backend/open_webui/routers/tasks.py

from fastapi import APIRouter, Depends, HTTPException, Response, status, Request
from fastapi.responses import JSONResponse, RedirectResponse

from pydantic import BaseModel
from typing import Optional
import logging
import re

from open_webui.utils.chat import generate_chat_completion
from open_webui.utils.task import (
    title_generation_template,
    query_generation_template,
    image_prompt_generation_template,
    autocomplete_generation_template,
    tags_generation_template,
    emoji_generation_template,
    moa_response_generation_template,
)
from open_webui.utils.auth import get_admin_user, get_verified_user
from open_webui.constants import TASKS

from open_webui.routers.pipelines import process_pipeline_inlet_filter
from open_webui.utils.filter import (
    get_sorted_filter_ids,
    process_filter_functions,
)
from open_webui.utils.task import get_task_model_id

from open_webui.config import (
    DEFAULT_TITLE_GENERATION_PROMPT_TEMPLATE,
    DEFAULT_TAGS_GENERATION_PROMPT_TEMPLATE,
    DEFAULT_IMAGE_PROMPT_GENERATION_PROMPT_TEMPLATE,
    DEFAULT_QUERY_GENERATION_PROMPT_TEMPLATE,
    DEFAULT_AUTOCOMPLETE_GENERATION_PROMPT_TEMPLATE,
    DEFAULT_EMOJI_GENERATION_PROMPT_TEMPLATE,
    DEFAULT_MOA_GENERATION_PROMPT_TEMPLATE,
)
from open_webui.env import SRC_LOG_LEVELS


log = logging.getLogger(__name__)
log.setLevel(SRC_LOG_LEVELS["MODELS"])

router = APIRouter()


##################################
#
# Task Endpoints
#
##################################


@router.get("/config")
async def get_task_config(request: Request, user=Depends(get_verified_user)):
    return {
        "TASK_MODEL": request.app.state.config.TASK_MODEL,
        "TASK_MODEL_EXTERNAL": request.app.state.config.TASK_MODEL_EXTERNAL,
        "TITLE_GENERATION_PROMPT_TEMPLATE": request.app.state.config.TITLE_GENERATION_PROMPT_TEMPLATE,
        "IMAGE_PROMPT_GENERATION_PROMPT_TEMPLATE": request.app.state.config.IMAGE_PROMPT_GENERATION_PROMPT_TEMPLATE,
        "ENABLE_AUTOCOMPLETE_GENERATION": request.app.state.config.ENABLE_AUTOCOMPLETE_GENERATION,
        "AUTOCOMPLETE_GENERATION_INPUT_MAX_LENGTH": request.app.state.config.AUTOCOMPLETE_GENERATION_INPUT_MAX_LENGTH,
        "TAGS_GENERATION_PROMPT_TEMPLATE": request.app.state.config.TAGS_GENERATION_PROMPT_TEMPLATE,
        "ENABLE_TAGS_GENERATION": request.app.state.config.ENABLE_TAGS_GENERATION,
        "ENABLE_TITLE_GENERATION": request.app.state.config.ENABLE_TITLE_GENERATION,
        "ENABLE_SEARCH_QUERY_GENERATION": request.app.state.config.ENABLE_SEARCH_QUERY_GENERATION,
        "ENABLE_RETRIEVAL_QUERY_GENERATION": request.app.state.config.ENABLE_RETRIEVAL_QUERY_GENERATION,
        "QUERY_GENERATION_PROMPT_TEMPLATE": request.app.state.config.QUERY_GENERATION_PROMPT_TEMPLATE,
        "TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE": request.app.state.config.TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE,
    }


class TaskConfigForm(BaseModel):
    TASK_MODEL: Optional[str]
    TASK_MODEL_EXTERNAL: Optional[str]
    ENABLE_TITLE_GENERATION: bool
    TITLE_GENERATION_PROMPT_TEMPLATE: str
    IMAGE_PROMPT_GENERATION_PROMPT_TEMPLATE: str
    ENABLE_AUTOCOMPLETE_GENERATION: bool
    AUTOCOMPLETE_GENERATION_INPUT_MAX_LENGTH: int
    TAGS_GENERATION_PROMPT_TEMPLATE: str
    ENABLE_TAGS_GENERATION: bool
    ENABLE_SEARCH_QUERY_GENERATION: bool
    ENABLE_RETRIEVAL_QUERY_GENERATION: bool
    QUERY_GENERATION_PROMPT_TEMPLATE: str
    TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE: str


@router.post("/config/update")
async def update_task_config(
    request: Request, form_data: TaskConfigForm, user=Depends(get_admin_user)
):
    request.app.state.config.TASK_MODEL = form_data.TASK_MODEL
    request.app.state.config.TASK_MODEL_EXTERNAL = form_data.TASK_MODEL_EXTERNAL
    request.app.state.config.ENABLE_TITLE_GENERATION = form_data.ENABLE_TITLE_GENERATION
    request.app.state.config.TITLE_GENERATION_PROMPT_TEMPLATE = (
        form_data.TITLE_GENERATION_PROMPT_TEMPLATE
    )

    request.app.state.config.IMAGE_PROMPT_GENERATION_PROMPT_TEMPLATE = (
        form_data.IMAGE_PROMPT_GENERATION_PROMPT_TEMPLATE
    )

    request.app.state.config.ENABLE_AUTOCOMPLETE_GENERATION = (
        form_data.ENABLE_AUTOCOMPLETE_GENERATION
    )
    request.app.state.config.AUTOCOMPLETE_GENERATION_INPUT_MAX_LENGTH = (
        form_data.AUTOCOMPLETE_GENERATION_INPUT_MAX_LENGTH
    )

    request.app.state.config.TAGS_GENERATION_PROMPT_TEMPLATE = (
        form_data.TAGS_GENERATION_PROMPT_TEMPLATE
    )
    request.app.state.config.ENABLE_TAGS_GENERATION = form_data.ENABLE_TAGS_GENERATION
    request.app.state.config.ENABLE_SEARCH_QUERY_GENERATION = (
        form_data.ENABLE_SEARCH_QUERY_GENERATION
    )
    request.app.state.config.ENABLE_RETRIEVAL_QUERY_GENERATION = (
        form_data.ENABLE_RETRIEVAL_QUERY_GENERATION
    )

    request.app.state.config.QUERY_GENERATION_PROMPT_TEMPLATE = (
        form_data.QUERY_GENERATION_PROMPT_TEMPLATE
    )
    request.app.state.config.TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE = (
        form_data.TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE
    )

    return {
        "TASK_MODEL": request.app.state.config.TASK_MODEL,
        "TASK_MODEL_EXTERNAL": request.app.state.config.TASK_MODEL_EXTERNAL,
        "ENABLE_TITLE_GENERATION": request.app.state.config.ENABLE_TITLE_GENERATION,
        "TITLE_GENERATION_PROMPT_TEMPLATE": request.app.state.config.TITLE_GENERATION_PROMPT_TEMPLATE,
        "IMAGE_PROMPT_GENERATION_PROMPT_TEMPLATE": request.app.state.config.IMAGE_PROMPT_GENERATION_PROMPT_TEMPLATE,
        "ENABLE_AUTOCOMPLETE_GENERATION": request.app.state.config.ENABLE_AUTOCOMPLETE_GENERATION,
        "AUTOCOMPLETE_GENERATION_INPUT_MAX_LENGTH": request.app.state.config.AUTOCOMPLETE_GENERATION_INPUT_MAX_LENGTH,
        "TAGS_GENERATION_PROMPT_TEMPLATE": request.app.state.config.TAGS_GENERATION_PROMPT_TEMPLATE,
        "ENABLE_TAGS_GENERATION": request.app.state.config.ENABLE_TAGS_GENERATION,
        "ENABLE_SEARCH_QUERY_GENERATION": request.app.state.config.ENABLE_SEARCH_QUERY_GENERATION,
        "ENABLE_RETRIEVAL_QUERY_GENERATION": request.app.state.config.ENABLE_RETRIEVAL_QUERY_GENERATION,
        "QUERY_GENERATION_PROMPT_TEMPLATE": request.app.state.config.QUERY_GENERATION_PROMPT_TEMPLATE,
        "TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE": request.app.state.config.TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE,
    }


@router.post("/title/completions")
async def generate_title(
    request: Request, form_data: dict, user=Depends(get_verified_user)
):

    if not request.app.state.config.ENABLE_TITLE_GENERATION:
        return JSONResponse(
            status_code=status.HTTP_200_OK,
            content={"detail": "Title generation is disabled"},
        )

    if getattr(request.state, "direct", False) and hasattr(request.state, "model"):
        models = {
            request.state.model["id"]: request.state.model,
        }
    else:
        models = request.app.state.MODELS

    model_id = form_data["model"]
    if model_id not in models:
        raise HTTPException(
            status_code=status.HTTP_404_NOT_FOUND,
            detail="Model not found",
        )

    # Check if the user has a custom task model
    # If the user has a custom task model, use that model
    task_model_id = get_task_model_id(
        model_id,
        request.app.state.config.TASK_MODEL,
        request.app.state.config.TASK_MODEL_EXTERNAL,
        models,
    )

    log.debug(
        f"generating chat title using model {task_model_id} for user {user.email} "
    )

    if request.app.state.config.TITLE_GENERATION_PROMPT_TEMPLATE != "":
        template = request.app.state.config.TITLE_GENERATION_PROMPT_TEMPLATE
    else:
        template = DEFAULT_TITLE_GENERATION_PROMPT_TEMPLATE

    content = title_generation_template(
        template,
        form_data["messages"],
        {
            "name": user.name,
            "location": user.info.get("location") if user.info else None,
        },
    )

    payload = {
        "model": task_model_id,
        "messages": [{"role": "user", "content": content}],
        "stream": False,
        **(
            {"max_tokens": 1000}
            if models[task_model_id].get("owned_by") == "ollama"
            else {
                "max_completion_tokens": 1000,
            }
        ),
        "metadata": {
            **(request.state.metadata if hasattr(request.state, "metadata") else {}),
            "task": str(TASKS.TITLE_GENERATION),
            "task_body": form_data,
            "chat_id": form_data.get("chat_id", None),
        },
    }

    # Process the payload through the pipeline
    try:
        payload = await process_pipeline_inlet_filter(request, payload, user, models)
    except Exception as e:
        raise e

    try:
        return await generate_chat_completion(request, form_data=payload, user=user)
    except Exception as e:
        log.error("Exception occurred", exc_info=True)
        return JSONResponse(
            status_code=status.HTTP_400_BAD_REQUEST,
            content={"detail": "An internal error has occurred."},
        )


@router.post("/tags/completions")
async def generate_chat_tags(
    request: Request, form_data: dict, user=Depends(get_verified_user)
):

    if not request.app.state.config.ENABLE_TAGS_GENERATION:
        return JSONResponse(
            status_code=status.HTTP_200_OK,
            content={"detail": "Tags generation is disabled"},
        )

    if getattr(request.state, "direct", False) and hasattr(request.state, "model"):
        models = {
            request.state.model["id"]: request.state.model,
        }
    else:
        models = request.app.state.MODELS

    model_id = form_data["model"]
    if model_id not in models:
        raise HTTPException(
            status_code=status.HTTP_404_NOT_FOUND,
            detail="Model not found",
        )

    # Check if the user has a custom task model
    # If the user has a custom task model, use that model
    task_model_id = get_task_model_id(
        model_id,
        request.app.state.config.TASK_MODEL,
        request.app.state.config.TASK_MODEL_EXTERNAL,
        models,
    )

    log.debug(
        f"generating chat tags using model {task_model_id} for user {user.email} "
    )

    if request.app.state.config.TAGS_GENERATION_PROMPT_TEMPLATE != "":
        template = request.app.state.config.TAGS_GENERATION_PROMPT_TEMPLATE
    else:
        template = DEFAULT_TAGS_GENERATION_PROMPT_TEMPLATE

    content = tags_generation_template(
        template, form_data["messages"], {"name": user.name}
    )

    payload = {
        "model": task_model_id,
        "messages": [{"role": "user", "content": content}],
        "stream": False,
        "metadata": {
            **(request.state.metadata if hasattr(request.state, "metadata") else {}),
            "task": str(TASKS.TAGS_GENERATION),
            "task_body": form_data,
            "chat_id": form_data.get("chat_id", None),
        },
    }

    # Process the payload through the pipeline
    try:
        payload = await process_pipeline_inlet_filter(request, payload, user, models)
    except Exception as e:
        raise e

    try:
        return await generate_chat_completion(request, form_data=payload, user=user)
    except Exception as e:
        log.error(f"Error generating chat completion: {e}")
        return JSONResponse(
            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
            content={"detail": "An internal error has occurred."},
        )


@router.post("/image_prompt/completions")
async def generate_image_prompt(
    request: Request, form_data: dict, user=Depends(get_verified_user)
):
    if getattr(request.state, "direct", False) and hasattr(request.state, "model"):
        models = {
            request.state.model["id"]: request.state.model,
        }
    else:
        models = request.app.state.MODELS

    model_id = form_data["model"]
    if model_id not in models:
        raise HTTPException(
            status_code=status.HTTP_404_NOT_FOUND,
            detail="Model not found",
        )

    # Check if the user has a custom task model
    # If the user has a custom task model, use that model
    task_model_id = get_task_model_id(
        model_id,
        request.app.state.config.TASK_MODEL,
        request.app.state.config.TASK_MODEL_EXTERNAL,
        models,
    )

    log.debug(
        f"generating image prompt using model {task_model_id} for user {user.email} "
    )

    if request.app.state.config.IMAGE_PROMPT_GENERATION_PROMPT_TEMPLATE != "":
        template = request.app.state.config.IMAGE_PROMPT_GENERATION_PROMPT_TEMPLATE
    else:
        template = DEFAULT_IMAGE_PROMPT_GENERATION_PROMPT_TEMPLATE

    content = image_prompt_generation_template(
        template,
        form_data["messages"],
        user={
            "name": user.name,
        },
    )

    payload = {
        "model": task_model_id,
        "messages": [{"role": "user", "content": content}],
        "stream": False,
        "metadata": {
            **(request.state.metadata if hasattr(request.state, "metadata") else {}),
            "task": str(TASKS.IMAGE_PROMPT_GENERATION),
            "task_body": form_data,
            "chat_id": form_data.get("chat_id", None),
        },
    }

    # Process the payload through the pipeline
    try:
        payload = await process_pipeline_inlet_filter(request, payload, user, models)
    except Exception as e:
        raise e

    try:
        return await generate_chat_completion(request, form_data=payload, user=user)
    except Exception as e:
        log.error("Exception occurred", exc_info=True)
        return JSONResponse(
            status_code=status.HTTP_400_BAD_REQUEST,
            content={"detail": "An internal error has occurred."},
        )


@router.post("/queries/completions")
async def generate_queries(
    request: Request, form_data: dict, user=Depends(get_verified_user)
):

    type = form_data.get("type")
    if type == "web_search":
        if not request.app.state.config.ENABLE_SEARCH_QUERY_GENERATION:
            raise HTTPException(
                status_code=status.HTTP_400_BAD_REQUEST,
                detail=f"Search query generation is disabled",
            )
    elif type == "retrieval":
        if not request.app.state.config.ENABLE_RETRIEVAL_QUERY_GENERATION:
            raise HTTPException(
                status_code=status.HTTP_400_BAD_REQUEST,
                detail=f"Query generation is disabled",
            )

    if getattr(request.state, "direct", False) and hasattr(request.state, "model"):
        models = {
            request.state.model["id"]: request.state.model,
        }
    else:
        models = request.app.state.MODELS

    model_id = form_data["model"]
    if model_id not in models:
        raise HTTPException(
            status_code=status.HTTP_404_NOT_FOUND,
            detail="Model not found",
        )

    # Check if the user has a custom task model
    # If the user has a custom task model, use that model
    task_model_id = get_task_model_id(
        model_id,
        request.app.state.config.TASK_MODEL,
        request.app.state.config.TASK_MODEL_EXTERNAL,
        models,
    )

    log.debug(
        f"generating {type} queries using model {task_model_id} for user {user.email}"
    )

    if (request.app.state.config.QUERY_GENERATION_PROMPT_TEMPLATE).strip() != "":
        template = request.app.state.config.QUERY_GENERATION_PROMPT_TEMPLATE
    else:
        template = DEFAULT_QUERY_GENERATION_PROMPT_TEMPLATE

    content = query_generation_template(
        template, form_data["messages"], {"name": user.name}
    )

    payload = {
        "model": task_model_id,
        "messages": [{"role": "user", "content": content}],
        "stream": False,
        "metadata": {
            **(request.state.metadata if hasattr(request.state, "metadata") else {}),
            "task": str(TASKS.QUERY_GENERATION),
            "task_body": form_data,
            "chat_id": form_data.get("chat_id", None),
        },
    }

    # Process the payload through the pipeline
    try:
        payload = await process_pipeline_inlet_filter(request, payload, user, models)
    except Exception as e:
        raise e

    try:
        return await generate_chat_completion(request, form_data=payload, user=user)
    except Exception as e:
        return JSONResponse(
            status_code=status.HTTP_400_BAD_REQUEST,
            content={"detail": str(e)},
        )


@router.post("/auto/completions")
async def generate_autocompletion(
    request: Request, form_data: dict, user=Depends(get_verified_user)
):
    if not request.app.state.config.ENABLE_AUTOCOMPLETE_GENERATION:
        raise HTTPException(
            status_code=status.HTTP_400_BAD_REQUEST,
            detail=f"Autocompletion generation is disabled",
        )

    type = form_data.get("type")
    prompt = form_data.get("prompt")
    messages = form_data.get("messages")

    if request.app.state.config.AUTOCOMPLETE_GENERATION_INPUT_MAX_LENGTH > 0:
        if (
            len(prompt)
            > request.app.state.config.AUTOCOMPLETE_GENERATION_INPUT_MAX_LENGTH
        ):
            raise HTTPException(
                status_code=status.HTTP_400_BAD_REQUEST,
                detail=f"Input prompt exceeds maximum length of {request.app.state.config.AUTOCOMPLETE_GENERATION_INPUT_MAX_LENGTH}",
            )

    if getattr(request.state, "direct", False) and hasattr(request.state, "model"):
        models = {
            request.state.model["id"]: request.state.model,
        }
    else:
        models = request.app.state.MODELS

    model_id = form_data["model"]
    if model_id not in models:
        raise HTTPException(
            status_code=status.HTTP_404_NOT_FOUND,
            detail="Model not found",
        )

    # Check if the user has a custom task model
    # If the user has a custom task model, use that model
    task_model_id = get_task_model_id(
        model_id,
        request.app.state.config.TASK_MODEL,
        request.app.state.config.TASK_MODEL_EXTERNAL,
        models,
    )

    log.debug(
        f"generating autocompletion using model {task_model_id} for user {user.email}"
    )

    if (request.app.state.config.AUTOCOMPLETE_GENERATION_PROMPT_TEMPLATE).strip() != "":
        template = request.app.state.config.AUTOCOMPLETE_GENERATION_PROMPT_TEMPLATE
    else:
        template = DEFAULT_AUTOCOMPLETE_GENERATION_PROMPT_TEMPLATE

    content = autocomplete_generation_template(
        template, prompt, messages, type, {"name": user.name}
    )

    payload = {
        "model": task_model_id,
        "messages": [{"role": "user", "content": content}],
        "stream": False,
        "metadata": {
            **(request.state.metadata if hasattr(request.state, "metadata") else {}),
            "task": str(TASKS.AUTOCOMPLETE_GENERATION),
            "task_body": form_data,
            "chat_id": form_data.get("chat_id", None),
        },
    }

    # Process the payload through the pipeline
    try:
        payload = await process_pipeline_inlet_filter(request, payload, user, models)
    except Exception as e:
        raise e

    try:
        return await generate_chat_completion(request, form_data=payload, user=user)
    except Exception as e:
        log.error(f"Error generating chat completion: {e}")
        return JSONResponse(
            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
            content={"detail": "An internal error has occurred."},
        )


@router.post("/emoji/completions")
async def generate_emoji(
    request: Request, form_data: dict, user=Depends(get_verified_user)
):

    if getattr(request.state, "direct", False) and hasattr(request.state, "model"):
        models = {
            request.state.model["id"]: request.state.model,
        }
    else:
        models = request.app.state.MODELS

    model_id = form_data["model"]
    if model_id not in models:
        raise HTTPException(
            status_code=status.HTTP_404_NOT_FOUND,
            detail="Model not found",
        )

    # Check if the user has a custom task model
    # If the user has a custom task model, use that model
    task_model_id = get_task_model_id(
        model_id,
        request.app.state.config.TASK_MODEL,
        request.app.state.config.TASK_MODEL_EXTERNAL,
        models,
    )

    log.debug(f"generating emoji using model {task_model_id} for user {user.email} ")

    template = DEFAULT_EMOJI_GENERATION_PROMPT_TEMPLATE

    content = emoji_generation_template(
        template,
        form_data["prompt"],
        {
            "name": user.name,
            "location": user.info.get("location") if user.info else None,
        },
    )

    payload = {
        "model": task_model_id,
        "messages": [{"role": "user", "content": content}],
        "stream": False,
        **(
            {"max_tokens": 4}
            if models[task_model_id].get("owned_by") == "ollama"
            else {
                "max_completion_tokens": 4,
            }
        ),
        "chat_id": form_data.get("chat_id", None),
        "metadata": {
            **(request.state.metadata if hasattr(request.state, "metadata") else {}),
            "task": str(TASKS.EMOJI_GENERATION),
            "task_body": form_data,
        },
    }

    # Process the payload through the pipeline
    try:
        payload = await process_pipeline_inlet_filter(request, payload, user, models)
    except Exception as e:
        raise e

    try:
        return await generate_chat_completion(request, form_data=payload, user=user)
    except Exception as e:
        return JSONResponse(
            status_code=status.HTTP_400_BAD_REQUEST,
            content={"detail": str(e)},
        )


@router.post("/moa/completions")
async def generate_moa_response(
    request: Request, form_data: dict, user=Depends(get_verified_user)
):

    if getattr(request.state, "direct", False) and hasattr(request.state, "model"):
        models = {
            request.state.model["id"]: request.state.model,
        }
    else:
        models = request.app.state.MODELS

    model_id = form_data["model"]

    if model_id not in models:
        raise HTTPException(
            status_code=status.HTTP_404_NOT_FOUND,
            detail="Model not found",
        )

    template = DEFAULT_MOA_GENERATION_PROMPT_TEMPLATE

    content = moa_response_generation_template(
        template,
        form_data["prompt"],
        form_data["responses"],
    )

    payload = {
        "model": model_id,
        "messages": [{"role": "user", "content": content}],
        "stream": form_data.get("stream", False),
        "metadata": {
            **(request.state.metadata if hasattr(request.state, "metadata") else {}),
            "chat_id": form_data.get("chat_id", None),
            "task": str(TASKS.MOA_RESPONSE_GENERATION),
            "task_body": form_data,
        },
    }

    # Process the payload through the pipeline
    try:
        payload = await process_pipeline_inlet_filter(request, payload, user, models)
    except Exception as e:
        raise e

    try:
        return await generate_chat_completion(request, form_data=payload, user=user)
    except Exception as e:
        return JSONResponse(
            status_code=status.HTTP_400_BAD_REQUEST,
            content={"detail": str(e)},
        )