OpenAI

AI 与机器学习

访问 OpenAI 模型、微调数据集并管理您的 API 使用情况--Neotask 通过 Neotask 统一运行。

无需编写代码即可调用 GPT 模型、DALL·E、Whisper 和 Embeddings
监控整个组织的 Token 使用量、成本和速率限制
通过简单对话管理微调任务和模型部署

你能做什么

按需模型推理

从单个指令调用任何 OpenAI 模型 - GPT-4o、o1、DALL·E 3、Whisper、TTS。传递结构化提示、设置温度和最大令牌，并将结果直接传送回您的工作流程。

使用情况和成本监控

向 Neotask 询问您的 OpenAI 支出（按型号、日期范围或团队成员）的明细。在达到预算上限之前发现失控的 API 调用。

微调工作管理

上传训练文件、启动微调运行、监控作业状态以及下载已完成的模型 - 所有这些都无需接触 OpenAI 仪表板。

嵌入生成

为文档、代码片段或搜索查询生成向量嵌入。在同一对话中将输出直接传送到矢量数据库（如 Pinecone 或 Weaviate）中。

API 密钥和组织管理

列出活跃的 API 密钥、检查速率限制层并审查组织成员 - 通过自然语言命令保持您的 OpenAI 帐户整洁。

尝试询问

“使用 GPT-4o 总结这份 10 页的文档，并将其控制在 200 字以内”
“这个月我们在 OpenAI 上花了多少钱，按模型细分？”
“使用这个 JSONL 文件开始微调工作，完成后通知我”
“为这 100 个产品描述生成嵌入并将它们作为 JSON 数组返回”
“我们当前的 GPT-4 速率限制等级是多少？”
“使用 Whisper 转录此音频文件”
“创建 DALL·E 形象：金融科技初创公司的简约徽标，白色背景”
“列出我们组织中所有经过微调的模型及其创建时间”

专业提示

通过 Neotask 路由批量嵌入作业，以便它可以自动批量请求并保持在速率限制范围内
要求提供每周成本报告，以便在模型错误路由复杂化之前发现它
将 OpenAI 微调与内部数据管道相结合 - 描述数据集形状并让 Neotask 处理上传格式
在将微调推广到生产之前，使用 Neotask 并排比较两个模型版本的输出
将您的 OpenAI 组织级 API 密钥存储在安全保管库中；使用每个工作流程的项目密钥进行清晰的成本归因

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Plans

Free

$0/mo

Download without a card and start for free.

Individual

$50/mo

The full personal agent platform for one person.

Business

$100/mo

One company workspace with room to add your team.

Enterprise

$200/mo

Multiple workspaces and capacity for larger teams.

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