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| 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 | 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x | import type { AnthropicCompleteResponse } from '@api/ai-providers/anthropic/types';
import { generateInvalidProviderResponseError } from '@api/utils/ai-provider';
import type {
AIProviderFunctionConfig,
ResponseChunkStreamTransformFunction,
ResponseTransformFunction,
} from '@shared/types/ai-providers/config';
import type { CompletionRequestBody } from '@shared/types/api/routes/completions-api/request';
import type {
CompletionFinishReason,
CompletionResponseBody,
} from '@shared/types/api/routes/completions-api/response';
import { AIProvider } from '@shared/types/constants';
import { anthropicErrorResponseTransform } from './chat-complete';
// TODO: this configuration does not enforce the maximum token limit for the input parameter. If you want to enforce this, you might need to add a custom validation function or a max property to the ParameterConfig interface, and then use it in the input configuration. However, this might be complex because the token count is not a simple length check, but depends on the specific tokenization method used by the model.
export const anthropicCompleteConfig: AIProviderFunctionConfig = {
model: {
param: 'model',
default: 'claude-instant-1',
required: true,
},
prompt: {
param: 'prompt',
transform: (saRequestBody: CompletionRequestBody) =>
`\n\nHuman: ${saRequestBody.prompt}\n\nAssistant:`,
required: true,
},
max_tokens: {
param: 'max_tokens_to_sample',
required: true,
},
temperature: {
param: 'temperature',
default: 1,
min: 0,
max: 1,
},
top_p: {
param: 'top_p',
default: -1,
min: -1,
},
top_k: {
param: 'top_k',
default: -1,
},
stop: {
param: 'stop_sequences',
transform: (saRequestBody: CompletionRequestBody) => {
if (saRequestBody.stop === null) {
return [];
}
return saRequestBody.stop;
},
},
stream: {
param: 'stream',
default: false,
},
user: {
param: 'metadata.user_id',
},
};
// TODO: The token calculation is wrong atm
export const anthropicCompleteResponseTransform: ResponseTransformFunction = (
aiProviderResponseBody,
aiProviderResponseStatus,
) => {
if (aiProviderResponseStatus !== 200) {
const errorResponse = anthropicErrorResponseTransform(
aiProviderResponseBody as Record<string, unknown>,
);
if (errorResponse) return errorResponse;
}
const response =
aiProviderResponseBody as unknown as AnthropicCompleteResponse;
if ('completion' in response) {
const responseObject: CompletionResponseBody = {
id: response.log_id,
object: 'text_completion',
created: Math.floor(Date.now() / 1000),
model: response.model,
choices: [
{
text: response.completion,
index: 0,
logprobs: null,
finish_reason: response.stop_reason as CompletionFinishReason,
},
],
};
return responseObject;
}
return generateInvalidProviderResponseError(
response as unknown as Record<string, unknown>,
AIProvider.ANTHROPIC,
);
};
export const anthropicCompleteStreamChunkTransform: ResponseChunkStreamTransformFunction =
(responseChunk) => {
let chunk = responseChunk.trim();
if (chunk.startsWith('event: ping')) {
return '';
}
chunk = chunk.replace(/^event: completion[\r\n]*/, '');
chunk = chunk.replace(/^data: /, '');
chunk = chunk.trim();
if (chunk === '[DONE]') {
return chunk;
}
const parsedChunk: AnthropicCompleteResponse = JSON.parse(chunk);
return `data: ${JSON.stringify({
id: parsedChunk.log_id,
object: 'text_completion',
created: Math.floor(Date.now() / 1000),
model: parsedChunk.model,
provider: 'anthropic',
choices: [
{
text: parsedChunk.completion,
index: 0,
logprobs: null,
finish_reason: parsedChunk.stop_reason,
},
],
})}\n\n`;
};
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