Files
simple-proxy/src/shared/api-schemas/anthropic.ts
T
2024-03-05 18:34:10 -06:00

239 lines
6.9 KiB
TypeScript

import { z } from "zod";
import { Request } from "express";
import { config } from "../../config";
import {
flattenOpenAIMessageContent,
OpenAIChatMessage,
OpenAIV1ChatCompletionSchema,
} from "./openai";
const CLAUDE_OUTPUT_MAX = config.maxOutputTokensAnthropic;
const AnthropicV1BaseSchema = z
.object({
model: z.string().max(100),
stop_sequences: z.array(z.string().max(500)).optional(),
stream: z.boolean().optional().default(false),
temperature: z.coerce.number().optional().default(1),
top_k: z.coerce.number().optional(),
top_p: z.coerce.number().optional(),
metadata: z.object({ user_id: z.string().optional() }).optional(),
})
.strip();
// https://docs.anthropic.com/claude/reference/complete_post [deprecated]
export const AnthropicV1TextSchema = AnthropicV1BaseSchema.merge(
z.object({
prompt: z.string(),
max_tokens_to_sample: z.coerce
.number()
.int()
.transform((v) => Math.min(v, CLAUDE_OUTPUT_MAX)),
})
);
const AnthropicV1MessageMultimodalContentSchema = z.array(
z.union([
z.object({ type: z.literal("text"), text: z.string() }),
z.object({
type: z.literal("image"),
source: z.object({
type: z.literal("base64"),
media_type: z.string().max(100),
data: z.string(),
}),
}),
])
);
// https://docs.anthropic.com/claude/reference/messages_post
export const AnthropicV1MessagesSchema = AnthropicV1BaseSchema.merge(
z.object({
messages: z.array(
z.object({
role: z.enum(["user", "assistant"]),
content: z.union([
z.string(),
AnthropicV1MessageMultimodalContentSchema,
]),
})
),
max_tokens: z
.number()
.int()
.transform((v) => Math.min(v, CLAUDE_OUTPUT_MAX)),
system: z.string().optional(),
})
);
export type AnthropicChatMessage = z.infer<
typeof AnthropicV1MessagesSchema
>["messages"][0];
export function openAIMessagesToClaudeTextPrompt(
messages: OpenAIChatMessage[]
) {
return (
messages
.map((m) => {
let role: string = m.role;
if (role === "assistant") {
role = "Assistant";
} else if (role === "system") {
role = "System";
} else if (role === "user") {
role = "Human";
}
const name = m.name?.trim();
const content = flattenOpenAIMessageContent(m.content);
// https://console.anthropic.com/docs/prompt-design
// `name` isn't supported by Anthropic but we can still try to use it.
return `\n\n${role}: ${name ? `(as ${name}) ` : ""}${content}`;
})
.join("") + "\n\nAssistant:"
);
}
export function openAIToAnthropicText(req: Request) {
const { body } = req;
const result = OpenAIV1ChatCompletionSchema.safeParse(body);
if (!result.success) {
req.log.warn(
{ issues: result.error.issues, body },
"Invalid OpenAI-to-Anthropic Text request"
);
throw result.error;
}
req.headers["anthropic-version"] = "2023-06-01";
const { messages, ...rest } = result.data;
const prompt = openAIMessagesToClaudeTextPrompt(messages);
let stops = rest.stop
? Array.isArray(rest.stop)
? rest.stop
: [rest.stop]
: [];
// Recommended by Anthropic
stops.push("\n\nHuman:");
// Helps with jailbreak prompts that send fake system messages and multi-bot
// chats that prefix bot messages with "System: Respond as <bot name>".
stops.push("\n\nSystem:");
// Remove duplicates
stops = [...new Set(stops)];
return {
model: rest.model,
prompt: prompt,
max_tokens_to_sample: rest.max_tokens,
stop_sequences: stops,
stream: rest.stream,
temperature: rest.temperature,
top_p: rest.top_p,
};
}
/**
* Converts an older Anthropic Text Completion prompt to the newer Messages API
* by splitting the flat text into messages.
*/
export function anthropicTextToAnthropicChat(req: Request) {
const { body } = req;
const result = AnthropicV1TextSchema.safeParse(body);
if (!result.success) {
req.log.warn(
{ issues: result.error.issues, body },
"Invalid Anthropic Text-to-Anthropic Chat request"
);
throw result.error;
}
req.headers["anthropic-version"] = "2023-06-01";
const { model, max_tokens_to_sample, prompt, ...rest } = result.data;
validateAnthropicTextPrompt(prompt);
// Iteratively slice the prompt into messages. Start from the beginning and
// look for the next `\n\nHuman:` or `\n\nAssistant:`. Anything before the
// first human message is a system message.
let index = prompt.indexOf("\n\nHuman:");
let remaining = prompt.slice(index);
const system = prompt.slice(0, index);
const messages: AnthropicChatMessage[] = [];
while (remaining) {
const isHuman = remaining.startsWith("\n\nHuman:");
// TODO: Are multiple consecutive human or assistant messages allowed?
// Currently we will enforce alternating turns.
const thisRole = isHuman ? "\n\nHuman:" : "\n\nAssistant:";
const nextRole = isHuman ? "\n\nAssistant:" : "\n\nHuman:";
const nextIndex = remaining.indexOf(nextRole);
// Collect text up to the next message, or the end of the prompt for the
// Assistant prefill if present.
const msg = remaining
.slice(0, nextIndex === -1 ? undefined : nextIndex)
.replace(thisRole, "")
.trimStart();
const role = isHuman ? "user" : "assistant";
messages.push({ role, content: msg });
remaining = remaining.slice(nextIndex);
if (nextIndex === -1) break;
}
// fix "messages: final assistant content cannot end with trailing whitespace"
const lastMessage = messages[messages.length - 1];
if (
lastMessage.role === "assistant" &&
typeof lastMessage.content === "string"
) {
messages[messages.length - 1].content = lastMessage.content.trimEnd();
}
return {
model,
system,
messages,
max_tokens: max_tokens_to_sample,
...rest,
};
}
function validateAnthropicTextPrompt(prompt: string) {
if (!prompt.includes("\n\nHuman:") || !prompt.includes("\n\nAssistant:")) {
throw new Error(
"Prompt must contain at least one human and one assistant message."
);
}
// First human message must be before first assistant message
const firstHuman = prompt.indexOf("\n\nHuman:");
const firstAssistant = prompt.indexOf("\n\nAssistant:");
if (firstAssistant < firstHuman) {
throw new Error(
"First Assistant message must come after the first Human message."
);
}
}
export function flattenAnthropicMessages(
messages: AnthropicChatMessage[]
): string {
return messages
.map((msg) => {
const name = msg.role === "user" ? "\n\nHuman: " : "\n\nAssistant: ";
const parts = Array.isArray(msg.content)
? msg.content
: [{ type: "text", text: msg.content }];
return `${name}: ${parts
.map((part) =>
part.type === "text"
? part.text
: `[Omitted multimodal content of type ${part.type}]`
)
.join("\n")}`;
})
.join("\n\n");
}