Setting the model_kwargs at the object initialization uses the parameters as default for all the subsequent calls to the generate response.arcee = Arcee(    model="DALM-Patent",    # arcee_api_key="ARCEE-API-KEY", # if not already set in the environment    arcee_api_url="https://custom-api.arcee.ai", # default is https://api.arcee.ai    arcee_app_url="https://custom-app.arcee.ai", # default is https://app.arcee.ai    model_kwargs={        "size": 5,        "filters": [            {                "field_name": "document",                "filter_type": "fuzzy_search",                "value": "Einstein"            }        ]    })Generating Text‚ÄãYou can generate text from Arcee by providing a prompt. Here's an example:# Generate textprompt = "Can AI-driven music therapy contribute to the rehabilitation of patients with disorders of consciousness?"response = arcee(prompt)Additional parameters‚ÄãArcee allows you to apply filters and set the size (in terms of count) of retrieved document(s) to aid text generation. Filters help narrow down the results. Here's how to use these parameters:# Define filtersfilters = [    {        "field_name": "document",        "filter_type": "fuzzy_search",        "value": "Einstein"    },    {        "field_name": "year",        "filter_type": "strict_search",        "value": "1905"    }]# Generate text with filters and size paramsresponse = arcee(prompt, size=5, filters=filters)PreviousAnyscaleNextAzure MLSetupAdditional ConfigurationGenerating TextAdditional parametersCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.
This notebook demonstrates how to use the Arcee class for generating text using Arcee's Domain Adapted Language Models (DALMs).
This notebook demonstrates how to use the Arcee class for generating text using Arcee's Domain Adapted Language Models (DALMs). ->: Setting the model_kwargs at the object initialization uses the parameters as default for all the subsequent calls to the generate response.arcee = Arcee(    model="DALM-Patent",    # arcee_api_key="ARCEE-API-KEY", # if not already set in the environment    arcee_api_url="https://custom-api.arcee.ai", # default is https://api.arcee.ai    arcee_app_url="https://custom-app.arcee.ai", # default is https://app.arcee.ai    model_kwargs={        "size": 5,        "filters": [            {                "field_name": "document",                "filter_type": "fuzzy_search",                "value": "Einstein"            }        ]    })Generating Text‚ÄãYou can generate text from Arcee by providing a prompt. Here's an example:# Generate textprompt = "Can AI-driven music therapy contribute to the rehabilitation of patients with disorders of consciousness?"response = arcee(prompt)Additional parameters‚ÄãArcee allows you to apply filters and set the size (in terms of count) of retrieved document(s) to aid text generation. Filters help narrow down the results. Here's how to use these parameters:# Define filtersfilters = [    {        "field_name": "document",        "filter_type": "fuzzy_search",        "value": "Einstein"    },    {        "field_name": "year",        "filter_type": "strict_search",        "value": "1905"    }]# Generate text with filters and size paramsresponse = arcee(prompt, size=5, filters=filters)PreviousAnyscaleNextAzure MLSetupAdditional ConfigurationGenerating TextAdditional parametersCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.