tjddlZddlmZmZmZmZmZddlZddlm Z ddl m Z ddl m Z mZejeZe ddd Gd d e e ZdS) N)AnyDictListMappingOptional) deprecated) Embeddings) BaseModel ConfigDictz0.3.1z1.0.0z!langchain_ollama.OllamaEmbeddings)sinceremovalalternative_importc&eZdZUdZdZeed< dZeed< dZeed< dZ eed < d Z e e ed < d Z e eed < d Ze eed < d Ze e ed< d Ze e ed< d Ze e ed< d Ze e ed< d Ze eed< d Ze eed< d Ze eeed< d Ze eed< d Ze e ed< d Ze eed< dZeed< d Ze eed< ede ee!ffdZ"d Z#e eed< ede$ee!ffdZ%e&dd !Z'd"edeefd#Z(d"eedeeefd$Z)d%eedeeefd&Z*d'edeefd(Z+d S))OllamaEmbeddingsaOllama locally runs large language models. To use, follow the instructions at https://ollama.ai/. Example: .. code-block:: python from langchain_community.embeddings import OllamaEmbeddings ollama_emb = OllamaEmbeddings( model="llama:7b", ) r1 = ollama_emb.embed_documents( [ "Alpha is the first letter of Greek alphabet", "Beta is the second letter of Greek alphabet", ] ) r2 = ollama_emb.embed_query( "What is the second letter of Greek alphabet" ) zhttp://localhost:11434base_urlllama2modelz passage: embed_instructionzquery: query_instructionNmirostat mirostat_eta mirostat_taunum_ctxnum_gpu num_thread repeat_last_nrepeat_penalty temperaturestoptfs_ztop_ktop_pF show_progressheadersreturnc|j|j|j|j|j|j|j|j|j|j |j |j |j |j d dS)z.Get the default parameters for calling Ollama.) rrrrrrrrrrr r!r")roptions)rrrrrrrrrrrr r!r"selfs c/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/langchain_community/embeddings/ollama.py_default_paramsz OllamaEmbeddings._default_paramsxshZ M $ 1 $ 1<<"o!%!3"&"5#/    model_kwargsc&id|ji|jS)zGet the identifying parameters.r)rr+r(s r*_identifying_paramsz$OllamaEmbeddings._identifying_paramssA7DJ'@4+?@@r,forbid)extraprotected_namespacesinputcddi|jpi} tj|jd||j|d|j}n.#tjj$r}td|d}~wwxYw|j dkrtd |j d |j  | }|d S#tjj $r}td |d |j d}~wwxYw)zProcess a response from the API. Args: response: The response from the API. Returns: The response as a dictionary. z Content-Typezapplication/jsonz/api/embeddings)rprompt)r$jsonz$Error raised by inference endpoint: Nz)Error raised by inference API HTTP code: z, embeddingzError raised by inference API: z . Response: ) r$requestspostrrr+ exceptionsRequestException ValueError status_codetextr7JSONDecodeError)r)r4r$resets r*_process_emb_responsez&OllamaEmbeddings._process_emb_responsesE . |!r   I-=111#zUSSd>RSCC "3 I I IGAGGHH H I ?c ! !*???CHH.   A[> !"2   L!LL#(LL  s-.>A)A$$A)B33C&C!!C&cjrA ddlm}||d}n.#t$rtd|}YnwxYw|}fd|DS)Nr)tqdmr)desczgUnable to show progress bar because tqdm could not be imported. Please install with `pip install tqdm`.c:g|]}|Sr1)rE).0r6r)s r* z+OllamaEmbeddings._embed..s'GGGv**622GGGr,)r#rG ImportErrorloggerwarning)r)r4rGiter_s` r*_embedzOllamaEmbeddings._embeds    %%%%%%U);<<<   >  EGGGGGGGGs&AAtextscNfd|D}|}|S)zEmbed documents using an Ollama deployed embedding model. Args: texts: The list of texts to embed. Returns: List of embeddings, one for each text. c&g|] }j|Sr1)r)rJr@r)s r*rKz4OllamaEmbeddings.embed_documents..s'QQQ4 6>>>QQQr,)rP)r)rQinstruction_pairs embeddingss` r*embed_documentsz OllamaEmbeddings.embed_documentss8RQQQ5QQQ[[!233 r,r@cT|j|}||gd}|S)zEmbed a query using a Ollama deployed embedding model. Args: text: The text to embed. Returns: Embeddings for the text. r)rrP)r)r@instruction_pairr9s r* embed_queryzOllamaEmbeddings.embed_querys8#4rls55555555555555666666000000********  8 $ $   : SSSSSy*SS  SSSr,