# Nagata99999/Affine-5CnxEmj5NAAZTVRquPvcK9Wr5GKjYtiJKYL5PYUAmdreKpH3 > Nagata99999/Affine-5CnxEmj5NAAZTVRquPvcK9Wr5GKjYtiJKYL5PYUAmdreKpH3 This file is intended for AI coding agents wiring an application to this specific Chutes model. ## Important URLs - Model page: https://chutes.ai/app/chute/nagata3-nagata99999-affine-5cnxemj5naaztvrqupvck9wr5gkjyti - Model llms.txt: https://chutes.ai/app/chute/nagata3-nagata99999-affine-5cnxemj5naaztvrqupvck9wr5gkjyti/llms.txt - Global Chutes llms.txt: https://chutes.ai/llms.txt - Full Chutes docs export: https://chutes.ai/llms-full.txt - OpenAPI schema: https://api.chutes.ai/openapi.json ## Model Identifiers - Name: `Nagata99999/Affine-5CnxEmj5NAAZTVRquPvcK9Wr5GKjYtiJKYL5PYUAmdreKpH3` - Chute ID: `07fa5a78-dd34-553b-9011-ff8a6e7fe238` - Slug: `nagata3-nagata99999-affine-5cnxemj5naaztvrqupvck9wr5gkjyti` - Owner: `nagata3` ## Authentication - Use `Authorization: Bearer $CHUTES_API_KEY` for inference calls. - Send JSON request bodies with `Content-Type: application/json` unless the endpoint documentation says otherwise. - The request body is FLAT — send the request fields at the top level (no `input_args`/`args` wrapper). - This model is served on the shared OpenAI-compatible gateway. Set the request `model` field to the exact Name above (`Nagata99999/Affine-5CnxEmj5NAAZTVRquPvcK9Wr5GKjYtiJKYL5PYUAmdreKpH3`), and use base URL `https://llm.chutes.ai/v1`. - For base64 media fields, send raw base64 strings in API requests. The web playground may use temporary Blob upload references internally for large files before proxying to Chutes. ## Endpoints ### 1. POST /v1/chat/completions - Base URL: `https://llm.chutes.ai` - Output content type: `application/json` - Streaming: yes Request fields: - `seed` (integer, optional) Default: 42. - `model` (string, optional) Default: "Nagata99999/Affine-5CnxEmj5NAAZTVRquPvcK9Wr5GKjYtiJKYL5PYUAmdreKpH3". - `stream` (boolean, optional) Default: true. - `messages` (array, optional) Default: [{"role":"user","content":""}]. - `max_tokens` (integer, optional) Default: 1024. - `temperature` (number, optional) Default: 0.7. Example call: ```bash curl -X POST "https://llm.chutes.ai/v1/chat/completions" \ -H "Authorization: Bearer $CHUTES_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "Nagata99999/Affine-5CnxEmj5NAAZTVRquPvcK9Wr5GKjYtiJKYL5PYUAmdreKpH3", "messages": [ { "role": "user", "content": "Hello!" } ], "stream": true, "max_tokens": 1024, "temperature": 0.7 }' ``` ### 2. POST /v1/completions - Base URL: `https://llm.chutes.ai` - Output content type: `application/json` - Streaming: yes Request fields: - `seed` (integer, optional) Default: 42. - `model` (string, optional) Default: "Nagata99999/Affine-5CnxEmj5NAAZTVRquPvcK9Wr5GKjYtiJKYL5PYUAmdreKpH3". - `prompt` (string, required) - `stream` (boolean, optional) Default: true. - `max_tokens` (integer, optional) Default: 1024. - `temperature` (number, optional) Default: 0.7. Example call: ```bash curl -X POST "https://llm.chutes.ai/v1/completions" \ -H "Authorization: Bearer $CHUTES_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "seed": 42, "model": "Nagata99999/Affine-5CnxEmj5NAAZTVRquPvcK9Wr5GKjYtiJKYL5PYUAmdreKpH3", "prompt": "a serene mountain lake at sunset", "stream": false, "max_tokens": 1024, "temperature": 0.7, "min_p": 0, "top_k": -1, "top_p": 1, "logprobs": false, "ignore_eos": false, "min_tokens": 0, "top_logprobs": 0, "length_penalty": 1, "use_beam_search": false, "presence_penalty": 0, "frequency_penalty": 0, "repetition_penalty": 1, "skip_special_tokens": true, "include_stop_str_in_output": false, "spaces_between_special_tokens": true }' ``` ### 3. POST /v1/chat/completions - Base URL: `https://llm.chutes.ai` - Output content type: `application/json` Request fields: - `seed` (integer, optional) Default: 42. - `model` (string, optional) Default: "Nagata99999/Affine-5CnxEmj5NAAZTVRquPvcK9Wr5GKjYtiJKYL5PYUAmdreKpH3". - `stream` (boolean, optional) Default: false. - `messages` (array, optional) Default: [{"role":"user","content":""}]. - `max_tokens` (integer, optional) Default: 1024. - `temperature` (number, optional) Default: 0.7. Example call: ```bash curl -X POST "https://llm.chutes.ai/v1/chat/completions" \ -H "Authorization: Bearer $CHUTES_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "Nagata99999/Affine-5CnxEmj5NAAZTVRquPvcK9Wr5GKjYtiJKYL5PYUAmdreKpH3", "messages": [ { "role": "user", "content": "Hello!" } ], "stream": false, "max_tokens": 1024, "temperature": 0.7 }' ``` ### 4. POST /v1/completions - Base URL: `https://llm.chutes.ai` - Output content type: `application/json` Request fields: - `seed` (integer, optional) Default: 42. - `model` (string, optional) Default: "Nagata99999/Affine-5CnxEmj5NAAZTVRquPvcK9Wr5GKjYtiJKYL5PYUAmdreKpH3". - `prompt` (string, required) - `stream` (boolean, optional) Default: false. - `max_tokens` (integer, optional) Default: 1024. - `temperature` (number, optional) Default: 0.7. Example call: ```bash curl -X POST "https://llm.chutes.ai/v1/completions" \ -H "Authorization: Bearer $CHUTES_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "seed": 42, "model": "Nagata99999/Affine-5CnxEmj5NAAZTVRquPvcK9Wr5GKjYtiJKYL5PYUAmdreKpH3", "prompt": "a serene mountain lake at sunset", "stream": false, "max_tokens": 1024, "temperature": 0.7, "min_p": 0, "top_k": -1, "top_p": 1, "logprobs": false, "ignore_eos": false, "min_tokens": 0, "top_logprobs": 0, "length_penalty": 1, "use_beam_search": false, "presence_penalty": 0, "frequency_penalty": 0, "repetition_penalty": 1, "skip_special_tokens": true, "include_stop_str_in_output": false, "spaces_between_special_tokens": true }' ``` ### 5. GET /v1/models - Base URL: `https://llm.chutes.ai` - Output content type: `application/json` Request fields: Example call: ```bash curl -X GET "https://llm.chutes.ai/v1/models" \ -H "Authorization: Bearer $CHUTES_API_KEY" \ -H "Content-Type: application/json" \ -d '{}' ``` ## Agent Integration Checklist - Pick the endpoint path that matches the desired task. - Set `CHUTES_API_KEY` in the server-side environment only. - Validate required fields before sending requests. - For media models, keep file upload, base64 conversion, and output preview/download handling explicit in the app UI.