阺h90 ddlmZddlZddlmZmZddlZddlmZmZm Z ddl m cm Z ddlmZddlmZddlmZddlmZdd lmZdd lmZd Zd Z ejZn#e$re d ZdCdZYnwxYwdDdZeddddddddd dEd)Zeddddddddd* dFd/Zej ej!d01Gd2d3ej"Z" dGdHd6Z# dGdId8Z$e dGdJd<Z%e dGdKd?Z% dGdLdBZ%dS)M) annotationsN)IterableSequence)roverloadTypeVar)get_default_text_client) string_utils) text_types) model_types)models) safety_typeszmodels/text-bison-001dTiterable Iterable[T]nintreturnIterable[list[T]]c#K|dkrtd|g}|D]0}||t||kr|Vg}1|r|VdSdS)Nz Batch size `n` must be >1, got: ) ValueErrorappendlen)rrbatchitems `/var/www/html/services/rag-service/venv/lib/python3.11/site-packages/google/generativeai/text.py_batchedr(s q55CCCDD D  D LL   5zzQ   KKKKK  promptstr | dict[str, str]glm.TextPromptct|trtj|St|trtj|St ddS)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 TypeErrorr s r_make_text_promptr,6sb&#D~6**** FD ! !D~f%%%BCCCCCr modelr temperaturecandidate_countmax_output_tokenstop_ptop_ksafety_settingsstop_sequencesr.model_types.AnyModelNameOptions str | Noner/ float | Noner0 int | Noner1r2r3r4(safety_types.SafetySettingOptions | Noner5str | Iterable[str] | Noneglm.GenerateTextRequestc tj|}t|}tj|d}t |t r|g}|rt|}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_settingsr%r&listr'GenerateTextRequestr-s r_make_generate_text_requestrDKsD  ' . .E f - - -F"<5O.#&&*().n--  "'+'%    r) r.r/r0r1r2r3r4r5clientr&rEglm.TextServiceClient | Nonetext_types.Completionc Tt||||||||| } 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-)rErequest)rD_generate_response) r.r r/r0r1r2r3r4r5rErIs r generate_textrKsIp*'+'%   G VW = = ==rF)initceZdZdZdS) Completionc |D]\}}t|||d|_|jr|jdd|_dSdS)Nroutput)itemssetattrresult candidates)selfkwargskeyvalues r__init__zCompletion.__init__sd ,,.. & &JC D#u % % % % ? 7/!,X6DKKK 7 7rN)__name__ __module__ __qualname__rYrrrNrNs#77777rrNrIglm.TextServiceClientcZ|t}||}t||}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. Nfilterssafety_feedbackrT_clientr]) rrKtypeto_dictr convert_filters_to_enums convert_safety_feedback_to_enumsconvert_candidate_enumsrN)rIrEresponses rrJrJs~(**##G,,HH~~%%h//H&?@STTHY"."O"###H *A(z&generate_embeddings..:s&&X&Xaqz&X&X&X&X&X&Xr embeddings)r r@rr%r&r'EmbedTextRequest embed_textrcrdrEMBEDDING_MAX_BATCH_SIZEBatchEmbedTextRequestbatch_embed_textextend)r.r$rEembedding_requestembedding_responseembedding_dictrSrs rrtrts>$  ' . .E ~(**$ 0u4HHH#../@AA01199:LMM&4[&A'&J{##r"d$<== Y YE # 9U S S S !'!8!89J!K!K !"455==>PQQN ;  & &&X&X>,;W&X&X&X X X X X r)rrrrrr)r r!rr")r.r6r r7r/r8r0r9r1r9r2r9r3r9r4r:r5r;rr<)r.r6r r&r/r8r0r9r1r9r2r8r3r8r4r:r5r;rErFrrGrr)rIr<rEr^rrN)r.r6r r&rErFrri)r.ror$r&rEr^rrp)r.ror$rvrEr^rrw)r.ror$ryrEr^rrz)& __future__r dataclassescollections.abcrr itertoolstypingrrgoogle.ai.generativelanguageaigenerativelanguager'google.generativeai.clientrgoogle.generativeair google.generativeai.typesr r r r DEFAULT_TEXT_MODELrbatchedrAttributeErrorrr,rDrK prettyprint dataclassrNrJrlrtr]rrrs#"""""..................*********>>>>>>,,,,,,000000111111&&&&&&222222, HH A      "DDDD..@ $"&$(@D15666666v.@ $"&$(@D15+/D>D>D>D>D>D>NE"""77777&77#"7GK22222@,0(((((" %)  %) %)&&&&&&&sAA21A2