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https://github.com/hwchase17/langchain
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Standardize SparkLLM (#25239)
- **Description:** Standardize SparkLLM, include: - docs, the issue #24803 - to support stream - update api url - model init arg names, the issue #20085
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maang-h
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@ -24,64 +24,149 @@ logger = logging.getLogger(__name__)
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class SparkLLM(LLM):
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"""iFlyTek Spark large language model.
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"""iFlyTek Spark completion model integration.
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To use, you should pass `app_id`, `api_key`, `api_secret`
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as a named parameter to the constructor OR set environment
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variables ``IFLYTEK_SPARK_APP_ID``, ``IFLYTEK_SPARK_API_KEY`` and
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``IFLYTEK_SPARK_API_SECRET``
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Setup:
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To use, you should set environment variables ``IFLYTEK_SPARK_APP_ID``,
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``IFLYTEK_SPARK_API_KEY`` and ``IFLYTEK_SPARK_API_SECRET``.
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Example:
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.. code-block:: bash
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export IFLYTEK_SPARK_APP_ID="your-app-id"
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export IFLYTEK_SPARK_API_KEY="your-api-key"
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export IFLYTEK_SPARK_API_SECRET="your-api-secret"
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Key init args — completion params:
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model: Optional[str]
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Name of IFLYTEK SPARK model to use.
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temperature: Optional[float]
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Sampling temperature.
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top_k: Optional[float]
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What search sampling control to use.
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streaming: Optional[bool]
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Whether to stream the results or not.
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Key init args — client params:
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app_id: Optional[str]
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IFLYTEK SPARK API KEY. Automatically inferred from env var `IFLYTEK_SPARK_APP_ID` if not provided.
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api_key: Optional[str]
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IFLYTEK SPARK API KEY. If not passed in will be read from env var IFLYTEK_SPARK_API_KEY.
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api_secret: Optional[str]
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IFLYTEK SPARK API SECRET. If not passed in will be read from env var IFLYTEK_SPARK_API_SECRET.
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api_url: Optional[str]
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Base URL for API requests.
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timeout: Optional[int]
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Timeout for requests.
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See full list of supported init args and their descriptions in the params section.
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Instantiate:
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.. code-block:: python
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client = SparkLLM(
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spark_app_id="<app_id>",
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spark_api_key="<api_key>",
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spark_api_secret="<api_secret>"
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)
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"""
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from langchain_community.llms import SparkLLM
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llm = SparkLLM(
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app_id="your-app-id",
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api_key="your-api_key",
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api_secret="your-api-secret",
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# model='Spark4.0 Ultra',
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# temperature=...,
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# other params...
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)
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Invoke:
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.. code-block:: python
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input_text = "用50个字左右阐述，生命的意义在于"
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llm.invoke(input_text)
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.. code-block:: python
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'生命的意义在于实现自我价值，追求内心的平静与快乐，同时为他人和社会带来正面影响。'
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Stream:
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.. code-block:: python
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for chunk in llm.stream(input_text):
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print(chunk)
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.. code-block:: python
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生命 | 的意义在于 | 不断探索和 | 实现个人潜能，通过 | 学习 | 、成长和对社会 | 的贡献，追求内心的满足和幸福。
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Async:
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.. code-block:: python
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await llm.ainvoke(input_text)
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# stream:
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# async for chunk in llm.astream(input_text):
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# print(chunk)
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# batch:
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# await llm.abatch([input_text])
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.. code-block:: python
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'生命的意义在于实现自我价值，追求内心的平静与快乐，同时为他人和社会带来正面影响。'
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""" # noqa: E501
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client: Any = None #: :meta private:
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spark_app_id: Optional[str] = None
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spark_api_key: Optional[str] = None
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spark_api_secret: Optional[str] = None
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spark_api_url: Optional[str] = None
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spark_llm_domain: Optional[str] = None
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spark_app_id: Optional[str] = Field(default=None, alias="app_id")
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"""Automatically inferred from env var `IFLYTEK_SPARK_APP_ID`
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if not provided."""
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spark_api_key: Optional[str] = Field(default=None, alias="api_key")
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"""IFLYTEK SPARK API KEY. If not passed in will be read from
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env var IFLYTEK_SPARK_API_KEY."""
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spark_api_secret: Optional[str] = Field(default=None, alias="api_secret")
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"""IFLYTEK SPARK API SECRET. If not passed in will be read from
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env var IFLYTEK_SPARK_API_SECRET."""
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spark_api_url: Optional[str] = Field(default=None, alias="api_url")
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"""Base URL path for API requests, leave blank if not using a proxy or service
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emulator."""
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spark_llm_domain: Optional[str] = Field(default=None, alias="model")
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"""Model name to use."""
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spark_user_id: str = "lc_user"
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streaming: bool = False
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request_timeout: int = 30
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"""Whether to stream the results or not."""
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request_timeout: int = Field(default=30, alias="timeout")
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"""request timeout for chat http requests"""
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temperature: float = 0.5
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"""What sampling temperature to use."""
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top_k: int = 4
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"""What search sampling control to use."""
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model_kwargs: Dict[str, Any] = Field(default_factory=dict)
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"""Holds any model parameters valid for API call not explicitly specified."""
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@pre_init
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def validate_environment(cls, values: Dict) -> Dict:
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values["spark_app_id"] = get_from_dict_or_env(
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values,
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"spark_app_id",
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["spark_app_id", "app_id"],
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"IFLYTEK_SPARK_APP_ID",
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)
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values["spark_api_key"] = get_from_dict_or_env(
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values,
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"spark_api_key",
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["spark_api_key", "api_key"],
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"IFLYTEK_SPARK_API_KEY",
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)
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values["spark_api_secret"] = get_from_dict_or_env(
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values,
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"spark_api_secret",
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["spark_api_secret", "api_secret"],
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"IFLYTEK_SPARK_API_SECRET",
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)
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values["spark_api_url"] = get_from_dict_or_env(
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values,
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"spark_api_url",
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["spark_api_url", "api_url"],
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"IFLYTEK_SPARK_API_URL",
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"wss://spark-api.xf-yun.com/v3.1/chat",
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"wss://spark-api.xf-yun.com/v3.5/chat",
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)
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values["spark_llm_domain"] = get_from_dict_or_env(
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values,
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"spark_llm_domain",
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["spark_llm_domain", "model"],
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"IFLYTEK_SPARK_LLM_DOMAIN",
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"generalv3",
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"generalv3.5",
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)
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# put extra params into model_kwargs
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values["model_kwargs"]["temperature"] = values["temperature"] or cls.temperature
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@ -163,7 +248,7 @@ class SparkLLM(LLM):
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[{"role": "user", "content": prompt}],
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self.spark_user_id,
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self.model_kwargs,
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self.streaming,
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True,
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)
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for content in self.client.subscribe(timeout=self.request_timeout):
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if "data" not in content:
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@ -200,11 +285,11 @@ class _SparkLLMClient:
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)
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self.api_url = (
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"wss://spark-api.xf-yun.com/v3.1/chat" if not api_url else api_url
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"wss://spark-api.xf-yun.com/v3.5/chat" if not api_url else api_url
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)
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self.app_id = app_id
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self.model_kwargs = model_kwargs
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self.spark_domain = spark_domain or "generalv3"
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self.spark_domain = spark_domain or "generalv3.5"
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self.queue: Queue[Dict] = Queue()
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self.blocking_message = {"content": "", "role": "assistant"}
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self.api_key = api_key
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@ -18,3 +18,28 @@ def test_generate() -> None:
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output = llm.generate(["Say foo:"])
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assert isinstance(output, LLMResult)
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assert isinstance(output.generations, list)
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def test_spark_llm_with_param_alias() -> None:
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"""Test SparkLLM with parameters alias."""
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llm = SparkLLM( # type: ignore[call-arg]
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app_id="your-app-id",
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api_key="your-api-key",
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api_secret="your-api-secret",
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model="Spark4.0 Ultra",
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api_url="your-api-url",
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timeout=20,
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)
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assert llm.spark_app_id == "your-app-id"
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assert llm.spark_api_key == "your-api-key"
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assert llm.spark_api_secret == "your-api-secret"
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assert llm.spark_llm_domain == "Spark4.0 Ultra"
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assert llm.spark_api_url == "your-api-url"
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assert llm.request_timeout == 20
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def test_spark_llm_with_stream() -> None:
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"""Test SparkLLM with stream."""
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llm = SparkLLM() # type: ignore[call-arg]
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for chunk in llm.stream("你好呀"):
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assert isinstance(chunk, str)
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