OpenAI 모델에 접근하고, 파인튜닝 데이터셋을 관리하고, API 사용량을 추적하세요 - Neotask이 Neotask을 통해 모든 것을 처리합니다.
코드 없이 GPT 모델, DALL·E, Whisper, Embeddings 호출
조직 전체의 토큰 사용량, 비용, 속도 제한 모니터링
평이한 대화로 파인튜닝 작업과 모델 배포 관리
할 수 있는 것
온디맨드 모델 추론
Invoke any OpenAI model - GPT-4o, o1, DALL·E 3, Whisper, TTS - from a single instruction. Pass structured prompts, set temperature and max tokens, and get results piped directly back into your workflow.
Usage and Cost Monitoring
Ask Neotask for a breakdown of your OpenAI spend by model, date range, or team member. Spot runaway API calls before they hit your budget cap.
Fine-Tuning Job Management
Upload training files, kick off fine-tuning runs, monitor job status, and download completed models - all without touching the OpenAI dashboard.
Embedding Generation
Generate vector embeddings for documents, code snippets, or search queries. Pipe the output directly into a vector database like Pinecone or Weaviate in the same conversation.
API Key and Organization Management
List active API keys, check rate limit tiers, and review organization members - keeping your OpenAI account tidy through natural language commands.
이렇게 물어보세요
"Summarize this 10-page document using GPT-4o and keep it under 200 words"
"How much have we spent on OpenAI this month, broken down by model?"
"Start a fine-tuning job with this JSONL file and notify me when it's done"
"Generate embeddings for these 100 product descriptions and return them as a JSON array"
"What's our current rate limit tier for GPT-4?"
"Transcribe this audio file using Whisper"
"Create a DALL·E image: a minimalist logo for a fintech startup, white background"
"List all fine-tuned models in our organization and when they were created"
프로 팁
Route bulk embedding jobs through Neotask so it can auto-batch requests and stay under rate limits
Ask for a weekly cost report to catch model mis-routing before it compounds
Combine OpenAI fine-tuning with your internal data pipeline - describe the dataset shape and let Neotask handle the upload format
Use Neotask to compare outputs from two model versions side by side before promoting a fine-tune to production
Store your OpenAI org-level API key in the secure vault; use project keys per workflow for clean cost attribution