> ## Documentation Index > Fetch the complete documentation index at: https://docs.mavera.io/llms.txt > Use this file to discover all available pages before exploring further. # Chat about video analysis > Have a conversation about a completed video analysis. The AI has full access to the analysis data and can explain metrics, provide recommendations, and answer questions. **Requirements**: The video analysis must be in `completed` status. ## OpenAPI ````yaml /openapi.json post /video-analyses/{id}/chat openapi: 3.0.3 info: title: Mavera API version: 1.0.0 description: >- # Getting Started The Mavera Responses API provides persona-powered AI responses using the **OpenAI Responses API format**. Use `client.responses.create()` with the OpenAI SDK — just set the base URL to `https://app.mavera.io/api/v1`. ## Authentication All API requests require a Bearer token. Create an API key in **Settings > Developer > API Keys**. ``` Authorization: Bearer mvra_live_your_key_here ``` ## Quick Start ### Step 1: Get a Persona ID Every response request requires a `persona_id`. First, list available personas: ```bash curl https://app.mavera.io/api/v1/personas \ -H "Authorization: Bearer mvra_live_your_key_here" ``` This returns personas you can use. Copy the `id` field from any persona. ### Step 2: Create a Response Use the persona ID in your request: ```bash curl https://app.mavera.io/api/v1/responses \ -H "Authorization: Bearer mvra_live_your_key_here" \ -H "Content-Type: application/json" \ -d '{ "model": "mavera-1", "persona_id": "YOUR_PERSONA_ID", "input": "Hello!" }' ``` ## Rate Limits Per-key sliding window limits based on your subscription tier: | Tier | Requests / min | |------|---------------| | Starter | 60 | | Basic | 120 | | Professional | 240 | | Enterprise | 600 | When rate limited, the response includes a `Retry-After` header indicating how many seconds to wait. ## Credits Each API call consumes credits from your subscription. The `usage.credits_used` field in the response shows the cost of each request. contact: name: Mavera Support url: https://mavera.io x-logo: url: /Mavera_Logo_Full.png altText: Mavera servers: - url: https://app.mavera.io/api/v1 description: Production - url: https://dev.mavera.io/api/v1 description: Development security: - BearerAuth: [] tags: - name: System description: Health checks and operational status. - name: Responses description: >- Generate persona-powered AI responses using the OpenAI Responses API format. Use `client.responses.create()` with the OpenAI SDK. - name: Models description: Discover available models and their capabilities. - name: Personas description: >- Browse available personas to inject specialized intelligence into responses via `persona_id`. - name: Custom Personas description: >- Create, manage, and customize AI-powered personas. Supports three creation pipelines: North Star (AI-generated from minimal input), Intermediate (guided 3-step process), and Advanced (full B2B/B2C customization with psychographics and purpose packs). 300 credits per persona. - name: Brand Voice description: >- Create, manage, and retrieve brand voice profiles for AI-powered content generation. Upload URLs and documents to analyze, and the AI will generate tone guidelines, vocabulary preferences, and writing style recommendations. - name: Generations description: >- Generate AI-powered content using pre-built templates with optional brand voice styling. Browse available generation apps, create content, and manage your generation history. Supports streaming responses. - name: Mave description: >- Mave is Mavera's AI-powered research and analysis agent. Send messages to conduct comprehensive investigations using multiple data sources, personas, and fact-checking. Mave uses a multi-phase orchestration process (Triage, Planning, Research, Execution, Validation) to deliver well-researched responses with sources. - name: Workspaces description: >- Manage workspaces for organizing your work. Workspaces contain projects, threads, personas, and other resources. Invite team members with role-based access control. Set budget alerts and usage limits. - name: Projects description: >- Organize work within workspaces using projects. Projects contain threads, generations, and other resources. Track usage and set per-project budget controls. - name: Meetings description: >- Access meeting recordings, transcripts, and AI-powered analysis. List meetings, retrieve transcripts in multiple formats (segments, text, SRT), get AI analysis with summaries, tasks, decisions, highlights, and coaching metrics. Run custom schemas to extract structured data from transcripts. - name: Schemas description: >- Create and manage meeting schemas for structured data extraction. Schemas define fields to extract from meeting transcripts, with support for various field types (text, enum, list, boolean, etc.), evidence tracking, and scoring. - name: Files description: >- Upload, manage, and retrieve files/assets. Use presigned URLs for direct uploads to avoid passing files through the API. Supports images, videos, documents, and more. File uploads count against your storage quota. - name: Folders description: >- Create and manage folders to organize your files. Folders can be favorited and shared with workspace members. - name: Video Analysis description: >- AI-powered video and advertisement analysis. Submit videos for comprehensive emotional, cognitive, behavioral, and technical analysis. Chat with AI about the results. - name: Focus Groups description: >- AI-powered synthetic focus group research. Create focus groups with personas to gather market research, product feedback, and audience insights. Supports 12 question types including NPS, Likert scales, and open-ended responses. - name: News description: >- AI-powered news intelligence. Browse trending stories, get AI analysis from persona perspectives, and manage scheduled news digests. Story analysis uses credits based on token usage. - name: Usage description: >- Monitor your subscription usage including credits, transcription minutes, storage, and API request metrics. Get real-time statistics on your billing period usage. paths: /video-analyses/{id}/chat: post: tags: - Video Analysis summary: Chat about video analysis description: >- Have a conversation about a completed video analysis. The AI has full access to the analysis data and can explain metrics, provide recommendations, and answer questions. **Requirements**: The video analysis must be in `completed` status. operationId: chatVideoAnalysis parameters: - name: id in: path required: true description: The video analysis ID. schema: type: string requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/VideoAnalysisChatRequest' responses: '200': description: Chat completion response. content: application/json: schema: $ref: '#/components/schemas/ResponseObject' text/event-stream: schema: type: string '400': description: Invalid request or analysis not completed. content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' '401': description: Authentication error. content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' '404': description: Video analysis not found. content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' x-codeSamples: - lang: curl label: cURL source: >- curl -X POST https://app.mavera.io/api/v1/video-analyses/YOUR_ANALYSIS_ID/chat \ -H "Authorization: Bearer mvra_live_your_key_here" \ -H "Content-Type: application/json" \ -d '{ "messages": [ { "role": "user", "content": "What are the main strengths of this ad?" } ] }' - lang: python label: Python source: |- import requests headers = {"Authorization": "Bearer mvra_live_your_key_here"} analysis_id = "YOUR_ANALYSIS_ID" # Chat about the analysis response = requests.post( f"https://app.mavera.io/api/v1/video-analyses/{analysis_id}/chat", headers=headers, json={ "messages": [ {"role": "user", "content": "What are the main strengths of this ad?"} ] } ) print(response.json()["choices"][0]["message"]["content"]) # Follow-up question response = requests.post( f"https://app.mavera.io/api/v1/video-analyses/{analysis_id}/chat", headers=headers, json={ "messages": [ {"role": "user", "content": "What are the main strengths of this ad?"}, {"role": "assistant", "content": response.json()["choices"][0]["message"]["content"]}, {"role": "user", "content": "How can we improve the emotional impact?"} ] } ) print(response.json()["choices"][0]["message"]["content"]) components: schemas: VideoAnalysisChatRequest: type: object required: - messages properties: messages: type: array description: Conversation messages. Maximum 50 messages. minItems: 1 maxItems: 50 items: type: object required: - role - content properties: role: type: string enum: - user - assistant description: Message role. content: type: string maxLength: 10000 description: Message content. example: - role: user content: What are the main strengths of this ad? stream: type: boolean default: false description: If true, stream the response via SSE. ResponseObject: type: object description: A completed response object. properties: id: type: string description: Unique response ID with `resp_` prefix. example: resp_abc123def456abc123def456 object: type: string enum: - response description: Always `response`. example: response created_at: type: integer description: Unix timestamp (seconds) when the response was created. example: 1706345678 status: type: string enum: - completed - in_progress - failed description: Response status. example: completed model: type: string description: The model used. example: mavera-1 output: type: array description: >- Ordered list of output items. Typically a single `message` item with text, or one or more `function_call` items when the model wants to call tools. items: oneOf: - type: object description: A message output item. properties: id: type: string example: msg_abc123def456 type: type: string enum: - message role: type: string enum: - assistant status: type: string enum: - completed - in_progress content: type: array description: Content parts of the message. items: type: object properties: type: type: string enum: - output_text text: type: string description: The generated text. - type: object description: >- A function call output item — the model wants you to execute this. properties: type: type: string enum: - function_call id: type: string example: fc_abc123def456 call_id: type: string description: >- Use this as `call_id` in your `function_call_output` input item. example: call_abc123 name: type: string example: get_weather arguments: type: string description: JSON-encoded function arguments. example: '{"city":"New York"}' usage: type: object description: Token and credit usage. properties: input_tokens: type: integer description: Tokens in the input. example: 42 output_tokens: type: integer description: Tokens in the output. example: 68 total_tokens: type: integer description: Total tokens. example: 110 credits_used: type: integer description: Credits consumed from your subscription. example: 3 server_tool_calls: type: array description: >- Mavera's built-in server-side tools automatically executed during this request. Only present when server tools were used. items: type: object properties: name: type: string example: tavily_search args: type: object example: query: latest AI news result: type: object analysis: type: object description: Structured analysis data. Present when `analysis_mode` is `true`. properties: response: type: string emotion: type: object properties: emotional_valence: type: number emotional_arousal: type: number explanation: type: string pragmatic: type: object properties: pragmatic_realism: type: number pragmatic_actionability: type: number explanation: type: string biases: type: array items: type: object properties: name: type: string description: type: string impact: type: number examples: type: array items: type: string suggested_mitigation: type: string confidence: type: number spread_of_opinions: type: number extreme_min_opinion: type: string extreme_max_opinion: type: string news_relevant: type: array items: type: object properties: story: type: string impact: type: number source: type: string source_url: type: string follow_up_questions: type: array items: type: string parsed: type: object description: >- Present when `text.format.type` is `json_schema`. Contains the parsed JSON object — a convenience field, same data is also in `output[0].content[0].text`. example: sentiment: positive score: 8.5 summary: Great product example: id: resp_abc123def456abc123def456 object: response created_at: 1706345678 status: completed model: mavera-1 output: - id: msg_abc123def456 type: message role: assistant status: completed content: - type: output_text text: >- Quantum computing uses qubits that can exist in multiple states simultaneously, enabling processing of many possibilities at once. usage: input_tokens: 42 output_tokens: 68 total_tokens: 110 credits_used: 3 ErrorResponse: type: object description: >- All error responses follow this format. The `type` field indicates the category of error, and `code` provides a machine-readable error code. properties: error: type: object properties: message: type: string description: A human-readable error message. example: Invalid API key. type: type: string enum: - invalid_request_error - authentication_error - insufficient_credits - not_found - rate_limit_error - api_error description: The category of error. example: authentication_error code: type: string description: A machine-readable error code. example: invalid_api_key param: type: string nullable: true description: The request parameter that caused the error, if applicable. example: null example: error: message: Invalid API key. type: authentication_error code: invalid_api_key param: null securitySchemes: BearerAuth: type: http scheme: bearer description: >- API key prefixed with `mvra_live_`. Create keys at **Settings > Developer > API Keys**. ````