Chat Routes

This module defines the API routes for the chat functionality of the chatbot.

class app.api.chat_routes.ChatRequest(*, message: Annotated[str, MinLen(min_length=1), MaxLen(max_length=1000)])

Bases: BaseModel

Model for chat request.

Parameters:

message – The user’s input message, with length constraints.

message: str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'message': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), MaxLen(max_length=1000)])}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class app.api.chat_routes.ConversationHistory(*, history: List[Tuple[str, str]], context_info: Dict[str, int] | None = None)

Bases: BaseModel

Model for conversation history with context information.

Parameters:

• history – A list of tuples containing the conversation history.

• context_info – A dictionary with information about the conversation context.

context_info: Dict[str, int] | None

history: List[Tuple[str, str]]

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'context_info': FieldInfo(annotation=Union[Dict[str, int], NoneType], required=False, default=None), 'history': FieldInfo(annotation=List[Tuple[str, str]], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class app.api.chat_routes.ErrorResponse(*, detail: str)

Bases: BaseModel

Model for error responses.

Parameters:

detail – A string describing the error.

detail: str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'detail': FieldInfo(annotation=str, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

async app.api.chat_routes.chat(request: ChatRequest, chat_service: ChatService = Depends(get_chat_service))

Endpoint for processing a chat message.

Parameters:

• request – The ChatRequest containing the user’s message.

• chat_service – An instance of ChatService, injected as a dependency.

Returns:

A ChatResponse containing the AI’s response.

Raises:

HTTPException – If the message is empty or an error occurs during processing.

app.api.chat_routes.clear_conversation(chat_service: ChatService = Depends(get_chat_service))

Endpoint for clearing the conversation history.

Parameters:

chat_service – An instance of ChatService, injected as a dependency.

Returns:

A Response with a 204 No Content status code on success.

Raises:

HTTPException – If an error occurs while clearing the conversation.

app.api.chat_routes.get_chat_service()

Dependency injection function to get the ChatService instance.

Returns:

An instance of ChatService.

async app.api.chat_routes.get_conversation(include_context: bool | None = Query(None), chat_service: ChatService = Depends(get_chat_service))

Endpoint for retrieving the conversation history and optionally context information.

Parameters:

• include_context – If True, includes context information in the response.

• chat_service – An instance of ChatService, injected as a dependency.

Returns:

A dictionary containing the conversation history and optionally context info.

Raises:

HTTPException – If an error occurs while retrieving the conversation history.