Movie Recommender is an OpenHome community ability for discovering movies by voice. It helps users find recommendations, trending titles, similar movies, release dates, ratings, summaries, and streaming options using The Movie Database (TMDB).Documentation Index
Fetch the complete documentation index at: https://docs.openhome.com/llms.txt
Use this file to discover all available pages before exploring further.
What It Does
- Recommends movies by genre, mood, year, or free-text request
- Finds trending and top-rated movies
- Finds similar movies from a title the user likes
- Gives details about a specific movie from the current results or by title
- Answers release-date questions, including upcoming movie phrasing
- Speaks ratings with a natural quality label like excellent, solid, mixed, or rough
- Looks up US streaming providers through TMDB watch providers
- Lets the user ask for more results without starting over
- Summarizes the current movie picks
- Handles vague requests with a clarifying question instead of a weak search
- Resolves ordinals and pronouns like
the second one,it, andthat one
Supported Requests
| Request type | Example | What happens |
|---|---|---|
| Recommendation | Recommend something scary | Searches TMDB for matching movies and speaks a few picks |
| Trending | What's trending in movies? | Returns currently trending movies |
| Top-rated | Best movies of all time | Returns highly rated movies |
| Similar movies | Movies like Inception | Finds the source title, then recommends similar titles |
| Details | Tell me about the second one | Opens a specific movie and speaks a short synopsis |
| Release date | When does it come out? | Gives the release date for a named or focused movie |
| Rating | What's that rated? | Speaks the TMDB score with a short quality description |
| Watch providers | Where can I watch it? | Lists available US streaming providers from TMDB |
| More results | Show me more | Pages through the current search |
| Summaries | What are these about? | Gives short overviews of current picks |
Example Prompts
- “What’s trending in movies?”
- “Find me some best movies.”
- “Recommend something scary.”
- “Sci-fi releases in 2025.”
- “Movies like The Matrix.”
- “Tell me about the second one.”
- “When does it come out?”
- “What’s that rated?”
- “Where can I watch it?”
Example Conversation
User: Recommend something scary. AI: Got it, finding a few that fit. Here are a few that fit: The Substance from 2024, rated 7.5. Smile 2 from 2024, rated 7.0. Longlegs from 2024, rated 6.6. User: Tell me about the second one. AI: Smile 2, from 2024, rated 7.0. A pop star battles an entity that twists her perception of reality before her world tour. User: Where can I watch it? AI: Smile 2 is on Paramount Plus.
Trigger Phrases
- “movie recommender”
- “recommend a movie”
- “what should I watch”
- “trending movies”
- “movie suggestion”
Data Source
| Source | OpenHome API key name | Role |
|---|---|---|
| The Movie Database (TMDB) | tmdb_api_key | Movie discovery, metadata, ratings, release dates, similar titles, watch providers |
Setup
Add your TMDB v3 API key in OpenHome Settings → API Keys astmdb_api_key. Use the short TMDB v3 API key only. Do not use the API Read Access Token or API Secret, and do not hardcode the key.
Getting a TMDB API Key
- Create or sign in to a TMDB account.
- Open your account settings.
- Go to the API section.
- Request API access if it is not already enabled.
- Choose Developer access and fill out the required application details.
- After approval, copy the short key labeled
API Key (v3 auth). - In OpenHome, open Settings -> API Keys.
- Add a new key named
tmdb_api_key. - Paste the TMDB v3 API key as the value and save it.
Voice UX Notes
- Short fillers before TMDB calls so the user knows the ability is working.
- Pre-formatted spoken lines — no LLM naturalize pass between filler and result, which keeps mic-hot time short.
- Continue prompts taper — turn 1 is a rich invitation, turn 2 is a shorter directional prompt, turn 3 onward listens silently.
- Exit routing owned by the LLM — “stop”, “okay stop”, “I’m done” are all recognized.
Developer Credit
Developed by @Kaushal-205.View on GitHub
Source code for the
movie-recommender community ability.
