p2d-duck 1.1.0

Free Python client for DuckDuckGo AI Chat (duck.ai). Sync, streaming, image generation, image edit, multimodal vision, web search. Auto-retry on challenge failures. No API key required.

p2d-duck

Free, no-API-key Python client for DuckDuckGo AI Chat (duck.ai).

• Single sync client — built on httpx. No async twin to drift out of sync.
• Auto-retry on challenge failures — fresh x-vqd-hash-1 solve, exponential backoff with jitter. Works on the first call, not the third.
• Session warm-up — cookies are seeded on construction so the very first chat request looks like a real browser session.
• 6 chat models + image generation: GPT-4o mini, GPT-5 mini, Claude Haiku 4.5, Llama 4 Scout, Mistral Small, GPT-OSS 120B.
• Reasoning effort switching (fast vs reasoning).
• Image generation (image-generation model).
• Image edit (caption + source image → edited image, same model).
• Image upload / multimodal (vision-capable chats).
• Web search tool opt-in per call on supported models (GPT-4o mini, GPT-5 mini, Claude Haiku 4.5).
• Built-in solver for the x-vqd-hash-1 JS challenge via mini-racer.
• CLI: p2d-duck.
• No account, no API key, no server, no fee.

Install

pip install p2d-duck

The Python import name is still duck_ai, e.g. from duck_ai import DuckChat.

Latest release: v1.1.0 — see the full changelog on the release page.

Quickstart

from duck_ai import DuckChat, gpt4

with DuckChat(model=gpt4) as duck:
    print(duck.ask("Explain quantum tunneling in one sentence."))

Switch models by passing an alias:

from duck_ai import DuckChat

with DuckChat(model="claude") as duck:
    print(duck.ask("Hi Claude!"))

You can pass any of: "gpt4", "gpt5_mini", "claude", "llama", "mistral", "gpt-oss", "image", or any raw model id.

Streaming

from duck_ai import DuckChat

with DuckChat() as duck:
    for chunk in duck.stream("Write a 4-line haiku about ducks."):
        print(chunk, end="", flush=True)

Multi-turn conversation

DuckChat keeps history automatically. Use duck.reset() to start fresh.

from duck_ai import DuckChat, claude

with DuckChat(model=claude) as duck:
    duck.ask("My name is Alice. Remember it.")
    print(duck.ask("What is my name?"))
    duck.reset()

Reasoning vs Fast mode

from duck_ai import DuckChat, gpt5_mini, claude

with DuckChat(model=gpt5_mini, effort="fast") as duck:
    print(duck.ask("Quick: 2+2?"))

with DuckChat(model=claude, effort="reasoning") as duck:
    print(duck.ask("Solve: I speak without a mouth..."))

Model	Supports fast / reasoning?	Default effort
gpt4 (gpt-4o-mini)	no	—
gpt5_mini	yes	minimal
claude (Haiku 4.5)	yes	low
gpt_oss (gpt-oss 120B)	yes	low
llama (Llama 4 Scout)	no	—
mistral (Small 2603)	no	—

Image generation

from duck_ai import DuckChat, image_generation

with DuckChat(model=image_generation) as duck:
    duck.generate_image(
        "a cute rubber duck wearing a wizard hat, digital art",
        save_to="duck_wizard.jpg",
    )

Image edit

Edit an existing image with a caption. Same image-generation model, same endpoint as image generation, but the user message carries both a text caption and an ImagePart:

from duck_ai import DuckChat, image_generation

with DuckChat(model=image_generation) as duck:
    duck.edit_image(
        "make the duck wear a tiny chef hat",
        "duck_wizard.jpg",
        save_to="duck_chef.jpg",
    )

Web search

Web search is an opt-in tool, off by default. Pass web_search=True per call. It is only sent to models that actually support it (GPT-4o mini, GPT-5 mini, Claude Haiku 4.5); the flag is silently ignored for the others.

from duck_ai import DuckChat, gpt5_mini, model_supports_web_search

assert model_supports_web_search(gpt5_mini)

with DuckChat(model=gpt5_mini) as duck:
    print(duck.ask(
        "What did Apple announce at WWDC this year?",
        web_search=True,
    ))

CLI:

p2d-duck -m gpt5_mini chat "Latest SpaceX launch?" --web-search

Image upload (multimodal)

from duck_ai import DuckChat, ImagePart

with DuckChat() as duck:
    print(duck.ask_with_image("What is in this image?", "photo.jpg"))

    print(duck.ask([
        "Compare these two images:",
        ImagePart.from_path("a.png"),
        ImagePart.from_path("b.png"),
    ]))

If your selected model has no vision capability, multimodal requests are automatically routed to a vision-capable model (gpt-5-mini).

CLI

p2d-duck                                       # interactive REPL
p2d-duck chat "Hello, who are you?"
p2d-duck -m claude chat "Hi Claude!"
p2d-duck -m gpt5_mini -e reasoning chat "Solve x^2 - 5x + 6 = 0"
p2d-duck chat "Describe this" --image cat.jpg
p2d-duck image "a watercolor moon over a lake" -o moon.jpg
p2d-duck edit "make the cat wear sunglasses" --image cat.jpg -o cat_cool.jpg
p2d-duck -m claude chat "Top news today" --web-search
p2d-duck models                                # list known models

The legacy duck-ai command is also installed for backwards compatibility, so existing scripts keep working.

Reliability — what changed

The previous version of this client raised on the very first 418 ERR_CHALLENGE, leaving callers to retry manually 2-3 times. This rewrite:

1. Warms the HTTP session by hitting the duck.ai homepage on construction so cookies are present before the first chat request.
2. Wraps every chat call in a retry loop. On ChallengeError, RemoteProtocolError, transient RateLimitError, dropped streams, or an empty SSE response, it re-fetches the x-vqd-hash-1 challenge and tries again with exponential backoff + jitter.
3. Treats ConversationLimitError as terminal so we don't burn retries on a permanent failure.
4. Refuses to fall back to a fake RSA key for durable streams. If cryptography isn't installed we raise immediately instead of sending a garbage public key the server will reject.

You can tune retries with DuckChat(max_retries=4, backoff_base=0.6).

Models

from duck_ai import (
    DuckChat,
    gpt4, gpt5_mini, claude, llama, mistral, gpt_oss, image_generation,
)

Alias	Resolved model id
gpt4 / gpt4o_mini	gpt-4o-mini
gpt5 / gpt5_mini	gpt-5-mini
claude / claude_haiku	claude-haiku-4-5
llama / llama4_scout	meta-llama/Llama-4-Scout-17B-16E-Instruct
mistral / mistral_small	mistral-small-2603
gpt_oss / gpt_oss_120b	tinfoil/gpt-oss-120b
image_generation / image	image-generation

You can also pass any model string directly: DuckChat(model="gpt-4o-mini").

How it works

DuckDuckGo's AI Chat backend (duck.ai/duckchat/v1/*) requires a per-request proof-of-work challenge encoded in the x-vqd-hash-1 header. The server returns an obfuscated JavaScript snippet that must be evaluated against a browser-like environment to compute valid client hashes.

p2d-duck ships with:

1. A minimal browser-DOM JavaScript shim (_stubs.js).
2. An embedded V8 isolate via mini-racer to execute the challenge.
3. SHA-256 hashing of the resulting fingerprint values.
4. A real RSA-OAEP public key for resumable streams (durable streams).

No external Node.js install is required.

Exceptions

Exception	When
DuckChatError	Generic error; base class.
ChallengeError	Couldn't solve the JS challenge.
RateLimitError	HTTP 429 from the server.
ConversationLimitError	Too many turns in one session (terminal).
APIError	Any other non-200 response (.status_code, .body).

If you hit HTTP 418 ERR_CHALLENGE after the retry budget is exhausted, your IP is being throttled by duck.ai's anti-abuse system. Wait 30-60 seconds between consecutive requests.

License

MIT. See LICENSE.

Disclaimer

This is an unofficial reverse-engineered client. It is not affiliated with or endorsed by DuckDuckGo. Use at your own risk and respect duck.ai's terms of service. The DuckDuckGo backend may change at any time and break this library.