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community node for interacting with the 302.ai chat completion API","maintainers":[{"name":"fengcch","email":"start.ans.w@gmail.com"}],"readme":"# @fengcch/n8n-nodes-302ai-chat\r\n\r\n[![NPM Version](https://img.shields.io/npm/v/@fengcch/n8n-nodes-302ai-chat?style=flat-square)](https://www.npmjs.com/package/@fengcch/n8n-nodes-302ai-chat)\r\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg?style=flat-square)](https://opensource.org/licenses/MIT)\r\n[![N8N Compatibility](https://img.shields.io/badge/N8N-v1.x-blueviolet?style=flat-square)](https://n8n.io)\r\n\r\nThis is an n8n community node for [302.AI](https://302.ai/) AI service integration.\r\n\r\n## Prerequisites\r\n\r\nYou need to have a valid API key from [302.AI](https://302.ai/) to use this node.\r\n\r\n## Installation\r\n\r\n1.  Go to **Settings > Community Nodes** in your n8n instance.\r\n2.  Select **Install** and enter `@fengcch/n8n-nodes-302ai-chat` in the search box.\r\n3.  Click **Install** to add the node to your n8n instance.\r\n\r\n## Configuration\r\n\r\n1.  In your n8n workflow, add the \"302.AI\" node.\r\n2.  In the \"Credentials\" section, click on **Create New**.\r\n3.  Give your credential a name.\r\n4.  Enter your API key from `302.AI` into the **API Key** field.\r\n5.  Click **Save** to create the credential.\r\n\r\n## Usage\r\n\r\n### Chat Operation\r\n\r\n1.  **Model Name or ID**: Select from available 302.ai models\r\n2.  **System Prompt**: (Optional) Provide context for the AI\r\n3.  **Message**: Your input message\r\n4.  **Additional Fields**: Temperature, max tokens, etc.\r\n\r\n### Multimodal Support\r\n- Supports both text and image inputs in chat conversations\r\n- Compatible with vision-capable models for image understanding\r\n- **Image URL**: Optional field to include images in your conversation\r\n- **Supported formats**: HTTP/HTTPS image URLs or base64 encoded images\r\n- **Use cases**: Image analysis, visual question answering, content understanding from images\r\n\r\n## Output\r\n\r\n- **Standard response**: `json.response` contains the model's reply\r\n- **Error handling**: `json.error` for any API issues\r\n\r\n## Examples\r\n\r\n### Basic Chat Example\r\n```json\r\n{\r\n  \"model\": \"gpt-3.5-turbo\",\r\n  \"message\": \"Hello, how can AI help with automation?\",\r\n  \"temperature\": 0.7\r\n}\r\n```\r\n\r\n### Pseudo-stream Mode\r\n\r\n- Enable the **Pseudo-stream Mode** toggle (below Image URL) when the target model only supports streaming responses, for example Qwen3.\r\n- The node consumes the full stream and still returns a single JSON result so you can read the reply from `json.response`.\r\n- If the service emits `reasoning_content`, it is exposed as `json.reasoning` for easier debugging.\r\n\r\n### Multimodal Example (Text + Image)\r\n```json\r\n{\r\n  \"model\": \"gpt-5\",\r\n  \"message\": \"What do you see in this image?\",\r\n  \"imageUrl\": \"https://example.com/image.jpg\",\r\n  \"temperature\": 0.5\r\n}\r\n```\r\n\r\n### Response Example\r\n```json\r\n{\r\n  \"response\": \"AI can help with automation in many ways, including data processing, decision making, content generation, and workflow optimization...\"\r\n}\r\n```\r\n\r\n## License\r\n\r\n[MIT](LICENSE)\r\n","readmeFilename":"README.md"}