| |
|
|
| import typing |
|
|
| from ..core.client_wrapper import AsyncClientWrapper, SyncClientWrapper |
| from ..core.request_options import RequestOptions |
| from ..requests.chat_completion_request_message import ChatCompletionRequestMessageParams |
| from ..requests.chat_completion_tool import ChatCompletionToolParams |
| from ..requests.stop_configuration import StopConfigurationParams |
| from ..requests.tool_choice_option import ToolChoiceOptionParams |
| from ..types.chat_completion_chunk import ChatCompletionChunk |
| from ..types.create_chat_completion_response import CreateChatCompletionResponse |
| from ..types.reasoning_effort import ReasoningEffort |
| from ..types.sarvam_model_ids import SarvamModelIds |
| from .raw_client import AsyncRawChatClient, RawChatClient |
|
|
| |
| OMIT = typing.cast(typing.Any, ...) |
|
|
|
|
| class ChatClient: |
| def __init__(self, *, client_wrapper: SyncClientWrapper): |
| self._raw_client = RawChatClient(client_wrapper=client_wrapper) |
|
|
| @property |
| def with_raw_response(self) -> RawChatClient: |
| """ |
| Retrieves a raw implementation of this client that returns raw responses. |
| |
| Returns |
| ------- |
| RawChatClient |
| """ |
| return self._raw_client |
|
|
| @typing.overload |
| def completions( |
| self, |
| *, |
| messages: typing.Sequence[ChatCompletionRequestMessageParams], |
| model: SarvamModelIds, |
| temperature: typing.Optional[float] = ..., |
| top_p: typing.Optional[float] = ..., |
| reasoning_effort: typing.Optional[ReasoningEffort] = ..., |
| max_tokens: typing.Optional[int] = ..., |
| stream: typing.Literal[True], |
| stop: typing.Optional[StopConfigurationParams] = ..., |
| n: typing.Optional[int] = ..., |
| seed: typing.Optional[int] = ..., |
| frequency_penalty: typing.Optional[float] = ..., |
| presence_penalty: typing.Optional[float] = ..., |
| wiki_grounding: typing.Optional[bool] = ..., |
| tools: typing.Optional[typing.Sequence[ChatCompletionToolParams]] = ..., |
| tool_choice: typing.Optional[ToolChoiceOptionParams] = ..., |
| request_options: typing.Optional[RequestOptions] = ..., |
| ) -> typing.Iterator[ChatCompletionChunk]: ... |
|
|
| @typing.overload |
| def completions( |
| self, |
| *, |
| messages: typing.Sequence[ChatCompletionRequestMessageParams], |
| model: SarvamModelIds, |
| temperature: typing.Optional[float] = ..., |
| top_p: typing.Optional[float] = ..., |
| reasoning_effort: typing.Optional[ReasoningEffort] = ..., |
| max_tokens: typing.Optional[int] = ..., |
| stream: typing.Optional[typing.Literal[False]] = ..., |
| stop: typing.Optional[StopConfigurationParams] = ..., |
| n: typing.Optional[int] = ..., |
| seed: typing.Optional[int] = ..., |
| frequency_penalty: typing.Optional[float] = ..., |
| presence_penalty: typing.Optional[float] = ..., |
| wiki_grounding: typing.Optional[bool] = ..., |
| tools: typing.Optional[typing.Sequence[ChatCompletionToolParams]] = ..., |
| tool_choice: typing.Optional[ToolChoiceOptionParams] = ..., |
| request_options: typing.Optional[RequestOptions] = ..., |
| ) -> CreateChatCompletionResponse: ... |
|
|
| def completions( |
| self, |
| *, |
| messages: typing.Sequence[ChatCompletionRequestMessageParams], |
| model: SarvamModelIds, |
| temperature: typing.Optional[float] = OMIT, |
| top_p: typing.Optional[float] = OMIT, |
| reasoning_effort: typing.Optional[ReasoningEffort] = OMIT, |
| max_tokens: typing.Optional[int] = OMIT, |
| stream: typing.Optional[bool] = OMIT, |
| stop: typing.Optional[StopConfigurationParams] = OMIT, |
| n: typing.Optional[int] = OMIT, |
| seed: typing.Optional[int] = OMIT, |
| frequency_penalty: typing.Optional[float] = OMIT, |
| presence_penalty: typing.Optional[float] = OMIT, |
| wiki_grounding: typing.Optional[bool] = OMIT, |
| tools: typing.Optional[typing.Sequence[ChatCompletionToolParams]] = OMIT, |
| tool_choice: typing.Optional[ToolChoiceOptionParams] = OMIT, |
| request_options: typing.Optional[RequestOptions] = None, |
| ) -> typing.Union[CreateChatCompletionResponse, typing.Iterator[ChatCompletionChunk]]: |
| """ |
| Parameters |
| ---------- |
| messages : typing.Sequence[ChatCompletionRequestMessageParams] |
| A list of messages comprising the conversation so far. |
| |
| model : SarvamModelIds |
| Model ID used to generate the response, like `sarvam-m`. |
| |
| temperature : typing.Optional[float] |
| What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. |
| We generally recommend altering this or `top_p` but not both. |
| |
| top_p : typing.Optional[float] |
| An alternative to sampling with temperature, called nucleus sampling, |
| where the model considers the results of the tokens with top_p probability |
| mass. So 0.1 means only the tokens comprising the top 10% probability mass |
| are considered. |
| |
| We generally recommend altering this or `temperature` but not both. |
| |
| reasoning_effort : typing.Optional[ReasoningEffort] |
| The effort to use for reasoning |
| |
| max_tokens : typing.Optional[int] |
| The maximum number of tokens that can be generated in the chat completion. |
| |
| stream : typing.Optional[bool] |
| If set to true, the model response data will be streamed to the client |
| as it is generated using [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format). |
| When true, returns an Iterator[ChatCompletionChunk] instead of CreateChatCompletionResponse. |
| |
| stop : typing.Optional[StopConfigurationParams] |
| |
| n : typing.Optional[int] |
| How many chat completion choices to generate for each input message. Note that you will be charged based on the number of generated tokens across all of the choices. Keep `n` as `1` to minimize costs. |
| |
| seed : typing.Optional[int] |
| This feature is in Beta. |
| If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same `seed` and parameters should return the same result. |
| Determinism is not guaranteed, and you should refer to the `system_fingerprint` response parameter to monitor changes in the backend. |
| |
| frequency_penalty : typing.Optional[float] |
| Number between -2.0 and 2.0. Positive values penalize new tokens based on |
| their existing frequency in the text so far, decreasing the model's |
| likelihood to repeat the same line verbatim. |
| |
| presence_penalty : typing.Optional[float] |
| Number between -2.0 and 2.0. Positive values penalize new tokens based on |
| whether they appear in the text so far, increasing the model's likelihood |
| to talk about new topics. |
| |
| wiki_grounding : typing.Optional[bool] |
| If set to true, the model response will be wiki grounded. |
| |
| tools : typing.Optional[typing.Sequence[ChatCompletionToolParams]] |
| A list of tools the model may call. Currently, only functions are supported as a tool. |
| |
| tool_choice : typing.Optional[ToolChoiceOptionParams] |
| Controls which (if any) tool is called by the model. |
| |
| request_options : typing.Optional[RequestOptions] |
| Request-specific configuration. |
| |
| Returns |
| ------- |
| CreateChatCompletionResponse or Iterator[ChatCompletionChunk] |
| When stream=False (default): CreateChatCompletionResponse. |
| When stream=True: Iterator yielding ChatCompletionChunk objects. |
| |
| Examples |
| -------- |
| from sarvamai import SarvamAI |
| |
| client = SarvamAI( |
| api_subscription_key="YOUR_API_SUBSCRIPTION_KEY", |
| ) |
| |
| # Non-streaming |
| response = client.chat.completions( |
| messages=[{"role": "user", "content": "Hello"}], |
| model="sarvam-m", |
| ) |
| |
| # Streaming |
| for chunk in client.chat.completions( |
| messages=[{"role": "user", "content": "Hello"}], |
| model="sarvam-m", |
| stream=True, |
| ): |
| print(chunk) |
| """ |
| if stream is True: |
| return self._raw_client.completions( |
| messages=messages, |
| model=model, |
| temperature=temperature, |
| top_p=top_p, |
| reasoning_effort=reasoning_effort, |
| max_tokens=max_tokens, |
| stream=True, |
| stop=stop, |
| n=n, |
| seed=seed, |
| frequency_penalty=frequency_penalty, |
| presence_penalty=presence_penalty, |
| wiki_grounding=wiki_grounding, |
| tools=tools, |
| tool_choice=tool_choice, |
| request_options=request_options, |
| ) |
|
|
| _response = self._raw_client.completions( |
| messages=messages, |
| model=model, |
| temperature=temperature, |
| top_p=top_p, |
| reasoning_effort=reasoning_effort, |
| max_tokens=max_tokens, |
| stream=stream, |
| stop=stop, |
| n=n, |
| seed=seed, |
| frequency_penalty=frequency_penalty, |
| presence_penalty=presence_penalty, |
| wiki_grounding=wiki_grounding, |
| tools=tools, |
| tool_choice=tool_choice, |
| request_options=request_options, |
| ) |
| return _response.data |
|
|
|
|
| class AsyncChatClient: |
| def __init__(self, *, client_wrapper: AsyncClientWrapper): |
| self._raw_client = AsyncRawChatClient(client_wrapper=client_wrapper) |
|
|
| @property |
| def with_raw_response(self) -> AsyncRawChatClient: |
| """ |
| Retrieves a raw implementation of this client that returns raw responses. |
| |
| Returns |
| ------- |
| AsyncRawChatClient |
| """ |
| return self._raw_client |
|
|
| @typing.overload |
| async def completions( |
| self, |
| *, |
| messages: typing.Sequence[ChatCompletionRequestMessageParams], |
| model: SarvamModelIds, |
| temperature: typing.Optional[float] = ..., |
| top_p: typing.Optional[float] = ..., |
| reasoning_effort: typing.Optional[ReasoningEffort] = ..., |
| max_tokens: typing.Optional[int] = ..., |
| stream: typing.Literal[True], |
| stop: typing.Optional[StopConfigurationParams] = ..., |
| n: typing.Optional[int] = ..., |
| seed: typing.Optional[int] = ..., |
| frequency_penalty: typing.Optional[float] = ..., |
| presence_penalty: typing.Optional[float] = ..., |
| wiki_grounding: typing.Optional[bool] = ..., |
| tools: typing.Optional[typing.Sequence[ChatCompletionToolParams]] = ..., |
| tool_choice: typing.Optional[ToolChoiceOptionParams] = ..., |
| request_options: typing.Optional[RequestOptions] = ..., |
| ) -> typing.AsyncIterator[ChatCompletionChunk]: ... |
|
|
| @typing.overload |
| async def completions( |
| self, |
| *, |
| messages: typing.Sequence[ChatCompletionRequestMessageParams], |
| model: SarvamModelIds, |
| temperature: typing.Optional[float] = ..., |
| top_p: typing.Optional[float] = ..., |
| reasoning_effort: typing.Optional[ReasoningEffort] = ..., |
| max_tokens: typing.Optional[int] = ..., |
| stream: typing.Optional[typing.Literal[False]] = ..., |
| stop: typing.Optional[StopConfigurationParams] = ..., |
| n: typing.Optional[int] = ..., |
| seed: typing.Optional[int] = ..., |
| frequency_penalty: typing.Optional[float] = ..., |
| presence_penalty: typing.Optional[float] = ..., |
| wiki_grounding: typing.Optional[bool] = ..., |
| tools: typing.Optional[typing.Sequence[ChatCompletionToolParams]] = ..., |
| tool_choice: typing.Optional[ToolChoiceOptionParams] = ..., |
| request_options: typing.Optional[RequestOptions] = ..., |
| ) -> CreateChatCompletionResponse: ... |
|
|
| async def completions( |
| self, |
| *, |
| messages: typing.Sequence[ChatCompletionRequestMessageParams], |
| model: SarvamModelIds, |
| temperature: typing.Optional[float] = OMIT, |
| top_p: typing.Optional[float] = OMIT, |
| reasoning_effort: typing.Optional[ReasoningEffort] = OMIT, |
| max_tokens: typing.Optional[int] = OMIT, |
| stream: typing.Optional[bool] = OMIT, |
| stop: typing.Optional[StopConfigurationParams] = OMIT, |
| n: typing.Optional[int] = OMIT, |
| seed: typing.Optional[int] = OMIT, |
| frequency_penalty: typing.Optional[float] = OMIT, |
| presence_penalty: typing.Optional[float] = OMIT, |
| wiki_grounding: typing.Optional[bool] = OMIT, |
| tools: typing.Optional[typing.Sequence[ChatCompletionToolParams]] = OMIT, |
| tool_choice: typing.Optional[ToolChoiceOptionParams] = OMIT, |
| request_options: typing.Optional[RequestOptions] = None, |
| ) -> typing.Union[CreateChatCompletionResponse, typing.AsyncIterator[ChatCompletionChunk]]: |
| """ |
| Parameters |
| ---------- |
| messages : typing.Sequence[ChatCompletionRequestMessageParams] |
| A list of messages comprising the conversation so far. |
| |
| model : SarvamModelIds |
| Model ID used to generate the response, like `sarvam-m`. |
| |
| temperature : typing.Optional[float] |
| What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. |
| We generally recommend altering this or `top_p` but not both. |
| |
| top_p : typing.Optional[float] |
| An alternative to sampling with temperature, called nucleus sampling, |
| where the model considers the results of the tokens with top_p probability |
| mass. So 0.1 means only the tokens comprising the top 10% probability mass |
| are considered. |
| |
| We generally recommend altering this or `temperature` but not both. |
| |
| reasoning_effort : typing.Optional[ReasoningEffort] |
| The effort to use for reasoning |
| |
| max_tokens : typing.Optional[int] |
| The maximum number of tokens that can be generated in the chat completion. |
| |
| stream : typing.Optional[bool] |
| If set to true, the model response data will be streamed to the client |
| as it is generated using [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format). |
| When true, returns an AsyncIterator[ChatCompletionChunk] instead of CreateChatCompletionResponse. |
| |
| stop : typing.Optional[StopConfigurationParams] |
| |
| n : typing.Optional[int] |
| How many chat completion choices to generate for each input message. Note that you will be charged based on the number of generated tokens across all of the choices. Keep `n` as `1` to minimize costs. |
| |
| seed : typing.Optional[int] |
| This feature is in Beta. |
| If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same `seed` and parameters should return the same result. |
| Determinism is not guaranteed, and you should refer to the `system_fingerprint` response parameter to monitor changes in the backend. |
| |
| frequency_penalty : typing.Optional[float] |
| Number between -2.0 and 2.0. Positive values penalize new tokens based on |
| their existing frequency in the text so far, decreasing the model's |
| likelihood to repeat the same line verbatim. |
| |
| presence_penalty : typing.Optional[float] |
| Number between -2.0 and 2.0. Positive values penalize new tokens based on |
| whether they appear in the text so far, increasing the model's likelihood |
| to talk about new topics. |
| |
| wiki_grounding : typing.Optional[bool] |
| If set to true, the model response will be wiki grounded. |
| |
| tools : typing.Optional[typing.Sequence[ChatCompletionToolParams]] |
| A list of tools the model may call. Currently, only functions are supported as a tool. |
| |
| tool_choice : typing.Optional[ToolChoiceOptionParams] |
| Controls which (if any) tool is called by the model. |
| |
| request_options : typing.Optional[RequestOptions] |
| Request-specific configuration. |
| |
| Returns |
| ------- |
| CreateChatCompletionResponse or AsyncIterator[ChatCompletionChunk] |
| When stream=False (default): CreateChatCompletionResponse. |
| When stream=True: AsyncIterator yielding ChatCompletionChunk objects. |
| |
| Examples |
| -------- |
| import asyncio |
| from sarvamai import AsyncSarvamAI |
| |
| client = AsyncSarvamAI( |
| api_subscription_key="YOUR_API_SUBSCRIPTION_KEY", |
| ) |
| |
| async def main() -> None: |
| # Non-streaming |
| response = await client.chat.completions( |
| messages=[{"role": "user", "content": "Hello"}], |
| model="sarvam-m", |
| ) |
| |
| # Streaming |
| async for chunk in client.chat.completions( |
| messages=[{"role": "user", "content": "Hello"}], |
| model="sarvam-m", |
| stream=True, |
| ): |
| print(chunk) |
| |
| asyncio.run(main()) |
| """ |
| if stream is True: |
| return await self._raw_client.completions( |
| messages=messages, |
| model=model, |
| temperature=temperature, |
| top_p=top_p, |
| reasoning_effort=reasoning_effort, |
| max_tokens=max_tokens, |
| stream=True, |
| stop=stop, |
| n=n, |
| seed=seed, |
| frequency_penalty=frequency_penalty, |
| presence_penalty=presence_penalty, |
| wiki_grounding=wiki_grounding, |
| tools=tools, |
| tool_choice=tool_choice, |
| request_options=request_options, |
| ) |
|
|
| _response = await self._raw_client.completions( |
| messages=messages, |
| model=model, |
| temperature=temperature, |
| top_p=top_p, |
| reasoning_effort=reasoning_effort, |
| max_tokens=max_tokens, |
| stream=stream, |
| stop=stop, |
| n=n, |
| seed=seed, |
| frequency_penalty=frequency_penalty, |
| presence_penalty=presence_penalty, |
| wiki_grounding=wiki_grounding, |
| tools=tools, |
| tool_choice=tool_choice, |
| request_options=request_options, |
| ) |
| return _response.data |
|
|
