> ## Documentation Index
> Fetch the complete documentation index at: https://docs.interhuman.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Build a Video Analyzer App

> Follow a step-by-step video tutorial to build a simple video analyzer app using Interhuman's upload analysis API.

Build a small app that uploads a video from your computer to Interhuman and returns structured analysis results.

In this codealong, you will:

* upload a local video to `POST /v1/upload/analyze`
* optionally request conversation-quality outputs
* render returned `signals[]` (including per-signal `rationale`) and quality metrics in your UI

This page is written so you can follow the build without the video, while the video helps with pacing and implementation details.

## Watch the codealong video

<div style={{ position: "relative", paddingBottom: "56.25%", height: 0, marginBottom: "1.5rem" }}>
  <iframe
    src="https://www.youtube.com/embed/RTOhpJjGHOU"
    title="Build a Video Analyzer App (Interhuman codealong)"
    style={{
  position: "absolute",
  top: 0,
  left: 0,
  width: "100%",
  height: "100%",
  border: 0,
  borderRadius: "12px",
}}
    allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
    allowFullScreen
  />
</div>

Keep the video and your editor side by side; pause after each major step.

<Note>
  The embedded YouTube codealong shows the legacy token-exchange flow. Follow this document for the current integration path: use your API key directly in `Authorization: Bearer <api_key>`.
</Note>

Reference implementation: [interhuman-video-analyzer-codealong on GitHub](https://github.com/InterhumanAI/interhuman-video-analyzer-codealong)

## Build steps

### 1) Prepare credentials and auth

Before calling upload, make sure you have an API key from [platform.interhuman.ai](https://platform.interhuman.ai). If needed, follow [Get an API key](/how-to/get-api-key).

### 2) Add a simple file-upload UI

Create a minimal UI with:

* a file input that accepts a local video file
* an `Analyze` button
* a results panel (for JSON output or parsed cards)

For this codealong, keep it simple. A plain HTML input and a single action button are enough to validate your integration end to end.

### 3) Call Upload & Analyze

When the user clicks `Analyze`, send the selected file to:

* `POST /v1/upload/analyze`
* with `Authorization: Bearer <api_key>`
* as multipart form data (`file`)

Reference: [Upload & Analyze API](/api-reference/upload-analyze)

### 4) Optionally include conversation quality

You can request conversation-quality outputs with include flags:

* `conversation_quality_overall`
* `conversation_quality_timeline`

If included, the API returns conversation quality both as a single overall view and as timeline windows.

References:

* [Upload & Analyze API](/api-reference/upload-analyze)
* [Conversation quality explanation](/explanations/conversation-quality)

### 5) Render results in the app

Once processing completes, render the response in your results panel.

At minimum, show:

* `signals[]` entries (`type`, `start`, `end`, `probability`, `rationale`)
* optional `conversation_quality.overall`
* optional `conversation_quality.timeline[]`

This gives users both event-level insight (what happened and why) and quality-level insight (how the interaction performed across time).

## What to inspect in the response

* **Signal timing**: `start`/`end` are in seconds from the beginning of the uploaded video.
* **Probability**: confidence bucket for each detected signal.
* **Rationale**: a structured explanation of observed behavior (for example speech pauses, tone shifts, gaze, and pacing cues).
* **Conversation quality**: overall plus core dimensions (`quality_index`, `energy`, `rapport`, `authority`, `learning`, `clarity`), and optionally a timeline that shows change over time.

## Next steps

* [Video Analysis quickstart](/getting-started/video-upload-quickstart) — complete request/response examples.
* [Social signals](/explanations/social-signals) — what each signal means and when it appears.
* [Conversation quality](/explanations/conversation-quality) — how quality dimensions are defined.
* [Upload & Analyze API](/api-reference/upload-analyze) — endpoint details and production-level behavior.
* Join the community: [community.interhuman.ai](http://community.interhuman.ai/)