deboramachadoandrade
commited on
Commit
•
d283025
0
Parent(s):
Project RAG app for nvidia file
Browse files- .chainlit/config.toml +97 -0
- .chainlit/translations/en-US.json +155 -0
- .chainlit/translations/pt-BR.json +155 -0
- Dockerfile +11 -0
- NVIDIA_report_app.ipynb +0 -0
- README.md +13 -0
- __pycache__/app.cpython-311.pyc +0 -0
- app.py +185 -0
- chainlit.md +2 -0
- requirements.txt +14 -0
.chainlit/config.toml
ADDED
@@ -0,0 +1,97 @@
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[project]
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# Whether to enable telemetry (default: true). No personal data is collected.
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enable_telemetry = true
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# List of environment variables to be provided by each user to use the app.
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user_env = []
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# Duration (in seconds) during which the session is saved when the connection is lost
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session_timeout = 3600
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# Enable third parties caching (e.g LangChain cache)
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cache = false
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# Authorized origins
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allow_origins = ["*"]
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# Follow symlink for asset mount (see https://github.com/Chainlit/chainlit/issues/317)
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# follow_symlink = false
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[features]
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# Show the prompt playground
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prompt_playground = true
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# Process and display HTML in messages. This can be a security risk (see https://stackoverflow.com/questions/19603097/why-is-it-dangerous-to-render-user-generated-html-or-javascript)
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unsafe_allow_html = false
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# Process and display mathematical expressions. This can clash with "$" characters in messages.
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latex = false
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# Authorize users to upload files with messages
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multi_modal = true
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# Allows user to use speech to text
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[features.speech_to_text]
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enabled = false
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# See all languages here https://github.com/JamesBrill/react-speech-recognition/blob/HEAD/docs/API.md#language-string
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# language = "en-US"
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[UI]
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# Name of the app and chatbot.
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name = "Chatbot"
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# Show the readme while the thread is empty.
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show_readme_as_default = true
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# Description of the app and chatbot. This is used for HTML tags.
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# description = ""
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# Large size content are by default collapsed for a cleaner ui
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default_collapse_content = true
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# The default value for the expand messages settings.
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default_expand_messages = false
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# Hide the chain of thought details from the user in the UI.
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hide_cot = false
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# Link to your github repo. This will add a github button in the UI's header.
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# github = ""
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# Specify a CSS file that can be used to customize the user interface.
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# The CSS file can be served from the public directory or via an external link.
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# custom_css = "/public/test.css"
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# Specify a Javascript file that can be used to customize the user interface.
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# The Javascript file can be served from the public directory.
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# custom_js = "/public/test.js"
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# Specify a custom font url.
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# custom_font = "https://fonts.googleapis.com/css2?family=Inter:wght@400;500;700&display=swap"
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# Override default MUI light theme. (Check theme.ts)
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[UI.theme]
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#font_family = "Inter, sans-serif"
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[UI.theme.light]
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#background = "#FAFAFA"
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#paper = "#FFFFFF"
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[UI.theme.light.primary]
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#main = "#F80061"
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#dark = "#980039"
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#light = "#FFE7EB"
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# Override default MUI dark theme. (Check theme.ts)
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[UI.theme.dark]
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#background = "#FAFAFA"
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#paper = "#FFFFFF"
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[UI.theme.dark.primary]
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#main = "#F80061"
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#dark = "#980039"
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#light = "#FFE7EB"
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[meta]
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generated_by = "1.0.301"
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.chainlit/translations/en-US.json
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@@ -0,0 +1,155 @@
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{
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"components": {
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"atoms": {
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"buttons": {
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"userButton": {
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"menu": {
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"settings": "Settings",
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"settingsKey": "S",
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"APIKeys": "API Keys",
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"logout": "Logout"
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}
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}
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}
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},
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"molecules": {
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"newChatButton": {
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"newChat": "New Chat"
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},
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"tasklist": {
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"TaskList": {
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"title": "\ud83d\uddd2\ufe0f Task List",
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"loading": "Loading...",
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"error": "An error occured"
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}
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},
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"attachments": {
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"cancelUpload": "Cancel upload",
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"removeAttachment": "Remove attachment"
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},
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"newChatDialog": {
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"createNewChat": "Create new chat?",
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"clearChat": "This will clear the current messages and start a new chat.",
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"cancel": "Cancel",
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"confirm": "Confirm"
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},
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"settingsModal": {
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"expandMessages": "Expand Messages",
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"hideChainOfThought": "Hide Chain of Thought",
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"darkMode": "Dark Mode"
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}
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},
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"organisms": {
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"chat": {
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"history": {
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"index": {
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"lastInputs": "Last Inputs",
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"noInputs": "Such empty...",
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"loading": "Loading..."
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}
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},
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"inputBox": {
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"input": {
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"placeholder": "Type your message here..."
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},
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"speechButton": {
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"start": "Start recording",
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"stop": "Stop recording"
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},
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"SubmitButton": {
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"sendMessage": "Send message",
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"stopTask": "Stop Task"
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},
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"UploadButton": {
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"attachFiles": "Attach files"
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},
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"waterMark": {
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"text": "Built with"
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}
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},
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"Messages": {
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"index": {
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"running": "Running",
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"executedSuccessfully": "executed successfully",
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"failed": "failed",
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"feedbackUpdated": "Feedback updated",
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"updating": "Updating"
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}
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},
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"dropScreen": {
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"dropYourFilesHere": "Drop your files here"
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},
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"index": {
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"failedToUpload": "Failed to upload",
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"cancelledUploadOf": "Cancelled upload of",
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"couldNotReachServer": "Could not reach the server",
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"continuingChat": "Continuing previous chat"
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},
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"settings": {
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"settingsPanel": "Settings panel",
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"reset": "Reset",
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"cancel": "Cancel",
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"confirm": "Confirm"
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}
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},
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"threadHistory": {
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"sidebar": {
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"filters": {
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"FeedbackSelect": {
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"feedbackAll": "Feedback: All",
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"feedbackPositive": "Feedback: Positive",
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"feedbackNegative": "Feedback: Negative"
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},
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"SearchBar": {
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"search": "Search"
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}
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},
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"DeleteThreadButton": {
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"confirmMessage": "This will delete the thread as well as it's messages and elements.",
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"cancel": "Cancel",
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"confirm": "Confirm",
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"deletingChat": "Deleting chat",
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"chatDeleted": "Chat deleted"
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},
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"index": {
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"pastChats": "Past Chats"
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},
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"ThreadList": {
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"empty": "Empty..."
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},
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"TriggerButton": {
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"closeSidebar": "Close sidebar",
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"openSidebar": "Open sidebar"
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}
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},
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"Thread": {
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"backToChat": "Go back to chat",
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"chatCreatedOn": "This chat was created on"
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}
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},
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"header": {
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"chat": "Chat",
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"readme": "Readme"
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}
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}
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},
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"hooks": {
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"useLLMProviders": {
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"failedToFetchProviders": "Failed to fetch providers:"
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}
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},
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"pages": {
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"Design": {},
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"Env": {
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"savedSuccessfully": "Saved successfully",
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"requiredApiKeys": "Required API Keys",
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"requiredApiKeysInfo": "To use this app, the following API keys are required. The keys are stored on your device's local storage."
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},
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"Page": {
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"notPartOfProject": "You are not part of this project."
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},
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"ResumeButton": {
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"resumeChat": "Resume Chat"
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}
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}
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}
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.chainlit/translations/pt-BR.json
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{
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"components": {
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"atoms": {
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"buttons": {
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"userButton": {
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"menu": {
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"settings": "Configura\u00e7\u00f5es",
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"settingsKey": "S",
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"APIKeys": "Chaves de API",
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"logout": "Sair"
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}
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}
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}
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},
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"molecules": {
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"newChatButton": {
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"newChat": "Nova Conversa"
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},
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"tasklist": {
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"TaskList": {
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"title": "\ud83d\uddd2\ufe0f Lista de Tarefas",
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"loading": "Carregando...",
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"error": "Ocorreu um erro"
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}
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},
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"attachments": {
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"cancelUpload": "Cancelar envio",
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"removeAttachment": "Remover anexo"
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},
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"newChatDialog": {
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"createNewChat": "Criar novo chat?",
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"clearChat": "Isso limpar\u00e1 as mensagens atuais e iniciar\u00e1 uma nova conversa.",
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33 |
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"cancel": "Cancelar",
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34 |
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"confirm": "Confirmar"
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},
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36 |
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"settingsModal": {
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37 |
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"expandMessages": "Expandir Mensagens",
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38 |
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"hideChainOfThought": "Esconder Sequ\u00eancia de Pensamento",
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39 |
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"darkMode": "Modo Escuro"
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40 |
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}
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41 |
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},
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42 |
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"organisms": {
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43 |
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"chat": {
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44 |
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"history": {
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"index": {
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46 |
+
"lastInputs": "\u00daltimas Entradas",
|
47 |
+
"noInputs": "Vazio...",
|
48 |
+
"loading": "Carregando..."
|
49 |
+
}
|
50 |
+
},
|
51 |
+
"inputBox": {
|
52 |
+
"input": {
|
53 |
+
"placeholder": "Digite sua mensagem aqui..."
|
54 |
+
},
|
55 |
+
"speechButton": {
|
56 |
+
"start": "Iniciar grava\u00e7\u00e3o",
|
57 |
+
"stop": "Parar grava\u00e7\u00e3o"
|
58 |
+
},
|
59 |
+
"SubmitButton": {
|
60 |
+
"sendMessage": "Enviar mensagem",
|
61 |
+
"stopTask": "Parar Tarefa"
|
62 |
+
},
|
63 |
+
"UploadButton": {
|
64 |
+
"attachFiles": "Anexar arquivos"
|
65 |
+
},
|
66 |
+
"waterMark": {
|
67 |
+
"text": "Constru\u00eddo com"
|
68 |
+
}
|
69 |
+
},
|
70 |
+
"Messages": {
|
71 |
+
"index": {
|
72 |
+
"running": "Executando",
|
73 |
+
"executedSuccessfully": "executado com sucesso",
|
74 |
+
"failed": "falhou",
|
75 |
+
"feedbackUpdated": "Feedback atualizado",
|
76 |
+
"updating": "Atualizando"
|
77 |
+
}
|
78 |
+
},
|
79 |
+
"dropScreen": {
|
80 |
+
"dropYourFilesHere": "Solte seus arquivos aqui"
|
81 |
+
},
|
82 |
+
"index": {
|
83 |
+
"failedToUpload": "Falha ao enviar",
|
84 |
+
"cancelledUploadOf": "Envio cancelado de",
|
85 |
+
"couldNotReachServer": "N\u00e3o foi poss\u00edvel conectar ao servidor",
|
86 |
+
"continuingChat": "Continuando o chat anterior"
|
87 |
+
},
|
88 |
+
"settings": {
|
89 |
+
"settingsPanel": "Painel de Configura\u00e7\u00f5es",
|
90 |
+
"reset": "Redefinir",
|
91 |
+
"cancel": "Cancelar",
|
92 |
+
"confirm": "Confirmar"
|
93 |
+
}
|
94 |
+
},
|
95 |
+
"threadHistory": {
|
96 |
+
"sidebar": {
|
97 |
+
"filters": {
|
98 |
+
"FeedbackSelect": {
|
99 |
+
"feedbackAll": "Feedback: Todos",
|
100 |
+
"feedbackPositive": "Feedback: Positivo",
|
101 |
+
"feedbackNegative": "Feedback: Negativo"
|
102 |
+
},
|
103 |
+
"SearchBar": {
|
104 |
+
"search": "Buscar"
|
105 |
+
}
|
106 |
+
},
|
107 |
+
"DeleteThreadButton": {
|
108 |
+
"confirmMessage": "Isso deletar\u00e1 a conversa, assim como suas mensagens e elementos.",
|
109 |
+
"cancel": "Cancelar",
|
110 |
+
"confirm": "Confirmar",
|
111 |
+
"deletingChat": "Deletando conversa",
|
112 |
+
"chatDeleted": "Conversa deletada"
|
113 |
+
},
|
114 |
+
"index": {
|
115 |
+
"pastChats": "Conversas Anteriores"
|
116 |
+
},
|
117 |
+
"ThreadList": {
|
118 |
+
"empty": "Vazio..."
|
119 |
+
},
|
120 |
+
"TriggerButton": {
|
121 |
+
"closeSidebar": "Fechar barra lateral",
|
122 |
+
"openSidebar": "Abrir barra lateral"
|
123 |
+
}
|
124 |
+
},
|
125 |
+
"Thread": {
|
126 |
+
"backToChat": "Voltar para a conversa",
|
127 |
+
"chatCreatedOn": "Esta conversa foi criada em"
|
128 |
+
}
|
129 |
+
},
|
130 |
+
"header": {
|
131 |
+
"chat": "Conversa",
|
132 |
+
"readme": "Leia-me"
|
133 |
+
}
|
134 |
+
},
|
135 |
+
"hooks": {
|
136 |
+
"useLLMProviders": {
|
137 |
+
"failedToFetchProviders": "Falha ao buscar provedores:"
|
138 |
+
}
|
139 |
+
},
|
140 |
+
"pages": {
|
141 |
+
"Design": {},
|
142 |
+
"Env": {
|
143 |
+
"savedSuccessfully": "Salvo com sucesso",
|
144 |
+
"requiredApiKeys": "Chaves de API necess\u00e1rias",
|
145 |
+
"requiredApiKeysInfo": "Para usar este aplicativo, as seguintes chaves de API s\u00e3o necess\u00e1rias. As chaves s\u00e3o armazenadas localmente em seu dispositivo."
|
146 |
+
},
|
147 |
+
"Page": {
|
148 |
+
"notPartOfProject": "Voc\u00ea n\u00e3o faz parte deste projeto."
|
149 |
+
},
|
150 |
+
"ResumeButton": {
|
151 |
+
"resumeChat": "Continuar Conversa"
|
152 |
+
}
|
153 |
+
}
|
154 |
+
}
|
155 |
+
}
|
Dockerfile
ADDED
@@ -0,0 +1,11 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
FROM python:3.9
|
2 |
+
RUN useradd -m -u 1000 user
|
3 |
+
USER user
|
4 |
+
ENV HOME=/home/user \
|
5 |
+
PATH=/home/user/.local/bin:$PATH
|
6 |
+
WORKDIR $HOME/Mid-term_copy
|
7 |
+
COPY --chown=user . $HOME/Mid-term_copy
|
8 |
+
COPY ./requirements.txt ~/Mid_term_copy/requirements.txt
|
9 |
+
RUN pip install -r requirements.txt
|
10 |
+
COPY . .
|
11 |
+
CMD ["chainlit", "run", "app.py", "--port", "7860"]
|
NVIDIA_report_app.ipynb
ADDED
The diff for this file is too large to render.
See raw diff
|
|
README.md
ADDED
@@ -0,0 +1,13 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
title: RAG NVIDIA Report
|
3 |
+
emoji: 🐨
|
4 |
+
colorFrom: pink
|
5 |
+
colorTo: indigo
|
6 |
+
sdk: streamlit
|
7 |
+
sdk_version: 1.32.2
|
8 |
+
app_file: app.py
|
9 |
+
pinned: false
|
10 |
+
license: openrail
|
11 |
+
---
|
12 |
+
|
13 |
+
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
|
__pycache__/app.cpython-311.pyc
ADDED
Binary file (5.56 kB). View file
|
|
app.py
ADDED
@@ -0,0 +1,185 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
#NVIDIA_report_app
|
2 |
+
|
3 |
+
#In the following notebook we'll build RAG pipelines that will allow us to interactively retrieve information from the report "NVIDIA 10-k Filings".
|
4 |
+
#We will further use Ragas to evaluate component-wise metrics, as well as end-to-end metrics about the performance of our RAG pipelines.
|
5 |
+
|
6 |
+
import os
|
7 |
+
import openai
|
8 |
+
from openai import AsyncOpenAI # importing openai for API usage
|
9 |
+
import chainlit as cl # importing chainlit for our app
|
10 |
+
#from chainlit.prompt import Prompt, PromptMessage # importing prompt tools
|
11 |
+
from chainlit.prompt import Prompt, PromptMessage
|
12 |
+
from chainlit.playground.providers import ChatOpenAI # importing ChatOpenAI tools
|
13 |
+
|
14 |
+
|
15 |
+
|
16 |
+
from getpass import getpass
|
17 |
+
|
18 |
+
openai.api_key = getpass("Please provide your OpenAI Key: ")
|
19 |
+
os.environ["OPENAI_API_KEY"] = openai.api_key
|
20 |
+
|
21 |
+
|
22 |
+
|
23 |
+
#Loading data
|
24 |
+
from langchain_community.document_loaders import PyMuPDFLoader
|
25 |
+
|
26 |
+
loader = PyMuPDFLoader(
|
27 |
+
"NVIDIA_report.pdf",
|
28 |
+
)
|
29 |
+
|
30 |
+
documents = loader.load()
|
31 |
+
|
32 |
+
#Splitting data
|
33 |
+
from langchain.text_splitter import RecursiveCharacterTextSplitter
|
34 |
+
|
35 |
+
text_splitter = RecursiveCharacterTextSplitter(
|
36 |
+
chunk_size = 1000,
|
37 |
+
chunk_overlap = 100
|
38 |
+
)
|
39 |
+
|
40 |
+
documents = text_splitter.split_documents(documents)
|
41 |
+
|
42 |
+
#Loading OpenAI embeddings model:
|
43 |
+
from langchain_openai import OpenAIEmbeddings
|
44 |
+
|
45 |
+
embeddings = OpenAIEmbeddings(
|
46 |
+
model="text-embedding-3-small"
|
47 |
+
)
|
48 |
+
|
49 |
+
#Creating a FAISS VectorStore:
|
50 |
+
from langchain_community.vectorstores import FAISS
|
51 |
+
|
52 |
+
vector_store = FAISS.from_documents(documents, embeddings)
|
53 |
+
|
54 |
+
#Creating a retriever:
|
55 |
+
retriever = vector_store.as_retriever()
|
56 |
+
|
57 |
+
#Creating a prompt template:
|
58 |
+
from langchain.prompts import ChatPromptTemplate
|
59 |
+
|
60 |
+
template = """Answer the question based only on the following context. If you cannot answer the question with the context, please respond with 'I don't know':
|
61 |
+
|
62 |
+
Context:
|
63 |
+
{context}
|
64 |
+
|
65 |
+
Question:
|
66 |
+
{question}
|
67 |
+
"""
|
68 |
+
|
69 |
+
prompt = ChatPromptTemplate.from_template(template)
|
70 |
+
|
71 |
+
#Creating a RAG chain:
|
72 |
+
from operator import itemgetter
|
73 |
+
|
74 |
+
from langchain_openai import ChatOpenAI
|
75 |
+
from langchain_core.output_parsers import StrOutputParser
|
76 |
+
from langchain_core.runnables import RunnablePassthrough
|
77 |
+
|
78 |
+
primary_qa_llm = ChatOpenAI(model_name="gpt-3.5-turbo", temperature=0)
|
79 |
+
|
80 |
+
retrieval_augmented_qa_chain = (
|
81 |
+
# INVOKE CHAIN WITH: {"question" : "<<SOME USER QUESTION>>"}
|
82 |
+
# "question" : populated by getting the value of the "question" key
|
83 |
+
# "context" : populated by getting the value of the "question" key and chaining it into the base_retriever
|
84 |
+
{"context": itemgetter("question") | retriever, "question": itemgetter("question")}
|
85 |
+
# "context" : is assigned to a RunnablePassthrough object (will not be called or considered in the next step)
|
86 |
+
# by getting the value of the "context" key from the previous step
|
87 |
+
| RunnablePassthrough.assign(context=itemgetter("context"))
|
88 |
+
# "response" : the "context" and "question" values are used to format our prompt object and then piped
|
89 |
+
# into the LLM and stored in a key called "response"
|
90 |
+
# "context" : populated by getting the value of the "context" key from the previous step
|
91 |
+
| {"response": prompt | primary_qa_llm, "context": itemgetter("context")}
|
92 |
+
)
|
93 |
+
|
94 |
+
#We will be using the advanced Multiquery retriever provided by Langchain:
|
95 |
+
from langchain.retrievers import MultiQueryRetriever
|
96 |
+
advanced_retriever = MultiQueryRetriever.from_llm(retriever=retriever, llm=primary_qa_llm)
|
97 |
+
|
98 |
+
#We create a chain to stuff our documents into our prompt:
|
99 |
+
from langchain.chains.combine_documents import create_stuff_documents_chain
|
100 |
+
from langchain import hub
|
101 |
+
|
102 |
+
retrieval_qa_prompt = hub.pull("langchain-ai/retrieval-qa-chat")
|
103 |
+
document_chain = create_stuff_documents_chain(primary_qa_llm, retrieval_qa_prompt)
|
104 |
+
|
105 |
+
#Create the new retrieval chain with advanced retriever:
|
106 |
+
from langchain.chains import create_retrieval_chain
|
107 |
+
retrieval_chain = create_retrieval_chain(advanced_retriever, document_chain)
|
108 |
+
|
109 |
+
#And we create our chatbot functions:
|
110 |
+
user_template = """{input}
|
111 |
+
Think through your response step by step.
|
112 |
+
"""
|
113 |
+
@cl.on_chat_start # marks a function that will be executed at the start of a user session
|
114 |
+
async def start_chat():
|
115 |
+
settings = {
|
116 |
+
"model": "gpt-3.5-turbo",
|
117 |
+
"temperature": 1.0,
|
118 |
+
"max_tokens": 500,
|
119 |
+
"top_p": 1,
|
120 |
+
"frequency_penalty": 0,
|
121 |
+
"presence_penalty": 0,
|
122 |
+
}
|
123 |
+
|
124 |
+
cl.user_session.set("settings", settings)
|
125 |
+
|
126 |
+
|
127 |
+
@cl.on_message # marks a function that should be run each time the chatbot receives a message from a user
|
128 |
+
async def main(message: cl.Message):
|
129 |
+
settings = cl.user_session.get("settings")
|
130 |
+
|
131 |
+
client = AsyncOpenAI(
|
132 |
+
api_key=os.environ.get("OPENAI_API_KEY"),
|
133 |
+
)
|
134 |
+
print(message.content)
|
135 |
+
|
136 |
+
prompt = Prompt(
|
137 |
+
#provider=ChatOpenAI.id,
|
138 |
+
provider="ChatOpenAI",
|
139 |
+
messages=[
|
140 |
+
PromptMessage(
|
141 |
+
role="system",
|
142 |
+
template=template,
|
143 |
+
formatted=template,
|
144 |
+
),
|
145 |
+
PromptMessage(
|
146 |
+
role="user",
|
147 |
+
template=user_template,
|
148 |
+
formatted=user_template.format(input=message.content),
|
149 |
+
),
|
150 |
+
],
|
151 |
+
inputs={"input": message.content},
|
152 |
+
settings=settings,
|
153 |
+
)
|
154 |
+
|
155 |
+
print([m.to_openai() for m in prompt.messages])
|
156 |
+
|
157 |
+
msg = cl.Message(content="")
|
158 |
+
|
159 |
+
# Call OpenAI
|
160 |
+
#async for stream_resp in await client.chat.completions.create(
|
161 |
+
# messages=[m.to_openai() for m in prompt.messages], stream=True, **settings
|
162 |
+
#):
|
163 |
+
|
164 |
+
# token = stream_resp.choices[0].delta.content
|
165 |
+
# if not token:
|
166 |
+
# token = ""
|
167 |
+
# await msg.stream_token(token)
|
168 |
+
|
169 |
+
# Update the prompt object with the completion
|
170 |
+
result = retrieval_chain.invoke({"input":message.content})
|
171 |
+
msg.content = result["answer"]
|
172 |
+
#print(temp)
|
173 |
+
#prompt.completion = msg.content
|
174 |
+
#prompt.completion = temp
|
175 |
+
#msg.content = temp
|
176 |
+
|
177 |
+
|
178 |
+
#prompt.completion = completion
|
179 |
+
msg.prompt = prompt
|
180 |
+
|
181 |
+
# Send and close the message stream
|
182 |
+
await msg.send()
|
183 |
+
|
184 |
+
|
185 |
+
|
chainlit.md
ADDED
@@ -0,0 +1,2 @@
|
|
|
|
|
|
|
1 |
+
# Talk to NVIDIA 10-k Filings report
|
2 |
+
|
requirements.txt
ADDED
@@ -0,0 +1,14 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chainlit
|
2 |
+
cohere==4.37
|
3 |
+
openai
|
4 |
+
tiktoken
|
5 |
+
python-dotenv==1.0.0
|
6 |
+
langchain
|
7 |
+
langchain-openai
|
8 |
+
langchain_core
|
9 |
+
langchain-community
|
10 |
+
langchainhub
|
11 |
+
ragas
|
12 |
+
faiss_cpu
|
13 |
+
pymupdf
|
14 |
+
pandas
|