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Local ChatGPT Web bridge with API, console, opencode integration, and character-game use case

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# ChatGPT Web Bridge

**A local API bridge for building real apps on top of ChatGPT Web accounts.**

Run chat, streaming, image generation, image editing, OCR/vision, Deep Research,
artifact downloads, opencode integration, and a full-stack character game from
one local stack.

<a href="#quick-start-with-docker">Quick Start</a>
 · <a href="#what-this-is">What It Does</a>
 · <a href="#account-capture">Account Capture</a>
 · <a href="#api-overview">API Routes</a>
 · <a href="#image-generation">Images</a>
 · <a href="#deep-research">Research</a>
 · <a href="#opencode-integration">opencode</a>
 · <a href="#documentation-index">Docs</a>

</div>

## The Pitch

This is for developers who want to put AI into a small web product, internal
tool, prototype, character game, or local agent workflow before paying for a
full official API deployment. It gives you a practical local API surface around
ChatGPT Web capacity you may already have, while keeping the risk and secrets on
your own machine.

It is not a hosted service and it is not an official API. It is a local bridge,
an operator console, a CLI, Docker packaging, and concrete use cases that show
how far a ChatGPT Web account can go when wrapped with sane routing, artifacts,
downloads, and developer tooling.

> [!IMPORTANT]
> This is a local developer bridge. It is useful for prototypes, small products,
> LAN tools, and agent workflows. It is not a public hosted proxy and should not
> be deployed with shared real account captures.

> [!NOTE]
> Maintainer support for issues, pull requests, and necessary fixes is planned
> through **June 30, 2026 (30/6/69 B.E.)**. After that, this repository will
> remain public under the MIT license, but ongoing feature work and guaranteed
> support are not planned because I have started a new personal main project
> that uses related ideas, and I need to keep that boundary clear. See
> [SUPPORT.md](SUPPORT.md) for details.
>
> ภาษาไทย: ผมจะช่วยตอบ issue, ดู PR, และแก้ปัญหาที่จำเป็นให้ถึง
> **30 มิถุนายน 2026 (30/6/69)** หลังจากนั้นยัง fork/แก้/เอาไปใช้ต่อได้ตาม
> MIT license แต่จะไม่รับประกันการดูแลต่อเนื่อง เพราะผมเพิ่งเริ่มทำโปรเจกต์ใหม่
> ส่วนตัวที่เป็นงานหลักของผมเองและใช้แนวคิดบางส่วนร่วมกัน ไม่ได้อยู่ภายใต้
> บริษัทไหน จึงต้องกันขอบเขตงานและผลประโยชน์ของผมเองให้ชัดเจน

<table>
 <tr>
 <td>Local API <code>/v1/chat/completions</code>, images, edits, vision, research, files, admin routes.</td>
 <td>Account Router Use one account or combine several accounts with failover, random, round-robin, weighted, or quota-aware routing.</td>
 </tr>
 <tr>
 <td>Operator Console Health, accounts, capacity, docs, storage, test lab, and opencode setup in a dedicated UI.</td>
 <td>Real Use Case A SvelteKit character/roleplay game shows how a normal web app can consume the bridge.</td>
 </tr>
 <tr>
 <td>Artifacts Images and Deep Research reports are saved to disk and exposed through download URLs for browser/LAN clients.</td>
 <td>Agent Integration opencode can be pointed at the local bridge for chat, tool-call style flows, image generation, and research.</td>
 </tr>
</table>

## Screenshots

| Console | Character Game |
| --- | --- |
| <img src="docs/assets/screenshots/oss-console-overview.png" alt="Console overview" width="440"> | <img src="docs/assets/screenshots/oss-game-setup.png" alt="Character game setup" width="440"> |

| API Docs | Storage / Library |
| --- | --- |
| <img src="docs/assets/screenshots/oss-console-docs.png" alt="Console docs" width="440"> | <img src="docs/assets/screenshots/oss-console-library.png" alt="Console artifact library" width="440"> |

## Capability Snapshot

| Capability | Route / surface | Current status |
| --- | --- | --- |
| Chat and streaming | `POST /v1/chat/completions` | implemented |
| Tool-call bridge | `tools` through chat completions | implemented |
| Image generation | `POST /v1/images/generations` | implemented |
| Image edit / composite | `POST /v1/images/edits` | implemented, one output image |
| OCR / describe up to 10 images | `POST /v1/chatgpt/vision` | implemented |
| Deep Research report export | `chatgpt-deep-research` model alias | implemented |
| File downloads | `GET/HEAD /v1/chatgpt/files/{id}/{filename}` | implemented |
| Account usage and limits | `GET /v1/chatgpt/usage` | implemented when ChatGPT reports data |
| opencode consumer config | `integrations/opencode/*` | implemented |
| Character game use case | `apps/character-game` | included as a working reference app |

## Tested Plan Notes

| Plan | What is known right now |
| --- | --- |
| Free | Live-tested for chat, vision/OCR, multi-image upload, and image edit/composite when quota is available. Multiple free accounts can increase local routing capacity, but hidden ChatGPT limits still apply. |
| Go | Expected to work through `auto` and plan-limited feature buckets, but not personally verified yet. |
| Plus | Expected to work with higher quota than Free/Go, but not personally verified yet. |
| Pro | Live-tested. Higher image/research capacity and higher recommended local concurrency. |

## Latest Validation Snapshot

These checks were run locally on 2026-06-28 for the `/v1/images/edits`
regression fixed in issue #3.

| Check | Result |
| --- | --- |
| Targeted transport suite: `python3 -m pytest tests/test_chatgpt_transport.py -q` | `32 passed` |
| Python full test suite: `python3 -m pytest -q` | `190 passed` |
| Live `/v1/images/edits` request through the local bridge | passed with a real generated output image, not the uploaded input image |
| Artifact download check for the generated image | `200 OK` |
| Whitespace check: `git diff --check` | passed |

The live proof used a local ChatGPT account capture. It verifies that the bridge
now skips uploaded input images that reappear as `sediment://<same_id>` while it
waits for the actual generated image asset.

Earlier frontend/demo checks from 2026-06-26:

| Check | Result |
| --- | --- |
| Bridge Console Svelte diagnostics: `bun run check` | `0 errors, 0 warnings` |
| Bridge Console production build: `bun run build` | passed |
| Character Game Svelte diagnostics: `bun run check` | `0 errors, 0 warnings` |
| Character Game unit tests: `bun run test` | `1 file / 6 tests passed` |
| Character Game production build: `bun run build` | passed |
| Svelte MCP autofixer on `App.svelte` | no issues |
| Docs/console stale-alias sweep | no `free-main`, `pro-main`, `plus-main`, or fake `pro/free` route examples found |

Docker and live ChatGPT account/image/OCR/research proofs require a real local
account capture and should be rerun on the target machine before publishing a
release build.

## Recommended Minimum Revision

If you cloned or forked this project before the current CLI/capture/docs
cleanup, update to this revision before testing Docker, the console, cURL
capture import, image edit/composite, OCR/vision, or Deep Research cancellation.
This revision is the recommended baseline because it:

- removes confusing fake plan-account examples such as `free-main`/`pro-main`
 from the docs and console;
- documents Chrome/Safari `Copy as cURL` capture import, including `Cookie:` or
 `-b` cookie input;
- clarifies that account names are local aliases, not plan selectors;
- fixes `/v1/images/edits` async polling so an uploaded input image echoed back
 as `sediment://<same_id>` is not returned as the generated output;
- keeps Docker startup separate from real ChatGPT account verification;
- updates CLI and console docs around routing, artifacts, upload/image usage,
 and Deep Research cancellation.

Older commits may still run, but they are easier to misconfigure and are not
the best starting point for new users.

## Best Fit

Use this when you want:

- AI chat inside a small web app without immediately paying official API spend
- image generation or image editing from a ChatGPT subscription you already pay for
- a local research worker that saves markdown reports for Codex or another agent
- a character/roleplay game backend with optional scene art
- a private LAN tool where artifacts need real download URLs
- a proof of concept before designing a full production AI backend

Do not use it as-is for a public multi-tenant platform. The backend is a
reference implementation and local bridge. Hosted production needs stronger
auth, tenant isolation, secret vaulting, request audit, queue durability, abuse
controls, observability, and deployment hardening.

## Scope Tiers

> [!IMPORTANT]
> This repository is a working reference prototype, not a hosted production
> service.

The project intentionally mixes working infrastructure with reference apps so
people can see the capability, run it locally, and adapt the parts they need.
Read it in three layers:

| Tier | What belongs here | How to judge it |
| --- | --- | --- |
| **Works now** | Local bridge, account capture, account routing, chat, streaming, image generation, image edits/composites, OCR/vision, Deep Research export, artifact downloads, Docker startup, the operator CLI, and the console control plane. | These are the core proof points. They should run locally and are the main reason this repo exists. |
| **Reference only** | Bridge Console UX, Character Game UX, opencode integration, screenshots, example prompts, demo storage views, docs UI, test lab flows. | These show how the API can be used. They are not the final commercial UX and may have rough edges. |
| **Production TODO** | Strong auth, tenant isolation, account vaulting, secret rotation, CORS policy, durable queues, storage lifecycle, audit logs, abuse controls, observability, backup/restore, deployment hardening. | Add these before turning the idea into a hosted multi-user product. They are known requirements, not forgotten work. |

That framing matters because the feature list is broad. The point of the repo
is to prove useful local capability and show realistic use cases, not to claim
that every included surface is already a polished production SaaS product.

## What This Is

`chatgpt-api` lets you run a local service that can:

- send normal and streaming chat requests through ChatGPT Web
- expose an OpenAI-shaped `POST /v1/chat/completions` route
- route across multiple ChatGPT accounts with failover or balancing strategies
- show live usage, model availability, image quota, and Deep Research quota
- generate images and save completed assets to disk
- edit or combine source images through ChatGPT image generation
- OCR or describe up to 10 input images per request
- run Deep Research and save the finished report as markdown
- return download URLs that work for local browsers and LAN clients
- inject/eject an opencode provider config
- power a separate SvelteKit character game app as a realistic product use case

The goal is not to pretend this is the official OpenAI API. The goal is a useful
local bridge with clear contracts, good operational tooling, and examples that
show what can be built with it.

## Unofficial Status, Risk, And Why This Exists

> [!WARNING]
> This is not official, not affiliated with OpenAI, and not guaranteed to keep
> working. ChatGPT Web can change, account captures can expire, browser-proof
> checks can fail, and hidden limits can appear. Use it only with that risk in
> mind.

This project is **not official** and is not affiliated with OpenAI. It drives
ChatGPT Web sessions from copied browser request captures and exposes a local
developer API around that behavior. That puts it in a gray area: it may break
when ChatGPT Web changes, it may be blocked by anti-abuse systems, and account
access can never be guaranteed.

Use it at your own risk:

- Do not run this as a public hosted proxy.
- Do not publish real account captures, cookies, or bearer tokens.
- Prefer a dedicated test account instead of a personal primary account.
- Keep concurrency low, especially for image generation, uploads, and research.
- Expect hidden burst limits even when the UI shows a large daily quota.

For local single-user workflows, the practical risk may be lower than operating
a public scraping service, but nobody can promise that an account will never be
restricted. The safest mental model is: this is an experimental local bridge,
not a supported product contract.

The reason it is still useful is simple: ChatGPT subscriptions and OpenAI API
billing are separate. If you already pay for a high ChatGPT plan such as Pro
(commonly around `$100/month` in supported regions; verify your local plan
price), the web product can include substantial image generation and Deep
Research capacity. Official API image generation is billed separately and can
become expensive at high quality. Verify current pricing before budgeting; as
a reference example for 1024x1024 image generation:

| Quality | Reference per-image API cost |
| --- | ---: |
| low | `$0.006` |
| medium | `$0.053` |
| high | `$0.211` |

> [!TIP]
> For image-heavy experiments, this bridge can be dramatically cheaper than
> paying per high-quality generated image through an official API, provided you
> already have ChatGPT Web quota. That does not remove the gray-area risk or
> hidden burst limits.

This bridge lets local tools use capacity you may already have in ChatGPT Web:
image generation, image editing/compositing, OCR/vision, and Deep Research.
That can also avoid burning Codex usage on tasks Codex is not best suited for:
for example, asking ChatGPT Web Deep Research to produce a markdown report,
then letting Codex read that local file and continue the coding work.

It is especially useful for smaller web products, internal tools, prototypes,
and demos where you want to add AI chat, image generation, OCR, or research
before committing to official API spend. A character/roleplay game is included
in this repository to show that the bridge can drive a real user-facing app,
not just a terminal demo. If you later turn the idea into a serious hosted
product, move to a proper production architecture and budget for official APIs
or a hardened provider layer.

Plan support is intentionally conservative. See [Tested Plan Notes](#tested-plan-notes)
for the current verified matrix.

The local router can combine several accounts, including free accounts, so chat
capacity can be much higher than a single account. This does not mean the
service is truly unlimited: ChatGPT Web can still apply hidden account, burst,
browser-proof, or abuse limits at any time.

In current testing, a Pro account can report roughly 1,000 image generations
remaining for the day, but that is not the same thing as unlimited burst
capacity. Too many concurrent image jobs can still trigger short hidden
cooldowns. The default local throttle keeps Pro image concurrency at `3` and
research concurrency at `2` for that reason.

## Built Solo In 30 Hours

This project was built by one person in roughly 30 hours as a practical AI
systems and product engineering prototype. It includes the provider layer,
local API, account routing, image/research artifact handling, operator console,
Docker stack, opencode integration, and a full-stack character game use case.

If this repository is useful to you or close to work your team needs, and you
think this level of solo output is valuable, I am open to employment,
contracting, and consulting opportunities around AI tooling, local agents,
automation, full-stack product prototypes, and developer infrastructure.

The public milestone is **100 GitHub stars**. If the project helps you, please
star the repository so there is a clear signal that this is worth continuing
after the initial open-source release.

## Open Source Scope

> [!NOTE]
> This repository is a working reference prototype, not a hosted production
> service. The console and game are included to prove the use cases, not to
> claim they are final commercial UI. The backend is intentionally scoped as a
> local bridge and example product foundation.

This is an MIT-licensed open-source project built to make the idea usable and
testable, not to provide a fully polished commercial product for free.

The Bridge Console and Character Game are reference applications. They prove
that the local API can drive real workflows, but they may still have rough UI,
unfinished edge cases, and bugs. They are intentionally included so people can
see the use cases, run them, fork them, open issues, and send pull requests.

The backend is also intentionally scoped as a local bridge and basic product
prototype. If you adapt this into a larger hosted system, you should add the
normal production layers: stronger auth, tenant isolation, stricter CORS,
request auditing, abuse controls, queue durability, account vaulting, secret
rotation, observability, backup/restore, deployment hardening, and a proper
storage lifecycle.

Those requirements are understood. They are outside the scope of a free
30-hour open-source release. If you need a more complete production version,
custom integration, stronger UX, or a hardened hosted setup, hire me.

## What This Is Not

- Not an official OpenAI service.
- Not a full clone of every OpenAI API endpoint.
- Not a hosted proxy. You run it locally or on your own machine.
- Not safe to publish with real captures or cookies. Account captures are
  credentials and must stay private.

Use the wording **OpenAI-shaped** or **Chat Completions-style** for this API.
Some clients can plug in easily, but several parameters and routes are
bridge-specific by design.

## Main Surfaces

| Surface | Default URL / command | Purpose |
| --- | --- | --- |
| Bridge API | `http://127.0.0.1:8000/v1` | Local app-facing API for chat, image, vision, research, files, and admin routes. |
| Bridge Console | `http://127.0.0.1:8080` | Operator UI for health, accounts, capacity, docs, test lab, storage, and opencode setup. |
| Character Game | `http://127.0.0.1:3000` | Full-stack SvelteKit roleplay game that consumes the bridge as a backend. |
| CLI | `python3 -m chatgpt_api` or `chatgpt-api` | Interactive and scriptable control plane for server launch, account management, tests, and artifacts. |
| opencode | `bun integrations/opencode/chatgpt-opencode.mjs` | Consumer setup that points opencode at the local bridge. |

## Quick Start With Docker

Docker is the fastest way to see the whole system: API, Console, Character
Game, storage, and docs.

### Five-Minute Path

| Time | Action | Result |
| --- | --- | --- |
| 1 min | Copy `.env.example` and start Docker | Console, API health, docs, and game shell are online. |
| 2 min | Add one ChatGPT account capture | Chat, image, vision/OCR, and research routes can use that account. |
| 1 min | Run capacity check | See accounts, model aliases, local concurrency, quota metadata, and artifact paths. |
| 1 min | Try the game or API examples | Confirm the bridge works as an app backend, not only a CLI demo. |

| Step | What works | What still needs an account capture |
| --- | --- | --- |
| Start Docker with no captures | API health, Console, docs, storage view, model aliases, Character Game shell | Real ChatGPT chat/image/research calls |
| Add one account capture | Chat, streaming, image generation, OCR/vision, research according to that account's plan and limits | More capacity/failover needs more accounts |

### Start The Stack

```sh
cp .env.example .env
mkdir -p secrets/accounts outputs
docker compose up --build
```

### Open The Surfaces

```text
API health:     http://127.0.0.1:8000/health
API base URL:   http://127.0.0.1:8000/v1
Console:        http://127.0.0.1:8080
Character game: http://127.0.0.1:3000
Bearer key:     local-dev-key
```

### Smoke Test

```sh
curl 'http://127.0.0.1:8000/health' \
  -H 'Authorization: Bearer local-dev-key'

curl 'http://127.0.0.1:8000/v1/models' \
  -H 'Authorization: Bearer local-dev-key'
```

These two checks only prove the local stack is online. Real ChatGPT chat,
image, vision, and research calls need at least one saved account capture.

### Add Your First Account

Console flow:

1. Open `http://127.0.0.1:8080`.
2. Go to Accounts.
3. Choose Add account.
4. Paste copied ChatGPT headers plus payload/request data, or paste full
   `Copy as cURL` output.
5. Save. The Console inspects required fields first and then live-verifies the
   account before routing it.

CLI flow while Docker is running:

```sh
python3 -m chatgpt_api admin account add --paste \
  --base-url http://127.0.0.1:8000/v1 \
  --api-key local-dev-key
```

After the account is saved, verify capacity:

```sh
python3 -m chatgpt_api admin capacity \
  --base-url http://127.0.0.1:8000/v1 \
  --api-key local-dev-key
```

## Quick Start Without Docker

Use the module command first. It works even when your Python scripts directory
is not on `PATH`.

```sh
python3 -m venv .venv
source .venv/bin/activate
python3 -m pip install -e '.[dev]'
python3 -m chatgpt_api doctor
python3 -m chatgpt_api menu
python3 -m chatgpt_api server start --interactive
```

If `chatgpt-api` works on your machine, it is only a shorter alias:

```sh
chatgpt-api doctor
chatgpt-api menu
```

Or use explicit flags:

```sh
python3 -m chatgpt_api server start \
  --account-strategy failover \
  --api-key local-dev-key \
  --host 127.0.0.1 \
  --port 8000 \
  --public-base-url http://127.0.0.1:8000/v1
```

For LAN use:

```sh
python3 -m chatgpt_api server start \
  --account-strategy failover \
  --api-key local-dev-key \
  --host 0.0.0.0 \
  --port 8000 \
  --public-base-url http://192.168.1.203:8000/v1
```

If you omit `--accounts`, the server auto-discovers saved captures under
`secrets/accounts/*`. Add `--accounts main-free,image-pro` only when you want to
pin a clean route pool or skip an old/broken capture. `--account` and
`--accounts` are local aliases you choose, such as `main-free`, `image-pro`,
`free-2`, or `work-pro`; they are not automatic plan selectors.

## Account Capture

Each ChatGPT account needs one copied browser request capture. The capture
contains cookies, bearer tokens, and browser proof headers. Treat it like a
password.

> [!CAUTION]
> Account captures are credentials. Never commit them, paste them into public
> issues, or share them with hosted services you do not control.

Supported capture paths today:

- Safari Web Inspector
- Chrome DevTools

Recommended routine:

1. Open `https://chatgpt.com` in a private/incognito window or dedicated browser
   profile.
2. Sign in to the account you want to use.
3. Do not log out after collecting the capture.
4. Open a fresh ChatGPT conversation, or use an existing conversation if that is
   easier. The capture is used for credentials/request shape; API calls still
   carry the message history you send in each request and do not automatically
   continue that browser chat.
5. Open DevTools or Web Inspector.
6. Go to Network.
7. Send a small message such as `hello`.
8. Wait until the ChatGPT response starts or finishes, then find the request to
   `https://chatgpt.com/backend-api/f/conversation`. Do not copy a
   `/conversation/prepare` request or a telemetry request.
9. Copy the request in one of these supported formats:
   - Chrome/Safari headers plus the full JSON payload or Safari `Request Data`.
   - Chrome/Safari `Copy as cURL` output, including Authorization, cookies
     through `Cookie:` or `-b`, and the `--data-raw ...` JSON body. Paste this
     command into the bridge capture field; do not run it against ChatGPT.
10. Paste the capture into the console account modal or save it to a local text
    file.

Account names must be ASCII slugs:

```text
valid:   main-free, image-pro, free_2, team-pro
invalid: บัญชีฟรี, pro main, pro/main
```

Do not commit:

```text
secrets/
.env
copied headers
cookies
bearer tokens
raw request captures
```

Captures are temporary. In practice they often last around 10 days, but this is
not guaranteed. Refresh demo accounts weekly if you do not want them to expire
in the middle of a run.

Full guide: [docs/ACCOUNT_CAPTURE.md](docs/ACCOUNT_CAPTURE.md)

## Add, Update, Verify, And Delete Accounts

Through the console:

```text
http://127.0.0.1:8080/#accounts
```

Through the CLI:

```sh
python3 -m chatgpt_api admin account add \
  --account main-free \
  --capture-file ./chatgpt-request.txt \
  --base-url http://127.0.0.1:8000/v1 \
  --api-key local-dev-key
```

Update an expired capture:

```sh
python3 -m chatgpt_api admin account update \
  --account main-free \
  --capture-file ./chatgpt-request.txt \
  --base-url http://127.0.0.1:8000/v1 \
  --api-key local-dev-key
```

Paste interactively instead of using a file:

```sh
python3 -m chatgpt_api admin account add --paste \
  --base-url http://127.0.0.1:8000/v1 \
  --api-key local-dev-key
```

The CLI accepts pasted headers plus payload, or a full `Copy as cURL` command,
until a line containing only:

```text
END_CAPTURE
```

Verify accounts:

```sh
python3 -m chatgpt_api admin account verify \
  --account all \
  --base-url http://127.0.0.1:8000/v1 \
  --api-key local-dev-key
```

Delete an account capture and settings:

```sh
python3 -m chatgpt_api admin account delete \
  --account old-free \
  --base-url http://127.0.0.1:8000/v1 \
  --api-key local-dev-key
```

The add/update flow inspects the capture first and should refuse to save when
required pieces are missing.

## API Overview

| Route | Purpose |
| --- | --- |
| `GET /health` | Server health and configuration summary. |
| `GET /v1/models` | Models and bridge aliases visible to the current route. |
| `GET /v1/chatgpt/usage` | Live per-account usage and quota metadata when ChatGPT reports it. |
| `POST /v1/chat/completions` | Chat, streaming chat, tool-call bridge, chat-triggered images, and Deep Research. |
| `POST /v1/images/generations` | Generate one completed image and save it. |
| `POST /v1/images/edits` | Upload source image(s), edit or composite them, and save one completed image. |
| `POST /v1/chatgpt/vision` | OCR, describe, or custom vision prompt for up to 10 input images. |
| `GET/HEAD /v1/chatgpt/files/{file_id}/{filename}` | Download generated images or Deep Research reports. `HEAD` returns the same metadata headers without the file body. |
| `GET /v1/chatgpt/operations/{operation_id}` | Inspect whether a long job has a selected account, conversation id, or Deep Research widget session. |
| `POST /v1/chatgpt/operations/{operation_id}/cancel` | Cancel long chat, image, or research work when possible. |
| `/v1/chatgpt/admin/*` | Local operator routes used by the console and CLI. |

Full route details: [docs/OPENAI_COMPATIBILITY.md](docs/OPENAI_COMPATIBILITY.md)

## Chat Example

```sh
curl 'http://127.0.0.1:8000/v1/chat/completions' \
  -X POST \
  -H 'Authorization: Bearer local-dev-key' \
  -H 'Content-Type: application/json' \
  --data-raw '{
    "model": "auto",
    "messages": [
      {
        "role": "user",
        "content": "Reply with exactly: bridge ok"
      }
    ],
    "stream": false
  }'
```

Example response:

```json
{
  "id": "chatcmpl_local",
  "object": "chat.completion",
  "created": 1782320100,
  "model": "auto",
  "chatgpt_account": "main-free",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "bridge ok"
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 0,
    "completion_tokens": 0,
    "total_tokens": 0
  }
}
```

Streaming uses the same route with `"stream": true` and returns SSE
`chat.completion.chunk` events followed by:

```text
data: [DONE]
```

## Tool-Calling Bridge

Clients can pass OpenAI-style `tools`. The bridge asks ChatGPT Web to emit a
strict JSON tool call, validates the requested tool name, and returns
OpenAI-style `tool_calls`.

Important behavior:

- the local server never executes tools
- the client or agent executes tool calls
- `@optimized` uses a compact agent bridge prompt
- `@opencode` preserves more opencode-style tool and skill detail

Example models:

```text
chatgpt-web/auto@optimized
chatgpt-web/auto@opencode
chatgpt-web/gpt-5-5@optimized
```

## Image Generation

`n` is fixed to one completed image in this bridge.

```sh
curl 'http://127.0.0.1:8000/v1/images/generations' \
  -X POST \
  -H 'Authorization: Bearer local-dev-key' \
  -H 'Content-Type: application/json' \
  --data-raw '{
    "model": "gpt-image-1",
    "prompt": "A clean blue glass app icon, no text",
    "n": 1
  }'
```

Example response:

```json
{
  "created": 1782320100,
  "chatgpt_account": "image-pro",
  "chatgpt_operation_id": "chatgptop_abc",
  "data": [
    {
      "url": "http://127.0.0.1:8000/v1/chatgpt/files/file_icon/icon.png",
      "download_url": "http://127.0.0.1:8000/v1/chatgpt/files/file_icon/icon.png",
      "path": "/Users/work/Desktop/chatgpt-api/outputs/chatgpt-images/icon.png",
      "filename": "icon.png",
      "content_type": "image/png"
    }
  ]
}
```

Use `download_url` from browsers and LAN devices. Use `path` only when the
client runs on the same filesystem as the API server.

## Image Edits And Multi-Image Composites

`POST /v1/images/edits` uploads one to 10 source images, asks ChatGPT to edit or
combine them, and saves exactly one completed output image.

Single image edit:

```sh
curl 'http://127.0.0.1:8000/v1/images/edits' \
  -X POST \
  -H 'Authorization: Bearer local-dev-key' \
  -H 'Content-Type: application/json' \
  --data-raw '{
    "prompt": "Change the icon letters to FW while preserving the same style.",
    "image": "./favicon.png",
    "aspect_ratio": "1:1"
  }'
```

Multi-image composite:

```sh
curl 'http://127.0.0.1:8000/v1/images/edits' \
  -X POST \
  -H 'Authorization: Bearer local-dev-key' \
  -H 'Content-Type: application/json' \
  --data-raw '{
    "prompt": "Combine these input images into one fantasy character poster.",
    "images": ["./character.png", "./armor-style.png", "./background.png"],
    "aspect_ratio": "4:3"
  }'
```

Supported aspect ratios:

```text
auto
1:1
3:4
9:16
4:3
16:9
```

Important: image edits preserve layout best when source images already match one
of the supported ratios. If `auto` is used with an unusual source ratio, the
output canvas can change size and object positions can shift.

## Vision And OCR

`POST /v1/chatgpt/vision` returns assistant text. By default OCR returns plain
text, but the route is prompt-driven: you can ask for markdown, strict JSON,
line blocks, approximate bounding boxes, translation pairs, or any other shape
your app wants to parse. It does not create an artifact file.

Structured OCR with approximate boxes:

```sh
curl 'http://127.0.0.1:8000/v1/chatgpt/vision' \
  -X POST \
  -H 'Authorization: Bearer local-dev-key' \
  -H 'Content-Type: application/json' \
  --data-raw '{
    "mode": "ocr",
    "image": "./panel.png",
    "prompt": "Return strict JSON only. Schema: {\"items\":[{\"text\":\"string\",\"bbox\":{\"x\":0,\"y\":0,\"w\":0,\"h\":0},\"confidence\":\"low|medium|high\"}]}. Use pixel coordinates relative to the input image. If exact boxes are uncertain, estimate them and set confidence accordingly."
  }'
```

Important: bbox output is model-estimated. This is useful for prototypes,
caption placement, manga/manhwa panel tooling, and lightweight UI overlays, but
it is not the same as a dedicated OCR engine with native layout detection. For
production-grade document OCR, use a real OCR/layout engine and optionally ask
ChatGPT to clean, translate, group, or interpret the result.

Accepted image inputs:

- local path on the API server
- public HTTP or HTTPS URL
- `data:image/...;base64,...`
- raw base64 image string
- arrays through `images`, `input_images`, or multimodal chat content

One request can include up to 10 input images. Upload concurrency is shared by
OCR, describe, chat-with-image, image edit, and image composite requests. The
same request also consumes ChatGPT `file_upload` usage when that quota is
reported by the account metadata.

## Deep Research

Use the `chatgpt-deep-research` model alias through chat completions.

```sh
curl 'http://127.0.0.1:8000/v1/chat/completions' \
  -X POST \
  -H 'Authorization: Bearer local-dev-key' \
  -H 'Content-Type: application/json' \
  --data-raw '{
    "model": "chatgpt-deep-research",
    "messages": [
      {
        "role": "user",
        "content": "Research whether LLMs can reach AGI. Keep it concise."
      }
    ]
  }'
```

Example response:

```json
{
  "id": "chatcmpl_research",
  "object": "chat.completion",
  "model": "chatgpt-deep-research",
  "chatgpt_account": "research-pro",
  "choices": [
    {
      "message": {
        "role": "assistant",
        "content": "Done. Deep Research report saved.\npath=/Users/work/Desktop/chatgpt-api/outputs/chatgpt-research/llm-agi.md\ndownload_url=http://127.0.0.1:8000/v1/chatgpt/files/file_research/llm-agi.md"
      },
      "finish_reason": "stop"
    }
  ]
}
```

The markdown file is the product. The chat response should only tell the client
where the report was saved. Deep Research should use normal ChatGPT chat mode,
not temporary chat mode, because the connector flow is not available in
temporary chats.

## Cancellation

Long requests return a `chatgpt_operation_id` when the bridge can expose one.
Frontends should cancel provider work when the user clicks cancel, closes a
route, refreshes the page, or aborts a request. Cancellation is best effort.
Operation records are runtime state, not durable storage. They are intended for
the currently running request and are lost when the API process or container
restarts. Completed artifact download URLs are separate and can survive restarts
when the artifact file and admin DB are persisted.
For Deep Research, the bridge reads the ChatGPT widget session from the WSS
stream first, then sends the Deep Research MCP `stop` call once it has
`conversation_id`, assistant `message_id`, and widget `session_id`.

```sh
curl 'http://127.0.0.1:8000/v1/chatgpt/operations/chatgptop_abc' \
  -H 'Authorization: Bearer local-dev-key'

curl 'http://127.0.0.1:8000/v1/chatgpt/operations/chatgptop_abc/cancel' \
  -X POST \
  -H 'Authorization: Bearer local-dev-key'
```

Example response:

```json
{
  "status": "ok",
  "operation": {
    "id": "chatgptop_abc",
    "kind": "research",
    "provider_selected": true,
    "conversation_id": "conversation-id",
    "deep_research_ready": true,
    "pending_reason": null,
    "cancel_requested": true,
    "completed": false,
    "last_cancel_result": {
      "conversation": {
        "status": "ok"
      }
    }
  }
}
```

If the stop identifiers are not known yet, the operation is marked
`cancel_requested` and the provider stop is attempted as soon as the running
request reaches the point where those identifiers are available. For a manual
Deep Research cancel, poll the operation route until `deep_research_ready=true`
or until the ChatGPT research job has passed the bypass / confirmation stage.

## Models

`GET /v1/models` is the source of truth for the current route. It merges the
aliases supported by the server with what the configured accounts appear to
support.

Representative aliases:

| Model alias | Use |
| --- | --- |
| `auto` | Safest default. Use this for Free and Go accounts. |
| `gpt-5-5` | Explicit ChatGPT Web model when the account supports it. |
| `gpt-5-5-thinking-standard` | Thinking mode, standard effort. |
| `gpt-5-5-thinking-extended` | Thinking mode, extended effort. |
| `gpt-5-5-thinking-max` | Thinking mode, highest effort. |
| `gpt-5-5-pro-standard` | Pro mode, standard effort. |
| `gpt-5-5-pro-extended` | Pro mode, extended effort. |
| `gpt-image-1` | Image generation route. |
| `chatgpt-deep-research` | Deep Research through chat completions. |
| `auto@optimized` | Compact agent/tool bridge prompt. |
| `auto@opencode` | Heavier opencode-oriented bridge prompt. |

Free and Go accounts should normally stay on `auto`. Higher-effort model aliases
should route only to accounts that actually support them.

## Accounts, Routing, And Local Limits

Routing strategies:

```text
auto
sticky
failover
random
round-robin
weighted
quota-aware
```

Recommended local concurrency defaults:

| Feature bucket | Free | Go | Plus | Pro |
| --- | ---: | ---: | ---: | ---: |
| chat | 1 | 2 | 3 | 4 |
| upload | 1 | 1 | 1 | 1 |
| image | 1 | 1 | 2 | 3 |
| research | 1 | 1 | 2 | 2 |

`upload` is the source-image bucket. It is used before OCR, image
description, chat-with-image, image edits, and multi-image composites. For
edit/composite requests the bridge checks both `image_gen` and `file_upload`
when ChatGPT reports those features. For Deep Research it checks
`deep_research`.

When several accounts are configured, normal routing order is still respected,
but image-input, image-generation, and research requests preflight reported
feature quota first. Accounts with a blocked or exhausted reported feature move
behind accounts that still look usable. If ChatGPT returns `not_reported`, the
bridge treats that as unknown capacity rather than blocked; this avoids
incorrectly skipping accounts whose plan simply does not expose that counter.
Hidden burst limits can still happen after preflight.

Two Pro accounts with image concurrency `3` each can run up to six local image
jobs. That is only a local throttle. ChatGPT Web can still apply hidden burst
rate limits, especially for image generation and Deep Research.

## Usage And Capacity

Check current account state:

```sh
curl 'http://127.0.0.1:8000/v1/chatgpt/usage' \
  -H 'Authorization: Bearer local-dev-key'
```

CLI:

```sh
chatgpt-api admin usage \
  --base-url http://127.0.0.1:8000/v1 \
  --api-key local-dev-key

chatgpt-api admin capacity \
  --base-url http://127.0.0.1:8000/v1 \
  --api-key local-dev-key
```

When ChatGPT reports reset times, the bridge returns them in UTC timestamps.
Some plans or features do not report every reset time.

## Files, Downloads, And LAN Use

Completed images and Deep Research reports are saved locally:

```text
outputs/chatgpt-images/
outputs/chatgpt-research/
```

The API also registers an HTTP download route:

```text
GET/HEAD /v1/chatgpt/files/{file_id}/{filename}
```

Download URLs survive API restarts when the artifact file and admin DB path are
kept on disk or mounted as Docker volumes. `GET` returns the file body; `HEAD`
returns the same metadata headers for clients that probe before downloading.

For LAN clients, start the API with `--host 0.0.0.0` and set
`--public-base-url` to the LAN address:

```sh
python3 -m chatgpt_api server start \
  --host 0.0.0.0 \
  --port 8000 \
  --api-key local-dev-key \
  --public-base-url http://192.168.1.203:8000/v1
```

If `public-base-url` stays on `127.0.0.1`, a phone or another computer on the
LAN will receive download links pointing back to itself instead of the bridge
machine.

List artifacts:

```sh
chatgpt-api admin artifacts \
  --base-url http://127.0.0.1:8000/v1 \
  --api-key local-dev-key
```

Delete metadata only:

```sh
chatgpt-api admin delete-artifact \
  --file-id file_example \
  --base-url http://127.0.0.1:8000/v1 \
  --api-key local-dev-key
```

Delete metadata and file:

```sh
chatgpt-api admin delete-artifact \
  --file-id file_example \
  --delete-file \
  --base-url http://127.0.0.1:8000/v1 \
  --api-key local-dev-key
```

## Bridge Console

The console is the operational UI, not just a demo page.

![Accounts page](https://raw.githubusercontent.com/suphotP/chatgpt-api/main/docs/assets/screenshots/oss-console-accounts.png)

It provides:

- system health and API status
- account list, add, update, verify, and delete flows
- account-name validation
- usage and capacity views
- route documentation with request and response examples
- test lab for chat, context, image, vision/OCR, and research
- storage/library view for completed artifacts
- opencode inject/eject/status controls

Run locally:

```sh
cd apps/bridge-console
bun install
bun run dev
```

Build:

```sh
cd apps/bridge-console
bun run check
bun run build
```

Docker serves the built console through nginx on port `8080`.

## Character Game Use Case

The character game is a separate app server that calls the bridge. It is meant
to show what a real product can do with the local API.

![Character game setup](https://raw.githubusercontent.com/suphotP/chatgpt-api/main/docs/assets/screenshots/oss-game-setup.png)

It owns:

- sessions
- messages
- route themes
- story state
- choices and hints
- scene-art jobs
- cancellation
- local SQLite persistence
- local image cache

The bridge owns:

- ChatGPT account routing
- provider credentials
- chat/image/research calls
- generated artifacts and download URLs

Run locally:

```sh
cd apps/character-game
cp .env.example .env
bun install
bun run dev
```

Useful environment:

| Variable | Default | Purpose |
| --- | --- | --- |
| `CHATGAME_OPENAI_BASE_URL` | `http://127.0.0.1:8000/v1` | Server-side bridge URL. |
| `CHATGAME_PUBLIC_OPENAI_BASE_URL` | same as internal URL | Browser-facing URL shown in route settings and downloads. |
| `CHATGAME_OPENAI_API_KEY` | `local-dev-key` | Bearer key for the local bridge. |
| `CHATGAME_CHAT_MODEL` | `chatgpt-web/auto` | Chat model used for story turns. |
| `CHATGAME_IMAGE_MODEL` | `chatgpt-web/auto` | Image model used for scene art. |
| `CHATGAME_DB_PATH` | `.data/arcadia.sqlite` | SQLite database path. |
| `CHATGAME_IMAGE_DIR` | `.data/images` | Game image cache directory. |
| `CHATGAME_AI_MODE` | `live` | Set `mock` for UI-only work without provider quota. |

Checks:

```sh
cd apps/character-game
bun run check
bun run test
bun run build
```

## opencode Integration

The opencode integration is a consumer adapter. It writes or removes opencode
config that points at the bridge. It does not manage ChatGPT accounts or start
the API server.

Interactive setup:

```sh
bun integrations/opencode/chatgpt-opencode.mjs
```

After setup, daily use should be normal opencode:

```sh
opencode .
```

Scriptable inject:

```sh
bun integrations/opencode/opencode-config.mjs --inject \
  --base-url http://127.0.0.1:8000/v1 \
  --api-key local-dev-key \
  --model chatgpt-web/auto@optimized
```

Status:

```sh
bun integrations/opencode/opencode-config.mjs --status \
  --base-url http://127.0.0.1:8000/v1 \
  --api-key local-dev-key
```

Eject:

```sh
bun integrations/opencode/opencode-config.mjs --eject \
  --base-url http://127.0.0.1:8000/v1 \
  --api-key local-dev-key
```

Full guide: [integrations/opencode/README.md](integrations/opencode/README.md)

## CLI Cheat Sheet

Use `python3 -m chatgpt_api ...` in docs and copy-paste commands. Use
`chatgpt-api ...` only if your shell can already find the installed script.

Interactive menu:

```sh
python3 -m chatgpt_api
python3 -m chatgpt_api menu
```

Doctor:

```sh
python3 -m chatgpt_api doctor
python3 -m chatgpt_api doctor --json
```

Print launch presets:

```sh
python3 -m chatgpt_api server command --preset local
python3 -m chatgpt_api server command --preset lan
python3 -m chatgpt_api server command --preset docker
python3 -m chatgpt_api server command \
  --preset local \
  --host 127.0.0.1 \
  --port 8010 \
  --public-base-url http://127.0.0.1:8010/v1 \
  --account-strategy random
python3 -m chatgpt_api admin presets
```

Start the API:

```sh
python3 -m chatgpt_api server start --interactive
python3 -m chatgpt_api server start --api-key local-dev-key
python3 -m chatgpt_api server start --account-strategy random --api-key local-dev-key
python3 -m chatgpt_api server start --accounts main-free,image-pro --account-strategy random --api-key local-dev-key
```

Start with a passphrase-derived key instead of the auto key file (prompts at
launch, never written to disk):

```sh
python3 -m chatgpt_api server start --secrets-passphrase-prompt
```

Rotate account-capture encryption onto a passphrase (or back onto a fresh
auto key file):

```sh
python3 -m chatgpt_api secrets rotate --accounts-dir secrets/accounts --to-passphrase-prompt
python3 -m chatgpt_api secrets rotate --accounts-dir secrets/accounts
```

API chat through the running server and router:

```sh
python3 -m chatgpt_api api chat \
  --message "Reply with exactly: bridge ok" \
  --accounts main-free,image-pro \
  --account-strategy random \
  --base-url http://127.0.0.1:8000/v1 \
  --api-key local-dev-key
```

API image generation:

```sh
python3 -m chatgpt_api api image \
  --prompt "small blue app icon, no text" \
  --output-dir ./outputs/manual-images \
  --base-url http://127.0.0.1:8000/v1 \
  --api-key local-dev-key
```

API OCR / vision:

```sh
python3 -m chatgpt_api api vision \
  --mode ocr \
  --input-image ./favicon.png \
  --prompt "Extract visible letters only" \
  --base-url http://127.0.0.1:8000/v1 \
  --api-key local-dev-key
```

API Deep Research with cancellation:

```sh
python3 -m chatgpt_api api research \
  --prompt "Briefly research whether LLMs could reach AGI." \
  --operation-id chatgptop_research_demo \
  --base-url http://127.0.0.1:8000/v1 \
  --api-key local-dev-key

python3 -m chatgpt_api api operation \
  --operation-id chatgptop_research_demo \
  --base-url http://127.0.0.1:8000/v1 \
  --api-key local-dev-key

python3 -m chatgpt_api api cancel \
  --operation-id chatgptop_research_demo \
  --base-url http://127.0.0.1:8000/v1 \
  --api-key local-dev-key
```

For Deep Research, wait until `api operation` shows
`deep_research_ready=yes` before expecting the MCP stop call to happen
immediately. Cancelling earlier still marks the operation as
`cancel_requested`, then the bridge attempts the stop once the widget session is
known.

The older direct provider commands (`chat`, `image`, `vision`) still exist for
local capture diagnostics. Use `api ...` when you want the real server route,
account strategy, artifact store, and operation cancellation behavior.

## Troubleshooting

### `chatgpt-api: command not found`

The package may be installed correctly while the generated script is outside
your shell `PATH`. `pip` prints the install directory when this happens. On
macOS framework Python it can be similar to
`/Library/Frameworks/Python.framework/Versions/3.13/bin`.

Use the module fallback:

```sh
python3 -m chatgpt_api doctor
python3 -m chatgpt_api server start --interactive
```

Or add the scripts directory printed by `pip` to your shell `PATH`.

### Docker starts, but chat/image does not work

That is expected when no account capture exists yet. Docker can boot the API,
Console, docs, storage, and game shell without accounts. Real ChatGPT calls
need at least one capture added from the Console Accounts page or the CLI:

```sh
python3 -m chatgpt_api admin account add --paste \
  --base-url http://127.0.0.1:8000/v1 \
  --api-key local-dev-key
```

Full CLI guide: [docs/CLI.md](docs/CLI.md)

## Configuration

Common environment variables:

| Variable | Default | Purpose |
| --- | --- | --- |
| `CHATGPT_API_HOST` | `127.0.0.1` locally, `0.0.0.0` in Docker | API bind host. |
| `CHATGPT_API_PORT` | `8000` | API port. |
| `CHATGPT_API_KEY` | `local-dev-key` in examples | Local bearer key. |
| `CHATGPT_ACCOUNT` | empty | Optional primary account alias. When blank, the first discovered/pinned account is used. |
| `CHATGPT_ACCOUNTS` | empty | Optional comma-separated account aliases. When blank, saved captures under `secrets/accounts/*` are auto-discovered. |
| `CHATGPT_ACCOUNT_STRATEGY` | `auto` locally, `failover` in compose | Account routing strategy. |
| `CHATGPT_ACCOUNTS_DIR` | `./secrets/accounts` | Account capture directory. |
| `CHATGPT_PUBLIC_BASE_URL` | `http://127.0.0.1:8000/v1` | Download URL base for artifacts. |
| `CHATGPT_IMAGE_OUTPUT_DIR` | `./outputs/chatgpt-images` | Generated image directory. |
| `CHATGPT_RESEARCH_OUTPUT_DIR` | `./outputs/chatgpt-research` | Deep Research report directory. |
| `CHATGPT_ADMIN_DB_PATH` | `./outputs/chatgpt-admin.sqlite` | Console/admin SQLite metadata. |
| `CHATGPT_AGENT_MODE` | `optimized` | Tool bridge prompt mode. |
| `CHATGPT_MODEL_FALLBACK` | `auto` | Fallback model after recoverable model errors. |
| `CHATGPT_TEMPORARY_CHAT` | `true` | Use temporary ChatGPT chats for normal chat completions. |
| `CHATGPT_WEB_TIMEOUT` | `5400` | Provider timeout in seconds; long enough for Deep Research. |
| `CHATGPT_CHAT_CONCURRENCY` | plan defaults | Local chat throttle. |
| `CHATGPT_UPLOAD_CONCURRENCY` | plan defaults | Local OCR/edit/composite upload throttle. |
| `CHATGPT_IMAGE_CONCURRENCY` | plan defaults | Local image throttle. |
| `CHATGPT_RESEARCH_CONCURRENCY` | plan defaults | Local Deep Research throttle. |

See [.env.example](.env.example) for the complete local template.

## Updating An Existing Checkout

Existing account captures and settings remain compatible with the current
code. Saved captures under `secrets/accounts/<account>/chatgpt-request.txt`
are still read from the same path, encrypted captures are decrypted with the
existing secrets key, and legacy plaintext captures are still read
transparently. If `CHATGPT_ACCOUNTS` is blank, the server continues to
auto-discover saved account folders.

Newer routing only adds extra preflight ordering for reported usage. It does
not change the account file format or require users to recreate captures. Keep
the same Docker volume mounts for `./secrets/accounts` and `./outputs` so
account captures, admin metadata, and generated files survive rebuilds.

## Docker

Compose services:

```text
chatgpt-api      -> http://127.0.0.1:8000
bridge-console   -> http://127.0.0.1:8080
character-game   -> http://127.0.0.1:3000
```

Build only the API image:

```sh
docker build -t chatgpt-api:local .
```

Run the whole stack:

```sh
docker compose up --build
```

Run in the background:

```sh
docker compose up -d --build
docker compose ps
```

Stop:

```sh
docker compose down
```

Docker images do not bundle account captures. The compose file mounts:

```text
./secrets/accounts -> /data/secrets/accounts
./outputs          -> /data/outputs
```

Full Docker guide: [docs/DOCKER.md](docs/DOCKER.md)

## Repository Map

```text
chatgpt_api/
  core/                 Provider-neutral request/response contracts.
  providers/chatgpt/    ChatGPT Web capture, auth, token refresh, proof, transport, models.
  api/                  Local HTTP API facade, admin routes, image input parsing, prompts.
  cli.py                Operator CLI and direct provider commands.

apps/
  bridge-console/       Svelte/Vite operator console.
  character-game/       SvelteKit roleplay game use case.

integrations/
  opencode/             opencode config injector and launcher.

docs/
  ACCOUNT_CAPTURE.md    Browser capture guide.
  ARCHITECTURE.md       Maintainer architecture notes.
  CLI.md                CLI guide.
  DOCKER.md             Docker and Compose guide.
  OPENAI_COMPATIBILITY.md API route and response details.
  PROJECT_ANALYSIS.md   Maintainer-level project analysis.
  assets/screenshots/   Screenshot evidence from the Docker stack.

tests/                  Python tests for capture parsing, auth, account info, CLI, and API.
secrets/                Local account captures. Never commit.
outputs/                Generated images, research reports, and SQLite metadata.
```

## Verification

Python:

```sh
python3 -m compileall chatgpt_api tests
python3 -m pytest
```

Console:

```sh
cd apps/bridge-console
bun install
bun run check
bun run build
```

Character game:

```sh
cd apps/character-game
bun install
bun run check
bun run test
bun run build
```

Docker:

```sh
docker compose up -d --build
curl 'http://127.0.0.1:8000/health' -H 'Authorization: Bearer local-dev-key'
curl 'http://127.0.0.1:8000/v1/models' -H 'Authorization: Bearer local-dev-key'
docker compose ps
```

Screenshot evidence:

```text
docs/assets/screenshots/
```

See [docs/assets/screenshots/README.md](docs/assets/screenshots/README.md) for
what each captured view proves.

## License

MIT. See [LICENSE](LICENSE).

## Security Notes

- Keep `secrets/` out of git.
- Keep `.env` out of git.
- Do not paste real captures into issues, screenshots, README examples, or logs.
- Do not expose the API to the public internet with a weak bearer key.
- For LAN demos, use a strong `CHATGPT_API_KEY`.
- Generated files under `outputs/` can contain private prompts, images, and
 research reports.
- Account captures are encrypted at rest. The first save under a
 `secrets/accounts/` tree auto-generates an owner-only (`0600`) master key
 file (`secrets/accounts/.master.key`) and encrypts the capture with it; old
 plaintext captures are still read transparently, so no manual migration is
 required.
- This default (auto key file) only protects against the capture file
 leaking on its own (a backup, a cloud sync, a copy-paste mistake). It does
 **not** protect against someone who copies the whole `secrets/` directory,
 since the key sits right next to the data it unlocks, and it does not
 protect against a live-compromised machine: while the bridge is running it
 holds decrypted tokens in memory to make real requests, and any caller who
 can reach the local API can already use those tokens. No local at-rest
 scheme closes that second gap.
- For real protection against a stolen laptop or leaked backup (the data
 carries no usable key at all), start the server with
 `--secrets-passphrase-prompt` instead of relying on the auto key file. You
 will be prompted for a passphrase at launch; it is held in memory for that
 process only and never written to disk or the environment. Use
 `CHATGPT_SECRETS_PASSPHRASE` instead if you need a non-interactive
 (Docker/headless) equivalent — convenient, but weaker, since the passphrase
 can end up in shell history, `.env` files, or process listings.
- Switching between key modes (auto key file <-> passphrase) requires
 re-encrypting existing captures, since the old key can no longer be derived
 automatically. Use:
 ```sh
 chatgpt-api secrets rotate --accounts-dir secrets/accounts --to-passphrase-prompt
 ```
 to move from the auto key file to a passphrase (this also deletes the old
 key file once every capture is confirmed re-encrypted), or omit
 `--to-passphrase-prompt` to encrypt legacy plaintext captures or rotate onto
 a fresh auto-generated key file.
 Add `--from-passphrase-prompt` if the captures are currently encrypted with
 a passphrase that is not in `CHATGPT_SECRETS_PASSPHRASE`. If you rotate back
 to auto key-file mode, unset `CHATGPT_SECRETS_PASSPHRASE` before starting the
 server; environment passphrases intentionally take priority at runtime.

## Troubleshooting

`request body must be JSON`
: Your curl command likely missed a trailing `\` before a header line or did not
  send `Content-Type: application/json`. Use the examples in this README as
  copy-paste templates.

`403` from ChatGPT Web
: Refresh the account capture from the same browser session. If Chrome keeps
  failing, try a fresh Chrome profile or Safari capture.

`conversation/init returned no metadata`
: ChatGPT did not return account metadata for the probe. Refresh the capture or
  retry later.

Image completes in ChatGPT but no file is returned
: Retry with another account/model after checking `/v1/chatgpt/usage`. The
  bridge only records completed image assets it can download and save.

LAN client cannot open image links
: Set `CHATGPT_PUBLIC_BASE_URL` or `--public-base-url` to the bridge machine's
  LAN URL instead of `127.0.0.1`.

Deep Research does not start
: Use `chatgpt-deep-research`, use an account that has Deep Research quota, and
  use normal chat mode instead of temporary chat mode.

opencode does not use the bridge
: Run the opencode injector again and verify `~/.config/opencode/opencode.json`
  points at your bridge base URL and bearer key.

## Documentation Index

- [Account capture guide](docs/ACCOUNT_CAPTURE.md)
- [CLI guide](docs/CLI.md)
- [Docker guide](docs/DOCKER.md)
- [OpenAI-shaped API guide](docs/OPENAI_COMPATIBILITY.md)
- [Architecture notes](docs/ARCHITECTURE.md)
- [Project analysis](docs/PROJECT_ANALYSIS.md)
- [opencode integration](integrations/opencode/README.md)
- [Character game README](apps/character-game/README.md)
- [Screenshot evidence](docs/assets/screenshots/README.md)

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