a bg@sddlZddlmZmZmZmZmZddlZddlm Z ddl m Z ddl m Z mZeeZe dddd Gd d d e e ZdS) N)AnyDictListMappingOptional) deprecated) Embeddings) BaseModel ConfigDictz0.3.1z1.0.0z!langchain_ollama.OllamaEmbeddings)ZsinceZremovalZalternative_importc@seZdZUdZdZeed<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<ee ee!fdddZ"d Z#e eed<ee$ee!fddd Z%e&d!d"d#Z'eeed$d%d&Z(eeeeed$d'd(Z)eeeeed)d*d+Z*eeed,d-d.Z+d S)/OllamaEmbeddingsaOllama locally runs large language models. To use, follow the instructions at https://ollama.ai/. Example: .. code-block:: python from langchain_community.embeddings import OllamaEmbeddings ollama_emb = OllamaEmbeddings( model="llama:7b", ) r1 = ollama_emb.embed_documents( [ "Alpha is the first letter of Greek alphabet", "Beta is the second letter of Greek alphabet", ] ) r2 = ollama_emb.embed_query( "What is the second letter of Greek alphabet" ) zhttp://localhost:11434base_urlZllama2modelz passage: embed_instructionzquery: query_instructionNmirostat mirostat_eta mirostat_taunum_ctxnum_gpu num_thread repeat_last_nrepeat_penalty temperaturestoptfs_ztop_ktop_pF show_progressheaders)returncCsB|j|j|j|j|j|j|j|j|j|j |j |j |j |j d dS)z.Get the default parameters for calling Ollama.) rrrrrrrrrrrrr)r options)r rrrrrrrrrrrrrselfr#s/var/www/html/cobodadashboardai.evdpl.com/venv/lib/python3.9/site-packages/langchain_community/embeddings/ollama.py_default_paramsxs z OllamaEmbeddings._default_params model_kwargscCsid|ji|jS)zGet the identifying parameters.r )r r%r!r#r#r$_identifying_paramssz$OllamaEmbeddings._identifying_paramsZforbidr#)extraZprotected_namespaces)inputrc Csddi|jpi}z*tj|jd||j|d|jd}Wn6tjjyr}ztd|WYd}~n d}~00|j dkrtd |j |j fz| }|d WStjj y}z"td |d |j WYd}~n d}~00dS) zProcess a response from the API. Args: response: The response from the API. Returns: The response as a dictionary. z Content-Typezapplication/jsonz/api/embeddings)r prompt)rjsonz$Error raised by inference endpoint: Nz/Error raised by inference API HTTP code: %s, %s embeddingzError raised by inference API: z . Response: ) rrequestspostr r r% exceptionsRequestException ValueError status_codetextr+JSONDecodeError)r"r)rresetr#r#r$_process_emb_responses2   $   z&OllamaEmbeddings._process_emb_responsecs\jrFzddlm}||dd}WqJtyBtd|}YqJ0n|}fdd|DS)Nr)tqdmr )desczgUnable to show progress bar because tqdm could not be imported. Please install with `pip install tqdm`.csg|]}|qSr#)r9).0r*r!r#r$ z+OllamaEmbeddings._embed..)rr: ImportErrorloggerwarning)r"r)r:Ziter_r#r!r$_embeds   zOllamaEmbeddings._embed)textsrcs fdd|D}|}|S)zEmbed documents using an Ollama deployed embedding model. Args: texts: The list of texts to embed. Returns: List of embeddings, one for each text. csg|]}j|qSr#)r)r<r4r!r#r$r=r>z4OllamaEmbeddings.embed_documents..)rB)r"rCZinstruction_pairsZ embeddingsr#r!r$embed_documentss  z OllamaEmbeddings.embed_documents)r4rcCs"|j|}||gd}|S)zEmbed a query using a Ollama deployed embedding model. Args: text: The text to embed. Returns: Embeddings for the text. r)rrB)r"r4Zinstruction_pairr-r#r#r$ embed_querys zOllamaEmbeddings.embed_query),__name__ __module__ __qualname____doc__r str__annotations__r rrrrintrfloatrrrrrrrrrrrrrboolrdictpropertyrrr%r&rr'r Z model_configr9rBrDrEr#r#r#r$r s<       $ r )loggingtypingrrrrrr.Zlangchain_core._api.deprecationrZlangchain_core.embeddingsrZpydanticr r getLoggerrFr@r r#r#r#r$s