File size: 4,255 Bytes
f56a29b | 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 | /**
* AI SDK Adapter for LangGraph
*
* Provides LangChain-compatible interface for LLM calls.
* Uses the unified callLLM / streamLLM layer which goes through
* Vercel AI SDK, supporting all providers (OpenAI, Anthropic, Google, etc.).
*/
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
import { BaseMessage, HumanMessage, AIMessage, SystemMessage } from '@langchain/core/messages';
import { CallbackManagerForLLMRun } from '@langchain/core/callbacks/manager';
import { ChatResult } from '@langchain/core/outputs';
import type { LanguageModel } from 'ai';
import { callLLM, streamLLM } from '@/lib/ai/llm';
import type { ThinkingConfig } from '@/lib/types/provider';
import { createLogger } from '@/lib/logger';
const log = createLogger('AISdkAdapter');
/**
* Stream chunk types for streaming generation
*/
export type StreamChunk =
| { type: 'delta'; content: string }
| {
type: 'tool_calls';
toolCalls: {
id: string;
index: number;
type: 'function';
function: { name: string; arguments: string };
}[];
}
| { type: 'done'; content: string };
/**
* Adapter to use any AI SDK LanguageModel with LangGraph
*
* Accepts a LanguageModel instance (from getModel()) instead of raw
* API credentials, enabling support for all providers.
*/
export class AISdkLangGraphAdapter extends BaseChatModel {
private languageModel: LanguageModel;
private thinking?: ThinkingConfig;
constructor(languageModel: LanguageModel, thinking?: ThinkingConfig) {
super({});
this.languageModel = languageModel;
this.thinking = thinking;
}
_llmType(): string {
return 'ai-sdk';
}
_combineLLMOutput() {
return {};
}
/**
* Convert LangChain messages to AI SDK message format
*/
private convertMessages(
messages: BaseMessage[],
): { role: 'system' | 'user' | 'assistant'; content: string }[] {
return messages.map((msg) => {
if (msg instanceof HumanMessage) {
return { role: 'user' as const, content: msg.content as string };
} else if (msg instanceof AIMessage) {
return { role: 'assistant' as const, content: msg.content as string };
} else if (msg instanceof SystemMessage) {
return { role: 'system' as const, content: msg.content as string };
} else {
return { role: 'user' as const, content: msg.content as string };
}
});
}
async _generate(
messages: BaseMessage[],
_options?: this['ParsedCallOptions'],
_runManager?: CallbackManagerForLLMRun,
): Promise<ChatResult> {
const aiMessages = this.convertMessages(messages);
try {
const result = await callLLM(
{
model: this.languageModel,
messages: aiMessages,
},
'chat-adapter',
undefined,
this.thinking,
);
const content = result.text || '';
log.info('[AI SDK Adapter] Response:', {
textLength: content.length,
});
// Create AI message
const aiMessage = new AIMessage({ content });
return {
generations: [
{
text: content,
message: aiMessage,
},
],
llmOutput: {},
};
} catch (error) {
log.error('[AI SDK Adapter Error]', error);
throw error;
}
}
/**
* Stream generate with text deltas
*
* Yields chunks of text as they arrive, then yields done with full content.
* Uses streamLLM which goes through Vercel AI SDK's streamText.
*/
async *streamGenerate(
messages: BaseMessage[],
options?: { tools?: Record<string, unknown>; signal?: AbortSignal },
): AsyncGenerator<StreamChunk> {
const aiMessages = this.convertMessages(messages);
const result = streamLLM(
{
model: this.languageModel,
messages: aiMessages,
abortSignal: options?.signal,
},
'chat-adapter-stream',
this.thinking,
);
let fullContent = '';
for await (const chunk of result.textStream) {
if (chunk) {
fullContent += chunk;
yield { type: 'delta', content: chunk };
}
}
// Yield done with full content
yield { type: 'done', content: fullContent };
}
}
|