Timepoint Flash

Experience Synthetic Time Travel — type any moment in history, get a complete historically grounded scene in seconds: characters with distinct voices, period-accurate dialog, relationship dynamics, and a photorealistic image — all verified against Google Search.

GitHub

timepointai/timepoint-flash — Apache-2.0, Python 3.10+, FastAPI

Detailed Docs

Full API reference, agent pipeline, and configuration docs

Flash runs behind the API Gateway with AUTH_ENABLED=false — it is a pure generation engine with no authentication of its own. All consumer access goes through api.timepointai.com, which handles auth, credits, and rate limiting before proxying requests to Flash.

How It Works

Flash uses a 14-agent pipeline where each agent specializes in one aspect of scene construction. The pipeline includes automated critique and retry loops to ensure historical accuracy.

Query → Judge → Timeline → Grounding (Google Search)
    → Scene → Characters + Moment + Camera [parallel]
    → Dialog → Critique (auto-retry)
    → ImagePrompt → Optimizer → ImageGen

Agent Pipeline

Agent	Role
Judge	Validates query, extracts temporal/spatial coordinates
Timeline	Builds historical context and event sequence
Grounding	Verifies facts against Google Search
Scene	Constructs physical setting, atmosphere, lighting
Characters	Builds character profiles with distinct voices
Moment	Captures the emotional/dramatic core
Camera	Composes the visual frame
Dialog	Generates period-accurate character speech
Critique	Reviews for anachronisms, errors — auto-retries if needed
ImagePrompt	Translates scene to image generation prompt
Optimizer	Refines prompt for photorealism
ImageGen	3-tier fallback: Google Imagen → OpenRouter Flux → Pollinations

Example Output

Query: “AlphaGo plays Move 37 against Lee Sedol, Seoul, March 10 2016” Result:

Full scene with location, date, atmosphere, tension level
5 characters with distinct speaking patterns
Multi-turn dialog capturing the moment
Photorealistic image
Source citations and confidence scores
TDF-formatted output with provenance

API

# Synchronous render
POST /api/v1/timepoints/generate/sync
Content-Type: application/json

{"query": "Moon landing, July 20 1969", "generate_image": true}

# Streaming render (SSE)
POST /api/v1/timepoints/generate/stream

LLM Providers

Provider	Role	Required
Google Gemini	Primary LLM for all agents	Yes
OpenRouter	Fallback LLM	Optional

Image Generation

3-tier fallback chain:

Google Imagen (primary)
OpenRouter Flux (fallback)
Pollinations.ai (free fallback)

Installation

git clone https://github.com/timepointai/timepoint-flash.git
cd timepoint-flash
pip install -e .
export GOOGLE_API_KEY="your-key"
flash serve

Live API: api.timepointai.com

Getting Started

Products

API Reference

Timepoint Flash

Timepoint Flash

GitHub

Detailed Docs

How It Works

Agent Pipeline

Example Output

API

LLM Providers

Image Generation

Installation

​Timepoint Flash

GitHub

Detailed Docs

​How It Works

​Agent Pipeline

​Example Output

​API

​LLM Providers

​Image Generation

​Installation

Timepoint Flash

How It Works

Agent Pipeline

Example Output

API

LLM Providers

Image Generation

Installation