shouldEmitToolCall = {
...currentToolCall,
input: JSON.parse(currentToolCall.input),
};
}
yield {
raw: part,
options: shouldEmitToolCall
? { toolCall: [shouldEmitToolCall] }
: currentToolCall
? {
toolCall: [currentToolCall],
}
: {},
delta: choice.delta.content ?? "",
};
}
toolCallMap.clear();
return;
}
static toTool(tool: BaseTool): ChatCompletionTool {
return {
type: "function",
function: {
name: tool.metadata.name,
description: tool.metadata.description,
parameters: tool.metadata.parameters,
},
};
}
}