> ## Documentation Index > Fetch the complete documentation index at: https://docs.infery.ai/llms.txt > Use this file to discover all available pages before exploring further. # Chat completions > POST /v1/chat/completions — OpenAI-compatible text and multimodal chat. Drop-in OpenAI-compatible chat endpoint. Supports streaming, tool calls, JSON mode, vision, PDF, audio input and **Files API `file_id` references**. ## Minimal example ```bash curl theme={null} curl https://api.infery.ai/v1/chat/completions \ -H "Authorization: Bearer $INFERY_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "gpt-4o", "messages": [ {"role": "user", "content": "Summarise Node.js streams in 2 sentences"} ] }' ``` ```python python theme={null} from openai import OpenAI client = OpenAI(api_key=API_KEY, base_url="https://api.infery.ai/v1") resp = client.chat.completions.create( model="gpt-4o", messages=[{"role": "user", "content": "Hi"}], ) ``` ```typescript node theme={null} import OpenAI from 'openai'; const client = new OpenAI({ apiKey: process.env.INFERY_API_KEY, baseURL: 'https://api.infery.ai/v1' }); const resp = await client.chat.completions.create({ model: 'gpt-4o', messages: [{ role: 'user', content: 'Hi' }], }); ``` ## Streaming Add `"stream": true`. Response is Server-Sent Events (`text/event-stream`). Each chunk is `data: {...}\n\n`; the stream ends with `data: [DONE]\n\n`. The **final chunk before `[DONE]`** carries usage info and Infery-specific `credits_used`: ``` data: {"choices":[{"delta":{"content":"..."}}]} data: {"choices":[],"usage":{"prompt_tokens":42,"completion_tokens":128}} data: {"choices":[],"usage":{...},"credits_used":2} data: [DONE] ``` OpenAI SDKs ignore chunks with empty `choices`, so `credits_used` is a non-breaking extension. ## Multimodal content Pass arrays in `content`: ```json theme={null} { "model": "gpt-4o", "messages": [{ "role": "user", "content": [ {"type": "text", "text": "What's in this image?"}, {"type": "image_url", "image_url": {"url": "https://example.com/photo.jpg"}} ] }] } ``` Supported block types: * `text` * `image_url` — HTTP URL or base64 `data:` URI * `input_audio` — inline base64 audio with `format` (wav/mp3/pcm16/webm) * `file` — inline `data` + `mime_type` **or** `file_id` reference ([Files API](/api-reference/files)) ### Using a Files API reference ```json theme={null} { "content": [ {"type": "text", "text": "Review this PDF"}, {"type": "file", "file_id": "file_abc123..."} ] } ``` The gateway resolves `file_id` to bytes on the server, injects them into the provider call, and returns a clear 400 if the id doesn't exist or is out of your workspace. ## Tool calls Works exactly like OpenAI's spec — `tools`, `tool_choice`, `function` schema and `tool` role messages. Every chat-capable model on Infery that supports tools honours the same format. ## JSON mode ```json theme={null} {"response_format": {"type": "json_object"}} ``` Or with a schema (Structured Outputs): ```json theme={null} { "response_format": { "type": "json_schema", "json_schema": { "schema": { ... }, "strict": true } } } ``` ## Vision and PDFs Models with `supportsVision: true` accept images directly. For PDFs, models with `supportsPdf: true` read them natively. Others get an **automatic PDF-to-image conversion** on the gateway (plus text extraction) — you pay a small extra fee per page (see billing), no code changes required. ## Parameters Full OpenAI parameter set: `temperature`, `top_p`, `presence_penalty`, `frequency_penalty`, `max_tokens`, `stop`, `seed`, `stream`, `tools`, `tool_choice`, `response_format`. Plus model-specific: * `top_k` — Gemini and some OSS models ## Response headers * `x-request-id` * `x-credits-used` * `x-model-used` (when fallback fires) * `x-fallback-from`, `x-fallback-depth` ## OpenAPI ````yaml openapi.json POST /v1/chat/completions openapi: 3.0.0 info: title: Infery Gateway description: >- Infery Inference Gateway — OpenAI-compatible API for LLMs, embeddings, images, audio, and video version: '1.0' contact: {} servers: - url: https://api.infery.ai description: Production - url: http://localhost:3001 description: Local security: [] tags: [] paths: /v1/chat/completions: post: tags: - Chat Completions summary: Create chat completion operationId: ChatController_completions parameters: - name: x-request-id in: header description: Optional request ID for tracking required: false schema: type: string requestBody: required: true content: application/json: schema: type: object required: - model - messages properties: model: type: string description: Model ID example: gpt-4o messages: type: array items: type: object properties: role: type: string enum: - system - user - assistant - tool content: type: string required: - role - content temperature: type: number minimum: 0 maximum: 2 max_tokens: type: integer top_p: type: number minimum: 0 maximum: 1 top_k: type: integer description: Top-K sampling (Google Gemini) presence_penalty: type: number minimum: -2 maximum: 2 description: Presence penalty (OpenAI, Google Gemini) frequency_penalty: type: number minimum: -2 maximum: 2 description: Frequency penalty (OpenAI, Google Gemini) seed: type: integer description: Seed for deterministic output (OpenAI, Google Gemini) stream: type: boolean default: false stop: oneOf: - type: string - type: array items: type: string tools: type: array items: type: object tool_choice: {} response_format: type: object responses: '200': description: >- Chat completion result. When stream=true, returns SSE (text/event-stream) where each data chunk is a `chat.completion.chunk`; the final chunk before `[DONE]` carries `usage` and `credits_used`. content: application/json: schema: type: object properties: id: type: string example: chatcmpl-abc123 object: type: string example: chat.completion created: type: integer example: 1713204900 model: type: string example: gpt-4o choices: type: array items: type: object properties: index: type: integer example: 0 message: type: object properties: role: type: string example: assistant content: type: string example: Hello! How can I help you today? tool_calls: type: array items: type: object description: Present when the model invokes tools finish_reason: type: string enum: - stop - length - tool_calls - content_filter example: stop usage: type: object properties: prompt_tokens: type: integer example: 42 completion_tokens: type: integer example: 128 total_tokens: type: integer example: 170 credits_used: type: integer example: 2 description: >- Credits deducted from the workspace balance for this request '400': description: Invalid request content: application/json: schema: $ref: '#/components/schemas/ErrorResponseDto' '401': description: Unauthorized — invalid or missing API key content: application/json: schema: $ref: '#/components/schemas/ErrorResponseDto' '404': description: Model not found content: application/json: schema: $ref: '#/components/schemas/ErrorResponseDto' security: - ApiKey: [] components: schemas: ErrorResponseDto: type: object properties: error: $ref: '#/components/schemas/ErrorDetailDto' required: - error ErrorDetailDto: type: object properties: message: type: string example: Model not found description: Human-readable error message type: type: string example: invalid_request_error description: Error category enum: - invalid_request_error - authentication_error - permission_error - quota_exceeded - rate_limit_error - server_error code: type: object example: model_not_found nullable: true description: Stable machine-readable error code param: type: object example: model nullable: true description: >- Name of the request parameter that triggered the error, if applicable required: - message - type - code - param securitySchemes: ApiKey: type: apiKey in: header name: Authorization description: 'API key in format: Bearer inf_***' ````