> ## Documentation Index > Fetch the complete documentation index at: https://docs.evolink.ai/llms.txt > Use this file to discover all available pages before exploring further. # Gemini 3.1 Pro - OpenAI SDK - Quick Start > - Call Gemini-3.1-pro model using OpenAI SDK format - Synchronous processing mode, returns conversation content in real-time - Minimal parameters for quick start - 💡 Need more features? Check [Full API Reference](./openai-sdk-reference) **BaseURL**: The default BaseURL is `https://direct.evolink.ai`, which has better support for text models and long-lived connections. `https://api.evolink.ai` is the primary endpoint for multimodal services and serves as a fallback address for text models. ## OpenAPI ````yaml /en/api-manual/language-series/gemini-3.1-pro/openai-sdk/openai-sdk-quickstart.json POST /v1/chat/completions openapi: 3.1.0 info: title: Gemini-3.1-pro Quick Start description: >- Get started with Gemini-3.1-pro chat API in 5 minutes for your first AI conversation license: name: MIT version: 1.0.0 servers: - url: https://direct.evolink.ai description: Production (recommended) - url: https://api.evolink.ai description: Alternative URL security: - bearerAuth: [] tags: - name: Chat Completion description: AI chat completion related APIs paths: /v1/chat/completions: post: tags: - Chat Completion summary: Gemini-3.1-pro Quick Chat description: >- - Call Gemini-3.1-pro model using OpenAI SDK format - Synchronous processing mode, returns conversation content in real-time - Minimal parameters for quick start - 💡 Need more features? Check [Full API Reference](./openai-sdk-reference) operationId: createChatCompletionQuick requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/ChatCompletionQuickRequest' responses: '200': description: Chat completion generated successfully content: application/json: schema: $ref: '#/components/schemas/ChatCompletionResponse' '400': description: Invalid request parameters content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: error: code: 400 message: Invalid request parameters type: invalid_request_error '401': description: Unauthorized, invalid or expired token content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: error: code: 401 message: Invalid or expired token type: authentication_error '402': description: Insufficient quota, recharge required content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: error: code: 402 message: Insufficient quota type: insufficient_quota_error fallback_suggestion: https://evolink.ai/dashboard/billing '403': description: Access denied content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: error: code: 403 message: Access denied for this model type: permission_error param: model '404': description: Resource not found content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: error: code: 404 message: Specified model not found type: not_found_error param: model fallback_suggestion: gemini-3.1-pro-preview '429': description: Rate limit exceeded content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: error: code: 429 message: Rate limit exceeded type: rate_limit_error fallback_suggestion: retry after 60 seconds '500': description: Internal server error content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: error: code: 500 message: Internal server error type: internal_server_error fallback_suggestion: try again later '502': description: Upstream service error content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: error: code: 502 message: Upstream AI service unavailable type: upstream_error fallback_suggestion: try different model '503': description: Service temporarily unavailable content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: error: code: 503 message: Service temporarily unavailable type: service_unavailable_error fallback_suggestion: retry after 30 seconds components: schemas: ChatCompletionQuickRequest: type: object required: - model - messages properties: model: type: string description: Chat model name enum: - gemini-3.1-pro-preview default: gemini-3.1-pro-preview example: gemini-3.1-pro-preview messages: type: array description: List of chat messages items: $ref: '#/components/schemas/MessageSimple' minItems: 1 example: - role: user content: Hello, introduce yourself ChatCompletionResponse: type: object properties: id: type: string description: Unique identifier for the chat completion example: chatcmpl-20251010015944503180122WJNB8Eid model: type: string description: Model name actually used example: gemini-3.1-pro-preview object: type: string enum: - chat.completion description: Response type example: chat.completion created: type: integer description: Creation timestamp example: 1760032810 choices: type: array description: List of chat completion choices items: $ref: '#/components/schemas/Choice' usage: $ref: '#/components/schemas/Usage' ErrorResponse: type: object properties: error: type: object properties: code: type: integer description: HTTP status error code message: type: string description: Error description type: type: string description: Error type param: type: string description: Related parameter name fallback_suggestion: type: string description: Suggestion when error occurs MessageSimple: type: object required: - role - content properties: role: type: string description: Message role enum: - user content: type: string description: Message content (plain text) Choice: type: object properties: index: type: integer description: Choice index example: 0 message: $ref: '#/components/schemas/AssistantMessage' finish_reason: type: string description: Finish reason enum: - stop - length - content_filter example: stop Usage: type: object description: Token usage statistics properties: prompt_tokens: type: integer description: Number of tokens in input content example: 13 completion_tokens: type: integer description: Number of tokens in output content example: 1891 total_tokens: type: integer description: Total number of tokens example: 1904 prompt_tokens_details: type: object description: Detailed input token information properties: cached_tokens: type: integer description: Number of cached tokens hit example: 0 text_tokens: type: integer description: Number of text tokens example: 13 audio_tokens: type: integer description: Number of audio tokens example: 0 image_tokens: type: integer description: Number of image tokens example: 0 completion_tokens_details: type: object description: Detailed output token information properties: text_tokens: type: integer description: Number of text tokens example: 0 audio_tokens: type: integer description: Number of audio tokens example: 0 reasoning_tokens: type: integer description: Number of reasoning tokens example: 1480 input_tokens: type: integer description: Number of input tokens (compatibility field) example: 0 output_tokens: type: integer description: Number of output tokens (compatibility field) example: 0 input_tokens_details: type: object nullable: true description: Detailed input token information (compatibility field) example: null AssistantMessage: type: object properties: role: type: string description: Message sender role enum: - assistant example: assistant content: type: string description: AI response message content example: |- Note: This is sample code! Hello! I'm pleased to introduce myself. I'm a Large Language Model, trained and developed by Google... securitySchemes: bearerAuth: type: http scheme: bearer description: >- ##All APIs require Bearer Token authentication## **Get API Key:** Visit [API Key Management Page](https://evolink.ai/dashboard/keys) to get your API Key **Add to request header:** ``` Authorization: Bearer YOUR_API_KEY ``` ````