o
    Zh                     @  s   d dl mZ d dlZd dlmZmZmZmZmZ d dl	Z	d dl
mZ d dlmZmZmZ d dlmZmZmZmZ d dlmZmZmZmZ eeZdd
dZdddZG dd deeZdS )    )annotationsN)AnyCallableDictListOptional)
Embeddings)convert_to_secret_strget_from_dict_or_envpre_init)	BaseModel
ConfigDictField	SecretStr)before_sleep_logretrystop_after_attemptwait_exponentialreturnCallable[[Any], Any]c                  C  s6   d} d}d}d}t dt|t| ||dtttjdS )z#Returns a tenacity retry decorator.         T)
multiplierminmax)reraisestopwaitbefore_sleep)r   r   r   r   loggerloggingWARNING)r   Zmin_secondsZmax_secondsmax_retries r$   ]/var/www/html/lang_env/lib/python3.10/site-packages/langchain_community/embeddings/minimax.py_create_retry_decorator   s   
r&   
embeddingsMiniMaxEmbeddingsargsr   kwargsc                   s&   t  }|d fdd}||i |S )	z*Use tenacity to retry the completion call.r)   r   r*   r   c                    s    j | i |S )N)embed)r)   r*   r'   r$   r%   _embed_with_retry(   s   z+embed_with_retry.<locals>._embed_with_retryN)r)   r   r*   r   r   r   )r&   )r'   r)   r*   Zretry_decoratorr-   r$   r,   r%   embed_with_retry$   s   r.   c                   @  s   e Zd ZU dZdZded< 	 dZded< 	 dZded< 	 d	Zded
< 	 e	dddZ
ded< 	 e	dddZded< 	 edddZed'ddZd(dd Zd)d!d"Zd*d%d&ZdS )+r(   u1  MiniMax embedding model integration.

    Setup:
        To use, you should have the environment variable ``MINIMAX_GROUP_ID`` and
        ``MINIMAX_API_KEY`` set with your API token.

        .. code-block:: bash

            export MINIMAX_API_KEY="your-api-key"
            export MINIMAX_GROUP_ID="your-group-id"

    Key init args — completion params:
        model: Optional[str]
            Name of ZhipuAI model to use.
        api_key: Optional[str]
            Automatically inferred from env var `MINIMAX_GROUP_ID` if not provided.
        group_id: Optional[str]
            Automatically inferred from env var `MINIMAX_GROUP_ID` if not provided.

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

    Instantiate:

        .. code-block:: python

            from langchain_community.embeddings import MiniMaxEmbeddings

            embed = MiniMaxEmbeddings(
                model="embo-01",
                # api_key="...",
                # group_id="...",
                # other
            )

    Embed single text:
        .. code-block:: python

            input_text = "The meaning of life is 42"
            embed.embed_query(input_text)

        .. code-block:: python

            [0.03016241, 0.03617699, 0.0017198119, -0.002061239, -0.00029994643, -0.0061320597, -0.0043635326, ...]

    Embed multiple text:
        .. code-block:: python

            input_texts = ["This is a test query1.", "This is a test query2."]
            embed.embed_documents(input_texts)

        .. code-block:: python

            [
                [-0.0021588828, -0.007608119, 0.029349545, -0.0038194496, 0.008031177, -0.004529633, -0.020150753, ...],
                [ -0.00023150232, -0.011122423, 0.016930554, 0.0083089275, 0.012633711, 0.019683322, -0.005971041, ...]
            ]
    z&https://api.minimax.chat/v1/embeddingsstrendpoint_urlzembo-01modeldbembed_type_dbqueryembed_type_queryNgroup_id)defaultaliaszOptional[str]minimax_group_idapi_keyzOptional[SecretStr]minimax_api_keyTZforbid)Zpopulate_by_nameextravaluesr   r   c                 C  s8   t |ddgd}tt |ddgd}||d< ||d< |S )z9Validate that group id and api key exists in environment.r9   r6   ZMINIMAX_GROUP_IDr;   r:   ZMINIMAX_API_KEY)r
   r	   )clsr=   r9   r;   r$   r$   r%   validate_environment}   s   

z&MiniMaxEmbeddings.validate_environmenttexts	List[str]
embed_typeList[List[float]]c           	      C  sx   | j ||d}d| j  dd}d| ji}tj| j|||d}| }|d d d	kr6td
|d  |d }|S )N)r1   typer@   zBearer zapplication/json)AuthorizationzContent-TypeZGroupId)paramsheadersjsonZ	base_respstatus_coder   zMiniMax API returned an error: Zvectors)	r1   r;   Zget_secret_valuer9   requestspostr0   rH   
ValueError)	selfr@   rB   payloadrG   rF   responseZparsed_responser'   r$   r$   r%   r+      s&   
zMiniMaxEmbeddings.embedc                 C  s   t | || jd}|S )zEmbed documents using a MiniMax embedding endpoint.

        Args:
            texts: The list of texts to embed.

        Returns:
            List of embeddings, one for each text.
        r@   rB   )r.   r3   )rM   r@   r'   r$   r$   r%   embed_documents   s   	z!MiniMaxEmbeddings.embed_documentstextList[float]c                 C  s   t | |g| jd}|d S )zEmbed a query using a MiniMax embedding endpoint.

        Args:
            text: The text to embed.

        Returns:
            Embeddings for the text.
        rP   r   )r.   r5   )rM   rR   r'   r$   r$   r%   embed_query   s   	
zMiniMaxEmbeddings.embed_query)r=   r   r   r   )r@   rA   rB   r/   r   rC   )r@   rA   r   rC   )rR   r/   r   rS   )__name__
__module____qualname____doc__r0   __annotations__r1   r3   r5   r   r9   r;   r   Zmodel_configr   r?   r+   rQ   rT   r$   r$   r$   r%   r(   /   s.   
 :

%)r   r   )r'   r(   r)   r   r*   r   r   r   ) 
__future__r   r!   typingr   r   r   r   r   rJ   Zlangchain_core.embeddingsr   Zlangchain_core.utilsr	   r
   r   Zpydanticr   r   r   r   tenacityr   r   r   r   	getLoggerrU   r    r&   r.   r(   r$   r$   r$   r%   <module>   s    


