class HeliconeManualLogger {
constructor(opts: IHeliconeManualLogger);
}

type IHeliconeManualLogger = {
apiKey: string;
headers?: Record<string, string>;
loggingEndpoint?: string; // defaults to https://api.hconeai.com/custom/v1/log
};

class HeliconeLogBuilder {
  constructor(
    logger: HeliconeManualLogger,
    request: HeliconeLogRequest,
    additionalHeaders?: Record<string, string>
  );

  setError(error: any): void;
  toReadableStream<T>(stream: Stream<T>): ReadableStream;
  setResponse(body: string): void;
  sendLog(): Promise<void>;
}

logRequest<T>(
    request: HeliconeLogRequest,
    operation: (resultRecorder: HeliconeResultRecorder) => Promise<T>,
    additionalHeaders?: Record<string, string>
  ): Promise<T>

type HeliconeLogRequest = ILogRequest | HeliconeCustomEventRequest; // ILogRequest is the type for the request object for custom model logging

// The name and structure of the prompt field depends on the model you are using.
// Eg: for chat models it is named "messages", for embeddings models it is named "input".
// Hence, the only enforced type is `model`, you need still add the respective prompt property for your model.
// You may also add more properties (eg: temperature, stop reason etc)
type ILogRequest = {
  model: string;
  [key: string]: any;
};

class HeliconeResultRecorder {
  private results: Record<string, any> = {};

  appendResults(data: Record<string, any>): void {
    this.results = { ...this.results, ...data };
  }

  getResults(): Record<string, any> {
    return this.results;
  }
}

logRequest<T>(
  request: HeliconeLogRequest,
  operation: (resultRecorder: HeliconeResultRecorder) => Promise<T>,
  additionalHeaders?: Record<string, string>
): Promise<T>

const result = await helicone.logRequest(
  requestBody,
  async (resultRecorder) => {
    const response = await llmProvider.createCompletion(requestBody);
    resultRecorder.appendResults(response);
    return response;
  },
  { "Helicone-User-Id": userId }
);

logStream<T>(
  request: HeliconeLogRequest,
  operation: (resultRecorder: HeliconeStreamResultRecorder) => Promise<T>,
  additionalHeaders?: Record<string, string>
): Promise<T>

const stream = await helicone.logStream(
  requestBody,
  async (resultRecorder) => {
    const response = await llmProvider.createChatCompletion({
      stream: true,
      ...requestBody,
    });
    const [stream1, stream2] = response.tee();
    resultRecorder.attachStream(stream2.toReadableStream());
    return stream1;
  },
  { "Helicone-User-Id": userId }
);

logSingleStream(
  request: HeliconeLogRequest,
  stream: ReadableStream,
  additionalHeaders?: Record<string, string>
): Promise<void>

const response = await llmProvider.createChatCompletion({
  stream: true,
  ...requestBody,
});
const stream = response.toReadableStream();
const [streamForUser, streamForLogging] = stream.tee();

helicone.logSingleStream(requestBody, streamForLogging, {
  "Helicone-User-Id": userId,
});

return streamForUser;

logSingleRequest(
  request: HeliconeLogRequest,
  body: string,
  options: {
    additionalHeaders?: Record<string, string>;
    latencyMs?: number;
  }
): Promise<void>

const response = await llmProvider.createCompletion(requestBody);
await helicone.logSingleRequest(requestBody, JSON.stringify(response), {
  additionalHeaders: { "Helicone-User-Id": userId },
});

logBuilder(
  request: HeliconeLogRequest,
  additionalHeaders?: Record<string, string>
): HeliconeLogBuilder

// Create a log builder
const heliconeLogBuilder = helicone.logBuilder(requestBody, {
  "Helicone-User-Id": userId,
});

try {
  // Make the LLM API call
  const response = await llmProvider.createChatCompletion({
    stream: true,
    ...requestBody,
  });

  // Convert the API response to a readable stream and return it
  return new Response(heliconeLogBuilder.toReadableStream(response));
} catch (error) {
  // Record any errors that occur
  heliconeLogBuilder.setError(error);
  throw error;
} finally {
  // Send the log (can be used with Vercel's "after" function)
  await heliconeLogBuilder.sendLog();
}

import { HeliconeManualLogger } from "@helicone/helpers";

// Initialize the Helicone logger
const heliconeLogger = new HeliconeManualLogger({
  apiKey: process.env.HELICONE_API_KEY!,
  headers: {}, // You can add custom headers here
});

// Your custom model API call that returns a stream
const response = await customModelAPI.generateStream(prompt);

// If your API supports splitting the stream
const [stream1, stream2] = response.tee();

// Log the stream to Helicone using the async stream parser
heliconeLogger.logStream(requestBody, async (resultRecorder) => {
  resultRecorder.attachStream(stream1);
});

// Process the stream for your application
for await (const chunk of stream2) {
  console.log(chunk);
}

import { HeliconeManualLogger } from "@helicone/helpers";
import { after } from "next/server";
import Together from "together-ai";

export async function POST(request: Request) {
  const { prompt } = await request.json();

  const together = new Together({ apiKey: process.env.TOGETHER_API_KEY });
  const helicone = new HeliconeManualLogger({
    apiKey: process.env.HELICONE_API_KEY!,
  });

  // Example with non-streaming response
  const nonStreamingBody = {
    model: "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo",
    messages: [{ role: "user", content: prompt }],
    stream: false,
  };

  const completion = await together.chat.completions.create(nonStreamingBody);

  // Log non-streaming response after sending the response to the client
  after(
    helicone.logSingleRequest(nonStreamingBody, JSON.stringify(completion))
  );

  // Example with streaming response
  const streamingBody = {
    model: "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo",
    messages: [{ role: "user", content: prompt }],
    stream: true,
  };

  const response = await together.chat.completions.create(streamingBody);
  const [stream1, stream2] = response.tee();

  // Log streaming response after sending the response to the client
  after(helicone.logSingleStream(streamingBody, stream2.toReadableStream()));

  return new Response(stream1.toReadableStream());
}