5P@i90 ddlmZddlZddlmZmZddlZddlmZmZm Z ddl m cm Z ddlmZddlmZddlmZddlmZdd lmZdd lmZd Zd Z ej2ZddZeddddddddd ddZeddddddddd d dZej@ejBdGddejDZ" d! d"dZ# d! d#dZ$e d! d$dZ%e d! d%dZ% d! d&dZ%y#e$re d ZddZYwxYw)') annotationsN)IterableSequence)roverloadTypeVar)get_default_text_client) string_utils) text_types) model_types)models) safety_typeszmodels/text-bison-001dTc#K|dkrtd|g}|D](}|j|t||k(s#|g}*|r|yyw)Nz Batch size `n` must be >1, got: ) ValueErrorappendlen)iterablenbatchitems b/home/www/lebenam.kofcorporation.com/venv/lib/python3.12/site-packages/google/generativeai/text.py_batchedr(sd q5?sCD D D LL 5zQ    K s :A A ct|trtj|St|trtj|St dy)aP Creates a `glm.TextPrompt` object based on the provided prompt input. Args: prompt: The prompt input, either a string or a dictionary. Returns: glm.TextPrompt: A TextPrompt object containing the prompt text. Raises: TypeError: If the provided prompt is neither a string nor a dictionary. )textz.Expected string or dictionary for text prompt.N) isinstancestrglm TextPromptdict TypeErrorprompts r_make_text_promptr%6s?&#~~6** FD !~~f%%BC modelr$ temperaturecandidate_countmax_output_tokenstop_ptop_ksafety_settingsstop_sequencesc tj|}t|}tj|d}t |t r|g}|r t|}tj||||||||| 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_settingsrrlistrGenerateTextRequestr's r_make_generate_text_requestr7KsD  ' ' .E f -F"<<5O.#&()n-  " "'+'%  r&) r(r)r*r+r,r-r.r/clientc Dt||||||||| } t| | S)aH 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. Returns: A `types.Completion` containing the model's text completion response. r')r8request)r7_generate_response) r(r$r)r*r+r,r-r.r/r8r:s r generate_textr<s9p*'+'% G VW ==r&F)initceZdZdZy) Completionc |jD]\}}t|||d|_|jr|jdd|_yy)Nroutput)itemssetattrresult candidates)selfkwargskeyvalues r__init__zCompletion.__init__sQ ,,. &JC D#u % & ??//!,X6DK r&N)__name__ __module__ __qualname__rJr&rr?r?s7r&r?c,| t}|j|}t|j|}t j |d|d<t j |d|d<t j|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. Returns: `Completion`: A `Completion` object with the generated text and response information. filterssafety_feedbackrE_clientrN) rr<typeto_dictr convert_filters_to_enums convert_safety_feedback_to_enumsconvert_candidate_enumsr?)r:r8responses rr;r;s~(*##G,HH~%%h/H&??@STHY"."O"O"##H *AA(z&generate_embeddings..:s&Xaqz&Xs embeddings)r r3rrrrEmbedTextRequest embed_textrSrTrEMBEDDING_MAX_BATCH_SIZEBatchEmbedTextRequestbatch_embed_textextend)r(rr8embedding_requestembedding_responseembedding_dictrDrs rraras $  ' ' .E ~(*$00u4H#../@A0199:LM&4[&A'&J{# r"d$<= YE # 9 9U S !'!8!89J!K !"45==>PQN ;  & &&X>,;W&X X  Y  r&)rz Iterable[T]rintreturnzIterable[list[T]])r$zstr | dict[str, str]rvzglm.TextPrompt)r(model_types.AnyModelNameOptionsr$z str | Noner) float | Noner* int | Noner+ryr,ryr-ryr.(safety_types.SafetySettingOptions | Noner/str | Iterable[str] | Nonervglm.GenerateTextRequest)r(rwr$rr)rxr*ryr+ryr,rxr-rxr.rzr/r{r8glm.TextServiceClient | Nonervztext_types.Completionr_)r:r|r8glm.TextServiceClientrvr?)r(rwr$rr8r}rvztext_types.TokenCount)r( model_types.BaseModelNameOptionsrrr8r~rvztext_types.EmbeddingDict)r(rrz Sequence[str]r8r~rvztext_types.BatchEmbeddingDict)r(rrzstr | Sequence[str]r8r~rvz8text_types.EmbeddingDict | text_types.BatchEmbeddingDict)& __future__r dataclassescollections.abcrr itertoolstypingrrgoogle.ai.generativelanguageaigenerativelanguagergoogle.generativeai.clientrgoogle.generativeair google.generativeai.typesr r r r DEFAULT_TEXT_MODELrnbatchedrAttributeErrorrr%r7r< prettyprint dataclassr?r;r[rarNr&rrs#...**>,01&2,  H$D..@ $"&$(@D156 *6 6 6  6 " 6 6 6>6/66v.@ $"&$(@D15+/D> *D> D> D>  D> " D> D> D>>D>/D> )D>D>NE"7&&7#7GK2 $2.C22@,0( *( ( )( (" %) +  "   %) +  "#  %)& +& & "&> &e A s D--EE