wehub-resource-sync
99 lines
3.4 KiB
Plaintext
99 lines
3.4 KiB
Plaintext
---
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# id: moonshot
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title: Moonshot
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sidebar_label: Moonshot
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---
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DeepEval's integration with Moonshot AI allows you to use any Moonshot models to power all of DeepEval's metrics.
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### Command Line
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To configure your Moonshot model through the CLI, run the following command:
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```bash
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deepeval set-moonshot \
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--model="kimi-k2-0711-preview" \
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--temperature=0
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```
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:::info
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The CLI command above sets Moonshot as the default provider for all metrics, unless overridden in Python code. To use a different default model provider, you must first unset Moonshot:
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```bash
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deepeval unset-moonshot
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```
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:::
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:::tip[Persisting settings]
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You can persist CLI settings with the optional `--save` flag.
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See [Flags and Configs -> Persisting CLI settings](/docs/evaluation-flags-and-configs#persisting-cli-settings-with---save).
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:::
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### Python
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Alternatively, you can define `KimiModel` directly in python code:
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<Tabs items={["Python", "ENV"]}>
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<Tab value="Python">
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```python
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from deepeval.models import KimiModel
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from deepeval.metrics import AnswerRelevancyMetric
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model = KimiModel(
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model="kimi-k2-0711-preview",
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api_key="your-api-key",
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temperature=0
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)
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answer_relevancy = AnswerRelevancyMetric(model=model)
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```
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</Tab>
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<Tab value="ENV">
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To use any Moonshot model directly in `deepeval`, set the `USE_MOONSHOT_MODEL=1` in your `env` and simply pass the name of your desired model in your metric initialization:
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```python
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from deepeval.metrics import AnswerRelevancyMetric
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answer_relevancy = AnswerRelevancyMetric(
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model="kimi-k2-0711-preview",
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)
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```
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You should also set the other necessary vars like `MOONSHOT_API_KEY` to be able to use the Moonshot models as shown above.
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</Tab>
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</Tabs>
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There are **ZERO** mandatory and **SIX** optional parameters when creating an `KimiModel`:
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- [Optional] `model`: A string specifying the name of the Kimi model to use. Defaults to `MOONSHOT_MODEL_NAME` if not passed; raises an error at runtime if unset.
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- [Optional] `api_key`: A string specifying your Kimi API key for authentication. Defaults to `MOONSHOT_API_KEY` if not passed; raises an error at runtime if unset.
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- [Optional] `temperature`: A float specifying the model temperature. Defaults to `TEMPERATURE` if not passed; falls back to `0.0` if unset and raises if < 0.
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- [Optional] `cost_per_input_token`: A float specifying the cost for each input token for the provided model. Defaults to `MOONSHOT_COST_PER_INPUT_TOKEN` if available in `deepeval`'s model cost registry, else `None`.
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- [Optional] `cost_per_output_token`: A float specifying the cost for each output token for the provided model. Defaults to `MOONSHOT_COST_PER_OUTPUT_TOKEN` if available in `deepeval`'s model cost registry, else `None`.
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- [Optional] `generation_kwargs`: A dictionary of additional generation parameters forwarded to the OpenAI `chat.completions.create(...)` call.
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:::tip
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Any `**kwargs` you would like to use for your model can be passed through the `generation_kwargs` parameter. However, we request you to double check the params supported by the model and your model provider in their [official docs](https://docs.together.ai/docs/inference-parameters).
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:::
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### Available Moonshot Models
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Below is a comprehensive list of available Moonshot models:
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- `kimi-k2-0711-preview`
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- `kimi-thinking-preview`
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- `moonshot-v1-8k`
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- `moonshot-v1-32k`
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- `moonshot-v1-128k`
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- `moonshot-v1-8k-vision-preview`
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- `moonshot-v1-32k-vision-preview`
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- `moonshot-v1-128k-vision-preview`
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- `kimi-latest-8k`
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- `kimi-latest-32k`
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- `kimi-latest-128k`
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