initial working commit

.gitignore

@@ -0,0 +1,13 @@
+**/vectorstores/*
+**/private/students.json
+.ragatouille/*
+*/__pycache__/*
+.chainlit/translations/
+code/.chainlit/translations/
+storage/logs/*
+vectorstores/*
+**/apps/*/storage/logs/*
+**/apps/*/private/*
+*.log
+**/.files/*
+.env

README.md

@@ -1 +1,7 @@
 ## App Templates
+
+```bash
+pip install edubotics-core
+```
+
+P.S. - Do remmber to setup your .env file

apps/ai_tutor/.chainlit/config.toml

@@ -0,0 +1,120 @@
+[project]
+# Whether to enable telemetry (default: true). No personal data is collected.
+enable_telemetry = true
+
+
+# List of environment variables to be provided by each user to use the app.
+user_env = []
+
+# Duration (in seconds) during which the session is saved when the connection is lost
+session_timeout = 3600
+
+# Enable third parties caching (e.g LangChain cache)
+cache = false
+
+# Authorized origins
+allow_origins = ["*"]
+
+# Follow symlink for asset mount (see https://github.com/Chainlit/chainlit/issues/317)
+# follow_symlink = false
+
+[features]
+# 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)
+unsafe_allow_html = true
+
+# Process and display mathematical expressions. This can clash with "$" characters in messages.
+latex = true
+
+# Automatically tag threads with the current chat profile (if a chat profile is used)
+auto_tag_thread = true
+
+# Authorize users to spontaneously upload files with messages
+[features.spontaneous_file_upload]
+    enabled = true
+    accept = ["*/*"]
+    max_files = 20
+    max_size_mb = 500
+
+[features.audio]
+    # Threshold for audio recording
+    min_decibels = -45
+    # Delay for the user to start speaking in MS
+    initial_silence_timeout = 3000
+    # Delay for the user to continue speaking in MS. If the user stops speaking for this duration, the recording will stop.
+    silence_timeout = 1500
+    # Above this duration (MS), the recording will forcefully stop.
+    max_duration = 15000
+    # Duration of the audio chunks in MS
+    chunk_duration = 1000
+    # Sample rate of the audio
+    sample_rate = 44100
+
+edit_message = true
+
+[UI]
+# Name of the assistant.
+name = "AI Tutor"
+
+# Description of the assistant. This is used for HTML tags.
+# description = ""
+
+# Large size content are by default collapsed for a cleaner ui
+default_collapse_content = true
+
+# Chain of Thought (CoT) display mode. Can be "hidden", "tool_call" or "full".
+cot = "hidden"
+
+# Link to your github repo. This will add a github button in the UI's header.
+github = "https://github.com/edubotics-ai/edubot-core"
+
+# Specify a CSS file that can be used to customize the user interface.
+# The CSS file can be served from the public directory or via an external link.
+custom_css = "/public/files/test.css"
+
+# Specify a Javascript file that can be used to customize the user interface.
+# The Javascript file can be served from the public directory.
+# custom_js = "/public/test.js"
+
+# Specify a custom font url.
+# custom_font = "https://fonts.googleapis.com/css2?family=Inter:wght@400;500;700&display=swap"
+
+# Specify a custom meta image url.
+custom_meta_image_url = "https://upload.wikimedia.org/wikipedia/commons/thumb/f/f5/Boston_University_seal.svg/1200px-Boston_University_seal.svg.png"
+
+# Specify a custom build directory for the frontend.
+# This can be used to customize the frontend code.
+# Be careful: If this is a relative path, it should not start with a slash.
+# custom_build = "./public/build"
+
+[UI.theme]
+    default = "light"
+    #layout = "wide"
+    #font_family = "Inter, sans-serif"
+# Override default MUI light theme. (Check theme.ts)
+[UI.theme.light]
+    #background = "#FAFAFA"
+    #paper = "#FFFFFF"
+
+    [UI.theme.light.primary]
+        #main = "#F80061"
+        #dark = "#980039"
+        #light = "#FFE7EB"
+    [UI.theme.light.text]
+        #primary = "#212121"
+        #secondary = "#616161"
+
+# Override default MUI dark theme. (Check theme.ts)
+[UI.theme.dark]
+    #background = "#FAFAFA"
+    #paper = "#FFFFFF"
+
+    [UI.theme.dark.primary]
+        #main = "#F80061"
+        #dark = "#980039"
+        #light = "#FFE7EB"
+    [UI.theme.dark.text]
+        #primary = "#EEEEEE"
+        #secondary = "#BDBDBD"
+
+[meta]
+generated_by = "1.1.402"

apps/ai_tutor/.chainlit/translations/en-US.json

@@ -0,0 +1,229 @@
+{
+    "components": {
+        "atoms": {
+            "buttons": {
+                "userButton": {
+                    "menu": {
+                        "settings": "Settings",
+                        "settingsKey": "S",
+                        "APIKeys": "API Keys",
+                        "logout": "Logout"
+                    }
+                }
+            }
+        },
+        "molecules": {
+            "newChatButton": {
+                "newChat": "New Chat"
+            },
+            "tasklist": {
+                "TaskList": {
+                    "title": "\ud83d\uddd2\ufe0f Task List",
+                    "loading": "Loading...",
+                    "error": "An error occurred"
+                }
+            },
+            "attachments": {
+                "cancelUpload": "Cancel upload",
+                "removeAttachment": "Remove attachment"
+            },
+            "newChatDialog": {
+                "createNewChat": "Create new chat?",
+                "clearChat": "This will clear the current messages and start a new chat.",
+                "cancel": "Cancel",
+                "confirm": "Confirm"
+            },
+            "settingsModal": {
+                "settings": "Settings",
+                "expandMessages": "Expand Messages",
+                "hideChainOfThought": "Hide Chain of Thought",
+                "darkMode": "Dark Mode"
+            },
+            "detailsButton": {
+                "using": "Using",
+                "used": "Used"
+            },
+            "auth": {
+                "authLogin": {
+                    "title": "Login to access the app.",
+                    "form": {
+                        "email": "Email address",
+                        "password": "Password",
+                        "noAccount": "Don't have an account?",
+                        "alreadyHaveAccount": "Already have an account?",
+                        "signup": "Sign Up",
+                        "signin": "Sign In",
+                        "or": "OR",
+                        "continue": "Continue",
+                        "forgotPassword": "Forgot password?",
+                        "passwordMustContain": "Your password must contain:",
+                        "emailRequired": "email is a required field",
+                        "passwordRequired": "password is a required field"
+                    },
+                    "error": {
+                        "default": "Unable to sign in.",
+                        "signin": "Try signing in with a different account.",
+                        "oauthsignin": "Try signing in with a different account.",
+                        "redirect_uri_mismatch": "The redirect URI is not matching the oauth app configuration.",
+                        "oauthcallbackerror": "Try signing in with a different account.",
+                        "oauthcreateaccount": "Try signing in with a different account.",
+                        "emailcreateaccount": "Try signing in with a different account.",
+                        "callback": "Try signing in with a different account.",
+                        "oauthaccountnotlinked": "To confirm your identity, sign in with the same account you used originally.",
+                        "emailsignin": "The e-mail could not be sent.",
+                        "emailverify": "Please verify your email, a new email has been sent.",
+                        "credentialssignin": "Sign in failed. Check the details you provided are correct.",
+                        "sessionrequired": "Please sign in to access this page."
+                    }
+                },
+                "authVerifyEmail": {
+                    "almostThere": "You're almost there! We've sent an email to ",
+                    "verifyEmailLink": "Please click on the link in that email to complete your signup.",
+                    "didNotReceive": "Can't find the email?",
+                    "resendEmail": "Resend email",
+                    "goBack": "Go Back",
+                    "emailSent": "Email sent successfully.",
+                    "verifyEmail": "Verify your email address"
+                },
+                "providerButton": {
+                    "continue": "Continue with {{provider}}",
+                    "signup": "Sign up with {{provider}}"
+                },
+                "authResetPassword": {
+                    "newPasswordRequired": "New password is a required field",
+                    "passwordsMustMatch": "Passwords must match",
+                    "confirmPasswordRequired": "Confirm password is a required field",
+                    "newPassword": "New password",
+                    "confirmPassword": "Confirm password",
+                    "resetPassword": "Reset Password"
+                },
+                "authForgotPassword": {
+                    "email": "Email address",
+                    "emailRequired": "email is a required field",
+                    "emailSent": "Please check the email address {{email}} for instructions to reset your password.",
+                    "enterEmail": "Enter your email address and we will send you instructions to reset your password.",
+                    "resendEmail": "Resend email",
+                    "continue": "Continue",
+                    "goBack": "Go Back"
+                }
+            }
+        },
+        "organisms": {
+            "chat": {
+                "history": {
+                    "index": {
+                        "showHistory": "Show history",
+                        "lastInputs": "Last Inputs",
+                        "noInputs": "Such empty...",
+                        "loading": "Loading..."
+                    }
+                },
+                "inputBox": {
+                    "input": {
+                        "placeholder": "Type your message here..."
+                    },
+                    "speechButton": {
+                        "start": "Start recording",
+                        "stop": "Stop recording"
+                    },
+                    "SubmitButton": {
+                        "sendMessage": "Send message",
+                        "stopTask": "Stop Task"
+                    },
+                    "UploadButton": {
+                        "attachFiles": "Attach files"
+                    },
+                    "waterMark": {
+                        "text": "Built with"
+                    }
+                },
+                "Messages": {
+                    "index": {
+                        "running": "Running",
+                        "executedSuccessfully": "executed successfully",
+                        "failed": "failed",
+                        "feedbackUpdated": "Feedback updated",
+                        "updating": "Updating"
+                    }
+                },
+                "dropScreen": {
+                    "dropYourFilesHere": "Drop your files here"
+                },
+                "index": {
+                    "failedToUpload": "Failed to upload",
+                    "cancelledUploadOf": "Cancelled upload of",
+                    "couldNotReachServer": "Could not reach the server",
+                    "continuingChat": "Continuing previous chat"
+                },
+                "settings": {
+                    "settingsPanel": "Settings panel",
+                    "reset": "Reset",
+                    "cancel": "Cancel",
+                    "confirm": "Confirm"
+                }
+            },
+            "threadHistory": {
+                "sidebar": {
+                    "filters": {
+                        "FeedbackSelect": {
+                            "feedbackAll": "Feedback: All",
+                            "feedbackPositive": "Feedback: Positive",
+                            "feedbackNegative": "Feedback: Negative"
+                        },
+                        "SearchBar": {
+                            "search": "Search"
+                        }
+                    },
+                    "DeleteThreadButton": {
+                        "confirmMessage": "This will delete the thread as well as it's messages and elements.",
+                        "cancel": "Cancel",
+                        "confirm": "Confirm",
+                        "deletingChat": "Deleting chat",
+                        "chatDeleted": "Chat deleted"
+                    },
+                    "index": {
+                        "pastChats": "Past Chats"
+                    },
+                    "ThreadList": {
+                        "empty": "Empty...",
+                        "today": "Today",
+                        "yesterday": "Yesterday",
+                        "previous7days": "Previous 7 days",
+                        "previous30days": "Previous 30 days"
+                    },
+                    "TriggerButton": {
+                        "closeSidebar": "Close sidebar",
+                        "openSidebar": "Open sidebar"
+                    }
+                },
+                "Thread": {
+                    "backToChat": "Go back to chat",
+                    "chatCreatedOn": "This chat was created on"
+                }
+            },
+            "header": {
+                "chat": "Chat",
+                "readme": "Readme"
+            }
+        }
+    },
+    "hooks": {
+        "useLLMProviders": {
+            "failedToFetchProviders": "Failed to fetch providers:"
+        }
+    },
+    "pages": {
+        "Design": {},
+        "Env": {
+            "savedSuccessfully": "Saved successfully",
+            "requiredApiKeys": "Required API Keys",
+            "requiredApiKeysInfo": "To use this app, the following API keys are required. The keys are stored on your device's local storage."
+        },
+        "Page": {
+            "notPartOfProject": "You are not part of this project."
+        },
+        "ResumeButton": {
+            "resumeChat": "Resume Chat"
+        }
+    }
+}

apps/ai_tutor/.chainlit/translations/zh-CN.json

@@ -0,0 +1,229 @@
+{
+    "components": {
+        "atoms": {
+            "buttons": {
+                "userButton": {
+                    "menu": {
+                        "settings": "\u8bbe\u7f6e",
+                        "settingsKey": "S",
+                        "APIKeys": "API \u5bc6\u94a5",
+                        "logout": "\u767b\u51fa"
+                    }
+                }
+            }
+        },
+        "molecules": {
+            "newChatButton": {
+                "newChat": "\u65b0\u5efa\u5bf9\u8bdd"
+            },
+            "tasklist": {
+                "TaskList": {
+                    "title": "\ud83d\uddd2\ufe0f \u4efb\u52a1\u5217\u8868",
+                    "loading": "\u52a0\u8f7d\u4e2d...",
+                    "error": "\u53d1\u751f\u9519\u8bef"
+                }
+            },
+            "attachments": {
+                "cancelUpload": "\u53d6\u6d88\u4e0a\u4f20",
+                "removeAttachment": "\u79fb\u9664\u9644\u4ef6"
+            },
+            "newChatDialog": {
+                "createNewChat": "\u521b\u5efa\u65b0\u5bf9\u8bdd\uff1f",
+                "clearChat": "\u8fd9\u5c06\u6e05\u9664\u5f53\u524d\u6d88\u606f\u5e76\u5f00\u59cb\u65b0\u7684\u5bf9\u8bdd\u3002",
+                "cancel": "\u53d6\u6d88",
+                "confirm": "\u786e\u8ba4"
+            },
+            "settingsModal": {
+                "settings": "\u8bbe\u7f6e",
+                "expandMessages": "\u5c55\u5f00\u6d88\u606f",
+                "hideChainOfThought": "\u9690\u85cf\u601d\u8003\u94fe",
+                "darkMode": "\u6697\u8272\u6a21\u5f0f"
+            },
+            "detailsButton": {
+                "using": "\u4f7f\u7528",
+                "used": "\u5df2\u7528"
+            },
+            "auth": {
+                "authLogin": {
+                    "title": "\u767b\u5f55\u4ee5\u8bbf\u95ee\u5e94\u7528\u3002",
+                    "form": {
+                        "email": "\u7535\u5b50\u90ae\u7bb1\u5730\u5740",
+                        "password": "\u5bc6\u7801",
+                        "noAccount": "\u6ca1\u6709\u8d26\u6237\uff1f",
+                        "alreadyHaveAccount": "\u5df2\u6709\u8d26\u6237\uff1f",
+                        "signup": "\u6ce8\u518c",
+                        "signin": "\u767b\u5f55",
+                        "or": "\u6216\u8005",
+                        "continue": "\u7ee7\u7eed",
+                        "forgotPassword": "\u5fd8\u8bb0\u5bc6\u7801\uff1f",
+                        "passwordMustContain": "\u60a8\u7684\u5bc6\u7801\u5fc5\u987b\u5305\u542b\uff1a",
+                        "emailRequired": "\u7535\u5b50\u90ae\u7bb1\u662f\u5fc5\u586b\u9879",
+                        "passwordRequired": "\u5bc6\u7801\u662f\u5fc5\u586b\u9879"
+                    },
+                    "error": {
+                        "default": "\u65e0\u6cd5\u767b\u5f55\u3002",
+                        "signin": "\u5c1d\u8bd5\u4f7f\u7528\u4e0d\u540c\u7684\u8d26\u6237\u767b\u5f55\u3002",
+                        "oauthsignin": "\u5c1d\u8bd5\u4f7f\u7528\u4e0d\u540c\u7684\u8d26\u6237\u767b\u5f55\u3002",
+                        "redirect_uri_mismatch": "\u91cd\u5b9a\u5411URI\u4e0eOAuth\u5e94\u7528\u914d\u7f6e\u4e0d\u5339\u914d\u3002",
+                        "oauthcallbackerror": "\u5c1d\u8bd5\u4f7f\u7528\u4e0d\u540c\u7684\u8d26\u6237\u767b\u5f55\u3002",
+                        "oauthcreateaccount": "\u5c1d\u8bd5\u4f7f\u7528\u4e0d\u540c\u7684\u8d26\u6237\u767b\u5f55\u3002",
+                        "emailcreateaccount": "\u5c1d\u8bd5\u4f7f\u7528\u4e0d\u540c\u7684\u8d26\u6237\u767b\u5f55\u3002",
+                        "callback": "\u5c1d\u8bd5\u4f7f\u7528\u4e0d\u540c\u7684\u8d26\u6237\u767b\u5f55\u3002",
+                        "oauthaccountnotlinked": "\u4e3a\u4e86\u9a8c\u8bc1\u60a8\u7684\u8eab\u4efd\uff0c\u8bf7\u4f7f\u7528\u6700\u521d\u4f7f\u7528\u7684\u540c\u4e00\u8d26\u6237\u767b\u5f55\u3002",
+                        "emailsignin": "\u65e0\u6cd5\u53d1\u9001\u90ae\u4ef6\u3002",
+                        "emailverify": "\u8bf7\u9a8c\u8bc1\u60a8\u7684\u7535\u5b50\u90ae\u4ef6\uff0c\u5df2\u53d1\u9001\u4e00\u5c01\u65b0\u90ae\u4ef6\u3002",
+                        "credentialssignin": "\u767b\u5f55\u5931\u8d25\u3002\u8bf7\u68c0\u67e5\u60a8\u63d0\u4f9b\u7684\u8be6\u7ec6\u4fe1\u606f\u662f\u5426\u6b63\u786e\u3002",
+                        "sessionrequired": "\u8bf7\u767b\u5f55\u4ee5\u8bbf\u95ee\u6b64\u9875\u9762\u3002"
+                    }
+                },
+                "authVerifyEmail": {
+                    "almostThere": "\u60a8\u5feb\u6210\u529f\u4e86\uff01\u6211\u4eec\u5df2\u5411 ",
+                    "verifyEmailLink": "\u8bf7\u5355\u51fb\u8be5\u90ae\u4ef6\u4e2d\u7684\u94fe\u63a5\u4ee5\u5b8c\u6210\u6ce8\u518c\u3002",
+                    "didNotReceive": "\u6ca1\u627e\u5230\u90ae\u4ef6\uff1f",
+                    "resendEmail": "\u91cd\u65b0\u53d1\u9001\u90ae\u4ef6",
+                    "goBack": "\u8fd4\u56de",
+                    "emailSent": "\u90ae\u4ef6\u5df2\u6210\u529f\u53d1\u9001\u3002",
+                    "verifyEmail": "\u9a8c\u8bc1\u60a8\u7684\u7535\u5b50\u90ae\u4ef6\u5730\u5740"
+                },
+                "providerButton": {
+                    "continue": "\u4f7f\u7528{{provider}}\u7ee7\u7eed",
+                    "signup": "\u4f7f\u7528{{provider}}\u6ce8\u518c"
+                },
+                "authResetPassword": {
+                    "newPasswordRequired": "\u65b0\u5bc6\u7801\u662f\u5fc5\u586b\u9879",
+                    "passwordsMustMatch": "\u5bc6\u7801\u5fc5\u987b\u4e00\u81f4",
+                    "confirmPasswordRequired": "\u786e\u8ba4\u5bc6\u7801\u662f\u5fc5\u586b\u9879",
+                    "newPassword": "\u65b0\u5bc6\u7801",
+                    "confirmPassword": "\u786e\u8ba4\u5bc6\u7801",
+                    "resetPassword": "\u91cd\u7f6e\u5bc6\u7801"
+                },
+                "authForgotPassword": {
+                    "email": "\u7535\u5b50\u90ae\u7bb1\u5730\u5740",
+                    "emailRequired": "\u7535\u5b50\u90ae\u7bb1\u662f\u5fc5\u586b\u9879",
+                    "emailSent": "\u8bf7\u68c0\u67e5\u7535\u5b50\u90ae\u7bb1{{email}}\u4ee5\u83b7\u53d6\u91cd\u7f6e\u5bc6\u7801\u7684\u6307\u793a\u3002",
+                    "enterEmail": "\u8bf7\u8f93\u5165\u60a8\u7684\u7535\u5b50\u90ae\u7bb1\u5730\u5740\uff0c\u6211\u4eec\u5c06\u53d1\u9001\u91cd\u7f6e\u5bc6\u7801\u7684\u6307\u793a\u3002",
+                    "resendEmail": "\u91cd\u65b0\u53d1\u9001\u90ae\u4ef6",
+                    "continue": "\u7ee7\u7eed",
+                    "goBack": "\u8fd4\u56de"
+                }
+            }
+        },
+        "organisms": {
+            "chat": {
+                "history": {
+                    "index": {
+                        "showHistory": "\u663e\u793a\u5386\u53f2",
+                        "lastInputs": "\u6700\u540e\u8f93\u5165",
+                        "noInputs": "\u5982\u6b64\u7a7a\u65f7...",
+                        "loading": "\u52a0\u8f7d\u4e2d..."
+                    }
+                },
+                "inputBox": {
+                    "input": {
+                        "placeholder": "\u5728\u8fd9\u91cc\u8f93\u5165\u60a8\u7684\u6d88\u606f..."
+                    },
+                    "speechButton": {
+                        "start": "\u5f00\u59cb\u5f55\u97f3",
+                        "stop": "\u505c\u6b62\u5f55\u97f3"
+                    },
+                    "SubmitButton": {
+                        "sendMessage": "\u53d1\u9001\u6d88\u606f",
+                        "stopTask": "\u505c\u6b62\u4efb\u52a1"
+                    },
+                    "UploadButton": {
+                        "attachFiles": "\u9644\u52a0\u6587\u4ef6"
+                    },
+                    "waterMark": {
+                        "text": "\u4f7f\u7528"
+                    }
+                },
+                "Messages": {
+                    "index": {
+                        "running": "\u8fd0\u884c\u4e2d",
+                        "executedSuccessfully": "\u6267\u884c\u6210\u529f",
+                        "failed": "\u5931\u8d25",
+                        "feedbackUpdated": "\u53cd\u9988\u66f4\u65b0",
+                        "updating": "\u6b63\u5728\u66f4\u65b0"
+                    }
+                },
+                "dropScreen": {
+                    "dropYourFilesHere": "\u5728\u8fd9\u91cc\u62d6\u653e\u60a8\u7684\u6587\u4ef6"
+                },
+                "index": {
+                    "failedToUpload": "\u4e0a\u4f20\u5931\u8d25",
+                    "cancelledUploadOf": "\u53d6\u6d88\u4e0a\u4f20",
+                    "couldNotReachServer": "\u65e0\u6cd5\u8fde\u63a5\u5230\u670d\u52a1\u5668",
+                    "continuingChat": "\u7ee7\u7eed\u4e4b\u524d\u7684\u5bf9\u8bdd"
+                },
+                "settings": {
+                    "settingsPanel": "\u8bbe\u7f6e\u9762\u677f",
+                    "reset": "\u91cd\u7f6e",
+                    "cancel": "\u53d6\u6d88",
+                    "confirm": "\u786e\u8ba4"
+                }
+            },
+            "threadHistory": {
+                "sidebar": {
+                    "filters": {
+                        "FeedbackSelect": {
+                            "feedbackAll": "\u53cd\u9988\uff1a\u5168\u90e8",
+                            "feedbackPositive": "\u53cd\u9988\uff1a\u6b63\u9762",
+                            "feedbackNegative": "\u53cd\u9988\uff1a\u8d1f\u9762"
+                        },
+                        "SearchBar": {
+                            "search": "\u641c\u7d22"
+                        }
+                    },
+                    "DeleteThreadButton": {
+                        "confirmMessage": "\u8fd9\u5c06\u5220\u9664\u7ebf\u7a0b\u53ca\u5176\u6d88\u606f\u548c\u5143\u7d20\u3002",
+                        "cancel": "\u53d6\u6d88",
+                        "confirm": "\u786e\u8ba4",
+                        "deletingChat": "\u5220\u9664\u5bf9\u8bdd",
+                        "chatDeleted": "\u5bf9\u8bdd\u5df2\u5220\u9664"
+                    },
+                    "index": {
+                        "pastChats": "\u8fc7\u5f80\u5bf9\u8bdd"
+                    },
+                    "ThreadList": {
+                        "empty": "\u7a7a\u7684...",
+                        "today": "\u4eca\u5929",
+                        "yesterday": "\u6628\u5929",
+                        "previous7days": "\u524d7\u5929",
+                        "previous30days": "\u524d30\u5929"
+                    },
+                    "TriggerButton": {
+                        "closeSidebar": "\u5173\u95ed\u4fa7\u8fb9\u680f",
+                        "openSidebar": "\u6253\u5f00\u4fa7\u8fb9\u680f"
+                    }
+                },
+                "Thread": {
+                    "backToChat": "\u8fd4\u56de\u5bf9\u8bdd",
+                    "chatCreatedOn": "\u6b64\u5bf9\u8bdd\u521b\u5efa\u4e8e"
+                }
+            },
+            "header": {
+                "chat": "\u5bf9\u8bdd",
+                "readme": "\u8bf4\u660e"
+            }
+        }
+    },
+    "hooks": {
+        "useLLMProviders": {
+            "failedToFetchProviders": "\u83b7\u53d6\u63d0\u4f9b\u8005\u5931\u8d25:"
+        }
+    },
+    "pages": {
+        "Design": {},
+        "Env": {
+            "savedSuccessfully": "\u4fdd\u5b58\u6210\u529f",
+            "requiredApiKeys": "\u5fc5\u9700\u7684API\u5bc6\u94a5",
+            "requiredApiKeysInfo": "\u8981\u4f7f\u7528\u6b64\u5e94\u7528\uff0c\u9700\u8981\u4ee5\u4e0bAPI\u5bc6\u94a5\u3002\u8fd9\u4e9b\u5bc6\u94a5\u5b58\u50a8\u5728\u60a8\u7684\u8bbe\u5907\u672c\u5730\u5b58\u50a8\u4e2d\u3002"
+        },
+        "Page": {
+            "notPartOfProject": "\u60a8\u4e0d\u662f\u6b64\u9879\u76ee\u7684\u4e00\u90e8\u5206\u3002"
+        },
+        "ResumeButton": {
+            "resumeChat": "\u6062\u590d\u5bf9\u8bdd"
+        }
+    }
+}

apps/ai_tutor/README.md

@@ -0,0 +1,12 @@
+# WIP
+
+
+## Run the encrypt_students script
+
+- If you don't want the emails to be public, run this script to encrypt the emails of the students.
+- This will create a new file in the public/files/ directory.
+- Place your file with the students' emails in the private/ directory (do not commit this file to the repository).
+
+```bash
+python encrypt_students.py --students-file private/students.json --encrypted-students-file public/files/students_encrypted.json
+```

apps/ai_tutor/app.py

@@ -0,0 +1,390 @@
+from fastapi import FastAPI, Request, Response, HTTPException
+from fastapi.responses import HTMLResponse, RedirectResponse
+from fastapi.templating import Jinja2Templates
+from google.oauth2 import id_token
+from google.auth.transport import requests as google_requests
+from google_auth_oauthlib.flow import Flow
+from chainlit.utils import mount_chainlit
+import secrets
+import json
+import base64
+from config.constants import (
+    OAUTH_GOOGLE_CLIENT_ID,
+    OAUTH_GOOGLE_CLIENT_SECRET,
+    CHAINLIT_URL,
+    EMAIL_ENCRYPTION_KEY,
+)
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.staticfiles import StaticFiles
+from helpers import (
+    get_time,
+    reset_tokens_for_user,
+    check_user_cooldown,
+)
+from edubotics_core.chat_processor.helpers import get_user_details, update_user_info
+from config.config_manager import config_manager
+import hashlib
+
+# set config
+config = config_manager.get_config().dict()
+
+# set constants
+GITHUB_REPO = config["misc"]["github_repo"]
+DOCS_WEBSITE = config["misc"]["docs_website"]
+ALL_TIME_TOKENS_ALLOCATED = config["token_config"]["all_time_tokens_allocated"]
+TOKENS_LEFT = config["token_config"]["tokens_left"]
+COOLDOWN_TIME = config["token_config"]["cooldown_time"]
+REGEN_TIME = config["token_config"]["regen_time"]
+
+GOOGLE_CLIENT_ID = OAUTH_GOOGLE_CLIENT_ID
+GOOGLE_CLIENT_SECRET = OAUTH_GOOGLE_CLIENT_SECRET
+GOOGLE_REDIRECT_URI = f"{CHAINLIT_URL}/auth/oauth/google/callback"
+
+app = FastAPI()
+app.mount("/public", StaticFiles(directory="public"), name="public")
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],  # Update with appropriate origins
+    allow_methods=["*"],
+    allow_headers=["*"],  # or specify the headers you want to allow
+    expose_headers=["X-User-Info"],  # Expose the custom header
+)
+
+templates = Jinja2Templates(directory="templates")
+session_store = {}
+CHAINLIT_PATH = "/chainlit_tutor"
+
+# only admin is given any additional permissions for now -- no limits on tokens
+with open("public/files/students_encrypted.json", "r") as file:
+    USER_ROLES = json.load(file)
+
+# Create a Google OAuth flow
+flow = Flow.from_client_config(
+    {
+        "web": {
+            "client_id": GOOGLE_CLIENT_ID,
+            "client_secret": GOOGLE_CLIENT_SECRET,
+            "auth_uri": "https://accounts.google.com/o/oauth2/auth",
+            "token_uri": "https://oauth2.googleapis.com/token",
+            "redirect_uris": [GOOGLE_REDIRECT_URI],
+            "scopes": [
+                "openid",
+                # "https://www.googleapis.com/auth/userinfo.email",
+                # "https://www.googleapis.com/auth/userinfo.profile",
+            ],
+        }
+    },
+    scopes=[
+        "openid",
+        "https://www.googleapis.com/auth/userinfo.email",
+        "https://www.googleapis.com/auth/userinfo.profile",
+    ],
+    redirect_uri=GOOGLE_REDIRECT_URI,
+)
+
+
+def get_user_role(username: str):
+
+    # Function to deterministically hash emails
+    def deterministic_hash(email, salt):
+        return hashlib.pbkdf2_hmac("sha256", email.encode(), salt, 100000).hex()
+
+    # encrypt email (#FIXME: this is not the best way to do this, not really encryption, more like a hash)
+    encryption_salt = EMAIL_ENCRYPTION_KEY.encode()
+    encrypted_email = deterministic_hash(username, encryption_salt)
+    role = USER_ROLES.get(encrypted_email, ["guest"])
+
+    if "guest" in role:
+        return "unauthorized"
+
+    return role
+
+
+async def get_user_info_from_cookie(request: Request):
+    user_info_encoded = request.cookies.get("X-User-Info")
+    if user_info_encoded:
+        try:
+            user_info_json = base64.b64decode(user_info_encoded).decode()
+            return json.loads(user_info_json)
+        except Exception as e:
+            print(f"Error decoding user info: {e}")
+            return None
+    return None
+
+
+async def del_user_info_from_cookie(request: Request, response: Response):
+    # Delete cookies from the response
+    response.delete_cookie("X-User-Info")
+    response.delete_cookie("session_token")
+    # Get the session token from the request cookies
+    session_token = request.cookies.get("session_token")
+    # Check if the session token exists in the session_store before deleting
+    if session_token and session_token in session_store:
+        del session_store[session_token]
+
+
+def get_user_info(request: Request):
+    session_token = request.cookies.get("session_token")
+    if session_token and session_token in session_store:
+        return session_store[session_token]
+    return None
+
+
+@app.get("/", response_class=HTMLResponse)
+async def login_page(request: Request):
+    user_info = await get_user_info_from_cookie(request)
+    if user_info and user_info.get("google_signed_in"):
+        return RedirectResponse("/post-signin")
+    return templates.TemplateResponse(
+        "login.html",
+        {"request": request, "GITHUB_REPO": GITHUB_REPO, "DOCS_WEBSITE": DOCS_WEBSITE},
+    )
+
+
+# @app.get("/login/guest")
+# async def login_guest():
+#     username = "guest"
+#     session_token = secrets.token_hex(16)
+#     unique_session_id = secrets.token_hex(8)
+#     username = f"{username}_{unique_session_id}"
+#     session_store[session_token] = {
+#         "email": username,
+#         "name": "Guest",
+#         "profile_image": "",
+#         "google_signed_in": False,  # Ensure guest users do not have this flag
+#     }
+#     user_info_json = json.dumps(session_store[session_token])
+#     user_info_encoded = base64.b64encode(user_info_json.encode()).decode()
+
+#     # Set cookies
+#     response = RedirectResponse(url="/post-signin", status_code=303)
+#     response.set_cookie(key="session_token", value=session_token)
+#     response.set_cookie(key="X-User-Info", value=user_info_encoded, httponly=True)
+#     return response
+
+
+@app.get("/unauthorized", response_class=HTMLResponse)
+async def unauthorized(request: Request):
+    return templates.TemplateResponse("unauthorized.html", {"request": request})
+
+
+@app.get("/login/google")
+async def login_google(request: Request):
+    # Clear any existing session cookies to avoid conflicts with guest sessions
+    response = RedirectResponse(url="/post-signin")
+    response.delete_cookie(key="session_token")
+    response.delete_cookie(key="X-User-Info")
+
+    user_info = await get_user_info_from_cookie(request)
+    # Check if user is already signed in using Google
+    if user_info and user_info.get("google_signed_in"):
+        return RedirectResponse("/post-signin")
+    else:
+        authorization_url, _ = flow.authorization_url(prompt="consent")
+        return RedirectResponse(authorization_url, headers=response.headers)
+
+
+@app.get("/auth/oauth/google/callback")
+async def auth_google(request: Request):
+    try:
+        flow.fetch_token(code=request.query_params.get("code"))
+        credentials = flow.credentials
+        user_info = id_token.verify_oauth2_token(
+            credentials.id_token, google_requests.Request(), GOOGLE_CLIENT_ID
+        )
+
+        email = user_info["email"]
+        name = user_info.get("name", "")
+        profile_image = user_info.get("picture", "")
+        role = get_user_role(email)
+
+        if role == "unauthorized":
+            return RedirectResponse("/unauthorized")
+
+        session_token = secrets.token_hex(16)
+        session_store[session_token] = {
+            "email": email,
+            "name": name,
+            "profile_image": profile_image,
+            "google_signed_in": True,  # Set this flag to True for Google-signed users
+        }
+
+        # add literalai user info to session store to be sent to chainlit
+        literalai_user = await get_user_details(email)
+        session_store[session_token]["literalai_info"] = literalai_user.to_dict()
+        session_store[session_token]["literalai_info"]["metadata"]["role"] = role
+
+        user_info_json = json.dumps(session_store[session_token])
+        user_info_encoded = base64.b64encode(user_info_json.encode()).decode()
+
+        # Set cookies
+        response = RedirectResponse(url="/post-signin", status_code=303)
+        response.set_cookie(key="session_token", value=session_token)
+        response.set_cookie(
+            key="X-User-Info", value=user_info_encoded, httponly=True
+        )  # TODO: is the flag httponly=True necessary?
+        return response
+    except Exception as e:
+        print(f"Error during Google OAuth callback: {e}")
+        return RedirectResponse(url="/", status_code=302)
+
+
+@app.get("/cooldown")
+async def cooldown(request: Request):
+    user_info = await get_user_info_from_cookie(request)
+    user_details = await get_user_details(user_info["email"])
+    current_datetime = get_time()
+    cooldown, cooldown_end_time = await check_user_cooldown(
+        user_details, current_datetime, COOLDOWN_TIME, TOKENS_LEFT, REGEN_TIME
+    )
+    print(f"User in cooldown: {cooldown}")
+    print(f"Cooldown end time: {cooldown_end_time}")
+    if cooldown and "admin" not in get_user_role(user_info["email"]):
+        return templates.TemplateResponse(
+            "cooldown.html",
+            {
+                "request": request,
+                "username": user_info["email"],
+                "role": get_user_role(user_info["email"]),
+                "cooldown_end_time": cooldown_end_time,
+                "tokens_left": user_details.metadata["tokens_left"],
+            },
+        )
+    else:
+        user_details.metadata["in_cooldown"] = False
+        await update_user_info(user_details)
+        await reset_tokens_for_user(
+            user_details,
+            config["token_config"]["tokens_left"],
+            config["token_config"]["regen_time"],
+        )
+        return RedirectResponse("/post-signin")
+
+
+@app.get("/post-signin", response_class=HTMLResponse)
+async def post_signin(request: Request):
+    user_info = await get_user_info_from_cookie(request)
+    if not user_info:
+        user_info = get_user_info(request)
+    user_details = await get_user_details(user_info["email"])
+    current_datetime = get_time()
+    user_details.metadata["last_login"] = current_datetime
+    # if new user, set the number of tries
+    if "tokens_left" not in user_details.metadata:
+        user_details.metadata["tokens_left"] = (
+            TOKENS_LEFT  # set the number of tokens left for the new user
+        )
+    if "last_message_time" not in user_details.metadata:
+        user_details.metadata["last_message_time"] = current_datetime
+    if "all_time_tokens_allocated" not in user_details.metadata:
+        user_details.metadata["all_time_tokens_allocated"] = ALL_TIME_TOKENS_ALLOCATED
+    if "in_cooldown" not in user_details.metadata:
+        user_details.metadata["in_cooldown"] = False
+    await update_user_info(user_details)
+
+    if "last_message_time" in user_details.metadata and "admin" not in get_user_role(
+        user_info["email"]
+    ):
+        cooldown, _ = await check_user_cooldown(
+            user_details, current_datetime, COOLDOWN_TIME, TOKENS_LEFT, REGEN_TIME
+        )
+        if cooldown:
+            user_details.metadata["in_cooldown"] = True
+            return RedirectResponse("/cooldown")
+        else:
+            user_details.metadata["in_cooldown"] = False
+            await reset_tokens_for_user(
+                user_details,
+                config["token_config"]["tokens_left"],
+                config["token_config"]["regen_time"],
+            )
+
+    if user_info:
+        username = user_info["email"]
+        role = get_user_role(username)
+        jwt_token = request.cookies.get("X-User-Info")
+        return templates.TemplateResponse(
+            "dashboard.html",
+            {
+                "request": request,
+                "username": username,
+                "role": role,
+                "jwt_token": jwt_token,
+                "tokens_left": user_details.metadata["tokens_left"],
+                "all_time_tokens_allocated": user_details.metadata[
+                    "all_time_tokens_allocated"
+                ],
+                "total_tokens_allocated": ALL_TIME_TOKENS_ALLOCATED,
+            },
+        )
+    return RedirectResponse("/")
+
+
+@app.get("/start-tutor")
+@app.post("/start-tutor")
+async def start_tutor(request: Request):
+    user_info = await get_user_info_from_cookie(request)
+    if user_info:
+        user_info_json = json.dumps(user_info)
+        user_info_encoded = base64.b64encode(user_info_json.encode()).decode()
+
+        response = RedirectResponse(CHAINLIT_PATH, status_code=303)
+        response.set_cookie(key="X-User-Info", value=user_info_encoded, httponly=True)
+        return response
+
+    return RedirectResponse(url="/")
+
+
+@app.exception_handler(HTTPException)
+async def http_exception_handler(request: Request, exc: HTTPException):
+    if exc.status_code == 404:
+        return templates.TemplateResponse(
+            "error_404.html", {"request": request}, status_code=404
+        )
+    return templates.TemplateResponse(
+        "error.html",
+        {"request": request, "error": str(exc)},
+        status_code=exc.status_code,
+    )
+
+
+@app.exception_handler(Exception)
+async def exception_handler(request: Request, exc: Exception):
+    return templates.TemplateResponse(
+        "error.html", {"request": request, "error": str(exc)}, status_code=500
+    )
+
+
+@app.get("/logout", response_class=HTMLResponse)
+async def logout(request: Request, response: Response):
+    await del_user_info_from_cookie(request=request, response=response)
+    response = RedirectResponse(url="/", status_code=302)
+    # Set cookies to empty values and expire them immediately
+    response.set_cookie(key="session_token", value="", expires=0)
+    response.set_cookie(key="X-User-Info", value="", expires=0)
+    return response
+
+
+@app.get("/get-tokens-left")
+async def get_tokens_left(request: Request):
+    try:
+        user_info = await get_user_info_from_cookie(request)
+        user_details = await get_user_details(user_info["email"])
+        await reset_tokens_for_user(
+            user_details,
+            config["token_config"]["tokens_left"],
+            config["token_config"]["regen_time"],
+        )
+        tokens_left = user_details.metadata["tokens_left"]
+        return {"tokens_left": tokens_left}
+    except Exception as e:
+        print(f"Error getting tokens left: {e}")
+        return {"tokens_left": 0}
+
+
+mount_chainlit(app=app, target="chainlit_app.py", path=CHAINLIT_PATH)
+
+if __name__ == "__main__":
+    import uvicorn
+
+    uvicorn.run(app, host="127.0.0.1", port=7860)

apps/ai_tutor/chainlit_app.py

@@ -0,0 +1,563 @@
+import chainlit.data as cl_data
+import asyncio
+from config.constants import (
+    LITERAL_API_KEY_LOGGING,
+    LITERAL_API_URL,
+)
+from edubotics_core.chat_processor.literal_ai import CustomLiteralDataLayer
+import json
+from typing import Any, Dict, no_type_check
+import chainlit as cl
+from edubotics_core.chat.llm_tutor import LLMTutor
+from edubotics_core.chat.helpers import (
+    get_sources,
+    get_history_chat_resume,
+    get_history_setup_llm,
+    # get_last_config,
+)
+from edubotics_core.chat_processor.helpers import (
+    update_user_info,
+    get_user_details,
+)
+from helpers import (
+    check_user_cooldown,
+    reset_tokens_for_user,
+)
+from helpers import get_time
+import copy
+from typing import Optional
+from chainlit.types import ThreadDict
+import base64
+from langchain_community.callbacks import get_openai_callback
+from datetime import datetime, timezone
+from config.config_manager import config_manager
+
+USER_TIMEOUT = 60_000
+SYSTEM = "System"
+LLM = "AI Tutor"
+AGENT = "Agent"
+YOU = "User"
+ERROR = "Error"
+
+# set config
+config = config_manager.get_config().dict()
+
+
+async def setup_data_layer():
+    """
+    Set up the data layer for chat logging.
+    """
+    if config["chat_logging"]["log_chat"]:
+        data_layer = CustomLiteralDataLayer(
+            api_key=LITERAL_API_KEY_LOGGING, server=LITERAL_API_URL
+        )
+    else:
+        data_layer = None
+
+    return data_layer
+
+
+async def update_user_from_chainlit(user, token_count=0):
+    if "admin" not in user.metadata["role"]:
+        user.metadata["tokens_left"] = user.metadata["tokens_left"] - token_count
+        user.metadata["all_time_tokens_allocated"] = (
+            user.metadata["all_time_tokens_allocated"] - token_count
+        )
+        user.metadata["tokens_left_at_last_message"] = user.metadata[
+            "tokens_left"
+        ]  # tokens_left will keep regenerating outside of chainlit
+    user.metadata["last_message_time"] = get_time()
+    await update_user_info(user)
+
+    tokens_left = user.metadata["tokens_left"]
+    if tokens_left < 0:
+        tokens_left = 0
+    return tokens_left
+
+
+class Chatbot:
+    def __init__(self, config):
+        """
+        Initialize the Chatbot class.
+        """
+        self.config = config
+
+    @no_type_check
+    async def setup_llm(self):
+        """
+        Set up the LLM with the provided settings. Update the configuration and initialize the LLM tutor.
+
+        #TODO: Clean this up.
+        """
+
+        llm_settings = cl.user_session.get("llm_settings", {})
+        (
+            chat_profile,
+            retriever_method,
+            memory_window,
+            llm_style,
+            generate_follow_up,
+            chunking_mode,
+        ) = (
+            llm_settings.get("chat_model"),
+            llm_settings.get("retriever_method"),
+            llm_settings.get("memory_window"),
+            llm_settings.get("llm_style"),
+            llm_settings.get("follow_up_questions"),
+            llm_settings.get("chunking_mode"),
+        )
+
+        chain = cl.user_session.get("chain")
+        memory_list = cl.user_session.get(
+            "memory",
+            (
+                list(chain.store.values())[0].messages
+                if len(chain.store.values()) > 0
+                else []
+            ),
+        )
+        conversation_list = get_history_setup_llm(memory_list)
+
+        old_config = copy.deepcopy(self.config)
+        self.config["vectorstore"]["db_option"] = retriever_method
+        self.config["llm_params"]["memory_window"] = memory_window
+        self.config["llm_params"]["llm_style"] = llm_style
+        self.config["llm_params"]["llm_loader"] = chat_profile
+        self.config["llm_params"]["generate_follow_up"] = generate_follow_up
+        self.config["splitter_options"]["chunking_mode"] = chunking_mode
+
+        self.llm_tutor.update_llm(
+            old_config, self.config
+        )  # update only llm attributes that are changed
+        self.chain = self.llm_tutor.qa_bot(
+            memory=conversation_list,
+        )
+
+        cl.user_session.set("chain", self.chain)
+        cl.user_session.set("llm_tutor", self.llm_tutor)
+
+    @no_type_check
+    async def update_llm(self, new_settings: Dict[str, Any]):
+        """
+        Update the LLM settings and reinitialize the LLM with the new settings.
+
+        Args:
+            new_settings (Dict[str, Any]): The new settings to update.
+        """
+        cl.user_session.set("llm_settings", new_settings)
+        await self.inform_llm_settings()
+        await self.setup_llm()
+
+    async def make_llm_settings_widgets(self, config=None):
+        """
+        Create and send the widgets for LLM settings configuration.
+
+        Args:
+            config: The configuration to use for setting up the widgets.
+        """
+        config = config or self.config
+        await cl.ChatSettings(
+            [
+                cl.input_widget.Select(
+                    id="chat_model",
+                    label="Model Name (Default GPT-3)",
+                    values=["local_llm", "gpt-3.5-turbo-1106", "gpt-4", "gpt-4o-mini"],
+                    initial_index=[
+                        "local_llm",
+                        "gpt-3.5-turbo-1106",
+                        "gpt-4",
+                        "gpt-4o-mini",
+                    ].index(config["llm_params"]["llm_loader"]),
+                ),
+                cl.input_widget.Select(
+                    id="retriever_method",
+                    label="Retriever (Default FAISS)",
+                    values=["FAISS", "Chroma", "RAGatouille", "RAPTOR"],
+                    initial_index=["FAISS", "Chroma", "RAGatouille", "RAPTOR"].index(
+                        config["vectorstore"]["db_option"]
+                    ),
+                ),
+                cl.input_widget.Slider(
+                    id="memory_window",
+                    label="Memory Window (Default 3)",
+                    initial=3,
+                    min=0,
+                    max=10,
+                    step=1,
+                ),
+                cl.input_widget.Switch(
+                    id="view_sources", label="View Sources", initial=False
+                ),
+                cl.input_widget.Switch(
+                    id="stream_response",
+                    label="Stream response",
+                    initial=config["llm_params"]["stream"],
+                ),
+                cl.input_widget.Select(
+                    id="chunking_mode",
+                    label="Chunking mode",
+                    values=["fixed", "semantic"],
+                    initial_index=1,
+                ),
+                cl.input_widget.Switch(
+                    id="follow_up_questions",
+                    label="Generate follow up questions",
+                    initial=False,
+                ),
+                cl.input_widget.Select(
+                    id="llm_style",
+                    label="Type of Conversation (Default Normal)",
+                    values=["Normal", "ELI5"],
+                    initial_index=0,
+                ),
+            ]
+        ).send()
+
+    @no_type_check
+    async def inform_llm_settings(self):
+        """
+        Inform the user about the updated LLM settings and display them as a message.
+        """
+        await cl.Message(
+            author=SYSTEM,
+            content="LLM settings have been updated. You can continue with your Query!",
+        ).send()
+
+    async def set_starters(self):
+        """
+        Set starter messages for the chatbot.
+        """
+        # Return Starters only if the chat is new
+
+        try:
+            thread = cl_data._data_layer.get_thread(
+                cl.context.session.thread_id
+            )  # see if the thread has any steps
+            if thread.steps or len(thread.steps) > 0:
+                return None
+        except Exception as e:
+            print(e)
+            return [
+                cl.Starter(
+                    label="recording on Transformers?",
+                    message="Where can I find the recording for the lecture on Transformers?",
+                    icon="/public/assets/images/starter_icons/adv-screen-recorder-svgrepo-com.svg",
+                ),
+                cl.Starter(
+                    label="where's the schedule?",
+                    message="When are the lectures? I can't find the schedule.",
+                    icon="/public/assets/images/starter_icons/alarmy-svgrepo-com.svg",
+                ),
+                cl.Starter(
+                    label="Due Date?",
+                    message="When is the final project due?",
+                    icon="/public/assets/images/starter_icons/calendar-samsung-17-svgrepo-com.svg",
+                ),
+                cl.Starter(
+                    label="Explain backprop.",
+                    message="I didn't understand the math behind backprop, could you explain it?",
+                    icon="/public/assets/images/starter_icons/acastusphoton-svgrepo-com.svg",
+                ),
+            ]
+
+    def rename(self, orig_author: str):
+        """
+        Rename the original author to a more user-friendly name.
+
+        Args:
+            orig_author (str): The original author's name.
+
+        Returns:
+            str: The renamed author.
+        """
+        rename_dict = {"Chatbot": LLM}
+        return rename_dict.get(orig_author, orig_author)
+
+    async def start(self):
+        """
+        Start the chatbot, initialize settings widgets,
+        and display and load previous conversation if chat logging is enabled.
+        """
+
+        await self.make_llm_settings_widgets(self.config)  # Reload the settings widgets
+
+        user = cl.user_session.get("user")
+
+        # TODO: remove self.user with cl.user_session.get("user")
+        try:
+            self.user = {
+                "user_id": user.identifier,
+                "session_id": cl.context.session.thread_id,
+            }
+        except Exception as e:
+            print(e)
+            self.user = {
+                "user_id": "guest",
+                "session_id": cl.context.session.thread_id,
+            }
+
+        memory = cl.user_session.get("memory", [])
+        self.llm_tutor = LLMTutor(self.config, user=self.user)
+
+        self.chain = self.llm_tutor.qa_bot(
+            memory=memory,
+        )
+        self.question_generator = self.llm_tutor.question_generator
+        cl.user_session.set("llm_tutor", self.llm_tutor)
+        cl.user_session.set("chain", self.chain)
+
+    async def stream_response(self, response):
+        """
+        Stream the response from the LLM.
+
+        Args:
+            response: The response from the LLM.
+        """
+        msg = cl.Message(content="")
+        await msg.send()
+
+        output = {}
+        for chunk in response:
+            if "answer" in chunk:
+                await msg.stream_token(chunk["answer"])
+
+            for key in chunk:
+                if key not in output:
+                    output[key] = chunk[key]
+                else:
+                    output[key] += chunk[key]
+        return output
+
+    async def main(self, message):
+        """
+        Process and Display the Conversation.
+
+        Args:
+            message: The incoming chat message.
+        """
+
+        chain = cl.user_session.get("chain")
+        token_count = 0  # initialize token count
+        if not chain:
+            await self.start()  # start the chatbot if the chain is not present
+            chain = cl.user_session.get("chain")
+
+        # update user info with last message time
+        user = cl.user_session.get("user")
+        await reset_tokens_for_user(
+            user,
+            self.config["token_config"]["tokens_left"],
+            self.config["token_config"]["regen_time"],
+        )
+        updated_user = await get_user_details(user.identifier)
+        user.metadata = updated_user.metadata
+        cl.user_session.set("user", user)
+
+        # see if user has token credits left
+        # if not, return message saying they have run out of tokens
+        if user.metadata["tokens_left"] <= 0 and "admin" not in user.metadata["role"]:
+            current_datetime = get_time()
+            cooldown, cooldown_end_time = await check_user_cooldown(
+                user,
+                current_datetime,
+                self.config["token_config"]["cooldown_time"],
+                self.config["token_config"]["tokens_left"],
+                self.config["token_config"]["regen_time"],
+            )
+            if cooldown:
+                # get time left in cooldown
+                # convert both to datetime objects
+                cooldown_end_time = datetime.fromisoformat(cooldown_end_time).replace(
+                    tzinfo=timezone.utc
+                )
+                current_datetime = datetime.fromisoformat(current_datetime).replace(
+                    tzinfo=timezone.utc
+                )
+                cooldown_time_left = cooldown_end_time - current_datetime
+                # Get the total seconds
+                total_seconds = int(cooldown_time_left.total_seconds())
+                # Calculate hours, minutes, and seconds
+                hours, remainder = divmod(total_seconds, 3600)
+                minutes, seconds = divmod(remainder, 60)
+                # Format the time as 00 hrs 00 mins 00 secs
+                formatted_time = f"{hours:02} hrs {minutes:02} mins {seconds:02} secs"
+                await cl.Message(
+                    content=(
+                        "Ah, seems like you have run out of tokens...Click "
+                        '<a href="/cooldown" style="color: #0000CD; text-decoration: none;" target="_self">here</a> for more info. Please come back after {}'.format(
+                            formatted_time
+                        )
+                    ),
+                    author=SYSTEM,
+                ).send()
+                user.metadata["in_cooldown"] = True
+                await update_user_info(user)
+                return
+            else:
+                await cl.Message(
+                    content=(
+                        "Ah, seems like you don't have any tokens left...Please wait while we regenerate your tokens. Click "
+                        '<a href="/cooldown" style="color: #0000CD; text-decoration: none;" target="_self">here</a> to view your token credits.'
+                    ),
+                    author=SYSTEM,
+                ).send()
+                return
+
+        user.metadata["in_cooldown"] = False
+
+        llm_settings = cl.user_session.get("llm_settings", {})
+        view_sources = llm_settings.get("view_sources", False)
+        stream = llm_settings.get("stream_response", False)
+        stream = False  # Fix streaming
+        user_query_dict = {"input": message.content}
+        # Define the base configuration
+        cb = cl.AsyncLangchainCallbackHandler()
+        chain_config = {
+            "configurable": {
+                "user_id": self.user["user_id"],
+                "conversation_id": self.user["session_id"],
+                "memory_window": self.config["llm_params"]["memory_window"],
+            },
+            "callbacks": (
+                [cb]
+                if cl_data._data_layer and self.config["chat_logging"]["callbacks"]
+                else None
+            ),
+        }
+
+        with get_openai_callback() as token_count_cb:
+            if stream:
+                res = chain.stream(user_query=user_query_dict, config=chain_config)
+                res = await self.stream_response(res)
+            else:
+                res = await chain.invoke(
+                    user_query=user_query_dict,
+                    config=chain_config,
+                )
+        token_count += token_count_cb.total_tokens
+
+        answer = res.get("answer", res.get("result"))
+
+        answer_with_sources, source_elements, sources_dict = get_sources(
+            res, answer, stream=stream, view_sources=view_sources
+        )
+        answer_with_sources = answer_with_sources.replace("$$", "$")
+
+        actions = []
+
+        if self.config["llm_params"]["generate_follow_up"]:
+            cb_follow_up = cl.AsyncLangchainCallbackHandler()
+            config = {
+                "callbacks": (
+                    [cb_follow_up]
+                    if cl_data._data_layer and self.config["chat_logging"]["callbacks"]
+                    else None
+                )
+            }
+            with get_openai_callback() as token_count_cb:
+                list_of_questions = await self.question_generator.generate_questions(
+                    query=user_query_dict["input"],
+                    response=answer,
+                    chat_history=res.get("chat_history"),
+                    context=res.get("context"),
+                    config=config,
+                )
+
+            token_count += token_count_cb.total_tokens
+
+            for question in list_of_questions:
+                actions.append(
+                    cl.Action(
+                        name="follow up question",
+                        value="example_value",
+                        description=question,
+                        label=question,
+                    )
+                )
+
+        # # update user info with token count
+        tokens_left = await update_user_from_chainlit(user, token_count)
+
+        answer_with_sources += (
+            '\n\n<footer><span style="font-size: 0.8em; text-align: right; display: block;">Tokens Left: '
+            + str(tokens_left)
+            + "</span></footer>\n"
+        )
+
+        await cl.Message(
+            content=answer_with_sources,
+            elements=source_elements,
+            author=LLM,
+            actions=actions,
+        ).send()
+
+    async def on_chat_resume(self, thread: ThreadDict):
+        # thread_config = None
+        steps = thread["steps"]
+        k = self.config["llm_params"][
+            "memory_window"
+        ]  # on resume, alwyas use the default memory window
+        conversation_list = get_history_chat_resume(steps, k, SYSTEM, LLM)
+        # thread_config = get_last_config(
+        #     steps
+        # )  # TODO: Returns None for now - which causes config to be reloaded with default values
+        cl.user_session.set("memory", conversation_list)
+        await self.start()
+
+    @cl.header_auth_callback
+    def header_auth_callback(headers: dict) -> Optional[cl.User]:
+        # try: # TODO: Add try-except block after testing
+        # TODO: Implement to get the user information from the headers (not the cookie)
+        cookie = headers.get("cookie")  # gets back a str
+        # Create a dictionary from the pairs
+        cookie_dict = {}
+        for pair in cookie.split("; "):
+            key, value = pair.split("=", 1)
+            # Strip surrounding quotes if present
+            cookie_dict[key] = value.strip('"')
+
+        decoded_user_info = base64.b64decode(
+            cookie_dict.get("X-User-Info", "")
+        ).decode()
+        decoded_user_info = json.loads(decoded_user_info)
+
+        return cl.User(
+            id=decoded_user_info["literalai_info"]["id"],
+            identifier=decoded_user_info["literalai_info"]["identifier"],
+            metadata=decoded_user_info["literalai_info"]["metadata"],
+        )
+
+    async def on_follow_up(self, action: cl.Action):
+        user = cl.user_session.get("user")
+        message = await cl.Message(
+            content=action.description,
+            type="user_message",
+            author=user.identifier,
+        ).send()
+        async with cl.Step(
+            name="on_follow_up", type="run", parent_id=message.id
+        ) as step:
+            await self.main(message)
+            step.output = message.content
+
+
+chatbot = Chatbot(config=config)
+
+
+async def start_app():
+    cl_data._data_layer = await setup_data_layer()
+    chatbot.literal_client = cl_data._data_layer.client if cl_data._data_layer else None
+    cl.set_starters(chatbot.set_starters)
+    cl.author_rename(chatbot.rename)
+    cl.on_chat_start(chatbot.start)
+    cl.on_chat_resume(chatbot.on_chat_resume)
+    cl.on_message(chatbot.main)
+    cl.on_settings_update(chatbot.update_llm)
+    cl.action_callback("follow up question")(chatbot.on_follow_up)
+
+
+loop = asyncio.get_event_loop()
+if loop.is_running():
+    asyncio.ensure_future(start_app())
+else:
+    asyncio.run(start_app())

apps/ai_tutor/config/config.yml

@@ -0,0 +1,60 @@
+log_dir: 'storage/logs' # str
+log_chunk_dir: 'storage/logs/chunks' # str
+device: 'cpu' # str [cuda, cpu]
+
+vectorstore:
+  load_from_HF: True # bool
+  reparse_files: True # bool
+  data_path: 'storage/data' # str
+  url_file_path: 'storage/data/urls.txt' # str
+  expand_urls: True # bool
+  db_option : 'RAGatouille' # str [FAISS, Chroma, RAGatouille, RAPTOR]
+  db_path : 'vectorstores' # str
+  model : 'sentence-transformers/all-MiniLM-L6-v2' # str [sentence-transformers/all-MiniLM-L6-v2, text-embedding-ada-002']
+  search_top_k : 3 # int
+  score_threshold : 0.2 # float
+
+  faiss_params: # Not used as of now
+    index_path: 'vectorstores/faiss.index' # str
+    index_type: 'Flat' # str [Flat, HNSW, IVF]
+    index_dimension: 384 # int
+    index_nlist: 100 # int
+    index_nprobe: 10 # int
+
+  colbert_params:
+    index_name: "new_idx" # str
+
+llm_params: 
+  llm_arch: 'langchain' # [langchain]
+  use_history: True # bool
+  generate_follow_up: False # bool
+  memory_window: 3 # int
+  llm_style: 'Normal' # str [Normal, ELI5]
+  llm_loader: 'gpt-4o-mini' # str [local_llm, gpt-3.5-turbo-1106, gpt-4, gpt-4o-mini]
+  openai_params:
+    temperature: 0.7 # float
+  local_llm_params:
+    temperature: 0.7 # float
+    repo_id: 'TheBloke/TinyLlama-1.1B-Chat-v1.0-GGUF' # HuggingFace repo id
+    filename: 'tinyllama-1.1b-chat-v1.0.Q5_0.gguf' # Specific name of gguf file in the repo
+    model_path: 'storage/models/tinyllama-1.1b-chat-v1.0.Q5_0.gguf' # Path to the model file
+  stream: False # bool
+  pdf_reader: 'gpt' # str [llama, pymupdf, gpt]
+
+chat_logging:
+  log_chat: True # bool
+  platform: 'literalai'
+  callbacks: True # bool
+
+splitter_options:
+  use_splitter: True # bool
+  split_by_token : True # bool
+  remove_leftover_delimiters: True # bool
+  remove_chunks: False # bool
+  chunking_mode: 'semantic' # str [fixed, semantic]
+  chunk_size : 300 # int
+  chunk_overlap : 30 # int
+  chunk_separators : ["\n\n", "\n", " ", ""] # list of strings
+  front_chunks_to_remove : null # int or None
+  last_chunks_to_remove : null # int or None
+  delimiters_to_remove : ['\t', '\n', '   ', '  '] # list of strings

apps/ai_tutor/config/config_manager.py

@@ -0,0 +1,189 @@
+from pydantic import BaseModel, conint, confloat, HttpUrl
+from typing import Optional, List
+import yaml
+
+
+class FaissParams(BaseModel):
+    index_path: str = "vectorstores/faiss.index"
+    index_type: str = "Flat"  # Options: [Flat, HNSW, IVF]
+    index_dimension: conint(gt=0) = 384
+    index_nlist: conint(gt=0) = 100
+    index_nprobe: conint(gt=0) = 10
+
+
+class ColbertParams(BaseModel):
+    index_name: str = "new_idx"
+
+
+class VectorStoreConfig(BaseModel):
+    load_from_HF: bool = True
+    reparse_files: bool = True
+    data_path: str = "storage/data"
+    url_file_path: str = "storage/data/urls.txt"
+    expand_urls: bool = True
+    db_option: str = "RAGatouille"  # Options: [FAISS, Chroma, RAGatouille, RAPTOR]
+    db_path: str = "vectorstores"
+    model: str = (
+        # Options: [sentence-transformers/all-MiniLM-L6-v2, text-embedding-ada-002]
+        "sentence-transformers/all-MiniLM-L6-v2"
+    )
+    search_top_k: conint(gt=0) = 3
+    score_threshold: confloat(ge=0.0, le=1.0) = 0.2
+
+    faiss_params: Optional[FaissParams] = None
+    colbert_params: Optional[ColbertParams] = None
+
+
+class OpenAIParams(BaseModel):
+    temperature: confloat(ge=0.0, le=1.0) = 0.7
+
+
+class LocalLLMParams(BaseModel):
+    temperature: confloat(ge=0.0, le=1.0) = 0.7
+    repo_id: str = "TheBloke/TinyLlama-1.1B-Chat-v1.0-GGUF"  # HuggingFace repo id
+    filename: str = (
+        "tinyllama-1.1b-chat-v1.0.Q5_0.gguf"  # Specific name of gguf file in the repo
+    )
+    model_path: str = (
+        "storage/models/tinyllama-1.1b-chat-v1.0.Q5_0.gguf"  # Path to the model file
+    )
+
+
+class LLMParams(BaseModel):
+    llm_arch: str = "langchain"  # Options: [langchain]
+    use_history: bool = True
+    generate_follow_up: bool = False
+    memory_window: conint(ge=1) = 3
+    llm_style: str = "Normal"  # Options: [Normal, ELI5]
+    llm_loader: str = (
+        "gpt-4o-mini"  # Options: [local_llm, gpt-3.5-turbo-1106, gpt-4, gpt-4o-mini]
+    )
+    openai_params: Optional[OpenAIParams] = None
+    local_llm_params: Optional[LocalLLMParams] = None
+    stream: bool = False
+    pdf_reader: str = "gpt"  # Options: [llama, pymupdf, gpt]
+
+
+class ChatLoggingConfig(BaseModel):
+    log_chat: bool = True
+    platform: str = "literalai"
+    callbacks: bool = True
+
+
+class SplitterOptions(BaseModel):
+    use_splitter: bool = True
+    split_by_token: bool = True
+    remove_leftover_delimiters: bool = True
+    remove_chunks: bool = False
+    chunking_mode: str = "semantic"  # Options: [fixed, semantic]
+    chunk_size: conint(gt=0) = 300
+    chunk_overlap: conint(ge=0) = 30
+    chunk_separators: List[str] = ["\n\n", "\n", " ", ""]
+    front_chunks_to_remove: Optional[conint(ge=0)] = None
+    last_chunks_to_remove: Optional[conint(ge=0)] = None
+    delimiters_to_remove: List[str] = ["\t", "\n", "   ", "  "]
+
+
+class RetrieverConfig(BaseModel):
+    retriever_hf_paths: dict[str, str] = {"RAGatouille": "XThomasBU/Colbert_Index"}
+
+
+class MetadataConfig(BaseModel):
+    metadata_links: List[HttpUrl] = [
+        "https://dl4ds.github.io/sp2024/lectures/",
+        "https://dl4ds.github.io/sp2024/schedule/",
+    ]
+    slide_base_link: HttpUrl = "https://dl4ds.github.io"
+
+
+class TokenConfig(BaseModel):
+    cooldown_time: conint(gt=0) = 60
+    regen_time: conint(gt=0) = 180
+    tokens_left: conint(gt=0) = 2000
+    all_time_tokens_allocated: conint(gt=0) = 1000000
+
+
+class MiscConfig(BaseModel):
+    github_repo: HttpUrl = "https://github.com/edubotics-ai/edubot-core"
+    docs_website: HttpUrl = "https://dl4ds.github.io/dl4ds_tutor/"
+
+
+class APIConfig(BaseModel):
+    timeout: conint(gt=0) = 60
+
+
+class Config(BaseModel):
+    log_dir: str = "storage/logs"
+    log_chunk_dir: str = "storage/logs/chunks"
+    device: str = "cpu"  # Options: ['cuda', 'cpu']
+
+    vectorstore: VectorStoreConfig
+    llm_params: LLMParams
+    chat_logging: ChatLoggingConfig
+    splitter_options: SplitterOptions
+    retriever: RetrieverConfig
+    metadata: MetadataConfig
+    token_config: TokenConfig
+    misc: MiscConfig
+    api_config: APIConfig
+
+
+class ConfigManager:
+    def __init__(self, config_path: str, project_config_path: str):
+        self.config_path = config_path
+        self.project_config_path = project_config_path
+        self.config = self.load_config()
+        self.validate_config()
+
+    def load_config(self) -> Config:
+        with open(self.config_path, "r") as f:
+            config_data = yaml.safe_load(f)
+
+        with open(self.project_config_path, "r") as f:
+            project_config_data = yaml.safe_load(f)
+
+        # Merge the two configurations
+        merged_config = {**config_data, **project_config_data}
+
+        return Config(**merged_config)
+
+    def get_config(self) -> Config:
+        return ConfigWrapper(self.config)
+
+    def validate_config(self):
+        # If any required fields are missing, raise an error
+        # required_fields = [
+        #     "vectorstore", "llm_params", "chat_logging", "splitter_options",
+        #     "retriever", "metadata", "token_config", "misc", "api_config"
+        # ]
+        # for field in required_fields:
+        #     if not hasattr(self.config, field):
+        #         raise ValueError(f"Missing required configuration field: {field}")
+
+        # # Validate types of specific fields
+        # if not isinstance(self.config.vectorstore, VectorStoreConfig):
+        #     raise TypeError("vectorstore must be an instance of VectorStoreConfig")
+        # if not isinstance(self.config.llm_params, LLMParams):
+        #     raise TypeError("llm_params must be an instance of LLMParams")
+        pass
+
+
+class ConfigWrapper:
+    def __init__(self, config: Config):
+        self._config = config
+
+    def __getitem__(self, key):
+        return getattr(self._config, key)
+
+    def __getattr__(self, name):
+        return getattr(self._config, name)
+
+    def dict(self):
+        return self._config.dict()
+
+
+# Usage
+config_manager = ConfigManager(
+    config_path="config/config.yml", project_config_path="config/project_config.yml"
+)
+# config = config_manager.get_config().dict()

apps/ai_tutor/config/constants.py

@@ -0,0 +1,26 @@
+from dotenv import load_dotenv
+import os
+
+load_dotenv()
+
+# API Keys - Loaded from the .env file
+
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
+LLAMA_CLOUD_API_KEY = os.getenv("LLAMA_CLOUD_API_KEY")
+HUGGINGFACE_TOKEN = os.getenv("HUGGINGFACE_TOKEN")
+LITERAL_API_KEY_LOGGING = os.getenv("LITERAL_API_KEY_LOGGING")
+LITERAL_API_URL = os.getenv("LITERAL_API_URL")
+CHAINLIT_URL = os.getenv("CHAINLIT_URL")
+EMAIL_ENCRYPTION_KEY = os.getenv("EMAIL_ENCRYPTION_KEY")
+
+OAUTH_GOOGLE_CLIENT_ID = os.getenv("OAUTH_GOOGLE_CLIENT_ID")
+OAUTH_GOOGLE_CLIENT_SECRET = os.getenv("OAUTH_GOOGLE_CLIENT_SECRET")
+
+opening_message = "Hey, What Can I Help You With?\n\nYou can me ask me questions about the course logistics, course content, about the final project, or anything else!"
+chat_end_message = (
+    "I hope I was able to help you. If you have any more questions, feel free to ask!"
+)
+
+# Model Paths
+
+LLAMA_PATH = "../storage/models/tinyllama"

apps/ai_tutor/config/project_config.yml

@@ -0,0 +1,20 @@
+retriever:
+  retriever_hf_paths:
+    RAGatouille: "XThomasBU/Colbert_Index"
+
+metadata:
+  metadata_links: ["https://dl4ds.github.io/sp2024/lectures/", "https://dl4ds.github.io/sp2024/schedule/"]
+  slide_base_link: "https://dl4ds.github.io"
+
+token_config:
+  cooldown_time: 60
+  regen_time: 180
+  tokens_left: 2000
+  all_time_tokens_allocated: 1000000
+
+misc:
+  github_repo: "https://github.com/edubotics-ai/edubot-core"
+  docs_website: "https://dl4ds.github.io/dl4ds_tutor/"
+
+api_config:
+  timeout: 60

apps/ai_tutor/config/prompts.py

@@ -0,0 +1,97 @@
+prompts = {
+    "openai": {
+        "rephrase_prompt": (
+            "You are someone that rephrases statements. Rephrase the student's question to add context from their chat history if relevant, ensuring it remains from the student's point of view. "
+            "Incorporate relevant details from the chat history to make the question clearer and more specific. "
+            "Do not change the meaning of the original statement, and maintain the student's tone and perspective. "
+            "If the question is conversational and doesn't require context, do not rephrase it. "
+            "Example: If the student previously asked about backpropagation in the context of deep learning and now asks 'what is it', rephrase to 'What is backpropagation.'. "
+            "Example: Do not rephrase if the user is asking something specific like 'cool, suggest a project with transformers to use as my final project' "
+            "Chat history: \n{chat_history}\n"
+            "Rephrase the following question only if necessary: '{input}'"
+            "Rephrased Question:'"
+        ),
+        "prompt_with_history": {
+            "normal": (
+                "You are an AI Tutor for the course DS598, taught by Prof. Thomas Gardos. Answer the user's question using the provided context. Only use the context if it is relevant. The context is ordered by relevance. "
+                "If you don't know the answer, do your best without making things up. Keep the conversation flowing naturally. "
+                "Use chat history and context as guides but avoid repeating past responses. Provide links from the source_file metadata. Use the source context that is most relevant. "
+                "Render math equations in LaTeX format between $ or $$ signs, stick to the parameter and variable icons found in your context. Be sure to explain the parameters and variables in the equations."
+                "Speak in a friendly and engaging manner, like talking to a friend. Avoid sounding repetitive or robotic.\n\n"
+                "Do not get influenced by the style of conversation in the chat history. Follow the instructions given here."
+                "Chat History:\n{chat_history}\n\n"
+                "Context:\n{context}\n\n"
+                "Answer the student's question below in a friendly, concise, and engaging manner. Use the context and history only if relevant, otherwise, engage in a free-flowing conversation.\n"
+                "Student: {input}\n"
+                "AI Tutor:"
+            ),
+            "eli5": (
+                "You are an AI Tutor for the course DS598, taught by Prof. Thomas Gardos. Your job is to explain things in the simplest and most engaging way possible, just like the 'Explain Like I'm 5' (ELI5) concept."
+                "If you don't know the answer, do your best without making things up. Keep your explanations straightforward and very easy to understand."
+                "Use the chat history and context to help you, but avoid repeating past responses. Provide links from the source_file metadata when they're helpful."
+                "Use very simple language and examples to explain any math equations, and put the equations in LaTeX format between $ or $$ signs."
+                "Be friendly and engaging, like you're chatting with a young child who's curious and eager to learn. Avoid complex terms and jargon."
+                "Include simple and clear examples wherever you can to make things easier to understand."
+                "Do not get influenced by the style of conversation in the chat history. Follow the instructions given here."
+                "Chat History:\n{chat_history}\n\n"
+                "Context:\n{context}\n\n"
+                "Answer the student's question below in a friendly, simple, and engaging way, just like the ELI5 concept. Use the context and history only if they're relevant, otherwise, just have a natural conversation."
+                "Give a clear and detailed explanation with simple examples to make it easier to understand. Remember, your goal is to break down complex topics into very simple terms, just like ELI5."
+                "Student: {input}\n"
+                "AI Tutor:"
+            ),
+            "socratic": (
+                "You are an AI Tutor for the course DS598, taught by Prof. Thomas Gardos. Engage the student in a Socratic dialogue to help them discover answers on their own. Use the provided context to guide your questioning."
+                "If you don't know the answer, do your best without making things up. Keep the conversation engaging and inquisitive."
+                "Use chat history and context as guides but avoid repeating past responses. Provide links from the source_file metadata when relevant. Use the source context that is most relevant."
+                "Speak in a friendly and engaging manner, encouraging critical thinking and self-discovery."
+                "Use questions to lead the student to explore the topic and uncover answers."
+                "Chat History:\n{chat_history}\n\n"
+                "Context:\n{context}\n\n"
+                "Answer the student's question below by guiding them through a series of questions and insights that lead to deeper understanding. Use the context and history only if relevant, otherwise, engage in a free-flowing conversation."
+                "Foster an inquisitive mindset and help the student discover answers through dialogue."
+                "Student: {input}\n"
+                "AI Tutor:"
+            ),
+        },
+        "prompt_no_history": (
+            "You are an AI Tutor for the course DS598, taught by Prof. Thomas Gardos. Answer the user's question using the provided context. Only use the context if it is relevant. The context is ordered by relevance. "
+            "If you don't know the answer, do your best without making things up. Keep the conversation flowing naturally. "
+            "Provide links from the source_file metadata. Use the source context that is most relevant. "
+            "Speak in a friendly and engaging manner, like talking to a friend. Avoid sounding repetitive or robotic.\n\n"
+            "Context:\n{context}\n\n"
+            "Answer the student's question below in a friendly, concise, and engaging manner. Use the context and history only if relevant, otherwise, engage in a free-flowing conversation.\n"
+            "Student: {input}\n"
+            "AI Tutor:"
+        ),
+    },
+    "tiny_llama": {
+        "prompt_no_history": (
+            "system\n"
+            "Assistant is an intelligent chatbot designed to help students with questions regarding the course DS598, taught by Prof. Thomas Gardos. Answer the user's question using the provided context. Only use the context if it is relevant. The context is ordered by relevance.\n"
+            "If you don't know the answer, do your best without making things up. Keep the conversation flowing naturally.\n"
+            "Provide links from the source_file metadata. Use the source context that is most relevant.\n"
+            "Speak in a friendly and engaging manner, like talking to a friend. Avoid sounding repetitive or robotic.\n"
+            "\n\n"
+            "user\n"
+            "Context:\n{context}\n\n"
+            "Question: {input}\n"
+            "\n\n"
+            "assistant"
+        ),
+        "prompt_with_history": (
+            "system\n"
+            "You are an AI Tutor for the course DS598, taught by Prof. Thomas Gardos. Answer the user's question using the provided context. Only use the context if it is relevant. The context is ordered by relevance. "
+            "If you don't know the answer, do your best without making things up. Keep the conversation flowing naturally. "
+            "Use chat history and context as guides but avoid repeating past responses. Provide links from the source_file metadata. Use the source context that is most relevant. "
+            "Speak in a friendly and engaging manner, like talking to a friend. Avoid sounding repetitive or robotic.\n"
+            "\n\n"
+            "user\n"
+            "Chat History:\n{chat_history}\n\n"
+            "Context:\n{context}\n\n"
+            "Question: {input}\n"
+            "\n\n"
+            "assistant"
+        ),
+    },
+}

apps/ai_tutor/encrypt_students.py

@@ -0,0 +1,53 @@
+import os
+import hashlib
+import json
+import argparse
+from dotenv import load_dotenv
+
+
+# Function to deterministically hash emails
+def deterministic_hash(email, salt):
+    return hashlib.pbkdf2_hmac("sha256", email.encode(), salt, 100000).hex()
+
+
+def main(args):
+    # Load the .env file
+    load_dotenv()
+
+    # Get the encryption key (salt)
+    encryption_salt = os.getenv("EMAIL_ENCRYPTION_KEY").encode()
+
+    # Load emails from the specified JSON file
+    with open(args.students_file, "r") as file:
+        emails = json.load(file)
+
+    # Replace emails with deterministic hashed emails, {hashed_email: [roles]}
+    hashed_emails = {
+        deterministic_hash(email, encryption_salt): roles
+        for email, roles in emails.items()
+    }
+
+    # Save hashed emails to the specified encrypted JSON file
+    with open(args.encrypted_students_file, "w") as file:
+        json.dump(hashed_emails, file)
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description="Encrypt student emails in a JSON file."
+    )
+    parser.add_argument(
+        "--students-file",
+        type=str,
+        default="private/students.json",
+        help="Path to the students JSON file",
+    )
+    parser.add_argument(
+        "--encrypted-students-file",
+        type=str,
+        default="public/files/students_encrypted.json",
+        help="Path to save the encrypted students JSON file",
+    )
+    args = parser.parse_args()
+
+    main(args)

apps/ai_tutor/helpers.py

@@ -0,0 +1,90 @@
+from datetime import datetime, timedelta, timezone
+import tiktoken
+from edubotics_core.chat_processor.helpers import update_user_info, convert_to_dict
+
+
+def get_time():
+    return datetime.now(timezone.utc).isoformat()
+
+
+async def check_user_cooldown(
+    user_info, current_time, COOLDOWN_TIME, TOKENS_LEFT, REGEN_TIME
+):
+    # # Check if no tokens left
+    tokens_left = user_info.metadata.get("tokens_left", 0)
+    if tokens_left > 0 and not user_info.metadata.get("in_cooldown", False):
+        return False, None
+
+    user_info = convert_to_dict(user_info)
+    last_message_time_str = user_info["metadata"].get("last_message_time")
+
+    # Convert from ISO format string to datetime object and ensure UTC timezone
+    last_message_time = datetime.fromisoformat(last_message_time_str).replace(
+        tzinfo=timezone.utc
+    )
+    current_time = datetime.fromisoformat(current_time).replace(tzinfo=timezone.utc)
+
+    # Calculate the elapsed time
+    elapsed_time = current_time - last_message_time
+    elapsed_time_in_seconds = elapsed_time.total_seconds()
+
+    # Calculate when the cooldown period ends
+    cooldown_end_time = last_message_time + timedelta(seconds=COOLDOWN_TIME)
+    cooldown_end_time_iso = cooldown_end_time.isoformat()
+
+    # Check if the user is still in cooldown
+    if elapsed_time_in_seconds < COOLDOWN_TIME:
+        return True, cooldown_end_time_iso  # Return in ISO 8601 format
+
+    user_info["metadata"]["in_cooldown"] = False
+    # If not in cooldown, regenerate tokens
+    await reset_tokens_for_user(user_info, TOKENS_LEFT, REGEN_TIME)
+
+    return False, None
+
+
+async def reset_tokens_for_user(user_info, TOKENS_LEFT, REGEN_TIME):
+    user_info = convert_to_dict(user_info)
+    last_message_time_str = user_info["metadata"].get("last_message_time")
+
+    last_message_time = datetime.fromisoformat(last_message_time_str).replace(
+        tzinfo=timezone.utc
+    )
+    current_time = datetime.fromisoformat(get_time()).replace(tzinfo=timezone.utc)
+
+    # Calculate the elapsed time since the last message
+    elapsed_time_in_seconds = (current_time - last_message_time).total_seconds()
+
+    # Current token count (can be negative)
+    current_tokens = user_info["metadata"].get("tokens_left_at_last_message", 0)
+    current_tokens = min(current_tokens, TOKENS_LEFT)
+
+    # Maximum tokens that can be regenerated
+    max_tokens = user_info["metadata"].get("max_tokens", TOKENS_LEFT)
+
+    # Calculate how many tokens should have been regenerated proportionally
+    if current_tokens < max_tokens:
+        # Calculate the regeneration rate per second based on REGEN_TIME for full regeneration
+        # If current_tokens is close to 0, then the regeneration rate is relatively high, and if current_tokens is close to max_tokens, then the regeneration rate is relatively low
+        regeneration_rate_per_second = (
+            max_tokens - max(current_tokens, 0)
+        ) / REGEN_TIME
+
+        # Calculate how many tokens should have been regenerated based on the elapsed time
+        tokens_to_regenerate = int(
+            elapsed_time_in_seconds * regeneration_rate_per_second
+        )
+
+        # Ensure the new token count does not exceed max_tokens
+        new_token_count = min(current_tokens + tokens_to_regenerate, max_tokens)
+
+        # Update the user's token count
+        user_info["metadata"]["tokens_left"] = new_token_count
+
+        await update_user_info(user_info)
+
+
+def get_num_tokens(text, model):
+    encoding = tiktoken.encoding_for_model(model)
+    tokens = encoding.encode(text)
+    return len(tokens)

apps/ai_tutor/private/placeholder_students_file.json

@@ -0,0 +1,5 @@
+{
+    "[email protected]": ["student", "bu"],
+    "[email protected]": ["student", "bu"],
+    "[email protected]": ["admin", "instructor", "bu"]
+}

apps/ai_tutor/public/files/students_encrypted.json

@@ -0,0 +1 @@
+{"0645db6f7b415e3b04a4fc327151c3c7bbcd25ec546ee0b3604957b571a79bc2": ["instructor", "bu"], "51ebf87ac51618300acfef8bfa9768fdee40e2d3f39cfb4ae8a76722ee336de4": ["admin", "instructor", "bu"], "7810b25bef84317130e2a59da978ee716bb96f6a8a9296c051b7ad4108aa8e6a": ["instructor", "bu"], "a95f36e2700c554639d3522834b47733f5ed1f05c5a43d04ac2575571dd43563": ["student", "bu"]}

apps/ai_tutor/public/files/test.css

@@ -0,0 +1,32 @@
+a[href*='https://github.com/Chainlit/chainlit'] {
+    visibility: hidden;
+}
+
+/* Hide the default avatar image */ 
+.MuiAvatar-root img.MuiAvatar-img {
+    display: none;
+  }
+  
+/* Target the container of the image and set a custom background image */
+.MuiAvatar-root.MuiAvatar-circular.css-m2icte {
+    background-image: url('/public/assets/images/avatars/ai-tutor.png'); /* Replace with your custom image URL */
+    background-size: cover; /* Ensure the image covers the entire container */
+    background-position: center; /* Center the image */
+    width: 100px; /* Ensure the dimensions match the original */
+    height: 100px; /* Ensure the dimensions match the original */
+    border-radius: 50%; /* Maintain circular shape */
+}
+.MuiAvatar-root.MuiAvatar-circular.css-v72an7 {
+    background-image: url('/public/assets/images/avatars/ai-tutor.png'); /* Replace with your custom image URL */
+    background-size: cover; /* Ensure the image covers the entire container */
+    background-position: center; /* Center the image */
+    width: 40px; /* Ensure the dimensions match the original */
+    height: 40px; /* Ensure the dimensions match the original */
+    border-radius: 50%; /* Maintain circular shape */
+}
+
+.MuiStack-root.css-14k6mw7 img {
+    content: url('/public/assets/images/avatars/ai-tutor.png'); /* Replace with the path to your custom image */
+    max-height: 45px; /* Ensure the height remains consistent */
+    max-width: 45px; /* Ensure the width remains consistent */
+}

apps/ai_tutor/storage/data/urls.txt

@@ -0,0 +1 @@
+https://dl4ds.github.io/sp2024/

apps/ai_tutor/templates/cooldown.html

@@ -0,0 +1,181 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Cooldown Period | Terrier Tutor</title>
+    <style>
+        @import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;600&display=swap');
+
+        body, html {
+            margin: 0;
+            padding: 0;
+            font-family: 'Inter', sans-serif;
+            background-color: #f7f7f7;
+            background-image: url('https://www.transparenttextures.com/patterns/cubes.png');
+            background-repeat: repeat;
+            display: flex;
+            align-items: center;
+            justify-content: center;
+            height: 100vh;
+            color: #333;
+        }
+
+        .container {
+            background: rgba(255, 255, 255, 0.9);
+            border: 1px solid #ddd;
+            border-radius: 8px;
+            width: 100%;
+            max-width: 400px;
+            padding: 50px;
+            box-sizing: border-box;
+            text-align: center;
+            box-shadow: 0 4px 15px rgba(0, 0, 0, 0.1);
+            backdrop-filter: blur(10px);
+            -webkit-backdrop-filter: blur(10px);
+        }
+
+        .avatar {
+            width: 90px;
+            height: 90px;
+            border-radius: 50%;
+            margin-bottom: 25px;
+            border: 2px solid #ddd;
+        }
+
+        .container h1 {
+            margin-bottom: 15px;
+            font-size: 24px;
+            font-weight: 600;
+            color: #1a1a1a;
+        }
+
+        .container p {
+            font-size: 16px;
+            color: #4a4a4a;
+            margin-bottom: 30px;
+            line-height: 1.5;
+        }
+
+        .cooldown-message {
+            font-size: 16px;
+            color: #333;
+            margin-bottom: 30px;
+        }
+
+        .tokens-left {
+            font-size: 14px;
+            color: #333;
+            margin-bottom: 30px;
+            font-weight: 600;
+        }
+
+        .button {
+            padding: 12px 0;
+            margin: 12px 0;
+            font-size: 14px;
+            border-radius: 6px;
+            cursor: pointer;
+            width: 100%;
+            border: 1px solid #4285F4;
+            background-color: #fff;
+            color: #4285F4;
+            transition: background-color 0.3s ease, border-color 0.3s ease;
+            display: none;
+        }
+
+        .button.start-tutor {
+            display: none;
+        }
+
+        .button:hover {
+            background-color: #e0e0e0;
+            border-color: #357ae8;
+        }
+
+        .sign-out-button {
+            border: 1px solid #FF4C4C;
+            background-color: #fff;
+            color: #FF4C4C;
+            display: block;
+        }
+
+        .sign-out-button:hover {
+            background-color: #ffe6e6;
+            border-color: #e04343;
+            color: #e04343;
+        }
+
+        #countdown {
+            font-size: 14px;
+            color: #555;
+            margin-bottom: 20px;
+        }
+
+        .footer {
+            font-size: 12px;
+            color: #777;
+            margin-top: 20px;
+        }
+    </style>
+</head>
+<body>
+    <div class="container">
+        <img src="/public/assets/images/avatars/ai-tutor.png" alt="AI Tutor Avatar" class="avatar">
+        <h1>Hello, {{ username }}</h1>
+        <p>It seems like you need to wait a bit before starting a new session.</p>
+        <p class="cooldown-message">Time remaining until the cooldown period ends:</p>
+        <p id="countdown"></p>
+        <p class="tokens-left">Tokens Left: <span id="tokensLeft">{{ tokens_left }}</span></p>
+        <button id="startTutorBtn" class="button start-tutor" onclick="startTutor()">Start AI Tutor</button>
+        <form action="/logout" method="get">
+            <button type="submit" class="button sign-out-button">Sign Out</button>
+        </form>
+        <div class="footer">Reload the page to update token stats</div>
+    </div>
+    <script>
+        function startCountdown(endTime) {
+            const countdownElement = document.getElementById('countdown');
+            const startTutorBtn = document.getElementById('startTutorBtn');
+            const endTimeDate = new Date(endTime);
+
+            function updateCountdown() {
+                const now = new Date();
+                const timeLeft = endTimeDate.getTime() - now.getTime();
+
+                if (timeLeft <= 0) {
+                    countdownElement.textContent = "Cooldown period has ended.";
+                    startTutorBtn.style.display = "block";
+                } else {
+                    const hours = Math.floor(timeLeft / 1000 / 60 / 60);
+                    const minutes = Math.floor((timeLeft / 1000 / 60) % 60);
+                    const seconds = Math.floor((timeLeft / 1000) % 60);
+                    countdownElement.textContent = `${hours}h ${minutes}m ${seconds}s`;
+                }
+            }
+
+            updateCountdown();
+            setInterval(updateCountdown, 1000);
+        }
+
+        function startTutor() {
+            window.location.href = "/start-tutor";
+        }
+
+        function updateTokensLeft() {
+            fetch('/get-tokens-left')
+                .then(response => response.json())
+                .then(data => {
+                    document.getElementById('tokensLeft').textContent = data.tokens_left;
+                })
+                .catch(error => console.error('Error fetching tokens:', error));
+        }
+
+        // Start the countdown
+        startCountdown("{{ cooldown_end_time }}");
+
+        // Update tokens left when the page loads
+        updateTokensLeft();
+    </script>
+</body>
+</html>

apps/ai_tutor/templates/dashboard.html

@@ -0,0 +1,145 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Dashboard | Terrier Tutor</title>
+    <style>
+        @import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;600&display=swap');
+
+        body, html {
+            margin: 0;
+            padding: 0;
+            font-family: 'Inter', sans-serif;
+            background-color: #f7f7f7; /* Light gray background */
+            background-image: url('https://www.transparenttextures.com/patterns/cubes.png'); /* Subtle geometric pattern */
+            background-repeat: repeat;
+            display: flex;
+            align-items: center;
+            justify-content: center;
+            height: 100vh;
+            color: #333;
+        }
+
+        .container {
+            background: rgba(255, 255, 255, 0.9);
+            border: 1px solid #ddd;
+            border-radius: 8px;
+            width: 100%;
+            max-width: 400px;
+            padding: 40px;
+            box-sizing: border-box;
+            text-align: center;
+            box-shadow: 0 4px 15px rgba(0, 0, 0, 0.1);
+            backdrop-filter: blur(10px);
+            -webkit-backdrop-filter: blur(10px);
+        }
+
+        .avatar {
+            width: 90px;
+            height: 90px;
+            border-radius: 50%;
+            margin-bottom: 20px;
+            border: 2px solid #ddd;
+        }
+
+        .container h1 {
+            margin-bottom: 20px;
+            font-size: 26px;
+            font-weight: 600;
+            color: #1a1a1a;
+        }
+
+        .container p {
+            font-size: 15px;
+            color: #4a4a4a;
+            margin-bottom: 25px;
+            line-height: 1.5;
+        }
+
+        .tokens-left {
+            font-size: 17px;
+            color: #333;
+            margin-bottom: 10px;
+            font-weight: 600;
+        }
+
+        .all-time-tokens {
+            font-size: 14px; /* Reduced font size */
+            color: #555;
+            margin-bottom: 30px;
+            font-weight: 500;
+            white-space: nowrap; /* Prevents breaking to a new line */
+        }
+
+        .button {
+            padding: 12px 0;
+            margin: 12px 0;
+            font-size: 15px;
+            border-radius: 6px;
+            cursor: pointer;
+            width: 100%;
+            border: 1px solid #4285F4; /* Button border color */
+            background-color: #fff; /* Button background color */
+            color: #4285F4; /* Button text color */
+            transition: background-color 0.3s ease, border-color 0.3s ease;
+        }
+
+        .button:hover {
+            background-color: #e0e0e0;
+            border-color: #357ae8; /* Darker blue for hover */
+        }
+
+        .start-button {
+            border: 1px solid #4285F4;
+            color: #4285F4;
+            background-color: #fff;
+        }
+
+        .start-button:hover {
+            background-color: #e0f0ff; /* Light blue on hover */
+            border-color: #357ae8; /* Darker blue for hover */
+            color: #357ae8; /* Blue text on hover */
+        }
+
+        .sign-out-button {
+            border: 1px solid #FF4C4C;
+            background-color: #fff;
+            color: #FF4C4C;
+        }
+
+        .sign-out-button:hover {
+            background-color: #ffe6e6; /* Light red on hover */
+            border-color: #e04343; /* Darker red for hover */
+            color: #e04343; /* Red text on hover */
+        }
+
+        .footer {
+            font-size: 12px;
+            color: #777;
+            margin-top: 25px;
+        }
+    </style>
+</head>
+<body>
+    <div class="container">
+        <img src="/public/assets/images/avatars/ai-tutor.png" alt="AI Tutor Avatar" class="avatar">
+        <h1>Welcome, {{ username }}</h1>
+        <p>Ready to start your AI tutoring session?</p>
+        <p class="tokens-left">Tokens Left: {{ tokens_left }}</p>
+        <p class="all-time-tokens">All-Time Tokens Allocated: {{ all_time_tokens_allocated }} / {{ total_tokens_allocated }}</p>
+        <form action="/start-tutor" method="post">
+            <button type="submit" class="button start-button">Start AI Tutor</button>
+        </form>
+        <form action="/logout" method="get">
+            <button type="submit" class="button sign-out-button">Sign Out</button>
+        </form>
+        <div class="footer">Reload the page to update token stats</div>
+    </div>
+    <script>
+        let token = "{{ jwt_token }}";
+        console.log("Token: ", token);
+        localStorage.setItem('token', token);
+    </script>
+</body>
+</html>

apps/ai_tutor/templates/error.html

@@ -0,0 +1,95 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Error | Terrier Tutor</title>
+    <style>
+        @import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;600&display=swap');
+
+        body, html {
+            margin: 0;
+            padding: 0;
+            font-family: 'Inter', sans-serif;
+            background-color: #f7f7f7; /* Light gray background */
+            background-image: url('https://www.transparenttextures.com/patterns/cubes.png'); /* Subtle geometric pattern */
+            background-repeat: repeat;
+            display: flex;
+            align-items: center;
+            justify-content: center;
+            height: 100vh;
+            color: #333;
+        }
+
+        .container {
+            background: rgba(255, 255, 255, 0.9);
+            border: 1px solid #ddd;
+            border-radius: 8px;
+            width: 100%;
+            max-width: 400px;
+            padding: 50px;
+            box-sizing: border-box;
+            text-align: center;
+            box-shadow: 0 4px 15px rgba(0, 0, 0, 0.1);
+            backdrop-filter: blur(10px);
+            -webkit-backdrop-filter: blur(10px);
+        }
+
+        .container h1 {
+            margin-bottom: 20px;
+            font-size: 26px;
+            font-weight: 600;
+            color: #1a1a1a;
+        }
+
+        .container p {
+            font-size: 18px;
+            color: #4a4a4a;
+            margin-bottom: 35px;
+            line-height: 1.5;
+        }
+
+        .button {
+            padding: 14px 0;
+            margin: 12px 0;
+            font-size: 16px;
+            border-radius: 6px;
+            cursor: pointer;
+            width: 100%;
+            border: 1px solid #ccc;
+            background-color: #007BFF;
+            color: #fff;
+            transition: background-color 0.3s ease, border-color 0.3s ease;
+        }
+
+        .button:hover {
+            background-color: #0056b3;
+            border-color: #0056b3;
+        }
+
+        .error-box {
+            background-color: #2d2d2d;
+            color: #fff;
+            padding: 10px;
+            margin-top: 20px;
+            font-family: 'Courier New', Courier, monospace;
+            text-align: left;
+            overflow-x: auto;
+            white-space: pre-wrap;
+            border-radius: 5px;
+        }
+    </style>
+</head>
+<body>
+    <div class="container">
+        <h1>Oops! Something went wrong...</h1>
+        <p>An unexpected error occurred. The details are below:</p>
+        <div class="error-box">
+            <code>{{ error }}</code>
+        </div>
+        <form action="/" method="get">
+            <button type="submit" class="button">Return to Home</button>
+        </form>
+    </div>
+</body>
+</html>

apps/ai_tutor/templates/error_404.html

@@ -0,0 +1,80 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>404 - Not Found</title>
+    <style>
+        @import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;600&display=swap');
+
+        body, html {
+            margin: 0;
+            padding: 0;
+            font-family: 'Inter', sans-serif;
+            background-color: #f7f7f7; /* Light gray background */
+            background-image: url('https://www.transparenttextures.com/patterns/cubes.png'); /* Subtle geometric pattern */
+            background-repeat: repeat;
+            display: flex;
+            align-items: center;
+            justify-content: center;
+            height: 100vh;
+            color: #333;
+        }
+
+        .container {
+            background: rgba(255, 255, 255, 0.9);
+            border: 1px solid #ddd;
+            border-radius: 8px;
+            width: 100%;
+            max-width: 400px;
+            padding: 50px;
+            box-sizing: border-box;
+            text-align: center;
+            box-shadow: 0 4px 15px rgba(0, 0, 0, 0.1);
+            backdrop-filter: blur(10px);
+            -webkit-backdrop-filter: blur(10px);
+        }
+
+        .container h1 {
+            margin-bottom: 20px;
+            font-size: 26px;
+            font-weight: 600;
+            color: #1a1a1a;
+        }
+
+        .container p {
+            font-size: 18px;
+            color: #4a4a4a;
+            margin-bottom: 35px;
+            line-height: 1.5;
+        }
+
+        .button {
+            padding: 14px 0;
+            margin: 12px 0;
+            font-size: 16px;
+            border-radius: 6px;
+            cursor: pointer;
+            width: 100%;
+            border: 1px solid #ccc;
+            background-color: #007BFF;
+            color: #fff;
+            transition: background-color 0.3s ease, border-color 0.3s ease;
+        }
+
+        .button:hover {
+            background-color: #0056b3;
+            border-color: #0056b3;
+        }
+    </style>
+</head>
+<body>
+    <div class="container">
+        <h1>You have ventured into the abyss...</h1>
+        <p>To get back to reality, click the button below.</p>
+        <form action="/" method="get">
+            <button type="submit" class="button">Return to Home</button>
+        </form>
+    </div>
+</body>
+</html>

apps/ai_tutor/templates/login.html

@@ -0,0 +1,132 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Login | Terrier Tutor</title>
+    <style>
+        @import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;600&display=swap');
+
+        body, html {
+            margin: 0;
+            padding: 0;
+            font-family: 'Inter', sans-serif;
+            background-color: #f7f7f7; /* Light gray background */
+            background-image: url('https://www.transparenttextures.com/patterns/cubes.png'); /* Subtle geometric pattern */
+            background-repeat: repeat;
+            display: flex;
+            align-items: center;
+            justify-content: center;
+            height: 100vh;
+            color: #333;
+        }
+
+        .container {
+            background: rgba(255, 255, 255, 0.9);
+            border: 1px solid #ddd;
+            border-radius: 8px;
+            width: 100%;
+            max-width: 400px;
+            padding: 50px;
+            box-sizing: border-box;
+            text-align: center;
+            box-shadow: 0 4px 15px rgba(0, 0, 0, 0.1);
+            backdrop-filter: blur(10px);
+            -webkit-backdrop-filter: blur(10px);
+        }
+
+        .avatar {
+            width: 90px;
+            height: 90px;
+            border-radius: 50%;
+            margin-bottom: 25px;
+            border: 2px solid #ddd;
+        }
+
+        .container h1 {
+            margin-bottom: 15px;
+            font-size: 24px;
+            font-weight: 600;
+            color: #1a1a1a;
+        }
+
+        .container p {
+            font-size: 16px;
+            color: #4a4a4a;
+            margin-bottom: 30px;
+            line-height: 1.5;
+        }
+
+        .button {
+            padding: 12px 0;
+            margin: 12px 0;
+            font-size: 14px;
+            border-radius: 6px;
+            cursor: pointer;
+            width: 100%;
+            border: 1px solid #4285F4; /* Google button border color */
+            background-color: #fff; /* Guest button color */
+            color: #4285F4; /* Google button text color */
+            transition: background-color 0.3s ease, border-color 0.3s ease;
+        }
+
+        .button:hover {
+            background-color: #e0f0ff; /* Light blue on hover */
+            border-color: #357ae8; /* Darker blue for hover */
+            color: #357ae8; /* Blue text on hover */
+        }
+
+        .footer {
+            margin-top: 40px;
+            font-size: 15px;
+            color: #666;
+            text-align: center; /* Center the text in the footer */
+        }
+
+        .footer a {
+            color: #333;
+            text-decoration: none;
+            font-weight: 500;
+            display: inline-flex;
+            align-items: center;
+            justify-content: center; /* Center the content of the links */
+            transition: color 0.3s ease;
+            margin-bottom: 8px;
+            width: 100%; /* Make the link block level */
+        }
+
+        .footer a:hover {
+            color: #000;
+        }
+
+        .footer svg {
+            margin-right: 8px;
+            fill: currentColor;
+        }
+    </style>
+</head>
+<body>
+    <div class="container">
+        <img src="/public/assets/images/avatars/ai-tutor.png" alt="AI Tutor Avatar" class="avatar">
+        <h1>Terrier Tutor</h1>
+        <p>Welcome to the DS598 AI Tutor. Please sign in to continue.</p>
+        <form action="/login/google" method="get">
+            <button type="submit" class="button">Sign in with Google</button>
+        </form>
+        <div class="footer">
+            <a href="{{ GITHUB_REPO }}" target="_blank">
+                <svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 24 24">
+                    <path d="M12 .5C5.596.5.5 5.596.5 12c0 5.098 3.292 9.414 7.852 10.94.574.105.775-.249.775-.553 0-.272-.01-1.008-.015-1.98-3.194.694-3.87-1.544-3.87-1.544-.521-1.324-1.273-1.676-1.273-1.676-1.04-.714.079-.7.079-.7 1.148.08 1.75 1.181 1.75 1.181 1.022 1.752 2.683 1.246 3.34.954.104-.74.4-1.246.73-1.533-2.551-.292-5.234-1.276-5.234-5.675 0-1.253.447-2.277 1.181-3.079-.12-.293-.51-1.47.113-3.063 0 0 .96-.307 3.15 1.174.913-.255 1.892-.383 2.867-.388.975.005 1.954.133 2.868.388 2.188-1.481 3.147-1.174 3.147-1.174.624 1.593.233 2.77.114 3.063.735.802 1.18 1.826 1.18 3.079 0 4.407-2.688 5.38-5.248 5.668.413.354.782 1.049.782 2.113 0 1.526-.014 2.757-.014 3.132 0 .307.198.662.783.553C20.21 21.411 23.5 17.096 23.5 12c0-6.404-5.096-11.5-11.5-11.5z"/>
+                </svg>
+                View on GitHub
+            </a>
+            <a href="{{ DOCS_WEBSITE }}" target="_blank">
+                <svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 24 24">
+                    <path d="M19 2H8c-1.103 0-2 .897-2 2v16c0 1.103.897 2 2 2h12c1.103 0 2-.897 2-2V7l-5-5zm0 2l.001 4H14V4h5zm-1 14H9V4h4v6h6v8zM7 4H6v16c0 1.654 1.346 3 3 3h9v-2H9c-.551 0-1-.449-1-1V4z"/>
+                </svg>
+                View Docs
+            </a>
+        </div>
+    </div>
+</body>
+</html>

apps/ai_tutor/templates/logout.html

@@ -0,0 +1,21 @@
+<!DOCTYPE html>
+<html>
+<head>
+    <title>Logout</title>
+    <script>
+        window.onload = function() {
+            fetch('/chainlit_tutor/logout', {
+                method: 'POST',
+                credentials: 'include'  // Ensure cookies are sent
+            }).then(() => {
+                window.location.href = '/';
+            }).catch(error => {
+                console.error('Logout failed:', error);
+            });
+        };
+    </script>
+</head>
+<body>
+    <p>Logging out... If you are not redirected, <a href="/">click here</a>.</p>
+</body>
+</html>

apps/ai_tutor/templates/unauthorized.html

@@ -0,0 +1,94 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Access Restricted</title>
+    <style>
+        @import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;600&display=swap');
+
+        body, html {
+            margin: 0;
+            padding: 0;
+            font-family: 'Inter', sans-serif;
+            background-color: #f7f7f7; /* Light gray background */
+            background-image: url('https://www.transparenttextures.com/patterns/cubes.png'); /* Subtle geometric pattern */
+            background-repeat: repeat;
+            display: flex;
+            align-items: center;
+            justify-content: center;
+            height: 100vh;
+            color: #333;
+        }
+
+        .container {
+            background: rgba(255, 255, 255, 0.9);
+            border: 1px solid #ddd;
+            border-radius: 8px;
+            width: 100%;
+            max-width: 400px;
+            padding: 50px;
+            box-sizing: border-box;
+            text-align: center;
+            box-shadow: 0 4px 15px rgba(0, 0, 0, 0.1);
+            backdrop-filter: blur(10px);
+            -webkit-backdrop-filter: blur(10px);
+        }
+
+        .avatar {
+            width: 90px;
+            height: 90px;
+            border-radius: 50%;
+            margin-bottom: 25px;
+            border: 2px solid #ddd;
+        }
+
+        .container h1 {
+            margin-bottom: 20px;
+            font-size: 26px;
+            font-weight: 600;
+            color: #1a1a1a;
+        }
+
+        .container p {
+            font-size: 18px;
+            color: #4a4a4a;
+            margin-bottom: 35px;
+            line-height: 1.5;
+        }
+
+        .button {
+            padding: 14px 0;
+            margin: 12px 0;
+            font-size: 16px;
+            border-radius: 6px;
+            cursor: pointer;
+            width: 100%;
+            border: 1px solid #ccc;
+            background-color: #007BFF;
+            color: #fff;
+            transition: background-color 0.3s ease, border-color 0.3s ease;
+        }
+
+        .button:hover {
+            background-color: #0056b3;
+            border-color: #0056b3;
+        }
+    </style>
+</head>
+<body>
+    <div class="container">
+        <img src="/public/assets/images/avatars/ai-tutor.png" alt="AI Tutor Avatar" class="avatar">
+        <h1>Access Restricted</h1>
+        <p>
+            We're currently testing things out for the <strong>DS598</strong> course. 
+            Access is restricted to students of the course. If you're enrolled in <strong>DS598</strong> and seeing this message, 
+            please reach out to us, and we'll help you get access.<br><br>
+            <em>P.S. Don't forget to use your BU email when logging in!</em>
+        </p>
+        <form action="/" method="get">
+            <button type="submit" class="button">Return to Home</button>
+        </form>
+    </div>
+</body>
+</html>

apps/chainlit_base/.chainlit/config.toml

@@ -0,0 +1,120 @@
+[project]
+# Whether to enable telemetry (default: true). No personal data is collected.
+enable_telemetry = true
+
+
+# List of environment variables to be provided by each user to use the app.
+user_env = []
+
+# Duration (in seconds) during which the session is saved when the connection is lost
+session_timeout = 3600
+
+# Enable third parties caching (e.g LangChain cache)
+cache = false
+
+# Authorized origins
+allow_origins = ["*"]
+
+# Follow symlink for asset mount (see https://github.com/Chainlit/chainlit/issues/317)
+# follow_symlink = false
+
+[features]
+# 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)
+unsafe_allow_html = false
+
+# Process and display mathematical expressions. This can clash with "$" characters in messages.
+latex = false
+
+# Automatically tag threads with the current chat profile (if a chat profile is used)
+auto_tag_thread = true
+
+# Authorize users to spontaneously upload files with messages
+[features.spontaneous_file_upload]
+    enabled = true
+    accept = ["*/*"]
+    max_files = 20
+    max_size_mb = 500
+
+[features.audio]
+    # Threshold for audio recording
+    min_decibels = -45
+    # Delay for the user to start speaking in MS
+    initial_silence_timeout = 3000
+    # Delay for the user to continue speaking in MS. If the user stops speaking for this duration, the recording will stop.
+    silence_timeout = 1500
+    # Above this duration (MS), the recording will forcefully stop.
+    max_duration = 15000
+    # Duration of the audio chunks in MS
+    chunk_duration = 1000
+    # Sample rate of the audio
+    sample_rate = 44100
+
+edit_message = true
+
+[UI]
+# Name of the assistant.
+name = "Assistant"
+
+# Description of the assistant. This is used for HTML tags.
+# description = ""
+
+# Large size content are by default collapsed for a cleaner ui
+default_collapse_content = true
+
+# Chain of Thought (CoT) display mode. Can be "hidden", "tool_call" or "full".
+cot = "full"
+
+# Link to your github repo. This will add a github button in the UI's header.
+# github = ""
+
+# Specify a CSS file that can be used to customize the user interface.
+# The CSS file can be served from the public directory or via an external link.
+custom_css = "/public/files/test.css"
+
+# Specify a Javascript file that can be used to customize the user interface.
+# The Javascript file can be served from the public directory.
+# custom_js = "/public/test.js"
+
+# Specify a custom font url.
+# custom_font = "https://fonts.googleapis.com/css2?family=Inter:wght@400;500;700&display=swap"
+
+# Specify a custom meta image url.
+# custom_meta_image_url = "https://chainlit-cloud.s3.eu-west-3.amazonaws.com/logo/chainlit_banner.png"
+
+# Specify a custom build directory for the frontend.
+# This can be used to customize the frontend code.
+# Be careful: If this is a relative path, it should not start with a slash.
+# custom_build = "./public/build"
+
+[UI.theme]
+    default = "dark"
+    #layout = "wide"
+    #font_family = "Inter, sans-serif"
+# Override default MUI light theme. (Check theme.ts)
+[UI.theme.light]
+    #background = "#FAFAFA"
+    #paper = "#FFFFFF"
+
+    [UI.theme.light.primary]
+        #main = "#F80061"
+        #dark = "#980039"
+        #light = "#FFE7EB"
+    [UI.theme.light.text]
+        #primary = "#212121"
+        #secondary = "#616161"
+
+# Override default MUI dark theme. (Check theme.ts)
+[UI.theme.dark]
+    #background = "#FAFAFA"
+    #paper = "#FFFFFF"
+
+    [UI.theme.dark.primary]
+        #main = "#F80061"
+        #dark = "#980039"
+        #light = "#FFE7EB"
+    [UI.theme.dark.text]
+        #primary = "#EEEEEE"
+        #secondary = "#BDBDBD"
+
+[meta]
+generated_by = "1.1.402"

apps/chainlit_base/chainlit.md

@@ -0,0 +1,14 @@
+# Welcome to Chainlit! 🚀🤖
+
+Hi there, Developer! 👋 We're excited to have you on board. Chainlit is a powerful tool designed to help you prototype, debug and share applications built on top of LLMs.
+
+## Useful Links 🔗
+
+- **Documentation:** Get started with our comprehensive [Chainlit Documentation](https://docs.chainlit.io) 📚
+- **Discord Community:** Join our friendly [Chainlit Discord](https://discord.gg/k73SQ3FyUh) to ask questions, share your projects, and connect with other developers! 💬
+
+We can't wait to see what you create with Chainlit! Happy coding! 💻😊
+
+## Welcome screen
+
+To modify the welcome screen, edit the `chainlit.md` file at the root of your project. If you do not want a welcome screen, just leave this file empty.

apps/chainlit_base/chainlit_base.py

@@ -0,0 +1,381 @@
+import chainlit.data as cl_data
+import asyncio
+from typing import Any, Dict, no_type_check
+import chainlit as cl
+from edubotics_core.chat.llm_tutor import LLMTutor
+from edubotics_core.chat.helpers import (
+    get_sources,
+    get_history_setup_llm,
+)
+import copy
+from langchain_community.callbacks import get_openai_callback
+from config.config_manager import config_manager
+
+USER_TIMEOUT = 60_000
+SYSTEM = "System"
+LLM = "AI Tutor"
+AGENT = "Agent"
+YOU = "User"
+ERROR = "Error"
+
+config = config_manager.get_config().dict()
+
+
+class Chatbot:
+    def __init__(self, config):
+        """
+        Initialize the Chatbot class.
+        """
+        self.config = config
+
+    @no_type_check
+    async def setup_llm(self):
+        """
+        Set up the LLM with the provided settings. Update the configuration and initialize the LLM tutor.
+
+        #TODO: Clean this up.
+        """
+
+        llm_settings = cl.user_session.get("llm_settings", {})
+        (
+            chat_profile,
+            retriever_method,
+            memory_window,
+            llm_style,
+            generate_follow_up,
+            chunking_mode,
+        ) = (
+            llm_settings.get("chat_model"),
+            llm_settings.get("retriever_method"),
+            llm_settings.get("memory_window"),
+            llm_settings.get("llm_style"),
+            llm_settings.get("follow_up_questions"),
+            llm_settings.get("chunking_mode"),
+        )
+
+        chain = cl.user_session.get("chain")
+        memory_list = cl.user_session.get(
+            "memory",
+            (
+                list(chain.store.values())[0].messages
+                if len(chain.store.values()) > 0
+                else []
+            ),
+        )
+        conversation_list = get_history_setup_llm(memory_list)
+
+        old_config = copy.deepcopy(self.config)
+        self.config["vectorstore"]["db_option"] = retriever_method
+        self.config["llm_params"]["memory_window"] = memory_window
+        self.config["llm_params"]["llm_style"] = llm_style
+        self.config["llm_params"]["llm_loader"] = chat_profile
+        self.config["llm_params"]["generate_follow_up"] = generate_follow_up
+        self.config["splitter_options"]["chunking_mode"] = chunking_mode
+
+        self.llm_tutor.update_llm(
+            old_config, self.config
+        )  # update only llm attributes that are changed
+        self.chain = self.llm_tutor.qa_bot(
+            memory=conversation_list,
+        )
+
+        cl.user_session.set("chain", self.chain)
+        cl.user_session.set("llm_tutor", self.llm_tutor)
+
+    @no_type_check
+    async def update_llm(self, new_settings: Dict[str, Any]):
+        """
+        Update the LLM settings and reinitialize the LLM with the new settings.
+
+        Args:
+            new_settings (Dict[str, Any]): The new settings to update.
+        """
+        cl.user_session.set("llm_settings", new_settings)
+        await self.inform_llm_settings()
+        await self.setup_llm()
+
+    async def make_llm_settings_widgets(self, config=None):
+        """
+        Create and send the widgets for LLM settings configuration.
+
+        Args:
+            config: The configuration to use for setting up the widgets.
+        """
+        config = config or self.config
+        await cl.ChatSettings(
+            [
+                cl.input_widget.Select(
+                    id="chat_model",
+                    label="Model Name (Default GPT-3)",
+                    values=["local_llm", "gpt-3.5-turbo-1106", "gpt-4", "gpt-4o-mini"],
+                    initial_index=[
+                        "local_llm",
+                        "gpt-3.5-turbo-1106",
+                        "gpt-4",
+                        "gpt-4o-mini",
+                    ].index(config["llm_params"]["llm_loader"]),
+                ),
+                cl.input_widget.Select(
+                    id="retriever_method",
+                    label="Retriever (Default FAISS)",
+                    values=["FAISS", "Chroma", "RAGatouille", "RAPTOR"],
+                    initial_index=["FAISS", "Chroma", "RAGatouille", "RAPTOR"].index(
+                        config["vectorstore"]["db_option"]
+                    ),
+                ),
+                cl.input_widget.Slider(
+                    id="memory_window",
+                    label="Memory Window (Default 3)",
+                    initial=3,
+                    min=0,
+                    max=10,
+                    step=1,
+                ),
+                cl.input_widget.Switch(
+                    id="view_sources", label="View Sources", initial=False
+                ),
+                cl.input_widget.Switch(
+                    id="stream_response",
+                    label="Stream response",
+                    initial=config["llm_params"]["stream"],
+                ),
+                cl.input_widget.Select(
+                    id="chunking_mode",
+                    label="Chunking mode",
+                    values=["fixed", "semantic"],
+                    initial_index=1,
+                ),
+                cl.input_widget.Switch(
+                    id="follow_up_questions",
+                    label="Generate follow up questions",
+                    initial=False,
+                ),
+                cl.input_widget.Select(
+                    id="llm_style",
+                    label="Type of Conversation (Default Normal)",
+                    values=["Normal", "ELI5"],
+                    initial_index=0,
+                ),
+            ]
+        ).send()
+
+    @no_type_check
+    async def inform_llm_settings(self):
+        """
+        Inform the user about the updated LLM settings and display them as a message.
+        """
+        await cl.Message(
+            author=SYSTEM,
+            content="LLM settings have been updated. You can continue with your Query!",
+        ).send()
+
+    async def set_starters(self):
+        """
+        Set starter messages for the chatbot.
+        """
+
+        return [
+            cl.Starter(
+                label="recording on Transformers?",
+                message="Where can I find the recording for the lecture on Transformers?",
+                icon="/public/assets/images/starter_icons/adv-screen-recorder-svgrepo-com.svg",
+            ),
+            cl.Starter(
+                label="where's the slides?",
+                message="When are the lectures? I can't find the schedule.",
+                icon="/public/assets/images/starter_icons/alarmy-svgrepo-com.svg",
+            ),
+            cl.Starter(
+                label="Due Date?",
+                message="When is the final project due?",
+                icon="/public/assets/images/starter_icons/calendar-samsung-17-svgrepo-com.svg",
+            ),
+            cl.Starter(
+                label="Explain backprop.",
+                message="I didn't understand the math behind backprop, could you explain it?",
+                icon="/public/assets/images/starter_icons/acastusphoton-svgrepo-com.svg",
+            ),
+        ]
+
+    def rename(self, orig_author: str):
+        """
+        Rename the original author to a more user-friendly name.
+
+        Args:
+            orig_author (str): The original author's name.
+
+        Returns:
+            str: The renamed author.
+        """
+        rename_dict = {"Chatbot": LLM}
+        return rename_dict.get(orig_author, orig_author)
+
+    async def start(self):
+        """
+        Start the chatbot, initialize settings widgets,
+        and display and load previous conversation if chat logging is enabled.
+        """
+
+        await self.make_llm_settings_widgets(self.config)  # Reload the settings widgets
+
+        # TODO: remove self.user with cl.user_session.get("user")
+        self.user = {
+            "user_id": "guest",
+            "session_id": cl.context.session.thread_id,
+        }
+
+        memory = cl.user_session.get("memory", [])
+        self.llm_tutor = LLMTutor(self.config, user=self.user)
+
+        self.chain = self.llm_tutor.qa_bot(
+            memory=memory,
+        )
+        self.question_generator = self.llm_tutor.question_generator
+        cl.user_session.set("llm_tutor", self.llm_tutor)
+        cl.user_session.set("chain", self.chain)
+
+    async def stream_response(self, response):
+        """
+        Stream the response from the LLM.
+
+        Args:
+            response: The response from the LLM.
+        """
+        msg = cl.Message(content="")
+        await msg.send()
+
+        output = {}
+        for chunk in response:
+            if "answer" in chunk:
+                await msg.stream_token(chunk["answer"])
+
+            for key in chunk:
+                if key not in output:
+                    output[key] = chunk[key]
+                else:
+                    output[key] += chunk[key]
+        return output
+
+    async def main(self, message):
+        """
+        Process and Display the Conversation.
+
+        Args:
+            message: The incoming chat message.
+        """
+
+        chain = cl.user_session.get("chain")
+        token_count = 0  # initialize token count
+        if not chain:
+            await self.start()  # start the chatbot if the chain is not present
+            chain = cl.user_session.get("chain")
+
+        # update user info with last message time
+        llm_settings = cl.user_session.get("llm_settings", {})
+        view_sources = llm_settings.get("view_sources", False)
+        stream = llm_settings.get("stream_response", False)
+        stream = False  # Fix streaming
+        user_query_dict = {"input": message.content}
+        # Define the base configuration
+        cb = cl.AsyncLangchainCallbackHandler()
+        chain_config = {
+            "configurable": {
+                "user_id": self.user["user_id"],
+                "conversation_id": self.user["session_id"],
+                "memory_window": self.config["llm_params"]["memory_window"],
+            },
+            "callbacks": (
+                [cb]
+                if cl_data._data_layer and self.config["chat_logging"]["callbacks"]
+                else None
+            ),
+        }
+
+        with get_openai_callback() as token_count_cb:
+            if stream:
+                res = chain.stream(user_query=user_query_dict, config=chain_config)
+                res = await self.stream_response(res)
+            else:
+                res = await chain.invoke(
+                    user_query=user_query_dict,
+                    config=chain_config,
+                )
+        token_count += token_count_cb.total_tokens
+
+        answer = res.get("answer", res.get("result"))
+
+        answer_with_sources, source_elements, sources_dict = get_sources(
+            res, answer, stream=stream, view_sources=view_sources
+        )
+        answer_with_sources = answer_with_sources.replace("$$", "$")
+
+        actions = []
+
+        if self.config["llm_params"]["generate_follow_up"]:
+            cb_follow_up = cl.AsyncLangchainCallbackHandler()
+            config = {
+                "callbacks": (
+                    [cb_follow_up]
+                    if cl_data._data_layer and self.config["chat_logging"]["callbacks"]
+                    else None
+                )
+            }
+            with get_openai_callback() as token_count_cb:
+                list_of_questions = await self.question_generator.generate_questions(
+                    query=user_query_dict["input"],
+                    response=answer,
+                    chat_history=res.get("chat_history"),
+                    context=res.get("context"),
+                    config=config,
+                )
+
+            token_count += token_count_cb.total_tokens
+
+            for question in list_of_questions:
+                actions.append(
+                    cl.Action(
+                        name="follow up question",
+                        value="example_value",
+                        description=question,
+                        label=question,
+                    )
+                )
+
+        await cl.Message(
+            content=answer_with_sources,
+            elements=source_elements,
+            author=LLM,
+            actions=actions,
+        ).send()
+
+    async def on_follow_up(self, action: cl.Action):
+        user = cl.user_session.get("user")
+        message = await cl.Message(
+            content=action.description,
+            type="user_message",
+            author=user.identifier,
+        ).send()
+        async with cl.Step(
+            name="on_follow_up", type="run", parent_id=message.id
+        ) as step:
+            await self.main(message)
+            step.output = message.content
+
+
+chatbot = Chatbot(config=config)
+
+
+async def start_app():
+    cl.set_starters(chatbot.set_starters)
+    cl.author_rename(chatbot.rename)
+    cl.on_chat_start(chatbot.start)
+    cl.on_message(chatbot.main)
+    cl.on_settings_update(chatbot.update_llm)
+    cl.action_callback("follow up question")(chatbot.on_follow_up)
+
+
+loop = asyncio.get_event_loop()
+if loop.is_running():
+    asyncio.ensure_future(start_app())
+else:
+    asyncio.run(start_app())

apps/chainlit_base/config/config.yml

@@ -0,0 +1,60 @@
+log_dir: 'storage/logs' # str
+log_chunk_dir: 'storage/logs/chunks' # str
+device: 'cpu' # str [cuda, cpu]
+
+vectorstore:
+  load_from_HF: True # bool
+  reparse_files: True # bool
+  data_path: 'storage/data' # str
+  url_file_path: 'storage/data/urls.txt' # str
+  expand_urls: True # bool
+  db_option : 'RAGatouille' # str [FAISS, Chroma, RAGatouille, RAPTOR]
+  db_path : 'vectorstores' # str
+  model : 'sentence-transformers/all-MiniLM-L6-v2' # str [sentence-transformers/all-MiniLM-L6-v2, text-embedding-ada-002']
+  search_top_k : 3 # int
+  score_threshold : 0.2 # float
+
+  faiss_params: # Not used as of now
+    index_path: 'vectorstores/faiss.index' # str
+    index_type: 'Flat' # str [Flat, HNSW, IVF]
+    index_dimension: 384 # int
+    index_nlist: 100 # int
+    index_nprobe: 10 # int
+
+  colbert_params:
+    index_name: "new_idx" # str
+
+llm_params: 
+  llm_arch: 'langchain' # [langchain]
+  use_history: True # bool
+  generate_follow_up: False # bool
+  memory_window: 3 # int
+  llm_style: 'Normal' # str [Normal, ELI5]
+  llm_loader: 'gpt-4o-mini' # str [local_llm, gpt-3.5-turbo-1106, gpt-4, gpt-4o-mini]
+  openai_params:
+    temperature: 0.7 # float
+  local_llm_params:
+    temperature: 0.7 # float
+    repo_id: 'TheBloke/TinyLlama-1.1B-Chat-v1.0-GGUF' # HuggingFace repo id
+    filename: 'tinyllama-1.1b-chat-v1.0.Q5_0.gguf' # Specific name of gguf file in the repo
+    model_path: 'storage/models/tinyllama-1.1b-chat-v1.0.Q5_0.gguf' # Path to the model file
+  stream: False # bool
+  pdf_reader: 'gpt' # str [llama, pymupdf, gpt]
+
+chat_logging:
+  log_chat: True # bool
+  platform: 'literalai'
+  callbacks: True # bool
+
+splitter_options:
+  use_splitter: True # bool
+  split_by_token : True # bool
+  remove_leftover_delimiters: True # bool
+  remove_chunks: False # bool
+  chunking_mode: 'semantic' # str [fixed, semantic]
+  chunk_size : 300 # int
+  chunk_overlap : 30 # int
+  chunk_separators : ["\n\n", "\n", " ", ""] # list of strings
+  front_chunks_to_remove : null # int or None
+  last_chunks_to_remove : null # int or None
+  delimiters_to_remove : ['\t', '\n', '   ', '  '] # list of strings

apps/chainlit_base/config/config_manager.py

@@ -0,0 +1,174 @@
+from pydantic import BaseModel, conint, confloat, HttpUrl
+from typing import Optional, List
+import yaml
+
+
+class FaissParams(BaseModel):
+    index_path: str = "vectorstores/faiss.index"
+    index_type: str = "Flat"  # Options: [Flat, HNSW, IVF]
+    index_dimension: conint(gt=0) = 384
+    index_nlist: conint(gt=0) = 100
+    index_nprobe: conint(gt=0) = 10
+
+
+class ColbertParams(BaseModel):
+    index_name: str = "new_idx"
+
+
+class VectorStoreConfig(BaseModel):
+    load_from_HF: bool = True
+    reparse_files: bool = True
+    data_path: str = "storage/data"
+    url_file_path: str = "storage/data/urls.txt"
+    expand_urls: bool = True
+    db_option: str = "RAGatouille"  # Options: [FAISS, Chroma, RAGatouille, RAPTOR]
+    db_path: str = "vectorstores"
+    model: str = (
+        "sentence-transformers/all-MiniLM-L6-v2"  # Options: [sentence-transformers/all-MiniLM-L6-v2, text-embedding-ada-002]
+    )
+    search_top_k: conint(gt=0) = 3
+    score_threshold: confloat(ge=0.0, le=1.0) = 0.2
+
+    faiss_params: Optional[FaissParams] = None
+    colbert_params: Optional[ColbertParams] = None
+
+
+class OpenAIParams(BaseModel):
+    temperature: confloat(ge=0.0, le=1.0) = 0.7
+
+
+class LocalLLMParams(BaseModel):
+    temperature: confloat(ge=0.0, le=1.0) = 0.7
+    repo_id: str = "TheBloke/TinyLlama-1.1B-Chat-v1.0-GGUF"  # HuggingFace repo id
+    filename: str = (
+        "tinyllama-1.1b-chat-v1.0.Q5_0.gguf"  # Specific name of gguf file in the repo
+    )
+    model_path: str = (
+        "storage/models/tinyllama-1.1b-chat-v1.0.Q5_0.gguf"  # Path to the model file
+    )
+
+
+class LLMParams(BaseModel):
+    llm_arch: str = "langchain"  # Options: [langchain]
+    use_history: bool = True
+    generate_follow_up: bool = False
+    memory_window: conint(ge=1) = 3
+    llm_style: str = "Normal"  # Options: [Normal, ELI5]
+    llm_loader: str = (
+        "gpt-4o-mini"  # Options: [local_llm, gpt-3.5-turbo-1106, gpt-4, gpt-4o-mini]
+    )
+    openai_params: Optional[OpenAIParams] = None
+    local_llm_params: Optional[LocalLLMParams] = None
+    stream: bool = False
+    pdf_reader: str = "gpt"  # Options: [llama, pymupdf, gpt]
+
+
+class ChatLoggingConfig(BaseModel):
+    log_chat: bool = True
+    platform: str = "literalai"
+    callbacks: bool = True
+
+
+class SplitterOptions(BaseModel):
+    use_splitter: bool = True
+    split_by_token: bool = True
+    remove_leftover_delimiters: bool = True
+    remove_chunks: bool = False
+    chunking_mode: str = "semantic"  # Options: [fixed, semantic]
+    chunk_size: conint(gt=0) = 300
+    chunk_overlap: conint(ge=0) = 30
+    chunk_separators: List[str] = ["\n\n", "\n", " ", ""]
+    front_chunks_to_remove: Optional[conint(ge=0)] = None
+    last_chunks_to_remove: Optional[conint(ge=0)] = None
+    delimiters_to_remove: List[str] = ["\t", "\n", "   ", "  "]
+
+
+class RetrieverConfig(BaseModel):
+    retriever_hf_paths: dict[str, str] = {"RAGatouille": "XThomasBU/Colbert_Index"}
+
+
+class MetadataConfig(BaseModel):
+    metadata_links: List[HttpUrl] = [
+        "https://dl4ds.github.io/sp2024/lectures/",
+        "https://dl4ds.github.io/sp2024/schedule/",
+    ]
+    slide_base_link: HttpUrl = "https://dl4ds.github.io"
+
+
+class APIConfig(BaseModel):
+    timeout: conint(gt=0) = 60
+
+
+class Config(BaseModel):
+    log_dir: str = "storage/logs"
+    log_chunk_dir: str = "storage/logs/chunks"
+    device: str = "cpu"  # Options: ['cuda', 'cpu']
+
+    vectorstore: VectorStoreConfig
+    llm_params: LLMParams
+    chat_logging: ChatLoggingConfig
+    splitter_options: SplitterOptions
+    retriever: RetrieverConfig
+    metadata: MetadataConfig
+    api_config: APIConfig
+
+
+class ConfigManager:
+    def __init__(self, config_path: str, project_config_path: str):
+        self.config_path = config_path
+        self.project_config_path = project_config_path
+        self.config = self.load_config()
+        self.validate_config()
+
+    def load_config(self) -> Config:
+        with open(self.config_path, "r") as f:
+            config_data = yaml.safe_load(f)
+
+        with open(self.project_config_path, "r") as f:
+            project_config_data = yaml.safe_load(f)
+
+        # Merge the two configurations
+        merged_config = {**config_data, **project_config_data}
+
+        return Config(**merged_config)
+
+    def get_config(self) -> Config:
+        return ConfigWrapper(self.config)
+
+    def validate_config(self):
+        # If any required fields are missing, raise an error
+        # required_fields = [
+        #     "vectorstore", "llm_params", "chat_logging", "splitter_options",
+        #     "retriever", "metadata", "token_config", "misc", "api_config"
+        # ]
+        # for field in required_fields:
+        #     if not hasattr(self.config, field):
+        #         raise ValueError(f"Missing required configuration field: {field}")
+
+        # # Validate types of specific fields
+        # if not isinstance(self.config.vectorstore, VectorStoreConfig):
+        #     raise TypeError("vectorstore must be an instance of VectorStoreConfig")
+        # if not isinstance(self.config.llm_params, LLMParams):
+        #     raise TypeError("llm_params must be an instance of LLMParams")
+        pass
+
+
+class ConfigWrapper:
+    def __init__(self, config: Config):
+        self._config = config
+
+    def __getitem__(self, key):
+        return getattr(self._config, key)
+
+    def __getattr__(self, name):
+        return getattr(self._config, name)
+
+    def dict(self):
+        return self._config.dict()
+
+
+# Usage
+config_manager = ConfigManager(
+    config_path="config/config.yml", project_config_path="config/project_config.yml"
+)
+# config = config_manager.get_config().dict()

apps/chainlit_base/config/project_config.yml

@@ -0,0 +1,10 @@
+retriever:
+  retriever_hf_paths:
+    RAGatouille: "XThomasBU/Colbert_Index"
+
+metadata:
+  metadata_links: ["https://dl4ds.github.io/sp2024/lectures/", "https://dl4ds.github.io/sp2024/schedule/"]
+  slide_base_link: "https://dl4ds.github.io"
+
+api_config:
+  timeout: 60

apps/chainlit_base/config/prompts.py

@@ -0,0 +1,97 @@
+prompts = {
+    "openai": {
+        "rephrase_prompt": (
+            "You are someone that rephrases statements. Rephrase the student's question to add context from their chat history if relevant, ensuring it remains from the student's point of view. "
+            "Incorporate relevant details from the chat history to make the question clearer and more specific. "
+            "Do not change the meaning of the original statement, and maintain the student's tone and perspective. "
+            "If the question is conversational and doesn't require context, do not rephrase it. "
+            "Example: If the student previously asked about backpropagation in the context of deep learning and now asks 'what is it', rephrase to 'What is backpropagation.'. "
+            "Example: Do not rephrase if the user is asking something specific like 'cool, suggest a project with transformers to use as my final project' "
+            "Chat history: \n{chat_history}\n"
+            "Rephrase the following question only if necessary: '{input}'"
+            "Rephrased Question:'"
+        ),
+        "prompt_with_history": {
+            "normal": (
+                "You are an AI Tutor for the course DS598, taught by Prof. Thomas Gardos. Answer the user's question using the provided context. Only use the context if it is relevant. The context is ordered by relevance. "
+                "If you don't know the answer, do your best without making things up. Keep the conversation flowing naturally. "
+                "Use chat history and context as guides but avoid repeating past responses. Provide links from the source_file metadata. Use the source context that is most relevant. "
+                "Render math equations in LaTeX format between $ or $$ signs, stick to the parameter and variable icons found in your context. Be sure to explain the parameters and variables in the equations."
+                "Speak in a friendly and engaging manner, like talking to a friend. Avoid sounding repetitive or robotic.\n\n"
+                "Do not get influenced by the style of conversation in the chat history. Follow the instructions given here."
+                "Chat History:\n{chat_history}\n\n"
+                "Context:\n{context}\n\n"
+                "Answer the student's question below in a friendly, concise, and engaging manner. Use the context and history only if relevant, otherwise, engage in a free-flowing conversation.\n"
+                "Student: {input}\n"
+                "AI Tutor:"
+            ),
+            "eli5": (
+                "You are an AI Tutor for the course DS598, taught by Prof. Thomas Gardos. Your job is to explain things in the simplest and most engaging way possible, just like the 'Explain Like I'm 5' (ELI5) concept."
+                "If you don't know the answer, do your best without making things up. Keep your explanations straightforward and very easy to understand."
+                "Use the chat history and context to help you, but avoid repeating past responses. Provide links from the source_file metadata when they're helpful."
+                "Use very simple language and examples to explain any math equations, and put the equations in LaTeX format between $ or $$ signs."
+                "Be friendly and engaging, like you're chatting with a young child who's curious and eager to learn. Avoid complex terms and jargon."
+                "Include simple and clear examples wherever you can to make things easier to understand."
+                "Do not get influenced by the style of conversation in the chat history. Follow the instructions given here."
+                "Chat History:\n{chat_history}\n\n"
+                "Context:\n{context}\n\n"
+                "Answer the student's question below in a friendly, simple, and engaging way, just like the ELI5 concept. Use the context and history only if they're relevant, otherwise, just have a natural conversation."
+                "Give a clear and detailed explanation with simple examples to make it easier to understand. Remember, your goal is to break down complex topics into very simple terms, just like ELI5."
+                "Student: {input}\n"
+                "AI Tutor:"
+            ),
+            "socratic": (
+                "You are an AI Tutor for the course DS598, taught by Prof. Thomas Gardos. Engage the student in a Socratic dialogue to help them discover answers on their own. Use the provided context to guide your questioning."
+                "If you don't know the answer, do your best without making things up. Keep the conversation engaging and inquisitive."
+                "Use chat history and context as guides but avoid repeating past responses. Provide links from the source_file metadata when relevant. Use the source context that is most relevant."
+                "Speak in a friendly and engaging manner, encouraging critical thinking and self-discovery."
+                "Use questions to lead the student to explore the topic and uncover answers."
+                "Chat History:\n{chat_history}\n\n"
+                "Context:\n{context}\n\n"
+                "Answer the student's question below by guiding them through a series of questions and insights that lead to deeper understanding. Use the context and history only if relevant, otherwise, engage in a free-flowing conversation."
+                "Foster an inquisitive mindset and help the student discover answers through dialogue."
+                "Student: {input}\n"
+                "AI Tutor:"
+            ),
+        },
+        "prompt_no_history": (
+            "You are an AI Tutor for the course DS598, taught by Prof. Thomas Gardos. Answer the user's question using the provided context. Only use the context if it is relevant. The context is ordered by relevance. "
+            "If you don't know the answer, do your best without making things up. Keep the conversation flowing naturally. "
+            "Provide links from the source_file metadata. Use the source context that is most relevant. "
+            "Speak in a friendly and engaging manner, like talking to a friend. Avoid sounding repetitive or robotic.\n\n"
+            "Context:\n{context}\n\n"
+            "Answer the student's question below in a friendly, concise, and engaging manner. Use the context and history only if relevant, otherwise, engage in a free-flowing conversation.\n"
+            "Student: {input}\n"
+            "AI Tutor:"
+        ),
+    },
+    "tiny_llama": {
+        "prompt_no_history": (
+            "system\n"
+            "Assistant is an intelligent chatbot designed to help students with questions regarding the course DS598, taught by Prof. Thomas Gardos. Answer the user's question using the provided context. Only use the context if it is relevant. The context is ordered by relevance.\n"
+            "If you don't know the answer, do your best without making things up. Keep the conversation flowing naturally.\n"
+            "Provide links from the source_file metadata. Use the source context that is most relevant.\n"
+            "Speak in a friendly and engaging manner, like talking to a friend. Avoid sounding repetitive or robotic.\n"
+            "\n\n"
+            "user\n"
+            "Context:\n{context}\n\n"
+            "Question: {input}\n"
+            "\n\n"
+            "assistant"
+        ),
+        "prompt_with_history": (
+            "system\n"
+            "You are an AI Tutor for the course DS598, taught by Prof. Thomas Gardos. Answer the user's question using the provided context. Only use the context if it is relevant. The context is ordered by relevance. "
+            "If you don't know the answer, do your best without making things up. Keep the conversation flowing naturally. "
+            "Use chat history and context as guides but avoid repeating past responses. Provide links from the source_file metadata. Use the source context that is most relevant. "
+            "Speak in a friendly and engaging manner, like talking to a friend. Avoid sounding repetitive or robotic.\n"
+            "\n\n"
+            "user\n"
+            "Chat History:\n{chat_history}\n\n"
+            "Context:\n{context}\n\n"
+            "Question: {input}\n"
+            "\n\n"
+            "assistant"
+        ),
+    },
+}