import { ChatParams, ChatMessageRole } from '@memberjunction/ai';
import { OpenAILLM } from '@memberjunction/ai-openai';

const llm = new OpenAILLM('your-api-key');

const params = new ChatParams();
params.model = 'gpt-4';
params.messages = [
    { role: ChatMessageRole.user, content: 'What is the capital of France?' }
];

const result = await llm.ChatCompletion(params);
console.log(result.data.choices[0].message.content);

const params = new ChatParams();
params.model = 'gpt-4';
params.streaming = true;
params.messages = [
    { role: ChatMessageRole.user, content: 'Explain quantum computing' }
];
params.streamingCallbacks = {
    OnContent: (chunk, isComplete) => process.stdout.write(chunk),
    OnComplete: (result) => console.log('\nDone!'),
    OnError: (error) => console.error('Stream error:', error)
};

await llm.ChatCompletion(params);

const paramsArray = [
    { ...baseParams, temperature: 0.3 },
    { ...baseParams, temperature: 0.7 },
    { ...baseParams, temperature: 1.0 }
];

const results = await llm.ChatCompletions(paramsArray, {
    OnCompletion: (result, index) => console.log(`Completion ${index} done`),
    OnAllCompleted: (results) => console.log(`All ${results.length} done`)
});

const params = new ChatParams();
params.model = 'gpt-4o';
params.messages = [
    {
        role: ChatMessageRole.user,
        content: [
            { type: 'text', content: 'What is in this image?' },
            { type: 'image_url', content: 'data:image/png;base64,...' }
        ]
    }
];

import { EmbedTextParams } from '@memberjunction/ai';
import { OpenAIEmbeddings } from '@memberjunction/ai-openai';

const embedder = new OpenAIEmbeddings('your-api-key');
const result = await embedder.EmbedText({
    model: 'text-embedding-ada-002',
    text: 'Sample text to embed'
});
console.log(result.embedding); // number[]

import { GetAIAPIKey } from '@memberjunction/ai';

// Reads from environment: AI_VENDOR_API_KEY__OPENAILLM
const key = GetAIAPIKey('OpenAILLM');

// With runtime override
const key2 = GetAIAPIKey('AnthropicLLM', [
    { driverClass: 'AnthropicLLM', apiKey: 'sk-ant-...' }
]);

import { BaseLLM, ChatParams, ChatResult } from '@memberjunction/ai';

export class MyProviderLLM extends BaseLLM {
    protected async nonStreamingChatCompletion(params: ChatParams): Promise<ChatResult> {
        // Implement provider-specific chat completion
    }

    public async ClassifyText(params: ClassifyParams): Promise<ClassifyResult> {
        // Implement or throw if not supported
    }

    public async SummarizeText(params: SummarizeParams): Promise<SummarizeResult> {
        // Implement or throw if not supported
    }

    // For streaming support, override these:
    public get SupportsStreaming(): boolean { return true; }
    protected async createStreamingRequest(params: ChatParams): Promise<AsyncIterable<unknown>> { /* ... */ }
    protected processStreamingChunk(chunk: unknown): { content: string } { /* ... */ }
    protected finalizeStreamingResponse(content: string, lastChunk: unknown, usage: unknown): ChatResult { /* ... */ }
}