U hEB@sddlZddlZddlZddlmZmZmZmZddlm m Z ddl m Z ddl mZddlmZddlmZeje jddd Zejee jd d d Zeje jd ddZeejee jdddZejee jdddZd:ddddejeeeejeeje jdddZ d;ddddejeeeejeeje jdddZ!dddddddddeej"eeeejeejee#ee$ee#ee#eeje j%d ddZ&dd Z'd!Z(d!dddddddddd" eej"eeeejeejee#ee$ee#ee#eejee j)ej*d# d$d%Z+e'e+j,ddddddddddd" eej"eeeejeejee#ee$ee#ee#eejee j-ej*d# d&d'Z.ej/j0ej/j1fd(krd)d*iZ2niZ2e'ej*j,ej3fe2d+d,iGd-d.d.ej*Z*e j%e j4ee j)e j-fe*d/d0d1Z5dN)IterableListOptionalUnion)get_default_discuss_client) get_default_discuss_async_client) discuss_types) model_types)contentreturncCs4t|tjr|St|tr&tj|dSt|SdS)Nr ) isinstanceglmMessagestrr r?/tmp/pip-unpacked-wheel-doshhd5e/google/generativeai/discuss.py _make_messages    r)messagesr cCst|tttjfrt|g}ndd|D}tdd|dddD}|sRd}n t|dkrh|}n t dtd d|dddD}|sd }n t|dkr|}n t dt d d|Dr|S||g}t |D]\}}||d|_ q|S) NcSsg|] }t|qSr)r).0messagerrr +sz"_make_messages..css|]}|jr|jVqdSNauthorrmsgrrr -sz!_make_messages..0z$Authors are not strictly alternatingcss|]}|jr|jVqdSrrrrrrr5s1css|] }|jVqdSrrrrrrr=s)r rdictrrrsetlenpoprZ AuthorErrorall enumerater)rZ even_authorsZ even_authorZ odd_authorsZ odd_authorZauthorsirrrr_make_messages's*       r))itemr cCst|tjr|St|trL|}t|d|d<t|d|d<t|St|trxt|\}}tjt|t|dSt|S)Ninputoutputr+r,)r rExampler"copyrrlist)r*r+r,rrr _make_exampleGs     r1)examplesr cCst|ddkrttdg}g}t|D]L\}}t|}|||ddkrVq.tj|d|dd}||g}q.|S)Nrrz You must pass `Primer` objects, pairs of messages, or an *even* number of messages, got: {len(primers)} messagesr r-) r$ ValueErrortextwrapdedentr'rappendrr.)r2resultpairnr*rZprimerrrr_make_examples_from_flatYs(   r:cCst|tjr|gSt|tr&t|gSt|}|s6|S|d}t|trrd|krXt|Sd|krhd|kstdnt|tj rt|Sg}|D]}| t|q|S)Nrr r+r,zTTo create an `Example` from a dict you must supply both `input` and an `output` keys) r rr.r"r1r0r: TypeErrorrZMESSAGE_OPTIONSr6)r2firstr7r*rrr_make_examplests*     r=contextr2r)promptr?r2rr cCs|dkrt|||d}nH|dk p.|dk p.|dk }|rzWYou can't set `prompt`, and its fields `(context, examples, messages)` at the same timerz.Found extra entries in the prompt dictionary: r2cSsi|]\}}|dk r||qSrr)rkvrrr sz-_make_message_prompt_dict..)r"r3r r MessagePromptr#keysissubsetrZMESSAGE_PROMPT_KEYSKeyErrorgetr=r)items)r@r?r2rZ flat_promptrErrr_make_message_prompt_dicts<        rJcCst||||d}t|S)Nr@r?r2r)rJrrDrKrrr_make_message_promptsrL)r?r2r temperaturecandidate_counttop_ptop_kr@) modelr?r2rrMrNrOrPr@r c Cs0t|}t||||d}tj||||||dS)NrK)rQr@rMrOrPrN)r Zmake_model_namerLrGenerateMessageRequest rQr?r2rrMrNrOrPr@rrr_make_generate_message_requests rTcsfdd}|S)Ncs |_|Sr)__doc__)fdocrrinnerszset_doc..innerr)rXrYrrWrset_docs rZzmodels/chat-bison-001) rQr?r2rrMrNrOrPr@client) rQr?r2rrMrNrOrPr@r[r c Cs&t|||||||||d } t| | dS)a" Calls the API and returns a `types.ChatResponse` containing the response. Args: model: Which model to call, as a string or a `types.Model`. context: Text that should be provided to the model first, to ground the response. If not empty, this `context` will be given to the model first before the `examples` and `messages`. This field can be a description of your prompt to the model to help provide context and guide the responses. Examples: * "Translate the phrase from English to French." * "Given a statement, classify the sentiment as happy, sad or neutral." Anything included in this field will take precedence over history in `messages` if the total input size exceeds the model's `Model.input_token_limit`. examples: Examples of what the model should generate. This includes both the user input and the response that the model should emulate. These `examples` are treated identically to conversation messages except that they take precedence over the history in `messages`: If the total input size exceeds the model's `input_token_limit` the input will be truncated. Items will be dropped from `messages` before `examples` messages: A snapshot of the conversation history sorted chronologically. Turns alternate between two authors. If the total input size exceeds the model's `input_token_limit` the input will be truncated: The oldest items will be dropped from `messages`. 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`. 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]. Typical values are in the `[0.9, 1.0]` range. prompt: You may pass a `types.MessagePromptOptions` **instead** of a setting `context`/`examples`/`messages`, but not both. client: If you're not relying on the default client, you pass a `glm.DiscussServiceClient` instead. Returns: A `types.ChatResponse` containing the model's reply. rSr[request)rT_generate_response rQr?r2rrMrNrOrPr@r[r]rrrchatsR r`c s,t|||||||||d } t| | dIdHS)NrSr\)rT_generate_response_asyncr_rrr chat_asyncXs rb) Zkw_onlyTinitFc@seZdZUejddddZeeje d<ddZ e e e jjjedd d Zeje jd d d Ze e jjje je jd ddZe e jjje je jd ddZdS) ChatResponsecCsdSrrrrrrzChatResponse.F)defaultrepr_clientcKs"|D]\}}t|||qdSr)rIsetattr)selfkwargskeyvaluerrr__init__szChatResponse.__init__)r cCs|jddS)Nr )r)rmrrrlastszChatResponse.last)rcCst|}||jd<dS)Nrr)rr)rmrrrrrss)rr cCsbt|jtjrtd|}|dt|d|d<|dt |t f|}t ||jdS)NzBreply can't be called on an async client, use reply_async instead. candidatesrr]r[) r rkrDiscussServiceAsyncClientr;to_dictr%r0r6rrTr^rmrr]rrrreplys  zChatResponse.replycsht|jtjrtd|}|dt|d|d<|dt |t f|}t ||jdIdHS)NzEreply_async can't be called on a non-async client, use reply instead.rtrru) r rkrDiscussServiceClientr;rwr%r0r6rrTrarxrrr reply_asyncs  zChatResponse.reply_asyncN)__name__ __module__ __qualname__ dataclassesfieldrkrrrz__annotations__rqpropertyrZrrfrsrUrsetterMessageOptionsryr{rrrrrf{s$    rf)r]responser[r cCst||}|d}|d|d<|d|d<|d|d<t||}|d|dd|dd|ddtf||dd |S) Nr@r2r?rrtrrMrN)rkrt)typerwr%r6 setdefaultrf)r]rr[r@rrr_build_chat_responses      r)r]r[r cCs$|dkrt}||}t|||Sr)rgenerate_messagerr]r[rrrrr^s r^cs*|dkrt}||IdH}t|||Sr)rrrrrrrrasra)r@r?r2rrQr[cCs:t||||d}|dkrt}|j||d}t||S)Nr>)rQr@)rLrcount_message_tokensrrw)r@r?r2rrQr[r7rrrrs r)N)N)N)N)9rsysr4typingrrrrZgoogle.ai.generativelanguageZaiZgenerativelanguagerZgoogle.generativeai.clientrrZgoogle.generativeai.typesrr rrrZMessagesOptionsr)ZExampleOptionsr.r1r:ZExamplesOptionsr=ZMessagePromptOptionsrrDrJrLZModelNameOptionsfloatintrRrTrZZDEFAULT_DISCUSS_MODELrzrfr`rUrvrb version_infomajorminorZDATACLASS_KWARGSZ dataclassZGenerateMessageResponserr^rarrrrrs"       " /   a  3