o !g3 @sddlmZddlZddlmZmZddlZddlmZmZm Z m Z ddl m m ZddlmZddlmZddlmZddlmZdd lmZdd lmZd Zd ZzejZWneyje d ZdLddZYnwdMddZeddddddddd dNd+d,Zedddddddddd- dOd4d5Z ej!ej"d6d7Gd8d9d9ej#Z#  dPdQd1, got: ) ValueErrorappendlen)rrbatchitemrZ/mnt/skqttb/ctump_chatbot/chatbot/lib/python3.10/site-packages/google/generativeai/text.py_batched(s   rpromptstr | dict[str, str]glm.TextPromptcCs6t|tr tj|dSt|trt|StddS)aP Creates a `glm.TextPrompt` object based on the provided prompt input. Args: prompt: The prompt input, either a string or a dictionary. Returns: glm.TextPrompt: A TextPrompt object containing the prompt text. Raises: TypeError: If the provided prompt is neither a string nor a dictionary. )textz.Expected string or dictionary for text prompt.N) isinstancestrglm TextPromptdict TypeErrorrrrr_make_text_prompt6s    r* modelr temperaturecandidate_countmax_output_tokenstop_ptop_ksafety_settingsstop_sequencesr,model_types.AnyModelNameOptions str | Noner- float | Noner. int | Noner/r0r1r2(safety_types.SafetySettingOptions | Noner3str | Iterable[str] | Noneglm.GenerateTextRequestc CsZt|}t|d}tj|dd}t|tr|g}|rt|}tj |||||||||d S)a Creates a `glm.GenerateTextRequest` object based on the provided parameters. This function generates a `glm.GenerateTextRequest` object with the specified parameters. It prepares the input parameters and creates a request that can be used for generating text using the chosen model. Args: model: The model to use for text generation. prompt: The prompt for text generation. Defaults to None. temperature: The temperature for randomness in generation. Defaults to None. candidate_count: The number of candidates to consider. Defaults to None. max_output_tokens: The maximum number of output tokens. Defaults to None. top_p: The nucleus sampling probability threshold. Defaults to None. top_k: The top-k sampling parameter. Defaults to None. safety_settings: Safety settings for generated text. Defaults to None. stop_sequences: Stop sequences to halt text generation. Can be a string or iterable of strings. Defaults to None. Returns: `glm.GenerateTextRequest`: A `GenerateTextRequest` object configured with the specified parameters. r)old)harm_category_setr+) r make_model_namer*r normalize_safety_settingsr#r$listr%GenerateTextRequestr+rrr_make_generate_text_requestKs( "  rA) r,r-r.r/r0r1r2r3clientrequest_optionsr$rBglm.TextServiceClient | NonerCdict[str, Any] | Nonetext_types.Completionc Cs(t|||||||||d } t| | | dS)az Calls the API and returns a `types.Completion` containing the response. Args: model: Which model to call, as a string or a `types.Model`. prompt: Free-form input text given to the model. Given a prompt, the model will generate text that completes the input text. temperature: Controls the randomness of the output. Must be positive. Typical values are in the range: `[0.0,1.0]`. Higher values produce a more random and varied response. A temperature of zero will be deterministic. candidate_count: The **maximum** number of generated response messages to return. This value must be between `[1, 8]`, inclusive. If unset, this will default to `1`. Note: Only unique candidates are returned. Higher temperatures are more likely to produce unique candidates. Setting `temperature=0.0` will always return 1 candidate regardless of the `candidate_count`. max_output_tokens: Maximum number of tokens to include in a candidate. Must be greater than zero. If unset, will default to 64. top_k: The API uses combined [nucleus](https://arxiv.org/abs/1904.09751) and top-k sampling. `top_k` sets the maximum number of tokens to sample from on each step. top_p: The API uses combined [nucleus](https://arxiv.org/abs/1904.09751) and top-k sampling. `top_p` configures the nucleus sampling. It sets the maximum cumulative probability of tokens to sample from. For example, if the sorted probabilities are `[0.5, 0.2, 0.1, 0.1, 0.05, 0.05]` a `top_p` of `0.8` will sample as `[0.625, 0.25, 0.125, 0, 0, 0]`. safety_settings: A list of unique `types.SafetySetting` instances for blocking unsafe content. These will be enforced on the `prompt` and `candidates`. There should not be more than one setting for each `types.SafetyCategory` type. The API will block any prompts and responses that fail to meet the thresholds set by these settings. This list overrides the default settings for each `SafetyCategory` specified in the safety_settings. If there is no `types.SafetySetting` for a given `SafetyCategory` provided in the list, the API will use the default safety setting for that category. stop_sequences: A set of up to 5 character sequences that will stop output generation. If specified, the API will stop at the first appearance of a stop sequence. The stop sequence will not be included as part of the response. client: If you're not relying on a default client, you pass a `glm.TextServiceClient` instead. request_options: Options for the request. Returns: A `types.Completion` containing the model's text completion response. r+)rBrequestrC)rA_generate_response) r,rr-r.r/r0r1r2r3rBrCrGrrr generate_texts: rIF)initc@seZdZddZdS) CompletioncKsB|D] \}}t|||qd|_|jr|jdd|_dSdS)Nroutput)itemssetattrresult candidates)selfkwargskeyvaluerrr__init__s zCompletion.__init__N)__name__ __module__ __qualname__rUrrrrrKs rKrGglm.TextServiceClientcCs|duri}|dur t}|j|fi|}t||}t|d|d<t|d|d<t|d|d<tdd|i|S)a Generates a response using the provided `glm.GenerateTextRequest` and client. Args: request: The text generation request. client: The client to use for text generation. Defaults to None, in which case the default text client is used. request_options: Options for the request. Returns: `Completion`: A `Completion` object with the generated text and response information. Nfilterssafety_feedbackrP_clientr) rrItypeto_dictr convert_filters_to_enums convert_safety_feedback_to_enumsconvert_candidate_enumsrK)rGrBrCresponserrrrHsrHtext_types.TokenCountcCsRt|}|dur i}|durt}|jtj|d|idfi|}t||S)Nr")r,r)r get_base_model_namercount_text_tokensr%CountTextTokensRequestr]r^)r,rrBrC base_modelrOrrrres re model_types.BaseModelNameOptionsr"text_types.EmbeddingDictcCdSNrr,r"rBrCrrrgenerate_embeddingsrm Sequence[str]text_types.BatchEmbeddingDictcCrjrkrrlrrrrmrnstr | Sequence[str]8text_types.EmbeddingDict | text_types.BatchEmbeddingDictc Cst|}|dur i}|durt}t|tr8tj||d}|j|fi|}t| |}|dd|d<|Sdgi}t |t D]'}tj ||d}|j |fi|}t| |}|ddd|dDqA|S) a$Calls the API to create an embedding for the text passed in. Args: model: Which model to call, as a string or a `types.Model`. text: Free-form input text given to the model. Given a string, the model will generate an embedding based on the input text. client: If you're not relying on a default client, you pass a `glm.TextServiceClient` instead. request_options: Options for the request. Returns: Dictionary containing the embedding (list of float values) for the input text. N)r,r" embeddingrT)r,textscss|]}|dVqdS)rTNr).0errr Ssz&generate_embeddings.. embeddings)r r=rr#r$r%EmbedTextRequest embed_textr]r^rEMBEDDING_MAX_BATCH_SIZEBatchEmbedTextRequestbatch_embed_textextend) r,r"rBrCembedding_requestembedding_responseembedding_dictrOrrrrrm$s4  )rrrrrr)rr rr!)r,r4rr5r-r6r.r7r/r7r0r7r1r7r2r8r3r9rr:)r,r4rr$r-r6r.r7r/r7r0r6r1r6r2r8r3r9rBrDrCrErrF)NN)rGr:rBrYrCrErrK) r,r4rr$rBrDrCrErrc) r,rhr"r$rBrYrCrErri) r,rhr"rorBrYrCrErrp) r,rhr"rqrBrYrCrErrr)' __future__r dataclassescollections.abcrr itertoolstypingrrrgoogle.ai.generativelanguageaigenerativelanguager%google.generativeai.clientrgoogle.generativeair google.generativeai.typesr r r r DEFAULT_TEXT_MODELr{batchedrAttributeErrorrr*rArI prettyprint dataclassrKrHrermrrrrs|          ;I   &