Saravanan666/pypi-org huggingface dataset:
Package: genius
Genius========Genius是一个开源的python中文分词组件，采用 CRF(Conditional Random Field)条件随机场算法。Feature========* 支持python2.x、python3.x以及pypy2.x。* 支持简单的pinyin分词* 支持用户自定义break* 支持用户自定义合并词典* 支持词性标注Source Install==========* 安装git: 1) ubuntu or debian `apt-get install git` 2) fedora or redhat `yum install git`* 下载代码：`git clone https://github.com/duanhongyi/genius.git`* 安装代码：`python setup.py install`Pypi Install============* 执行命令：`easy_install genius`或者`pip install genius`Algorithm==========* 采用trie树进行合并词典查找* 基于wapiti实现条件随机场分词* 可以通过genius.loader.ResourceLoader来重载默认的字典功能 1)：分词`genius.seg_text`方法==============* `genius.seg_text`函数接受5个参数，其中text是必填参数:* `text`第一个参数为需要分词的字符* `use_break`代表对分词结构进行打断处理，默认值`True`* `use_combine`代表是否使用字典进行词合并，默认值`False`* `use_tagging`代表是否进行词性标注，默认值`True`* `use_pinyin_segment`代表是否对拼音进行分词处理，默认值`True`代码示例( 全功能分词 )#encoding=utf-8import geniustext = u"""昨天,我和施瓦布先生一起与部分企业家进行了交流,大家对中国经济当前、未来发展的态势、走势都十分关心。"""seg_list = genius.seg_text(text,use_combine=True,use_pinyin_segment=True,use_tagging=True,use_break=True)print('\n'.join(['%s\t%s' % (word.text, word.tagging) for word in seg_list]))功能 2)：面向索引分词==============* `genius.seg_keywords`方法专门为搜索引擎索引准备，保留歧义分割，其中text是必填参数。* `text`第一个参数为需要分词的字符* `use_break`代表对分词结构进行打断处理，默认值`True`* `use_tagging`代表是否进行词性标注，默认值`False`* `use_pinyin_segment`代表是否对拼音进行分词处理，默认值`False`* 由于合并操作与此方法有意义上的冲突，此方法并不提供合并功能；并且如果采用此方法做索引时候，检索时不推荐`genius.seg_text`使用`use_combine=True`参数。代码示例#encoding=utf-8import geniusseg_list = genius.seg_keywords(u'南京市长江大桥')print('\n'.join([word.text for word in seg_list]))功能 3)：关键词提取==============* `genius.tag_extract`方法专门为提取tag关键字准备，其中text是必填参数。* `text`第一个参数为需要分词的字符* `use_break`代表对分词结构进行打断处理，默认值`True`* `use_combine`代表是否使用字典进行词合并，默认值`False`* `use_pinyin_segment`代表是否对拼音进行分词处理，默认值`False`代码示例#encoding=utf-8import geniustag_list = genius.extract_tag(u'南京市长江大桥')print('\n'.join(tag_list))其他说明 4)：=================* 目前分词语料出自人民日报1998年1月份，所以对于新闻类文章分词较为准确。* CRF分词效果很大程度上依赖于训练语料的类别以及覆盖度，若解决语料问题分词和标注效果还有很大的提升空间。
Package: geniusbot
GeniusbotVersion: 3.29.1The Ever-learning and ever-improving tool!Click the arrows on the left of each of the items below to see more information about them.Geniusbot ChatChat with your friendly and extremely intelligent Geniusbot.Powered by Artificial Intelligence scaled to your PC's performance!Media DownloaderDownload videos from various websites!Supports:YouTubeDailyMotionRumbleTwitterBitChuteAnd More!Examples for how to find user & channel.Open File allows you to browse for a text file that has a list of YouTube links.
Examples contents:https://www.youtube.com/watch?v=75-siCngYCc
https://www.youtube.com/watch?v=7RSpZkIjK4w
https://www.youtube.com/watch?v=7qRSAUb96wgMedia ManagerManage your media library by:
- Cleaning up names of files and folders based off pre-built filters. 
- Apply subtitles located in "Sub" folder within each media directory
- Move files to final destination after processingDownload as MP3 or MP4Website ArchivingArchive any website by taking screenshots of any website entered or scraping that site for specific file types.Choose from a variety of options like file type, quality, and image size.Subtitle ShiftShift a subtitle forward or backward a few seconds so it aligns with your video!Report ManagerGenerate report analysis using:
- Visualization plots
- Pandas Profiling
- Report Analysis Text fileMerge reports with the following methods:InnerOuterLeftRightAppendMultiple column selection optional for Inner, Outer, Left, and Right joiningRepository ManagerManage your repositories by cloning, pulling, or running your own set of git commands on a given directoryRom ManagerConvert Game ROMs to Compressed Hunks of Data (CHD) file format or RVZ file formatAutomatically generate missing .cue files for your .bin files!Systems ManagerManage your Linux/Windows System!Install ApplicationsCleanUpdateUpgrade GeniusbotEnable Windows FeaturesInstallpipinstallgeniusbotRepository Owners:
Package: genius-chatbot
Genius ChatbotVersion: 1.10.0Chatbot that uses any hugging face model or OpenAI endpoint.Local vector store supported with ChromaDB, or connect to a PGVector databaseAllows for scalable intelligence tailored for hardware limitationsThis repository is actively maintained - Contributions are welcome!Contribution Opportunities:Support more vector databasesGet list of models to choose fromOutput everything as JSON when selectedUsage:Short FlagLong FlagDescription-h--helpSee Usage-a--assimilateAssimilate knowledge from media provided in directory--batch-tokenNumber of tokens per batch--chromadb-directoryNumber of chunks to use--chunksNumber of chunks to use-e--embeddings-modelEmbeddings modelto use--hide-sourceHide source of answer-j--jsonExport to JSON--openai-tokenOpenAI Token--openai-apiOpenAI API Url--pgvector-userPGVector user--pgvector-passwordPGVector password--pgvector-hostPGVector host--pgvector-portPGVector port--pgvector-databasePGVector database--pgvector-driverPGVector driver-p--promptPrompt for chatbot--mute-streamMute stream of generation-m--modelCopyGPT4All.bin file from the Model Explorer--max-token-limitMaximum token to generate--model-directoryDirectory to store models locally--model-engineGPT4All LlamaCPP, or OpenAIExample:genius-chatbot--assimilate"/directory/of/documents"genius-chatbot--prompt"What is the 10th digit of Pi?"genius-chatbot--prompt"Chatbots are cool because they"\--model"wizardlm-13b-v1.1-superhot-8k.ggmlv3.q4_0.bin"\--model-engine"GPT4All"\--assimilate"/directory/of/documents"\--jsonInstallation Instructions:Install Python PackageWindows Prerequisites:Visual Studio Code 2022wingetinstall-e--idKitware.CMakeUbuntu Prerequisites:aptinstall-ypandocpython-mpipinstallgenius-chatbotRepository Owners:
Package: geniusdotpy
genius.pyPython wrapper for Genius APIWith genius.py, enjoy an easy-to-use interface to interact withGenius APITable of ContentsTable of ContentsFeaturesInstallGetting StartedReferencesFeaturesFeature rich interfaceEasy to useLyrics web scraperInstallpipinstallgeniusdotpyGetting StartedTo get started...Get your Client Access TokenhereCreate a newGeniusobjectfromgeniusdotpy.geniusimportGenius# Get your client access token from https://genius.com/api-clientsclient_access_token="token"# Create a GeniusBuilder objectgenius=Genius(client_access_token=client_access_token)# Search for a track by IDtrack1=genius.search_track_by_id(378195)print(repr(track1))# Search artist by IDartist1=genius.search_artist(track1.artist.id)print(repr(artist1))# Search for a track by querytrack3=genius.search("Beat It")[0]print(repr(track3))# Search tracks by artisttracks:list[Track]=genius.search_track_by_artist(artist_id=16775)track4=tracks[0]print(repr(track4))# Retrieve lyricstrack4.get_lyrics()print(track4.lyrics)???ProfitReferencesGenius APICreated with 💖 byjjoeldaniel
Package: geniuses
Genius Lyrics API Python ClientA Lightweight client for typed interaction withGenius API.Examplesfrom geniuses import GeniusClient

client = GeniusClient("<your_token>")
songs = client.search("Cariñito los hijos")

print(songs[0].primary_artist.name)  # Los hijos del sol
print(songs[0].lyrics)  # Lloro por quererte ...

songs_from_artist = list(songs[0].primary_artist.get_songs())
print(songs_from_artist)  # [<Song(title=Cariñito, id=1949442)>, <Song(title=Si Me Quieres, id=2078361)>]CLIWIPDevelopmentThis project usestoxfor running tests and
other things (style check, coverage reports).It is recommended to installcondaalong withtox-condafor using tox.
Afterwards,toxcommand will run all the steps for you.This project strictly usesblackas an opinionated code style.
Any written line should comply with that (don’t forget to runblack .for PRs).LicenseReleased underthe Apache License.
Package: geniushub
GeniusHubPython library to provide connect to Genius Hub on a local network.InstallationEither clone this resposition and runpython setup.py install, or install from pip usingpip install genius.APIThis library makes use of the undocumented API for communicating to the Genius Hub. This API may change with future updates to the Genius Hub Firmware.The library supports the following functions:getClimateList()
getSwitchList()
getTRVList()
getSensorList()
getSwitchList()
getZone(zoneId)
getDevice(zoneId, addr)
GET_CLIMATE(zone)
GET_SWITCH(zone)
getSensor(cv)
getTRV(cv)
GET_MODE(zone)
putjson(device_id, data)UsageInitialise a link to the hub by passing in the local IP address, username and password. The username and password are the same that you use to log into your Genius application. Once logged in successfully the module will poll the hub at regular intervals so that getting values from the hub will be cached locally.What is read from the getters is self explanatory. The putjson POST the data to the Genius Hub. The format of the json can be discovered by exploring the Genius application and view the requests posted to the hub.import asyncio
from geniushub import GeniusHub

IP_ADDRESS = 'Your local ip address'
USERNAME = 'Your user name'
PASSWORD = 'Your password'
INTERVAL = 60


async def main():
    genius_hub = GeniusHub(IP_ADDRESS, USERNAME, PASSWORD, INTERVAL)
    await genius_hub.getjson('/zones')

    # Get the zones with a temperature
    climate_list = genius_hub.getClimateList()

    print("Climate -------------------------------------------------------------")
    for zone in climate_list:
        print(zone)

    trvs = genius_hub.getTRVList()

    print("TRV -----------------------------------------------------------------")
    for trv in trvs:
        print(trv)

    switches = genius_hub.getSwitchList()

    print("Switches ------------------------------------------------------------")
    for switch in switches:
        print(switch)

    sensors = genius_hub.getSensorList()

    print("Sensors -------------------------------------------------------------")
    for sensor in sensors:
        print(sensor)

loop = asyncio.get_event_loop()
loop.run_until_complete(main())
loop.close()
Package: genius-lite
genius_lite基于 Python requests 库封装的轻量爬虫系统安装pip install genius_lite使用fromgenius_liteimportGeniusLiteclassMySpider(GeniusLite):defstart_requests(self):yieldself.crawl('https://www.google.com',self.parse_google_page)defparse_google_page(self,response):print(response.text)detail_urls=[...]forurlindetail_urls:yieldself.crawl(url,self.parse_detail_page)defparse_detail_page(self,response):...if__name__=='__main__':my_spider=MySpider()my_spider.run()start_requests所有爬虫请求的入口，爬虫子类必须重写该方法以生成请求种子fromgenius_liteimportGeniusLiteclassMySpider(GeniusLite):defstart_requests(self):yieldself.crawl(url='https://www.google.com',parser=self.parse_func)defparse_func(self,response):print(response.text)self.crawl通过 yield 该方法生成爬虫请求种子，部分参数可查看requests文档url: 请求地址parser: 响应解析函数，参数为 response 对象method: (default='GET') 请求方法params: (optional) 查询参数data: (optional) POST 请求参数headers: (optional) 请求头payload: (optional) 携带到响应解析函数的数据，通过 response.payload 形式读取encoding: (optional) response 编码设置unique: (default=True) 设置该请求是否唯一，设为 True 时将根据 url、method、params、data 内容过滤相同请求kwargs: (optional) 支持的关键字参数如下：
cookies, files, json, auth, hooks, timeout, verify, stream, cert, allow_redirects, proxiesresponse参考requests.ResponseGeniusLite configfromgenius_liteimportGeniusLiteclassMySpider(GeniusLite):spider_name='MySpider'spider_config={'timeout':15}log_config={'output':'/absolute/path'}...spider_name爬虫命名，不设置则默认为运行的爬虫子类名spider_configname       | type              | default
————————————————————————————————————————————
timeout    | num or (num, num) | 10爬虫全局设置log_configname       | type              | default
————————————————————————————————————————————
enable     | bool              | False
level      | str               | 'DEBUG'
output     | str               | Nonelog 配置
Package: genius-lyrics
GeniusFind the lyrics of the song you are listening to directly from your Linux terminal. Lyrics are fromGeniusRequirementsPython 3BeautifulSoupOptionalargcompletewithactive global completion: tab completion of argumentsHow to usegit clone https://github.com/golim/genius
cd genius
chmod +x genius-lyricsSet an environment variable calledGENIUS_TOKENwith the token you can requesthereand reboot../genius-lyricsHow to InstallUsingpip:pip install genius-lyricsFrom cloned source code:sudo cp genius-lyrics /usr/local/bin/genius-lyricsScreenshotWarningDue to the stupid search function of genius it may happen that the script finds the wrong song.
Package: geniusmlapi
GeniusMLAPIPyPI package to use Genius.Getting StartedDependenciesYou need Python 3.7 or later to usegeniusmlapi. You can find it atpython.org.
You also need setuptools, wheel and twine packages, which is available fromPyPI. If you have pip, just run:pip install setuptools
pip install wheel
pip install twineInstallationClone this repo to your local machine using:git clone https://github.com/fagnercandido/GeniusMLAPIFeaturesFile structure for PyPI packagesSetup with package informationsLicense exampleRunningpip install geniusmlapiAnd thenfrom geniusmlapi import gmlFinally:genius = gml.GeniusLM(ACCESS_TOKEN)
songs = genius.search('my search')
dataframe = genius.get_dataframe(songs)
dataframe.head()
Package: geniuspy
GeniuspyA Python wrapper around the Genius API.IntroductionThis package provides a pure Python interface for theGenius API.Genius provides information about songs lyrics and music knowledge. The aim of this package is to make the use of the Genius API easier when coding.InstallingYou can install geniuspy using:$ pip install geniuspyGetting the codeThe code is hosted athttps://github.com/Lletfrix/geniuspy.Download the latest development version with:$ git clone git://github.com/lletfrix/geniuspy.git
$ cd geniuspy
Package: geniusrise
AI EcosystemDocumentation||Examples||CloudAboutGeniusriseis a modular, loosely-coupled
MLOps framework designed for the era of Large Language Models,
offering flexibility and standardization in designing networks of
AI agents.It defines components and orchestrates them providing observability, state management and data handling,
all while supporting diverse infrastructures. With its modular and unopinonated architecture,Geniusriseempowers teams to build, share,
and deploy AI across various platforms.Geniusrise is powered by its components:geniusrise-text: Text components offerring:Inference APIsBulk inferenceFine-tuninggeniusrise-audio: Audio components offerring:Inference APIsBulk inferenceFine-tuninggeniusrise-vision: Vision components offerring:Inference APIsBulk inferenceFine-tuninggeniusrise-listeners: Streaming data ingestiongeniusrise-databases: Bulk data ingestionLinksWebsite:geniusrise.aiFrameworkThis is the base geniusrise framework, also thegeniusCLI.
It provides the base structure and orchestration primitives forSpouts andBolts, and also covers operations.Docs:docs.geniusrise.aiExamples:geniusrise/examplesCloud:geniusrise.com
Package: geniusrise-audio
AI EcosystemDocumentation||Examples||CloudAboutGeniusriseis a modular, loosely-coupled
MLOps framework designed for the era of Large Language Models,
offering flexibility and standardization in designing networks of
AI agents.It defines components and orchestrates them providing observability, state management and data handling,
all while supporting diverse infrastructures. With its modular and unopinonated architecture,Geniusriseempowers teams to build, share,
and deploy AI across various platforms.Geniusrise is powered by its components:geniusrise-text: Text components offerring:Inference APIsBulk inferenceFine-tuninggeniusrise-audio: Audio components offerring:Inference APIsBulk inferenceFine-tuninggeniusrise-vision: Vision components offerring:Inference APIsBulk inferenceFine-tuninggeniusrise-listeners: Streaming data ingestiongeniusrise-databases: Bulk data ingestionLinksWebsite:geniusrise.aiDocs:docs.geniusrise.aiExamples:geniusrise/examplesCloud:geniusrise.comAudio ComponentsThese are audio components, mainly focused around models of the audio modality (either input or output).
Package: geniusrise-databases
Database SpoutsThis is a collection of generic batch spouts for various databases.Includes:No.NameDescriptionOutput TypeInput Type1HBaseBatch spout for HBaseBatchHBase2PostgreSQLBatch spout for PostgreSQLBatchPostgreSQL3MySQLBatch spout for MySQLBatchMySQL4MongoDBBatch spout for MongoDBBatchMongoDB5CassandraBatch spout for CassandraBatchCassandra6RedisBatch spout for RedisBatchRedis7ElasticsearchBatch spout for ElasticsearchBatchElasticsearch8OracleBatch spout for OracleBatchOracle9SQL ServerBatch spout for SQL ServerBatchSQL Server10SQLiteBatch spout for SQLiteBatchSQLite11Neo4jBatch spout for Neo4jBatchNeo4j12BigtableBatch spout for BigtableBatchBigtable13DynamoDBBatch spout for DynamoDBBatchDynamoDB14Azure Table StorageBatch spout for Azure Table StorageBatchAzure Table Storage15CouchbaseBatch spout for CouchbaseBatchCouchbase16InfluxDBBatch spout for InfluxDBBatchInfluxDB17TimescaleDBBatch spout for TimescaleDBBatchTimescaleDB18TeradataBatch spout for TeradataBatchTeradata19TiDBBatch spout for TiDBBatchTiDB20VoltdbBatch spout for VoltdbBatchVoltdb21SybaseBatch spout for SybaseBatchSybase22DB2Batch spout for DB2BatchDB223PrestoBatch spout for PrestoBatchPresto24RiakBatch spout for RiakBatchRiak25MemSQLBatch spout for MemSQLBatchMemSQL26LDAPBatch spout for LDAPBatchLDAP27KeySpacesBatch spout for KeySpacesBatchKeySpaces28KairosDBBatch spout for KairosDBBatchKairosDB29GraphiteBatch spout for GraphiteBatchGraphite30FireStoreBatch spout for FireStoreBatchFireStore31DocumentDBBatch spout for DocumentDBBatchDocumentDB32CockroachBatch spout for CockroachBatchCockroach33Cloud SQLBatch spout for Cloud SQLBatchCloud SQL34CosmosDBBatch spout for CosmosDBBatchCosmosDB35AthenaBatch spout for AthenaBatchAthena36ArangoDBBatch spout for ArangoDBBatchArangoDB37NuodbBatch spout for NuodbBatchNuodb38OpenTSDBBatch spout for OpenTSDBBatchOpenTSDB39OpenTSDBBatch spout for VerticaBatchVertica40OpenTSDBBatch spout for Google BigqueryBatchBigquery41SpannerBatch spout for Google SpannerBatchSpanner
Package: geniusrise-huggingface
DocumentationAboutGeniusriseis a modular, loosely-coupled
AgentOps / MLOps framework designed for the era of Large Language Models,
offering flexibility, inclusivity, and standardization in designing networks of
AI agents.It seamlessly integrates tasks, state management, data handling, and model
versioning, all while supporting diverse infrastructures and user expertise
levels. With its plug-and-play architecture,Geniusriseempowers teams to build, share,
and deploy AI agent workflows across various platforms.Huggingface BoltsThis is a collection of generic streaming and (micro) batch bolts interfacing
with the huggingface ecosystem.Includes:No.NameDescriptionInput TypeOutput Type1Text ClassificationFine-tuning for text classification tasksBatchBatch2Instruction TuningFine-tuning for instruction tuning tasksBatchBatch3Commonsense ReasoningFine-tuning for commonsense reasoning tasksBatchBatch4Language ModelingFine-tuning for language modeling tasksBatchBatch5Named Entity RecognitionFine-tuning for named entity recognition tasksBatchBatch6Question AnsweringFine-tuning for question answering tasksBatchBatch7Sentiment AnalysisFine-tuning for sentiment analysis tasksBatchBatch8SummarizationFine-tuning for summarization tasksBatchBatch9TranslationFine-tuning for translation tasksBatchBatch
Package: geniusrise-openai
DocumentationAboutGeniusriseis a modular, loosely-coupled
AgentOps / MLOps framework designed for the era of Large Language Models,
offering flexibility, inclusivity, and standardization in designing networks of
AI agents.It seamlessly integrates tasks, state management, data handling, and model
versioning, all while supporting diverse infrastructures and user expertise
levels. With its plug-and-play architecture,Geniusriseempowers teams to build, share,
and deploy AI agent workflows across various platforms.Openai BoltsThis is a collection of generic streaming and (micro) batch bolts interfacing
with the openai ecosystem.Includes:No.NameDescriptionInput TypeOutput Type1Text ClassificationFine-tuning for text classification tasksBatchBatch2Instruction TuningFine-tuning for instruction tuning tasksBatchBatch3Commonsense ReasoningFine-tuning for commonsense reasoning tasksBatchBatch4Language ModelingFine-tuning for language modeling tasksBatchBatch5Named Entity RecognitionFine-tuning for named entity recognition tasksBatchBatch6Question AnsweringFine-tuning for question answering tasksBatchBatch7Sentiment AnalysisFine-tuning for sentiment analysis tasksBatchBatch8SummarizationFine-tuning for summarization tasksBatchBatch9TranslationFine-tuning for translation tasksBatchBatchExamplesPlease refer to theexamplesdirectory.
Package: geniusrise-prompt-actions
Database SpoutsThis is a collection of generic batch spouts for various databases.Includes:No.NameDescriptionOutput TypeInput Type1HBaseBatch spout for HBaseBatchHBase2PostgreSQLBatch spout for PostgreSQLBatchPostgreSQL3MySQLBatch spout for MySQLBatchMySQL4MongoDBBatch spout for MongoDBBatchMongoDB5CassandraBatch spout for CassandraBatchCassandra6RedisBatch spout for RedisBatchRedis7ElasticsearchBatch spout for ElasticsearchBatchElasticsearch8OracleBatch spout for OracleBatchOracle9SQL ServerBatch spout for SQL ServerBatchSQL Server10SQLiteBatch spout for SQLiteBatchSQLite11Neo4jBatch spout for Neo4jBatchNeo4j12BigtableBatch spout for BigtableBatchBigtable13DynamoDBBatch spout for DynamoDBBatchDynamoDB14Azure Table StorageBatch spout for Azure Table StorageBatchAzure Table Storage15CouchbaseBatch spout for CouchbaseBatchCouchbase16InfluxDBBatch spout for InfluxDBBatchInfluxDB17TimescaleDBBatch spout for TimescaleDBBatchTimescaleDB18TeradataBatch spout for TeradataBatchTeradata19TiDBBatch spout for TiDBBatchTiDB20VoltdbBatch spout for VoltdbBatchVoltdb21SybaseBatch spout for SybaseBatchSybase22DB2Batch spout for DB2BatchDB223PrestoBatch spout for PrestoBatchPresto24RiakBatch spout for RiakBatchRiak25MemSQLBatch spout for MemSQLBatchMemSQL26LDAPBatch spout for LDAPBatchLDAP27KeySpacesBatch spout for KeySpacesBatchKeySpaces28KairosDBBatch spout for KairosDBBatchKairosDB29GraphiteBatch spout for GraphiteBatchGraphite30FireStoreBatch spout for FireStoreBatchFireStore31DocumentDBBatch spout for DocumentDBBatchDocumentDB32CockroachBatch spout for CockroachBatchCockroach33Cloud SQLBatch spout for Cloud SQLBatchCloud SQL34CosmosDBBatch spout for CosmosDBBatchCosmosDB35AthenaBatch spout for AthenaBatchAthena36ArangoDBBatch spout for ArangoDBBatchArangoDB37NuodbBatch spout for NuodbBatchNuodb38OpenTSDBBatch spout for OpenTSDBBatchOpenTSDB39OpenTSDBBatch spout for VerticaBatchVertica40OpenTSDBBatch spout for Google BigqueryBatchBigquery41SpannerBatch spout for Google SpannerBatchSpanner
Package: geniusrise-text
AI EcosystemDocumentation||Examples||CloudAboutGeniusriseis a modular, loosely-coupled
MLOps framework designed for the era of Large Language Models,
offering flexibility and standardization in designing networks of
AI agents.It defines components and orchestrates them providing observability, state management and data handling,
all while supporting diverse infrastructures. With its modular and unopinonated architecture,Geniusriseempowers teams to build, share,
and deploy AI across various platforms.Geniusrise is powered by its components:geniusrise-text: Text components offerring:Inference APIsBulk inferenceFine-tuninggeniusrise-audio: Audio components offerring:Inference APIsBulk inferenceFine-tuninggeniusrise-vision: Vision components offerring:Inference APIsBulk inferenceFine-tuninggeniusrise-listeners: Streaming data ingestiongeniusrise-databases: Bulk data ingestionLinksWebsite:geniusrise.aiDocs:docs.geniusrise.aiExamples:geniusrise/examplesCloud:geniusrise.comText ComponentsThese are text components, mainly focused around models of the text modality (both input and output).
This also includes large language models.