Files
tapir/docs/use-cases/chat_transcript.feature
T
mathiasandClaude Opus 4.8 71df696448
CI / Lint / Test / Vet (push) Successful in 10s
CI / Build & Import (push) Successful in 10s
feat(web): per-video chat over the stored transcript (ADR-027)
A deeper-dive chat entered from the summary view: ask questions about a video
against its already-stored transcript (ADR-021), no caption fetch, ever.

Safety by construction — the load-bearing property. The chat handlers reach the
chat.Service only after reading the SHARED stored transcript via Store.GetTranscript
(a pure DB read); the service holds no VideoSource. So an enabled chat cannot
trigger a caption fetch, touch the rate gate, or reach YouTube. A video with no
stored transcript gets an honest "not available" — no fetch, no model call. The
key web test wires the summarize/fetch collaborators as tripwires that fail the
test if chat ever routes into them, and asserts the model answered from the
stored text.

Model defaults to the summary's own model and is switchable among the ADR-022
chain (phi4-mini → gemma4-26b → mistral-small); switching re-runs against the
same transcript — deliberate model-comparison instrumentation. The cloud model
is absent from the switcher when TAPIR_CLOUD_FALLBACK_MODEL="" (the local-first /
NDA lever), honoured the same way the summarizer honours it. Reuses the existing
LiteLLM gateway client (a chat is a different call, not a new integration) and
the TAPIR_MAX_TRANSCRIPT_CHARS truncation, surfacing an honest bounded-context
note when a long transcript is cut.

Ephemeral v1: the multi-turn conversation rides in hidden request fields; no
table, no migration, nothing persisted. Entry is RLS-scoped through
GetSummaryByVideo, so chat is reachable only from the user's own summary view.
Show-source verification and on-demand fetch are deferred (ADR-027).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-11 09:26:58 +02:00

64 lines
2.7 KiB
Gherkin

Feature: Chat with a video's stored transcript
As a reader whose summary made me want to dig deeper
I want to ask questions about the video without watching it
So that I can go further on the ones worth it, without leaving the reader
# ADR-027. The load-bearing constraint is safety-by-construction: chat runs
# ONLY against an already-stored transcript (ADR-021) and never fetches captions,
# never touches the rate gate, never reaches YouTube. Entry is from the summary
# view of one's OWN video; the conversation is ephemeral (no persisted history).
Background:
Given I have a summarized video with a stored transcript
Scenario: A summary view offers a deeper-dive into the video
When I view the summary
Then I see a "dig deeper" affordance that opens a chat about this video
Scenario: Ask a question answered from the stored transcript
When I ask a question in the chat
Then the answer is produced from the stored transcript
And no caption fetch and no YouTube call occurs
Scenario: Chat never fetches captions or reaches YouTube
When I ask a question in the chat
Then Tapir reads only the stored transcript
And the caption-fetch and video-fetch paths are never invoked
Scenario: A video with no stored transcript offers no chat
Given a video that has no stored transcript
When I open the chat for it
Then I am told chat is not available
And no fetch is attempted and no model is called
Scenario: The default model is the summary's model and is switchable
When I open the chat
Then the model defaults to the model that produced the summary
And I can switch among the offered chain models
Scenario: Switching models re-runs against the same transcript
When I ask a question with a different chain model selected
Then the chosen model answers
And it answers against the same stored transcript
Scenario: The cloud model is hidden when cloud is disabled
Given the cloud fallback model is disabled
Then the chat switcher offers only local models
Scenario: A long transcript is bounded and the chat says so
Given the stored transcript is longer than the model budget
When I ask a question
Then the answer is produced from a bounded portion
And the chat notes that it worked from a bounded portion
Scenario: A multi-turn conversation is ephemeral
When I ask a follow-up question
Then the prior turn is carried into the answer
And nothing about the conversation is written to the database
Scenario: Chat is reachable only from my own summary view
Given another user has a summarized video with a stored transcript
When I try to open the chat for their video
Then I get a not-found response
And no model is called