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https://github.com/BerriAI/litellm.git
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4170433365
* fix _pass_through_moderation_endpoint_factory * fix route_llm_request * doc moderations api * docs on /moderations * add e2e tests for moderations api * docs moderations api * test_pass_through_moderation_endpoint_factory * docs text completion
135 lines
3.7 KiB
Markdown
135 lines
3.7 KiB
Markdown
import Tabs from '@theme/Tabs';
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import TabItem from '@theme/TabItem';
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# Moderation
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### Usage
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<Tabs>
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<TabItem value="python" label="LiteLLM Python SDK">
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```python
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from litellm import moderation
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response = moderation(
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input="hello from litellm",
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model="text-moderation-stable"
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)
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```
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</TabItem>
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<TabItem value="proxy" label="LiteLLM Proxy Server">
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For `/moderations` endpoint, there is **no need to specify `model` in the request or on the litellm config.yaml**
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Start litellm proxy server
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```
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litellm
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```
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<Tabs>
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<TabItem value="python" label="OpenAI Python SDK">
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```python
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from openai import OpenAI
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# set base_url to your proxy server
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# set api_key to send to proxy server
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client = OpenAI(api_key="<proxy-api-key>", base_url="http://0.0.0.0:4000")
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response = client.moderations.create(
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input="hello from litellm",
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model="text-moderation-stable" # optional, defaults to `omni-moderation-latest`
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)
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print(response)
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```
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</TabItem>
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<TabItem value="curl" label="Curl Request">
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```shell
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curl --location 'http://0.0.0.0:4000/moderations' \
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--header 'Content-Type: application/json' \
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--header 'Authorization: Bearer sk-1234' \
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--data '{"input": "Sample text goes here", "model": "text-moderation-stable"}'
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```
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</TabItem>
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</Tabs>
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</TabItem>
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</Tabs>
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## Input Params
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LiteLLM accepts and translates the [OpenAI Moderation params](https://platform.openai.com/docs/api-reference/moderations) across all supported providers.
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### Required Fields
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- `input`: *string or array* - Input (or inputs) to classify. Can be a single string, an array of strings, or an array of multi-modal input objects similar to other models.
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- If string: A string of text to classify for moderation
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- If array of strings: An array of strings to classify for moderation
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- If array of objects: An array of multi-modal inputs to the moderation model, where each object can be:
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- An object describing an image to classify with:
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- `type`: *string, required* - Always `image_url`
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- `image_url`: *object, required* - Contains either an image URL or a data URL for a base64 encoded image
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- An object describing text to classify with:
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- `type`: *string, required* - Always `text`
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- `text`: *string, required* - A string of text to classify
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### Optional Fields
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- `model`: *string (optional)* - The moderation model to use. Defaults to `omni-moderation-latest`.
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## Output Format
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Here's the exact json output and type you can expect from all moderation calls:
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[**LiteLLM follows OpenAI's output format**](https://platform.openai.com/docs/api-reference/moderations/object)
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```python
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{
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"id": "modr-AB8CjOTu2jiq12hp1AQPfeqFWaORR",
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"model": "text-moderation-007",
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"results": [
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{
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"flagged": true,
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"categories": {
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"sexual": false,
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"hate": false,
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"harassment": true,
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"self-harm": false,
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"sexual/minors": false,
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"hate/threatening": false,
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"violence/graphic": false,
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"self-harm/intent": false,
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"self-harm/instructions": false,
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"harassment/threatening": true,
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"violence": true
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},
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"category_scores": {
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"sexual": 0.000011726012417057063,
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"hate": 0.22706663608551025,
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"harassment": 0.5215635299682617,
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"self-harm": 2.227119921371923e-6,
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"sexual/minors": 7.107352217872176e-8,
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"hate/threatening": 0.023547329008579254,
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"violence/graphic": 0.00003391829886822961,
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"self-harm/intent": 1.646940972932498e-6,
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"self-harm/instructions": 1.1198755256458526e-9,
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"harassment/threatening": 0.5694745779037476,
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"violence": 0.9971134662628174
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}
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}
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]
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}
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```
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## **Supported Providers**
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| Provider |
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|-------------|
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| OpenAI |
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