> ## Documentation Index > Fetch the complete documentation index at: https://docs.mixpeek.com/docs/llms.txt > Use this file to discover all available pages before exploring further. # Execute Raw Inference > Execute raw inference with provider+model or custom plugin. This endpoint provides direct access to inference services without the retriever framework overhead. Supports two modes: 1. **Provider + Model**: Use standard providers (openai, google, anthropic) 2. **Custom Plugin**: Use your custom inference plugins by inference_name ## Supported Providers - **openai**: GPT models, embeddings, Whisper transcription - **google**: Gemini models, Vertex multimodal embeddings (1408D) - **anthropic**: Claude models ## Examples ### Custom Plugin (by inference_name) ```json { "inference_name": "my_text_embedder_1_0_0", "inputs": {"text": "hello world"}, "parameters": {} } ``` ### Custom Plugin (by feature_uri) ```json { "feature_uri": "mixpeek://my_custom_embedder@1.0.0/embedding", "inputs": {"text": "hello world"}, "parameters": {} } ``` ### Builtin Embedder (by feature_uri) ```json { "feature_uri": "mixpeek://text_extractor@v1/multilingual_e5_large_instruct_v1", "inputs": {"text": "hello world"}, "parameters": {} } ``` ### Chat Completion ```json { "provider": "openai", "model": "gpt-4o-mini", "inputs": {"prompts": ["What is AI?"]}, "parameters": {"temperature": 0.7, "max_tokens": 500} } ``` ### Text Embedding (OpenAI) ```json { "provider": "openai", "model": "text-embedding-3-large", "inputs": {"text": "machine learning"}, "parameters": {} } ``` ### Text Embedding (Google Vertex Multimodal - 1408D) ```json { "provider": "google", "model": "multimodalembedding", "inputs": {"text": "machine learning"}, "parameters": {} } ``` ### Image Embedding (Google Vertex Multimodal - 1408D) ```json { "provider": "google", "model": "multimodalembedding", "inputs": {"image_url": "https://example.com/image.jpg"}, "parameters": {} } ``` ### Image Embedding from Base64 ```json { "provider": "google", "model": "multimodalembedding", "inputs": {"image_base64": ""}, "parameters": {} } ``` ### Video Embedding (Google Vertex Multimodal - 1408D) ```json { "provider": "google", "model": "multimodalembedding", "inputs": {"video_url": "https://example.com/video.mp4"}, "parameters": {} } ``` ### Video Embedding from Base64 ```json { "provider": "google", "model": "multimodalembedding", "inputs": {"video_base64": ""}, "parameters": {} } ``` ### Audio Transcription ```json { "provider": "openai", "model": "whisper-1", "inputs": {"audio_url": "https://example.com/audio.mp3"}, "parameters": {} } ``` ### Vision (Multimodal LLM) ```json { "provider": "openai", "model": "gpt-4o", "inputs": { "prompts": ["Describe this image"], "image_url": "https://example.com/image.jpg" }, "parameters": {"temperature": 0.5} } ``` Args: request: FastAPI request object (populated by middleware) payload: Raw inference request Returns: Inference response with results and metadata Raises: 400 Bad Request: Invalid provider, model, or inputs 401 Unauthorized: Missing or invalid API key 429 Too Many Requests: Rate limit exceeded 500 Internal Server Error: Inference execution failed ## OpenAPI ````yaml post /v1/inference openapi: 3.1.0 info: title: Mixpeek API description: >- This is the Mixpeek API, providing access to various endpoints for data processing and retrieval. termsOfService: https://mixpeek.com/terms contact: name: Mixpeek Support url: https://mixpeek.com/contact email: info@mixpeek.com version: '0.82' servers: - url: https://api.mixpeek.com description: Production security: [] paths: /v1/inference: post: tags: - Inference summary: Execute Raw Inference description: >- Execute raw inference with provider+model or custom plugin. This endpoint provides direct access to inference services without the retriever framework overhead. Supports two modes: 1. **Provider + Model**: Use standard providers (openai, google, anthropic) 2. **Custom Plugin**: Use your custom inference plugins by inference_name ## Supported Providers - **openai**: GPT models, embeddings, Whisper transcription - **google**: Gemini models, Vertex multimodal embeddings (1408D) - **anthropic**: Claude models ## Examples ### Custom Plugin (by inference_name) ```json { "inference_name": "my_text_embedder_1_0_0", "inputs": {"text": "hello world"}, "parameters": {} } ``` ### Custom Plugin (by feature_uri) ```json { "feature_uri": "mixpeek://my_custom_embedder@1.0.0/embedding", "inputs": {"text": "hello world"}, "parameters": {} } ``` ### Builtin Embedder (by feature_uri) ```json { "feature_uri": "mixpeek://text_extractor@v1/multilingual_e5_large_instruct_v1", "inputs": {"text": "hello world"}, "parameters": {} } ``` ### Chat Completion ```json { "provider": "openai", "model": "gpt-4o-mini", "inputs": {"prompts": ["What is AI?"]}, "parameters": {"temperature": 0.7, "max_tokens": 500} } ``` ### Text Embedding (OpenAI) ```json { "provider": "openai", "model": "text-embedding-3-large", "inputs": {"text": "machine learning"}, "parameters": {} } ``` ### Text Embedding (Google Vertex Multimodal - 1408D) ```json { "provider": "google", "model": "multimodalembedding", "inputs": {"text": "machine learning"}, "parameters": {} } ``` ### Image Embedding (Google Vertex Multimodal - 1408D) ```json { "provider": "google", "model": "multimodalembedding", "inputs": {"image_url": "https://example.com/image.jpg"}, "parameters": {} } ``` ### Image Embedding from Base64 ```json { "provider": "google", "model": "multimodalembedding", "inputs": {"image_base64": ""}, "parameters": {} } ``` ### Video Embedding (Google Vertex Multimodal - 1408D) ```json { "provider": "google", "model": "multimodalembedding", "inputs": {"video_url": "https://example.com/video.mp4"}, "parameters": {} } ``` ### Video Embedding from Base64 ```json { "provider": "google", "model": "multimodalembedding", "inputs": {"video_base64": ""}, "parameters": {} } ``` ### Audio Transcription ```json { "provider": "openai", "model": "whisper-1", "inputs": {"audio_url": "https://example.com/audio.mp3"}, "parameters": {} } ``` ### Vision (Multimodal LLM) ```json { "provider": "openai", "model": "gpt-4o", "inputs": { "prompts": ["Describe this image"], "image_url": "https://example.com/image.jpg" }, "parameters": {"temperature": 0.5} } ``` Args: request: FastAPI request object (populated by middleware) payload: Raw inference request Returns: Inference response with results and metadata Raises: 400 Bad Request: Invalid provider, model, or inputs 401 Unauthorized: Missing or invalid API key 429 Too Many Requests: Rate limit exceeded 500 Internal Server Error: Inference execution failed operationId: execute_raw_inference_v1_inference_post parameters: [] requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/RawInferenceRequest' responses: '200': description: Successful Response content: application/json: schema: $ref: '#/components/schemas/RawInferenceResponse' '400': description: Bad Request content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' '401': description: Unauthorized content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' '403': description: Forbidden content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' '404': description: Not Found content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' '422': description: Validation Error content: application/json: schema: $ref: '#/components/schemas/HTTPValidationError' '500': description: Internal Server Error content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' components: schemas: RawInferenceRequest: properties: provider: anyOf: - type: string - type: 'null' title: Provider description: >- Provider name: openai, google, anthropic (required if inference_name not set) examples: - openai - google - anthropic model: anyOf: - type: string - type: 'null' title: Model description: >- Model identifier specific to the provider (required if inference_name not set) examples: - gpt-4o-mini - gemini-1.5-flash - claude-3-5-sonnet - text-embedding-3-large - whisper-1 inference_name: anyOf: - type: string - type: 'null' title: Inference Name description: Custom plugin inference name (alternative to provider+model) examples: - my_text_embedder_1_0_0 - custom_reranker_2_0_0 feature_uri: anyOf: - type: string - type: 'null' title: Feature Uri description: >- Feature URI to resolve to inference_name (alternative to inference_name). Format: mixpeek://{extractor}@{version}/{vector_index_name} examples: - mixpeek://text_extractor@v1/multilingual_e5_large_instruct_v1 - mixpeek://my_custom_embedder@1.0.0/embedding inputs: additionalProperties: true type: object title: Inputs description: >- Model-specific inputs. Chat: {prompts: [str]}, Embeddings: {text: str} or {texts: [str]}, Transcription: {audio_url: str}, Vision: {prompts: [str], image_url: str} examples: - prompts: - What is the capital of France? - text: machine learning - audio_url: https://example.com/audio.mp3 parameters: anyOf: - additionalProperties: true type: object - type: 'null' title: Parameters description: >- Optional parameters for inference. Common: temperature (float), max_tokens (int), schema (dict for structured output) examples: - max_tokens: 500 temperature: 0.7 enable_semantic_cache: type: boolean title: Enable Semantic Cache description: >- Enable semantic caching (vCache) for LLM chat operations. When enabled, semantically similar prompts may return cached responses, reducing latency and cost. Only applies to chat/completion models. default: false cache_delta: anyOf: - type: number maximum: 1 minimum: 0 - type: 'null' title: Cache Delta description: >- Maximum error rate for semantic cache (0.0-1.0). Lower values are more conservative. Default uses system setting (0.02 = 2%). type: object required: - inputs title: RawInferenceRequest description: >- Request for raw inference without retriever framework. This endpoint provides direct access to inference services with minimal configuration. Ideal for simple LLM calls, embeddings, transcription, or vision tasks without requiring collection setup or retriever configuration. You can either use: - `provider` + `model` for standard providers (openai, google, anthropic) - `inference_name` for custom plugins Examples: # Chat completion (provider + model) { "provider": "openai", "model": "gpt-4o-mini", "inputs": {"prompts": ["What is AI?"]}, "parameters": {"temperature": 0.7, "max_tokens": 500} } # Text embedding (provider + model) { "provider": "openai", "model": "text-embedding-3-large", "inputs": {"text": "machine learning"}, "parameters": {} } # Custom plugin (inference_name) { "inference_name": "my_text_embedder_1_0_0", "inputs": {"text": "hello world"}, "parameters": {} } # Audio transcription { "provider": "openai", "model": "whisper-1", "inputs": {"audio_url": "https://example.com/audio.mp3"}, "parameters": {} } # Vision (multimodal) { "provider": "openai", "model": "gpt-4o", "inputs": { "prompts": ["Describe this image"], "image_url": "https://example.com/image.jpg" }, "parameters": {"temperature": 0.5} } RawInferenceResponse: properties: data: title: Data description: Inference results (structure varies by modality) provider: type: string title: Provider description: Provider that was used model: type: string title: Model description: Model that was used tokens_used: anyOf: - additionalProperties: type: integer type: object - type: 'null' title: Tokens Used description: Token usage statistics (if available) examples: - completion: 120 prompt: 15 total: 135 latency_ms: type: number title: Latency Ms description: Total inference latency in milliseconds cached: type: boolean title: Cached description: Whether the response was served from semantic cache (vCache) default: false type: object required: - data - provider - model - latency_ms title: RawInferenceResponse description: |- Response from raw inference. Returns the inference results along with metadata about the request. ErrorResponse: properties: success: type: boolean title: Success description: Always false for error responses default: false status: type: integer title: Status description: HTTP status code for this error error: $ref: '#/components/schemas/ErrorDetail' description: Error details payload type: object required: - status - error title: ErrorResponse description: Error response model. examples: - error: details: id: ns_123 resource: namespace message: Namespace not found type: NotFoundError status: 404 success: false HTTPValidationError: properties: detail: items: $ref: '#/components/schemas/ValidationError' type: array title: Detail type: object title: HTTPValidationError ErrorDetail: properties: message: type: string title: Message description: Human-readable error message type: type: string title: Type description: Stable error type identifier (machine-readable) code: anyOf: - type: string - type: 'null' title: Code description: >- Fine-grained error code for programmatic handling (e.g., namespace_name_taken, feature_extractor_not_found). Present only when consumers may need to branch on a specific error condition. details: anyOf: - additionalProperties: true type: object - type: 'null' title: Details description: >- Optional structured details to help debugging (validation errors, IDs, etc.) type: object required: - message - type title: ErrorDetail description: Error detail model. ValidationError: properties: loc: items: anyOf: - type: string - type: integer type: array title: Location msg: type: string title: Message type: type: string title: Error Type type: object required: - loc - msg - type title: ValidationError ````