File size: 5,639 Bytes
8d88d9b
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
import type { ToolResult, Tool } from "$lib/types/Tool";
import {
	MessageReasoningUpdateType,
	MessageUpdateType,
	type MessageUpdate,
} from "$lib/types/MessageUpdate";
import { AbortedGenerations } from "../abortedGenerations";
import type { TextGenerationContext } from "./types";
import type { EndpointMessage } from "../endpoints/endpoints";
import { generateFromDefaultEndpoint } from "../generateFromDefaultEndpoint";
import { generateSummaryOfReasoning } from "./reasoning";
import { logger } from "../logger";

type GenerateContext = Omit<TextGenerationContext, "messages"> & { messages: EndpointMessage[] };

export async function* generate(
	{ model, endpoint, conv, messages, assistant, isContinue, promptedAt }: GenerateContext,
	toolResults: ToolResult[],
	preprompt?: string,
	tools?: Tool[]
): AsyncIterable<MessageUpdate> {
	// reasoning mode is false by default
	let reasoning = false;
	let reasoningBuffer = "";
	let lastReasoningUpdate = new Date();
	let status = "";
	const startTime = new Date();
	if (
		model.reasoning &&
		(model.reasoning.type === "regex" || model.reasoning.type === "summarize")
	) {
		// if the model has reasoning in regex or summarize mode, it starts in reasoning mode
		// and we extract the answer from the reasoning
		reasoning = true;
		yield {
			type: MessageUpdateType.Reasoning,
			subtype: MessageReasoningUpdateType.Status,
			status: "Started reasoning...",
		};
	}

	for await (const output of await endpoint({
		messages,
		preprompt,
		continueMessage: isContinue,
		generateSettings: assistant?.generateSettings,
		tools,
		toolResults,
		isMultimodal: model.multimodal,
		conversationId: conv._id,
	})) {
		// text generation completed
		if (output.generated_text) {
			let interrupted =
				!output.token.special && !model.parameters.stop?.includes(output.token.text);

			let text = output.generated_text.trimEnd();
			for (const stopToken of model.parameters.stop ?? []) {
				if (!text.endsWith(stopToken)) continue;

				interrupted = false;
				text = text.slice(0, text.length - stopToken.length);
			}

			let finalAnswer = text;
			if (model.reasoning && model.reasoning.type === "regex") {
				const regex = new RegExp(model.reasoning.regex);
				finalAnswer = regex.exec(reasoningBuffer)?.[1] ?? text;
			} else if (model.reasoning && model.reasoning.type === "summarize") {
				yield {
					type: MessageUpdateType.Reasoning,
					subtype: MessageReasoningUpdateType.Status,
					status: "Summarizing reasoning...",
				};
				try {
					const summary = yield* generateFromDefaultEndpoint({
						messages: [
							{
								from: "user",
								content: `Question: ${
									messages[messages.length - 1].content
								}\n\nReasoning: ${reasoningBuffer}`,
							},
						],
						preprompt: `Your task is to summarize concisely all your reasoning steps and then give the final answer. Keep it short, one short paragraph at most. If the reasoning steps explicitly include a code solution, make sure to include it in your answer.

If the user is just having a casual conversation that doesn't require explanations, answer directly without explaining your steps, otherwise make sure to summarize step by step, make sure to skip dead-ends in your reasoning and removing excess detail.

Do not use prefixes such as Response: or Answer: when answering to the user.`,
						generateSettings: {
							max_new_tokens: 1024,
						},
					});
					finalAnswer = summary;
					yield {
						type: MessageUpdateType.Reasoning,
						subtype: MessageReasoningUpdateType.Status,
						status: `Done in ${Math.round((new Date().getTime() - startTime.getTime()) / 1000)}s.`,
					};
				} catch (e) {
					finalAnswer = text;
					logger.error(e);
				}
			}

			yield {
				type: MessageUpdateType.FinalAnswer,
				text: finalAnswer,
				interrupted,
				webSources: output.webSources,
			};
			continue;
		}

		if (model.reasoning && model.reasoning.type === "tokens") {
			if (output.token.text === model.reasoning.beginToken) {
				reasoning = true;
				reasoningBuffer += output.token.text;
				yield {
					type: MessageUpdateType.Reasoning,
					subtype: MessageReasoningUpdateType.Status,
					status: "Started thinking...",
				};
			} else if (output.token.text === model.reasoning.endToken) {
				reasoning = false;
				reasoningBuffer += output.token.text;
				yield {
					type: MessageUpdateType.Reasoning,
					subtype: MessageReasoningUpdateType.Status,
					status: `Done in ${Math.round((new Date().getTime() - startTime.getTime()) / 1000)}s.`,
				};
			}
		}
		// ignore special tokens
		if (output.token.special) continue;

		// pass down normal token
		if (reasoning) {
			reasoningBuffer += output.token.text;

			// yield status update if it has changed
			if (status !== "") {
				yield {
					type: MessageUpdateType.Reasoning,
					subtype: MessageReasoningUpdateType.Status,
					status,
				};
				status = "";
			}

			// create a new status every 5 seconds
			if (new Date().getTime() - lastReasoningUpdate.getTime() > 4000) {
				lastReasoningUpdate = new Date();
				try {
					generateSummaryOfReasoning(reasoningBuffer).then((summary) => {
						status = summary;
					});
				} catch (e) {
					logger.error(e);
				}
			}
			yield {
				type: MessageUpdateType.Reasoning,
				subtype: MessageReasoningUpdateType.Stream,
				token: output.token.text,
			};
		} else {
			yield { type: MessageUpdateType.Stream, token: output.token.text };
		}

		// abort check
		const date = AbortedGenerations.getInstance().getList().get(conv._id.toString());
		if (date && date > promptedAt) break;

		// no output check
		if (!output) break;
	}
}