SparkLLM

Setup:

To use, you should set environment variables IFLYTEK_SPARK_APP_ID, IFLYTEK_SPARK_API_KEY and IFLYTEK_SPARK_API_SECRET.

.. code-block:: bash

    export IFLYTEK_SPARK_APP_ID="your-app-id"
    export IFLYTEK_SPARK_API_KEY="your-api-key"
    export IFLYTEK_SPARK_API_SECRET="your-api-secret"

Key init args — completion params: model: Optional[str] Name of IFLYTEK SPARK model to use. temperature: Optional[float] Sampling temperature. top_k: Optional[float] What search sampling control to use. streaming: Optional[bool] Whether to stream the results or not.

Key init args — client params: app_id: Optional[str] IFLYTEK SPARK API KEY. Automatically inferred from env var IFLYTEK_SPARK_APP_ID if not provided. api_key: Optional[str] IFLYTEK SPARK API KEY. If not passed in will be read from env var IFLYTEK_SPARK_API_KEY. api_secret: Optional[str] IFLYTEK SPARK API SECRET. If not passed in will be read from env var IFLYTEK_SPARK_API_SECRET. api_url: Optional[str] Base URL for API requests. timeout: Optional[int] Timeout for requests.

See full list of supported init args and their descriptions in the params section.

Instantiate:

.. code-block:: python

from langchain_community.llms import SparkLLM

llm = SparkLLM( app_id="your-app-id", api_key="your-api_key", api_secret="your-api-secret", # model='Spark4.0 Ultra', # temperature=..., # other params... )

Invoke:

.. code-block:: python

input_text = "用50个字左右阐述，生命的意义在于"
llm.invoke(input_text)

.. code-block:: python

'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。'

Stream:

.. code-block:: python

for chunk in llm.stream(input_text):
    print(chunk)

.. code-block:: python

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。

Async:

.. code-block:: python

await llm.ainvoke(input_text)

# stream:
# async for chunk in llm.astream(input_text):
#    print(chunk)

# batch:
# await llm.abatch([input_text])

.. code-block:: python

'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。'