API Reference

Modules

`api.v1.cmd`	This module provides an API endpoint to ask questions against a vector store using OpenAI's language model.
`api.v1.data`	This module provides API endpoints for managing text snippets and PDFs in a vector store.
`api.v1.auth`	This module defines the authentication routes for the FastAPI application, specifically handling the generation of access tokens for users.
`util.v1.chroma_handler`	This module provides utility functions to handle vector stores using Chroma.

cmd-Methods

api.v1.cmd.cmd_ask_question

Endpoint to ask a question against a vector store.

data-Methods

`api.v1.data.data_add_texts`	Endpoint to add text snippets to a vector store.
`api.v1.data.data_add_pdfs`	Endpoint to add pdfs to a vector store.
`api.v1.data.data_get_texts`	Endpoint to get text snippets from specified vector store.
`api.v1.data.data_get_pdfs`	Endpoint to get pdf name from specified vector store.
`api.v1.data.data_get_databases`	Endpoint to get all present database names.
`api.v1.data.data_update_texts`	Endpoint to update text snippets.
`api.v1.data.data_delete_texts`	Endpoint to delete text snippets.
`api.v1.data.data_delete_pdfs`	Endpoint to delete all text snippets from the specified pdfs.
`api.v1.data.data_delete_databases`	Endpoint to delete all databases.

auth-Methods

# util.v1.auth.fake_users_db: util.v1.auth.verify_password util.v1.auth.get_password_hash util.v1.auth.get_user util.v1.auth.authenticate_user util.v1.auth.create_access_token util.v1.auth.get_current_user util.v1.auth.get_current_active_user

chroma_handler-Methods

`util.v1.chroma_handler.create_vector_store`	Create a vector store for a given identifier.
`util.v1.chroma_handler.get_vector_store`	Retrieve the vector store for a given identifier, creating it if necessary.
`util.v1.chroma_handler.add_texts`	Add texts to the vector store for a given identifier.
`util.v1.chroma_handler.add_pdfs`	Add PDFs to the vector store for a given identifier.
`util.v1.chroma_handler.get_texts`	Retrieve texts from the vector store for a given identifier.
`util.v1.chroma_handler.get_pdfs`	Retrieve PDF filenames from the vector store for a given identifier.
`util.v1.chroma_handler.get_databases`	Retrieve all database identifiers.
`util.v1.chroma_handler.update_texts`	Update texts in the vector store for a given identifier.
`util.v1.chroma_handler.delete_texts`	Delete texts from the vector store for a given identifier.
`util.v1.chroma_handler.delete_pdfs`	Delete PDFs from the vector store for a given identifier.
`util.v1.chroma_handler.delete_databases`	Delete databases for given identifiers.
`util.v1.chroma_handler.build_question`	Build a question template with snippets from the vector store.

Types

Modules

`models.v1.cmd`	This module contains models and enums used for the command API.
`models.v1.data`	This module contains Pydantic models for handling data requests and responses related to texts and PDFs in the fRAGme application.
`models.v1.auth`

cmd-Models

`models.v1.cmd.RoleEnum`	Enum representing the role in a chat.
`models.v1.cmd.ChatAction`	Model representing an action in a chat.
`models.v1.cmd.Question`	Model representing a question with its context and parameters.
`models.v1.cmd.CmdAskQuestionRequest`	Model representing a request to ask a question.
`models.v1.cmd.CmdAskQuestionResponse`	Model representing a response to the asked question.

data-Models

`models.v1.data.Text`	Model representing a text entry with associated metadata.
`models.v1.data.TextUpdate`	Model representing an update to a text entry.
`models.v1.data.DataAddTextsRequest`	Request model for adding multiple text entries.
`models.v1.data.DataAddTextsResponse`	Response model indicating the status of adding text entries.
`models.v1.data.DataAddPDFsResponse`	Response model indicating the status of adding PDF entries.
`models.v1.data.DataGetTextsRequest`	Request model for retrieving specific text entries by their IDs.
`models.v1.data.DataGetTextsResponse`	Response model containing the requested text entries.
`models.v1.data.DataGetPDFsRequest`	Request model for retrieving PDFs associated with an identifier.
`models.v1.data.DataGetPDFsResponse`	Response model containing the requested PDF names.
`models.v1.data.DataGetDatabasesResponse`	Response model containing the list of available databases.
`models.v1.data.DataUploadTextsRequest`	Request model for uploading updates to text entries.
`models.v1.data.DataUploadTextsResponse`	Response model indicating the status of uploading text updates.
`models.v1.data.DataDeleteTextsRequest`	Request model for deleting specific text entries by their IDs.
`models.v1.data.DataDeleteTextsResponse`	Response model indicating the status of deleting text entries.
`models.v1.data.DataDeletePDFsRequest`	Request model for deleting specific PDFs by their names.
`models.v1.data.DataDeletePDFsResponse`	Response model indicating the status of deleting PDF entries.
`models.v1.data.DataDeleteDatabasesRequest`	Request model for deleting specific databases by their identifiers.
`models.v1.data.DataDeleteDatabasesResponse`	Response model indicating the status of deleting databases.

auth-Models

`models.v1.auth.Token`	Represents an access token.
`models.v1.auth.TokenData`	Represents the data contained within a token.
`models.v1.auth.User`	Represents a user in the system.
`models.v1.auth.UserInDB`	Represents a user stored in the database.