Press n or j to go to the next uncovered block, b, p or k for the previous block.
| 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 | 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 1x 1x 1x 1x 1x 1x 1x | import { googleErrorResponseTransform } from '@api/ai-providers/google/chat-complete';
import { generateInvalidProviderResponseError } from '@api/utils/ai-provider';
import type {
AIProviderFunctionConfig,
ResponseTransformFunction,
} from '@shared/types/ai-providers/config';
import {
ChatCompletionFinishReason,
type ChatCompletionRequestBody,
type ChatCompletionResponseBody,
} from '@shared/types/api/routes/chat-completions-api';
import { ChatCompletionMessageRole } from '@shared/types/api/routes/shared/messages';
import { AIProvider } from '@shared/types/constants';
// TODOS: 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 palmChatCompleteConfig: AIProviderFunctionConfig = {
model: {
param: 'model',
required: true,
default: 'model/chat-bison-001',
},
messages: {
param: 'prompt',
default: '',
transform: (saRequestBody: ChatCompletionRequestBody) => {
const { messages } = saRequestBody;
const palmMessages = messages?.map((message) => ({
author:
message.role === ChatCompletionMessageRole.DEVELOPER
? 'system'
: message.role,
content: message.content,
}));
const prompt = {
messages: palmMessages,
// examples, // TODO: Move to header config
// context, // TODO: Move to header config
};
return prompt;
},
},
temperature: {
param: 'temperature',
default: 1,
min: 0,
max: 1,
},
top_p: {
param: 'topP',
default: 1,
min: 0,
max: 1,
},
top_k: {
param: 'topK',
default: 1,
min: 0,
max: 1,
},
n: {
param: 'candidateCount',
default: 1,
min: 1,
max: 8,
},
max_tokens: {
param: 'maxOutputTokens',
default: 100,
min: 1,
},
max_completion_tokens: {
param: 'maxOutputTokens',
default: 100,
min: 1,
},
stop: {
param: 'stopSequences',
},
};
export const palmChatCompleteResponseTransform: ResponseTransformFunction = (
aiProviderResponseBody,
aiProviderResponseStatus,
) => {
if (aiProviderResponseStatus !== 200) {
const errorResponse = googleErrorResponseTransform(
aiProviderResponseBody,
AIProvider.PALM,
);
if (errorResponse) return errorResponse;
}
if ('candidates' in aiProviderResponseBody) {
const candidates = aiProviderResponseBody.candidates as {
content: string;
}[];
const palmResponse: ChatCompletionResponseBody = {
id: Date.now().toString(),
object: 'chat.completion',
created: Math.floor(Date.now() / 1000),
model: 'Unknown',
choices:
candidates.map((generation, index) => ({
message: {
role: ChatCompletionMessageRole.ASSISTANT,
content: generation.content ?? '',
},
index: index,
finish_reason: ChatCompletionFinishReason.LENGTH,
})) ?? [],
};
return palmResponse;
}
return generateInvalidProviderResponseError(
aiProviderResponseBody,
AIProvider.PALM,
);
};
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