> ## Documentation Index > Fetch the complete documentation index at: https://portkey-docs-add-third-party-integration-issues-fixes.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # Create Transcription ## OpenAPI ````yaml post /audio/transcriptions openapi: 3.0.0 info: title: Portkey API description: >- The Portkey REST API. Please see https://portkey.ai/docs/api-reference for more details. version: 2.0.0 termsOfService: https://portkey.ai/terms contact: name: Portkey Developer Forum url: https://portkey.wiki/community license: name: MIT url: https://github.com/Portkey-AI/portkey-openapi/blob/master/LICENSE servers: - url: https://api.portkey.ai/v1 description: Portkey API Public Endpoint security: - Portkey-Key: [] tags: - name: Assistants description: Build Assistants that can call models and use tools. - name: Audio description: Turn audio into text or text into audio. - name: Chat description: >- Given a list of messages comprising a conversation, the model will return a response. - name: Realtime description: WebSocket proxy for provider Realtime APIs - name: Collections description: Create, List, Retrieve, Update, and Delete collections of prompts. - name: Labels description: Create, List, Retrieve, Update, and Delete labels. - name: Prompt Collections description: Create, List, Retrieve, Update, and Delete prompt collections. - name: PromptPartials description: Create, List, Retrieve, Update, and Delete prompt partials. - name: Prompts description: >- Given a prompt template ID and variables, will run the saved prompt template and return a response. - name: Guardrails description: Create, List, Retrieve, Update, and Delete prompt Guardrails. - name: Completions description: >- Given a prompt, the model will return one or more predicted completions, and can also return the probabilities of alternative tokens at each position. - name: Embeddings description: >- Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms. - name: Rerank description: >- Rerank a list of documents based on their relevance to a query. Supported providers include Cohere, Voyage, Jina, Pinecone, Bedrock, and Azure AI. - name: Fine-tuning description: Manage fine-tuning jobs to tailor a model to your specific training data. - name: Batch description: Create large batches of API requests to run asynchronously. - name: Files description: >- Files are used to upload documents that can be used with features like Assistants and Fine-tuning. - name: Images description: Given a prompt and/or an input image, the model will generate a new image. - name: Models description: List and describe the various models available in the API. - name: Moderations description: >- Given a input text, outputs if the model classifies it as potentially harmful. - name: Configs description: Create, List, Retrieve, and Update your Portkey Configs. - name: Feedback description: Send and Update any feedback. - name: Logs description: Custom Logger to add external logs to Portkey. - name: Integrations description: Create, List, Retrieve, Update, and Delete your Portkey Integrations. - name: Integrations > Workspaces description: Manage workspace access for your Portkey Integrations. - name: Integrations > Models description: Manage model access for your Portkey Integrations. - name: Providers description: Create, List, Retrieve, Update, and Delete your Portkey Providers. - name: Virtual-keys description: Create, List, Retrieve, Update, and Delete your Portkey Virtual keys. - name: Users description: Create and manage users. - name: User-invites description: Create and manage user invites. - name: Workspaces description: Create and manage workspaces. - name: Workspaces > Members description: Create and manage workspace members. - name: MCP Integrations description: Create, List, Retrieve, Update, and Delete MCP Integrations. - name: MCP Integrations > Workspaces description: Manage workspace access for MCP Integrations. - name: MCP Integrations > Capabilities description: List and manage capabilities for MCP Integrations. - name: MCP Integrations > Metadata description: Get MCP Integration metadata and sync info. - name: MCP Servers description: >- Create, List, Retrieve, Update, and Delete MCP Servers (workspace instances of MCP Integrations). - name: MCP Servers > Capabilities description: List and manage capabilities for MCP Servers. - name: MCP Servers > User Access description: List and manage user access for MCP Servers. - name: MCP Servers > Connections description: List and manage user connections for MCP Servers. - name: Api-Keys description: Create, List, Retrieve, Update, and Delete your Portkey API keys. - name: Logs Export description: Exports logs service. - name: Audit Logs description: Get audit logs for your Portkey account. - name: Analytics description: >- Get analytics over different data points like requests, costs, tokens, etc. - name: Analytics > Graphs description: Get data points for graphical representation. - name: Analytics > Summary description: Get overall summary for the selected time bucket. - name: Analytics > Groups description: Get grouped metrics for the selected time bucket. - name: Usage Limits Policies description: Manage usage limits policies to control total usage over time - name: Rate Limits Policies description: Manage rate limits policies to control request or token rates - name: Model Pricing description: Model pricing configurations for 2300+ LLMs across 40+ providers - name: Secret-References description: >- Create, List, Retrieve, Update, and Delete secret references to external secret managers. paths: /audio/transcriptions: servers: - url: https://api.portkey.ai/v1 description: Portkey API Public Endpoint - url: SELF_HOSTED_GATEWAY_URL description: Self-Hosted Gateway URL post: tags: - Audio summary: Create Transcription operationId: createTranscription requestBody: required: true content: multipart/form-data: schema: $ref: '#/components/schemas/CreateTranscriptionRequest' responses: '200': description: OK content: application/json: schema: oneOf: - $ref: '#/components/schemas/CreateTranscriptionResponseJson' - $ref: >- #/components/schemas/CreateTranscriptionResponseVerboseJson security: - Portkey-Key: [] Virtual-Key: [] - Portkey-Key: [] Provider-Auth: [] Provider-Name: [] - Portkey-Key: [] Config: [] - Portkey-Key: [] Provider-Auth: [] Provider-Name: [] Custom-Host: [] x-code-samples: - lang: curl label: Default source: | curl https://api.portkey.ai/v1/audio/transcriptions \ -H "x-portkey-api-key: $PORTKEY_API_KEY" \ -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \ -H "Content-Type: multipart/form-data" \ -F file="@/path/to/file/audio.mp3" \ -F model="whisper-1" - lang: python label: Default source: | from portkey_ai import Portkey client = Portkey( api_key = "PORTKEY_API_KEY", virtual_key = "PROVIDER_VIRTUAL_KEY" ) audio_file = open("speech.mp3", "rb") transcript = client.audio.transcriptions.create( model="whisper-1", file=audio_file ) - lang: javascript label: Default source: | import fs from "fs"; import Portkey from 'portkey-ai'; const client = new Portkey({ apiKey: 'PORTKEY_API_KEY', virtualKey: 'PROVIDER_VIRTUAL_KEY' }); async function main() { const transcription = await client.audio.transcriptions.create({ file: fs.createReadStream("audio.mp3"), model: "whisper-1", }); console.log(transcription.text); } main(); - lang: curl label: Self-Hosted source: | curl -X POST "SELF_HOSTED_GATEWAY_URL/audio/transcriptions" \ -H "Content-Type: application/json" \ -H "x-portkey-api-key: $PORTKEY_API_KEY" \ -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \ -d '{ "model": "whisper-1", "file": "@/path/to/file/audio.mp3" }' \ --output transcription.json - lang: python label: Self-Hosted source: | from portkey_ai import Portkey client = Portkey( api_key = "PORTKEY_API_KEY", virtual_key = "PROVIDER_VIRTUAL_KEY", base_url="SELF_HOSTED_GATEWAY_URL" ) audio_file = open("speech.mp3", "rb") transcript = client.audio.transcriptions.create( model="whisper-1", file=audio_file ) - lang: javascript label: Self-Hosted source: | import fs from "fs"; import Portkey from 'portkey-ai'; const client = new Portkey({ apiKey: 'PORTKEY_API_KEY', virtualKey: 'PROVIDER_VIRTUAL_KEY', baseUrl: 'SELF_HOSTED_GATEWAY_URL' }); const audioFile = fs.createReadStream("speech.mp3"); async function main() { const transcription = await client.audio.transcriptions.create({ file: audioFile, model: "whisper-1", }); console.log(transcription.text); } main(); components: schemas: CreateTranscriptionRequest: type: object additionalProperties: false properties: file: description: > The audio file object (not file name) to transcribe, in one of these formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm. type: string x-oaiTypeLabel: file format: binary model: description: > ID of the model to use. The options are `gpt-4o-transcribe`, `gpt-4o-mini-transcribe`, and `whisper-1`. example: whisper-1 anyOf: - type: string - type: string enum: - whisper-1 x-oaiTypeLabel: string language: description: > The language of the input audio. Supplying the input language in [ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) format will improve accuracy and latency. type: string prompt: description: > An optional text to guide the model's style or continue a previous audio segment. The [prompt](https://platform.openai.com/docs/guides/speech-to-text/prompting) should match the audio language. type: string response_format: description: > The format of the transcript output, in one of these options: `json`, `text`, `srt`, `verbose_json`, or `vtt`. type: string enum: - json - text - srt - verbose_json - vtt default: json temperature: description: > The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. If set to 0, the model will use [log probability](https://en.wikipedia.org/wiki/Log_probability) to automatically increase the temperature until certain thresholds are hit. type: number default: 0 timestamp_granularities[]: description: > The timestamp granularities to populate for this transcription. `response_format` must be set `verbose_json` to use timestamp granularities. Either or both of these options are supported: `word`, or `segment`. Note: There is no additional latency for segment timestamps, but generating word timestamps incurs additional latency. type: array items: type: string enum: - word - segment default: - segment required: - file - model CreateTranscriptionResponseJson: type: object description: >- Represents a transcription response returned by model, based on the provided input. properties: text: type: string description: The transcribed text. required: - text CreateTranscriptionResponseVerboseJson: type: object description: >- Represents a verbose json transcription response returned by model, based on the provided input. properties: language: type: string description: The language of the input audio. duration: type: string description: The duration of the input audio. text: type: string description: The transcribed text. words: type: array description: Extracted words and their corresponding timestamps. items: $ref: '#/components/schemas/TranscriptionWord' segments: type: array description: Segments of the transcribed text and their corresponding details. items: $ref: '#/components/schemas/TranscriptionSegment' required: - language - duration - text TranscriptionWord: type: object properties: word: type: string description: The text content of the word. start: type: number format: float description: Start time of the word in seconds. end: type: number format: float description: End time of the word in seconds. required: - word - start - end TranscriptionSegment: type: object properties: id: type: integer description: Unique identifier of the segment. seek: type: integer description: Seek offset of the segment. start: type: number format: float description: Start time of the segment in seconds. end: type: number format: float description: End time of the segment in seconds. text: type: string description: Text content of the segment. tokens: type: array items: type: integer description: Array of token IDs for the text content. temperature: type: number format: float description: Temperature parameter used for generating the segment. avg_logprob: type: number format: float description: >- Average logprob of the segment. If the value is lower than -1, consider the logprobs failed. compression_ratio: type: number format: float description: >- Compression ratio of the segment. If the value is greater than 2.4, consider the compression failed. no_speech_prob: type: number format: float description: >- Probability of no speech in the segment. If the value is higher than 1.0 and the `avg_logprob` is below -1, consider this segment silent. required: - id - seek - start - end - text - tokens - temperature - avg_logprob - compression_ratio - no_speech_prob securitySchemes: Portkey-Key: type: apiKey in: header name: x-portkey-api-key Virtual-Key: type: apiKey in: header name: x-portkey-virtual-key Provider-Auth: type: http scheme: bearer Provider-Name: type: apiKey in: header name: x-portkey-provider Config: type: apiKey in: header name: x-portkey-config Custom-Host: type: apiKey in: header name: x-portkey-custom-host ````