pollinations.ai - Free AI Image, Text, and Audio Generation
pollinations.ai: (https://pollinations.ai/)
Work with the best generative AI from Pollinations using this Python SDK. 🐝
Installing
pip install pollinations
pip install pollinations.ai
# Linux/macOS
python3 -m pip install pollinations
python3 -m pip install pollinations.ai
# Windows
py -3 -m pip install pollinations
py -3 -m pip install pollinations.ai
Usage
Image Generation
View Code Example
import pollinations
"""
(method) def __init__(
self: Self@Image,
model: ImageModel | None = "flux",
width: Width | None = 1024,
height: Height | None = 1024,
seed: Seed | None = "random",
nologo: NoLogo | None = False,
private: Private | None = False,
enhance: Enhance | None = False,
safe: Safe | None = False,
referrer: Referrer | None = "pollinations.py",
*any_kwargs_will_be_passed_in_request: Args,
**kwargs: Kwargs,
) -> None
"""
model = pollinations.Image()
"""
(method) def __call__(
self: Self@Image,
prompt: Prompt,
negative: Negative | None = "",
*args: Args,
file: Filename | None = "pollinations-image.jpeg",
save: Save = False,
*kwargs: Kwargs
) -> PILImage
"""
image = model("A dog and cat.")
image.save("my_image.jpeg")
# Alternatively:
# image = model.Generate("A dog and cat.", file="my_image.jpeg", save=True)
(Async) View Code Example
import pollinations
"""
(method) def __init__(
self: Self@Image,
model: ImageModel | None = "flux",
width: Width | None = 1024,
height: Height | None = 1024,
seed: Seed | None = "random",
nologo: NoLogo | None = False,
private: Private | None = False,
enhance: Enhance | None = False,
safe: Safe | None = False,
referrer: Referrer | None = "pollinations.py",
*any_kwargs_will_be_passed_in_request: Args,
**kwargs: Kwargs,
) -> None
"""
model = pollinations.Image()
"""
(method) async def Async(
self: Self@Image,
prompt: Prompt,
negative: Negative | None = "",
*args: Args,
file: Filename | None = "pollinations-image.jpeg",
save: Save = False,
*kwargs: Kwargs
) -> PILImage
"""
image = await model.Async("A dog and cat.")
image.save("my_image.jpeg")
# Alternatively:
# image = await model.Async("A dog and cat.", file="my_image.jpeg", save=True)
Text Generation
View Code Example
import pollinations
"""
(method) def __init__(
self: Self@Text,
model: Model | None = "openai",
system: System | None = "You are a helpful AI assistant.",
contextual: Contextual | None = False,
messages: Messages | None = [],
private: Private | None = False,
seed: Seed | None = "random",
reasoning_effort: ReasoningEffort | None = "medium",
tools: Tools | None = [],
tool_choices: ToolChoice | None = [],
voice: Voice | None = None,
json_mode: JsonMode | None = False,
referrer: Referrer | None = "pollinations.py",
openai_endpoint: UseOpenAIEndpoint | None = False,
*any_kwargs_will_be_passed_in_request: Args,
**kwargs: Kwargs,
) -> None
"""
model = pollinations.Text()
"""
(method) def __call__(
self: Self@Text,
prompt: Prompt | None = None,
*any_kwargs_will_be_passed_in_request: Args,
stream: Stream | None = False,
**kwargs: Kwargs
) -> Output
"""
print(model("Hello, what is 1 + 1?"))
# Alternatively:
# print(model.Generate("Hello, what is 1 + 1?"))
# Streaming
for token in model("Hello, what is 1 + 1?", stream=True):
print(token, end="", flush=True)
# Alternatively:
# for token in model.Generate("Hello, what is 1 + 1?", stream=True):
# print(token, end="", flush=True)
(Async) View Code Example
import pollinations
"""
(method) def __init__(
self: Self@Text,
model: Model | None = "openai",
system: System | None = "You are a helpful AI assistant.",
contextual: Contextual | None = False,
messages: Messages | None = [],
private: Private | None = False,
seed: Seed | None = "random",
reasoning_effort: ReasoningEffort | None = "medium",
tools: Tools | None = [],
tool_choices: ToolChoice | None = [],
voice: Voice | None = None,
json_mode: JsonMode | None = False,
referrer: Referrer | None = "pollinations.py",
openai_endpoint: UseOpenAIEndpoint | None = False,
*any_kwargs_will_be_passed_in_request: Args,
**kwargs: Kwargs,
) -> None
"""
model = pollinations.Text()
"""
(method) async def Async(
self: Self@Text,
prompt: Prompt | None = None,
*any_kwargs_will_be_passed_in_request: Args,
stream: Stream | None = False,
**kwargs: Kwargs
) -> Output
"""
print(await model.Async("Hello, what is 1 + 1?"))
# Streaming
async for token in await model.Async("Hello, what is 1 + 1?", stream=True):
print(token, end="", flush=True)
Audio Transcription
View Code Examples
import pollinations
"""
(method) def __init__(
self: Self@Text,
model: Model | None = "openai",
system: System | None = "You are a helpful AI assistant.",
contextual: Contextual | None = False,
messages: Messages | None = [],
private: Private | None = False,
seed: Seed | None = "random",
reasoning_effort: ReasoningEffort | None = "medium",
tools: Tools | None = [],
tool_choices: ToolChoice | None = [],
voice: Voice | None = None,
json_mode: JsonMode | None = False,
referrer: Referrer | None = "pollinations.py",
openai_endpoint: UseOpenAIEndpoint | None = False,
*any_kwargs_will_be_passed_in_request: Args,
**kwargs: Kwargs,
) -> None
"""
model = pollinations.Text()
"""
(method) def Transcribe(
self: Self@Text,
file: Filename,
*any_kwargs_will_be_passed_in_request: Args,
**kwargs: Kwargs
) -> Output
"""
print(model.Transcribe("my_audio.mp3"))
(Async) View Code Examples
import pollinations
"""
(method) def __init__(
self: Self@Text,
model: Model | None = "openai",
system: System | None = "You are a helpful AI assistant.",
contextual: Contextual | None = False,
messages: Messages | None = [],
private: Private | None = False,
seed: Seed | None = "random",
reasoning_effort: ReasoningEffort | None = "medium",
tools: Tools | None = [],
tool_choices: ToolChoice | None = [],
voice: Voice | None = None,
json_mode: JsonMode | None = False,
referrer: Referrer | None = "pollinations.py",
openai_endpoint: UseOpenAIEndpoint | None = False,
*any_kwargs_will_be_passed_in_request: Args,
**kwargs: Kwargs,
) -> None
"""
model = pollinations.Text()
"""
(method) def Transcribe(
self: Self@Text,
file: Filename,
*any_kwargs_will_be_passed_in_request: Args,
**kwargs: Kwargs
) -> Output
"""
print(await model.TranscribeAsync("my_audio.mp3"))
Audio Generation
Coming soon
Feed Reading
View Code Example
import pollinations
"""
(method) def __init__(
self: Self@Feed,
type: FeedType = "image",
max_data: MaxData | None = None,
*args: Args,
**kwargs: Kwargs
) -> None
"""
feed = pollinations.Feed()
# feed = pollinations.Feed("text", 10) # Optionally specify type and amount
"""
(method) def __call__(
self: Self@Feed,
*args: Args,
**kwargs: Kwargs
) -> Iterator[Data]
"""
for item in feed():
print(len(feed.data), item.data)
# Alternatively:
# for item in feed.Get():
# print(len(feed.data), item.data)
(Async) View Code Example
import pollinations
"""
(method) def __init__(
self: Self@Feed,
type: FeedType = "image",
max_data: MaxData | None = None,
*args: Args,
**kwargs: Kwargs
) -> None
"""
feed = pollinations.Feed()
# feed = pollinations.Feed("text", 10) # Optionally specify type and amount
"""
(method) async def Async(
self: Self@Feed,
*args: Args,
**kwargs: Kwargs
) -> AsyncIterator[Data]
"""
async for item in feed.Async():
print(len(feed.data), item.data)
Links
1 maintainer
Metadata
1 maintainer
Release files for pollinations.ai 4.5.1
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|---|---|---|---|---|
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Built distribution (wheel)
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|---|---|---|---|---|
| pollinations_ai-4.5.1-py3-none-any.whl | Python 3 | none | any | Details for pollinations_ai-4.5.1-py3-none-any.whl |
Total release size: 56.4 kB
Release files / pollinations_ai-4.5.1.tar.gz
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|---|---|
| Size | 22.1 kB |
| Tags | Source |
|
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No |
| Uploaded via |
twine/6.1.0 CPython/3.13.3
|
Release files / pollinations_ai-4.5.1-py3-none-any.whl
| Download URL | pollinations_ai-4.5.1-py3-none-any.whl |
|---|---|
| Size | 34.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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| Uploaded via |
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|
Security for pollinations.ai 4.5.1
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