GitHub - JoshuaC215/agent-service-toolkit: Full toolkit for running an AI agent service built with LangGraph, FastAPI and StreamlitYou signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. Reload to refresh your session. You switched accounts on another tab or window. Reload to refresh your session. Dismiss alert
Overview - Chainlit
Key features Build fast: Integrate seamlessly with an existing code base or start from scratch in minutes Multi Platform: Write your assistant logic once, use everywhere Data persistence: Collect, monitor and analyze data from your users Visualize multi-steps reasoning: Understand the intermediary steps that produced an output at a glance
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ã¤ãã‚ŠãªãŒã‚‰å¦ã¶ï¼AIアプリ開発入門 - LangChain & Streamlit ã«ã‚ˆã‚‹ ChatGPT API 徹底活用
ã¤ãã‚ŠãªãŒã‚‰å¦ã¶ï¼AIアプリ開発入門 - LangChain & Streamlit ã«ã‚ˆã‚‹ ChatGPT API 徹底活用 ã“ã®æœ¬ã§ã¯ã€LangChain 㨠Streamlit を用ã„ã¦ã€ChatGPT APIを活用ã™ã‚‹AIアプリを開発ã—ã¦ã„ãã¾ã™ã€‚ã¤ãã‚ŠãªãŒã‚‰å¦ã¶ã“ã¨ã‚’é‡è¦–ã—ã€ç°¡å˜ãªãƒãƒ£ãƒƒãƒˆã‚¢ãƒ—リ開発ã‹ã‚‰å§‹ã‚ã¦ã€Embeddingを活用ã™ã‚‹ã‚¢ãƒ—リ開発ã¾ã§ã€ã‚¹ãƒ†ãƒƒãƒ—ãƒã‚¤ã‚¹ãƒ†ãƒƒãƒ—ã§å¦ã¹ã¾ã™ã€‚ AIアプリをãƒãƒ¼ã‚«ãƒ«ç’°å¢ƒã§é–‹ç™ºã—ãŸå¾Œã¯ã€WEB上ã«ãƒ‡ãƒ—ãƒã‚¤ã™ã‚‹æ–¹æ³•ã‚‚å¦ã³ã¾ã™ã€‚クラウドã®çŸ¥è˜ã‚‚ã»ã¼å¿…è¦ãªãã€ãƒ©ãƒ³ãƒ‹ãƒ³ã‚°ã‚³ã‚¹ãƒˆã‚‚掛ã‹ã‚‰ãªã„方法ã§è¡Œã†ãŸã‚ã€ãœã²ä½œã£ãŸã‚¢ãƒ—リを公開ã™ã‚‹ã“ã¨ã«ãƒãƒ£ãƒ¬ãƒ³ã‚¸ã—ã¦ã¿ã¾ã—ょã†ã€‚ 500円ã¨è¨å®šã—ã¦ã„ã¾ã™ãŒæŠ•ã’éŠç”¨ã§ã™ã€‚本文ã¯å…¨ã¦ç„¡æ–™ã§èªã‚ã¾ã™ã€‚
Streamlitã§è‡ªåˆ†ç”¨ChatGPTを作る
自分用ChatGPTã®ã‚ˆã†ãªã‚‚ã®ã‚’作りãŸã„ã¨æ€ã„ã¾ã—ãŸã€‚UIã®å®Ÿè£…ã¯ã€Streamlitを使ã†ã¨æ¥½ã§ããã†ã§ã™ã€‚ ã§ããŸã‚‚ã® ã¨ã„ã†ã§ã‚ã‘ã§ã€ã“ã‚“ãªæ„Ÿã˜ã®ã‚‚ã®ãŒã‚µã‚¯ãƒƒã¨ä½œã‚Œã¾ã—ãŸï¼ˆæ–°ã—ã„発言ãŒä¸Šã«è¡¨ç¤ºã•ã‚Œã‚‹ä»•æ§˜ã§ã™ï¼‰ã€‚UIã«ã¯å‰è¿°ã®é€šã‚ŠStreamlitã‚’ã€ãƒã‚¸ãƒƒã‚¯éƒ¨åˆ†ã«ã¯LangChainを使ã£ã¦ã„ã¾ã™ã€‚ ã“ã‚“ãªã“ã¨ãŒã§ãã¾ã™ã€‚ ç ”ç©¶ã‚¢ã‚·ã‚¹ã‚¿ãƒ³ãƒˆã¨ã—ã¦æŒ¯ã‚‹èˆžã† ãƒãƒ£ãƒƒãƒˆé¢¨ã®UIã§ä¼šè©±ã§ãã‚‹ 会話履æ´ã«åŸºã¥ã„ã¦ä¼šè©±ã§ãã‚‹ 今ã®ã¨ã“ã‚ã¯ã€ChatGPTã®Web版を使ã†ã®ã¨ãã‚“ãªã«å¤‰ã‚ã‚Šã¾ã›ã‚“。ソースコードã¯ã€ä»¥ä¸‹ã®ãƒªãƒã‚¸ãƒˆãƒªã«ç½®ã„ã¦ã‚ã‚Šã¾ã™ã€‚ 開発ã™ã‚‹ä¸Šã§ãƒãƒžã£ãŸã“㨠ãƒãƒ£ãƒƒãƒˆã®ãƒã‚¸ãƒƒã‚¯éƒ¨åˆ†ã«é–¢ã—ã¦ã¯ã€ã€ŒLangChain ã® ãƒãƒ£ãƒƒãƒˆãƒ¢ãƒ‡ãƒ« (ChatGPTã®æ–°ã—ã„抽象化) を試ã™ï½œnpakaã€ãªã©ã‚’å‚考ã«ã™ã‚Œã°ã€ç°¡å˜ã«å®Ÿè£…ã§ãã‚‹ã§ã—ょã†ã€‚ 会話履æ´åŸºã¥ã„ã¦ç™ºè¨€ã§ãるよã†ã«ã™ã‚‹ãŸã‚ã«ã¯ã€L
Streamlit with Google Cloud: Firebase èªè¨¼
å‰å›žã«å¼•ã続ãã€ä»Šå›žã¯ Streamlit アプリケーションã«ã€Firebase èªè¨¼ã«ã‚ˆã‚‹ãƒã‚°ã‚¤ãƒ³æ©Ÿèƒ½ã‚’実装ã—ã€Cloud Run ã§å‹•ã‹ã—ã¦ã¿ã¾ã™ã€‚ ã“ã®é€£è¼‰ã§ã¯ã€Google Cloud 上㧠Streamlit を上手ã«å‹•ã‹ã™æ–¹æ³•ã‚’ã”紹介ã—ã¦ã„ã¾ã™ã€‚ Cloud Run ã§ã® Hello, world! Firebase èªè¨¼ã¨ã®é€£æº （本記事） BigQuery ã¸ã®ã‚¯ã‚¨ãƒª GitHubã€GitLabã€Cloud Build ã§ã® CI/CD Firebase プãƒã‚¸ã‚§ã‚¯ãƒˆã‚’準備ã™ã‚‹ 1. プãƒã‚¸ã‚§ã‚¯ãƒˆã‚’è¿½åŠ https://console.firebase.google.com/ ã§ã€Œãƒ—ãƒã‚¸ã‚§ã‚¯ãƒˆã‚’作æˆã€ã‚’クリック。 プãƒã‚¸ã‚§ã‚¯ãƒˆã¯é¸æŠžè‚¢ã®ä¸ã‹ã‚‰ã‚¯ãƒ©ã‚¦ãƒ‰ã«ç”¨æ„ã—ãŸãƒ—ãƒã‚¸ã‚§ã‚¯ãƒˆåã‚’é¸æŠžã—ã¦ã€ç¶šè¡Œã€‚ プランを確èªã€ç¶šè¡Œã¨é€²ã¿ã¾ã™ã€‚「ã“ã®ãƒ—ãƒã‚¸ã‚§ã‚¯ãƒˆã§ Google アナリティクスを
ã€GCP】Cloud Runã§Python FastAPI・Streamlitをデプãƒã‚¤ | Yukkuri Machine Learning
ã¯ã˜ã‚ã« Cloud Runã¯ã‚µãƒ¼ãƒãƒ¼ãƒ¬ã‚¹ãªã‚³ãƒ³ãƒ†ãƒŠå®Ÿè¡Œç’°å¢ƒã‚’æä¾›ã™ã‚‹GCPã®ã‚µãƒ¼ãƒ“スã§ã™ã€‚ Cloud Runを使ã†ã“ã¨ã«ã‚ˆã£ã¦ã€Dockerイメージを構築ã™ã‚‹ã ã‘ã§ã‚¢ãƒ—リã®ãƒ‡ãƒ—ãƒã‚¤ã‚’ç°¡å˜ã«ãŠã“ãªã†ã“ã¨ãŒã§ãã¾ã™ã€‚ ã“ã®è¨˜äº‹ã§ã¯ã€pythonã®ã‚¢ãƒ—リケーションをCloud Runã«ãƒ‡ãƒ—ãƒã‚¤ã™ã‚‹æ–¹æ³•ã«ã¤ã„ã¦è¿°ã¹ã¾ã™ã€‚ gcloudを使用ã™ã‚‹ã®ã§ã€ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã§ãã¦ã„ãªã„æ–¹ã¯å…¬å¼ãƒ‰ã‚ュメントã«ã—ãŸãŒã£ã¦ã€ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã—ã¾ã—ょã†ã€‚ ã“ã®è¨˜äº‹ã§ä½¿ç”¨ã—ãŸã‚½ãƒ¼ã‚¹ã‚³ãƒ¼ãƒ‰ã¯ä»¥ä¸‹ã®GitHubã§åˆ©ç”¨ã§ãã¾ã™ã€‚
ã€Python】Streamlitã¨FastAPIã§æ¤œç´¢ã‚¢ãƒ—リをã¤ãる｜ã¯ã‚„ã¶ã•ã®æŠ€è¡“ノート
ã“ã‚“ã«ã¡ã¯ã€‚ç¾å½¹ã‚¨ãƒ³ã‚¸ãƒ‹ã‚¢ã®â€ã¯ã‚„ã¶ã•â€@Cpp_Learningã§ã™ã€‚全文検索エンジンや検索システムã«èˆˆå‘³ãŒã‚ã£ã¦å‹‰å¼·ä¸ã§ã™ã€‚ 実践を兼ããŸå‹‰å¼·ã¨ã—ã¦ã€æ¤œç´¢ã‚¢ãƒ—リを作ã£ã¦ã„ã¾ã™ã€‚ 以å‰ã¤ãã£ãŸå…¨æ–‡æ¤œç´¢ã‚¢ãƒ—リã«ã€Œå…¥åŠ›ã—ãŸæ¤œç´¢ã‚ーワードã®åŒç¾©èªžã‚’検索候補ã¨ã—ã¦è¡¨ç¤ºã™ã‚‹æ©Ÿèƒ½ã€ã‚’è¿½åŠ ã—ã¾ã—ãŸã€‚ pic.twitter.com/NcaxB9myLv — ã¯ã‚„ã¶ã•@技術ノート (@Cpp_Learning) November 7, 2021 作り方ãªã©ã®å‚™å¿˜éŒ²ã¨ã—ã¦æœ¬è¨˜äº‹ã‚’書ãã¾ã™ã€‚
Streamlitã¨FastAPIã§éžåŒæœŸæŽ¨è«–MLアプリを作る
Streamlitã¯Pythonã ã‘ã§webアプリを作るã“ã¨ãŒã§ãるツール（ライブラリ）ã§ã™ã€‚フãƒãƒ³ãƒˆã«é–¢ã™ã‚‹çŸ¥è˜ãŒã»ã¨ã‚“ã©ä¸è¦ãªãŸã‚ã€ç°¡å˜ãªãƒ€ãƒƒã‚·ãƒ¥ãƒœãƒ¼ãƒ‰ã‚„デモアプリを作るã®ã«é©ã—ã¦ã„ã¾ã™ã€‚å…¬å¼ã®ãƒšãƒ¼ã‚¸ã§ã¯æ§˜ã€…ãªã‚µãƒ³ãƒ—ルアプリãŒå…¬é–‹ã•ã‚Œã¦ã„ã¾ã™ã€‚ ã¨ã“ã‚ã§æ©Ÿæ¢°å¦ç¿’（特ã«æ·±å±¤å¦ç¿’）モデルã§ã¯ã€ä¾‹ãˆã°ç”»åƒ1æžšã‚ãŸã‚Šæ•°ç§’ã®æŽ¨è«–時間ãŒã‹ã‹ã‚‹ã“ã¨ã‚‚ã‚ã‚Šã¾ã™ã€‚Streamlitã¯æ©Ÿæ¢°å¦ç¿’ã®ãƒ‡ãƒ¢ã‚¢ãƒ—リ用途ã¨ã—ã¦ã‚‚é©ã—ã¦ã„ã‚‹ã¨æ€ã„ã¾ã™ãŒã€æŽ¨è«–ã«æ™‚é–“ãŒã‹ã‹ã‚‹å ´åˆã«ã„ã¡ã„ã¡æŽ¨è«–完了を待ã¤ã®ã¯é€€å±ˆã‹ã‚‚ã—ã‚Œã¾ã›ã‚“。ã“ã“ã§ã¯Pythonã®webフレームワークã§ã‚ã‚‹FastAPIを組ã¿åˆã‚ã›ã‚‹ã“ã¨ã§ã€æŽ¨è«–ã‚’éžåŒæœŸã§è¡Œã†ç”»åƒèªè˜ã‚¢ãƒ—リケーションを作りã¾ã™ã€‚ コードã¯ã“ã¡ã‚‰ã«é…ç½®ã—ã¾ã—ãŸã€‚ アプリ内容 Streamlitã«ã‚ˆã‚‹GUIã¯ä»¥ä¸‹ã®ã‚ˆã†ã«ãªã‚Šã¾ã™ã€‚ç”»åƒã‚’アップãƒãƒ¼ãƒ‰ã—ã€ã€ŒSubmitã€ãƒœã‚¿ãƒ³ã‚’押ã™ã“ã¨ã§ç”»åƒèªè˜
Streamlit with Google Cloud: Hello, world!
Streamlitã€ã¨ã¦ã‚‚便利ã§ã™ã‚ˆãï¼å°ã•ãªã‚¢ãƒ—リã¨ã—ã¦ã‚‚ã€ãƒ‡ãƒ¼ã‚¿å¯è¦–化ã«ã—ã¦ã‚‚。 連載を通ã—ã¦ã€Google Cloud 上㧠Streamlit を上手ã«å‹•ã‹ã™æ–¹æ³•ã‚’ã”紹介ã—ã¾ã™ã€‚ Cloud Run ã§ã® Hello, world! （本記事） Firebase èªè¨¼ã¨ã®é€£æº BigQuery ã¸ã®ã‚¯ã‚¨ãƒª GitHubã€GitLabã€Cloud Build ã§ã® CI/CD Streamlit？ãªãœ Google Cloud ã§ï¼Ÿ Streamlit ã¯ã€Œãƒ‡ãƒ¼ã‚¿åˆ†æžã‚¹ã‚¯ãƒªãƒ—トをã€æ•°åˆ†ã§ "共有ã§ãã‚‹ Web アプリ" ã«å¤‰ãˆã‚‹ã€ã¨ã„ã†ã‚ャッãƒã‚³ãƒ”ー通りã€Python ã§æ›¸ã‹ã‚ŒãŸãƒã‚¸ãƒƒã‚¯ã‚’ãã®ã¾ã¾ã€ç›´æ„Ÿçš„ã«ã€ãƒ•ãƒãƒ³ãƒˆã‚¨ãƒ³ãƒ‰ã®çµŒé¨“ãŒãªã„人ã§ã‚‚数分㧠Web アプリケーションã«ã—ã¦ã—ã¾ãˆã‚‹ã‚ˆã†ãªã¨ã¦ã‚‚優れãŸãƒ•ãƒ¬ãƒ¼ãƒ ワークã§ã™ã€‚ ã¾ãšã¯ãœã²ã€å…¬å¼ã‚µã‚¤ãƒˆã®ã‚®ãƒ£ãƒ©ãƒªãƒ¼ ã®ä¸€ä¾‹ã‚’見ã¦ã¿ã¦ãã ã•ã„
GitHub - logan-markewich/llama_index_starter_pack: This repository provides very basic flask, streamlit, and docker examples for the llama_index (fka gpt_index) package
There are two main example folders flask_react (runs three services on localhost:5601/5602/3000) sh launch_app.sh creates a simple api that loads the text from the documents folder (if any), also launches the react frontend the "/query" endpoint accepts requests that contain a "text" parameter, which is used to query the index the "/upload" endpoint is a POST endpoint that inserts an attached text
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Streamlit ホスティング基盤をã©ã®ã‚ˆã†ã«ä½œã£ãŸã‹
Streamlitã§çµåˆãƒ†ã‚¹ãƒˆå·¥æ•°ã®å‰Šæ¸›ã«æˆåŠŸã—ãŸè©±
GitHub - pottava/streamlit-on-googlecloud
GitHub - davidefiocco/streamlit-fastapi-model-serving: Simple web app example serving a PyTorch model using streamlit and FastAPI
GitHub - mafda/ml_with_fastapi_and_streamlit: Prototyping a Machine Learning Application with Streamlit, FastAPI, Hugging Face and Docker
Streamlit Community Cloud • Streamlit
My Experience Building A FastAPI + Streamlit App - Pybites
GitHub - kotarotanahashi/cvpr: search papers of cvpr 2023 by chat gpt
GitHub - hackingthemarkets/financial-news-llama-index: Financial News Analysis with Llama Index, GPT-4, and Streamlit
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